The MDS Mortality Risk Index: The evolution of a method for predicting 6-month mortality in nursing home residents

BackgroundAccurate prognosis is vital to the initiation of advance care planning particularly in a vulnerable, at risk population such as care home residents. The aim of this paper is to report on the revision and simplification of the MDS Mortality Rating Index (MMRI) for use in clinical practice to predict the probability of death in six months for care home residents.MethodsThe design was a secondary analysis of a US Minimum Data Set (MDS) for long term care residents using regression analysis to identify predictors of mortality within six months.ResultsUsing twelve easy to collect items, the probability of mortality within six months was accurately predicted within the MDS database. The items are: admission to the care home within three months; lost weight unintentionally in past three months; renal failure; chronic heart failure; poor appetite; male; dehydrated; short of breath; active cancer diagnosis; age; deteriorated cognitive skills in past three months; activities of daily living score.ConclusionA lack of recognition of the proximity of death is often blamed for inappropriate admission to hospital at the end of an older person's life. An accurate prognosis for older adults living in a residential or nursing home can facilitate end of life decision making and planning for preferred place of care at the end of life. The original MMRI was derived and validated from a large database of long term care residents in the USA. However, this simplification of the revised index (MMRI-R) may provide a means for facilitating prognostication and end of life discussions for application outside the USA where the MDS is not in use. Prospective testing is needed to further test the accuracy of the MMRI-R and its application in the UK and other non-MDS settings.

[1]  Marilyn Rantz,et al.  A profile of residents admitted to long-term care facilities for end-of-life care. , 2003, Journal of the American Medical Directors Association.

[2]  M. Wagener,et al.  Pneumonia in a long-term care facility. A prospective study of outcome. , 1996, Archives of internal medicine.

[3]  Shai Linn,et al.  New patient-oriented summary measure of net total gain in certainty for dichotomous diagnostic tests , 2006, Epidemiologic perspectives & innovations : EP+I.

[4]  J. Costello,et al.  Nursing older dying patients: findings from an ethnographic study of death and dying in elderly care wards. , 2001, Journal of advanced nursing.

[5]  D. Mehr,et al.  Stability and sensitivity of nursing home quality indicators. , 2004, The journals of gerontology. Series A, Biological sciences and medical sciences.

[6]  M. Rantz,et al.  Hospice and nonhospice nursing home residents. , 2003, Journal of palliative medicine.

[7]  D. Mehr,et al.  Nursing home quality, cost, staffing, and staff mix. , 2004, The Gerontologist.

[8]  R. Kruse,et al.  Experience with implementation of a quality improvement project for the care of nursing home residents. , 2009, Journal of nursing care quality.

[9]  Marilyn Rantz,et al.  Predicting death in the nursing home: development and validation of the 6-month Minimum Data Set mortality risk index. , 2005, The journals of gerontology. Series A, Biological sciences and medical sciences.

[10]  D. Mehr,et al.  MDS Cognitive Performance Scale. , 1994, Journal of gerontology.

[11]  S. Prevost,et al.  Two methods for predicting limited life expectancy in nursing homes. , 2006, Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing.

[12]  R. D'Agostino,et al.  Predictors of mortality for lower respiratory infections in nursing home residents with dementia were validated transnationally. , 2006, Journal of clinical epidemiology.

[13]  R. D'Agostino,et al.  Predicting mortality in nursing home residents with lower respiratory tract infection: The Missouri LRI Study. , 2001, JAMA.

[14]  Zoë Lawrence,et al.  Building on the best – choice, responsiveness and equity in the NHS , 2004, Health expectations : an international journal of public participation in health care and health policy.

[15]  D. Kiely,et al.  A Practical Approach to Identifying Mortality‐Related Factors in Established Long‐Term Care Residents , 1998, Journal of the American Geriatrics Society.

[16]  D. Seamark Caring for the Dying at Home , 2003 .

[17]  B E Fries,et al.  Scaling ADLs within the MDS. , 1999, The journals of gerontology. Series A, Biological sciences and medical sciences.

[18]  P. Edmonds,et al.  'If only someone had told me . . .' A review of the care of patients dying in hospital. , 2003, Clinical medicine.

[19]  Stanley Lemeshow,et al.  Applied Logistic Regression, Second Edition , 1989 .

[20]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[21]  S. Fischer,et al.  A practical tool to identify patients who may benefit from a palliative approach: the CARING criteria. , 2006, Journal of pain and symptom management.

[22]  "If only someone had told me…": lessons from rural providers. , 2011, The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association.

[23]  B. Álvarez-Fernández Estimating prognosis for nursing home residents with advanced dementia. , 2004, JAMA.

[24]  H. Keselman,et al.  Backward, forward and stepwise automated subset selection algorithms: Frequency of obtaining authentic and noise variables , 1992 .

[25]  W J Mackillop,et al.  Measuring the accuracy of prognostic judgments in oncology. , 1997, Journal of clinical epidemiology.