Does Hospital Price Competition Influence
Nurse Staffing and Quality of Care?
Julie Sochalski, PhD1
R. Tamara Konetzka, PhD2
Jingsan Zhu, MBA1
Joanne Spetz, PhD3
Kevin Volpp, MD, PhD1,4
Introduction
• Over past 20 years hospitals shift from competing on
quality/amenities
competing on price.
• Evidence that price competition rate of increase in
hospital costs, profits
efficiencies or lower quality?
• Examine impact of price competition on one feature
associated with hospital quality – nurse staffing.
Academy Health
June, 2005
3
1 University of Pennsylvania
University of California at San Francisco
2
University of Chicago
Philadelphia VA Medical Center
4
Nurse Staffing – Patient Outcomes
Relationship
• CrossCross-sectional studies over 3 decades show higher nurse
staffing associated with reduced mortality.
• Recent longitudinal study found increases in RN staffing
linked to lower mortality, with diminishing returns.
• Most studies rely on hospitalhospital-wide measure of nurse
staffing which may obscure relationship.
In summary:
• Substantial gaps in understanding of nurse staffing—
staffing—
quality relationship.
• Rely on crude staffing measures to explore relationship.
• Lack information on current hospital responses to price
competition.
Hospital Responses to Price Competition
• Hospital personnel increased from 1980s to early 1990s.
• RNs increased commensurate with volume and CMI
while other nursing personnel declined.
• Spetz (1999) found HMO penetration was not
associated with RN staffing through early 1990s.
Research Questions
• Are changes in nurse staffing levels associated
with patient outcomes?
• What hospital and market features are associated
with staffing changes and thereby outcomes?
• 1999 – California passes AB 394 to establish minimum
nurse staffing ratios.
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Data
Study Design
• California’s Office of Statewide Health Planning and
Development (OSHPD) discharge data from 1991.
• California acute care hospitals, 19911991-2001
• Three AHRQ inpatient quality indicators:
• OSHPD annual disclosure (financial) data 1991-2001
• State death certificates 1991-2001.
– 3030-day mortality for AMI, stroke, and hip fracture
• Sample:
– Hospitals:
n = 421 short-term acute hospitals
(non-federal, non-Kaiser)
– Patients:
• AMI:
n = 352,536 (15.5%)
• Stroke:
Stroke
n = 592,651 (14.1%)
• Hip fracture: n = 276,628 (5.3%)
Control Variables
Key Study Variables
• Nurse staffing
– RN, LVN, Nurse Aide
– Nursing productive hours per patient day
– Acute medicalmedical-surgical units
• Market factors
– HMO penetration for hospital market area (fixed radius)
– High vs. low competition market areas
• Age
• Gender
• Race
• Ethnicity
• Expected source of payment: Medicare,
Medicaid, uninsured, private
• Elixhauser comorbidities
• Hospital casecase-mix index
• Year dummies 19911991-2001 (1991 is reference)
• Hospital fixed effects controls for timetimeinvariant hospital and market factors
Model
Generalized linear model with hospitalhospital-level fixed
effects + time fixed effects
Model 1
Pr( Death) pht = β 0 h + β v Staffing ht + β wYeart + β1HospitalCMI ht + β x PatientSeverity pht +
β y PatientDemographics pht + β z PaymentSource pht + ε pht
Model 2
RNhppd ht = β 0 h + β v Staffing ht + β wYeart + β1 HospitalCMI ht + β 2 MCPht + β 3 MCP * COMPht + β 4WageIndexht +
β x PatientSeverityht + β y PatientDemographicsht + β z PaymentSourceht + ε ht
Hospital Summary Statistics
No. of hospitals:
Avg. # beds:
Urban:
Teaching:
Ownership:
Non-profit:
Government:
For-profit:
Avg. CMI
421
192
88%
18.7%
52.7%
20.7%
26.6%
1.114
2
Change in CMCM-adjusted RN medicalmedical-surgical hours
per patient day, 19911991-2001
Effects of nurse staffing on 3030-day mortality
20.0%
15.0%
10.0%
5.0%
0.0%
1992
1993
1994
1995
AMI
Stroke
Hip
Fracture
RN
-0.004*
(0.001)
-0.002*
(0.001)
0.002
(0.001)
LVN
-0.003
(0.002)
0.0004
(0.001)
0.0008
(0.001)
Aide
0.001
(0.001)
-0.0002
(0.0007)
-0.0001
(0.0007)
RN*baseline
0.0004†
(0.0002)
-0.0001
(0.0001)
-0.0004
(0.0003)
Model:
75th
1996
1997
1998
1999
2000
2001
-5.0%
25th
-10.0%
* p < .05
†
p < .1
-15.0%
Effects of price competition on nurse staffing
Caveats/Limitations
HMO Penetration
2.479** (0.696)
• Changes over time in DRGs,
DRGs, coding, zip codes (but
smoothed/corrected to the extent possible)
HMO
Penetration*HHI
-3.192* (1.245)
• Limited to California – generalizable to other states?
* p < .01
• Limited to mortality–
mortality– generalizable to other quality
measures?
** p < .001
• Are there thresholds to staffingstaffing-quality relationship?
Conclusions
• Extent to which changes in RN staffing levels are
associated with lower mortality varies by condition.
• Increasing managed care penetration is associated
with higher RN staffing except in most competitive
markets.
• Limiting the number of patients per nurse may
improve quality outcomes.
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