Assumption: Current staffing patterns
at the national level reflect a balance
of supply and demand.
Assumption: Differences within types
of care in factors such as patient acuity
do not vary substantially across counties.
Assumption: RN commuting patterns are
similar to the commuting patterns of
other workers in terms of county inflow
and outflow.
This method reflects an effort to create
a more “realistic” model with which to
assess the extent of nursing shortages
in counties across the U.S. It incorporates
elements of several of the models described
above.
A. Estimating
Health Care Utilization
Demand for RNs was estimated for 14 different
settings. In eight of these settings (short-term
inpatient, long-term inpatient, hospital
outpatient, emergency department, psychiatric
inpatient, hospital nursing home unit,
other nursing home, and home health),
demand was estimated based on actual or
estimated use of services at the county
level. In the other six settings (nurse
education, public/community health, school
health, occupational health, ambulatory
care, and all other settings), estimates
of demand were based on the size of the
population.
Short-term inpatient days (non-psychiatric
hospitals): Data on inpatient days
in short-term general hospitals by county
was available from the ARF.
The ARF does not separate inpatient days
in short-term non-general and long-term
hospitals, but does separate several specific
types of short-term non-general and long-term
hospitals: short-term psychiatric, short-term
rehabilitation, short-term children’s
psychiatric, long-term general medical
and surgical, long-term psychiatric, long-term
rehabilitation, and long-term children’s
psychiatric. This allowed the division
of many of the most common hospital types
into short-term non-general and long-term.
Short-term non-general and long-term inpatient
days that fell outside of these categories
were categorized as short-term non-general
and long-term based upon whether hospitals
in the county that did not fall into any
of the specific categories were short-term
non-general or long-term hospitals.
Only 34 counties had both short-term
non-general and long-term hospitals that
fell outside the seven categories above,
so in most cases it was easy to determine
whether the remaining inpatient days were
either short-term non-general or long-term.
In the remaining 34 counties, the unidentified
inpatient days were assigned as either
short-term non-general or long-term based
upon the proportion of hospital beds in
the county falling into either of those
categories.
This produced reasonable estimates of
short-term non-general inpatient days
by county, but these estimates included
inpatient days spent in nursing home units.
ARF provided estimates of nursing home
unit inpatient days for short-term non-general
and long-term hospitals, but did not separate
the two. Once again, however, nursing
home unit beds were separated into short-term
non-general versus long-term, and this
proportion was used to assign nursing
home unit inpatient days to the two categories
of hospitals. Inpatient days spent in
nursing home units in short-term non-general
hospitals were subtracted from the total
number of inpatient days in short-term
non-general hospitals, and are dealt with
separately. The same was done for short-term
general hospitals.
Days in short-term psychiatric and children’s
psychiatric hospitals were also then subtracted
from total short-term non-general hospital
inpatient days. These will also be treated
separately. In a few cases, it was apparent
that nursing home unit days in short-term
non-general hospitals were being reported
by short-term psychiatric hospitals (e.g.,
because the only short-term non-general
hospital in the county was psychiatric,
leaving this as the only explanation [3]),
and in those cases subtracting both nursing
home inpatient days and psychiatric inpatient
days would have resulted in double subtraction
and negative values. This was handled
by subtracting only short-term psychiatric
inpatient days in the counties where this
occurred.
Long-term inpatient days (non-psychiatric
hospitals): As described above, inpatient
days in long-term hospitals were separated
from those in short-term non-general hospitals
using information about inpatient days
in specific types of long-term hospitals
and information about other hospitals
in the county. Once again, however, these
estimates contained nursing home unit
days, which were subtracted as described
for short-term non-general inpatient days.
Days in long-term psychiatric and children’s
psychiatric hospitals were also then subtracted
from total long-term hospital inpatient
days.
As with short-term non-general inpatient
days, it was evident that a small number
of long-term psychiatric hospitals had
reported nursing home unit days [4].
Because subtracting both nursing home
inpatient days and psychiatric inpatient
days would result in double subtraction
and negative values, this was handled
by only subtracting long-term psychiatric
inpatient days in the counties where this
occurred.
