scholarly journals A refined methodology for validation of information models derived from flowsheet data and applied to a genitourinary case

2020 ◽  
Vol 27 (11) ◽  
pp. 1732-1740
Author(s):  
Bonnie L Westra ◽  
, Kay S Lytle ◽  
Luann Whittenburg ◽  
Mischa Adams ◽  
Samira Ali ◽  
...  

Abstract Use of electronic health record data is expanding to support quality improvement and research; however, this requires standardization of the data and validation within and across organizations. Information models (IMs) are created to standardize data elements into a logical organization that includes data elements, definitions, data types, values, and relationships. To be generalizable, these models need to be validated across organizations. The purpose of this case report is to describe a refined methodology for validation of flowsheet IMs and apply the revised process to a genitourinary IM created in one organization. The refined IM process, adding evidence and input from experts, produced a clinically relevant and evidence-based model of genitourinary care. The refined IM process provides a foundation for optimizing electronic health records with comparable nurse sensitive data that can add to common data models for continuity of care and ongoing use for quality improvement and research.

2018 ◽  
Vol 31 (3) ◽  
pp. 398-409 ◽  
Author(s):  
Jennifer R. Hemler ◽  
Jennifer D. Hall ◽  
Raja A. Cholan ◽  
Benjamin F. Crabtree ◽  
Laura J. Damschroder ◽  
...  

2020 ◽  
Vol 17 (4) ◽  
pp. 346-350
Author(s):  
Denise Esserman

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.


2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Courtney Omary ◽  
Michelle Cox-Henley ◽  
Vicki Stover Hertzberg ◽  
John N. Cranmer ◽  
Roy L. Simpson

2010 ◽  
Vol 01 (01) ◽  
pp. 32-37 ◽  
Author(s):  
David Bates ◽  
Adam Wright

SummaryBackground: Many natural phenomena demonstrate power-law distributions, where very common items predominate. Problems, medications and lab results represent some of the most important data elements in medicine, but their overall distribution has not been reported.Objective: Our objective is to determine whether problems, medications and lab results demonstrate a power law distribution.Methods: Retrospective review of electronic medical record data for 100,000 randomly selected patients seen at least twice in 2006 and 2007 at the Brigham and Women’s Hospital in Boston and its affiliated medical practices.Results: All three data types exhibited a power law distribution. The 12.5% most frequently used problems account for 80% of all patient problems, the top 11.8% of medications account for 80% of all medication orders and the top 4.5% of lab result types account for all lab results.Conclusion: These three data elements exhibited power law distributions with a small number of common items representing a substantial proportion of all orders and observations, which has implications for electronic health record design.


Author(s):  
Anna E. Schorer ◽  
Richard Moldwin ◽  
Jacob Koskimaki ◽  
Elmer V. Bernstam ◽  
Neeta K. Venepalli ◽  
...  

PURPOSE The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) requires eligible clinicians to report clinical quality measures (CQMs) in the Merit-Based Incentive Payment System (MIPS) to maximize reimbursement. To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS CQMs, EHR data aggregated by ASCO's CancerLinQ platform were analyzed. MATERIALS AND METHODS Using the CancerLinQ health technology platform, 19 Oncology MIPS (oMIPS) CQMs were evaluated to determine the presence of data elements (DEs) necessary to satisfy each CQM and the DE percent population with patient data (fill rates). At the time of this analysis, the CancerLinQ network comprised 63 active practices, representing eight different EHR vendors and containing records for more than 1.63 million unique patients with one or more malignant neoplasms (1.73 million cancer cases). RESULTS Fill rates for the 63 oMIPS-associated DEs varied widely among the practices. The average site had at least one filled DE for 52% of the DEs. Only 35% of the DEs were populated for at least one patient record in 95% of the practices. However, the average DE fill rate of all practices was 23%. No data were found at any practice for 22% of the DEs. Since any oMIPS CQM with an unpopulated DE component resulted in an inability to compute the measure, only two (10.5%) of the 19 oMIPS CQMs were computable for more than 1% of the patients. CONCLUSION Although EHR systems had relatively high DE fill rates for some DEs, underfilling and inconsistency of DEs in EHRs render automated oncology MIPS CQM calculations impractical.


Trials ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 18 ◽  
Author(s):  
Justin Doods ◽  
Florence Botteri ◽  
Martin Dugas ◽  
Fleur Fritz ◽  

2016 ◽  
Vol 51 (6) ◽  
pp. 1030-1033
Author(s):  
Jason C. Fisher ◽  
David H. Godfried ◽  
Jennifer Lighter-Fisher ◽  
Joseph Pratko ◽  
Mary Ellen Sheldon ◽  
...  

2018 ◽  
Vol 37 (4) ◽  
pp. 635-643 ◽  
Author(s):  
Deborah J. Cohen ◽  
David A. Dorr ◽  
Kyle Knierim ◽  
C. Annette DuBard ◽  
Jennifer R. Hemler ◽  
...  

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Michael Klompas ◽  
Chaim Kirby ◽  
Jason McVetta ◽  
Paul Oppedisano ◽  
John Brownstein ◽  
...  

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