ISSUES IN PEDIATRIC IMMUNIZATION

Effect of Method of Defining the Active Patient Population on Measured Immunization Rates in Predominantly Medicaid and Non-Medicaid
Practices
Ardythe L. Morrow, PhD*; R. Clinton Crews, MPH*; Henry J. Carretta, MPH*; Mekibib Altaye, PhD*; Albert B. Finch, MD‡; and Jeffrey S. Sinn, PhD*

Abstract. Objective. To examine the effect of patient selection criteria on immunization practice assessment outcomes.
Methods. In 3 high- (50%–85%) and 7 low- (<25%) Medicaid pediatric practices in urban eastern Virginia, we assessed immunization rates of children 12 and 24 months old comparing the standard criteria (charts in the active files excluding those that documented the child moved or went elsewhere) with 3 alternative cri- teria for selecting active patients: 1) follow-up: the chart contained a complete immunization record or the pa- tient was found to be active in the practice through follow-up contact by phone or mail; 2) seen in the past year: the chart indicated that the patient was seen in the practice in the past year; 3) consecutive: patients that were seen consecutively for any reason.
Results. Of the 1823 charts assessed in the high- and low-Medicaid practices, follow-up identified 61% and 83% as active patients; 78% and 95% were ever seen in the past year. At 24 months, mean practice immuniza- tion rates were lower for standard (70%) than all 3 alternative criteria (78%–86%). Immunization rate dif- ferences between standard and alternative criteria were greater in high- (17%–23%) than low-Medicaid practices (5%–13%).
Conclusion. The standard for practice assessment should be based on a consistent definition of active patients as the immunization rate denominator. Pediatrics 2000;106:171–176; immunization assess- ment, quality of pediatric care, methodologic research, Medicaid, assessment of preventive services.

ABBREVIATIONS. CDC, Centers for Disease Control and Pre- vention; PROS, Pediatric Research in Office Settings (network); UTD, up-to-date; DTP, diphtheria-tetanus-whole cell or acellu- lar pertussis vaccine; MMR, measles-mumps-rubella vaccine; Hib, Haemophilus influenzae type b vaccine; CASA, Clinic As- sessment Software Application.
The immunization status of children ,2 years old remains a leading indicator of quality of care.1–5 Routine assessment of immunization rates is a national standard for pediatric practice,4 and results in increased practice immunization rates.6–8 The national standard for immunization practice assessment, established by the Centers for Disease Control and Prevention (CDC), involves ran- dom or systematic selection of the records of age- eligible children documented as having at least 1 visit to the practice, which is operationalized in different states either as 1 medical or immunization visit or as 1 well-child or immunization visit.9 Charts are ex- cluded if they contain adequate documentation that the patient has moved or gone elsewhere for care.9,10 However, this standard is being reevaluated to pro- mote widespread adoption of immunization practice assessment in the private sector.7,8,11,12 A key issue in immunization assessment methodology is defining the patient population for which the private pediatric provider is responsible, and the appropriate selection of charts for assessment. The ideal target population to include in practice assessment may be patients who are active in the practice as defined by the parent or guardian, but this definition is difficult to opera- tionalize. Practical alternative criteria for defining the active patients to be assessed include consecutive patients or patients seen in the practice in the past year.12 A methodologic study in the Pediatric Re- search in Office Settings (PROS) network found that the CDC standard assessment yielded mean immuni- zation rates 8 to 10 percentage points below the rates obtained from assessment of consecutive patients or patients determined to be active in the practice by follow-up contact.11 Given the national emphasis on quality assurance assessment in private practice, more methodologic studies are needed.
In 1996–1997, we conducted a physician-led quality improvement initiative that increased im- munization rates in 10 pediatric practices in east- ern Virginia.8 During this initiative, many partici- pating pediatricians indicated that they considered the current national assessment standard to be bi- ased because it fails to exclude inactive patients. To address this concern, we evaluated the immuniza- tion rates obtained from practice assessments con- ducted using standard criteria for patient selection
From the *Center for Pediatric Research, Eastern Virginia Medical School, Children’s Hospital of The King’s Daughters and ‡Children’s Hospital of The King’s Daughters and Its Physician Partners, Eastern Virginia Medical School, Norfolk, Virginia.
Received for publication Aug 2, 1999; accepted Dec 29, 1999. Reprint requests to (A.L.M.) Center for Pediatric Research, 855 W Brambleton Ave, Norfolk, VA 23510. E-mail: amorrow@chkd.com PEDIATRICS (ISSN 0031 4005). Copyright © 2000 by the American Acad- emy of Pediatrics.

