Geriatric Nursing
Volume 28, Issue 6 , Pages 377-386 , November 2007

Implementation of the Resident Assessment Instrument/Minimum Data Set in the Nursing Home as Organization: Implications for Quality Improvement in RN Clinical Assessment

References 

  1. Mor V. A comprehensive clinical assessment tool to inform policy and practice: applications of the Minimum Data Set. Med Care. 2004;42:III50–III59
  2. Morris JA, Hawes C, Fries BE, et al. Designing the national resident assessment instrument for nursing homes. Gerontologist. 1990;30:293–302
  3. Arling G, Kane RL, Lewis T, et al. Future development of nursing home quality indicators. Gerontologist. 2005;45:147–156
  4. Shortell SM, Bennett CL, Byck GR. Assessing the impact of continuous quality improvement on clinical practice: what it will take to accelerate progress. Milbank Quarterly. 1998;76:593–624
  5. Grol R, Wensing M, Eccles M. Improving patient care: the implementation of change in clinical practice. London: Elsevier, Butterworth, Heinemann; 2003;
  6. Phillips CD. Yali’s question and the study of nursing homes as organizations. Gerontologist. 2002;42:154–155
  7. Morris JN, Nonemaker S, Murphy K, et al. A commitment to change: revision of HCFA’s RAI;1997;45:1011-16.
  8. Saliba D, Maslow K. Revising the MDS to increase nursing home resident voice. 58th Annual Scientific Meeting of the Gerontological Society of America. Nov. 18-22, Orlando, Florida. p. 373. 2005;
  9. Centers for Medicare and Medicaid Services. Revised long-term care resident assessment instrument user’s manual (version 2.0). Baltimore: Author; 2002;
  10. Dellefield ME. Interdisciplinary care planning and the written care plan in nursing homes: a critical review. Gerontologist. 2006;46:128–133
  11. Fries BE, Schneider DP, Foley WJ, et al. Refining a case-mix measure for nursing homes: resource utilization groups (RUG-III). Med Care. 1994;32:668;5
  12. Centers for Medicare and Medicaid Services. http://new.cms.hhs.gov/SNFPPS/Cited December 20, 2006
  13. Zimmerman DR. Improving nursing home quality of care through outcomes data: the MDS quality indicators. Int J Geriatr Psychiatry. 2002;18:250–257
  14. Arling GK, Kane RL, Lewis T, et al. Future development of nursing home quality indicators. Gerontologist. 2005;45:147–156
  15. Bates-Jensen BM, Simmons SF, Schnelle J, et al. Evaluating the accuracy of minimum data set bed mobility ratings against independent performance assessments: systematic error and directions for improvement. Gerontologist. 2005;45:731–738
  16. Lum TY, Lin W, Kane RL. Use of proxy respondents and accuracy of minimum data set assessments of activities of daily living. J Gerontol A Biol Sci Med Sci. 2005;60:654–659
  17. Schnelle JF, Bates-Jensen BM, Chu L, et al. Accuracy of nursing home medical record information about care-process delivery: implications for staff management and improvement. Am J Geriatr Soc. 2004;52:1378–1383
  18. Schnelle JF, Cadogan MP, Yoshii J, et al. The minimum data set urinary incontinence quality indicators: do they reflect differences in care processes related to incontinence?. Med Care. 2003;41:909–922
  19. Bates-Jensen BM, Cadogan M, Osterweil D, et al. The minimum data set pressure ulcer indicator: does it reflect differences in care processes related to pressure ulcer prevention and treatment in nursing homes. J Am Geriatr Soc. 2003;51:1203–1212
  20. Simmons SF, Garcia ET, Cadogan MP, et al. The minimum data set weight-loss quality indicator: does it reflect differences in care processes related to weight loss?. J Am Geriatr Soc. 2003;51:1410–1418
  21. Cadogan MP, Schnelle JF, Yamamoto-Mitani N, et al. 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;59:281–285
  22. Schnelle JF, Bates-Jensen BM, Levy-Storms L, et al. The minimum data set prevalence of restraint quality indicator: does it reflect differences in care?. Gerontologist. 2004;44:245–255
