{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,25]],"date-time":"2025-11-25T20:42:23Z","timestamp":1764103343838,"version":"3.28.0"},"reference-count":37,"publisher":"Georg Thieme Verlag KG","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Objective\u2003Data derived from the electronic health record (EHR) are commonly reused for quality improvement, clinical decision-making, and empirical research despite having data quality challenges. Research highlighting EHR data quality concerns has largely been examined and identified during traditional in-person visits. To understand variations in data quality among patients managing type 2 diabetes mellitus (T2DM) with and without a history of telehealth visits, we examined three EHR data quality dimensions: timeliness, completeness, and information density.<\/jats:p><jats:p>\n          Methods\u2003We used EHR data (2016\u20132021) from a local enterprise data warehouse to quantify timeliness, completeness, and information density for diagnostic and laboratory test data. Means and chi-squared significance tests were computed to compare data quality dimensions between patients with and without a history of telehealth use.<\/jats:p><jats:p>\n          Results\u2003Mean timeliness or T2DM measurement age for the study sample was 77.8 days (95% confidence interval [CI], 39.6\u2013116.4). Mean completeness for the sample was 0.891 (95% CI, 0.868\u20130.914). The mean information density score was 0.787 (95% CI, 0.747\u20130.827). EHR data for patients managing T2DM with a history of telehealth use were timelier (73.3 vs. 79.8 days), and measurements were more uniform across visits (0.795 vs. 0.784) based on information density scores, compared with patients with no history of telehealth use.<\/jats:p><jats:p>\n          Conclusion\u2003Overall, EHR data for patients managing T2DM with a history of telehealth visits were generally timelier and measurements were more uniform across visits than for patients with no history of telehealth visits. Chronic disease care relies on comprehensive patient data collected via hybrid care delivery models and includes important domains for continued data quality assessments prior to secondary reuse purposes.<\/jats:p>","DOI":"10.1055\/s-0042-1758737","type":"journal-article","created":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T00:26:58Z","timestamp":1671064018000},"page":"1172-1180","source":"Crossref","is-referenced-by-count":9,"title":["Quantifying Electronic Health Record Data Quality in Telehealth and Office-Based Diabetes Care"],"prefix":"10.1055","volume":"13","author":[{"given":"Kevin K.","family":"Wiley","sequence":"additional","affiliation":[{"name":"Department of Healthcare Leadership and Management, Medical University of South Carolina, Charleston, South Carolina, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eneida","family":"Mendonca","sequence":"additional","affiliation":[{"name":"University of Cincinnati, Cincinnati, Ohio, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Justin","family":"Blackburn","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nir","family":"Menachemi","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, Indiana, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary De","family":"Groot","sequence":"additional","affiliation":[{"name":"Indiana University School of Medicine, Indianapolis, Indiana"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua R.","family":"Vest","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, Richard M. 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Telemedicine for Covid-19","volume":"382","author":"J E Hollander","year":"2020","journal-title":"N Engl J Med"},{"issue":"06","key":"ref15","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1007\/s11606-020-05673-w","article-title":"\u201cI'm not feeling like I'm part of the conversation\u201d patients' perspectives on communicating in clinical video telehealth visits","volume":"35","author":"H S Gordon","year":"2020","journal-title":"J Gen Intern Med"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.procs.2015.08.499","article-title":"Effect of home telehealth data quality on decision support system performance","volume":"64","author":"M S Mohktar","year":"2015","journal-title":"Procedia Comput Sci"},{"issue":"03","key":"ref17","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1177\/1932296818812062","article-title":"Measures of accuracy for continuous