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compared with 3 alternative criteria used to define active patients: 1) follow-up: patients included in the standard assessment who had a complete im- munization record in their chart or were identified as active in the practice by phone or mail follow-up contact; 2) seen in the past year: patients included in the standard assessment whose chart noted that they were seen in the practice in the past year for any reason; and 3) consecutive: a separate survey of patients seen consecutively in the practice in the past month for any reason. We compared assess- ment outcomes for the practices overall, and be- tween predominantly Medicaid and non-Medicaid practices to examine the relationship between im- munization assessment methodology and type of practice or patient population.

METHODS
Study Design and Population
This study included 10 pediatric practices that were partici- pating in a previously reported immunization quality improve- ment initiative.8 The study population consisted of practice patients between 12 and 30 months old on December 12, 1997. In 3 practices, defined as high-Medicaid, 50% to 85% of patients were Medicaid-insured. In 7 practices, defined as low-Medicaid, ,25% of patients were Medicaid-insured. The percent of pa- tients who were Medicaid-insured was estimated by office man- agers based on patient visit data. Participating practices varied in size, from 2 to 10 full-time pediatricians, and in their policy for purging records from their active files. High-Medicaid prac- tices tended to maintain records of all patients seen, purging the records of inactive patients only every few years, while low- Medicaid practices typically purged the records of inactive pa- tients annually or semiannually, with inactive status based on not having been seen in the past year.

Outcome Measures
The primary outcome measures were the percent of children up-to-date (UTD) with immunizations at 12 (UTD12) and 24 (UTD24) months old, defined as having all recommended doses of diphtheria-tetanus- whole cell or acellular pertussis (DTP), polio, measles-mumps-rubella (MMR), and Haemophilus influ- enzae type b (Hib) vaccines. UTD12 was defined as having 3 DTP, 2 polio, and 2 Hib vaccine doses; UTD24 was defined as having 4 DTP, 3 polio, 1 MMR, and 3 Hib vaccine doses. A secondary outcome was the percent of patient charts included in the standard assessment that were classified as active based on independent criteria.

Assessment Methods
All practices were assessed comparing 4 different criteria for defining the active patient population and selecting patient charts, as detailed below: standard, follow-up, seen in the past year, and consecutive assessment criteria. This study was ap- proved by the Institutional Review Board of Eastern Virginia Medical School.

