Chronic Disease Surveillance Using Electronic Health Records From Health Centers in a Large Urban Setting.
Journal
Journal of public health management and practice : JPHMP
ISSN: 1550-5022
Titre abrégé: J Public Health Manag Pract
Pays: United States
ID NLM: 9505213
Informations de publication
Date de publication:
Historique:
pubmed:
7
11
2019
medline:
16
10
2021
entrez:
6
11
2019
Statut:
ppublish
Résumé
To assess the validity of electronic health records (EHRs) from a network of health centers for chronic disease surveillance among an underserved population in an urban setting. EHRs from a network of health centers were used to calculate the prevalence of chronic disease among adult and child patient populations during 2016. Two population-based surveys with local estimates of chronic disease prevalence were compared with the EHR prevalences. A network of health centers that provides health care services to an underserved population in a large urban setting. A total of 187 292 patients who had at least 1 health care visit recorded in the Philadelphia health center network. Chronic disease indicator (CDI) prevalence of adult obesity, adult smoking, adult diabetes, adult hypertension, child obesity, and child asthma. Health center CDI proportions were compared with survey estimates. Overall consistency between the health center estimates and surveys varied by CDI. With the exception of childhood obesity, all health center CDI proportions fell within the 95% CI for at least 1 comparison survey estimate. Statistically significant differences were observed and varied by CDI. This analysis presents a novel use of existing EHR data to estimate chronic disease prevalence among underserved populations. With the increased use of EHRs in health centers, data from health center networks may supplement chronic disease surveillance efforts, if used appropriately.
Identifiants
pubmed: 31688745
pii: 00124784-202103000-00013
doi: 10.1097/PHH.0000000000001097
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Pagination
186-192Informations de copyright
Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors declare that they have no conflicts of interest.
Références
Waters H, Graf M. The costs of chronic diseases in the U.S. Milken Institute Web site. https://assets1b.milkeninstitute.org/assets/Publication/ResearchReport/PDF/ChronicDiseases-HighRes-FINAL.pdf . Updated August 2018. Accessed September 2018.
Kochanek KD, Murphy SL, Xu JQ, Arias E. Mortality in the United States, 2016. Hyattsville, MD: National Center for Health Statistics; 2017. NCHS Data Brief No. 293.
Holt JB, Huston SL, Heidari K, et al. Indicators for chronic disease surveillance—United States, 2013. MMWR Morb Mortal Wkly Rep. 2015;64(RR-01):1–15.
Birkhead GS, Klompas M, Shah NR. Uses of electronic health records for public health surveillance to advance public health. Annu Rev Public Health. 2015;36(1):345–359.
Wagaw F, Okoro CA, Kim S, Park J, Rachman F. Linking data from health surveys and electronic health records: a demonstration project in two Chicago health center clinics. Prev Chronic Dis. 2018;15:E09.
Pierannunzi C, Hu SS, Balluz L. A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS), 2004-2011. BMC Med Res Methodol. 2013;13:49.
Cronin KA, Miglioretti DL, Krapcho M, et al. Bias associated with self-report of prior screening mammography. Cancer Epidemiol Biomarkers Prev. 2009;18(6):1699–1705.
Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obes Rev. 2007;8(4):307–326.
Newton-Dame R, McVeigh KH, Schreibstein L, et al. Design of the New York City Macroscope: innovations in population health surveillance using electronic health records. EGEMS (Wash DC). 2016;4(1):1265.
Flood TL, Zhao YQ, Tomayko EJ, Tandias A, Carrel AL, Hanrahan LP. Electronic health records and community health surveillance of childhood obesity. Am J Prev Med. 2015;48(2):234–240.
Klompas M, McVetta J, Lazarus R, et al. Integrating clinical practice and public health surveillance using electronic medical record systems. Am J Prev Med. 2012;42(6)(suppl 2):S154–S162.
Kukafka R, Ancker JS, Chan C, et al. Redesigning electronic health record systems to support public health. J Biomed Inform. 2007;40(4):398–409.
McVeigh KH, Newton-Dame R, Chan PY, et al. Can electronic health records be used for population health surveillance? Validating population health metrics against established survey data. EGEMS (Wash DC). 2016;4(1):1267.
US Census Bureau. 2012-2016 American Community Survey 5-year estimates. https://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml . Accessed October 2, 2018.
Health Center Controlled Networks. Health Resources and Services Administration Web site. https://bphc.hrsa.gov/qualityimprovement/strategicpartnerships/hccn.html . Updated September 2018. Accessed January 14, 2019.
Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Survey Data. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2015.
Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Survey Questionnaire. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2015.
Ogden CL, Carroll MD, Fakhouri TH, et al. Prevalence of obesity among youths by household income and education level of head of household—United States 2011-2014. MMWR Morb Mortal Wkly Rep. 2018;67(6):186–189.
Thorpe LE, McVeigh KH, Perlman S, et al. Monitoring prevalence, treatment, and control of metabolic conditions in New York City adults using 2013 primary care electronic health records: a surveillance validation study. EGEMS (Wash DC). 2016;4(1):1266.
Gutilla MJ, Davidson AJ, Daley MF, Anderson GB, Marshall JA, Magzamen S. Data for community health assessment in rural Colorado: a comparison of electronic health records to public health surveys to describe childhood obesity. J Public Health Manag Pract. 2017;23(suppl 4) Suppl, Community Health Status Assessment):S53–S62.