NAU publications by CHER
Faculty & staff publications
NAU faculty and staff have the opportunity to publish their findings and knowledge as authors. CHER has many researchers that have been cited multiple times in major publications for their great work. The Center for Health Equity Research has accumulated all faculty publications into one, easy to navigate database.
Please type in a key word or author LAST name to search
Camplain, Ricky; Kucharska-Newton, Anna; Keyserling, Thomas C; Layton, Bradley J; Loehr, Laura; Heiss, Gerardo Incidence of Heart Failure Observed in Emergency Departments, Ambulatory Clinics, and Hospitals Journal Article The American Journal of Cardiology, 121 (1), pp. 1328-1335, 2018. @article{Camplain2018, title = {Incidence of Heart Failure Observed in Emergency Departments, Ambulatory Clinics, and Hospitals}, author = {Ricky Camplain and Anna Kucharska-Newton and Thomas C Keyserling and Bradley J Layton and Laura Loehr and Gerardo Heiss}, url = {https://www.sciencedirect.com/science/article/pii/S0002914918302509?via%3Dihub}, doi = {10.1016/j.amjcard.2018.02.014}, year = {2018}, date = {2018-06-01}, journal = {The American Journal of Cardiology}, volume = {121}, number = {1}, pages = {1328-1335}, abstract = {Reports on the burden of heart failure (HF) have largely omitted HF diagnosed in outpatient settings. We quantified annual incidence rates ([IR] per 1,000 person years) of HF identified in ambulatory clinics, emergency departments (EDs), and during hospital stays in a national probability sample of Medicare beneficiaries from 2008 to 2014, by age and race/ethnicity. A 20% random sample of Medicare beneficiaries ages ≥65 years with continuous Medicare Parts A, B, and D coverage was used to estimate annual IRs of HF identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Of the 681,487 beneficiaries with incident HF from 2008 to 2014, 283,451 (41%) presented in ambulatory clinics, 76,919 (11%) in EDs, and 321,117 (47%) in hospitals. Overall, incidence of HF in ambulatory clinics decreased from 2008 (IR 22.2, 95% confidence interval [CI] 22.0, 22.4) to 2014 (IR 15.0, 95% CI 14.8, 15.1). Similarly, incidence of HF-related ED visits without an admission to the hospital decreased somewhat from 2008 (IR 5.5, 95% CI 5.4, 5.6) to 2012 (IR 4.2, 95% CI 4.1, 4.3) and stabilized from 2013 to 2014. Similar to previous reports, HF hospitalizations, both International Classification of Diseases, Ninth Revision, Clinical Modification code 428.x in the primary and any position, decreased over the study period. More than half of all new cases of HF in Medicare beneficiaries presented in an ambulatory clinic or ED. The overall incidence of HF decreased from 2008 to 2014, regardless of health-care setting. In conclusion, consideration of outpatient HF is warranted to better understand the burden of HF and its temporal trends.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Reports on the burden of heart failure (HF) have largely omitted HF diagnosed in outpatient settings. We quantified annual incidence rates ([IR] per 1,000 person years) of HF identified in ambulatory clinics, emergency departments (EDs), and during hospital stays in a national probability sample of Medicare beneficiaries from 2008 to 2014, by age and race/ethnicity. A 20% random sample of Medicare beneficiaries ages ≥65 years with continuous Medicare Parts A, B, and D coverage was used to estimate annual IRs of HF identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Of the 681,487 beneficiaries with incident HF from 2008 to 2014, 283,451 (41%) presented in ambulatory clinics, 76,919 (11%) in EDs, and 321,117 (47%) in hospitals. Overall, incidence of HF in ambulatory clinics decreased from 2008 (IR 22.2, 95% confidence interval [CI] 22.0, 22.4) to 2014 (IR 15.0, 95% CI 14.8, 15.1). Similarly, incidence of HF-related ED visits without an admission to the hospital decreased somewhat from 2008 (IR 5.5, 95% CI 5.4, 5.6) to 2012 (IR 4.2, 95% CI 4.1, 4.3) and stabilized from 2013 to 2014. Similar to previous reports, HF hospitalizations, both International Classification of Diseases, Ninth Revision, Clinical Modification code 428.x in the primary and any position, decreased over the study period. More than half of all new cases of HF in Medicare beneficiaries presented in an ambulatory clinic or ED. The overall incidence of HF decreased from 2008 to 2014, regardless of health-care setting. In conclusion, consideration of outpatient HF is warranted to better understand the burden of HF and its temporal trends. |