  23. Simmons SF, Cadogan MP, Cabrera GR, et al. The minimum data set depression quality indicator: does it reflect differences in care processes?. Gerontologist. 2004;44:554–564
  24. Topping S, Hernandez SR. Health care strategy research, 1985-1990: a critical review. Med Care Rev. 1991;48:47–89
  25. Kane RL. The implications of assessment. J Gerontol. 1993;48(Special Issue):27–31
  26. American Health Care Association. The long-term care survey. Washington, DC: American Health Care Association; 2005;
  27. Institute of Medicine (US). Nursing staff in hospitals and nursing homes: is it adequate?. Washington, DC: National Academy Press; 1996;
  28. Center for health Workforce Distribution Studies University of California San Francisco. Supply, demand, and use of licensed practical nurses. Washington, DC: Department of Health and Human Services; 2004;Grant No. 1-U79-HP-00032-01
  29. Mueller C. The legalities of nursing supervision: the interchangeability of the RN and LPN role in nursing homes. The 58th Annual Scientific Meeting of the Gerontological Society of America; Nov. 18-22, 2005; Orlando, Florida. p. 387.
  30. United States General Accounting Office. Nursing home resident assessment data. Washington, DC: Author; 2001;
  31. Harrington C, Carrillo H, Mullan JH. Nurse staffing in nursing homes in the United States. J Gerontol Nurs. 2005;31:18–23
  32. Hawes C, Morris JN, Phillips CD, et al. Reliability estimates for the minimum data set for nursing home resident assessment and care screening (MDS). Gerontologist. 1995;35:172–178
  33. Fries BE, Hawes C, Morris JN, et al. Effect of the national resident assessment instrument on selected health conditions and problems. Am J Geriatr Soc. 1997;45:994–1001
  34. Hawes C, Mor V, Phillips CD, et al. The OBRA-87 nursing home regulations and implementation of the resident assessment instrument: effects on process quality. Am J Geriatr Soc. 1997;45:977–985
  35. Mor V, Intrator O, Fries BE, et al. Changes in hospitalization associated with introducing the resident assessment instrument. Am J Geriatr Soc. 1997;45:1002–1010
  36. Phillips CD, Morris JN, Hawes C, et al. Association of the resident assessment instrument (RAI) with changes in function, cognition, and psychosocial status. Am J Geriatr Soc. 1997;45:986–993
  37. Casten R, Lawton MP, Parmelee PA, et al. Psychometric characteristics of the minimum data set I: confirmatory factor analysis. Gerontologist. 1998;46:726–735
  38. Lawton MP, Casten R, Parmelee PA, et al. Psychometric characteristics of the minimum data set II: validity. Gerontologist. 1998;46:736–744
  39. Snowdon M, McCormick W, Russo J, et al. Validity and responsiveness of the minimum data set. Am J Geriatr Soc. 1999;47:1000–1004
  40. Crooks VC, Schnelle JF, Ouslander JP, et al. Use of the minimum data set to rate incontinence severity. Am J Geriatr Soc. 1995;43:1363–1369
  41. Gambassi G, Landi F, Peng L, et al. Validity of diagnostic and drug data in standardized nursing home resident assessments: potential for geriatric pharmacoepidemiology. Med Care. 1998;36:167–179
  42. Mentes J, Culp K, Maas M, et al. Acute confusion indicators: risk factors and prevalence using MDS data. Res Nurs Health. 1999;22:95–105
  43. Culp K, Mentes JC, McConnel ES. Studying acute confusion in long-term care: clinical investigation or secondary data analysis using the minimum data set?. J Gerontol Nurs. 2001;41–48April
  44. Hendrix C, Sakauye KM, Karabatsos G, et al. The use of the minimum data set to identify depression in the elderly. J Am Med Dir Assoc. 2003;308–312November/December
  45. Stevenson KB, Moore JW, Sleeper B. Validity of the minimum data set in identifying urinary tract infections in residents of long-term care facilities. Am J Geriatr Soc. 2004;52:707–711
  46. Avidan AY, Fries BE, James ML, et al. Insomnia and hypnotic use, recorded in the minimum data set as predictors of falls and hip fractures in Michigan nursing homes. Am J Geriatr Soc. 2005;53:955–962
  47. Morris JN, Fries BE, Mehr DR, et al. MDS cognitive performance scale. J Gerontol A Biol Sci Med Sci. 1994;49:M174–M182
