OBJECTIVES: To determine whether comorbidity information derived from electronic health record (EHR) problem lists is accurate. STUDY DESIGN: Retrospective cohort study of 1596 men diagnosed with prostate cancer between 1998 and 2004 at 2 Southern California Veterans Affairs Medical Centers with long-term follow-up. METHODS: We compared EHR problem list-based comorbidity assessment with manual review of EHR free-text notes in terms of sensitivity and specificity for identification of major comorbidities and Charlson Comorbidity Index (CCI) scores. We then compared EHR-based CCI scores with free-text-based CCI scores in prediction of long-term mortality. RESULTS: EHR problem list-based comorbidity assessment had poor sensitivity for detecting major comorbidities: myocardial infarction (8%), cerebrovascular disease (32%), diabetes (46%), chronic obstructive pulmonary disease (42%), peripheral vascular disease (31%), liver disease (1%), and congestive heart failure (23%). Specificity was above 94% for all comorbidities. Free-text-based CCI scores were predictive of long-term other-cause mortality, whereas EHR problem list-based scores were not. CONCLUSIONS: Inaccuracies in EHR problem list-based comorbidity data can lead to incorrect determinations of case mix. Such data should be validated prior to application to risk adjustment.
OBJECTIVES: To determine whether comorbidity information derived from electronic health record (EHR) problem lists is accurate. STUDY DESIGN: Retrospective cohort study of 1596 men diagnosed with prostate cancer between 1998 and 2004 at 2 Southern California Veterans Affairs Medical Centers with long-term follow-up. METHODS: We compared EHR problem list-based comorbidity assessment with manual review of EHR free-text notes in terms of sensitivity and specificity for identification of major comorbidities and Charlson Comorbidity Index (CCI) scores. We then compared EHR-based CCI scores with free-text-based CCI scores in prediction of long-term mortality. RESULTS: EHR problem list-based comorbidity assessment had poor sensitivity for detecting major comorbidities: myocardial infarction (8%), cerebrovascular disease (32%), diabetes (46%), chronic obstructive pulmonary disease (42%), peripheral vascular disease (31%), liver disease (1%), and congestive heart failure (23%). Specificity was above 94% for all comorbidities. Free-text-based CCI scores were predictive of long-term other-cause mortality, whereas EHR problem list-based scores were not. CONCLUSIONS: Inaccuracies in EHR problem list-based comorbidity data can lead to incorrect determinations of case mix. Such data should be validated prior to application to risk adjustment.
Authors: Bat-Zion Hose; Peter L T Hoonakker; Abigail R Wooldridge; Thomas B Brazelton Iii; Shannon M Dean; Ben Eithun; James C Fackler; Ayse P Gurses; Michelle M Kelly; Jonathan E Kohler; Nicolette M McGeorge; Joshua C Ross; Deborah A Rusy; Pascale Carayon Journal: Appl Clin Inform Date: 2019-02-13 Impact factor: 2.342
Authors: Hamid Emamekhoo; Cibele B Carroll; Chelsea Stietz; Jeffrey B Pier; Michael D Lavitschke; Daniel Mulkerin; Mary E Sesto; Amye J Tevaarwerk Journal: JCO Clin Cancer Inform Date: 2022-06
Authors: Lina M Brinker; Matthew C Konerman; Pedram Navid; Michael P Dorsch; Jennifer McNamara; Cristen J Willer; Mary E Tinetti; Scott L Hummel; Parag Goyal Journal: Am J Med Date: 2020-08-18 Impact factor: 4.965
Authors: Candice L Wilshire; Carson C Fuller; Christopher R Gilbert; John R Handy; Kimberly E Costas; Brian E Louie; Ralph W Aye; Alexander S Farivar; Eric Vallières; Jed A Gorden Journal: Can Respir J Date: 2020-03-26 Impact factor: 2.409
Authors: Rebecca P Luoh; Amye J Tevaarwerk; Thevaa Chandereng; Elena M Smith; Cibele B Carroll; Hamid Emamekhoo; Mary E Sesto Journal: Cancer Med Date: 2021-08-28 Impact factor: 4.452
Authors: Marianne E Weiss; Olga Yakusheva; Kathleen L Bobay; Linda Costa; Ronda G Hughes; Susan Nuccio; Morris Hamilton; Sarah Bahr; Danielle Siclovan; James Bang Journal: JAMA Netw Open Date: 2019-01-04