Standard Assessment
We conducted practice assessments using the Clinic Assess- ment Software Application (CASA),9,10 which determined the number of records to be assessed per practice based on the practice size. To ensure that all charts had equal chance of inclusion, assessed charts were systematically selected from active patient files using a randomly selected start point and a calculated sampling interval. Charts were eligible for inclusion if the patient fell within the target age range and had at least 1 well-child or immunization visit in the practice but were ex- cluded if the chart documented that the patient had moved or gone elsewhere for care.9 Based on that criteria, we excluded charts that documented that the patient was receiving all of their immunizations from a military or public health clinic. In prac- tices with 2 systems of record-keeping (eg, paper and comput- erized medical records), we searched both systems as needed. All assessments were performed by well-trained staff who were blind to study hypotheses.
Follow-Up
Based on follow-up criteria, patients were defined as active patients of the practice if their immunization record in the practice was complete or, if they were otherwise identified as active patients of the practice through contact with a parent or guardian by telephone or mail. Children lacking 1 or more doses of DTP, polio, MMR, or Hib based on their age at assessment were identified using CASA software. Current contact informa- tion was obtained from each practice for all children who were overdue for 1 or more immunizations given their month of age. Trained interviewers representing the practice network at- tempted to contact the family by telephone, with at least 3 attempts made, as necessary, on different occasions. When the patient’s parent or guardian was contacted, they were informed that the call was part of a quality assurance initiative of their doctor’s practice and that their participation was helpful but not required. Parents who agreed to participate were asked if the practice was their child’s current, usual source for well-child care and immunizations, any other providers the child may have ever seen for immunizations, and they were asked to read the child’s immunization record to the interviewer over the phone if possible.
A 1-page print version of the survey was mailed to families that could not be reached by telephone, with a preaddressed, postage-paid return envelope and a cover letter from the medical director (A.B.F.) of the physician-hospital organization, to which all of the practices belonged. The external envelope re- quested the US Postal Service to provide an address correction, if needed. A second wave of surveys was mailed to families that did not respond initially. Thus, we made up to 5 attempts to contact the family by telephone and mail.
To complete partial records, we requested immunization records from all providers listed by the family except for mili- tary and out-of-country providers. Updated information was provided to each participating practice as part of their ongoing quality assurance efforts. Based on the follow-up results, pa- tients identified as moved or gone elsewhere or with unknown status were considered inactive and excluded from the assess- ment. The primary analysis of immunization outcomes was restricted to the practices’ original immunization data; however, a secondary analysis assessed the effect of having augmented immunization records.

Seen in the Past Year
This assessment used the standard assessment patients ex- cluding those not seen in the practice in the past year. During the standard assessment, staff recorded the date that the child was last seen in the practice for any reason, and this date classified children as seen or not seen in the past year.

Consecutive Patients
The consecutive assessment involved a separate survey of 100 patients who were seen consecutively for any reason. Each practice generated a list of patients who visited the practice between November 12 and December 12, 1997. We analyzed only those patients who were between 12 and 30 months old on November 12, 1997.

Statistical Analysis
We calculated immunization rates for each practice and as- sessment method, and the mean and 95% confidence interval of the practice level rates. All patients were included in the UTD12 calculations; patients 24 to 30 months old were included in the UTD24 calculations. The mean differences in practice level im- munization rates between the different assessment methods were analyzed using paired t tests, or when the data were not normally distributed, by the Wilcoxon signed rank test. The difference in mean immunization rates between high- and low- Medicaid practices were analyzed by the 2-sample t test. We examined differences in patient follow-up between high- versus low- Medicaid practices using a x2 test adjusted for practice

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level clustering.13 Data analysis was conducted using SAS sta- tistical software (version 6.12; SAS Institute, Cary, NC).
RESULTS
Practice Charts Assessed
As shown in Table 1, the standard assessment included a total of 1823 patients charts, 641 in the high-Medicaid practices and 1182 in the low-Med- icaid practices. The consecutive patient assessment included an additional 851 patient charts, 241 in the high-Medicaid and 610 in the low-Medicaid practices.

Follow-Up
Of the 1823 patient charts included in the standard assessment, 63% had complete immunization histo- ries and were presumed to be active patients. Tele- phone and mail surveys documented an additional 13% to be active patients, 18% to have unknown status, and 6% to have moved or gone to another practice. As shown in Fig 1, the follow-up status of patients differed significantly between high- and low- Medicaid practices (x2adj 5 25.5; P , .001). For high- and low-Medicaid practices alike, patients of un- known status were 20 to 25 percentage points below documented active patients in terms of immunization rates and the percent who were seen in the past year, but were similar to patients documented to have moved or gone elsewhere. This pattern confirmed our decision to classify patients of unknown status as not active in the practice.

