Staying the Course: Facility and Profession Retention

among Nursing Assistants in Nursing Homes

Sally C. Stearns, PhDLaura D’Arcy, MPA

The University of North Carolina at Chapel Hill

Support provided by National Institute on Aging

AcademyHealth 2008 Annual Research MeetingWashington, DC

June 9, 2008

Overview

• Nursing homes face substantial turnover in staff, especially nursing assistants (NAs)– US annual turnover rate for NAs: 71%– NA turnover costs $4 billion per year

• Why so costly?– Replacement costs, lost productivity,

compromised quality, and lowered morale

Prior Studies of Causes of Facility Turnover

• Early:– NAs concerned with job security, interactive aspects of

jobs, and growth potential (Atchinson 1998, Parsons et al 2003).

• Additional factors studied more recently:– NA turnover lower with higher administrative

expenditures and wages (Kash et al. 2006) – Castle and colleagues (2005, 2006, 2007):

Top management turnover, for-profit, larger size, work schedule, and lower staffing, quality, training, and benefits correlated with higher turnover

– Job satisfaction an important antecedent of intent to leave; both are important antecedents of turnover (Castle et al 2007 and Wagner 2007)

Definitions of Turnover

• Some distinctions important– Voluntary versus involuntary– May reflect elimination of poor performers– May indicate poor facility quality

• Turnover hard to measure in cross-sectional data sets. Alternatives are:– Job satisfaction– Intent to leave

Gaps in Literature

• Prior studies of facility turnover based on:– Facility data only– Small samples of NAs

• Limited study of some important factors– Injuries and devices related to lifting

patients

• No known prior studies of intent to stay in the NA profession

Research Question/Contributions

• Are the same factors associated with:– NA intent to leave current facility/job?– NA intent to leave NA profession?

• Specific focus on:– NA assessments of supervision/work

schedule, injury/training, pay/benefits– Unobserved facility factors (e.g.,

management quality)

• Use nationally representative NA survey

Figure 1: Conceptual Model

Job Satisfaction and Organizational Commitment

Intent to Leave

Current Job or Facility

NA Personal and Socio-economic Characteristics

NA Reported Job Characteristics• Supervision/Schedule• Training/Safety• Benefits

Turnover

(Facility and NA Profession)

Facility & Area Characteristics

(Observed and unobserved)

Intent to Leave

NA Profession

Data: National Nursing Assistant Survey 2004

• NNAS 2004 conducted by NCHS provides data on:– what draws people to NA careers and to work in nursing homes– what contributes to satisfaction and likelihood of staying in jobs

• Sample from 2004 National Nursing Home Survey– 790 homes (out of 1500) selected to participate in the NNAS– 582 homes (76%) provided contact information for 4,542 NAs– 3,017 NAs (71%) completed an interview– Combined response rate of 53%– Missing data reduced analysis sample to 2,328 observations

• NNAS – Panel of multiple NA respondents per facility strengthens analysis– Public use versions NNHS and NNAS can not be merged due to

confidentiality

Dependent Variables

• Three dichotomous intent to leave measures

– Intent to leave facility/job (2 measures)Broad: NA is very or somewhat likely to leave

current job in next yearStrong: Same as above plus currently looking

for a job

– Intent to leave profession: NA does not expect next job to be as a NABut could not tell if leaving health professions

Key Explanatory Variables

• NA assessments of:– Supervisor quality, whether NA is respected, whether

NA has enough time for duties– Quality of training, input into training topics, injury

experience, and lifting equipment availability– Benefits (wages; paid time off for holidays,

vacation/personal days, sick days; HI available)

• Observed facility characteristics– Bedsize, ownership, urban/rural

• Facility fixed effects for unobserved facility characteristics (average 4 NAs per facility)

Other Controls

• Income• Age• Gender• Race/ethnicity• Education• Marital Status• Young children at home• Citizenship• Full time vs. part time

Methods

• OLS (Linear probability models) instead of logit for final models

• Tested OLS models with and without facility fixed effects

• Used survey weights and robust standard errors

Descriptive Statistics

• Intent to Leave– Broad intent to leave facility: 43%– Strong intent to leave facility: 20%– Intent to leave profession: 48%

• Surprisingly little correlation between intent to leave facility/job and profession

• Surprisingly high within-facility variation in NA reports of benefits, scheduling, safety, etc.

Main Results: Impacts on Intent to Leave

Broad Facility Strong Facility Profession

Good relationship with supervisor Reduce Reduce

Lifting devices always available Reduce Reduce

Hourly wage Reduce Reduce

Paid time for personal days Reduce Reduce

White Increase

Younger age Increase Reduce

Widowed (vs married) Increase

High income (versus low) Increase

GED/HS degree (vs no degree)

Some college (vs no degree) Increase Increase

For profit Reduce

Facility FE (observed & unobserved) Important Important

Summary of Results

• Facility and profession retention affected by substantially different factors– Facility policies and NA perceptions of job

aspects critical for facility retention– Profession retention associated only with socio-

demographic factorsLack of effect of wages due to study design?

• Facility fixed effects– Only significant in intent to leave facility

analysis– Reflect both facility and area characteristics

Policy Implications

• Facilities can undertake specific actions to reduce their turnover (intent to leave)– Injury prevention and training– Pay and flexible holidays– Important unmeasured facility policies

• Profession retention more encompassing– Need to make profession financially

competitive– Within-profession promotion and

responsibility undoubtedly important