OBJECTIVES: The Health Care Financing Administration requires that patients admitted to certified nursing homes be assessed with the Minimum Data Set, a data collection instrument containing more than 300 demographic, diagnostic, clinical, and treatment variables. Long-term care databases potentially may be used to assess the outcomes of specific treatments as well as drug effectiveness. The authors sought to ascertain reliability and validity of diagnostic and drug data in a database obtained by merging the Minimum Data Set with detailed information on drugs consumed by each resident. METHODS: A population of 296,379 residents of 1,492 nursing homes in Kansas, Maine, Mississippi, New York, and South Dakota participated in the study between 1992 and 1994. Minimum Data Set clinical diagnoses were contrasted with selected resident characteristics and a variety of symptoms and treatments. Limited to individuals who had been hospitalized in the 6 months preceding the first assessment, Minimum Data Set diagnoses were compared with those on the hospital discharge claims maintained in the Medicare Provider Analysis and Review database. Finally, the probability that the use of selected drugs predicted the correspondent gender-specific, age-specific, or unique labeled indication was estimated. RESULTS: The positive predictive value for Minimum Data Set diagnoses compared with gender or function measures exceeded 0.9, and it was 0.8 for specific symptoms and 0.6 for virtually all other comparisons. The positive predictive value for Minimum Data Set diagnoses compared with those from hospital claims was approximately 0.7 for all chronic medical conditions, except for depression and asthma/chronic obstructive pulmonary disease/emphysema. The positive predictive value for acute/subacute diagnoses (ie, pneumonia, urinary tract infection, anemia) that may resolve during hospital stay was less than 0.5. The positive predictive value for selected drugs, except estrogens, compared with age and gender was close to 1.0 in all cases. When compared to their labeled indication, the positive predictive value was more than 0.6 for all drugs considered, with 0.97, 0.91, and 0.87 for tacrine and Alzheimer's disease, antidiabetics and diabetes mellitus, and L-dopa and Parkinson's disease, respectively. CONCLUSIONS: These findings point to the overall validity of the drug and clinical data in this Minimum Data Set-based data set. Additional validation efforts will determine whether this data set can be used for studies of geriatric pharmacoepidemiology and for analyses of the influence of different policies and practices on residents' outcomes.
OBJECTIVES: The Health Care Financing Administration requires that patients admitted to certified nursing homes be assessed with the Minimum Data Set, a data collection instrument containing more than 300 demographic, diagnostic, clinical, and treatment variables. Long-term care databases potentially may be used to assess the outcomes of specific treatments as well as drug effectiveness. The authors sought to ascertain reliability and validity of diagnostic and drug data in a database obtained by merging the Minimum Data Set with detailed information on drugs consumed by each resident. METHODS: A population of 296,379 residents of 1,492 nursing homes in Kansas, Maine, Mississippi, New York, and South Dakota participated in the study between 1992 and 1994. Minimum Data Set clinical diagnoses were contrasted with selected resident characteristics and a variety of symptoms and treatments. Limited to individuals who had been hospitalized in the 6 months preceding the first assessment, Minimum Data Set diagnoses were compared with those on the hospital discharge claims maintained in the Medicare Provider Analysis and Review database. Finally, the probability that the use of selected drugs predicted the correspondent gender-specific, age-specific, or unique labeled indication was estimated. RESULTS: The positive predictive value for Minimum Data Set diagnoses compared with gender or function measures exceeded 0.9, and it was 0.8 for specific symptoms and 0.6 for virtually all other comparisons. The positive predictive value for Minimum Data Set diagnoses compared with those from hospital claims was approximately 0.7 for all chronic medical conditions, except for depression and asthma/chronic obstructive pulmonary disease/emphysema. The positive predictive value for acute/subacute diagnoses (ie, pneumonia, urinary tract infection, anemia) that may resolve during hospital stay was less than 0.5. The positive predictive value for selected drugs, except estrogens, compared with age and gender was close to 1.0 in all cases. When compared to their labeled indication, the positive predictive value was more than 0.6 for all drugs considered, with 0.97, 0.91, and 0.87 for tacrine and Alzheimer's disease, antidiabetics and diabetes mellitus, and L-dopa and Parkinson's disease, respectively. CONCLUSIONS: These findings point to the overall validity of the drug and clinical data in this Minimum Data Set-based data set. Additional validation efforts will determine whether this data set can be used for studies of geriatric pharmacoepidemiology and for analyses of the influence of different policies and practices on residents' outcomes.
Authors: Micaela Jantzi; Amy C Maher; George Ioannidis; John P Hirdes; Lora M Giangregorio; Alexandra Papaioannou Journal: Age Ageing Date: 2014-11-14 Impact factor: 10.668
Authors: Josephine P Gomes; Wassim H Shaheen; Son V Truong; Edward F Brown; Brent W Beasley; Byron J Gajewski Journal: J Gen Intern Med Date: 2003-11 Impact factor: 5.128
Authors: Rosa Liperoti; Graziano Onder; Francesco Landi; Kate L Lapane; Vincent Mor; Roberto Bernabei; Giovanni Gambassi Journal: J Clin Psychiatry Date: 2009-10 Impact factor: 4.384