Comparison of Active Patient Definitions
Based on the charts included in the standard assessment, we compared the percent of patients classified as active by the 2 independent criteria used in this study: follow-up and being seen in the past year (Fig 2). Consecutive patients were not compared because they were obtained by a separate survey and, by definition, all were considered ac- tive patients. Classification of patients as active or inactive by follow-up and seen in the past year criteria was significantly correlated (r 5 .44; P 5
.024). However, significantly (P , .001; paired t
test) fewer patients were classified as active based on follow-up (76%) compared with seen in the past year criteria (89%). Further, high-Medicaid prac- tices had significantly (P , .001; 2-sample t test) fewer patient charts classified as active than low- Medicaid practices, whether by follow-up (61% vs 83%) or by seen in the past year criteria (78% vs 95%). Compared with follow-up criteria as the gold standard, having been seen in the past year pro- vided high sensitivity as a screening criterion for identifying active patients: 367 of 394 (93%) active patients in the high-Medicaid and 974 of 985 (99%) in the low-Medicaid practices. On the other hand, the specificity was modest to poor for identifying inactive patients: 112 of 247 (45%) inactive pa- tients in the high-Medicaid and 53 of 197 (27%) in the low- Medicaid practices. Thus, defining active patients as those seen in the past year did not exclude many of the patients who were classified as inactive by follow-up.

Comparative Outcomes
The mean practice immunization rates obtained using the 4 different selection criteria are shown in Table 1, and the mean differences in practice im- munization rates between alternative and standard criteria are shown in Fig 3. Use of any of the alter- native patient selection criteria resulted in immu- nization rates that were consistently higher than the standard (all practices: at 12 months–4 to 10 percentage points, at 24 months–8 to 16 percentage points); all of these comparisons were significant (P # .05) by paired t test or by Wilcoxon signed rank test. Further, the mean differences in immu- nization rates were greater for high- than low-Medicaid practices, comparing alternative to standard assessments (Table 2). At 12 months, the mean differences in immunization rates between alternative and standard assessments ranged from 7 to 15 percentage points for high-Medicaid practices versus 3 to 7 percentage points for low-Medicaid practices. At 24 months, the mean differences in immunization rates between alternative and stan- dard assessments ranged from 17 to 23 percentage
TABLE 1. The Number of Patient Charts Assessed for All Ten Practices, and for High- and Low-Medicaid Practices, and Percent of Patients UTD at 12 and 24 Months Using Standard and Alternative Assessment Criteria

Practice Type Assessment
Criteria
Standard 1823 83.0 (76.6, 89.4) 714 69.6 (61.1, 78.2) Follow-up 1379 91.6 (88.4, 94.8) 563 85.5 (81.3, 89.7) Seen in past year 1621 87.1 (82.5, 91.6) 603 78.8 (73.4, 84.2) Consecutive 851 92.5 (89.6, 95.4) 226 77.9 (70.4, 85.4)
Standard 641 71.8 (59.0, 84.7) 250 53.8 (48.2, 59.4) Follow-up 394 85.1 (81.0, 89.2) 168 77.2 (75.9, 78.5) Seen in past year 502 79.3 (70.7, 87.8) 175 72.0 (69.7, 74.3) Consecutive 241 86.8 (82.5, 91.1) 77 70.4 (63.7, 77.0)
Standard 1182 87.8 (83.6, 91.7) 464 76.4 (69.1, 83.8) Follow-up 985 94.4 (92.8, 96.0) 395 89.0 (85.7, 92.4) Seen in past year 1119 90.4 (87.2, 93.6) 428 81.7 (75.1, 88.3) Consecutive 610 95.0 (93.4, 96.5) 149 81.7 (72.1, 91.4)
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Children 12 to 30 Months Children 24 to 30 Months

Number of Charts
UTD 12 Mean Immunization Rate (95% Confidence
Interval)
Number of Charts
UTD 24 Mean Immunization Rate (95% Confidence
Interval)

All practices (N 5 10)
High-Medicaid (N 5 3)
Low-Medicaid (N 5 7)

