1999 HSR&D Annual Meeting Abstracts
51. Determinants of House Staff Time Use in the
Inpatient Setting
Timothy Dresselhaus MD. Center for the Study of Healthcare
Provider Behavior, San Diego, CA. D Timberlake. Jeff Luck MBA, PhD. UCLA
School of Public Health, Los Angeles, CA. B Wright and R Spragg. Samuel Bozzette
MD, PhD, Center for the Study of Healthcare Provider Behavior, San Diego, CA.
Objectives: As patient care in the VA shifts to the ambulatory
setting, the inpatient time of house staff will be constrained. To maintain the value of
inpatient time, training programs must preserve activities contributing directly to
patient care and education. Data on time allocation and the determinants of time use are
needed to inform the redesign of inpatient training. We used automated random sampling to
measure house staff inpatient work and developed prediction models to identify factors
influencing house staff time allocation in the inpatient setting.
Methods: We developed and validated a computer assisted self
interview (CASI) survey and assigned house staff rotating on our VA medical service
hand-held computers for periods of five consecutive weekdays. House staff were prompted
randomly within consecutive intervals to complete the work survey. Fifty-one medical house
staff (30 interns, 21 residents) were sampled during 480 weekdays. We analyzed activities
according to three content domains: direct patient care (time with patient), indirect
patient care (time supporting patient care but not with patient), and education. In
predicting the proportion of time allocated to these domains, the following independent
variables were included in three multivariate models: gender, house staff type (intern or
resident), program director ratings of overall clinical performance, attending ratings of
clinical performance for the concurrent rotation (rotation rating), type of day in call
schedule (long call, post-call, short call, pre-call), scheduled clinic day, and patient
load. Two separate random-effects linear regression models were used to identify the
significant predictors of the proportions of time that house staff participated in
indirect patient care and education. For direct patient care, a logistic regression model
incorporating robust variance estimates for clustered data was used to identify the
predictors of days in which sampled activities included direct patient care versus days in
which sampled activities did not include direct patient care.
Results: In the 480 days of observation, 3,762 complete
responses were obtained. House staff spent more time in indirect (56%) than direct patient
care (14%) or educational activities (45%). The proportion of time spent in indirect
patient care was negatively associated with rotation rating (p<0.01) and long call (vs
pre-call, p<0.01). Time spent in direct patient care was positively correlated to long
call (vs pre-call, p<0.001) and short call (vs pre-call, p<0.01), but negatively
correlated to scheduled clinic day (p<0.05). Time spent in education was negatively
associated with female gender (p<0.05), short call (vs pre-call, p<0.01), and intern
status (vs resident, p<0.01) but positively associated with rotation rating
(p<0.05).
Conclusions: House staff at our VA spend more of their workday
in activities indirectly supporting patient care than in time with patients or in
educational activities. Elements of program structure correlate to time spent in direct
patient care, while house staff factors, including ratings of clinical performance,
correlate to the amount of time in educational or indirect patient care activities.
Impact: Planners must consider the influence of structural
change upon house staff time allocation to patient care and education when redesigning
house staff inpatient work. Further research is needed to understand how time use is
related to the clinical performance of house staff.
52. Effects of Race, Income, and Psychological
Well-being on HIV Patient Decisions about Emergency Department (ED) Use.
Allen Gifford, MD. San Diego VA Medical Center. San Diego,
CA. R Collins and D Timberlake. Samuel Bozzette, MD, PhD, Center for the
Study of Healthcare Provider Behavior, San Diego, CA. M Shapiro, M Schuter, and D
Kanouse.
Objectives: Veterans with HIV often choose the ED for care
of both non-urgent and urgent symptoms, however ED care is expensive, and quality of care
may suffer due to poor integration of ED care with primary care. To understand what
determines HIV patient decisions to go to the ED or to their usual source of primary care
(USOC), we interviewed a probability sample of both veteran and non-veteran HIV patients
in the U.S. to determine how they would seek care in response to several symptom
scenarios.
Methods: A nationally representative probability sample of all
U.S. HIV+ adults in care underwent detailed structured interviews. Three brief clinical
scenarios describing headache, respiratory, and other HIV-related symptoms were asked of
each subject. Different scenarios were asked of early stage (non-AIDS) and late stage
(AIDS) patients. Scenario response options included "I would go to the emergency
room" and "I would go to the doctorÆs office the same day."
Sociodemographic (SD), access to care, health status, psychological, and
knowledge/attitude/belief (KAB) variables were also assessed. Weights were used to adjust
for the sampling design, and non-response; linearization methods corrected for weights and
multistage sample design. Proportional logit models to identify independent predictors of
propensity to seek ED care were estimated separately for early and late stage patients. A
hypothesis-driven regression approach was used to evaluate the relative contributions of
SD, access, health, and KAB variables to propensity to choose ED care (among those who
would seek immediate care).
Results: Data were collected from 1245 non-AIDS and 1612 AIDS
patients representing 86,800 and 126,420 HIV patients respectively nationwide. In a full
multivariate model of those with AIDS, African-American race was the strongest independent
predictor of propensity to use the ED (Adjusted odds ratio [AOR] compared with white 2.87,
p<.0001), even with adjustment for all other SD, access, health, psychological, and KAB
variables. Other independent predictors were low income (AOR 1.64, p<.04), low
psychological well-being (AOR 1.08, p<.02), cognitive denial coping (AOR 1.01,
p<.05), and several access (travel time to USOC, usually see the same person at USOC,
length of time with same USOC provider) and attitude (prefer doctor to make decisions)
variables. Among HIV+ patients without AIDS, African-American race was again the strongest
independent predictor of propensity to use the ED (AOR 3.73, p<.0001), again with
adjustment for all other variables; Hispanic ethnicity was also a predictor (AOR 2.17,
p<.005), as was female gender (AOR 1.45, p<.03). Other predictors were again low
income (AOR 2.00, p<.009), low psychological well-being (AOR 1.11, p<.02), and
access (wait time for appointment date, wait time at appointment) variables. Health
insurance category was not associated with propensity to use the ED in either model.
Conclusions: African-American race is a significant, independent
predictor of propensity to use the ED across stages of disease, even after adjustment for
access, income, insurance, and other variables. Income, psychological well-being, and
access variables are also important.
Impact: Cultural preferences or habits that go beyond
socioeconomic and access issues may influence propensity to use the ED among
African-Americans.
53. Cost-effectiveness of the Primary Care Provider
Program at the West Los Angeles VAMC
Hwai-Tai Lam, PhD. VA Greater Los Angeles Healthcare System,
Los Angeles, CA. D Norman, S Cretin, G Sun, M Gee, and M Wong.
Objectives: Primary Care Provider Program (PCP) was
implemented at the West Los Angeles VA Medical Center in 1996. This study evaluates the
cost-effectiveness of that program. Patients' total medical costs and admission rates for
a period of eleven months, from October 1997 through August 1998, were used as outcome
measures to answer the following questions: (1) Does the coordination of a PCP reduce
patients' overall medical costs? (2) Does the coordination of a PCP reduce patients'
admission rates?
Methods: This study includes patients who have utilized the West
Los Angeles health care system during the study period, and who had at least three
outpatient visits. Patients referred from other VA facilities and psychiatric patients who
did not utilize surgical or medical clinics were excluded. Cost data were downloaded from
the Decision Support System (DSS). Patients were categorized into three groups based on
their contact with their primary care provider teams. Group one (N=5,444) was patients who
were seen by their PCP teams in more than 50% of their primary care clinic visits. Group
two (N=5,452) was patients seen by their PCP team in less than 50% of their primary care
visits. Group three patients (N=15,081) had no primary care clinic visits during the study
period. A linear regression model controlling for risk factors assessed the effect of
contacting with primary care provider teams on patients' overall medical costs.
Results: Group one patients, who had the most contact with their
PCP, had the lowest average total cost ($8,298) per patient when compared to Group two
($9,470) and Group three ($9,451). Group one patients also had the lowest inpatient cost
($2,731); Group two and Group three's costs were $4,022 and $6,341, respectively. It had
an admission rate of 0.27 while Group two and Group three's rates were 0.34, and an
average length of hospital stay of 5.64 days (Group two: 7.41 days, Group three: 6.69
days). However, Group one patients had the highest outpatient costs of $5,567 (Group two:
$5,447, Group three: $3,110). Although Group two patients had the highest average total
costs, after controlling for age and principal diagnoses, the linear regression model
showed that Group two's costs were lower than Group three's (p=0.0001), and Group one's
cost were lowest of all.
Conclusions: Use of a PCP team had a significant effect on
reducing patients' total costs and length of hospital stay. The effect would be greater if
patients were seen at the primary care clinics by their assigned PCPs or by other
providers of the same team. The setting of services provided by PCPs seemed to shift from
inpatient to outpatient.
Impact: Currently, at the West LA VAMC, the PCP program and the
patient self-coordinated system coexist. Patients can have access to sub-specialty care
for a long period of time without going through the PCP program. The results of this study
attest to the cost-effectiveness of a PCP program and support its reinforcement.
54. The Impact of Involving LPNs in Colorectal
Cancer Screening
Nancy Thompson, PhD. University of Iowa, Iowa City, IA. Michael
Chapko, PhD. VA Puget Sound Health Care System, Seattle, WA.
Objectives: The objective was to determine if involving nurses
in the delivery of fecal occult blood tests (FOBT) for early detection of colorectal
cancer would improve the utilization of FOBTs without negatively impacting the patient
return rate in a VA primary care clinic.
Methods: The study was conducted between January and March 1998.
The intervention involved having licensed practical nurses (LPNs) assess need for and
order FOBTs during the time they interacted with 50-69 year old patients scheduled to see
primary care providers in the General Internal Medicine Clinic at the Seattle VAMC. The
orders were to be made on the basis of a predefined protocol. As the clinic is organized
as a firm, it was randomly divided into experimental and control units. In the
experimental unit FOBT orders were placed by the primary care providers(physicians/nurse
practitioners MD/NP)or the LPNs. In the control unit FOBT orders were placed by only the
primary care providers. Data were collected regarding orders, and returns as well as other
characteristics of both the patients and providers. A 90-day window of time was allowed to
elapse prior to categorizing a test as "returned" or "not returned."
Descriptive and regression analyses were conducted.
Results: A total of 1109 patients were included in the study (545
experimental, 564 control). The experimental and control units were found to be comparable
in terms of the variables of interest. The experimental unit ordered significantly more
FOBT tests than the control unit for all patients (52 vs 15%, p<.000) as well as for
FOBT eligible patients (72 vs 19%, p<.000).
Within the experimental unit, the LPN orders were returned as
frequently as the MD/NP orders (LPN 42% vs MD/NP 59%, p =.0951)and were less likely to be
placed inappropriately (LPN 6% vs MD/NP 31%, p <.000. Finally, the LPNs' involvement in
ordering FOBTs did not decrease their ability to provide other expected services.
Conclusions: The use of LPNs in ordering FOBTs significantly
increased the rates of ordering without compromising the potential for its return rate or
other expected LPN services. Efforts to improve the delivery of preventive services should
consider changes to the system that support use of nurses in delivering preventive
services.
Impact: This study has demonstrated that LPNs ordering FOBTs in
a VA medical facility can produce nearly a threefold increase in the number of veterans
receiving and returning the test with minimal cost.
55. A Standardized Method for Assessing Urgency
Among Walk-in VA Patients
Donna Washington, MD, MPH. Assistant Professor of Medicine,
UCLA, Los Angeles, CA. Paul Shekelle, MD. West LA VA Medical Center, Los Angeles,
CA. CD Stevens and RH Brook.
Objectives: Faced with the challenge of delivering maximum
medical value within a fixed budget, the Department of Veteran Affairs has begun adopting
managed care principles. Both cost and quality concerns dictate the need to shift from
unscheduled, episodic care in hospital emergency departments to a strengthened primary
care system. However, few systematic methods exist for identifying walk-in patients who
are safe for triage to primary care settings. We developed, operationalized and validated
a method to direct walk-in VA patients to emergency, urgent, or deferred (by up to 1 week)
care.
Methods: Using the scientific literature and expert opinion, a
17-member multidisciplinary physician panel rated the safety of deferring care for 365
detailed clinical scenarios representing common complaints (abdominal pain,
musculoskeletal pain, and respiratory infection symptoms) of ambulatory adults presenting
to emergency departments. We converted ratings into explicit, standardized triage
algorithms for use by emergency department nurses. Following training in their use, nurses
at the West Los Angeles VAMC applied the algorithms to 1,187 consecutive walk-in patients
who had conditions covered by the guidelines. Patients meeting deferred care criteria were
offered the option of an appointment within 1 week in the ambulatory care clinic. All
other patients received same day care in the emergency department or urgent care clinic at
the study site. We measured nurse triage times using our guidelines in comparison to usual
implicit judgment methods. We also assessed non-elective hospitalizations at all southern
California and Nevada VA facilities within 7 days of triage and 30-day mortality using the
VA National Health Exchange and Beneficiary Identification Records Locator System
databases respectively.
Results: The mean nurse triage time using the criteria was 9.95
minutes (95% C.I. 8.1 to 11.8) in contrast to 9.52 minutes (95% C.I., 7.9 to 11.2) without
the criteria. 226 (19%) patients met deferred care criteria, and of this group, 154 (68%)
had their care deferred by up to one week. Transportation difficulties represented the
most common reason for declining a deferred care appointment. Patients meeting deferred
care criteria experienced zero (95% C.I., 0% to 1.2%) related non-elective VA
hospitalizations within 7 days of evaluation, and none died within 30 days. By contrast,
7% (95% C.I., 5.5 to 8.9%) of patients who did not meet deferred care criteria were
hospitalized non-electively for related conditions, and five (0.5%) died.
Conclusions: We developed standardized, clinically-detailed
triage guidelines for deferring care that apply to a significant proportion of patients
with common ambulatory conditions. Trained nurses applied the criteria to a large group of
patients without adverse impact on triage time or work flow. No patient classified as safe
for deferred care using the guidelines was hospitalized within a week at a VA facility or
died within 30 days.
Impact: This explicit triage approach may allow facilities to
manage their acute care resources more efficiently by safely diverting a significant
proportion of walk-in patients from the emergency department to primary care settings. The
safety and reliability of achieving this goal with the implicit triage methods currently
used at most facilities is unknown.
56. Determining the Cost of VA Health Care
Paul Barnett, PhD. Center for Healthcare Evaluation, Menlo Park, CA.
Objectives: Cost data are needed to conduct cost-effectiveness
analysis and to increase the policy relevance of health services research. Since VA does
not routinely prepare patient bills, it is difficult to determine the cost of VA provided
health care. This workshop will introduce the data sources and methods needed to determine
the cost of VA health care for use in health services research. Cost finding will be
illustrated from examples drawn from health services research projects and clinical trials
conducted by the Cooperative Studies Program.
Target: The workshop is intended for
health services researchers and VA managers with research problems requiring cost data.
Attendees need not have a health economics background.
Methods: Methods for estimating VA costs
will be described, including micro-cost and average-cost methods. Micro-cost methods
include time activity analysis and the use of detailed VA utilization data and cost
estimates from non-VA settings, either by preparing a pseudo-bill, or by estimating a
clinical cost function from non-VA data. Average cost methods combine VA cost and
utilization data, and resource weights obtained from the non-VA sector. Data
sources that are useful for cost-determination will be described. VA data sources include
the Cost Distribution Report, the Financial Management System, Fee Basis Files,
centralized VA utilization data bases such as the Patient Treatment File and National
Ambulatory Care Database, and decentralized utilization data from the VISTA clinical data
system. The workshop will also describe extraction of cost data from the VA Decision
Support System. Non-VA data sources, including Medicare DRG weights and reimbursement
schedules, will also be described. Cost determination methods will
be illustrated by example. Examples will include a health services study of costs incurred
by patients treated for substance abuse disorders, and clinical trials of interventions in
cardiology and primary care. The workshop presenters will lead a discussion of the
advantages and drawbacks of the different methods, along with suggestions for the methods
appropriate to different types of research.