Camplain, Ricky; Kucharska-Newton, Anna; Loehr, Laura; Keyserling, Thomas C; Layton, Bradley J; Wruck, Lisa; Folsom, Aaron R; Bertoni, Alain G; Heiss, Gerardo Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study Journal Article Journal of Cardiac Failure, 23 (11), pp. 802-808, 2017. @article{Camplain2017b, title = {Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study}, author = {Ricky Camplain and Anna Kucharska-Newton and Laura Loehr and Thomas C Keyserling and Bradley J Layton and Lisa Wruck and Aaron R Folsom and Alain G Bertoni and Gerardo Heiss}, url = {https://www.ncbi.nlm.nih.gov/pubmed/28893677}, year = {2017}, date = {2017-11-01}, journal = {Journal of Cardiac Failure}, volume = {23}, number = {11}, pages = {802-808}, 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.}, keywords = {}, pubstate = {published}, tppubtype = {article} } 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. |
Camplain, Ricky; Kucharska-Newton, Anna; Loehr, Laura; Keyserling, Thomas C; Layton, Bradley J; Wruck, Lisa; Folsom, Aaron R; Bertoni, Alain G; Heiss, Gerardo Accuracy of self-reported heart failure. The atherosclerosis risk in communities (ARIC) study Journal Article Journal of Cardiac Failure, 23 (11), pp. 802-808, 2017. @article{Camplain2017c, title = {Accuracy of self-reported heart failure. The atherosclerosis risk in communities (ARIC) study}, author = {Ricky Camplain and Anna Kucharska-Newton and Laura Loehr and Thomas C Keyserling and Bradley J Layton and Lisa Wruck and Aaron R Folsom and Alain G Bertoni and Gerardo Heiss}, url = {https://www.sciencedirect.com/science/article/pii/S1071916417311673?via%3Dihub}, year = {2017}, date = {2017-11-01}, journal = {Journal of Cardiac Failure}, volume = {23}, number = {11}, pages = {802-808}, 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.}, keywords = {}, pubstate = {published}, tppubtype = {article} } 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. |
Camplain, Ricky; Kucharska-Newton, Anna; Cuthbertson, Carmen C; Wright, Jacqueline D; Alonso, Alvaro; Heiss, Gerardo Pharmacoepidemiology and Drug Safety, 26 (4), pp. 421-428, 2017. @article{Camplain2017c, title = {Misclassification of incident hospitalized and outpatient heart failure in administrative claims data: the Atherosclerosis Risk in Communities (ARIC) study.}, author = {Ricky Camplain and Anna Kucharska-Newton and Carmen C Cuthbertson and Jacqueline D Wright and Alvaro Alonso and Gerardo Heiss}, url = {http://onlinelibrary.wiley.com/doi/10.1002/pds.4162/abstract;jsessionid=84471AF98391D8C41703CB2E376B34F1.f04t01}, year = {2017}, date = {2017-01-25}, journal = {Pharmacoepidemiology and Drug Safety}, volume = {26}, number = {4}, pages = {421-428}, abstract = {PURPOSE: The aim of this study was to quantify the influence of the length of the look-back period on misclassification of heart failure (HF) incidence in Medicare claims available for participants of a population-based cohort. METHODS: Atherosclerosis Risk in Communities participants with ≥3 years of continuous fee-for-service Medicare enrollment from 2000 to 2012 was assigned an index date 36 months after enrollment separating the time-in-observation period into the look-back and the incidence periods. Incident HF events were identified using ICD-9-CM code algorithms as the first observed hospitalization claim or the second of two HF outpatient claims occurring within 12 months. Using 36 months as a referent, the look-back period was reduced by 6-month increments. For each look-back period, we calculated the incidence rate, percent of prevalent HF events misclassified as incident, and loss in sample size. RESULTS: We identified 9568 Atherosclerosis Risk in Communities participants at risk for HF. For hospitalized and outpatient HF, the number of events misclassified as incident increased, and the total number of incident events decreased with increased length of the look-back period. The incident rate (per 1000 person years) decreased with increased length of the look-back period from 6 to 36 months and had a greater impact on outpatient HF; for example, from 11.2 to 10.6 for ICD-9-CM 428.xx hospitalization in the primary position and 10.5 to 7.9 for outpatient HF. CONCLUSION: Our estimates can be used to optimize trade-offs between the degree of misclassification and number of events in the estimation of incident HF from administrative claims data, as pertinent to different study questions. Copyright © 2017 John Wiley & Sons, Ltd.