Fig 1. The classification of patients included in the standard assessment after extensive efforts to follow-up patients lacking a complete immunization history.
Fig 2. Percent of patient charts included in the standard assessment that were clas- sified as active by follow-up and seen in the past year criteria.
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points for high-Medicaid practices versus 5 to 13 percentage points for low-Medicaid practices. In general, the alternative assessment rates were sim- ilar and could not be readily distinguished from each other (Table 1), but follow-up assessments tended to have the highest rates. In the high-Med- icaid practices at 24 months, the mean immuniza- tion rate for the follow-up assessment was 5 per- centage points higher than the seen in the past year assessment rate (P , .05; paired t test).

Fig 3. The mean difference in im- munization rates obtained from al- ternative criteria assessments mi- nus the standard criteria assessments. The symbols repre- sent significance levels: 1 P ,
.001, by paired t test; * P , .01, by paired t test; § P 5 .05, by Wil- coxon signed rank test.
TABLE 2. Mean Differences between UTD Immunization Rate Outcomes for Alternative and Standard Patient Selection Criteria, Comparing High- and Low-Medicaid Practices

Criteria UTD 12 Rate
Mean Difference
UTD 24 Rate Mean Difference

High-Medicaid Low-Medicaid P* High-Medicaid Low-Medicaid P*

Follow-up
(minus standard)
14.9 7.2 .112 16.6 6.3 .220
 
13.3 6.6 .089 23.4 12.6 .018
7.4 2.6 .030 18.2 5.3 ,.001
Seen in past year
(minus standard)
Consecutive
(minus standard) * by 2-sample t test.

As previously noted, the follow-up assessment immunization rates presented in this article used only the original data from each practice to com- pare the effects of patient selection criteria. How- ever, we conducted a secondary analysis to exam- ine the effect of combining all sources of immunization data. The combined data yielded rates 0 to 4 percentage points higher than those obtained using the original practice data only.

DISCUSSION
Our study, conducted in a single urban area and network of pediatric practices, demonstrates that substantial differences in immunization rates can occur because of variation in functional definitions of the patient population denominator. The mean practice immunization rates were significantly lower using the standard criteria compared with 3 independent alternative criteria for defining and selecting active patients: at 12 months, 4 to 10 percentage points, and at 24 months, 8 to 16 per- centage points. In this methodologic study, the im- munization rates obtained using the standard crite- ria compared with the alternative criteria differed more for high-Medicaid practices (at 24 months, 17 to 23 percentage points) than for low-Medicaid practices (at 24 months, 5 to 13 percentage points).
Using the standard criteria, the patient denomi- nator is largely defined by the charts found in the active files of each practice and the extent to which practices document that patients have moved or gone elsewhere for care.9,12 We found, as previ- ously reported, that pediatric practices vary in their policy and routine of purging patient records, as well as the percent of charts maintained in active files that pertain to patients seen in past year (only 78% of high-Medicaid practice charts versus 95% of low-Medicaid practice charts). After exhaustive follow-up efforts to determine the status of patients lacking a complete immunization history, the per- cent of patients considered active in the practice also differed between high-Medicaid (61%) com- pared with low-Medicaid (83%) practices. Our findings suggest that some practices, notably those that care for predominantly Medicaid patients, may appear to have substantially lower immunization rates when assessed using the standard criteria be- cause they maintain records of patients not seen in the past year in the active patient files, and/or because they have greater difficulty in identifying the status of former patients, despite reasonable follow-up efforts. We found that the wide gap in immunization rates between high- and low-Medic- aid practices seen in the standard assessments nar- rowed but did not wholly disappear when alterna- tive assessment criteria were used. Differences in record-purging policies therefore appear to explain some, but not all, of the reason for lower immuni- zation rates measured in high-Medicaid practices.
Health departments throughout the country work with private practices to conduct assessments, typi- cally using a variant of the standard assessment method first issued by the CDC in 1992. The current guidelines are applied somewhat flexibly, allowing assessors to include the charts of patients with 1 or more medical visits or 1 or more well-child visits.9 Had we used any medical visit rather than a well- child visit as the inclusion criterion in this study, review of our excluded charts indicated that the stan- dard assessment rates would have decreased 1 to 2