57. Using VHA Administrative Data to Measure
Performance: Methodological Issues of HEDIS
Ann Hendricks, PhD, Debra Jones, PhD, Cheryl Hankin, PhD, James
Rothendler, MD, Bei-Hung Chang, ScD. Bedford VA Medical Center, Bedford, MA. Catherine
Comstock, MPH. Carlisle, MA. Amy Rosen, PhD and Mark Prashker, MD, MPH. Center for
Health Quality, Outcomes, and Economic Research, Bedford, MA.
Objectives: The primary goal of this workshop is to explore the
methodological issues faced by managers and researchers trying to construct standardized
VISN-level performance measures. The topic is timely and consistent with the conference
theme (research at the interface) because it relates to policymakers' attempts to monitor
performance in the delivery of health care. Activities: The workshop presenters include
researchers and clinicians who will illustrate the issues using experience with six HEDIS
measures applied to VHA and then lead discussions regarding possible solutions for
research and management. Specific aims are to give a general overview of moving from
theory to practice in applying HEDIS measures in VHA and to discuss five methodological
areas and our methods in resolving issues: 1) definitions and construction of denominators
and numerators using different VA databases (illustrated by rates of eye exams for people
with diabetes), 2) defining levels of severity for psychiatric illnesses (illustrated for
rates of follow-up care and readmissions for people hospitalized for mental illness), 3)
risk adjusting for underlying prevalence of disease in the denominator population
(illustrated for rates of cardiac procedures), 4) comparisons across providers (Bayesian
techniques for VISN comparisons), and 5) veterans use of VA and Medicare. Materials based
on the project will be disseminated.
Audience: Health services researchers with an interest in either
developing or evaluating VA performance measures, and medical and mental health care
managers who use such measures in assessing VISN-level or facility-level performance.
58. Implementing Ambulatory Care Case-Mix Measures
in the VA: From Theory to Practice Amy Rosen, PhD, Arlene Ash, PhD, James
Rothendler, MD,and Susan Loveland, MAT, Bedford VA Medical Center, Bedford, MA.
Objectives: Ambulatory care case-mix measures are currently
being used by health care organizations to describe the illness burden of their
populations, evaluate the content of ambulatory practice, assess the costs and quality of
care, and predict resource utilization. As the VA evolves into an integrated health care
delivery system, methods that take account of the unique issues related to ambulatory care
and that can classify patients into clinically homogeneous groupings are critical for
accurately assessing VA's effectiveness as a managed care organization.
Activities: This workshop will discuss the theoretical and
operational frameworks useful in constructing population-based ambulatory care case-mix
measures with VA administrative data. We will lead a series of presentations that will
describe: 1) the importance of using case-mix measures to evaluate health care delivery in
VA; 2) the leading case-mix measurement systems, Ambulatory Care Groups (ACGs) and
Diagnostic Cost Groups (DCGs) that are currently being used; 3) the data and file
requirements necessary for implementing the ACG and DCG software; and 4) the special
considerations in constructing input and output measures using VA inpatient and outpatient
data. Examples of how specific outcome measures were constructed from VA files will be
presented by the speakers; however, as this is an interactive workshop, participants are
encouraged to bring examples using ambulatory care case-mix measures from their own
research studies.
Target Audience: This workshop is intended for researchers
interested in using administrative databases to evaluate changes in health care delivery
using case-mix measurement systems, as well as managers and clinicians who need to use the
results of these analyses for evaluating health care delivery.
Audience's Assumed Familiarity with the Subject: Some
familiarity with the subject of risk adjustment as well as the different VA databases
would be helpful but is not required.
59. Are Clinical Practice Guidelines Implemented in
Clinical Practice?
Mark Bauer, MD. Mental Health and Behavioral Sciences
Service, Providence, RI.
Objectives: Clinical practice guidelines have been proposed to
fill many roles from improving quality of care to reducing health care costs. Several
major efforts have been undertaken to develop guidelines for mental health. However, we
have little information regarding the extent to which guidelines are actually implemented
in medical, surgical, or mental health practice. This paper reviews the available evidence
regarding guideline implementation in medical, surgical, and mental health general
clinical practice settings.
Methods: All available articles on adherence to guidelines, as
defined by IOM, were located through Medline search supplemented by review of
bibliographies of located articles. Abstracts and articles were then reviewed and the
study categorized as positive or negative according to the authors' principle
interpretation.
Results: This review found 36 articles distributed across three
types of studies: cross-sectional, pre/post, and intervention trials. 33% of
cross-sectional and pre/post trials and 67% of intervention trials demonstrate adherence
to practice guidelines, for an overall adherence rate of approximately 45%. Additional
studies indicate that when intervention trials finish, rates of adherence return to
baseline.
Conclusions: Thus the substantial expenditure of effort among
leading academics and major professional organizations may actually be having little
effect on > general clinical practice.
Impact: The issue of how to facilitate the adoption of
guidelines in general clinical practice must become a focus of research; otherwise we run
the risk of putting tremendous effort into documents that will have primarily archival
value, and negligible public health impact. In addition, some data indicate that there may
be value in investigating this issue from the perspective of "diffusion
research." This decades-old multidisciplinary approach has been successfully applied
to understanding the adoption of new technologies in many fields, but has been applied to
health care delivery issues only sporadically.
HSR&D Funded: DEV 97-015
60. VA Cooperative Study #430: Reducing the
Efficacy-Effectiveness Gap in Bipolar Disorder
Mark Bauer MD. Mental Health and Behavioral Sciences
Service, Providence, RI. E Dawson, N Shea, L McBride, and WO Williford.
Objectives: The VA Cooperative Study has funded a 12-site
randomized controlled trial of an easy-access program for bipolar disorder from 1997-2003.
This study proposes that increased access and provider and patient education will reduce
the "efficacy-effectiveness gap" for bipolar disorder. We specifically
hypothesize that compared to usual VA care (UVAC) the easy-access Bipolar Disorders
Program (BDP), will improve clinical, functional, and economic outcome.
Methods: Patients who are admitted to a acute psychiatric ward
with a primary or co-primary admission diagnosis of bipolar disorder type I or II are
screened for the study. One hundred and ninety-one patients are being randomized to each
of the two treatment groups (BDP and UVAC). All enrolled patients are followed up for
three years.
Results: All 12 sites have been trained to criterion and are
fully functioning. Statistics regarding training to criterion are presented. As of October
15, 1998, 996 patients have been screened and 124 patients have been randomized (67 BDP
and 57 UVAC), which is 107% of the current randomization goal. Follow-up data flow is also
presented with quality of follow-up evaluation.
Conclusions: Complex treatment interventions can be implemented
validly across multiple sites. Monitors based on "CQI" principles can provide
important process information. Reliability of outcome data can be assured by training and
ongoing monitoring.
Impact: In terms of impact, this study will have impact on both
the private and the government healthcare sectors. It is designed to evaluate the basic
principle that augmenting ambulatory access for major mental illness will improve outcome
and reduce overall treatment costs. If results are positive, this study will provide
reason to reconsider the prevailing trend toward limitation of ambulatory service that is
characteristic of many managed care systems today. Further, the study will provide
specific direction with regard to how to structure such ambulatory services.
HSR&D Funded: CSP #430
61. Consistent Satisfaction Measured by American
Board of Internal Medicine Patient Satisfaction Questionnaire Following Initial Evaluation
of Inpatients by VA Medical Center Interns
MJ Bittner, MD. Omaha VA Medical Center, Omaha, NE. EC
Rich, RL Recker, PD Turner, and MW Lubeley.
Objectives: As academic medical centers face more
competition and as inpatient care in VA medical centers evolves, concern heightens about
maintaining patient satisfaction. Among Lexington VA inpatients with chronic obstructive
pulmonary disease studied January-May 1995, greater intern workloads were associated with
diminished patient satisfaction. (Acad Med 1998;73:427-429) We looked for this finding
among patients with a variety of diagnoses, studying patients shortly after admission.
Methods: We studied patients of Creighton medical interns
assigned to non-intensive care unit inpatient floors at the Omaha VA Medical Center July
6-October 12, using the American Board of Internal Medicine's Patient Satisfaction
Questionnaire (PSQ). This ten-item instrument assesses physicians' interpersonal skills.
Each item has five responses, from 1 (excellent) to 5 (poor). We analyzed responses from
patients who completed the questionnaire in a face-to-face interview the morning after
admission; however, for patients admitted after 5 pm, the interview occurred the second
day after admission. At the interview we noted these variables based on the Lexington
study: patient age, intern gender, intern census size, and severity of illness (modified
APACHE II score). Additionally, we noted the number of admissions to the intern in the
previous 24 hours and whether the admission occurred after inaugurating stricter
utilization review (August 24). Using multiple linear regression, we studied mean PSQ
response as the dependent variable, assessing the effect of intern workload (census,
admissions) and controlling for the effect of patient factors (age, illness severity),
intern gender, and utilization review.
Results: Of 254 assigned patients, we excluded those initially
admitted to intensive care (48), unavailable for interview (11), not competent (12), or
not completing all items (59). Because some patients were excluded for multiple reasons,
182 remained for analysis. Satisfaction scores obtained shortly after admission (mean
1.79, standard deviation 0.74) resembled those from Lexington patients just before
discharge (1.7, s.d. 0.9). Fewer of our patients (19.2%) rated all ten items as excellent
(Lexington, 37%). The mean age was 65.8 (s.d. 13.9), modified APACHE II score 7.27 (s.d.
3.53), intern census 3.23 (s.d. 1.84), and intern admissions 0.77 (s.d. 1.03). Of the
admissions, 37.4% were to women interns and 42.9% occurred after instituting stricter
review criteria. Only 2.7% of the admissions involved interns with more than three
admissions in the 24-hour period before the questionnaire administration. In the multiple
linear regression model, neither census, admissions, nor any of the other explanatory
variables were significantly associated with PSQ response.
Conclusions: Greater workload adversely affected satisfaction
among Lexington COPD patients, and greater age was associated with more satisfaction among
Lexington patients. In a setting with a limited number of intern admissions and limited
intern census, we observed neither finding; nor did we find an association between
satisfaction and intern gender, modified APACHE II score, or institution of stricter
utilization review.
Impact: An academic VA medical center can achieve a consistently
high level of patient satisfaction with physician interpersonal and communication skills,
even among inexperienced house officers, in an environment where intern workload is
controlled.
62. The Effect of Depression on Change in Stroke
Patients' Physical and Mental Health
Hayden Bosworth PhD and Ronnie Horner PhD. Center for Health
Services Research in Primary Care, Durham, NC. David B. Matchar
Objectives: This study examined the effect of depressive
symptoms on change in acute ischemic stroke patients' physical and mental health using a
subset of data from the VA Acute Stroke (VASt) study, a nationwide prospective cohort of
881 patients admitted for acute stroke at any of nine VA sites between 4/1/95 and 3/31/97.
Methods: Patients were interviewed at 1, 6, and 12 months post
admission via telephone regarding depressive symptoms (short form CES-D), activities of
daily living (ADL), and preference for current health state (measured by the time-tradeoff
method). Analyses were confined to the 246 patients (M=66 years of age; SD=10 years) who
had three measurements and complete data (28%). Proxies (n=451) were not included because
they cannot provide valid responses regarding patients' psychological health. Besides the
proxies, there were 184 (21%) had incomplete data at baseline. Patients who were able to
participate were on average younger, had more education, were less likely to be married,
and have less physical problems in contrast to those patients that required a proxy to
compete the questionnaire for them or had missing data.
Results: A repeated ANOVA controlling for age, gender, level of
education, race, and ADL at baseline indicated that increased time was positively
associated with increased patients' perceptions of their current health state over the
12-months post hospital admissions (F[2, 204]=3.13, p<.04). After adjusting for related
factors, number of depressive symptoms
(F[1, 204]=10.89, p<.001) was inversely related to patients'
perception of their current health state at 1, 6, and 12-months post-stroke (i.e.,
willingness to trade more years of life to live in perfect health), despite improvements
in physical function. In a similar model that examined change in physical function,
increased number of depressive symptoms was also associated with worse function (F[1,
238]=9.88; p<.002). There were no significant interactions between depressive symptoms
and any independent variable for either model.
Conclusions: It has been suggested that depression may be a
reactive process to the physical limitation effects of stroke. We found that depressive
symptoms continue to be independently related to both short (1 month) and longer-term
(12-months) perceptions of quality of life in this
sample of veteran stroke patients, despite increased improvement in
physical function. Presence of increased depressive symptoms was also independently
associated with both short and longer- term physical function. Further studies are
necessary to determine if the effect of depression is even more profound in more
debilitated stroke patients.
Impact: Depressive symptoms aggravate veterans' perceptions of
quality of life, thereby possibly reducing the effects of the recovery process and
inhibiting the process and the benefits of rehabilitation. Health care providers may need
to focus more attention on the mental health needs of stroke patients.
HSR&D Funded: SDR 93-003 "Clinical Management of
Patients with Stroke at VAMCs
63. Implementing Depression Screening in Primary
Care: An Effective Strategy?
Edmund Chaney PhD, Nicole Hasenberg MPH, and Susan Hedrick, PhD,
VA Puget Sound Health Care System, Seattle, WA .
Objective: Although increasingly recommended or mandated in
quality improvement efforts, the utility of screening for depression in primary care
remains controversial. This study addresses one critical issue on which there is little
data: what is the actual gain in detection of unrecognized, untreated major depression for
which the patient is at least amenable to discussing treatment alternatives?
Methods: Preliminary data are drawn from a four-month period in
which patients responded to a comprehensive primary care clinic-wide health promotion
survey as they checked in for their appointment. Clinical records for patients screening
positive on the two survey depression items were examined to determine whether patients
were being actively treated for depression in Mental Health Clinic. Those who were not
were contacted by telephone and, if willing, were administered a structured
computer-assisted interview based on the Prime-MD by a trained evaluator. Those positive
for major depression or dysthymia were asked whether they were interested in treatment
(and if interested, that information was conveyed to their primary care provider.)
Results: The General Internal Medicine primary care clinic of
the Seattle Division of the VA Puget Sound Health Care System in which the survey was
conducted currently has an enrollment of 9100 patients and averages 850 visits per week.
Patients are predominantly male (95%), Caucasian (90%), elderly (mean age 65), and not
working (86%). During the four- month period, 837 patients were positive on the depression
screen and 508 have been reviewed to date. Chart review found 45% to be in mental health
treatment, either in the primary care setting, or in specialty care. After interview we
found that 15% met MDD criteria and 2% had a mood disorder secondary to alcohol abuse. Of
the rest, 11% could not be contacted, 2% could not be interviewed because of hearing or
cognition, 12% declined to be interviewed and 3% we are still attempting to reach. Of
those interviewed, 10% did not meet depression criteria. Of these currently untreated
patients, almost all of the former group (and some of the latter) were amenable to
discussing treatment alternatives.
Conclusions: In this population, a high percentage of patients
screened were either already in treatment or met depression criteria, suggesting a short
screen is an effective method of identifying depression. However, following up on those
patients not in treatment requires a significant investment of staff time, even using
computer-assisted technology.
Impacts: This study provides information on one component of
depression treatment guidelines implementation in primary care which can be used by
planners in deciding how to distribute available resources.
64. Coronary Artery Stent Outcomes in Department of
Veterans Affairs Medical Centers
Michael Chapko, PhD and Nathan Every, MD, MPH. VA Puget
Sound Health Care System. Seattle, WA. C Maynard and JL Ritchie
Objectives: Randomized trials of coronary stents versus
conventional balloon percutaneous transluminal coronary angioplasty (PTCA) have
demonstrated improved short and long-term outcomes for selected patients receiving stents.
PTCA caseloads in Department of Veterans Affairs (VA) medical centers have increased from
about 5,000 per year in fiscal year (FY) 1993 to 6,000 per year in FY 97 In FY 96, the
first year the ICD-9 stent code was used, there were 3895 conventional PTCA and 2573 stent
cases (40%). In FY 97, the number of stent cases increased 39% to 3588 and accounted for
58% of all PTCAs. The purpose of this study is to compare outcomes in patients with stents
with outcomes in patients with conventional PTCA in the VA in FY 97.
Methods: Data on the outcomes of conventional PTCA and PTCA with
stents were obtained for all VA medical facilities from the Austin Automation Center. For
patients with more than 1 procedure, only the index case is considered, and results are
reported separately for men with and without the primary diagnosis of acute miocardial
infarction (AMI).
