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      Temporal and Geographic variation in the validity and internal consistency of the Nursing Home Resident Assessment Minimum Data Set 2.0

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          Abstract

          Background

          The Minimum Data Set (MDS) for nursing home resident assessment has been required in all U.S. nursing homes since 1990 and has been universally computerized since 1998. Initially intended to structure clinical care planning, uses of the MDS expanded to include policy applications such as case-mix reimbursement, quality monitoring and research. The purpose of this paper is to summarize a series of analyses examining the internal consistency and predictive validity of the MDS data as used in the "real world" in all U.S. nursing homes between 1999 and 2007.

          Methods

          We used person level linked MDS and Medicare denominator and all institutional claim files including inpatient (hospital and skilled nursing facilities) for all Medicare fee-for-service beneficiaries entering U.S. nursing homes during the period 1999 to 2007. We calculated the sensitivity and positive predictive value (PPV) of diagnoses taken from Medicare hospital claims and from the MDS among all new admissions from hospitals to nursing homes and the internal consistency (alpha reliability) of pairs of items within the MDS that logically should be related. We also tested the internal consistency of commonly used MDS based multi-item scales and examined the predictive validity of an MDS based severity measure viz. one year survival. Finally, we examined the correspondence of the MDS discharge record to hospitalizations and deaths seen in Medicare claims, and the completeness of MDS assessments upon skilled nursing facility (SNF) admission.

          Results

          Each year there were some 800,000 new admissions directly from hospital to US nursing homes and some 900,000 uninterrupted SNF stays. Comparing Medicare enrollment records and claims with MDS records revealed reasonably good correspondence that improved over time (by 2006 only 3% of deaths had no MDS discharge record, only 5% of SNF stays had no MDS, but over 20% of MDS discharges indicating hospitalization had no associated Medicare claim). The PPV and sensitivity levels of Medicare hospital diagnoses and MDS based diagnoses were between .6 and .7 for major diagnoses like CHF, hypertension, diabetes. Internal consistency, as measured by PPV, of the MDS ADL items with other MDS items measuring impairments and symptoms exceeded .9. The Activities of Daily Living (ADL) long form summary scale achieved an alpha inter-consistency level exceeding .85 and multi-item scale alpha levels of .65 were achieved for well being and mood, and .55 for behavior, levels that were sustained even after stratification by ADL and cognition. The Changes in Health, End-stage disease and Symptoms and Signs (CHESS) index, a summary measure of frailty was highly predictive of one year survival.

          Conclusion

          The MDS demonstrates a reasonable level of consistency both in terms of how well MDS diagnoses correspond to hospital discharge diagnoses and in terms of the internal consistency of functioning and behavioral items. The level of alpha reliability and validity demonstrated by the scales suggest that the data can be useful for research and policy analysis. However, while improving, the MDS discharge tracking record should still not be used to indicate Medicare hospitalizations or mortality. It will be important to monitor the performance of the MDS 3.0 with respect to consistency, reliability and validity now that it has replaced version 2.0, using these results as a baseline that should be exceeded.

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          Most cited references45

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          MDS Cognitive Performance Scale.

          Chronic cognitive impairment is a major problem in U.S. nursing homes, yet traditional assessment systems in most facilities included only limited information on cognitive status. Following the Congressional mandate in the Omnibus Reconciliation Act of 1987 (OBRA '87), U.S. nursing homes now complete the Minimum Data Set (MDS), a standardized, comprehensive assessment of each resident's functional, medical, psychosocial, and cognitive status. We designed a Cognitive Performance Scale (CPS) that uses MDS data to assign residents into easily understood cognitive performance categories. Information was drawn from three data sets, including two multistate data sets constructed for the Health Care Financing Administration. The prevalence and reliability of the MDS cognitive performance variables were established when assessed by trained nursing personnel. Five selected MDS items were combined to create the single, functionally meaningful seven-category hierarchical Cognitive Performance Scale. The CPS scale corresponded closely with scores generated by the Mini-Mental State Examination and the Test for Severe Impairment, nursing judgments of disorientation, and neurological diagnoses of Alzheimer's disease and other dementias. The new CPS provides a functional view of cognitive performance, using readily available MDS data. It should prove useful to clinicians and investigators using the MDS to determine a resident's cognitive assets.
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            Designing the national resident assessment instrument for nursing homes.

            In response to the Omnibus Reconciliation Act of 1987 mandate for the development of a national resident assessment system for nursing facilities, a consortium of professionals developed the first major component of this system, the Minimum Data Set (MDS) for Resident Assessment and Care Screening. A two-state field trial tested the reliability of individual assessment items, the overall performance of the instrument, and the time involved in its application. The trial demonstrated reasonable reliability for 55% of the items and pinpointed redundancy of items and initial design of scales. On the basis of these analyses and clinical input, 40% of the original items were kept, 20% dropped, and 40% altered. The MDS provides a structure and language in which to understand long-term care, design care plans, evaluate quality, and describe the nursing facility population for planning and policy efforts.
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              Refining a case-mix measure for nursing homes: Resource Utilization Groups (RUG-III).

              A case-mix classification system for nursing home residents is developed, based on a sample of 7,658 residents in seven states. Data included a broad assessment of resident characteristics, corresponding to items of the Minimum Data Set, and detailed measurement of nursing staff care time over a 24-hour period and therapy staff time over a 1-week period. The Resource Utilization Groups, Version III (RUG-III) system, with 44 distinct groups, achieves 55.5% variance explanation of total (nursing and therapy) per diem cost and meets goals of clinical validity and payment incentives. The mean resource use (case-mix index) of groups spans a nine-fold range. The RUG-III system improves on an earlier version not only by increasing the variance explanation (from 43%), but, more importantly, by identifying residents with "high tech" procedures (e.g., ventilators, respirators, and parenteral feeding) and those with cognitive impairments; by using better multiple activities of daily living; and by providing explicit qualifications for the Medicare nursing home benefit. RUG-III is being implemented for nursing home payment in 11 states (six as part of a federal multistate demonstration) and can be used in management, staffing level determination, and quality assurance.
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                Author and article information

                Journal
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central
                1472-6963
                2011
                15 April 2011
                : 11
                : 78
                Affiliations
                [1 ]Department of Community Health and Center for Gerontology & Health Care Research, Brown University Medical School, Box G-S121, Providence, Rhode Island, USA
                [2 ]Center for Gerontology & Health Care Research and, Department of Community Health, Brown University Medical School, Box G-S121, Providence, Rhode Island, USA
                [3 ]Department of Community Health, Brown University Medical School, Box G-S121, Providence, Rhode Island, USA
                Article
                1472-6963-11-78
                10.1186/1472-6963-11-78
                3097253
                21496257
                32d223dc-b3a2-404b-9f51-72db4eb01254
                Copyright ©2011 Mor 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.

                History
                : 23 August 2010
                : 15 April 2011
                Categories
                Research Article

                Health & Social care
                Health & Social care

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