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

BMC Research Notes

Peter G Norton¹  Jennifer A Knopp-Sihota³  Carole A Estabrooks² 

[1] Department of Family Medicine, University of Calgary, Calgary, Alberta T2N 4N1, Canada;Faculty of Nursing, University of Alberta, Edmonton, Alberta T6G 1C9, Canada;Faculty of Health Disciplines, Athabasca University, Edmonton, Alberta T5K 2J8, Canada

关键词: Quality indicators;    RAI-MDS;    Performance measurement;    Nursing home;   

Others  :  1140830
DOI  :  10.1186/1756-0500-6-460

 received in 2013-08-01, accepted in 2013-11-05,  发布年份 2013

【 摘 要 】

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.

【 授权许可】

   
2013 Estabrooks et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]Poss JW, Jutan NM, Hirdes JP, Fries BE, Morris JN, Teare GF, Reidel K: A review of evidence on the reliability and validity of Minimum Data Set data. Healthc Manage Forum 2008, 21(1):33-39.
• [2]Canadian Institute for Health Information: Continuing care reporting system (CCRS) quality indicators risk adjustment methodology. Ottawa, ON: Canadian Institute for Health Information; 2013.
• [3]Estabrooks CA, Hutchinson AM, Squires JE, Birdsell J, Cummings GG, Degner L, Morgan D, Norton PG: Translating Research in Elder Care: an introduction to a study protocol series. Implement Sci 2009, 4:51. BioMed Central Full Text
• [4]Estabrooks CA, Squires JE, Cummings GG, Teare GF, Norton PG: Study protocol for the Translating Research in Elder Care (TREC): building context - an organizational monitoring program in long-term care project (project one). Implement Sci 2009, 4:52. BioMed Central Full Text
• [5]Cranley LA, Norton PG, Cummings GG, Barnard D, Estabrooks CA: SCOPE: Safer Care for Older Persons (in residential) Environments: a study protocol. Implement Sci 2011, 6:71. BioMed Central Full Text
• [6]Hutchinson AM, Draper K, Sales AE: Public reporting of nursing home quality of care: lessons from the United States experience for Canadian policy discussion. Healthc Policy 2009, 5(2):87-105.
• [7]Totten A, Wagner J, Tiwari A, O’Haire C, Griffin J, Walker M: Public reporting as a quality improvement strategy. Rockville, MD: Agency for Healthcare Research and Quality; 2012.
• [8]Berg K, Mor V, Morris J, Murphy KM, Moore T, Harris Y: Identification and evaluation of existing nursing homes quality indicators. Health Care Financ Rev 2002, 23(4):19-36.
• [9]Wodchis WP, Teare GF, Anderson GM: Cost and quality: evidence from Ontario long term care hospitals. Med Care 2007, 45(10):981-988.
• [10]Jones RN, Hirdes JP, Poss JW, Kelly M, Berg K, Fries BE, Morris JN: Adjustment of nursing home quality indicators. BMC Health Serv Res 2010, 10:96. BioMed Central Full Text
• [11]Canadian Institute for Health Information. http://www.cihi.ca webcite
• [12]Cranley LA, Norton PG, Cummings GG, Barnard D, Batra-Garga N, Estabrooks CA: Identifying resident care areas for a quality improvement intervention in long-term care: a collaborative approach. BMC Geriatrics 2012, 12:59. BioMed Central Full Text
• [13]Poss J, Murphy KM, Woodbury MG, Orsted H, Stevenson K, Williams G, MacAlpine S, Curtin-Telegdi N, Hirdes JP: Development of the interRAI Pressure Ulcer Risk Scale (PURS) for use in long-term care and home care settings. BMC Geriatrics 2010, 10:67. BioMed Central Full Text
• [14]Poss JW, Hirdes JP, Fries BE, McKillop I, Chase M: Validation of resource utilization groups version III for home care (RUG-III/HC): evidence from a Canadian home care jurisdiction. Med Care 2008, 46(4):380-387.
• [15]Hirdes JP, Ljunggren G, Morris JN, Frijters DH, Finne Soveri H, Gray L, Bjorkgren M, Gilgen R: Reliability of the interRAI suite of assessment instruments: a 12-country study of an integrated health information system. BMC Health Serv Res 2008, 8:277. BioMed Central Full Text
• [16]Hirdes JP, Fries BE, Morris JN, Ikegami N, Zimmerman D, Dalby DM, Aliaga P, Hammer S, Jones R: Home care quality indicators (HCQIs) based on the MDS-HC. Gerontologist 2004, 44(5):665-679.
• [17]Boulkedid R, Abdoul H, Loustau M, Sibony O, Alberti C: Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review. PloS One 2011, 6(6):e20476.
• [18]Centers for Medicare & Medicaid Services: MDS 3.0 quality measures: user’s manual. Research Triangle Park, NC: RTI International; 2013.
• [19]Long-term care public reporting website technical report. http://www.hqontario.ca/public-reporting/long-term-care webcite
• [20]Simmons SF, Cadogan MP, Cabrera GR, Al-Samarrai NR, Jorge JS, Levy-Storms L, Osterweil D, Schnelle JF: The Minimum Data Set depression quality indicator: does it reflect differences in care processes? Gerontologist 2004, 44(4):554-564.
• [21]Hill-Westmoreland EE, Gruber-Baldini AL: Falls documentation in nursing homes: agreement between the minimum data set and chart abstractions of medical and nursing documentation. J Am Geriatr Soc 2005, 53(2):268-273.
• [22]Hutchinson A, Milke D, Maisey S, Johnson C, Squires J, Teare G, Estabrooks C: The Resident Assessment Instrument-Minimum Data Set 2.0 quality indicators: a systematic review. BMC Health Serv Res 2010, 10:166. BioMed Central Full Text
• [23]Simmons SF, Garcia ET, Cadogan MP, Al-Samarrai NR, Levy-Storms LF, Osterweil D, Schnelle JF: The Minimum Data Set weight-loss quality indicator: does It reflect differences in care processes related to weight loss? J Am Geriatr Soc 2003, 51(10):1410-1418.
• [24]Stevenson KB, Moore JW, Sleeper B: Validity of the Minimum Data Set in identifying urinary tract infections in residents of long-term care facilities. J Am Geriatr Soc 2004, 52(5):707-711.
• [25]Cadogan MP, Schnelle JF, Yamamoto-Mitani N, Cabrera G, Simmons SF: A Minimum Data Set prevalence of pain quality indicator: is It accurate and does It reflect differences in care processes? J Gerontol A Biol Sci Med Sci 2004, 59(3):M281-M285.