Results: For both AMI and no AMI patients, the stent (N: AMI =
607; No AMI = 2389) and no stent (N: AMI = 485; No AMI = 1999) groups were comparable with
respect to age, race, and medical histories including diabetes, hypertension, myocardial
infarction, and chronic heart failure. For both AMI and no AMI patients there was no
significant difference in mortality rates (< 11 days after admission) between patients
receiving (AMI = 2.8%; No AMI = .8%) and not receiving stents (AMI = 3.3%; No AMI = 1.2%).
However, patients receiving stents (AMI = 0.2%; No AMI = 0.8%) had significantly lower
rates of coronary artery bypass graft surgery (CABG) compared to patients who did not
receive stents (AMI = 2.1%; No AMI = 3.0%). This association did not change after
multivariate adjustment. In VA medical centers, the use of stents has increased, and the
rate of same admission CABG has decreased.
Conclusions: The observational data from the VA with regard to
the reduction in CABG rates is consistent with previous clinical trails that demonstrated
the positive outcomes from the use of stents.
Impact: This study has the potential to encourage the continued
use of stents and thereby reduce CABG rates within the VA.
HSR&D Funded: IIR 94-044
65. Symptom-Based Predictors of a Ten-Year Course
of Treated Depression
Ruth Cronkite, PhD and Rudolf Moos, PhD. Center for Health
Care Evaluation, Menlo Park, CA
Objectives: The primary objective of this research is to predict
the likelihood of a long-term chronic course of depression from a set of risk factors that
reflect three symptom domains associated with poor outcome: severity of specific
depressive symptoms, lack of self-confidence, and a tendency toward social isolation and
avoidance coping. We also examine the intensity of the index episode of treatment as a
moderator of the influence of baseline risk factors on long-term outcome.
Methods: In a sample of 313 unipolar depressed patients, 20
potential symptom-based risk factors were assessed at treatment intake in the following
domains: depressive symptoms, self-concept, and social functioning and coping. These
patients were followed for ten years and were categorized into two groups: (1) those who
were considered to have followed a chronic course, and (2) those who were considered to
have followed a course of remission or partial remission.Chi-square analyses were used to
select a set of baseline risk factors that were most strongly associated with a chronic
course. Scores reflecting the number of risk factors present at intake were used to
identify the relationship between the number of risk factors and chronic course. Logistic
regression analysis was used to examine the influence of the amount of treatment on the
association between the number of risk factors and long-term chronic course.
Results: The prototypic chronically depressed patient was an
individual who at baseline experienced more severe symptoms of fatigue, loss of interest
in usual activities, trouble sleeping, and thoughts about death or suicide; was not calm,
successful, or self-confident; did not socialize with friends outside the home, and
frequently coped with stressors by avoiding other people. A larger number of risk factors
was associated with a higher likelihood of experiencing a chronic course. High-risk
patients who received more psychological treatment during the index episode were more
likely to experience a long-term course of remission or partial remission.
Conclusion: Symptoms that change more slowly during treatment
and that are more closely tied to behavioral concomitants of depressed mood may be better
predictors of outcome than depressed mood itself. Frequent thoughts of death and suicidal
ideation are especially serious symptoms and are strong predictors of chronicity. Lack of
self-confidence and social withdrawal are also important predictors of long-term chronic
course and point to the heterogeneity of the mechanisms that influence chronicity.
Impact: Information about specific risk factors may help to
direct treatment efforts and point to the need for continuing care. When patients report
ongoing severe symptoms that predict a chronic course, a longer and more intensive course
of treatment may be indicated. When the patient has a low self-concept, is socially
isolated, and tries to manage stressors by avoiding people, these issues should be
specifically addressed in treatment. By alerting the clinician to the patient's need for
additional care, feedback obtained from a risk factor index can help to address the
pervasive under- treatment of depression.
66. Family Satisfaction with VA Hospice Care
Elaine Czarnowski, RN, Elaine Hickey, RN, MSN, Cheryl Hankin,
PhD. Bedford VA Medical Center, Bedford, MA. J Anderson. Carol VanDeusen
Lukas, EdD. Boston VA Medical Center, Boston, MA. L Leonard
Objective: VA's emphasis on patient-centered care requires
the evaluation of satisfaction with services. We present data regarding family
satisfaction with hospice care as a component of a Congressionally mandated study to
evaluate VA hospice programs.
Methods: As part of The Veterans Hospice Care Study, The
National Hospice Organization (NHO) Family Satisfaction Survey was completed by a random
sample of 528 family members of recently deceased veterans who received VA hospice care.
Family members were asked to rate levels of satisfaction with eight aspects of hospice
care. These aspects were: 1) satisfaction with the patient's pain control after hospice
admission; 2) satisfaction with other symptom control; 3) quality of family and patient
education; 4) responsiveness of the interdisciplinary care team to patient and family
needs; 5) staff assistance in managing patient and family stress and anxiety; 6) staff
support of patient and family spiritual needs; 7) perceived timeliness of patient's
referral to hospice; 8) staff efforts to support the patient's quality of life. Levels of
satisfaction were measured on a scale of 1 (very dissatisfied) to 5 (very satisfied), so
that higher mean scores (closer to 5.0) correspond to greater levels of satisfaction. VA
survey findings were compared with responses from 17,510 family members from private
(non-VA) hospices. In addition, family members of veterans were asked to identify what
they believed were the strengths and barriers of VA hospice programs.
Results: Both VA mean satisfaction scores and NHO reported
scores ranged from satisfied (4.0) to very satisfied (5.0). In comparison to the NHO
results, the levels of satisfaction reported by all VA hospice patients were similar but
slightly lower than NHO scores. (VA mean satisfaction scores ranged from 95% to 100% of
the NHO mean scores.) The most frequently cited strength of VA hospice programs was the
commitment and skill of VA hospice staff. Family members specifically commented on staff's
willingness to individualize care to meet the changing needs of patients and families. The
most frequently cited barrier to effective hospice care was a perceived delay in veterans'
referrals to hospice. Some family members stated that they believed the veteran would have
benefited from hospice services earlier during his or her disease.
Conclusions: Study results show that overall, family members of
VA hospice patients were satisfied to highly satisfied with the care that veterans
received. Levels of satisfaction with VA hospice care were comparable to those reported in
the NHO survey of non-VA hospices. The average length of stay in hospice for the veterans
in this sample was 65 days compared to 58 days for NHO patients. Although veterans' length
of stay was longer than those reported for non-VA hospice patients, some family members
would have preferred earlier referrals.
Statements: Satisfaction with care is an essential part of any
program evaluation. High levels of satisfaction among family members of veterans who
received hospice care are an indicator of the effectiveness of VA hospice programs. Family
comments indicate that care must be taken to assure timely referral to hospice.
HSR&D Funded: MMR 97-004
67. Mental Health Services Delivery in the
Department of Veterans Affairs: Treatment in Psychiatric, Primary Care, and Specialty
Medical Settings
Benjamin Druss, MD, MPH and Robert Rosenheck, MD. Northwest
Program Evaluation Center, West Haven, CT.
Objectives: Epidemiological surveys suggest that half of
patients with mental disorders in the US are treated in general medical settings. This
paper examines delivery of mental health services in psychiatric, primary care, and
specialty medical clinics in the Department of Veterans Affairs (VA), the largest public
sector health care system in the US.
Methods: Using national VA encounter files, we examined all
outpatient visits to the VA during an 18-month period: October 1996-March 1998. During
this time, VA policy promoted a general shift to a primary care-based delivery system.
Among veterans with any visit for a primary diagnosis of a mental or substance abuse
disorder, we compared the locus, diagnoses, and procedures performed in each of three
settings -- specialty mental health clinics, primary care medical clinics, and medical
subspecialty clinics.
Results: Of 437,035 veterans treated for a mental disorder
during the final 6 months of the study period, 83.0% were seen for their mental disorders
only in specialty mental health clinics; 5.0% were seen exclusively in primary care
medical clinics; 1.7% in specialty medical clinics; and 10.3% in multiple settings. Over
90% of individuals with serious Axis I disorders (Schizophrenia, major depression, bipolar
disorder and PTSD) received mental health care only in specialty mental health settings.
There was no change in the distribution of care between medical and mental health settings
over time, although there was a shift in mental health services delivery from specialty
medical to primary care settings.
Conclusions: A far greater percentage of mental health care in
the VA than in community or HMO populations is provided through specialty mental health
clinics. In contrast to private sector samples, the high levels of psychiatric morbidity
seen in VA patients may make medical treaters reluctant to assume a large portion of their
patients' mental health care.
Impact: These findings may help inform debates regarding mental
health staffing projections both in the VA and in the larger "de facto" US
mental health care system. Estimates of mental health staffing needs based on
"benchmarking," or extrapolation from current managed care staffing patterns,
have generally projected a surplus of mental health providers in the US. However, mental
health's two-tiered public/private system may make such techniques problematic to apply to
mental health services. Developing mental health staffing models that can be generalized
to both the private and public sectors will ultimately require better methods of adjusting
for case-mix and estimating need in these very different populations.
68. Provider Advice and Walking for Exercise in
Elderly Primary Care Patients, and Speciality medical Setting
Patricia Dubbert, PhD. GU "Sonny" Montgomery VA
Medical Center, Jackson, MS. ER Meydrech, KA Kirchner, KM Cooper, and DE Bilbrew.
Objectives: Recent studies have confirmed that physical
activity is beneficial for elderly men and women. Epidemiologic studies and health
guidelines suggest that many elders could decrease risk of disability and premature
mortality by increasing moderate intensity activity such as walking. The purpose of this
study was to examine prevalence and potential predictors of walking for exercise among
patients being screened for the Seniors Telephone Exercise Primary Care Study (STEPS), an
exercise nurse counseling intervention trial.
Methods: Methods:Participants were veterans, 60-80 years of age,
enrolled in VA primary care clinics, and whose health status permitted increased walking.
From 352 identified by medical record and PC provider review, 280 completed a phone
prescreening which included questions about health habits and recall of provider advice to
exercise. 182 subsequently completed a screening visit which allowed collection of
demographic and additional health data.
Results: 164 (59%) of the 280 phone prescreen participants
reported some walking for exercise. Of those already walking, 56% walked <= one day
ago, 68% within the past 3 days, and 72% within the past week. 68% reported walks >= 20
minutes duration. The frequency distribution of walking was bimodal, with about 40% of
participants walking 2-3 times per week and 27% reporting daily walking. 58% reported they
had been walking for 6 months or longer. 16% of patients reported doing regular exercise,
but not walking. Information obtained from the 182 participants who completed a screening
visit found the mean age was 68.8 (S.D. 4.5) years, 26% were minority, 79% married, 22%
employed, 55% lived in a rural setting, and 47% had < HS education. Participants had on
average 3 major medical diagnoses. 143 (51%) of the 280 prescreening participants recalled
being given exercise advice by their health care provider. Estimated in a model that
included ethnicity, number of medical conditions, and urban vs. rural dwelling, recall of
provider advice was significantly related to walking for exercise (O.R. =2.27, C.I.
1.23-4.17, P<.01). None of the other covariates was significantly related to walking.
Conclusions: More than half of elderly VA primary care patients
with chronic illness whose providers thought they could increase physical activity were
already doing some walking for exercise. Notably, those who recalled a provider advising
them to exercise were more likely to be walking. Speed/intensity of walking was not
assessed, and it is likely that the health benefits of walking could be improved if some
participants walked faster or for longer periods of time.
Implications: Although these data are observational, the results
support previous research with younger, healthier populations which indicate that provider
counseling can increase physical activity in sedentary patients. At least 1/3 of
participants reported no regular physical activity. Providers should continue to encourage
patients to be active as their health status permits. Future studies should address
barriers to activity and cost-effective methods of preventive counseling including
physical activity
HSR&D Funded: NRI 95-022
69. Evaluating Screening Criteria for Adverse
Outcomes in Medical Patients
Ron Evans, MSW. VA Puget Sound health Care System, Seattle,
WA.
Objectives: The purpose of the current study was to identify
variables near hospital admission that could effectively discriminate patients at risk for
nursing home placement, lengthy hospital stay, or readmission. The specific goals were to
determine the sensitivity and specificity of differing screening strategies in predicting
adverse outcomes.
Methods: We evaluated the screening criteria, including those
available through hospital billing and resource usage data, to determine if a subset of
generic screens might efficiently identify outcome. Risk criteria reported in the
literature were used to predict discharge destination and duration of care for 1,332
admissions.
Results: Factors that discriminated outcome included:
comorbidity, mental status, living arrangement, transfer to a special care unit, prior
admission within 1 year, iatrogenic trauma, and pending litigation. Sensitivity and
specificity of individual screens varied widely. Prior hospitalization was the most
sensitive [64%] but least specific [47%]. Transfer to a special care unit was specific
[91%] but not sensitive [11%]. Transfer to another hospital was intermediate [sensitivity
32%, specificity 71%]. Combinations of screens were compared, including some using only
resource usage data. The most sensitive strategy using billing data detected 44% of
adverse outcomes and cost only $4 per admission [$51 per adverse event], versus $14 per
admission [$94 per event] when all records were reviewed.
Conclusion: We concluded that use of cumulative risk scores can
result in accurate prediction of hospital outcome, which may be useful in targeting
patients for intervention.
Impact: Using screens available through billing and resource use
data, although insensitive, would be the most cost effective strategy.
70. A Pilot Study: Telecare in the Management of
Diabetes.
Stephan Gaehde, MD, MPH. Boston VA Medical Center, Boston,
MA. BG Fincke. Dan Berlowitz, MD, MPH. Bedford VA Medical Center, Bedford,
MA. J Clark and J Anderson.
Objectives: Recent advances in telemedicine may lead to
substantial changes in the outpatient management of chronic illness. Changes in computer
technology and the development of sophisticated disease management software that is both
physician and patient-friendly may lead to reduced distance between doctors and patients
and improved patient self-management of complex health problems, such a diabetes.Here we
present the results from a pilot study to assess the feasibility of a telemedicine program
that links VA physicians with outpatients with diabetes, through a system of personal
computers in physician offices and their patients' homes connected by ISDN lines that
enable data transfer and videoconferencing. Specific study objectives were to: 1)
Characterize how the technology is adopted, accepted and integrated into the process of
care by patients and providers. 2) Determine effect size of the intervention on
satisfaction with care, degree of glycemic control, health-related quality of life, and
utilization of health care resources.
Methods: In this descriptive pilot study using a pre/post
intervention design, we enrolled 20 patients with type 2 diabetes mellitus requiring
insulin from 5 provider panels at the Boston VAMC. Study outcomes include degree of
glycemic control, patient satisfaction with care, health-related quality of life, and
utilization of resources. Qualitative data regarding acceptability and adoption of the
intervention were collected in structured interviews conducted by a medical sociologist.
Use of the system was characterized by analysis of descriptive data. Outcomes were
assessed using a pre/post intervention design.
Results: Patient interviews prior to having the computers set up
in their homes and at study termination revealed a varied response. Some patients found
the system facile to use and said that the routine of interacting with the program and
reporting the results of glucose and symptoms served to reinforce their motivation for
self-management while several patients had used the system very little, either because
they could not get the system to work or they lost interest. Glycemic control improved
from a mean value of 9.4% to 8.7% (p=0.24) from the start of training to 4.5 months. We
also report how the intervention was used and adopted by patients as well as its effect on
health-related quality of life, satisfaction with care, utilization of resources, and
outpatient visits.
Conclusions: This project has demonstrated that: 1) elderly
veterans without previous computer experience are able to use a technically sophisticated
telemedicine intervention 2) successful deployment of a sophisticated telemedicine system
in actual clinical care. Telemedicine may reduce the distance between physicians and their
patients, who are responsible for following a complicated self-management regimens at
home, with patients experiencing the closer attention as supportive.
Impact: The findings of this study will provide important
insights into how such interventions are adopted by patients and providers and how they
may be best positioned in the process of clinical care in a VA setting. These finding will
be very useful in designing effective future interventions. Further, the findings will
allow estimation of effect sizes of several outcomes including glycemic control,
health-related quality of life and patient satisfaction with care.
HSR&D Funded: SDR 94-11
71. Assessing VA's National Formulary Policy
by Physician Survey
Chester Good, MD, MPH. Pittsburgh VA Medical Center,
Pittsburgh, PA. Peter Glassman, MD. West Los Angeles VA Medical Center. Los
Angeles, CA. M Kelley, M Bradley, M Valentino, J Ogden, and K Kizer.
