Comparative Performance of Diagnosis-based and Prescription-based Comorbidity Scores to Predict Health-related Quality of Life

Hemalkumar Mehta, Sneha D. Sura, Manvi Sharma, Michael L. Johnson, Taylor S. Riall

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

OBJECTIVES:: To compare the performance of the health-related quality of life-comorbidity index (HRQoL-CI) with the diagnosis-based Charlson, Elixhauser, and combined comorbidity scores and the prescription-based chronic disease score (CDS) in predicting HRQoL in Agency of Healthcare Research and Quality priority conditions (asthma, breast cancer, diabetes, and heart failure). METHODS:: The Medical Expenditure Panel Survey (2005 and 2007–2011) data was used for this retrospective study. Four disease-specific cohorts were developed that included adult patients (age 18 y and above) with the particular disease condition. The outcome HRQoL [physical component score (PCS) and mental component score (MCS)] was measured using the Short Form Health Survey, Version 2 (SF-12v2). Multiple linear regression analyses were conducted with the PCS and MCS as dependent variables. Comorbidity scores were compared using adjusted R. RESULTS:: Of 140,046 adult participants, the study cohort included 7436 asthma (5.3%), 1054 breast cancer (0.8%), 13,829 diabetes (9.9%), and 937 heart failure (0.7%) patients. Among individual scores, HRQoL-CI was best at predicting PCS and MCS. Adding prescription-based comorbidity scores to HRQoL-CI in the same model improved prediction of PCS and MCS. HRQoL-CI+CDS performed the best in predicting PCS (adjusted R): asthma (43.7%), breast cancer (31.7%), diabetes (32.7%), and heart failure (20.0%). HRQoL-CI+CDS and Elixhauser+CDS had superior and comparable performance in predicting MCS (adjusted R): asthma (HRQoL-CI+CDS=20.1%; Elixhauser+CDS=19.6%), breast cancer (HRQoL-CI+CDS=12.9%; Elixhauser+CDS=14.1%), diabetes (HRQoL-CI+CDS=17.7%; Elixhauser+CDS=17.7%), and heart failure (HRQoL-CI+CDS=18.1%; Elixhauser+CDS=17.7%). CONCLUSIONS:: HRQoL-CI performed best in predicting HRQoL. Combining prescription-based scores to diagnosis-based scores improved the prediction of HRQoL.

Original languageEnglish (US)
JournalMedical Care
DOIs
StateAccepted/In press - Feb 25 2016

Fingerprint

Prescriptions
Comorbidity
Chronic Disease
Quality of Life
Asthma
Heart Failure
Breast Neoplasms
Health Services Research
Health Expenditures
Health Surveys
Linear Models
Cohort Studies
Retrospective Studies
Regression Analysis

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health

Cite this

Comparative Performance of Diagnosis-based and Prescription-based Comorbidity Scores to Predict Health-related Quality of Life. / Mehta, Hemalkumar; Sura, Sneha D.; Sharma, Manvi; Johnson, Michael L.; Riall, Taylor S.

In: Medical Care, 25.02.2016.

Research output: Contribution to journalArticle

Mehta, Hemalkumar ; Sura, Sneha D. ; Sharma, Manvi ; Johnson, Michael L. ; Riall, Taylor S. / Comparative Performance of Diagnosis-based and Prescription-based Comorbidity Scores to Predict Health-related Quality of Life. In: Medical Care. 2016.
@article{143591000e704d50b208cb75c9044aaa,
title = "Comparative Performance of Diagnosis-based and Prescription-based Comorbidity Scores to Predict Health-related Quality of Life",
abstract = "OBJECTIVES:: To compare the performance of the health-related quality of life-comorbidity index (HRQoL-CI) with the diagnosis-based Charlson, Elixhauser, and combined comorbidity scores and the prescription-based chronic disease score (CDS) in predicting HRQoL in Agency of Healthcare Research and Quality priority conditions (asthma, breast cancer, diabetes, and heart failure). METHODS:: The Medical Expenditure Panel Survey (2005 and 2007–2011) data was used for this retrospective study. Four disease-specific cohorts were developed that included adult patients (age 18 y and above) with the particular disease condition. The outcome HRQoL [physical component score (PCS) and mental component score (MCS)] was measured using the Short Form Health Survey, Version 2 (SF-12v2). Multiple linear regression analyses were conducted with the PCS and MCS as dependent variables. Comorbidity scores were compared using adjusted R. RESULTS:: Of 140,046 adult participants, the study cohort included 7436 asthma (5.3{\%}), 1054 breast cancer (0.8{\%}), 13,829 diabetes (9.9{\%}), and 937 heart failure (0.7{\%}) patients. Among individual scores, HRQoL-CI was best at predicting PCS and MCS. Adding prescription-based comorbidity scores to HRQoL-CI in the same model improved prediction of PCS and MCS. HRQoL-CI+CDS performed the best in predicting PCS (adjusted R): asthma (43.7{\%}), breast cancer (31.7{\%}), diabetes (32.7{\%}), and heart failure (20.0{\%}). HRQoL-CI+CDS and Elixhauser+CDS had superior and comparable performance in predicting MCS (adjusted R): asthma (HRQoL-CI+CDS=20.1{\%}; Elixhauser+CDS=19.6{\%}), breast cancer (HRQoL-CI+CDS=12.9{\%}; Elixhauser+CDS=14.1{\%}), diabetes (HRQoL-CI+CDS=17.7{\%}; Elixhauser+CDS=17.7{\%}), and heart failure (HRQoL-CI+CDS=18.1{\%}; Elixhauser+CDS=17.7{\%}). CONCLUSIONS:: HRQoL-CI performed best in predicting HRQoL. Combining prescription-based scores to diagnosis-based scores improved the prediction of HRQoL.",
author = "Hemalkumar Mehta and Sura, {Sneha D.} and Manvi Sharma and Johnson, {Michael L.} and Riall, {Taylor S.}",
year = "2016",
month = "2",
day = "25",
doi = "10.1097/MLR.0000000000000517",
language = "English (US)",
journal = "Medical Care",
issn = "0025-7079",
publisher = "Lippincott Williams and Wilkins",