glucose monitoring and blood glucose monitoring devices","volume":"13","author":"G Freckmann","year":"2019","journal-title":"J Diabetes Sci Technol"},{"issue":"04","key":"ref18","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.2337\/diacare.26.4.1002","article-title":"A comparison of diabetes education administered through telemedicine versus in person","volume":"26","author":"R E Izquierdo","year":"2003","journal-title":"Diabetes Care"},{"key":"ref19","first-page":"1b","article-title":"A patient-centric, provider-assisted diabetes telehealth self-management intervention for urban minorities","volume":"8","author":"E L Carter","year":"2011","journal-title":"Perspect Health Inf Manag"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"S33","DOI":"10.2337\/diacare.26.2007.S33","article-title":"Standards of medical care for patients with diabetes mellitus","volume":"26","author":"American Diabetes Association","year":"2003","journal-title":"Diabetes Care"},{"issue":"02","key":"ref21","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1093\/fampra\/20.2.173","article-title":"Quality of recording of data from patients with type 2 diabetes is not a valid indicator of quality of care. A cross-sectional study","volume":"20","author":"A N Goudswaard","year":"2003","journal-title":"Fam Pract"},{"issue":"05","key":"ref22","doi-asserted-by":"crossref","first-page":"1214","DOI":"10.1377\/hlthaff.24.5.1214","article-title":"The Indiana network for patient care: a working local health information infrastructure. 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immunization data in Washington State in 2010: a comparison of data exchange methods","volume":"2012","author":"R A Hills","year":"2012","journal-title":"AMIA Annu Symp Proc"},{"key":"ref27","first-page":"1318","article-title":"Quantifying the longitudinal value of healthcare record collections for pharmacoepidemiology","volume":"2011","author":"M Sperrin","year":"2011","journal-title":"AMIA Annu Symp Proc"},{"issue":"05","key":"ref28","doi-asserted-by":"crossref","first-page":"830","DOI":"10.1016\/j.jbi.2013.06.010","article-title":"Defining and measuring completeness of electronic health records for secondary use","volume":"46","author":"N G Weiskopf","year":"2013","journal-title":"J Biomed Inform"},{"issue":"09","key":"ref29","doi-asserted-by":"crossref","first-page":"1515","DOI":"10.2337\/diacare.24.9.1515","article-title":"Organizing diabetes care: identify, monitor, prioritize, intensify","volume":"24","author":"P J O'Connor","year":"2001","journal-title":"Diabetes Care"},{"key":"ref30","first-page":"1080","article-title":"Adoption and use of an online patient portal for diabetes (Diabetes-STAR)","volume":"2006","author":"S E Ross","year":"2006","journal-title":"AMIA Annu Symp Proc"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1038\/s41746-018-0030-8","article-title":"From smartphone to EHR: a case report on integrating patient-generated health data","volume":"1","author":"N Genes","year":"2018","journal-title":"NPJ Digit Med"},{"issue":"06","key":"ref32","doi-asserted-by":"crossref","first-page":"e205867","DOI":"10.1001\/jamanetworkopen.2020.5867","article-title":"Frequency and types of patient-reported errors in electronic health record ambulatory care notes","volume":"3","author":"S K Bell","year":"2020","journal-title":"JAMA Netw Open"},{"issue":"05","key":"ref33","doi-asserted-by":"crossref","first-page":"1574","DOI":"10.1016\/j.jvs.2018.08.173","article-title":"Vascular surgery residents spend one fifth of their time on electronic health records after duty hours","volume":"69","author":"F Aziz","year":"2019","journal-title":"J Vasc Surg"},{"issue":"12","key":"ref34","doi-asserted-by":"crossref","first-page":"e2136405","DOI":"10.1001\/jamanetworkopen.2021.36405","article-title":"Assessment of patient preferences for Telehealth in post-COVID-19 pandemic health care","volume":"4","author":"Z S Predmore","year":"2021","journal-title":"JAMA Netw Open"},{"key":"ref40","first-page":"33","volume-title":"Measuring data accuracy: a framework and review","author":"T C Redman","year":"2014"},{"key":"ref41","first-page":"724","article-title":"A system for solution-orientated reporting of errors associated with the extraction of routinely collected clinical data for research and quality improvement","volume":"160","author":"G Michalakidis","year":"2010","journal-title":"Stud Health Technol 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