Objectives: The VA National Formulary (VANF) was implemented
in June 1997 to improve equity of access to pharmaceuticals across VHA and to improve
accountability of VA's 1.6 billion dollar pharmaceutical program. We surveyed physicians
approximately 1 year after implementation to help assess VANF's effects on patient care,
access to drugs, physician workload and VA's ability to train resident staff.
Methods: Questions, scored on a 5-point Likert scale, addressed
general issues about the VANF and specific effects of choosing selected drugs within six
drug classes. Respondents also provided demographic information. The sample population (n
= 4640), based on the circulation files of The Veterans Health Journal, included all
listed general internists (n = 2824) and convenience samples of neurologists (n = 238),
psychiatrists (n=997), general surgeons (n = 429), neurologists (n = 238) and urologists
(n = 152). Non-responding physicians received a second survey approximately 1 month after
the first. A total of 104 physicians were declared ineligible, leaving a final sample of
4536. Comparisons across groups were by Chi-squared analysis.
Results: Overall response rate was 45% (2041/4536). Physicians
were all attendings, average age 49 years, with 11 years of VA service, and averaging 5
half-day outpatient clinics per week; 73% were full-time employees; 20% practiced in other
health systems with formularies, and 13% were on VA Pharmacy Committees. Most physicians
(63%) agreed that they could prescribe needed drugs; 66% agreed that patients could obtain
non-formulary drugs, when necessary. About one-third (32%) of physicians disagreed that
access to prescription pharmaceuticals had increased over the past year. Although 29%
stated the VANF impinged on providing quality care to their patients, fewer physicians
(24%) felt that it impinged on providing quality care to other VA patients. Thirty-eight
percent (38%) felt that the VANF was more restrictive than private sector formularies but
only 16% felt that the VANF diminished the ability to train residents for managed care.
Most physicians (60%) did not agree that the Formulary added substantially to their
workload. Regarding questions on drug class selections, the overall perception was that
selections had nominal effect on patient care. For example, choosing lovastatin and
simvastatin as formulary drugs was felt to have a positive effect on patient care by 29%
of physicians, no effect by 46% and a negative effect by 8%. We noted significant
differences among physicians on many issues. For example, VA physicians who worked in
other health care systems with formularies were less likely to agree that the VANF added
substantially to workload (28% vs. 38%, P < .001).
Conclusions: Most participating VA physicians did not perceive
that the VANF negatively affected quality of patient care, access to pharmaceuticals,
physician workload or resident training.
Impact: VHA is the first national health care system to assess
the impact of formulary policy by surveying physicians. Survey results are being used to
increase understanding of the VANF and to improve its functioning, with further policy
evaluations now being directed towards ensuring access to non-formulary products and
towards understanding effects on physician workload. Future surveys are planned.
72. Does Military Status Influence Use of VA
Ambulatory Care?
Nancy Harada, PhD, Donna Washington, MD, MPH, and JoAnn
Damron-Rodriguez, PhD. West Los Angeles VA Medical Center, Los Angeles, CA. T
Makinodan, H Liu, and S Dhanani.
Objectives: Military experiences have been documented to
influence a veteran's subsequent use of health care services. Specifically, these military
experiences may serve as predisposing, enabling, or need variables affecting VA ambulatory
care utilization. The objectives of this study were to identify military status factors
predictive of VA ambulatory care use, and to determine whether these factors remain
significant after controlling for race/ethnicity, sociodemographic, and health status
characteristics.
Methods: The source of data was the 1992 National Survey of
Veterans (NSV). Since the NSV sample is 97% male, our analyses were limited to this gender
group. Bivariate analyses were conducted to describe the demographic and military status
characteristics of VA ambulatory care users and non-users. A hierarchical logistic
regression analysis was conducted with use of VA ambulatory care as the dependent
variable. The initial logistic model included several variables descriptive of military
status, followed by 3 additional models controlling for race/ethnicity, sociodemographic,
and health status.
Results: Of the total sample (n=7,851, mean age=56 years), 41%
had used VA ambulatory care services in the previous year. Sixty-four percent of the VA
users came exclusively to the VA for ambulatory care, and the remaining had used the VA in
conjunction with non-VA ambulatory care. The first model explored the contribution of
military status variables to ambulatory care use without controlling for race/ethnicity,
sociodemographic, or health status. Significant military status variables included
retirement from the military for disability (OR=1.6), combat exposure (OR=1.1), service in
the Marines (OR=1.3), Army (OR=1.3), or during the Korean Conflict (OR=1.3),
service-connected injury (OR=1.6), 6 or more years of military service (OR=1.3), and
retirement from the military after 20 years of service (OR=.58). Controlling for
race/ethnicity in the second model did not alter the list of significant military status
variables. The inclusion of sociodemographic characteristics in model 3 decreased the list
of significant military status variables to service in the Marines (OR=1.6),
service-connected injury (OR=1.2), and 6 or more years of service (OR=1.4). After
controlling for race/ethnicity, sociodemographic, and health status in the final model
only military service for 6 or more years remained significant (OR=1.4). However the final
model showed that veterans who are minorities, of lower socioeconomic status, uninsured,
have poor health status and a service-connected disability have a greater likelihood of
being a VA ambulatory care user.
Conclusions: The findings demonstrate that the VA serves as an
important source of health care for veterans with service-connected disabilities and long
term service in the military. In addition, veterans who are minorities, of low
socioeconomic status and poor health status also use the VA for ambulatory care.
Impact: Military status characteristics describing veterans who
use ambulatory care highlight the importance of health care entitlement for Americans who
served their country. The VA serves as an important source of ambulatory care for veterans
with service-connected disabilities and long term service in the military. As the VA seeks
to restructure its delivery of ambulatory care, it must create policies to benefit this
deserving population.
HSR&D Funded: ECV 97-028
73. How Primary Care Providers Treat Depression:
Attitudes, Skills, Barriers and Personal Experience
Nicole Hasenberg, MPH, Edmund Chaney, PhD, CE Hansen, and Susan
Hedrick, PhD. VA Puget Sound Health Care System, Seattle, WA.
Objectives: We wanted to learn more about primary care providers
(PCP) attitudes regarding the diagnosis and treatment of depression with the eventual goal
of targeting different educational interventions toward PCPs and improving medical care
for patients who are depressed.
Methods: We obtained cross-sectional data from PCPs as part of a
larger study about depression treatment at the General Internal Medicine Clinic at the VA
Puget Sound Health Care System in Seattle. We asked them to evaluate their attitudes,
skills, and barriers to treating their patients with major depression. We also were
interested in whether having personal experience with depression would influence
self-reported skills and comfort level with treating depression.
Results: At the end of two GIMC Journal Clubs and several
Resident Post-Clinic Case Conferences during January, February, July, and August of 1998,
we notified PCPs about the depression study and asked them to complete an anonymous 5 to
10-minute questionnaire. During that time, 90 Primary Care Providers were on staff, of
whom 31(34%) were Attending
Physicians or Medical Fellows, 18(20%) were Nurse Practitioners and
41(46%) were Medical Residents. Of those on staff, 61(68%) PCPs completed the survey.
Almost all PCPs (91.8%) feel comfortable writing referrals for further
depression treatment. Overall comfort level with skill-based treatment was good; 40(78.7%)
PCPs said they felt somewhat or very skilled at making a diagnosis; 39(63.9%) felt
somewhat or very skilled about writing a prescription for anti-depressant medication; and
28(45.9%) believed the same about counseling and education regarding depression.
Many providers reported the following barriers to care limit them a
great deal in treating depression: no time for education and/or counseling (54%);
preferred medication difficult to obtain (43%); viewing other medical problems as more
pressing (36%); perceiving the patient as reluctant to accept diagnosis or treatment
(30%); inadequate time for follow-up (28%); and lack of availability of mental health
professionals (25%).
In terms of provision of care, 59% think depression usually should be
treated in primary care settings compared with 31% who think those with depression should
be referred to specialty clinics.
In this population 48(79%) providers report that they or a close friend
or family member had personal experiences with depression. We tested whether there was an
association between providers who had personal experience with depression and all the
mentioned skills and barriers to care. None of the variables were statistically
significant, however small numbers in each cell may influence such results.
Conclusions: Primary care provider education may be more
effective if it is tailored toward counseling and educating a person who is depressed.
Individual VAs can focus on particular systems barriers (such as getting different
medications on the formulary or providing more time for care of depressed patients) to
improve the treatment of depression. Finally, initial analysis suggests that personal
experience with depression does not seem to significantly influence skills and barriers to
treatment.
Impact: These results can be used for educating primary care
providers and for planning and delivering depression treatment in ambulatory care
settings.
HSR&D Funded: 95-097
74. The Use of Ambulatory Care Sensitive
Hospitalization as a Qualitative Indicator of Primary Care
Laura Hechtel, PhD, Margaret Byrne PhD, and Carol Ashton MD, MPH.
Houston VA Medical Center, Houston, TX.
Objectives: Ambulatory care sensitive (ACS) conditions have been
proposed as an indicator of access to, and quality of, primary care. In this study, we
examine the validity of using such an indicator as it relates to primary care enrollment.
Methods: From the Outpatient Clinic file (OPC, FY 1996), users
were considered to be enrolled in primary care if they had at least one primary care
clinic stop. From the Patient Treatment File (FY 1996), ACS and non-ACS hospitalizations
were determined for each OPC user and for each hospital facility. In addition, the 10 most
frequent DRG's for primary care (PC) enrollees and non-primary care (NPC) enrollees were
collected.
Results: 31.0% of PC enrollees were hospitalized for any
condition as compared to 21.7 % for NPC enrollees. PC enrollees had a significantly higher
(p=0.0001) hospitalization rate (1130 per 1000 individuals) than NPC enrollees (1068 per
1000 individuals). The proportion of hospitalizations that were for ACS conditions was
significantly greater (p=0.0001) in PC enrollees (12.8%) than in NPC enrollees (7.5%).
This outcome was consistent across hospital facilities (n=153). Among 10 most frequent
DRG's, 4 were ACS conditions while the other 6 were psychiatric diseases. All 4 ACS
conditions were more common than expected in PC enrollees, while 4 of the 6 psychiatric
diseases were more common than expected in the NPC enrollees.
Conclusions: The hospitalization rate for ACS conditions is
higher in VA users enrolled in PC compared with those not enrolled in PC. That this
finding was consistent across all VA facilities makes it highly unlikely that the ACS
hospitalization rate is measuring quality of care. It is more likely that ACS
hospitalization rates are reflecting systematic differences in the prevalence and severity
of certain diseases between the PC and NPC VA user populations. If hospitalization rates
for ACS conditions are to be used as an indicator of quality of care, more research is
needed into their validity.
Impact: Using hospitalization rates for ACS conditions as a
quality of care indicator assumes that the populations under study are clinically similar
and utilize VA hospital facilities in the same manner. However, this study shows that this
may not be true. Health science research must take into consideration population
characteristics in order to more reliably assess quality of care. Our findings show that
it is inappropriate at the present time to use hospitalization rates for ACS conditions as
a quality indicator with VA system.
75. Treatment can Enhance the Effectiveness of
Substance Abuse Self-Help Groups
Keith Humphreys, PhD. VA Palo Alto Health Care System, Menlo
Park, CA. Rudolf Moos, PhD. VA Palo Alto Health Care System, Palo Alto, CA.
Objectives: Affiliation with Alcoholics Anonymous (AA) and other
12-step self-help groups is becoming more common at the same time as professional
substance abuse treatment services are becoming less available and of shorter duration. As
a result of these two trends, patients' outcomes may be increasingly influenced by the
degree to which professional treatment programs help patients take maximum advantage of
self-help groups. The present study of 3018 treated veterans examined how the theoretical
orientation of a substance abuse treatment program affects (1) The proportion of its
patients that participate in self- help groups, and, (2) The degree of benefit patients
derive from participation in self-help groups.
Methods: A 1-year longitudinal study at 15 VA facilities
nationwide.
Results: Patients treated in 12-step and eclectic treatment
programs had higher rates of subsequent participation in 12-step self-help groups than did
patients treated in cognitive behavioral programs. Further, the theoretical orientation of
treatment moderated the outcome of self-help group participation: As the degree of
programs' emphasis on 12-step approaches increased, the positive relationships of 12-step
group participation to better substance use and psychological outcomes became stronger.
Conculsions: Hence, it appears that 12-step oriented treatment
programs enhance the effectiveness of 12-step self-help groups. Findings are discussed in
terms of implications for clinical practice and for future evaluations of the combined
effects of treatment and self-help groups.
Impact: These findings present a practical way for VA clinicians
to improve outcomes at little additional costs.
76. Do Oral Health-Related Quality of Life Measures
Relate to Use of Dental Care?
Judith Jones, DDS, MPH, Nancy Kressin, PhD, A Spiro III, PhD, Donald
Miller, ScD and Lewis Kazis, ScD. Bedford VA Medical Center, Bedford, MA. RI
Garcia.
Objectives: Valid dental outcome measures should vary with
the use of dental services. The purpose of this analysis is to examine the relationship of
oral health-related quality of life measures to past use of dental care in two
populations.
Methods: We examined the retrospective relationships of
self-reported oral health measures to self-reported use of care in two contrasting samples
of veterans, the Veterans Health Study (VHS, N=538, mean age=62) and the VA Dental
Longitudinal Study (DLS, N=278, mean age =71). Self-reported oral health measures included
a single-item self-report measure of oral health (OH1), the 3-item Oral Health-Related
Quality of Life measure (OHQOL, Kressin, et al, 1996) the 12-item Geriatric Oral Health
Assessment (GOHAI, Atchison & Dolan, 1990), and the 49-item Oral Health Impact Profile
(OHIP, Slade & Spencer, 1994). Use of care was categorized into <=1year, >1year;
and <=2years, >2years. Reason for last visit was divided into emergency and routine
care (exam and cleaning, fillings, other).
Results: In the VHS sample, better oral health (OH1) was
associated with recency of dental visit, i.e., better oral health was associated
(p<0.05) with more recent use (in last year and last 2 years). Better scores on the
OH1, OHQOL and OHIP were significantly associated with reason for last visit, with
approximately 0.5 sdev lower scores, on average, in persons who used emergency as compared
to routine care. In the DLS sample, there were no significant differences in mean
self-reported oral health scores by recency of use or reason for last visit; however
trends were in the expected directions.
Conclusions: The validity of these self-report measures of oral
health is suggested by the association with recency of dental care and reason for last
visit in VA health care users. However, no significant associations were observed in the
DLS, most of whom use routine dental care.
Impact: Self-reported oral health measures may be useful to
monitor the effects of dental care on patients' quality of life in users of VA health
care.
HSR&D Funded: IIR 93-025
77. Health Outcomes of Veterans Using SF-36V: 1998
National Survey of Ambulatory Care Patients
Lewis Kazis, ScD. Bedford VA Medical Center, Bedford, MA. N
Wilson, W Rogers, and A Lee. Xinhua Ren, PhD, Katherine Skinner, PhD, Alfredo
Selim, MD, MPH, and Donald Miller, ScD. Bedford VA Medical Center, Bedford, MA.
Objectives: The Veterans Health Administration (VHA) is now
implementing patient centered measures of functional status as part of its performance
measurement system to set goals and standards for the 22 VISNs (geographically based
groups of hospitals), individual hospitals and providers. To monitor the changes in health
status over time, we established a cohort of veteran users of the VHA who were
administered the SF-36V in 1996 and again in 1998. These changes may be related to the
processes of care.
Methods: The SF-36V (Short Form Health Survey for Veterans) was
mailed to a national probability sample of 25,040 veterans between January and February
1998 who had been administered the same questionnaire, 17 months earlier in 1996. For the
cohort, the response rate was 85.2% using a modified Total Design Methodology approach
developed by Dillman. The SF-36V, developed in the Veterans Health Study is a patient
based questionnaire designed specifically for use among veterans who are in ambulatory
care. The SF-36V is a reliable and valid measure of health status with increased precision
over the MOS SF-36. Eight concepts of health are summarized into physical (PCS) and mental
(MCS) component summaries standardized to the U.S. population with a mean of 50. Each of
the patient scores were computed as the difference of the 1996 score from the 1998 score
for PCS and MCS, respectively. A negative score denotes worsening. Overall trends in the
VA were compared to the Medical Outcomes Study (MOS), a general population in civilian
managed care for the same duration of follow-up. Comparisons of the trends over time among
VISNs were made with multivariable adjustments for case mix using age, gender, and
diagnoses with a previously validated approach using ICD-9 codes.
