Validity of the RAI-MDS for ascertaining diabetes and comorbid conditions in long-term care facility residents.

Lisa M Lix,David Blackburn,Lin Yan,Verena Schneider-Lindner,Nianping Hu,Gary F Teare

doi:10.1186/1472-6963-14-17

Abstract

BackgroundThis study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs).MethodsHospital inpatient, outpatient physician billing, RAI-MDS, and population registry data for 1997 to 2011 from Saskatchewan, Canada were used to ascertain cases of diabetes and 12 comorbid conditions. Prevalence estimates were calculated for both RAI-MDS and administrative health data. Sensitivity, specificity, and positive and negative predictive values (PPV and NPV) were calculated using population-based administrative health data as the validation data source. Cohen’s κ was used to estimate agreement between the two data sources.Results23,217 LTCF residents were in the diabetes case ascertainment cohort. Diabetes prevalence was 25.3% in administrative health data and 21.9% in RAI-MDS data. Overall sensitivity of a RAI-MDS diabetes diagnoses was 0.79 (95% CI: 0.79, 0.80) and the PPV was 0.92 (95% CI: 0.91, 0.92), when compared to administrative health data. Sensitivity of the RAI-MDS for ascertaining comorbid conditions ranged from 0.21 for osteoporosis to 0.92 for multiple sclerosis; specificity was high for most conditions.ConclusionsRAI-MDS clinical assessment data are sensitive to ascertain diabetes cases in LTCF populations when compared to administrative health data. For many comorbid conditions, RAI-MDS data have low validity when compared to administrative data. Risk-adjustment measures based on these comorbidities might not produce consistent results for RAI-MDS and administrative health data, which could affect the conclusions of studies about health outcomes and quality of care across facilities.

Highlights

This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs)
Mor et al [6] found that diagnoses in RAI-MDS data had fair to good sensitivity and specificity but low positive predictive value (PPV) when compared to diagnoses in hospital records for residents admitted to LTCFs from acute care hospitals
In summary, this study found that validity of diagnostic information in RAI-MDS was very good for diabetes but variable, and generally poorer, for comorbid chronic conditions when administrative health data were used as the validation data source

Summary

Introduction

This study assessed the validity of the Resident Assessment Instrument Minimum Data Set (RAI-MDS) Version 2.0 for diagnoses of diabetes and comorbid conditions in residents of long-term care facilities (LTCFs). Electronic, population-based data sources for ascertaining chronic and acute conditions in LTCFs include administrative health data, like hospital and physician records, and clinical assessment data, like the Resident Assessment Instrument Minimum Data Set (RAI-MDS) [4,5,6]. Wodchis et al [7] obtained similar results Neither of these studies assessed validity of the diagnoses captured in the RAIMDS for the entire LTCF resident population, not just those admitted from hospital, nor did they use both inpatient and outpatient data as the validation data source when assessing the validity of the RAI-MDS data

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