}, keywords = {}, pubstate = {published}, tppubtype = {article} } PURPOSE: The aim of this study was to quantify the influence of the length of the look-back period on misclassification of heart failure (HF) incidence in Medicare claims available for participants of a population-based cohort. METHODS: Atherosclerosis Risk in Communities participants with ≥3 years of continuous fee-for-service Medicare enrollment from 2000 to 2012 was assigned an index date 36 months after enrollment separating the time-in-observation period into the look-back and the incidence periods. Incident HF events were identified using ICD-9-CM code algorithms as the first observed hospitalization claim or the second of two HF outpatient claims occurring within 12 months. Using 36 months as a referent, the look-back period was reduced by 6-month increments. For each look-back period, we calculated the incidence rate, percent of prevalent HF events misclassified as incident, and loss in sample size. RESULTS: We identified 9568 Atherosclerosis Risk in Communities participants at risk for HF. For hospitalized and outpatient HF, the number of events misclassified as incident increased, and the total number of incident events decreased with increased length of the look-back period. The incident rate (per 1000 person years) decreased with increased length of the look-back period from 6 to 36 months and had a greater impact on outpatient HF; for example, from 11.2 to 10.6 for ICD-9-CM 428.xx hospitalization in the primary position and 10.5 to 7.9 for outpatient HF. CONCLUSION: Our estimates can be used to optimize trade-offs between the degree of misclassification and number of events in the estimation of incident HF from administrative claims data, as pertinent to different study questions. Copyright © 2017 John Wiley & Sons, Ltd. |
2018 |
Camplain, Ricky; Kucharska-Newton, Anna; Keyserling, Thomas C; Layton, Bradley J; Loehr, Laura; Heiss, Gerardo Incidence of Heart Failure Observed in Emergency Departments, Ambulatory Clinics, and Hospitals Journal Article The American Journal of Cardiology, 121 (1), pp. 1328-1335, 2018. @article{Camplain2018, title = {Incidence of Heart Failure Observed in Emergency Departments, Ambulatory Clinics, and Hospitals}, author = {Ricky Camplain and Anna Kucharska-Newton and Thomas C Keyserling and Bradley J Layton and Laura Loehr and Gerardo Heiss}, url = {https://www.sciencedirect.com/science/article/pii/S0002914918302509?via%3Dihub}, doi = {10.1016/j.amjcard.2018.02.014}, year = {2018}, date = {2018-06-01}, journal = {The American Journal of Cardiology}, volume = {121}, number = {1}, pages = {1328-1335}, abstract = {Reports on the burden of heart failure (HF) have largely omitted HF diagnosed in outpatient settings. We quantified annual incidence rates ([IR] per 1,000 person years) of HF identified in ambulatory clinics, emergency departments (EDs), and during hospital stays in a national probability sample of Medicare beneficiaries from 2008 to 2014, by age and race/ethnicity. A 20% random sample of Medicare beneficiaries ages ≥65 years with continuous Medicare Parts A, B, and D coverage was used to estimate annual IRs of HF identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Of the 681,487 beneficiaries with incident HF from 2008 to 2014, 283,451 (41%) presented in ambulatory clinics, 76,919 (11%) in EDs, and 321,117 (47%) in hospitals. Overall, incidence of HF in ambulatory clinics decreased from 2008 (IR 22.2, 95% confidence interval [CI] 22.0, 22.4) to 2014 (IR 15.0, 95% CI 14.8, 15.1). Similarly, incidence of HF-related ED visits without an admission to the hospital decreased somewhat from 2008 (IR 5.5, 95% CI 5.4, 5.6) to 2012 (IR 4.2, 95% CI 4.1, 4.3) and stabilized from 2013 to 2014. Similar to previous reports, HF hospitalizations, both International Classification of Diseases, Ninth Revision, Clinical Modification code 428.x in the primary and any position, decreased over the study period. More than half of all new cases of HF in Medicare beneficiaries presented in an ambulatory clinic or ED. The overall incidence of HF decreased from 2008 to 2014, regardless of health-care setting. In conclusion, consideration of outpatient HF is warranted to better understand the burden of HF and its temporal trends.