Results: Rates of physical decline in the VA were about a third
of that observed in the civilian sector (MOS) (p<0.01). For PCS, the 17-month physical
decline was -0.39. The MOS study showed a much greater rate of decline equivalent to -1.08
over the same time period. There were no important differences in the trends among the
VISNs for PCS. For MCS, the rate of mental decline in the VA compared to the MOS study was
comparable (p>0.20). However, we found considerable variation in mental health trends
across the VISNs. Trends varied from 0.69 to -0.93, an overall range of 1.62 (p< 0.05).
After discounting sampling errors, regression to the mean effects and attrition, trends in
PCS for the VA compared to the civilian sector remained significant and clinically
important. For MCS, differences in the trends observed among VISNs, are larger than case
mix explanations would suggest even after taking random sampling errors into account. The
differences in the trends for MCS are equivalent to treating the psychological impact of
two medical conditions.
Conclusions: Substantial variation in MCS trends among VISNs
were observed and for the most part, were not explained by case mix or methodologic
factors. These findings suggest that processes of care are likely candidates to explain
these differences.
Impact: These results have important implications for quality
assessment and for setting goals for the VISN performance measures.
HSR&D Funded: SDR 91-006
78. Multi-site Research: Overcoming Hurdles
Anne Keane PA-C, JD, Nathan Every MD, MPH, and Anne Sales PhD,
RN. VA Puget Sound Health Care System, Seattle, WA.
Objectives: In this paper, we describe the process and costs of
obtaining Institutional Review Board (IRB or Human Subjects Committee) approval and access
to electronic data systems at each of 30 VA Medical Centers (VAMCs) in five Networks for a
study of patient outcomes and clinical integration in cardiology. We then propose changes
to some of the processes of obtaining necessary approvals that would enable research to be
done at less cost while still preserving adequate reviews for patient safety at each
medical center and facility providing patient care.
Methods: As part of the proposal process, we gained approval
from our local IRB for the protocol. This submission and required revisions are not
included in our estimates of time and cost. Beginning in January 1998, we contacted the
IRBs for all of the VAMCs in the five VISNs included in our study: VISNs 13, 18, 19, 20,
and 22. We contacted the people who had supported the study at each of the medical
centers, and obtained the contacts for the local IRB. We then submitted the application
required for the local IRB, as well as complete copies of the protocol, human subject
submission and approval from our own IRB. During the same time period, we began to contact
Information Resource Management (IRM) at each medical center to obtain the applications
for gaining access to electronic records. Once we had obtained IRB approval at each site,
we requested IRM access.
Results: We found a wide variety of IRB mechanisms in the 35
sites we initially contacted. We began the process in January 1998, and are still
completing IRB negotiations at one site in November 1998. Most sites had given us approval
by June 1998. We had to drop some sites from the study because of the difficulties of
negotiating IRB approval. The project manager and secretarial support staff spent the most
time involved in obtaining IRB approval, for a combined total of approximately 800 hours
of effort, at a cost of approximately $20500. Several staff members were involved in
obtaining IRM access, with a combined total of 560 hours, for a total cost of $15600. The
two Principal Investigators were involved to a lesser extent, for about 32 hours, at a
cost of approximately $1100. The total cost of this piece of the project was approximately
$37200. The final number of VAMCs participating in the study is 30, for an average cost of
$1240 to obtain both IRB approval and IRM access to each medical center.
Conclusions: Obtaining IRB approval and IRM access for a large,
multi-site study is time-consuming and expensive. The process worked best when there were
dedicated staff, and when we could link medical centers together in a geographic region,
generally the VISN.
Impact: These results are likely to be of interest to VA HSRD
Management, researchers in the field, and VISN staff who have a vested interest in
VISN-wide research studies. Obtaining high quality comparative data at relatively low cost
across medical centers is a high priority for these groups.
HSR&D Funded: ACC 97-001
79. Toward Gender-Aware VA Health Care: Staff
Ideology, Sensitivity, and Knowledge
Lynda King, PhD and Daniel King, PhD. National Center for
PTSD, Boston, MA. P Miller and V Savarese. J Wolfe
Objectives: Despite VHA efforts to better accommodate the
healthcare needs of a growing number of women veterans, an historical orientation towards
treating male patients may have resulted in a less than optimal care environment for
female patients. Our guiding hypothesis is that this environment is influenced by three
overlapping personal characteristics of VHA employees: (1) the tendency to work without
gender stereotypes, (2) sensitivity to female patientsÆ special needs, and (3) knowledge
of women veterans and their healthcare. Together these comprise what we have termed gender
awareness. For this three-year project, we seek to develop a reliable and valid
self-report measure of gender awareness for use with all VHA personnel. The project has
four objectives: (1) to refine the definitions of the gender awareness components and
create the instrument, (2) to establish the instrumentÆs psychometric properties, (3) to
obtain normative data, and (4) to make the instrument available for large-scale use.
Methods: The design is observational and cross-sectional, with
multiple waves of data for reliability and validity analyses. Participants are VHA
employees selected using proportional stratified random sampling from the VA New England
Healthcare System. In the first year, 621 employees received a preliminary version of the
instrument; 371 (60%) were completed. The sampleÆs mean age was 46.01 years (SD = 11.58);
60% were female; and 25% were military veterans. Analyses included computation of
descriptive statistics and frequency distributions for all questionnaire items,
probabilities of endorsement, item-total correlations, coefficients of internal
consistency reliability (alpha), and interscale correlations.
Results: The 18-item scale assessing the ideology component of
gender awareness had a mean of 72.38 (SD = 11.77; range = 39-90); alpha = .90. The 19-item
sensitivity scale had a mean of 75.72 (SD = 8.08; range = 56-94); alpha = .75. On the
36-item knowledge test, the mean number of correct responses was 19.60 (SD = 4.92; range =
0-29). The most-missed knowledge items were related to demographics of women veterans,
eligibility for sexual trauma services, and VHA utilization rates.
Conclusions: The project is ongoing. Year 1 was successful, with
the more affective components of gender awareness, ideology and sensitivity, having
established discriminant validity, correlating .38. Presently, the instrument is being
further refined, as the sensitivity scale is seeing additional adjustments to improve its
consistency.
Impact: The gender awareness assessment instrument will provide
a means to identify and measure factors that contribute to the quality of VA healthcare
for women veterans, and will provide a mechanism to pinpoint training needs for the
education and remediation of employees. Moreover, the instrument will afford a means to
monitor organizational improvements in gender awareness over time. Our long-term goal is
to have a product that has justifiable transportability on a large scale. At an
organizational level, we anticipate that the proposed project will contribute to the
contemporary emphasis on outcomes measurement. The gender awareness assessment package can
fit nicely within a program to monitor patient satisfaction among the growing number of
women veterans, as that satisfaction relates to features of organizational climate.
HSR&D Funded: GEN 97-014
80. Is Depression Associated with Oral
Health-Related Quality of Life?
Nancy Kressin, PhD, Avron Spiro III, PhD, Katherine Skinner, PhD
and Judith Jones, DDS, MPH. Bedford VA Medical Center, Bedford, MA.
Objectives: The health-related quality of life (functional
status, emotional well-being) of patients with depression is often as low as, or lower
than, that of patients with chronic medical conditions. However, we do not know whether
depression has a similar effect on oral health- related quality of life (oral QOL). VA
dental policymakers, clinicians and researchers are increasingly relying on oral QOL
ratings to evaluate dental treatment needs and outcomes of care. Thus, it is important to
understand what factors influence such ratings.
Methods: We examined the association between depression
(measured by the CES-D) and oral QOL, using two different indices: the Geriatric Oral
Health Assessment Index (GOHAI) and the Oral Health-Related Quality of Life measure
(OHQOL). Using data from 3 veteran samples: male VA patients in the Veterans Health Study
(VHS), female VA patients in the VA Women's Health Project (WHP), and male community
dwelling veterans who do not use VA care (Normative Aging Study (NAS)), we examined
whether individuals who screened positive for depression (scoring above the standard
cutpoint) had worse oral QOL than those who were not, controlling for sociodemographics
(age, education, marital status), and self-reported oral health.
Results: In bivariate analyses, being depressed was associated
with worse OHQOL scores in both the VHS and WHP veteran patient samples, as well as in the
NAS. Depressed individuals had worse GOHAI scores in the VHS and WHP, but not in the NAS.
After controlling for self-reported oral health, age, income, marital status and
education, depression remained significantly associated with both oral quality of life
measures in all samples, and the independent and control variables together explained
between 15 and 30% of the variance.
Conclusions: These results suggest that there is a strong
association between depression and oral quality of life, suggesting further negative
health impacts of depression in addition to those already quantified with regard to
physical health. However, these cross-sectional data cannot prove causality. Future
research should further explore the mechanisms of the association of depression and oral
quality of life through the use of longitudinal data.
Impact: The understanding of psychosocial and other factors
which influence patients' ratings of quality of life is crucial to the accurate
interpretation of findings by researchers, clinicians, and policy makers. Recognizing that
depression is a significant correlate of oral health outcomes improves the measurement of
oral quality of life and provides a potential avenue for interventions to improve oral
health outcomes.
HSR&D Funded: 93-05, SD 91-006, SDR 93-101, HFP 91-012
81. An Overview of the Decision Support System
Joseph Kubal, MA, Denise Hynes RN, PhD, Diane Cowper, MA, Michael
Kerr, MS, MA and J Palmer. VA Information Resource Center, Hines IL.
Objectives: The primary objective of this informational poster
is to present summary information on the currently evolving Decision Support System (DSS).
DSS is a database that provides integrated clinical and financial data to help managers
make informed tactical and strategic decisions. The DSS software was developed and
tailored for the VA by Transition Systems Incorporated (TSI). The information for this
poster was developed by the VHA Chief Information Office and the DSS Program Office and is
being presented by VA Information Resource Center (VIREC) staff to inform HSR&D
researchers of this new VA-wide system which ultimately has ramifications for health
services research.
Methods: All the data in the DSS come from existing VA databases
resident at the Austin Automation Center (AAC). These include: 1) Personnel and Accounting
Integrated Data (PAID), 2) Consolidated Memorandum of Receipt (CMR), 3) Financial
Management System, 4) National Patient Care Database (NPCD), 5) Patient Treatment File
(PTF), and 6) Patient Assessment Instrument (PAI).
Results: DSS: 1) Allows budgeting and budget modeling for
medical centers, VISNs and VHA based on case-specific workload, 2) provides for resource
distribution to the medical centers and VISNs based on performance, 3) Supports
implementation of managed care for the VHA system, 4) Allows equitable comparisons of
medical centers, 5) Supports VHA funding request to OMB and Congress, 6) Supports quality
management and quality improvement initiatives, 7) Supports the development of an itemized
patient bill for the Medical Care Cost Recovery (MCCR) program and 8) Provides
productivity analysis and patient specific costs.
Conclusions: The VA is now realizing what private hospitals have
known for some time û becoming and remaining competitive ensures success and survival.
The health care industry is rapidly evolving; the VA must keep up and compete with other
health care organizations to remain viable. DSS is designed to provide the information
that is needed to make those business decisions that are required in a competitive
marketplace.
Impact: DSS will provide the critical tools necessary for VA
hospitals to remain cost effective and efficient in the dynamic U.S. health care
environment. The VA strategy for implementing DSS emphasizes an interdisciplinary
approach, integrating clinical and administrative cost accounting systems, and now senior
leadership. Consistent use of this approach in DSS will permit VHA to become and remain
competitive now and in the future. Finally, DSS information will prove useful to
HSR&D, CSP, and other VA researchers in their ongoing quest for accurate clinical and
cost data.
HSR&D Funded: SDR 98-004
82. Establishing Clinical Equivalence: An Example
from a Study of Self-Care Center versus Full-Care Hemodialysis
Martin Lee PhD, CA Landis, Mingming Wang MPH, Elizabeth Yano
PhD, Lisa Rubenstein MD, MSPH, Center for the Study of Healthcare Provider Behavior,
Sepulveda, CA.
Objective: In most studies, the goal of the research is to
demonstrate that one or more of the intervention groups is superior in some sense to other
arms of the study. These comparisons may be dealt with using standard statistical
approaches. However, on some occasions, the objective may be to demonstrate that an
intervention is no worse than another, since such a finding might be helpful if this new
approach is easier to use, more cost-effective, etc., and could be used if the clinical
effectiveness is basically equivalent to existing methodologies. A failure to reject the
usual statistical null hypothesis of no difference is not grounds for reaching this
conclusion because of power considerations arising from small sample sizes. Our objective
here is to demonstrate how to reach the conclusion of clinical equivalence using a proper
statistical framework within the context of a study on two methods for the care of chronic
dialysis patients.
Method: An observational retrospective cohort study was
conducted on 135 patients undergoing hemodialysis patients at the West Los Angeles VA
Medical Center between June 1977 and December 1994. Forty-nine subjects used a self-care
approach (at the center) and 86 received traditional full-care hemodialysis. Patient
mortality was the primary endpoint insofar as demonstrating clinical equivalence of these
two methods for care delivery. The Cox proportional hazards model was used to generate the
adjusted the 1, 2, and 5-year survival probabilities with respect to patient age and
presence of pulmonary disease (the only significant baseline covariates). The comparison
of these probabilities was based on the usual two-sample Z-statistic with the hypothesis
testing paradigm modified whereby the null hypothesis was one of inferiority (defined as a
difference in survival probabilities of more than 10%) and the alternative hypothesis
indicating clinical equivalence.
Results: The estimates of the survival probabilities were .976
for self-care and .928 for full-care at 1 year, .891 for self-care and .752 for full-care
at 2 years, and .719 and .466 at 5-years. The test of inferiority was significant in each
case (p<.001), providing statistical evidence of a lack of inferiority for the
self-care approach.
Conclusion: Using an appropriate statistical strategy, it was
possible to demonstrate that a self-care center approach to hemodialysis is no worse than
the traditional method for delivery of this care. Given the potential for cost-savings and
improved patient quality of life, this approach may be a reasonable alternative.
Impact: This study indicates that alternatives to full-service
clinical care at a VA center are reasonable to consider, and may in fact, be potentially
superior. This is particularly relevant as the VA healthcare system further embarks on the
examination of practice patterns to identify and promulgate best practices through the
QUERI process.
83. Evaluating the Effect of Primary Care Clinic
Visits on Survival for Hospitalization
Martin Lee PhD, Mingming Wang MPH, Elizabeth Yano PhD, and Lisa
Rubenstein MD, MSPH, Center for the Study of Healthcare Provider Behavior, Sepulveda,
CA.
Objectives: Objective: From an examination of patients
hospitalized at the Sepulveda and West Los Angeles VA Medical Centers, we evaluated the
possibility that more frequent primary care users had a greater likelihood of surviving a
hospital stay for one of a set of significant clinical situations.
Methods: Method: All patients hospitalized during the 1993
fiscal year at Sepulveda VA (SVA) and the West Los Angeles VA (WVA) (two
academically-affiliated VA medical centers with active primary care programs in Southern
California) were identified. The subset of individuals identified as being admitted for
major cardiac, cerebrovascular and respiratory conditions based on ICD-9 codes were
specifically utilized in this study, as these conditions appeared to be the most likely to
be affected by frequent primary care. We classified each case according to whether the
patient survived (survivors), died in hospital or within thirty days of discharge (early
death), or died between thirty days and one year after discharge (late death). We obtained
demographic information and the mean number of primary care clinic visits during the
twelve months prior to hospitalization for patients in each of these three categories. We
used a polytomous logistic regression model to determine whether there was a relationship
between primary care visitation and survival after adjustment for key independent survival
indicators such as age. We also utilized a Cox proportional hazards regression model to
examine the same variables as a function of the actual survival time (potentially censored
twelve months after hospital discharge). Initial univariate analyses were considered to
compare the three study groupings with respect to mean primary care visitation (using the
Kruskal-Wallis test).