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percentage points, and the differences between stan- dard and follow-up or seen in the past year assess- ments would have increased accordingly. Thus, some differences in immunization rates can occur as a re- sult of using these different standard criteria. Another variant of the standard assessment, which is increas- ingly used, restricts assessment to patients seen in the past year. We found that using only the charts of patients seen in the past year is a simple and appro- priate modification to current practice assessment methodology.
In several aspects, this study confirms the findings of the previous methodologic study that involved 15 practices of the PROS network.11 Darden and others found that immunization rates at 24 months were 8 to 10 percentage points higher for assessments based on consecutive patients or active follow-up compared with standard chart selection. Our findings for the low-Medicaid practices resemble those of the PROS network, while our high-Medicaid practices had much greater disparities between alternative and standard assessment rates than previously reported. Also, the PROS network practices had notably better patient follow-up (unknown: 7%) than we could achieve in our highly mobile urban population (un- known: 11%, low-Medicaid practices; 30%, high- Medicaid practices).
While contributing new insights to practice as- sessment, our study has several limitations. First, this study was conducted in a single region, and thus may not be generalized to the United States as a whole. Nevertheless, our region and practice sam- ple may be similar to practices in urban areas with mobile populations, and provides a complement to the PROS network sample.11 Second, the follow-up criteria used in this study assumed that patients with a complete immunization history were active with the practice. This approach is consistent with the advice given to providers, ie, charts lacking complete immunization data can be excluded if providers document that the patient has moved or gone elsewhere for care. We estimate that our ap- proach may have biased the measured immuniza- tion rates upward by about 6 percentage points. However, we did not include immunization data from outside sources in the primary analysis, which is a downward bias of up to 4 percentage points. Thus, on balance, the overall bias in the follow-up assessment rates reported in this study is likely to be minimal.
To our knowledge, this is the first published study comparing the relative impact of differing patient definition and selection criteria on assess- ment outcomes in different types of practices (high- and low-Medicaid), and to examine the effect of restricting chart selection to patients seen in the past year. Our study demonstrates the importance of standardizing the patient denominator, and sug- gests that immunization assessments should be conducted using an appropriate, operationally fea- sible definition of active patient. Assessment of consecutive patients is easiest for practices to en- act, but Darden and Taylor note that the approach tends to oversample frequent users of the health care system.12 Assessment of patients seen in the past year is consistent with the record-purging pol- icy of many practices, is less likely to oversample frequent users of the health care system, and ap- pears to be a conservative measure of being active with the practice. Finally, our findings underscore the problem of discontinuity in medical care,14 es- pecially in the Medicaid population, and the need to strengthen the medical home as part of improv- ing immunization rates and quality of care in ur- ban, mobile populations.
ACKNOWLEDGMENTS
This work was supported in part by Children’s Hospital of The King’s Daughters Health Foundation and Virginia Depart- ment of Health (VDH), Division of Immunization.
We gratefully acknowledge the funding provided by the Chil- dren’s Hospital of The King’s Daughters Health System and VDH, Division of Immunization, the support of Jim Farrell (VDH), Dr Jorge Rosenthal (CDC), and the technical consultation provided by Igor Bulim and John Stevenson (CDC). This project would not have been possible without the excellent pediatri- cians and staff of Children’s Hospital of The King’s Daughters and Its Physician Partners; the staff of the Center for Pediatric Research, including J. Andrew McCraw, Krystal Hilton, Ner- mina Nakas, Cynthia Collins-Odoms, Nancy Stromann, and Anne Wright; and local health department staff. We thank them all for their invaluable assistance with this project.
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