Supply, Demand, and
Use of Licensed
Practical Nurses
Joanne Spetz, Ph.D.
Wendy Dyer, M.S.
Jean Ann Seago, Ph.D., R.N
Susan Chapman, Ph.D., R.N.
Kevin Grumbach, M.D.
University of California, San Francisco
June, 2005
1
What are LPNs?

Licensed practical nurses


1-2 years education


Compare to 2+ years for Registered Nurses
Licensure mandated in all states by 1965


Licensed vocational nurses (LVNs) in CA and TX
Licensed grated by state agency
Scope of practice varies across states
2
Where do LPNs work?



596,355 LPNs in 2000
889,027 LPN licenses in 2000
LPNs held about 702,000 jobs in 2000



29% worked in nursing homes
28% worked in hospitals
14% worked in physicians' offices and clinics
3
The shortage of RNs has
raised interest in LPNs

Policymakers and employers and considering
LPNs as substitutes for RNs


California’s minimum nurse-to-patient ratios
permit LPNs to hold half the licensed nurse jobs
Bureau of Health Professions requested a study
on LPNs, including potential for substitution
4
Can LPNs substitute for RNs in
hospitals?

Is the supply of LPNs different than RNs?

What affects demand for LPNs?
5
Analysis of supply of LPNs

If LPN supply is affected by different factors
than RN supply, then LPNs might be better
substitutes for RNs



Compare LPN and RN supply equations
Current Population Survey, 1994-2001
LPNs and RNs identified by occupation

Licensure not available
6
Methods to analyze supply


Multivariate regression of cross-section data
Dependent variable:


Usual weekly hours of work
Explanatory variables:




Wage
Gender, age, education, race/ethnicity
Marital status, kids, household earnings, elder in
the house
Region of US, unionization rates, population in
city
7
Problem: wages are
endogenous

Wages are jointly determined by supply and
demand

Solutions:

Use market wage


Each state has 2 market wages, for urban and rural
regions
Instrumental variables


State-level average manufacturing wages
Number of physicians per 100,000 people
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Results: RN and LPN weekly
hours (IV models)
Wage
Wage squared
Male
Age
Age squared
Some college
AA degree
BS/MS/PhD
LPNs
3.238*
-0.128*
3.309**
0.623**
-0.008**
-0.477
0.393
1.158*
RNs
-0.887*
0.017**
4.016**
0.708**
-0.009**
-0.353
0.371
0.820*
9
Results: RN and LPN weekly
hours (IV models)
Black
Hispanic
Native American
Asian
Not citizen
Naturalized cit.
Household income
Elder in house
LPNs
1.211**
-0.678
0.074
0.778
0.250
2.578**
-0.001
1.049
RNs
2.020**
1.567**
1.576**
3.015**
1.383**
1.354**
-0.001**
-0.344
10
Results: RN and LPN weekly
hours (IV models)
Married
Prev. married
# kids age 0-5
# kids age 6-12
# kids age 13-17
% state unionized
LPNs
-2.119**
0.452
-0.815**
-0.888**
-0.432*
-0.196
RNs
-1.614**
0.792**
-2.918**
-1.759**
-0.271**
-0.550
11
Results: RN and LPN weekly
hours (IV models)
Northeast
Midwest
South
Pop 100-500K
Pop 500K-1M
Pop 1-2.5 M
Pop 2.5M +
LPNs
-0.852*
-0.457
1.360**
-0.509
-0.703
-0.250
0.264
RNs
-0.750**
-0.737**
0.760**
-0.126
0.170
-0.822**
-0.257
12
Conclusions about supply

Similar factors affect RN and LPN supply


LPN supply might be more responsive to wage
increases
Minority and male RNs more likely to work

Increased diversity of RN workforce will increase
supply
13
What about demand?

Key factor for demand is scope of practice



Can LPNs do what employers need?
Most scope of practice information is in published
regulations
Variations in:



Assessment of patients and development of care
plan
Drawing blood
Intravenous administration
14
Ratings of scope of practice


Obtained documents & surveyed states about
scopes of practice
Rated scopes of practice on:


Restrictiveness: not allowing a level of autonomy,
flexibility, or independence in the practice of LPNs
Specificity: explicating defined parameters of
practice of LPNs
15
Demand analysis methods

Multivariate regression, 2001 AHA data (3785 obs)

Dependent variable: log FTE LPNs
16
Demand analysis methods

Explanatory variables:





Hospital characteristics
 Number of patient days, Service mix (Saidin Index),
Medicaid share of patient days, Ownership
Market characteristics
 Wages, HMO penetration, Per capita income
Patient characteristics
 Average length of stay, Case mix
Regulatory characteristics
 Specificity of scope of practice
 Restrictiveness of scope of practice
State dummy variables
17
Endogeneity of wages

Instrumental variables for wages:




Average age of LPNs in the market area
Percent of all workers unionized in the state
County unemployment rates were not significant
predictors of wage
Tests indicate that wages are probably not
endogenous
18
Endogeneity of scope of practice

Instrumental variables: political variables from
1998






Dummy for Democratic control of both legislative houses
and the governorship
Dummy for if control of the houses and/or governorship is
divided between Democrats and Republicans
Ratio of per-capita state debt to per-capita income
Dummy for whether the governor has a line-item veto
Percent of the upper legislative house who are Democrats
Percent of the lower legislative house who are Democrats
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Demand for LPNs in US
Hospitals
Basic model
Instrument for
scope
Instrument for
scope & wage
Specific
-0.077*
-0.085**
0.221
Restrictive
-0.137**
-0.136**
-0.060
RN wage
-0.092
-0.093
1.912
LPN wage
-0.857**
-0.838**
-4.929
Aide wage
0.667**
0.725**
0.183
Patient days
0.615**
0.615**
0.631**
LOS
-0.418**
-0.420**
-0.436**
Case mix
0.098
0.087
0.076
Service mix
-0.022*
-0.021*
-0.022*
Medicare share 0.067**
0.069**
0.083**
20
DV: Demand for LPNs in US
hospitals (continued)
Basic model
Instrument for
scope
Instrument for
scope & wage
For-profit
0.035
0.039
0.044
District
0.154**
0.159**
0.137**
Government
0.127**
0.134**
0.132**
# HMOs
-0.049**
-0.049**
-0.026
HMO pen
-0.138
-0.120
-0.131
# HMO * pen
0.042
0.040
-0.003
Income per cap -0.00001**
-0.00001**
-0.000009**
R-squared
0.542
0.539
0.498
N
3,890
3.798
3.798
21
DV: Demand for LPNs as a share
of total nurses (US hospitals)
Basic model
Instrument for
scope
Instrument for
scope & wage
Specific
-0.025**
-0.0001
0.045
Restrictive
-0.004
-0.038**
-0.027**
RN wage
-0.154*
-0.152*
0.150
LPN wage
-0.108
-0.106
-0.722
Aide wage
0.054
0.059
-0.022
Patient days
-0.025**
-0.026**
-0.024**
LOS
0.034**
0.035**
0.033**
Case mix
-0.057**
-0.057**
-0.059**
Service mix
-0.001
-0.001
-0.001
0.006**
0.008**
Medicare share 0.006**
22
DV: Demand for LPNs as a share
of total nurses (US hospitals)
(continued)
Basic model
Instrument for
scope
Instrument for
scope & wage
For-profit
-0.001
-0.0002
0.0003
District
0.022**
0.022**
0.019**
Government
0.015*
0.016*
0.015*
# HMOs
-0.006**
-0.006**
-0.003
HMO pen.
-0.046**
-0.045**
-0.008
#HMO*pen
0.009**
0.009**
0.002
Income per cap -0.000001**
-0.0000001**
-0.0000001**
R-squared
0.529
0.527
0.464
N
3,963
3,867
3,867
23
Interpretation of key results

Scope of practice



Restrictive scope of practice reduces demand for
LPNs
More specific scope of practice reduces demand
for LPNs
Wages


Higher LPN wages predict a decrease in LPN
demand when no Instrumental variables used
Higher aide wages may predict in increase in LPN
demand
24
Interpretation of key results

Patients



Higher volumes increase LPN demand overall,
but reduce relative demand
Higher length of stay reduces LPN demand
overall, but increases relative LPN demand
Relative demand for LPNs drops as case mix
rises
25
Interpretation of key results

Managed care



HMO penetration reduces overall demand for
LPNs
Greater HMO penetration and competition
reduces relative demand for LPNs
But the effect diminishes with interaction of these
factors
26
Conclusions

Scope of practice affects hospital demand for
LPNs



Restrictive and specific scopes of practice have
negative effect on LPN use in hospitals
Acuity of illness reduces LPN demand
LPN demand is potentially responsive to LPN
and aide wages

RN wages do not affect LPN demand
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