Psychiatric hospital inpatient days:
Because inpatient days in both short-term
and long-term psychiatric and children’s
psychiatric hospitals were separated out
in the ARF for all counties, psychiatric
hospital inpatient days were not difficult
to count. The only complexity was that
18 of these hospitals, as discussed above,
appeared to report nursing home unit days.
Because this seemed improbable, the decision
was made to ignore the nursing home days
rather than subtracting them from the
totals for psychiatric inpatient days
and adding them to the total for hospital
nursing home unit days [5].
Nursing home unit inpatient days:
Nursing home unit inpatient days were
presented in ARF for both short-term general
and short-term non-general and long-term
hospitals. The data was clear except for
the issue discussed above of a small number
of psychiatric hospitals (both short-term
and long-term) apparently reporting nursing
home unit days. These nursing home days
were removed from the nursing home days
total for short-term non-general and long-term
hospitals.
Example: Tuscaloosa, Alabama
Short-term general days were 187,432.
Short-term non-general and long-term
days were 393,627. The county had
two long-term hospitals (both psychiatric)
and no short-term non-general hospitals,
and all of the 393,627 days were
in long-term rather than short-term
non-general hospitals. In total,
61,861 nursing home unit days in
long-term hospitals were reported
for this county, and by definition
had to be reported for one of the
long-term psychiatric hospitals.
These days were treated as long-term
psychiatric days rather than nursing
home days. The total number of short-term
days for Tuscaloosa County was 187,432,
and the total number of long-term
non-psychiatric days was 0. The
number of psychiatric inpatient
days was 393,627, and the number
of nursing home inpatient days was
counted as 0.
Example: Pima County, Arizona
Short-term general days were 555,167.
Short-term non-general and long-term
days were 75,844. The county had
four short-term non-general hospitals
(totaling 251 beds) and one-long-term
hospital (totaling 51 beds). Inpatient
days in short-term non-general and
long-term hospitals (75,844) were
apportioned according to the ratio
of beds (approximately 83% short-term
general and 17% long-term), to produce
63,036 short-term non-general days
and 12,808 long-term days. |
Outpatient visits (non-emergency):
Outpatient visits to hospital non-emergency
departments for short-term hospitals and
short-term non-general and long-term hospitals
were available in ARF. The sum of these
two figures was used to produce the figure
for total non-emergency hospital outpatient
visits.
Emergency department visits: Visits
to hospital emergency departments for
short-term hospitals and short-term non-general
and long-term hospitals were available
in ARF. The sum of these two figures was
used to produce the figure for total hospital
emergency department visits.
Non-hospital nursing home population:
The 2000 U.S. Census has data by county
for those living in specific types of
group quarters, including nursing homes.
Home health patients: The number
of home health patients per county was
estimated using the age and gender distribution
of the population, based upon national
age-specific and gender-specific utilization
rates taken from a CDC report available
online at: www.cdc.gov/nchs/data/nhhcsd/curhomecare00.pdf.
Example: Albany County, New
York
Table 40, below, illustrates how
national age- and gender-specific
rates were applied to the population
of Albany County to obtain estimates
of 528 male and 1,155 female home
health patients in the county (total
home health patients = 1,683).
Table
40. Illustrative Application of
Age- and Gender-Adjusted Utilization
Rates Are Applied for a County
0-17 |
34,074 |
9.1 |
31 |
32,004 |
8.6 |
28 |
18-44 |
58,186 |
9.3 |
54 |
60,733 |
13.2 |
80 |
45-64 |
32,013 |
35.6 |
114 |
34,655 |
33.9 |
117 |
65-69 |
4,571 |
98 |
45 |
5,687 |
107.5 |
61 |
70-74 |
4,512 |
103.8 |
47 |
6,013 |
203.7 |
122 |
75-79 |
3,576 |
216.8 |
78 |
5,550 |
377.9 |
210 |
80-84 |
2,324 |
358.5 |
83 |
4,376 |
432.3 |
189 |
85+ |
1,387 |
553.9 |
77 |
4,596 |
754.9 |
347 |
Total |
140,643 |
35.1 |
528 |
153,614 |
61.8 |
1,155 |
|
Other nursing care: The use of
other types of nursing care (nurse education,
public and community health, school health,
occupational health, non-hospital ambulatory
care, and other) was estimated based upon
population ratios as described below.
B. Estimating
Current National RN Staffing
Using data from the NSSRN, it was possible
to estimate RN staffing by setting at
the national level.
