Validating diagnostic information on the Minimum Data Set in Ontario Hospital-based long-term care.
BACKGROUND
Over 20 countries currently use the Minimum Data Set Resident Assessment Instrument (MDS) in long-term care settings for care planning, policy, and research purposes. A full assessment of the quality of the diagnostic information recorded on the MDS is lacking.


OBJECTIVE
The primary goal of this study was to examine the quality of diagnostic coding on the MDS.


METHODS
Subjects for this study were admitted to Ontario Complex Continuing Care Hospitals (CCC) directly from acute hospitals between April 1, 1997 and March 31, 2005 (n = 80,664).


METHODS
Encrypted unique identifiers, common across acute and CCC administrative databases, were used to link administrative records for patients in the sample. After linkage, each resident had 2 sources of diagnostic information: the acute discharge abstract database and the MDS. Using the discharge abstract database as the reference standard, we calculated the sensitivity for each of 43 MDS diagnoses.


RESULTS
Compared with primary diagnoses coded in acute care abstracts, 12 of 43 MDS diagnoses attained a sensitivity of at least 0.80, including 7 of the 10 diagnoses with the highest prevalence as an acute care primary diagnosis before CCC admission.


CONCLUSIONS
Although the sensitivity was high for many of the most prevalent conditions, important diagnostic information is missed increasing the potential for suboptimal clinical care. Emphasis needs to be put on improving information flow across care settings during patient transitions. Researchers should exercise caution when using MDS diagnoses to identify patient populations, particularly those shown to have low sensitivity in this study.
Wodchis
Walter P
WP
Department of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada. walter.wodchis@utoronto.ca
Naglie
Gary
G
Teare
Gary F
GF
D016208:Databases, Factual; D003953:Diagnosis-Related Groups / Q000145:classification*; D006801:Humans; D038801:International Classification of Diseases; D008134:Long-Term Care / Q000145:classification / Q000706:statistics & numerical data*; D009735:Nursing Homes / Q000706:statistics & numerical data*; D009864:Ontario; D011787:Quality of Health Care; D015203:Reproducibility of Results