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1 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
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2 What are LPNs? Licensed practical nurses Licensed vocational nurses (LVNs) in CA and TX 1-2 years education Compare to 2+ years for Registered Nurses Licensure mandated in all states by 1965 Licensed grated by state agency Scope of practice varies across states
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3 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
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4 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
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5 Can LPNs substitute for RNs in hospitals? Is the supply of LPNs different than RNs? What affects demand for LPNs?
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6 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
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7 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
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8 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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9 Results: RN and LPN weekly hours (IV models) LPNsRNs Wage3.238*-0.887* Wage squared-0.128*0.017** Male3.309**4.016** Age0.623**0.708** Age squared-0.008**-0.009** Some college-0.477-0.353 AA degree0.3930.371 BS/MS/PhD1.158*0.820*
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10 Results: RN and LPN weekly hours (IV models) LPNsRNs Black1.211**2.020** Hispanic-0.6781.567** Native American0.0741.576** Asian0.7783.015** Not citizen0.2501.383** Naturalized cit.2.578**1.354** Household income-0.001-0.001** Elder in house1.049-0.344
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11 Results: RN and LPN weekly hours (IV models) LPNsRNs Married-2.119**-1.614** Prev. married0.4520.792** # kids age 0-5-0.815**-2.918** # kids age 6-12-0.888**-1.759** # kids age 13-17-0.432*-0.271** % state unionized-0.196-0.550
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12 Results: RN and LPN weekly hours (IV models) LPNsRNs Northeast-0.852*-0.750** Midwest-0.457-0.737** South1.360**0.760** Pop 100-500K-0.509-0.126 Pop 500K-1M-0.7030.170 Pop 1-2.5 M-0.250-0.822** Pop 2.5M +0.264-0.257
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13 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
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14 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
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15 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
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16 Demand analysis methods Multivariate regression, 2001 AHA data (3785 obs) Dependent variable: log FTE LPNs
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17 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
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18 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
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19 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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20 Demand for LPNs in US Hospitals Basic modelInstrument for scope Instrument for scope & wage Specific-0.077*-0.085**0.221 Restrictive-0.137**-0.136**-0.060 RN wage-0.092-0.0931.912 LPN wage-0.857**-0.838**-4.929 Aide wage0.667**0.725**0.183 Patient days0.615** 0.631** LOS-0.418**-0.420**-0.436** Case mix0.0980.0870.076 Service mix-0.022*-0.021*-0.022* Medicare share0.067**0.069**0.083**
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21 DV: Demand for LPNs in US hospitals (continued) Basic modelInstrument for scope Instrument for scope & wage For-profit0.0350.0390.044 District0.154**0.159**0.137** Government0.127**0.134**0.132** # HMOs-0.049** -0.026 HMO pen-0.138-0.120-0.131 # HMO * pen0.0420.040-0.003 Income per cap-0.00001** -0.000009** R-squared0.5420.5390.498 N3,8903.798
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22 DV: Demand for LPNs as a share of total nurses (US hospitals) Basic modelInstrument for scope Instrument for scope & wage Specific-0.025**-0.00010.045 Restrictive-0.004-0.038**-0.027** RN wage-0.154*-0.152*0.150 LPN wage-0.108-0.106-0.722 Aide wage0.0540.059-0.022 Patient days-0.025**-0.026**-0.024** LOS0.034**0.035**0.033** Case mix-0.057** -0.059** Service mix-0.001 Medicare share0.006** 0.008**
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23 DV: Demand for LPNs as a share of total nurses (US hospitals) (continued) Basic modelInstrument for scope Instrument for scope & wage For-profit-0.001-0.00020.0003 District0.022** 0.019** Government0.015*0.016*0.015* # HMOs-0.006** -0.003 HMO pen.-0.046**-0.045**-0.008 #HMO*pen0.009** 0.002 Income per cap-0.000001**-0.0000001** R-squared0.5290.5270.464 N3,9633,867
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24 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
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25 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
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26 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
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27 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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28 Visit us! http://futurehealth.ucsf.edu/ http://futurehealth.ucsf.edu/cchws.html
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