Short-term inpatient (non-psychiatric
hospitals): The RNs included as employed
in this category of care were all those
working in hospital units other than emergency
department, outpatient, home health, radiologic,
or dialysis in non-federal, non-psychiatric
short-term hospitals, federal government
hospitals [6],
and other types of hospitals.
Long-term inpatient (non-psychiatric
hospitals): The RNs included as employed
in this category of care were all those
working in hospital units other than emergency
department, outpatient, home health, radiologic,
or dialysis in non-federal non-psychiatric
long-term hospitals.
Psychiatric inpatient (non-federal):
The RNs included as employed in this category
of care were all those working in hospital
units other than emergency department,
outpatient, home health, radiologic, or
dialysis in non-federal psychiatric hospitals.
Nursing home unit inpatient: The
RNs included as employed in this category
of care were all those who reported working
in a “nursing home unit in hospital.”
Outpatient (non-emergency): The
RNs included as employed in this category
of care were all those who reported working
in outpatient, radiologic, or dialysis
units in any type of hospital.
Emergency outpatient: The RNs
included as employed in this category
of care were all those who reported working
in emergency departments in any type of
hospital.
Non-hospital nursing home: The
RNs included as employed in this category
of care were all those who reported working
in a nursing home other than a hospital
nursing home unit.
Home health: The RNs included
as employed in this category of care were
all those who reported working in a home
health unit in a hospital of any type
or any type of home health agency.
Nurse education: The RNs included
as employed in this category of care were
all those who reported working in any
type of nursing care education program,
including LPN and CNA programs.
Public and community health: The
RNs included as employed in this category
of care were all those who worked in state
or local health departments, community
mental health and substance abuse facilities,
any kind of community health clinic (CHC,
family planning clinic, RHC), or a day
care, hospice, or other community health
setting.
School health: The RNs included
as employed in this category of care were
all those who worked in public or private
school health services, elementary through
high school. Those working in college
or university health services were not
included.
Occupational health: The RNs included
as employed in this category of care were
all those who worked in private, government,
or other occupational health services.
Non-hospital ambulatory care:
The RNs included as employed in this category
of care were all those who worked in physician
or nurse practices, clinics, HMOs, or
other non-hospital ambulatory settings.
Other nursing care: The RNs included
as employed in this category of care were
all those who worked in any setting not
included in the above, including facilities
for the mentally retarded, college health
services, insurance companies, state boards
of nursing, and professional associations.
C. Estimating
RN Demand by Setting
The national estimates for utilization
and current RN staffing were combined
to produce ratios of RNs to units of care,
as shown in Table 41 below. These ratios
were then applied to utilization and population
counts at the county level to estimate
how many RNs would be needed to achieve
these ratios.
Table
41. RNs per Unit of Care in Fourteen Health
Care Settings in Selected Years
All
inpatient Units in Short-Term Hospitals
(2004) |
861,113 |
ST
Inpatient Days (2003) |
173,161,615 |
4.97
RNs per
1,000 Inpatient Days |
All
inpatient Units in Long-Term Hospitals
(2004) |
84,662 |
LT
Inpatient Days (2003) |
7,261,248 |
11.66
RNs per
1,000 Inpatient Days |
All
inpatient Units in Psychiatric Hospitals
(2004) |
36,651 |
Psychiatric
Inpatient Days (2003) |
25,313,077 |
1.45
RNs per
1,000 Inpatient Days |
Nursing
Home Unit in Hospital (2004) |
12,090 |
Total
Nursing Home Hospital Inpatient
Days (2003) |
25,374,490 |
0.48
RNs per
1,000 Inpatient Days |
Other
Nursing Home (2000) |
118,898 |
Nursing
Home Resident Population (2000) |
1,720,500 |
0.07
RNs per
NH Resident |
Nurse
Education Programs (2000) |
46,301 |
Estimated
Active RNs (2000) |
2,233,864 |
0.02
per
Active RN |
Public/Community
Health RNs (2000) |
148,507 |
Total
Population (2000) |
281,421,906 |
5.28
RNs per
10,000 Pop |
School
Health (excl. college) |
66,587 |
Population
Age 5-17 |
53,089,688 |
12.5
RNs per
10,000 Pop |
Occupational
Health (2000) |
36,099 |
Population
Age 18-64 |
174,294,950 |
2.07
RN per
Pop |
Home
Health (2000) |
131497 |
Estimated
Home Health
Patients (2000) |
1,365,940 |
0.10
RNs per
Patient |
Outpatient
or Diagnostic Units in All Hosp
(2000) |
85,433 |
Outpatient
Visits - Other Than ED (All hospitals)
(2000) |
600,155,715 |
0.14
RNs per
1,000 Visits |
EDs
in All Hospitals (2000) |
91,732 |
ED
Visits (All Hospitals) (2000) |
107,293,419 |
0.86
RNs per
1,000 Visits |
Ambulatory
Care (2000) |
209,165 |
Total
Population (2000) |
281,421,906 |
7.43
per
10,000 Pop |
Other |
114,958 |
Total
Population (2000) |
281,421,906 |
4.1
RNs per
10,000 Pop |
D. Estimating
Supply of RNs
The only nationally available figures
for RNs by county were from the 2000 Census,
and were based on county of residence.