  48. Mor V, Branco K, Fleishman J, et al. The structure of social engagement among nursing home residents. J Gerontol B Psychol Sci Med Sci. 1995;50B:P1–P8
  49. Hartmaier SL, Sloane PD, Guess HA, et al. Validation of the minimum data set cognitive performance scale: agreement with the mini-mental state examination. J Gerontol A Biol Sci Med Sci. 1995;M128–M133
  50. Williams BC, Li Y, Fries BE, Warren RL. Predicting patient score between the functional independence measure and the minimum data set: development and performance of a FIM-MDS “crosswalk.”. Arch Phys Med Rehabil. 1997;78:48–54
  51. Fries BE, Simon SE, Morris JN, et al. Pain in U.S. nursing homes: validating a pain scale for the minimum data set. Gerontologist. 2001;41:173–179
  52. Hides JP, Frijters DH, Teare GF. The MDS-CHESS scale: a new measure to predict mortality in institutionalized older people. Am J Geriatr Soc. 2003;51:96–100
  53. Fries BE, Schroll M, Hawes C, et al. Approaching cross-national comparisons of nursing home residents. Age Ageing. 1997;26(S2):13–18
  54. Ikegami N, Morris JN, Fries BE. Low-care cases in long-term care settings: variations among nations. Age Ageing. 1997;26(Suppl 2):67–71
  55. Hill A, Yu W. Evaluation of the VA nursing home resident assessment instrument minimum data set: resource utilization group III in FY2001 and FY 2002. Menlo Park, CA: Health Economics Resource Center; 2004;
  56. Office of Inspector GeneralNursing home resident assessment resource utilization groups. Washington, DC: Department of Health and Human Services; 2000;
  57. Office of Inspector General. Nursing home resident assessment quality of care. Washington, DC: Department of Health and Human Services; 2001;
  58. Rantz MJ, Popejoy L, Zwygart-Stauffacher M, et al. Minimum data set and resident assessment instrument: can using standardized assessment improve clinical practice and outcomes of care?. J Gerontol Nurs. 1999;35–43June
  59. Rantz MJ, Zwygart-Stauffacher M, Popejoy LL, et al. The minimum data set: no longer just for clinical assessment. Ann Long-Term Care. 1999;7:354–360
  60. Teresi JA, Holmes D. Should MDS data be used for research. Gerontologist. 1992;32:148–149
  61. Hawes C, Phillips CD, Mor V, et al. MDS data should be used for research. Gerontologist. 1992;32:563–564
  62. Oatway D. AANAC membership survey results (American Association of Nurse Assessment Coordinators). In: The Quarterly Newsletter for Nurse Assessment Coordinators. 2001;p. 4–6
  63. Nichols CL, Willis LA. The paired RAI/MDS specialist model. J Gerontol Nurs. 2004;6–11October
  64. American Association of Nurse Assessment Coordinators. http://www.AANAC.orgCited September 20, 2006
  65. Brown L, editor. The new shorter oxford English dictionary on historical principles, Vol 1. Oxford;Clarendon Press.
  66. Piven ML, Ammarell N, Bailey D, et al. MDS coordinator relationships and nursing home process. West J Nurs Res. 2006;28:294–309
  67. Tauton RL, Swagerty DL, Smith B, et al. Care planning for nursing home residents: incorporating the minimum data set requirements into practice. J Geront Nurs. 2004;40–49December
  68. Donabedian A. The role of outcomes in quality assessment and assurance. Qual Rev Bul 11:356-60.
  69. Weiner A, Ronich J. Culture change in long-term care. New York: Haworth Press; 2003;
  70. Shephard R. SNF PPS revisions. Adv Prov Post-Acute Care. 2006;9/10:18–19
  71. Krichbaum KE, Pearson V, Hanscom J. Better care in nursing homes: advanced practice nurses’ strategies for improving staff use of protocols. Clin Nurse Spec;14:40-6.
  72. Hanley T. Our system rewards poor quality. NH Mag. 2004;2:8
  73. Konetzka RT, Norton EC, Sloane PD, et al. Medicare prospective payment and quality of care for long-stay nursing facility residents. Med Care. 2006;44:270–276

PII: S0197-4572(07)00059-6

doi: 10.1016/j.gerinurse.2007.03.002

Geriatric Nursing
Volume 28, Issue 6 , Pages 377-386 , November 2007