Institutional members access full text with Ovid®

Share this article on:

Validating Diagnostic Information on the Minimum Data Set in Ontario Hospital-Based Long-Term Care

Wodchis, Walter P. PhD*†‡; Naglie, Gary MD*†§¶; Teare, Gary F. PhD*‡∥

doi: 10.1097/MLR.0b013e3181789471
Brief Report

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.

Study Sample: 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.

Supplemental Digital Content is Available in the Text.

From the *Department of Health Policy Management and Evaluation, University of Toronto, Toronto; †Toronto Rehabilitation Institute, Toronto; ‡Institute for Clinical Evaluative Sciences, Toronto; §Department of Medicine, University of Toronto, Toronto; ¶Division of General Internal Medicine, University Health Network, Toronto; and ∥Health Quality Council, Saskatoon, Saskatchewan, Canada.

Supported by a Canadian Institutes for Health Research New Investigator Award (to W.P.W.) and the Mary Trimmer Chair in Geriatric Medicine Research, University of Toronto (to G.N.).

Reprints: Walter P. Wodchis, PhD, Health Management Policy and Evaluation, Faculty of Medicine, University of Toronto, 155 College Street, 4th Floor, Ontario M5T 3M6, Toronto. E-mail: walter.wodchis@utoronto.ca.

© 2008 Lippincott Williams & Wilkins, Inc.