For a substantial portion of the RN workforce,
however, county of residence was different
from county of employment. To adjust for
this, county-to-county commuting flows
were obtained from the U.S. Census Bureau,
and RN estimates were adjusted based upon
the ratio of workers living in the county
to workers working in the county. This
methodology assumed that the commuting
patterns of RNs did not differ substantially
from the commuting patterns of the civilian
workforce overall.
Example: Albany County,
New York
In 2000, 117,668 residents of Albany
County worked in Albany County,
and another 24,174 residents of
Albany County worked outside of
Albany County (a total of 141,842
residents of Albany County worked,
with 17% commuting out). An additional
101,045 workers commuted into Albany
County, resulting in a total workforce
of 218,713 in Albany County [117,668
+ 101,045], with 46% commuting into
the county from other counties.
The ratio of workers (both residents
and non-residents) working in the
county to residents of the county
who worked (both within and outside
the county) was 1.5419 [218,713/141,842].
This adjustment factor was applied
to the number of RNs living in Albany
County [3,205 x 1.5419] to estimate
that 4,942 RNs actually worked in
Albany County. |
E. Estimating
RN Shortages
The estimation of RN shortages was based
upon the difference between estimated
demand for RNs and the number of RNs in
the county (adjusted for commuting patterns).
Raw shortage numbers were then standardized
as a percent of demand. This methodology
did not assess shortages at the national
level because it theoretically redistributed
the current number of RNs into counties
according to patterns of health care utilization.
While a small national shortage occurred
using our procedures, this may have been
an artifact of using data from different
years for different types of care (hospital
ratios used 2004 nurse data and 2003 hospital
data, while ratios for other types of
care used 2000 nurse and hospital data).
At the state level, however, some interesting
patterns emerge (Table 42, below). Half
of the states were not seen to have shortages,
and those with the largest relative supplies
of RNs were Vermont, New Hampshire, and
Alaska. On the other hand, the District
of Columbia had a 49% shortage, while
Louisiana had a 25% shortage, and Oklahoma
had a 20% shortage.
Table
42. Estimated Percentage Shortages of
RNs in the U.S.
