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Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension
BACKGROUND: Electronic health record (EHR) data, collected primarily for individual patient care and billing purposes, compiled in health information exchanges (HIEs) may have a secondary use for population health surveillance of noncommunicable diseases. However, data compilation across fragmented...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694493/ https://www.ncbi.nlm.nih.gov/pubmed/31412826 http://dx.doi.org/10.1186/s12889-019-7367-z |
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author | Horth, Roberta Z. Wagstaff, Shelly Jeppson, Theron Patel, Vishal McClellan, Jefferson Bissonette, Nicole Friedrichs, Michael Dunn, Angela C. |
author_facet | Horth, Roberta Z. Wagstaff, Shelly Jeppson, Theron Patel, Vishal McClellan, Jefferson Bissonette, Nicole Friedrichs, Michael Dunn, Angela C. |
author_sort | Horth, Roberta Z. |
collection | PubMed |
description | BACKGROUND: Electronic health record (EHR) data, collected primarily for individual patient care and billing purposes, compiled in health information exchanges (HIEs) may have a secondary use for population health surveillance of noncommunicable diseases. However, data compilation across fragmented data sources into HIEs presents potential barriers and quality of data is unknown. METHODS: We compared 2015 patient data from a mid-size health system (Database A) to data from System A patients in the Utah HIE (Database B). We calculated concordance of structured data (sex and age) and unstructured data (blood pressure reading and A1C). We estimated adjusted hypertension and diabetes prevalence in each database and compared these across age groups. RESULTS: Matching resulted in 72,356 unique patients. Concordance between Database A and Database B exceeded 99% for sex and age, but was 89% for A1C results and 54% for blood pressure readings. Sensitivity, using Database A as the standard, was 57% for hypertension and 55% for diabetes. Age and sex adjusted prevalence of diabetes (8.4% vs 5.8%, Database A and B, respectively) and hypertension (14.5% vs 11.6%, respectively) differed, but this difference was consistent with parallel slopes in prevalence over age groups in both databases. CONCLUSIONS: We identified several gaps in the use of HIE data for surveillance of diabetes and hypertension. High concordance of structured data demonstrate some promise in HIEs capacity to capture patient data. Improving HIE data quality through increased use of structured variables may help make HIE data useful for population health surveillance in places with fragmented EHR systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-019-7367-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6694493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-66944932019-08-19 Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension Horth, Roberta Z. Wagstaff, Shelly Jeppson, Theron Patel, Vishal McClellan, Jefferson Bissonette, Nicole Friedrichs, Michael Dunn, Angela C. BMC Public Health Research Article BACKGROUND: Electronic health record (EHR) data, collected primarily for individual patient care and billing purposes, compiled in health information exchanges (HIEs) may have a secondary use for population health surveillance of noncommunicable diseases. However, data compilation across fragmented data sources into HIEs presents potential barriers and quality of data is unknown. METHODS: We compared 2015 patient data from a mid-size health system (Database A) to data from System A patients in the Utah HIE (Database B). We calculated concordance of structured data (sex and age) and unstructured data (blood pressure reading and A1C). We estimated adjusted hypertension and diabetes prevalence in each database and compared these across age groups. RESULTS: Matching resulted in 72,356 unique patients. Concordance between Database A and Database B exceeded 99% for sex and age, but was 89% for A1C results and 54% for blood pressure readings. Sensitivity, using Database A as the standard, was 57% for hypertension and 55% for diabetes. Age and sex adjusted prevalence of diabetes (8.4% vs 5.8%, Database A and B, respectively) and hypertension (14.5% vs 11.6%, respectively) differed, but this difference was consistent with parallel slopes in prevalence over age groups in both databases. CONCLUSIONS: We identified several gaps in the use of HIE data for surveillance of diabetes and hypertension. High concordance of structured data demonstrate some promise in HIEs capacity to capture patient data. Improving HIE data quality through increased use of structured variables may help make HIE data useful for population health surveillance in places with fragmented EHR systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12889-019-7367-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-08-14 /pmc/articles/PMC6694493/ /pubmed/31412826 http://dx.doi.org/10.1186/s12889-019-7367-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Horth, Roberta Z. Wagstaff, Shelly Jeppson, Theron Patel, Vishal McClellan, Jefferson Bissonette, Nicole Friedrichs, Michael Dunn, Angela C. Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title | Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title_full | Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title_fullStr | Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title_full_unstemmed | Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title_short | Use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
title_sort | use of electronic health records from a statewide health information exchange to support public health surveillance of diabetes and hypertension |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694493/ https://www.ncbi.nlm.nih.gov/pubmed/31412826 http://dx.doi.org/10.1186/s12889-019-7367-z |
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