Results: The SVA sample included 3,459 inpatients (88.8%
survived, 5.9% late deaths, 5.3% early deaths) and the WVA sample had 5,344 individuals
(87.4% survived, 6.2% late deaths, 6.4% early deaths). On a univariate basis, both
institutions' survivors had significantly more primary care visits (average 6.7/yr: SVA,
5.3/yr: WVA) than early death (5.1/yr:SVA, 2.7/yr:WLA) or late death (4.1/yr:SVA,
2.7/yr:WLA) patients.This significance held up in both multivariate models.
Conclusions: Patients admitted with serious major medical
conditions who had been seen more often in primary care clinics prior to their
hospitalization were more likely to survive their hospital stay. The significance of the
primary care visitation pattern may be to hospitalize the patient earlier in the course of
an illness episode or result in better peri-hospital management. It is also possible that
the more frequent users had different casemix characteristics than less frequent users,
although we did attempt to adjust for many of these potential covariates. At the very
least, investigators evaluating the significance of primary care should consider visit
patterns into consideration.
Impact: With the emphasis in the VA healthcare system on the
delivery of primary care, this study suggests that such care may have a direct impact on
future hospitalization survival. This provides further impetus for the continuing efforts
to adequately deliver this care.
84. The Economic Impact of Automated Primary
Screening for Cervical Cancer: Use of a Markov Chain Model
Martin Lee, PhD. Sepulveda VA Medical Center, Sepulveda, CA.
BL Smith, S Leader, and P Westlake.
Objective: The Papanicolaou (Pap) smear detects precursor
changes to cervical cancer enabling therapeutic interventions to potentially avert
invasive cervical cancer. Its widespread use has resulted in more than a 70% decline in
cervical cancer-related morbidity and mortality in the United States over the past forty
years. Yet, cervical cancer continues to be prevalent. Newly developed technologies such
as automated primary screening have been introduced to reduce the incidence of false
negative Pap exams. We have examined one such device, the AutoPap« Primary Screening
System (Neopath, Inc., Redmond, WA) with respect to its economic impact on the healthcare
system, since this device has been previously shown to be more sensitive and specific than
manual examination of Pap smears. This study serves to address the concern as to whether a
clinically effective diagnostic procedure can also be cost effective.
Method: To evaluate the economic impact of AutoPap, we developed
a model of the progression of cervical disease that involves six stages of pathology from
a healthy state through death. This traditional model was expanded to include substances
that allow for treatment (or its absence) and the success thereof within each stage.
During a fixed time interval (say, one year), patients are allowed to move between stages
or remain in the same stage with certain fixed probabilities. This was represented by a
basic first-order Markov model. The probabilities that populated this model were
determined from the literature or from consultation with medical practitioners. Ranges
(determined by a modified Delphi process) were use to assess model sensitivity. The model
was run on a hypothetical group of 18 year old women whose mortality pattern represented
that for the general population of women of that age in the US. The program DATA (TreeAge
Software, V3.0.17) was used to run the simulation.
Results: Annual screening with AutoPap produced a meaningful
increase in life expectancy of 32.1 days relative to manual screening at a marginal
savings of $628 per person (or -$7,144 per life year saved). Less frequent screening
yielded lower positive savings.
Conclusion: Automated screening for cervical cancer has the
potential to significantly improve healthcare outcomes and reduce cost. The use of
appropriate mathematical models for the evaluation of the economic impact of such new
interventions can be of great value in these determinations.
Impact: Given that as of the end of 1996 there were 1.2 million
female veterans, an evaluation such as that reported here may prove to have a significant
economic impact for the VA system.
85. Patient-Centered Alternative to Psychiatric
Hospitalization
James Lohr, MD. VA San Diego Healthcare System. San Diego,
CA. W Hawthorne, B Green
Objectives: The purpose of this study was to assess the
effectiveness of an alternative to acute psychiatric hospital treatment, the Short-Term
Acute Residential Treatment(START) model.
Methods: A total of 376 START program clients participated in
the study, which used a repeated measures design and assessed participants on multiple
standardized measures of symptoms and functioning at admission, discharge, and at a
4-month follow-up interval. Ex post facto comparisons were made with data from 186
psychiatric hospital patients from previously conducted outcome studies utilizing the same
instruments and procedures. Measures included the Brief Symptom Inventory, the Behavior
and Symptom Identification Scale-32, the Medical Outcome Short Form 36, and the Client
Satisfaction Questionnaire-8, as well as demographic and other data.
Results: The results of this study indicate that START
facilities and psychiatric hospital programs admit persons with similar levels of acute
distress, demonstrate comparable levels of improvement by discharge, and produce an
equivalent degree of short-term stability of treatment gains.
Conclusions: This study supports the START program model as a
less costly yet similarly effective alternative to psychiatric hospitalization for many
voluntary adults.
Impact: During the 1997 fiscal year, the VHA spent 1.5 billion
dollars on mental health services for veterans, of which inpatient psychiatric hospital
services accounted for 50% of those costs. The development of START programs could have
significant impact on this very costly aspect of psychiatric care.
86. VA Utilization by Level of Diagnostic Cost
Group (DCG) Predicted Risk
Susan Loveland and Amy Rosen. Bedford VA Medical Center,
Bedford, MA. A Ash Cheryl Hankin, PhD, James Rothendler, MD, Dan Berlowitz, MD,
MPH, and Jennifer Anderson, PhD. Bedford VA Medical Center, Bedford, MA. Mark
Moskowitz, MD. Boston University School of Medicine, Boston, MA.
Objectives: As VHA adopts managed care practices, it needs to
understand the disease burden and resource utilization of its population. Risk adjustment
methods, such as Diagnostic Cost Groups (DCGs), can be used to profile and predict the
health care resource consumption of population subgroups across VHA facilities. This study
examines the relationship between levels of DCG predicted risk (DPR) and resource
utilization among a sample of VA health care users.
Methods: We used VA administrative data, specifically the
outpatient, inpatient, extended care, and census files from FY97. We selected a random 1%
sample of all veterans (N=26,165) with any utilization during that period, retaining
diagnostic information assigned during "face-to-face" provider encounters and
deleting diagnoses associated with lab, x-ray and telephone stops. We divided the sample
into two patient subgroups based on the setting in which they received care: outpatient
care only (N=21,765), or those with any inpatient care (N=4,400). Patients with any
nursing home care (N=484) were separately identified as were those who received inpatient
care for substance abuse problems (N=632). The DCG model profiled the disease burden of
the population by summarizing the diagnostic information (i.e., ICD-9-CM codes) available
for each veteran during the study period and produced a risk score (DPR) to predict
utilization during the same period. We ranked patients into deciles of DPR, where the
first decile contains patients with the lowest DPR, and the 10th, those with the highest
DPR. We examined the composition of the deciles and computed the mean number of service
days (the sum of outpatient visit days and inpatient days) within each decile.
Results: Ten percent of the outpatients fell into the highest
two deciles of DPR, in contrast to 69.4% of the inpatients. Similarly 70.1% of the
outpatients fell into the lowest 6 deciles compared to only 10.1% of the inpatients. As
DPR increased, the mean service days of the outpatients increased from 3.6 to 27.6. A
similar pattern of increasing utilization with level of DPR was found for inpatients in
the highest risk deciles, with mean service days increasing from 46.5 to 65.8.
Furthermore, while only 1.8% of all patients were identified as nursing home residents,
60.5% fell into the highest DPR decile. Similarly, 95.9% of substance abuse patients fell
into the two highest risk deciles, with mean service days in the 9th and 10th deciles of
60.7 and 102.6, respectively.
Conclusions: Higher levels of predicted risk were associated
with increased levels of utilization among specific subgroups of the VA population. In
addition, inpatients and nursing home residents, who would be expected to have higher
utilization were, in fact, classified in the highest deciles.
Impact: This study validates the usefulness of the DCG
methodology in measuring the disease burden of the VA population. Reliable risk
stratification can lead to a better understanding of the factors that drive resource
consumption, an understanding which is critical in managing health care delivery.
HSR&D Funded: MPC 97-009
87. Mortality and Days of Survival for Medicare
Beneficiaries in the Fee-for-Service and HMO Systems
Matthew Maciejewski, PhD. VA Puget Sound Health Care System,
Seattle, WA.
Objectives: To compare the mortality rates and days of survival
for elderly Medicare beneficiaries enrolled in fee-for-service (FFS) health plans with
enrollees and disenrollees of health maintenance organizations (HMOs) under capitation.
Methods: Data for this study are based on 1993 and 1994 Medicare
Patient Activity Record and enrollment files, as well as county-level data on enrollment
in Medicare HMOs under capitation (TEFRA-risk HMOs) and Medicare capitation payments. The
sample of Medicare beneficiaries is based upon FFS and HMO enrollees in the 124 counties
with the greatest enrollment in TEFRA-risk HMOs. The first part of the analysis compared a
cohort of FFS and HMO enrollees, and the second part compared a cohort of FFS enrollees
and HMO disenrollees. The mortality rate for Medicare beneficiaries in the two delivery
systems was estimated using logistic regression. For beneficiaries that died between April
1, 1993 and April 1, 1994, the number of days of survival in each system was estimated
using ordinary least squares. Selection bias was partially controlled using variables for
age, gender, and institutional status. The analyses also included several county-specific
variables of interest.
Results: HMO enrollees had lower mortality rates and higher days
of survival than FFS enrollees. Conversely, HMO disenrollees had higher mortality rates
and lower days of survival than a comparable group of FFS enrollees.
Conclusions: Movement of elderly Americans into HMOs under
capitation is associated with lower mortality rates and higher survival times until death.
Although this analysis did not completely control for selection bias, this study provides
some evidence that alternative delivery systems may yield better health outcomes for
elderly veterans than conventional, FFS systems. However, some elderly beneficiaries in
poor health or likely to be in poor health may find HMOs to be incompatible with their
needs and will disenroll. These beneficiaries may be able to obtain better outcomes by
remaining in the FFS system.
Impact: The VA may be able to improve patient outcomes by
introducing new organizational structures and financial incentives applied successfully in
other settings. Greater enrollment of veterans into community-based outpatient clinics is
one such alternative delivery system that contracts with providers under capitation in
some sites. The VA may be able to capitalize on some of the lessons learned from
Medicare's experience with TEFRA-risk HMOs in its own efforts to promote veterans' health.
88. Recidivism among Veterans with Schizophrenia
Living in Board and Care: An Outcome Evaluation of the Community Residential Care Program
Alvin Mares MSPS, MSW, and J McGuire. Alhambra, CA.
Objectives: Recidivism-the repeated use of inpatient
services--among veterans diagnosed with schizophrenia is an important problem. In FY96,
veterans with schizophrenia consumed 21% of all inpatient bed days while representing only
4% of the total inpatient population. Health providers are increasingly using intensive
community-based case management interventions such as Assertive Community Treatment (ACT)
and Intensive Psychiatric Community Care to reduce the risk of recidivism. While much is
known about intensive community interventions (especially ACT), little is known of the
effectiveness of less intensive community interventions, such as the Community Residential
Care (CRC) Program, in reducing the risk of recidivism. CRC provides schizophrenic
veterans and others who live in privately operated board and care homes with monthly home
visits. The purpose of this study is to estimate the effect of CRC home visits on the risk
of recidivism among patients at West Los Angeles VAMC.
Methods: A retrospective cohort study design was used. A group
CRC patients (N=214) was followed from their first CRC home visit until 8/31/98 for first
psych/SA and med/surg admission. DHCP Patient File was queried on 9/17/98 for all patients
matching the street address or facility name of one of the 27 participating board and care
homes. A total of 321 matches were made-214 CRC patients and 107 non-CRC patients. All 214
CRC patients (52% of the total CRC patient roster) were included in the study. This method
of selecting subjects was chosen to allow for future comparisons of inpatient lengths of
stay among CRC and matched comparison subjects. Five secondary data sources were used.
DHCP Patient, Outpatient Clinic Visit, and Patient Treatment Files provided data on
socio-demographics, CRC home visits, and hospitalizations, respectively. The CRC program
database provided additional licensing data on board and care homes. Psychiatric/substance
abuse (psych/SA) and medical/surgical (med/surg) hospitalizations were defined based on
discharge ward. Twenty inpatient wards were designated psych/SA wards and forty wards as
med/surg. All domiciliary and nursing home admissions were excluded. Cox regression was
used, in concert with the Andersen Behavioral Model, to identify recidivism risk factors.
Twelve dichotomized covariates were included: visit duration, worker profession, home
size, age, marital status, race, income, service connected percentage, family support,
psychiatric diagnosis, symptoms, and alcohol/substance abuse diagnosis.
Results: Psych/SA recidivism risk factors included: home visit
duration fewer than four years (RR=2.86, p=.0002), minority status (RR=1.94, p=.0273), and
schizophrenia diagnosis (RR=1.79, p=.1056). Med/surg risk factors included: home visit
duration fewer than four years and med/surg (RR=3.88, p=.0055), residence in a facility
having 80+ beds (RR=1.97, p=.1103), and limited family contact (RR=1.82, p=.1126).
Conclusions: Minority status, schizophrenia diagnosis, and
shorter time receiving CRC home visits were associated with increased psych/SA recidivism.
Living in a larger board and care, having limited social contact with family, and shorter
time receiving CRC home visits were associated with increased med/surg recidivism.
Impact: Additional efforts may be warranted to reduce recidivism
among minority, those with schizophrenia, residents of larger facilities, those isolated
from family, and recently enrolled CRC patients.
89. Patterns of Medical Treatment for Congestive
Heart Failure (CHF) in a Veteran Population
JL Meier, PharmD. VANC Health Care System, Martinez, CA. JR
Lopez, RM Moskowitz, and D Siegel
Objectives: Evidence of the beneficial effect of angiotensin
converting enzyme (ACE) inhibitors in reducing morbidity and mortality in patients with
CHF has accumulated over the past decade. Although ACE inhibitor use in patients with CHF
has increased, only 36% of patients studied by Smith et al (Arch Int Med, 1998) in
1994-1995 received treatment with ACE inhibitors. Hydralazine and isosorbide dinitrate in
combination also reduce morbidity and mortality in patients with CHF, and angiotensin II
antagonists are being studied for this purpose. To determine the extent of ACE inhibitor
and other medication use in patients with CHF in the VA Northern California Health Care
System (VANCHCS).
Methods: ICD-9 codes from patient encounter forms identified
patients with CHF in the VANCHCS database between 4/1/97 and 3/31/98. Researchers related
this data to prescriptions for drugs categorized in the VA Cardiovascular Series,
including ACE inhibitors, angiotensin II antagonists, hydralazine, isosorbide dinitrate,
nitroglycerin patches, digoxin, loop diuretics, hydrochlorothiazide, and potassium-sparing
diuretics filled over a six month period (1/1/98 to 6/30/98) using Access=99 and Excel=99.
Results: Of 1518 patients with CHF, the percentage receiving a
drug included: diuretic (78%), ACE inhibitor (63%), digoxin (50%), nitrate (34%)
angiotensin II antagonist (10%), and hydralazine (5%). Seventy-four patients 5%) received
prescriptions for both hydralazine and a nitrate, and 840 (55%) received a diuretic and an
ACE inhibitor. Thirty-two percent of patients received a combination of a diuretic,
digoxin, and either an ACE inhibitor or an angiotensin II antagonist.
Conclusions: ACE inhibitor use in this analysis is higher than
published data from other populations that have been studied. Greater use of ACE
inhibitors or hydralazine with nitrates may further improve patient outcomes.
Impact: A higher proportion of patients with CHF are treated
with ACE inhibitors at VANCHCS. However, there is potential to further increase use and
improve CHF management.
90. Comparison of Health Care Use and Outcomes for
HIV-Infected Patients in VA Versus Non-VA Settings
Terri Menke, PhD, Linda Rabeneck, MD, MPH, and Nelda Wray, MD,
MPH. Houston, VA Medical Center, Houston, TX.
Objectives: To compare VA and non-VA health care utilization and
outcomes for HIV-infected patients.