District
of Columbia |
4,267.6 |
8,672.8 |
49% |
Louisiana |
11,210.7 |
44,913.0 |
25% |
Oklahoma |
5,765.5 |
29,281.2 |
20% |
Nevada |
2,732.2 |
14,182.6 |
19% |
Mississippi |
4,955.5 |
27,235.9 |
18% |
New
York |
29,697.8 |
187,629.5 |
16% |
Texas
|
25,686.1 |
163,456.0 |
16% |
West
Virginia |
2,654.7 |
17,625.0 |
15% |
Arkansas |
3,280.4 |
23,831.6 |
14% |
Hawaii |
1,190.0 |
9,650.9 |
12% |
California |
28,761.9 |
233,938.4 |
12% |
Rhode
Island |
1,232.7 |
10,761.8 |
11% |
Virginia |
5,797.4 |
57,588.5 |
10% |
Georgia |
6,027.4 |
63,405.5 |
10% |
Florida |
10,510.1 |
134,832.0 |
8% |
Idaho
|
394.2 |
8,434.0 |
5% |
New
Jersey |
2,570.5 |
70,834.1 |
4% |
Kentucky |
962.3 |
35,434.4 |
3% |
Tennessee |
1,292.1 |
49,246.3 |
3% |
Alabama |
878.9 |
37,830.2 |
2% |
Arizona |
366.6 |
34,685.2 |
1% |
New
Mexico |
111.6 |
12,177.3 |
1% |
Utah |
92.8 |
13,787.5 |
1% |
Missouri |
77.7 |
50,013.8 |
0% |
South
Carolina |
-127.4 |
32,188.9 |
0% |
Montana |
-76.6 |
7,054.3 |
-1% |
North
Carolina |
-1,503.8 |
67,261.0 |
-2% |
Pennsylvania
|
-2,632.2 |
116,156.5 |
-2% |
North
Dakota |
-249.1 |
6,312.6 |
-4% |
Colorado |
-1,398.4 |
28,716.7 |
-5% |
Maryland |
-2,480.0 |
41,098.5 |
-6% |
Indiana |
-2,936.6 |
48,152.2 |
-6% |
Wyoming |
-212.2 |
3,370.4 |
-6% |
Michigan |
-5,070.8 |
73,520.9 |
-7% |
Massachusetts |
-5,061.8 |
63,465.1 |
-8% |
Iowa |
-2,506.4 |
26,343.7 |
-10% |
Kansas |
-2,293.4 |
22,984.5 |
-10% |
South
Dakota |
-793.3 |
6,863.4 |
-12% |
Nebraska |
-1,920.6 |
14,639.6 |
-13% |
Ohio |
-12,283.5 |
90,622.4 |
-14% |
Connecticut |
-4,402.6 |
28,395.4 |
-16% |
Oregon |
-3,846.4 |
21,216.4 |
-18% |
Maine
|
-2,077.4 |
9,736.7 |
-21% |
Delaware |
-1,400.2 |
6,488.7 |
-22% |
Wisconsin |
-8,450.0 |
38,179.5 |
-22% |
Washington |
-8,082.2 |
35,861.5 |
-23% |
Illinois |
-22,402.1 |
99,354.8 |
-23% |
Minnesota |
-9,245.4 |
38,000.9 |
-24% |
Alaska |
-1,156.6 |
3,805.3 |
-30% |
New
Hampshire |
-3,224.8 |
8,929.8 |
-36% |
Vermont |
-1,653.6 |
4,052.7 |
-41% |
Total |
43,029.4 |
2,282,219 |
2% |
Eighteen counties in the U.S. had a 100%
shortage (all of these counties had no
RNs), but a handful more counties had
shortages of more than 90%.
When counties were aggregated into metropolitan
and micropolitan areas (shown below),
the MSA with the greatest shortage was
the Boone, Iowa micropolitan area (80%).
Relatively few major metropolitan areas
had serious shortages -- the notable exceptions
were Las Vegas (with a 25% shortage),
New Orleans (22%)[7],
and New York (also 22%). Oklahoma City,
Los Angeles, Topeka, and Honolulu also
had shortages (16%, 14%, 13%, and 12%,
respectively). Despite the serious shortage
estimated for the District of Columbia
proper, the Washington-Arlington-Alexandria
MSA (which included counties in Maryland,
Virginia, and West Virginia, as well as
D.C.) had a shortage of only 2%.
[3]
It was not clear why psychiatric hospitals
would report nursing home unit days. As
this occurred in only 10 of the 3,140
counties it was possible that this was
simply due to a reporting error.
[4] This occurred in
eight of the 3,140 counties, and may be
due to reporting errors.
[5] The potential result
of this, if these reports were not in
error, could be to overestimate demand
for RNs in psychiatric hospitals if some
of these hospitals did indeed contain
nursing home units. RN staffing in psychiatric
hospitals is typically more intensive
than in nursing home units, so misclassifying
nursing home days as psychiatric days
could inflate the demand figures for RNs.
[6] Federal government
hospitals include some long-term and psychiatric
hospitals, but these were not distinguished
in the NSSRN. Most federal hospitals are
VAs, which tend to provide short-term
general care, and so RNs in federal government
hospitals will be included in this category
rather than another.
[7] This was using data
from before Hurricane Katrina in 2005.
New Orleans may currently have a much
greater shortage.
|