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Appl Clin Inform 2017; 08(01): 279-290
DOI: 10.4338/ACI-2016-10-RA-0176
Research Article
Schattauer GmbH

Application of Electronic Algorithms to Improve Diagnostic Evaluation for Bladder Cancer[*]

Daniel R. Murphy
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
,
Ashley N.D. Meyer
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
,
Viralkumar Vaghani
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
,
Elise Russo
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
,
Dean F. Sittig
3   University of Texas Health Science Center at Houston’s School of Biomedical Informatics and the UT-Memorial Hermann Center for Healthcare Quality & Safety, Houston, Texas, USA
,
Kyle A. Richards
4   Department of Urology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
,
Li Wei
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
,
Louis Wu
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
,
Hardeep Singh
1   Houston VA Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
2   Baylor College of Medicine, Department of Medicine, Houston, Texas, USA
› Institutsangaben Funding This project is funded by a Veteran Affairs Health Services Research and Development CREATE grant (CRE-12-033) and partially funded by the Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety (CIN 13-413). Dr. Murphy is additionally funded by an Agency for Healthcare Research & Quality Mentored Career Development Award (K08-HS022901) and Dr. Singh is additionally supported by the VA Health Services Research and Development Service (CRE 12-033; Presidential Early Career Award for Scientists and Engineers USA 14-274), the VA National Center for Patient Safety and the Agency for Health Care Research and Quality (R01HS022087). These funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
Weitere Informationen

Publikationsverlauf

Received: 20. Oktober 2016

Accepted: 13. Januar 2017

Publikationsdatum:
20. Dezember 2017 (online)

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Summary

Background: Strategies to ensure timely diagnostic evaluation of hematuria are needed to reduce delays in bladder cancer diagnosis.

Objective: To evaluate the performance of electronic trigger algorithms to detect delays in hematuria follow-up.

Methods: We developed a computerized trigger to detect delayed follow-up action on a urinalysis result with high-grade hematuria (>50 red blood cells/high powered field). The trigger scanned clinical data within a Department of Veterans Affairs (VA) national data repository to identify all patient records with hematuria, then excluded those where follow-up was unnecessary (e.g., terminal illness) or where typical follow-up action was detected (e.g., cystoscopy). We manually reviewed a randomly-selected sample of flagged records to confirm delays. We performed a similar analysis of records with hematuria that were marked as not delayed (non-triggered). We used review findings to calculate trigger performance.

Results: Of 310,331 patients seen between 1/1/2012-12/31/2014, the trigger identified 5,857 patients who experienced high-grade hematuria, of which 495 experienced a delay. On manual review of 400 randomly-selected triggered records and 100 non-triggered records, the trigger achieved positive and negative predictive values of 58% and 97%, respectively.

Conclusions: Triggers offer a promising method to detect delays in care of patients with high-grade hematuria and warrant further evaluation in clinical practice as a means to reduce delays in bladder cancer diagnosis.

Keywords

Electronic health records - medical informatics - urologic neoplasms - hematuria - delayed diagnosis - triggers - monitoring and surveillance - data mining

* The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.


 

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