Methods: For VA users, we collected data on both VA and non-VA
health care obtained during 1994 for 470 patients at five VAMCs: New York, Miami, Houston,
Los Angeles, and San Francisco. Data on VA health care came from VAÆs HIV Registry, which
electronically extracts data on all HIV-infected patients from VISTA. Information on the
sampled patientsÆ use of non-VA health care and patient characteristics was obtained from
patient interviews. We used the questionnaire from the AIDS Costs and Service Utilization
Survey (ACSUS), a study of non-VA HIV-infected patients conducted by the Agency for Health
Care Policy and Research. The ACSUS study provided the non-VA sample with which our VA
sample was compared in terms of utilization and outcomes. We estimated regression
equations for seventeen utilization measures. We used logistic regression to estimate the
probabilities of any use for hospitalizations, physician visits, emergency department
visits, nursing home stays, mental health visits, substance abuse visits, home health
visits, dental visits, and anti-retroviral medication. We used Poisson regression to
estimate equations among users of each type of health care for the amount of use (e.g.,
number of hospitalizations among those with inpatient stays). We used linear regression to
estimate an equation for inpatient length of stay in logarithm form. The covariates
included measures of HIV illness severity, age, ethnicity, HIV transmission route,
education, social support, health insurance, employment status, income, health status,
physical function, role function, social function, and mental function. Dummy variables
were used to estimate differences in use among three patient categories, controlling for
the covariates: (1) VA only users; (2) dual VA and non-VA users; and (3) only non-VA. We
used Cox proportional hazards modeling to compare progression from early to late stage HIV
disease or death among the three patient groups.
Results: There were no significant differences among VA-only,
dual VA and non-VA, and non-VA only users in the use of inpatient hospital or nursing home
care, or in the number of physician, emergency, mental health, substance abuse, or home
health visits among users. Dual VA and non-VA users had higher probabilities of physician,
mental health, substance abuse, and dental visits than the other patient groups. Compared
to those who only used non-VA care, both dual users and VA-only users had lower
probabilities of emergency department visits and anti-retroviral medication use, but
obtained more dental visits per user. VA-only users had a lower probability of home health
use than the other patient groups.
Conclusions: Depending on the type of health care, HIV-infected
patients in VA obtained the same or less care compared to patients in non-VA settings.
Outcomes were the same for VA and non-VA patients. These results imply that VA care for
HIV-infected patients is more efficient than non-VA care.
Impact: In this era when VA must compete with non-VA settings in
terms of providing cost-effective care, this study demonstrates that VA is more efficient
at least for HIV-infected patients.
HSR&D Funded: IIR 95.107
91. Developing Algorithms to Define Episodes of
Care
Terri Menke PhD, Nelda Wray MD, MPH, Carol Ashton MD, MPH, and
Linda Rabeneck MD, MPH. Houston VA Medical Center, Houston, TX.
Objectives: To define episodes of care that include
hospitalizations, including the time frames pre and post-hospitalization, and the health
care to be included.
Methods: An expert panel of physicians selected high-volume
diagnoses or surgical procedures to examine, and developed criteria for defining episodes
of care. Among the conditions selected were: coronary artery bypass, colon cancer
procedures, total hip replacement, bleeding ulcer, and congestive heart failure. For each
condition selected, computer printouts using VA administrative data from FY1997 were
generated of the frequency of: (1) visits by clinic stop, by month, from 6 months prior to
admission to 6 months following discharge; (2) outpatient tests and procedures by CPT code
for relevant organ systems, by month, from 6 months prior to admission to 6 months
following discharge; (3) readmissions by ICD-9 code of the primary diagnosis, by week, up
to 6 months following discharge from the index hospitalization; and (4) nursing home
stays, by week, up to 6 months following discharge. The expert panel used their clinical
knowledge and the computer printouts to determine how long prior to the hospitalization
the episode began, how long after discharge the episode ended, and which specific clinic
stops, tests, readmissions, and nursing home stays should be included in the episode.
Results: Episodes of care for surgical hospitalizations took the
following general form. Episodes of care for medical diagnoses were defined analogously.
(1) Pre-admission care: (a) started 90 days prior to admission for most surgeries; (b)
included visits to principal medicine clinics, relevant medical specialty and surgery
clinics, nursing, relevant behavioral counseling, and clinics designated as pre-operative;
and (c) included outpatient tests or procedures specific to the evaluation of the extent
or indication for surgery. (2) Post-discharge outpatient care: (a) included visits to
principal medicine or nursing clinics within 4-6 weeks after discharge, depending on the
surgery; and (b) included visits to all other clinics specified in (1) and relevant
rehabilitation visits up to 6 months following discharge. (3) Readmissions: (a) were all
included up to 1-6 weeks after discharge, depending on the surgery; (b) were included in
the episode based on containing a relevant surgical procedure or primary diagnosis if they
occurred between the time specified in (a) and 6 months after discharge. (4) Nursing home
stays were included if they immediately followed the initial hospitalization, or a
readmission that was included in the episode.
Conclusions: A process combining clinical knowledge and relevant
data was developed for defining episodes of care that include a hospitalization. The
algorithms developed can be applied by managers or researchers who want to examine the
costs, efficiency, or outcomes for episodes of care.
Impact: Current organizational features of health care have
shifted the focus of quality and efficiency evaluation from the health care event (e.g.
hospitalization) to the entire package of services required to treat an episode of
illness. This shift is evident in VAÆs adoption of the VERA system, which allocates
funding to VISNs on a capitated basis.
HSR&D Funded: IIR 95-139
92. Designing Guidelines for Successful
Dissemination and Implementation: The California Guidelines for Alzheimer's Disease
Management
Brian Mittman, MD. VA Greater Los Angeles Health Care
System, Sepulveda, CA. Saliba, DA Lang, and BG Vickrey.
Objectives: Efforts to improve the quality and outcomes of
healthcare through clinical practice guidelines have generally been disappointing: while
hundreds of guidelines are developed and disseminated yearly, studies continue to show low
levels of guideline use and minimal impact on clinical practice. The Executive Committee
of the California Workgroup on Guidelines for Alzheimer's Disease Management in Primary
Care (a broad public-private coalition including VHA representatives) sought to avoid this
problem by commissioning the Sepulveda Field Program to form a guideline
dissemination/implementation team. Our overall goal was to enhance acceptance and impact
of the guideline, which was then still under development. We sought to accomplish this
goal by (1) collaborating with the guideline development Workgroup to ensure that the
guideline's content, format and other characteristics reflected current thinking regarding
attributes facilitating guideline use and acceptance, and by (2) developing a
comprehensive dissemination and implementation plan containing recommendations for the
Executive Committee and for provider organizations scheduled to receive the guideline.
Methods: Our efforts to influence guideline content and format
began with presentations at Workgroup and subcommittee meetings regarding dissemination
and implementation challenges and solutions. We presented results of published research
and reviews, and detailed examples from our own work. We illustrated our recommendations
by revising specific guideline sections and by drafting recommended additions (e.g.,
purpose and scope statements). Our content/format recommendations addressed language
(e.g., clear, declarative recommendation statements rather than unstructured text or
broad, ambiguous statements), overall guideline structure (e.g., development of one-page
recommendation list and accompanying narrative summarizing relevant evidence) and other
issues. Our dissemination/implementation report included a brief analysis of the
guideline's features relevant to implementation success and strategies, assessment of the
guideline's likely impact on quality, cost and other outcomes, and detailed
recommendations for dissemination and implementation activities, accompanied by reviews of
relevant literature and other evidence. We addressed (1) guideline development (e.g.,
recruitment of key stakeholder groups as collaborators in guideline development, to ensure
buy-in and subsequent dissemination support), (2) publicity (collaborative press
conferences and guideline release activities), (3) publication (preparation of a
manuscript for journal publication in conjunction with the stand-alone guideline document,
preparation of summaries for inclusion in guideline directories and compilations), (4)
guideline tools (e.g., medical record checklists, patient brochures), (5) implementation
support packages (sample educational program outlines and resources, detailed plans for
provider organization implementation projects), and (6) funding strategies
(recommendations regarding private foundations, for-profit industry organizations such as
pharmaceutical companies, and government agencies).
Results: The guideline development Workgroup, subcommittees and
Executive Committee accepted nearly all of the dissemination/implementation team's
recommendations regarding guideline content and format, and is currently implementing many
of the dissemination/implementation report's recommendations.
Conclusions: Guideline dissemination and implementation remain
key challenges to success of clinical practice guidelines as quality improvement tools.
Attending to these challenges during the development of a guideline, rather than after its
release, should help meet many of these challenges.
Impact: Development of the guideline was enhanced by the
emphasis placed on dissemination and implementation needs and the resulting awareness and
attention the guideline development Workgroup devoted to implementation barriers and
challenges. Acceptance and use of the guideline are likely to be enhanced as well.
93. Health and Functional Status Differences
Between Veterans Admitted to State Veterans Homes Compared to Community Nursing Homes
Joan Penrod, MSW, PhD. University of Nebraska Medical
Center, Omaha, NE. M Vandivort, L Zhao, D Shutzer, and J Potter.
Objectives: To examine factors associated with admission of
veterans to state veterans homes (SVHs) compared to community nursing homes (CNHs) in
Nebraska.
Methods: The Minimum Data Set (MDS) was obtained for veterans
admitted to SVHs and CNHs in Nebraska over a 12 month period. Demographic, health, and
functional status differences in the two admission cohorts were examined. Multiple
logistic regression was used to estimate the effects of admission functional and cognitive
status, age, gender, social support, marital status, presence of behavior, mental health,
and incontinence problems, and number of medications used on the probability of admission
to a SVH versus a CNH.
Results: Veterans admitted to Nebraska SVHs (N = 188) are
significantly less functionally impaired at admission (p= .003) compared to those admitted
to CNHs (N = 126). However, a history of mental problems (p< .001) and use of
anti-psychotic medication (p = .001) is more prevalent in the SVH admission cohort.
Moreover, the results of the multiple logistic regression indicate as functionally
disability increases, veterans' odds of admission to a SVH as compared to a CNH decrease
(p = .01). Also, veterans with cognitive impairment and mental health problems are more
likely to be admitted to a SVH rather than a CNH. Finally, veterans living alone, admitted
from home rather than a hospital or nursing home, and those with daily contact with family
are less likely to enter a SVH compared to a CNH. Age, gender, incontinence, and marital
status had no effect of the odds of admission to SVHs.
Conclusions: The SVHs in Nebraska appear to admit from a
different population of veterans than the CNHs. In particular, SVHs are more likely to
accept veteran residents with mental health problems compared to the CNHs. However,
Nebraska SVHs attract a less functionally disabled admission cohort. Nebraska SVHs have a
policy of not accepting ventilator dependent residents. This may account for part of the
higher level of functional disability in the CNH veteran cohort. Furthermore many CNHs are
reluctant to take residents with significant mental health problems and by rule, can not
accept applicants if a psychiatric illness is the primary diagnosis at admission. Thus,
the SVHs may serve veterans who would otherwise have difficulty with traditional
institutional long-term care arrangements.
Impact: Reorganization, consolidation, and closer management of
VA nursing home resources is a major focus at the Federal, VA Network, and State level.
This study provides relevant information to assist in that effort. Specifically, moves to
reduce reliance on SVHs will need to consider alternative care arrangement for veterans
with mental health problems.
HSR&D Funded: DEV 97-019
94. Access to Care Among Adults with Diabetes in VA
and County Clinics
John Piette, PhD, Center for health Care Evaluation, Menlo
Park, CA.
Objectives: In a prior study, we found that VA patients with
diabetes were substantially more satisfied with their access to care than similar patients
in a nearby county health care system. In this study, we sought to determine the actual
prevalence of access problems perceived by patients in the two systems.
Methods: Data were collected via structured telephone surveys of
patients participating in two randomized trials of automated diabetes management with
nurse follow-up. Participants in the trials were recruited at the time of visits to
general medicine clinics in each health system. Data for the current study were from
follow-up surveys for 108 patients recruited through 4 VA clinics and 132 patients
recruited through 2 county clinics who all were randomized to the control groups.
Results: Compared to county patients, VA patients were older,
more likely to be married, and had better glucose control. In the six months prior to
their surveys, between 9% and 10% of county patients reported that they failed to refill a
prescription, seek care for an urgent health problem, or call an ambulance because of cost
concerns. However, less than 2% of VA patients perceived similar barriers (each p
<.01). Compared to county patients, fewer VA patients failed to seek medical advice by
phone because they did not know the number or thought that they would be put on hold (14%
versus 23%, respectively; p = .07). Fewer VA patients failed to seek urgent care because
they thought that the clinic would not be helpful (2% versus 11%; p < .01). Roughly
equal numbers of patients in both systems failed to refill a prescription because they
"didn't know how" (13% for VA patients and 11% for county patients, p = .66).
None of these differences were substantially changed when we adjusted for sociodemographic
factors that could affect perceived access (e.g., social support, education, and age).
Conclusions: Overall, the proportion of VA patients with
diabetes who perceived financial barriers to accessing medical care was small on an
absolute level and relative to county clinic patients. Relative to county patients, VA
patients perceived the system's telephone services and emergency care services as more
accessible. Nevertheless, a significant minority of VA patients perceived problems
accessing telephone care services and medication refills.
Impact: VA policy-makers can be assured that few patients with
diabetes perceive financial barriers to receiving care. The problems reported by county
patients suggest that VA patients' perceptions might be worsened if they faced significant
co-payments. VA should focus on improving the perceived accessibility of telephone care
and medication refills.
HSR&D Funded: IIR 95-084
95. Ambulatory Care Groups and SF-36 Mental and
Phusical Component Summary Scores
Kenneth Pietz, PhD, and Carol Ashton, MD. MPH. Houston VA
Medical Center, Houston, TX. J Tuchschmidt, G Twedt, and J Bellah. Nelda Wray,
MD, MPH. Houston VA Medical Center, Houston, TX.
Objectives: Determine the relationship between Adjusted Clinical
Groups (ACGs) and SF-36 physical and mental component summary scores. Determine whether
these SF-36 summary scores can be used as case-mix adjustment variables in resource
utilization studies, as proxy for patients' frailty and illness burden. Determine how
much of the variation in per-patient resource utilization is explained by the SF-36
summary scores.
Methods: The data consists of 24,726 patients in the Northwest
Network (VISN 20) who voluntarily completed an SF-36, who had inpatient or outpatient care
during the study period from September 1, 1997 to August 31, 1998 and who had a primary
care provider assigned. The amount of utilization of each of nine resources for the study
period was known for each patient. The resources were: bed days of care, hospital stays,
medical encounters, laboratory tests and cost, radiology tests and cost, prescriptions,
and pharmacy cost. The ACG of each patient was computed using he/her demographic
information and inpatient and outpatient ICD-9 codes. A significant amount of the
variation in patients' resource utilization is explained by the patient's ACG.
For each patient the Kazis physical and mental component summary scores (PCS and MCS,
respectively) were calculated from their SF-36 health self-assessment. The PCS ranged from
a minimum of 3.1 to a maximum of 70.6. The mean and standard deviation were 33.4 and 11.4,
respectively. The MCS ranged from a minimum of 3.8 to a maximum of 78.9. The mean and
standard deviation were 44.8 and 13.9, respectively. The effect of using PCS and MCS to
explain variation in resource usage was evaluated. Also, these scores were added as
independent variables to the regression models which model resource utilization as a
function of the patient's ACG. Finally, regression models were generated which
evaluated the ability of the ACGs to explain variation in PCS and MCS.
Findings: The amount of variation in the resource utilization
explained by the PCS and MCS was highest for prescriptions. The amounts of variation
explained in the logarithms of prescriptions and pharmacy cost explained by PCS and MCS
combined were 12.3% and 8.9% respectively, compared with 27.4% and 19.7% explained by
ACGs. For the other resources the amount of variation explained by the PCS and MCS was
less than 7%. The change in $-squared by adding the summary scores to the ACG models of
resource utilization was negligible except for prescriptions and pharmacy costs. Finally,
ACGs explain 8.1% of the variation in PCS and 5.5% of the variation in MCS.
Conclusions: The PCS and MCS summary scores add to the ability
of ACGs to predict prescriptions and pharmacy cost in this population of veterans. PCS and
MCS add little predictive ability to ACGs for the other utilization outcomes. The summary
scores cannot replace ACGs as case-mix adjustment covariates.
Impact: SF-36 physical and mental component summary scores are
not usable as case-mix adjustment covariates as a proxy for frailty and illness burden in
a population of veteran patients.
