Practice sensitive quality indicators in RAI-MDS 2.0 nursing home data

Carole A. Estabrooks, Jennifer A. Knopp-Sihota, Peter G. Norton

Research output: Contribution to journalJournal Articlepeer-review

30 Citations (Scopus)

Abstract

Background: In recent years, improving the quality of care for nursing home residents has generated a considerable amount of attention. In response, quality indicators (QIs), based on available evidence and expert consensus, have been identified within the Resident Assessment Instrument - Minimum Data Set 2.0 (RAI-MDS 2.0), and validated as proxy measures for quality of nursing home care. We sought to identify practice sensitive QIs; that is, those QIs believed to be the most sensitive to clinical practice. Method. We enlisted two experts to review a list of 35 validated QIs and to select those that they believed to be the most sensitive to practice. We then asked separate groups of practicing physicians, nurses, and policy makers to (1) rank the items on the list for overall "practice sensitivity" and then, (2) to identify the domain to which the QI was most sensitive (nursing care, physician care, or policy maker). Results: After combining results of all three groups, pressure ulcers were identified as the most practice sensitive QI followed by worsening pain, physical restraint use, the use of antipsychotic medications without a diagnosis of psychosis, and indwelling catheters. When stratified by informant group, although the top five QIs stayed the same, the ranking of the 13 QIs differed by group. Conclusions: In addition to identifying a reduced and manageable set of QIs for regular reporting, we believe that focusing on these 13 practice sensitive QIs provides both the greatest potential for improving resident function and slowing the trajectory of decline that most residents experience.

Original languageEnglish
Article number460
JournalBMC Research Notes
Volume6
Issue number1
DOIs
Publication statusPublished - 2013

Keywords

  • Nursing home
  • Performance measurement
  • Quality indicators
  • RAI-MDS

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