The Impact of Markets, Information and Regulation on NH Quality

1. The Impact of Markets, Information and Regulation on NH Quality Farida K. Ejaz, Ph.D., L.I.S.W.1 & Jane Straker, Ph.D.2 Presented at AcademyHealth’s Annual Research Meeting (ARM) San Diego, 2004 Margaret Blenkner Research Institute, Benjamin Rose, 850 Euclid Avenue, Suite 1100 Cleveland, OH 44114-3301 Fejaz@benrose.org 216.373.1660 Scripps Gerontology Center, 396 Upham Hall, Miami University, Oxford,OH 45056 strakejk@muohio.edu 513.529.5949

2. Overview of Presentation • Historical overview of key sources of NH quality information; • Impact of NH quality information and identify limitations; • Current research*; • Identify user-friendly presentations of data for quality improvement*. *Funded by the Commonwealth Foundation.

3. History of NH Quality Information • 1959: Senate subcommittee identifies poor NH care (Morris et al, 1990). • 1970’s: HE&W study confirms that compliance with regulations vary widely. • 1984: Smith & Heckler confirm that Sec of HHS is responsible for NHs to meet regulatory standards. • 1986: IOM report on NH quality is published. • 1987: NH Reform Law (OBRA).

4. Changes in the Certification System • Prior to 1985: Certification focused on structure & process (policies/procedures). • After OBRA 87: The focus shifted to resident outcomes. • OSCAR: Stems from the annual survey and includes facility deficiencies, staffing, and resident characteristics. • Complaint surveys: Data collected by surveyors as a result of a complaint.

5. Focus on Resident Outcomes • RAI: OBRA also mandated the development of a uniform resident assessment instrument. • MDS: Implemented 10/1990; collected quarterly or during a significant change in the resident’s condition. • Cost Reports: MDS also used to reimburse NHs based on facility costs and resident characteristics (RUGs/case-mix scores).

6. QIs & QMs from the MDS • QIs and the QMs • Late 1990s: 24 QIs were developed to help NHs identify areas for quality improvement; and, to help surveyors identify residents to include in their state surveys. • 2002: 14 quality measures (QMs) released for public reporting & quality improvement. - QMs generally for consumers - QIs are for nursing homes and surveyors.

7. Impact of OBRA 87 • Wealth of Information: OSCAR, RAIs/MDS, Cost Reports, the QIs, and QMs. • 2001 IOM report: Improvements in NH quality of care (e.g. physical restraints). • Serious problems still remain (pain, pressure sores, malnutrition & urinary incontinence). • Quality of life of residents has also shown some but not remarkable improvement.

8. Limitations & Gaps in the Data • Data are received piece meal. • No one data source is enough to provide a holistic picture of quality. • Discrepancies in data sources often stem from different time referents & risk adjustment methods. • Relationships between the various data sources relatively unexamined.

9. Commonwealth Fund Grant on Improving the NH Quality of Care Study has two major goals: • To examine the relationships between various data sources in Ohio. • Examine provider preferences for receiving such data to help improve NH quality.

10. Steps to Achieve Goals • Obtained permission to acquire 10 datasets for research purposes. • Computed facility level data for datasets in which only the individual/resident level data were available. • Example: For each item in the resident and family satisfaction surveys, 4 variables were computed: 1) mean, 2) median, 3) modal facility score, and 4) the % of negative responses. Overall measures of satisfaction also created.

11. Datasets that were Merged • MDS 2.0 (last quarter of 2001 aggregated to facility level). • OSCAR: Deficiencies and some facility characteristics. • Complaint surveys. • Ohio Medicaid Cost Report. • Annual Survey of Long-Term Care Facilities (ASLTCF). Collected from about 90% of Ohio’s NHs regarding characteristics, occupancy, turnover, charges and reimbursement.

12. Merged Datasets cont.. • Resident Satisfaction Surveys. • Family Satisfaction Surveys. • QMs • OLTCCG • 2000 County Census data. Census county information was used to provide information about each facility’s nursing home market (competitiveness, capacity per 1,000 older persons, etc.).

13. Ohio’s Mega Quality Information Dataset • Result: A Mega dataset on quality information for Ohio’s NHs. • Has information on over 1,000 (facilities) cases and 1,930 variables. • However, only about 750 facilities have data from 8 or more sources.

14. Outcomes from the Mega Dataset • Models examining the relationships between key indicators of quality from the various datasets have been developed. • Challenge to develop models that are simple & examine relationships between 2-3 variables. • Models currently being tested by statisticians at the Scripps Gerontology Center.

15. Challenges Faced in Merging the Datasets • Time-consuming. • Tracking changes in a facility id number. • Examining comparable data elements from one source to another. • The algorithms for computing federal QI or the QMs unavailable so QMs downloaded from NH Compare website.

16. Next Steps • Various reports demonstrating basic (simple) relationships will be developed. • Focus groups to critique reports. • Explore whether technical assistance is needed in interpreting reports. • Two focus groups: HealthRays Alliance/AOPHA; and OHCA.

17. Important Contributions of this Work • Contribute to knowledge about the information needed and found useful by nursing home staff. • The Mega Quality Information dataset sets a new standard for NH quality. • Previous research on NH quality relied on one or two sources of data. • Our success may inspire other researchers/states to do similar work.