96. Development of a Case Mix Adjustment Model for
Hemoglobin A1c
Leonard Pogach, MD. Houston VA Medical Center, Houston, TX. QW
Zhang, S Dhar, H Cheng, G Hawley,and D Repke.
Objectives: The current VA health outcome performance
measure for glycemic control, the proportion of veterans exceeding an unadjusted
glycohemoglobin of 10 percent, was chosen because of the absence of laboratory
standardization and case mix adjustment. The objective of this study was to validate a
case mix model that would permit accurate cross sectional comparisons of mean Hemoglobin
A1c (HbA1c) values among administrative units.
Methods: A cohort of 53,343 patients with documented HbA1c
values was identified from a larger cohort of 203,987 veterans receiving oral agents,
insulin and/or blood glucose monitoring supplies from 130 participating stations in the
FY1996 National Center for Cost Containment Diabetes Cost and Outcomes Report using a
previously validated data extraction program based upon the DHCP pharmacy file. A
hierarchical, mixed effects models was utilized that employed a nested data structure to
estimate random variance and covariance components among dependent measures to increase
the model's explanatory value. High-normal adjusted HbA1c levels (subtracting the upper
normative limit from each individual value) were predicted by linear age (centered at the
median of 66 years), quadratic age, gender, race/ethnicity, patient's financial means
classification (temporary surrogate of SES), treatment modality (insulin, oral agents,
insulin and oral agents, and neither insulin nor oral agents), blood glucose monitoring
(yes/no), total number of VA clinic visits (natural log transformed), and the interactions
of demographic variables with treatment modality and blood glucose monitoring. The last
HbA1c record was utilized. Fixed parameter estimates (beta) were determined for each
predictor.
Results: The intercept for the cohort mean adjusted HbA1c was
1.93 [percent above high normal value]. No difference in HbA1c level was found between
gender groups or individuals receiving monitoring supplies. HgbA1c level was higher in
younger than in older patients. Compared to those who used oral medications only, patients
treated by insulin had higher HgbA1c results (beta=.546, p=.0001), while those treated
with both insulin and oral agents during FY96 had even higher HgbA1c (beta=.96, p=.0001)
while patients receiving only monitoring supplies showed a lower level of HgbA1c
(beta=-1.068, p=.0001). There was a complex interaction between ethnicity and treatment
modality, and Black Hispanic/African American patients had higher HgbA1c (beta=0.28,
p=0.0001) than White patients for those who received oral or oral plus insulin therapy.
The number of outpatient visits to a VA clinic was associated with a significantly lower
level of HgbA1c (beta=.115, p=.0001). The predictor betas were almost identical whether
adjusted or unadjusted means or threshold proportions were utilized. However, the modality
of reporting HbA1c results determined which facilities were classified as outliers from
the national means. After adjusting for the upper limit of the normative ranges, a
significant (p<0.05) difference in mean adjusted HbA1c occurred in 26 of 48
participating facilities.
Conclusions: Age, ethnicity, treatment modality and clinic
visits, but not gender, socioeconomic status or blood glucose monitoring were
statistically significant predictors of HbA1c values.
Impact: Future diabetes performance measures for HbA1c could
utilize case mix adjustment to compare mean HbA1c values of populations as well as
proportions of individuals exceeding a threshold measure.
97. Extending the Use of the Self-Administered
Quality of Well-Being to Patients with Depression
Jeff Pyne, MD. North Little Rock VA Medical Center, North
Little Rock, AR. WJ Sieber, K David, and DK Williams
Objective: We examined the sensitivity of the
self-administered Quality of Well-Being (QWB-SA) Scale to changing levels of depression
severity. The original QWB Scale was designed as a generic measure for use in
cost-effectiveness analyses and provided the recommended health policy effectiveness unit
of quality-adjusted life years (QALYs). The QWB-SA was developed in response to concerns
that the original interviewer version of the QWB took too long and was too costly to
administer. The QWB-SA takes approximately 7 minutes to complete, has been used to
estimate QALYs in migraine and arthritic patients, and has well-established validity and
reliability.
Methods: A total of 67 subjects participated in the study: 51
male (39 inpatient and 12 outpatient) and 16 female (7 inpatient and 9 outpatient). All
subjects were diagnosed with a current major depressive episode using the Structured
Clinical Interview for DSM-IV and were simultaneously administered the QWB-SA, the
interview version of the QWB Scale, 17-item Hamilton Rating Scale for Depression (HRSD),
and Beck Depression Inventory (BDI). The output from both QWB scales is a single score
between 0.0 (death) and 1.0 (perfect health). The study design was observational. Acute
treatment response was determined using weekly QWB and depression ratings during 4 weeks
of medication treatment or until criteria for a 50% improvement from baseline HRSD was met
(defined as the mean HRSD score from weeks 1 and 2), and longer term response was
determined at 4-months post-treatment.
Results: There were no differences found between male and female
subjects on any measure and therefore the data were combined for all reported analyses. To
place the QWB-SA scores in context, the reported mean score (SD) for migraineurs without
headache was .619 (.15), with headache .484 (.15); patients with rheumatoid arthritis .509
(.14); in the current sample depressed outpatients .479 (.12), inpatients .382 (.12).
Baseline correlations between QWB-SA, HRSD and BDI were -.38 (p<.01) and -.30
(p<.05), respectively. Acute change score correlations between QWB-SA, HRSD and BDI
were both -.27 (p<.05). Four month change score correlations between QWB-SA, HRSD and
BDI were -.51 (p<.01) and -.57 (p<.01), respectively. Interviewer QWB change score
correlations with HRSD and BDI were non-significant for acute treatment response and less
robust for the 4-month response.
Conclusions: The QWB-SA scores for depressed subjects were
similar or lower than QWB-SA scores for other chronic disorders, namely migraine and
rheumatoid arthritis patients. The baseline QWB-SA correlation with depression severity is
significant and consistent with a medium effect size. The acute and 4-months
post-treatment change score correlations are significant and consistent with a medium and
large effect size, respectively. The QWB-SA appears to be more sensitive to acute change
in depression severity than the interviewer QWB.
Impacts: The QWB-SA is an inexpensive and low staff impact
method for documenting the cost-effectiveness of medical interventions and for comparing
the cost per QALY across specialties. The QWB-SA may be a valuable measure to inform
healthcare resource allocation decisions.
98. The Relationship between Functional Status and
Satisfaction of Care among Patients Served by the Veterans Health Administration
Xinhua Ren, PhD and Lewis Kazis, ScD. Bedford VA Medical
Center, Bedford, MA. A Lee and W Rogers. Susan Pendergrass, DPH. Department
of Veterans Affairs, Ridgeland, MS.
Objectives: As the Veterans Health Administration (VHA) places
high priority on quality of care, comprehensive frameworks for quality accountability have
been established to manage performance within the VHA. To address this accountability,
there is an increasing need for the VHA to assess the outcomes of health care. In this
presentation, we assess the relationship between two domains of VHA health care value,
patient satisfaction of care and functional status, in the context of sociodemographic
characteristics such as age, gender, race, marital status, educational attainment, and
periods of service (WWII, Korea, Vietnam, and Persian Gulf).
Methods: We analyzed both the cross-sectional data from the 1996
National Survey of VA Ambulatory Care Patients and the cohort data from the 1998 National
Survey of VA Ambulatory Care Patients. The 1996 Survey included 32,631 patients, among
whom 26,424 patients were followed in the 1998 Survey. Participants in the study were
mailed a health status (the SF-36V) and a Customer Service Standards (or patient
satisfaction) questionnaire. Using the cross-sectional data, we first conducted Pearson's
product moment correlations to examine the relationship between functional status and
patient satisfaction. Then using ordinary least squares regression (OLS), we examined the
effects of sociodemographics (such as age, gender, race, marital status,, education, and
periods of service) and functional status on domains of patient satisfaction. Using the
cohort data, we conducted "cross correlations" between patient satisfaction and
functional status in wave 1 (1996 Survey) and patient satisfaction and functional status
in wave 2 (1998 Survey) to examine the causal relationship between functional status and
patient satisfaction.
Results: In the cross-sectional data analysis, the SF-36V scales
had significant, negative correlation coefficients with the satisfaction scales (p <
0.001), indicating that patients with better functional status were less likely to be
dissatisfied with the care they received within the VHA. Furthermore, compared to physical
health (or PCS), mental health (or MCS) seemed to be more strongly correlated with patient
satisfaction. Patients who were older, white, married, and more educated had significant,
negative regression coefficients on satisfaction scales (p < 0.01), indicating that
those patients were less likely to be dissatisfied with the care they received within the
VHA. In the cohort data analysis, the relationship between physical (PCS) or mental (MCS)
health and domains of patient satisfaction was rather stable over time; however, the
effect of PCS or MCS on patient satisfaction seemed to be more important than that of
patient satisfaction on PCS or MCS.
Conclusions: The study results suggest that after adjusting for
sociodemographics such as age, gender, race, marital status, education, and periods of
service, patients with poorer functional status are more likely to be dissatisfied with
the care they received from the VHA than patients with better functional status.
Impact: Results have implications for the use of the SF-36V as
an important adjuster in future work. The physical and mental component summary scales
from the SF-36V are both correlated with the satisfaction scales, suggesting that
comparisons across VISNs should consider both unadjusted and adjusted satisfaction scale
scores.
99. VISN 10 Automated ICU Severity Adjustment Tool:
SISVISTA
Marta Render MD. Cincinnati VA Medical Center, Cincinnati,
OH. SH Timmons, R Hayward, D Welsh. Timothy Hofer, MD, MSc. Ann Arbor VA
Medical Center, Ann Arbor, MI.
Objective: Proprietary intensive care unit (ICU) risk adjustment
tools are costly. We developed an automated ICU risk adjustment tool using only those
variables from APACHE III found in the computerized database of the Department of Veterans
Affairs (VistA).
Methods: We included the first admission of each patient to any
intensive care unit in three Ohio Veterans Affairs hospitals from 2/1/98 through 7/31/97.
Customized programming in the VistA database at each facility identified eligible patients
and extracted relevant variables: diagnosis, age, comorbidity, admission source (direct or
transfer) and a modified Acute Physiology score, hematocrit, white blood count, albumin,
sodium, glucose, bilirubin, blood urea nitrogen, creatinine, partial pressure of
oxygen/fraction of inspired oxygen, partial pressure of carbon dioxide and pH. A window
surrounding admission (+ 24 hours) identified variables and applied APACHE III
weights. Direct admissions were those patients admitted to the ICU from the emergency area
or transferred to the ICU within 1 day of surgery; all others were considered transfers.
APACHE III comorbid diagnoses were defined using ICD.9.CM coding from the inpatient
treatment file (PTF). The ICD.9.CM ICU discharge code from the PTF file was sorted first
into APACHE III diagnostic groups, then into 10 groups of organ system dysfunction.
Statistics: Odds ratios for predictor variables, summary
statistics including the C statistic, and goodness of fit testing are reported for the
logistic regression model predicting 30 day mortality.
Results: 4626 of 4851 patients (99.5% of the cohort, 477 deaths)
had complete datasets. Of the 4626 patients, 1389 were classified as post-operative (30%).
Patients were 63 + 12 years and predominantly male (97.5%). 74% of patients were
directly admitted to ICU from the emergency area, and 26% were transferred into the ICU.
Mortality was increased in patients transferring to the unit (21%) compared to those
directly admitted (6.5%, p = 0.001); and increased as the length of time from hospital
admission to ICU transfer increased (mortality at 1 day 15.6%, at 2-4 days 19%, and at
> 4 days 25.2%, p = 0.002). The most common diagnoses were cardiovascular diseases (MI,
CHF). In multivariable analysis, age score (OR [95%C1] = 1.05 [1.02, 1.07]), some
diagnostic systems (Hematology, neurology, orthopedics, respiratory, sepsis and trauma, p<0.05),
comorbidity score (OR [95%C1]=1.11[1.08, 1.1]), direct admission (OR [95%C1]-0.4[0.3,
0.5]), and the sum of the laboratory scores (OR [95%C1]=1.07[1.06,1.08]) were significant.
The model had excellent discrimination and calibration (C statistic = 0.85, Hosmer
Lemeshow, p = 0.07).
Conclusion: This relatively economical automated ICU risk
adjustment system has discrimination similar to existing risk adjustment systems (APACHE
II, SAPS II).
Impact: An automated risk adjustment system has broad potential
administrative and research applications in the VHA locally, regionally and nationally,
and in community health care systems with advanced information systems. These results are
being validated in a national database.
HSR&D Funded: DEV 97-032
100. Psychogeriatric Interventions Saves Inpatient
Costs: Preliminary Findings
Joel Rosansky, LCSW, R Anderson, R Bastani, R Gould, D Huang, L
F Jarvik, G Kominsk, A E Maxwell, J Sanchez, and S Taylor, UPBEAT Program Staff. VA
Greater Los Angeles Healthcare System, Los Angeles, CA.
Objectives: The Unified Psychogeriatric Biopsychosocial
Evaluation and Treatment (UPBEAT) Program is a multi-center, interdisciplinary,
randomized, six year outcome-based clinical demonstration project sponsored by the
Department of Veterans Affairs to improve health care and reduce utilization by geriatric
veterans. Specifically, UPBEAT Care is expected to reduce inpatient utilization and
unscheduled hospital visits, and increase consumer satisfaction.
Methods: UPBEAT staff at each of the nine participating VA
Medical Centers use the Veterans Health Information System and Technology Architecture
(VISTA) to identify patients 60 years or older, admitted to acute medical/surgical
inpatient services. Patients are invited to participate in the program evaluation unless
they meet exclusion criteria. Exclusion criteria include: psychiatric appointments during
the preceding or subsequent 6 months, diagnosed with Post Traumatic Stress Disorder,
psychosis, dementia or other cognitive impairment, spinal cord injury, rehabilitation
plan, outside catchment area, homeless, admission from nursing home, chemotherapy, hospice
care, or previous assignment to UPBEAT or Usual Care. Eligible patients providing informed
consent are interviewed at bedside with the anxiety and depression subscales from the
Mental Health Index (MHI-38), the Alcohol Use Disorder Identification Test (AUDIT) and the
RAND 36-item Health Survey Short Form (SF-36) for patients meeting cutoff scores for
anxiety, depression, or alcohol misuse symptomatology. Qualified patients are randomized
to UPBEAT or Usual Care. UPBEAT Care patients receive in-depth diagnostic assessments,
including the following scales: Geriatric Depression, Hamilton Anxiety and Depression,
Lubben, Affect Balance, Activities of Daily Living, Cumulative Illness Rating, Mini-Mental
State Examination, Multi-Axial Diagnostic Assessment. Each UPBEAT Care patient is assigned
to an UPBEAT Care Coordinator from an interdisciplinary team. UPBEAT Care teams, with
expertise in psychogeriatrics, are staffed from psychiatry, nursing, social work, and at
some sites psychology. Based on the diagnostic assessment, UPBEAT Care Coordinators
provide patients with referrals to community and hospital services, or if necessary,
direct interventions utilizing educational, psychosocial, psychotherapeutic or
psychopharmacologic approaches. Outcome evaluation includes follow-up interviews of both
UPBEAT and Usual Care patients at 6, 12 and 24 months after enrollment. In addition,
utilization and cost data are obtained for both groups from VHA databases.
Results: Based on preliminary data from the Allocation Resource
Center for 420 UPBEAT Care and 462 Usual Care patients, the net changes in inpatient
utilization between 12 months pre- and 12 months post-enrollment yielded a first-year
savings of 5.4 inpatient days/patient for UPBEAT Care over Usual Care. This resulted in a
savings of over $2,184,000 based on the Cost Distribution Report average inpatient cost of
$963/day.
Conclusions: The UPBEAT Program, i.e. skilled clinical
assessment with identification of symptoms of depression, anxiety and alcohol misuse
followed by community-based mental health care management by an interdisciplinary team
with expertise in psychogeriatrics, resulted in reduced inpatient utilization and thereby,
cost savings.
Impact: UPBEAT is expected to demonstrate that skilled clinical
assessment and community-based mental health care coordination (primary and secondary
mental health and other health care intervention and prevention) by an interdisciplinary
team with expertise in psychogeriatrics can yield enhanced delivery of integrated health
care and decreased utilization of expensive acute inpatient services (medical/surgical/
psychiatric).
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