Ricky Camplain1, Anna Kucharska-Newton2, Laura Loehr2, Thomas C Keyserling3, J Bradley Layton2, Lisa Wruck4, Aaron R Folsom5, Alain G Bertoni6, Gerardo Heiss2. 1. Center for Health Equity, Northern Arizona University, Flagstaff, Arizona; Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America. Electronic address: ricky.camplain@nau.edu. 2. Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America. 3. Department of Medicine, The University of North Carolina, Chapel Hill, North Carolina, United States of America. 4. Center for Predictive Medicine, Duke Clinical Research Institute, Durham, North Carolina, United States of America. 5. Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, United States of America. 6. Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America.
Abstract
OBJECTIVE: The aim of this work was to estimate agreement of self-reported heart failure (HF) with physician-diagnosed HF and compare the prevalence of HF according to method of ascertainment. METHODS AND RESULTS: ARIC cohort members (60-83 years of age) were asked annually whether a physician indicated that they have HF. For those self-reporting HF, physicians were asked to confirm their patients' HF status. Physician-diagnosed HF included surveillance of hospitalized HF and hospitalized and outpatient HF identified in administrative claims databases. We estimated sensitivity, specificity, positive predicted value, kappa, prevalence and bias-adjusted kappa (PABAK), and prevalence. Compared with physician-diagnosed HF, sensitivity of self-report was low (28%-38%) and specificity was high (96%-97%). Agreement was poor (kappa 0.32-0.39) and increased when adjusted for prevalence and bias (PABAK 0.73-0.83). Prevalence of HF measured by self-report (9.0%), ARIC-classified hospitalizations (11.2%), and administrative hospitalization claims (12.7%) were similar. When outpatient HF claims were included, prevalence of HF increased to 18.6%. CONCLUSIONS: For accurate estimates HF burden, self-reports of HF are best confirmed by means of appropriate diagnostic tests or medical records. Our results highlight the need for improved awareness and understanding of HF by patients, because accurate patient awareness of the diagnosis may enhance management of this common condition. Published by Elsevier Inc.
OBJECTIVE: The aim of this work was to estimate agreement of self-reported heart failure (HF) with physician-diagnosed HF and compare the prevalence of HF according to method of ascertainment. METHODS AND RESULTS: ARIC cohort members (60-83 years of age) were asked annually whether a physician indicated that they have HF. For those self-reporting HF, physicians were asked to confirm their patients' HF status. Physician-diagnosed HF included surveillance of hospitalized HF and hospitalized and outpatient HF identified in administrative claims databases. We estimated sensitivity, specificity, positive predicted value, kappa, prevalence and bias-adjusted kappa (PABAK), and prevalence. Compared with physician-diagnosed HF, sensitivity of self-report was low (28%-38%) and specificity was high (96%-97%). Agreement was poor (kappa 0.32-0.39) and increased when adjusted for prevalence and bias (PABAK 0.73-0.83). Prevalence of HF measured by self-report (9.0%), ARIC-classified hospitalizations (11.2%), and administrative hospitalization claims (12.7%) were similar. When outpatient HF claims were included, prevalence of HF increased to 18.6%. CONCLUSIONS: For accurate estimates HF burden, self-reports of HF are best confirmed by means of appropriate diagnostic tests or medical records. Our results highlight the need for improved awareness and understanding of HF by patients, because accurate patient awareness of the diagnosis may enhance management of this common condition. Published by Elsevier Inc.
Entities:
Keywords:
Heart failure; administrative claims; medical records; self-report
Authors: Jane S Saczynski; Susan E Andrade; Leslie R Harrold; Jennifer Tjia; Sarah L Cutrona; Katherine S Dodd; Robert J Goldberg; Jerry H Gurwitz Journal: Pharmacoepidemiol Drug Saf Date: 2012-01 Impact factor: 2.890
Authors: Yuji Okura; Lynn H Urban; Douglas W Mahoney; Steven J Jacobsen; Richard J Rodeheffer Journal: J Clin Epidemiol Date: 2004-10 Impact factor: 6.437
Authors: Laura R Loehr; Sunil K Agarwal; Chris Baggett; Lisa M Wruck; Patricia P Chang; Scott D Solomon; Eyal Shahar; Hanyu Ni; Wayne D Rosamond; Gerardo Heiss Journal: Circ Heart Fail Date: 2013-05-06 Impact factor: 8.790
Authors: D W Kitzman; J M Gardin; J S Gottdiener; A Arnold; R Boineau; G Aurigemma; E K Marino; M Lyles; M Cushman; P L Enright Journal: Am J Cardiol Date: 2001-02-15 Impact factor: 2.778
Authors: Leah Rethy; Thanh-Huyen T Vu; Nilay S Shah; Mercedes R Carnethon; Tara Lagu; Mark D Huffman; Clyde W Yancy; Donald M Lloyd-Jones; Sadiya S Khan Journal: Circ Heart Fail Date: 2022-04-28 Impact factor: 10.447
Authors: César Caraballo; Rohan Khera; Philip G Jones; Carole Decker; Wade Schulz; John A Spertus; Harlan M Krumholz Journal: Circ Cardiovasc Qual Outcomes Date: 2020-06-19
Authors: Li Zhao; Rani Zierath; Jenine E John; Brian Lee Claggett; Michael E Hall; Donald Clark; Kenneth R Butler; Adolfo Correa; Amil M Shah Journal: JAMA Netw Open Date: 2022-09-01
Authors: Parag Goyal; Matthew T Mefford; Ligong Chen; Madeline R Sterling; Raegan W Durant; Monika M Safford; Emily B Levitan Journal: BMC Med Res Methodol Date: 2020-03-04 Impact factor: 4.615
Authors: Wen-Chih Wu; Mengna Huang; Tracey H Taveira; Mary B Roberts; Lisa W Martin; Gregory A Wellenius; Karen C Johnson; JoAnn E Manson; Simin Liu; Charles B Eaton Journal: J Am Heart Assoc Date: 2020-03-20 Impact factor: 5.501