Factors Influencing Nursing Home Response to Quality Measure Publication

Jacqueline Zinn, Ph.D.Temple University

Dana Mukamel, Ph.D.University of California, Irvine

William Spector, Ph.D.Agency for Healthcare Research and Quality

David L. Weimer, Ph.DUniversity of Wisconsin

This research was funded through National Institute of Aging Grant AG023177

Background

• Since Nov 2002 CMS has published a nursing home quality report card currently providing information on 19 quality measures (QMs)

• Motivation of Nursing Home Compare (NHC) is to generate positive incentives for quality improvement

• Some QMs show improvement, others not• Nursing homes appear to be selectively

responding to public disclosure of quality performance

Research Objectives

• To determine whether nursing homes were motivated to invest substantial resources in staffing and equipment in response to publication

• To investigate the factors associated with nursing home infrastructure investments in response to QM publication

Resource Dependence Theory

• Organizational decision-making with respect to the allocation of resources may reflect accommodation intended to secure a stable flow of resources from the environment

• NHC publication changed the environment in ways that could affect the ability to attract and retain residents

• Nursing homes would have the incentive to address performance expectations of resource providers potentially influenced by public reporting

• Nursing homes will be more likely to take resource intensive actions in response to QM publication to the extent they are perceived to influence– H1: professional referrals– H2: choices made by residents and significant others– H3: the state survey process

• H4: Nursing homes will be more likely to take resource intensive actions in response to QM publication in more competitive markets

• H5: Having a managed care contract will make it less likely that nursing homes will take resource intensive actions in response to QM publication

Hypotheses

Methods: data and sample

• Nursing home administrators surveyed in 2007 on whether and how they responded to publication– National 10% random sample (1407 facilities)– 38.3% response rate (results weighted for non-response)

• Respondents more likely than non-respondents to be non-profit and located in West North Central states; no differences on QMs or facility characteristics

• Merged with data on quality measures and facility characteristics from Nursing Home Compare

Methods: dependent variable measurement

• All dependent variables dichotomous (0,1), indicating whether or not nursing home did the following in response to QM publication:– Hired a new nursing director (13%) – Hired a new medical director (7%)– Hired additional care-giving staff (17%) – Increased staff wages (20%)– Took other initiatives to hire/retain staff (12%)– Purchased new equipment/technology (13%)

Methods: independent variable measurement

• Dichotomous independent variables (0,1)– QMs influence professional referrals (50%)– QMs influence choice of nursing home facility (56%)– QMs influence state survey process (44%)– Perceived highest competition in local market (45%)– Facility contracts with managed care organization(s)

(51%)

Methods: control variable measurement

• Number of quality measures in bottom 20%of state distribution: mean = 2.77 SD = (1.98)

• Dichotomous controls (0,1)– Belief that QMs reflect true quality of care (57%)– Quarterly review of QMs (%)– For-profit Status (57%)– Chain Affiliation (50%)– Strategic type

• Prospector (22%)• Defender (37%)• Analyzer (36%)• Reactor (05%)

Results

• Logistic regression used to estimate models• H1: perception that reported QMs influence referrals:

– increased likelihood of hiring a new medical or nursing director by over 250%

– doubled odds of taking other hiring/retention initiatives – more than doubled odds of purchasing new technology/equipment

• H2: belief that QMs influence choice of nursing home associated with a two-fold increase in likelihood of hiring new staff

• H3: perceived influence on the state survey process:– doubled odds of hiring new nursing director – more than tripled odds of hiring new medical director– more than doubled odds of hiring new staff– Increased likelihood of increasing wages by 51%– Increased likelihood of purchasing new equipment by 71%

Results

• H4 not supported, no association with perceived competition• H5: having a managed care contract associated with a

– 38% decrease in likelihood of hiring a new nursing director– 63% decrease in likelihood of hiring a new medical director– 32% decrease in likelihood of hiring new staff

• Neither for-profit status nor chain affiliation associated with measures of resource allocation

• Poorer quality associated with a 12% increase in likelihood of increasing wages

• Belief that reported QMs are true reflections of quality:– Doubled odds of hiring new medical director– Increased likelihood of hiring more clinical staff by 63% and

increasing wages by 87%– Increased likelihood of other hiring initiatives 69% and

equipment purchase 89%

Results

• Quarterly review of QMs:– Doubled odds of hiring new nursing director– More than tripled odds of hiring new medical director– Increased likelihood of purchasing new equipment by 63%

• Analyzer status almost tripled odds of hiring more staff

Conclusions

• A substantial proportion of nursing homes now perceive that the NHC report card influences professional referrals, consumer choice and the state survey regulatory process

• As theory predicts, action taken, but different actions for different constituents

• Most nursing homes (77%) report high levels of competition

• Reliable sources of admissions from MCOs may bypass professional referral sources

Policy Implications

• Publication appears to be having the desired effect of motivating facilities to make investments to improve quality scores

• Because this motivation appears to be based on perceived influence on key constituencies, suggests efforts to increase awareness may increase nursing home effectiveness

• Additional research directed at understanding the relationship between specific investments and resident outcomes is needed