Preferred
Method
Staff members of the Center for Health
Workforce Studies have been working with
the Lewin Group on the update of the HRSA
Nurse Supply Model (NSM) and Nurse Demand
Model (NDM). Although the exact analyses
included in the NDM could not be replicated
at the county level due to data constraints,
the basic logic employed in the NDM was
very useful in thinking about demand for
RNs.
The project staff decided to apply a
simplified version of the NDM logic to:
1) estimate health care utilization in
different settings for counties (e.g.,
inpatient days); 2) estimate current national
RN staffing by setting (e.g., RNs working
in inpatient units); 3) calculate national
RN staffing intensity for each setting
(e.g., RNs per inpatient day); 4) apply
national RN staffing intensity ratios
to measures of utilization for each county;
and 5) sum estimate demand for each setting
to produce overall RN demand for individual
counties. Each step is summarized briefly
below.
A.
Estimate Health Care Utilization
The data on county-level health care utilization
primarily came from the Area Resource
File (ARF). The ARF included data on:
- Short-term inpatient days (non-psychiatric
hospitals)
- Long-term inpatient days (non-psychiatric
hospitals)
- Psychiatric hospital inpatient days
- Nursing home unit inpatient days
(hospitals)
- Outpatient visits (non-emergency)
- Emergency department visits
The number of (non-hospital) nursing
home residents in a county was obtained
from the 2000 Census. This was based on
the Census short-form data, which is theoretically
obtained from 100% of the U.S. population.
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 from the Centers for
Disease Control and Prevention (CDC).
Although this estimate was based upon
population characteristics rather than
actual use of services, home health patients
by definition were receiving services
where they live, so this was somewhat
less problematic than estimating other
types of utilization based upon population
characteristics.
B.
Estimate Current National RN Staffing
Data for current levels of RN staffing
by setting were taken from the 2000 NSSRN,
which included data on the number of RNs
employed in the following types of care:
- Short-term inpatient (non-psychiatric
hospitals)
- Long-term inpatient (non-psychiatric
hospitals)
- Psychiatric inpatient (non-Federal)
- Nursing home unit (hospital)
- Outpatient (non-emergency)
- Emergency outpatient
- Non-hospital nursing home
- Home health
- Nurse education
- Public/community health
- School health
- Occupational health
- Non-hospital ambulatory care
- Other nursing care
These numbers were combined with the
national utilization data described above
to compute national levels of RN staffing
intensity for the various types of care.
The national ratios are shown in the table
below.
Table
14. National RN Staffing Ratios by Type
of Care
4.97
RNs / 1,000 Inpatient Days |
11.66
RNs / 1,000 Inpatient Days |
1.45
RNs / 1,000 Inpatient Days |
0.48
RNs / 1,000 Inpatient Days |
0.07
RNs / NH Resident |
0.02
RNs / Active RN |
5.28
RNs / 10,000 Pop |
12.5
RNs / 10,000 Pop 5-17 |
2.07
RN / Pop 18-64 |
0.10
RNs / Home Health Patient |
0.14
RNs / 1,000 Visits |
0.86
RNs / 1,000 Visits |
7.43
/ 10,000 Pop |
4.1
RNs / 10,000 Pop |
C.
Estimating RN Demand by County
These national staffing ratios were then
applied to the utilization rates for each
county. For example, the national ratio
was 4.97 RNs working in hospital inpatient
units per inpatient day. If County A has
12,000 inpatient days per year, their
demand for RNs in inpatient units is estimated
at 59.6 (4.97 x [12,000/1,000]).
Overall RN demand for the county was
obtained by summing RN demand in the county
across all settings. (This procedure also
opens the possibility of comparing setting-specific
demand to setting-specific supply if data
on RN supply by setting are available
at the county level.)
D.
Use Supply of RNs to Estimate RN Shortages
RN shortages were thus measured as follows:
RN shortage = Estimated demand
for RNs in the county
minus the number of RNs in the county
(adjusted for commuting patterns).
Raw shortage estimates were then standardized
as a percent of demand. The results are
presented for all counties in the U.S.
in the map in Figure 8. The counties with
the greatest shortages are shaded black.
The full technical report has separate
maps for all 50 states, along with a table
with the numerical scores.
This method has advantages over any of
the other methods examined in this study,
especially in relation to the guiding
principles initially proposed for the
study:
- It uses nationally available data
that is periodically updated.
- It uses actual health care utilization
patterns by county.
- It accounts for multiple types of
care (including non-clinical services).
- It accounts for differences in RN
staffing intensity across settings.
Some limitations persist, however. It
does not account for county or state
variations in health systems (e.g.,
HMO penetration, use of LPNs), and does
not account for patient acuity within
types of care. Furthermore, it assumes
current RN staffing levels were adequate
at the national level in 2000, which
may not have been the case.
The NDM uses factors such as HMO penetration
and LPN staffing in regressions to adjust
estimated staffing intensity and make
it specific to each county rather than
applying national ratios. A similar procedure
might eventually be used to do the same
thing here. |