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Reports on the burden of heart failure (HF) have largely omitted HF diagnosed in outpatient settings. We quantified annual incidence rates ([IR] per 1,000 person years) of HF identified in ambulatory clinics, emergency departments (EDs), and during hospital stays in a national probability sample of Medicare beneficiaries from 2008 to 2014, by age and race/ethnicity. A 20% random sample of Medicare beneficiaries ages ≥65 years with continuous Medicare Parts A, B, and D coverage was used to estimate annual IRs of HF identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Of the 681,487 beneficiaries with incident HF from 2008 to 2014, 283,451 (41%) presented in ambulatory clinics, 76,919 (11%) in EDs, and 321,117 (47%) in hospitals. Overall, incidence of HF in ambulatory clinics decreased from 2008 (IR 22.2, 95% confidence interval [CI] 22.0, 22.4) to 2014 (IR 15.0, 95% CI 14.8, 15.1). Similarly, incidence of HF-related ED visits without an admission to the hospital decreased somewhat from 2008 (IR 5.5, 95% CI 5.4, 5.6) to 2012 (IR 4.2, 95% CI 4.1, 4.3) and stabilized from 2013 to 2014. Similar to previous reports, HF hospitalizations, both International Classification of Diseases, Ninth Revision, Clinical Modification code 428.x in the primary and any position, decreased over the study period. More than half of all new cases of HF in Medicare beneficiaries presented in an ambulatory clinic or ED. The overall incidence of HF decreased from 2008 to 2014, regardless of health-care setting. In conclusion, consideration of outpatient HF is warranted to better understand the burden of HF and its temporal trends. |
2017 |
Camplain, Ricky; Kucharska-Newton, Anna; Loehr, Laura; Keyserling, Thomas C; Layton, Bradley J; Wruck, Lisa; Folsom, Aaron R; Bertoni, Alain G; Heiss, Gerardo Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study Journal Article Journal of Cardiac Failure, 23 (11), pp. 802-808, 2017. @article{Camplain2017b, title = {Accuracy of Self-Reported Heart Failure. The Atherosclerosis Risk in Communities (ARIC) Study}, author = {Ricky Camplain and Anna Kucharska-Newton and Laura Loehr and Thomas C Keyserling and Bradley J Layton and Lisa Wruck and Aaron R Folsom and Alain G Bertoni and Gerardo Heiss}, url = {https://www.ncbi.nlm.nih.gov/pubmed/28893677}, year = {2017}, date = {2017-11-01}, journal = {Journal of Cardiac Failure}, volume = {23}, number = {11}, pages = {802-808}, 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.}, keywords = {}, pubstate = {published}, tppubtype = {article} } 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. |
Camplain, Ricky; Kucharska-Newton, Anna; Loehr, Laura; Keyserling, Thomas C; Layton, Bradley J; Wruck, Lisa; Folsom, Aaron R; Bertoni, Alain G; Heiss, Gerardo Accuracy of self-reported heart failure. The atherosclerosis risk in communities (ARIC) study Journal Article Journal of Cardiac Failure, 23 (11), pp. 802-808, 2017. @article{Camplain2017c, title = {Accuracy of self-reported heart failure. The atherosclerosis risk in communities (ARIC) study}, author = {Ricky Camplain and Anna Kucharska-Newton and Laura Loehr and Thomas C Keyserling and Bradley J Layton and Lisa Wruck and Aaron R Folsom and Alain G Bertoni and Gerardo Heiss}, url = {https://www.sciencedirect.com/science/article/pii/S1071916417311673?via%3Dihub}, year = {2017}, date = {2017-11-01}, journal = {Journal of Cardiac Failure}, volume = {23}, number = {11}, pages = {802-808}, 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.}, keywords = {}, pubstate = {published}, tppubtype = {article} } 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. |
