Minimum Data Set Changes in Health, End‐Stage Disease and Symptoms and Signs Scale: A Revised Measure to Predict Mortality in Nursing Home Residents

• Autores: Jessica A. Ogarek, Ellen M. McCreedy, Kali S. Thomas, Joan M. Teno, Pedro L. Gozalo
• Localización: Journal of the American Geriatrics Society, ISSN 0002-8614, Vol. 66, Nº. 5, 2018, págs. 976-981
• Idioma: inglés
• Enlaces
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• Resumen

  • Objectives To revise the Minimum Data Set (MDS) Changes in Health, End‐stage disease and Symptoms and Signs (CHESS) scale, an MDS 2.0‐based measure widely used to predict mortality in institutional settings, in response to the release of MDS 3.0.

    Design Development of a predictive scale using observational data from the MDS and Medicare Master Beneficiary Summary File.

    Setting All Centers for Medicare and Medicaid Services (CMS)‐certified nursing homes in the United States.

    Participants Development cohort of 1.3 million Medicare beneficiaries newly admitted to a CMS‐certified nursing home during 2012. Primary validation cohort of 1.2 million Medicare recipients who were newly admitted to a CMS‐certified nursing home during 2013.

    Measurements Items from the MDS 3.0 assessments identified as likely to predict mortality. Death information was obtained from the Medicare Master Beneficiary Summary File.

    Results MDS‐CHESS 3.0 scores ranges from 0 (most stable) to 5 (least stable). Ninety‐two percent of the primary validation sample with a CHESS scale score of 5 and 15% with a CHESS scale of 0 died within 1 year. The risk of dying was 1.63 times as great (95% CI=1.628–1.638) for each unit increase in CHESS scale score. The MDS‐CHESS 3.0 is also strongly related to hospitalization within 30 days and successful discharge to the community. The scale predicted death in long‐stay residents at 30 days (C=0.759, 95% confidence interval (CI)=0.756–0.761), 60 days (C=0.716, 95% CI=0.714–0.718) and 1 year (C=0.655, 95% CI=0.654–0.657).

    Conclusion The MDS‐CHESS 3.0 predicts mortality in newly admitted and long‐stay nursing home populations. The additional relationship to hospitalizations and successful discharges to community increases the utility of this scale as a potential risk adjustment tool.