articleAdjustment of nursing home quality indicators

Background: This manuscript describes a method for adjustment of nursing home quality indicators (QIs) defined using the Center for Medicaid & Medicare Services (CMS) nursing home resident assessment system, the Minimum Data Set (MDS). QIs are intended to characterize quality of care delivered in a facility. Threats to the validity of the measurement of presumed quality of care include baseline resident health and functional status, pattern of comorbidities, and facility case mix. The goal of obtaining a valid facility-level estimate of true quality of care should include adjustment for residentand facility-level sources of variability. Methods: We present a practical and efficient method to achieve risk adjustment using restriction and indirect and direct standardization. We present information on validity by comparing QIs estimated with the new algorithm to one currently used by CMS. Results: More than half of the new QIs achieved a "Moderate" validation level. Conclusions: Given the comprehensive approach and the positive findings to date, research using the new quality indicators is warranted to provide further evidence of their validity and utility and to encourage their use in quality improvement activities. Background In 1986, the Institute of Medicine Committee on Nursing Home Regulation made recommendations to Congress [1] to improve quality of care in nursing homes (NH). One was the systematic collection of standardized data on all NH residents: a minimum data set. Under this mandate, the U.S. Center for Medicare and Medicaid Services (CMS) implemented the Resident Assessment Instrument Minimum Data Set (MDS). All U.S. longterm care (LTC) facilities must complete standardized MDS assessments of each resident to participate. The MDS includes a clinical assessment of over 400 items covering demographics, medical condition, cognitive, physical, emotional and social functioning, medical diagnoses, therapies, treatments and medication use. The aggregation of individual MDS assessments into archives can be used to generate representative data sets used for prospective payment systems [2], monitoring [3,4] and improving [5-7] quality of care. Inspections were targeted based upon continuous collection of resident characteristics. Quality indicators (QIs), computed from residentlevel clinical data, are aggregated to facility level and used for targeting facilities for review [8,9]. Following its implementation in the United States, the MDS has been adopted in a number of other countries. The Canadian Institute for Health Information's (CIHI) Continuing Care Reporting System is the data warehouse for MDS data from eight Canadian provinces/territories. QIs, in raw form, are fractions derived from a numerator (number of residents with a particular outcome) and a denominator (number of residents at risk for the outcome and not otherwise excluded from the QI). QIs may include risk adjustment procedures, including restrictions or exclusions and covariate adjustment. QIs can be used by the facility to target care problems for continuous quality improvement efforts [10]. There are challenges in deriving QIs from resident assessment data. First, differences in types of residents living in facilities make direct comparisons difficult. Second, specification of the care recipient population whose outcome data reflect quality of care must be carefully considered. For example, some residents may be admitted for relatively short term rehabilitative care, short term respite care, or long term custodial care. The clinical trajectories of such different patient populations and differ* Correspondence: jones@hrca.harvard. edu 1 Institute for Aging Research, Hebrew SeniorLife, Boston MA, USA Full list of author information is available at the end of the article BioMed Central © 2010 Jones et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Jones et al. BMC Health Services Research 2010, 10:96 http://www.biomedcentral. com/1472-6963/10/96 Page 2 of 8 ences in their mix across facilities lead to different expectations regarding facility QI performance. Third, many relevant NH outcome measures are rare, resulting in imprecise estimates. Finally, although the MDS is a standardized data collection instrument, facilities may measure outcomes differently or with varying sensitivity [11].