scholarly journals Identification and validation of uterine perforation, intrauterine device expulsion, and breastfeeding in four health care systems with electronic health records

2019 ◽  
Vol Volume 11 ◽  
pp. 635-643 ◽  
Author(s):  
Mary S Anthony ◽  
Mary Anne Armstrong ◽  
Darios Getahun ◽  
Delia Scholes ◽  
Jennifer Gatz ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Health Care Systems ◽  
Intrauterine Device ◽  
Uterine Perforation ◽  
Health Records ◽  
Care Systems ◽  
Electronic Health

scholarly journals Biases introduced by filtering electronic health records for patients with “complete data”

2017 ◽  
Vol 24 (6) ◽  
pp. 1134-1141 ◽  
Author(s):  
Griffin M Weber ◽  
William G Adams ◽  
Elmer V Bernstam ◽  
Jonathan P Bickel ◽  
Kathe P Fox ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Large Scale ◽  
Health Care Systems ◽  
Data Types ◽  
Health Records ◽  
Data Completeness ◽  
Number Of Patients ◽  
Care Systems ◽  
Electronic Health

Abstract Objective One promise of nationwide adoption of electronic health records (EHRs) is the availability of data for large-scale clinical research studies. However, because the same patient could be treated at multiple health care institutions, data from only a single site might not contain the complete medical history for that patient, meaning that critical events could be missing. In this study, we evaluate how simple heuristic checks for data “completeness” affect the number of patients in the resulting cohort and introduce potential biases. Materials and Methods We began with a set of 16 filters that check for the presence of demographics, laboratory tests, and other types of data, and then systematically applied all 216 possible combinations of these filters to the EHR data for 12 million patients at 7 health care systems and a separate payor claims database of 7 million members. Results EHR data showed considerable variability in data completeness across sites and high correlation between data types. For example, the fraction of patients with diagnoses increased from 35.0% in all patients to 90.9% in those with at least 1 medication. An unrelated claims dataset independently showed that most filters select members who are older and more likely female and can eliminate large portions of the population whose data are actually complete. Discussion and Conclusion As investigators design studies, they need to balance their confidence in the completeness of the data with the effects of placing requirements on the data on the resulting patient cohort.

scholarly journals From screening to ascertainment of the primary outcome using electronic health records: Challenges in the STRIDE trial

2020 ◽  
Vol 17 (4) ◽  
pp. 346-350
Author(s):  
Denise Esserman
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Health Care Systems ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Health Records ◽  
Record Data ◽  
Care Systems ◽  
Electronic Health ◽  
Data Elements

Electronic health record data are a rich resource and can be utilized to answer a wealth of research questions. It is important when using electronic health record data in clinical trials that systems be put in place and vetted prior to enrollment to ensure data elements can be collected consistently across all health care systems. It is often overlooked how something conceptualized on paper (e.g. use of the electronic health record in a study) can be difficult to implement in practice. This article discusses some of the challenges in using electronic health records in the conduct of the STRIDE (Strategies to Reduce Injuries and Develop Confidence in Elders) trial, how we handled those challenges, and the lessons we learned for the conduct of future trials looking to employ the electronic health record.

Negotiating stigma in health care: disclosure and the role of electronic health records

2015 ◽  
Vol 24 (3) ◽  
pp. 227-241 ◽  
Author(s):  
Timothy Stablein ◽  
Joseph Lorenzo Hall ◽  
Chauna Pervis ◽  
Denise L. Anthony
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health
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