title: Patient perception versus medical record entry of health-related conditions among patients with heart failure.
abstract: A shared understanding of medical conditions between patients and their health care providers may improve self-care and outcomes. In this study, the concordance between responses to a medical history self-report (MHSR) form and the corresponding provider documentation in electronic health records (EHRs) of 19 select co-morbidities and habits in 230 patients with heart failure were evaluated. Overall concordance was assessed using the κ statistic, and crude, positive, and negative agreement were determined for each condition. Concordance between MHSR and EHR varied widely for cardiovascular conditions (κ = 0.37 to 0.96), noncardiovascular conditions (κ = 0.06 to 1.00), and habits (κ = 0.26 to 0.69). Less than 80% crude agreement was seen for history of arrhythmias (72%), dyslipidemia (74%), and hypertension (79%) among cardiovascular conditions and lung disease (70%) and peripheral arterial disease (78%) for noncardiovascular conditions. Perfect agreement was observed for only 1 of the 19 conditions (human immunodeficiency virus status). Negative agreement >80% was more frequent than >80% positive agreement for a condition (15 of 19 [79%] vs 8 of 19 [42%], respectively, p = 0.02). Only 20% of patients had concordant MSHRs and EHRs for all 7 cardiovascular conditions; in 40% of patients, concordance was observed for ≤5 conditions. For noncardiovascular conditions, only 28% of MSHR-EHR pairs agreed for all 9 conditions; 37% agreed for ≤7 conditions. Cumulatively, 39% of the pairs matched for ≤15 of 19 conditions. In conclusion, there is significant variation in the perceptions of patients with heart failure compared to providers' records of co-morbidities and habits. The root causes of this variation and its impact on outcomes need further study.
authors.affiliation: Cardiology Division, Emory University School of Medicine, Atlanta, Georgia, USA.
authors.forename: Adnan S
authors.initials: AS
authors.lastname: Malik
authors.forename: Grigorios
authors.initials: G
authors.lastname: Giamouzis
authors.forename: Vasiliki V
authors.initials: VV
authors.lastname: Georgiopoulou
authors.forename: Lucy V
authors.initials: LV
authors.lastname: Fike
authors.forename: Andreas P
authors.initials: AP
authors.lastname: Kalogeropoulos
authors.forename: Catherine R
authors.initials: CR
authors.lastname: Norton
authors.forename: Dan
authors.initials: D
authors.lastname: Sorescu
authors.forename: Sidra
authors.initials: S
authors.lastname: Azim
authors.forename: Sonjoy R
authors.initials: SR
authors.lastname: Laskar
authors.forename: Andrew L
authors.initials: AL
authors.lastname: Smith
authors.forename: Sandra B
authors.initials: SB
authors.lastname: Dunbar
authors.forename: Javed
authors.initials: J
authors.lastname: Butler
mesh_terms: D000368:Aged; D000465:Algorithms; D057286:Electronic Health Records; D005260:Female; D006184:Habits; D006333:Heart Failure / Q000150:complications / Q000523:psychology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010361:Patients / Q000523:psychology*; D011446:Prospective Studies; D057566:Self Report