}

TY - JOUR

T1 - Comparative Performance of Diagnosis-based and Prescription-based Comorbidity Scores to Predict Health-related Quality of Life

AU - Mehta, Hemalkumar

AU - Sura, Sneha D.

AU - Sharma, Manvi

AU - Johnson, Michael L.

AU - Riall, Taylor S.

PY - 2016/2/25

Y1 - 2016/2/25

N2 - OBJECTIVES:: To compare the performance of the health-related quality of life-comorbidity index (HRQoL-CI) with the diagnosis-based Charlson, Elixhauser, and combined comorbidity scores and the prescription-based chronic disease score (CDS) in predicting HRQoL in Agency of Healthcare Research and Quality priority conditions (asthma, breast cancer, diabetes, and heart failure). METHODS:: The Medical Expenditure Panel Survey (2005 and 2007–2011) data was used for this retrospective study. Four disease-specific cohorts were developed that included adult patients (age 18 y and above) with the particular disease condition. The outcome HRQoL [physical component score (PCS) and mental component score (MCS)] was measured using the Short Form Health Survey, Version 2 (SF-12v2). Multiple linear regression analyses were conducted with the PCS and MCS as dependent variables. Comorbidity scores were compared using adjusted R. RESULTS:: Of 140,046 adult participants, the study cohort included 7436 asthma (5.3%), 1054 breast cancer (0.8%), 13,829 diabetes (9.9%), and 937 heart failure (0.7%) patients. Among individual scores, HRQoL-CI was best at predicting PCS and MCS. Adding prescription-based comorbidity scores to HRQoL-CI in the same model improved prediction of PCS and MCS. HRQoL-CI+CDS performed the best in predicting PCS (adjusted R): asthma (43.7%), breast cancer (31.7%), diabetes (32.7%), and heart failure (20.0%). HRQoL-CI+CDS and Elixhauser+CDS had superior and comparable performance in predicting MCS (adjusted R): asthma (HRQoL-CI+CDS=20.1%; Elixhauser+CDS=19.6%), breast cancer (HRQoL-CI+CDS=12.9%; Elixhauser+CDS=14.1%), diabetes (HRQoL-CI+CDS=17.7%; Elixhauser+CDS=17.7%), and heart failure (HRQoL-CI+CDS=18.1%; Elixhauser+CDS=17.7%). CONCLUSIONS:: HRQoL-CI performed best in predicting HRQoL. Combining prescription-based scores to diagnosis-based scores improved the prediction of HRQoL.

AB - OBJECTIVES:: To compare the performance of the health-related quality of life-comorbidity index (HRQoL-CI) with the diagnosis-based Charlson, Elixhauser, and combined comorbidity scores and the prescription-based chronic disease score (CDS) in predicting HRQoL in Agency of Healthcare Research and Quality priority conditions (asthma, breast cancer, diabetes, and heart failure). METHODS:: The Medical Expenditure Panel Survey (2005 and 2007–2011) data was used for this retrospective study. Four disease-specific cohorts were developed that included adult patients (age 18 y and above) with the particular disease condition. The outcome HRQoL [physical component score (PCS) and mental component score (MCS)] was measured using the Short Form Health Survey, Version 2 (SF-12v2). Multiple linear regression analyses were conducted with the PCS and MCS as dependent variables. Comorbidity scores were compared using adjusted R. RESULTS:: Of 140,046 adult participants, the study cohort included 7436 asthma (5.3%), 1054 breast cancer (0.8%), 13,829 diabetes (9.9%), and 937 heart failure (0.7%) patients. Among individual scores, HRQoL-CI was best at predicting PCS and MCS. Adding prescription-based comorbidity scores to HRQoL-CI in the same model improved prediction of PCS and MCS. HRQoL-CI+CDS performed the best in predicting PCS (adjusted R): asthma (43.7%), breast cancer (31.7%), diabetes (32.7%), and heart failure (20.0%). HRQoL-CI+CDS and Elixhauser+CDS had superior and comparable performance in predicting MCS (adjusted R): asthma (HRQoL-CI+CDS=20.1%; Elixhauser+CDS=19.6%), breast cancer (HRQoL-CI+CDS=12.9%; Elixhauser+CDS=14.1%), diabetes (HRQoL-CI+CDS=17.7%; Elixhauser+CDS=17.7%), and heart failure (HRQoL-CI+CDS=18.1%; Elixhauser+CDS=17.7%). CONCLUSIONS:: HRQoL-CI performed best in predicting HRQoL. Combining prescription-based scores to diagnosis-based scores improved the prediction of HRQoL.

UR - http://www.scopus.com/inward/record.url?scp=84959208772&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84959208772&partnerID=8YFLogxK

U2 - 10.1097/MLR.0000000000000517

DO - 10.1097/MLR.0000000000000517

M3 - Article

JO - Medical Care

JF - Medical Care

SN - 0025-7079

ER -