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Future Directions for Residential Long-Term Care Health Services Research

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Summary

Expert Meeting, October 14-15, 1999


In October 1999, long-term care experts met to help guide the long-term care research agenda and provide advice on alternative approaches to data collection for the Agency for Healthcare Research and Quality (AHRQ, then the Agency for Health Care Policy and Research). The meeting was cosponsored by AHRQ's Center for Organization and Delivery Studies and Center for Cost and Financing Studies.

Select to access the Full Text of the Expert Meeting Summary.


By William D. Spector, D.E.B. Potter, Jan De La Mare

To help AHRQ develop its long-term care agenda on data collection, meeting participants were asked to list their top research and policy questions concerning residential long-term care. Their responses reflected a number of concerns in six major categories:

  • Cost-effectiveness.
  • Equity/access.
  • Financial and market incentives.
  • Consumer issues.
  • Quality assurance.
  • Methodology.

Expert opinion was solicited about quality measures and associated risk factors that could be used to monitor changes in quality over time. Participants generally conceptualized residential long-term care as all of the care provided in residential care settings (e.g., personal care, the quality of life associated with the home, the environment, and acute and preventive care). They included both quality of care and quality of life.

Participants discussed outcome, process, and structural measures, although they viewed process as more difficult to measure. Experts agreed that quality-of-life indicators and evaluations of clinical management are high-priority areas needing more methodological development.

They also felt that for an outcome measure to be used as a quality indicator, evidence must show that the outcome is malleable and that a facility has control over changing that outcome. If a process or structural measure is used as a quality indicator, evidence must show that those measures affect resident outcomes.

During the morning of day two, presenters highlighted major features of national long-term care surveys and administrative data systems and discussed Departmental goals associated with data integration. Participants discussed pros and cons of person-based versus facility-based sampling methods and what each design would imply for the various research goals. They generally agreed that each approach has unique strengths. There were concerns that when integrating data, some of these strengths might be lost, especially in analyzing subpopulations and their transitions of care, outcomes, and long-term care expenditures.

Participants recommended that the following data be collected:

  • Demographic and health characteristics of residents.
  • Facility characteristics, including services provided and hotel-type amenities offered.
  • Services received by each resident.
  • Health outcomes.
  • Expenditures and sources of payment, including costs and revenues. Market information and prices.
  • Longitudinal information about the transitions of residents to and between health care settings.

During the afternoon of day two, discussion focused on alternative strategies for data collection, leading to the following consensus recommendations:

  • Develop a facility frame that includes the full continuum of long-term care facilities.
  • Collect data on persons in the community and all types of residential settings, not just nursing homes.
  • Obtain longitudinal information about changes in health status and care received across settings.
  • Use both facility-based and person-based sampling designs.
  • Improve facility and market data.
  • Select a sufficient sample size to study subpopulations.

Participants discussed alternative ways to reach these goals, including:

  • How to construct a comprehensive frame, increase the Medicare Current Beneficiary Survey (MCBS) sample size of persons in long-term care settings.
  • Conduct specialized periodic surveys.
  • Explore the feasibility of supplementing survey data with administrative data.

Current as of October 2000

 

The information on this page is archived and provided for reference purposes only.

 

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