Camplain, Ricky; Kucharska-Newton, Anna; Cuthbertson, Carmen C; Wright, Jacqueline D; Alonso, Alvaro; Heiss, Gerardo Pharmacoepidemiology and Drug Safety, 26 (4), pp. 421-428, 2017. @article{Camplain2017c, title = {Misclassification of incident hospitalized and outpatient heart failure in administrative claims data: the Atherosclerosis Risk in Communities (ARIC) study.}, author = {Ricky Camplain and Anna Kucharska-Newton and Carmen C Cuthbertson and Jacqueline D Wright and Alvaro Alonso and Gerardo Heiss}, url = {http://onlinelibrary.wiley.com/doi/10.1002/pds.4162/abstract;jsessionid=84471AF98391D8C41703CB2E376B34F1.f04t01}, year = {2017}, date = {2017-01-25}, journal = {Pharmacoepidemiology and Drug Safety}, volume = {26}, number = {4}, pages = {421-428}, abstract = {PURPOSE: The aim of this study was to quantify the influence of the length of the look-back period on misclassification of heart failure (HF) incidence in Medicare claims available for participants of a population-based cohort. METHODS: Atherosclerosis Risk in Communities participants with ≥3 years of continuous fee-for-service Medicare enrollment from 2000 to 2012 was assigned an index date 36 months after enrollment separating the time-in-observation period into the look-back and the incidence periods. Incident HF events were identified using ICD-9-CM code algorithms as the first observed hospitalization claim or the second of two HF outpatient claims occurring within 12 months. Using 36 months as a referent, the look-back period was reduced by 6-month increments. For each look-back period, we calculated the incidence rate, percent of prevalent HF events misclassified as incident, and loss in sample size. RESULTS: We identified 9568 Atherosclerosis Risk in Communities participants at risk for HF. For hospitalized and outpatient HF, the number of events misclassified as incident increased, and the total number of incident events decreased with increased length of the look-back period. The incident rate (per 1000 person years) decreased with increased length of the look-back period from 6 to 36 months and had a greater impact on outpatient HF; for example, from 11.2 to 10.6 for ICD-9-CM 428.xx hospitalization in the primary position and 10.5 to 7.9 for outpatient HF. CONCLUSION: Our estimates can be used to optimize trade-offs between the degree of misclassification and number of events in the estimation of incident HF from administrative claims data, as pertinent to different study questions. Copyright © 2017 John Wiley & Sons, Ltd.}, keywords = {}, pubstate = {published}, tppubtype = {article} } PURPOSE: The aim of this study was to quantify the influence of the length of the look-back period on misclassification of heart failure (HF) incidence in Medicare claims available for participants of a population-based cohort. METHODS: Atherosclerosis Risk in Communities participants with ≥3 years of continuous fee-for-service Medicare enrollment from 2000 to 2012 was assigned an index date 36 months after enrollment separating the time-in-observation period into the look-back and the incidence periods. Incident HF events were identified using ICD-9-CM code algorithms as the first observed hospitalization claim or the second of two HF outpatient claims occurring within 12 months. Using 36 months as a referent, the look-back period was reduced by 6-month increments. For each look-back period, we calculated the incidence rate, percent of prevalent HF events misclassified as incident, and loss in sample size. RESULTS: We identified 9568 Atherosclerosis Risk in Communities participants at risk for HF. For hospitalized and outpatient HF, the number of events misclassified as incident increased, and the total number of incident events decreased with increased length of the look-back period. The incident rate (per 1000 person years) decreased with increased length of the look-back period from 6 to 36 months and had a greater impact on outpatient HF; for example, from 11.2 to 10.6 for ICD-9-CM 428.xx hospitalization in the primary position and 10.5 to 7.9 for outpatient HF. CONCLUSION: Our estimates can be used to optimize trade-offs between the degree of misclassification and number of events in the estimation of incident HF from administrative claims data, as pertinent to different study questions. Copyright © 2017 John Wiley & Sons, Ltd. |