TY - JOUR
T1 - Improving the Accuracy of a Clinical Decision Support System for Cervical Cancer Screening and Surveillance
AU - Ravikumar, K. E.
AU - MacLaughlin, Kathy L.
AU - Scheitel, Marianne R.
AU - Kessler, Maya
AU - Wagholikar, Kavishwar B.
AU - Liu, Hongfang
AU - Chaudhry, Rajeev
N1 - Publisher Copyright:
© 2018 Georg Thieme Verlag. All rights reserved.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Background Clinical decision support systems (CDSS) for cervical cancer prevention are generally limited to identifying patients who are overdue for their next routine/next screening, and they do not provide recommendations for follow-up of abnormal results. We previously developed a CDSS to automatically provide follow-up recommendations based on the American Society of Colposcopy and Cervical Pathology (ASCCP) guidelines for women with both previously normal and abnormal test results leveraging information available in the electronic medical record (EMR). Objective Enhance the CDSS by improving its accuracy and incorporating changes to reflect the latest revision of the guidelines. Methods After making enhancements to the CDSS, we evaluated the performance of the clinical recommendations on 393 patients selected through stratified sampling from a set of 3,704 patients in a nonclinical setting. We performed chart review of individual patient's record to evaluate the performance of the system. An expert clinician assisted by a resident manually reviewed the recommendation made by the system and verified whether the recommendations were as per the ASCCP guidelines. Results The recommendation accuracy of the enhanced CDSS improved to 93%, which is a substantial improvement over the 84% reported previously. A detailed analysis of errors is presented in this article. We fixed the errors identified in this evaluation that were amenable to correction to further improve the accuracy of the system. The source code of the updated CDSS is available at https://github.com/ohnlp/MayoNlpPapCdss. Conclusion We made substantial enhancements to our earlier prototype CDSS with the updated ASCCP guidelines and performed a thorough evaluation in a nonclinical setting to improve the accuracy of the CDSS. The CDSS will be further refined as it is utilized in the practice.
AB - Background Clinical decision support systems (CDSS) for cervical cancer prevention are generally limited to identifying patients who are overdue for their next routine/next screening, and they do not provide recommendations for follow-up of abnormal results. We previously developed a CDSS to automatically provide follow-up recommendations based on the American Society of Colposcopy and Cervical Pathology (ASCCP) guidelines for women with both previously normal and abnormal test results leveraging information available in the electronic medical record (EMR). Objective Enhance the CDSS by improving its accuracy and incorporating changes to reflect the latest revision of the guidelines. Methods After making enhancements to the CDSS, we evaluated the performance of the clinical recommendations on 393 patients selected through stratified sampling from a set of 3,704 patients in a nonclinical setting. We performed chart review of individual patient's record to evaluate the performance of the system. An expert clinician assisted by a resident manually reviewed the recommendation made by the system and verified whether the recommendations were as per the ASCCP guidelines. Results The recommendation accuracy of the enhanced CDSS improved to 93%, which is a substantial improvement over the 84% reported previously. A detailed analysis of errors is presented in this article. We fixed the errors identified in this evaluation that were amenable to correction to further improve the accuracy of the system. The source code of the updated CDSS is available at https://github.com/ohnlp/MayoNlpPapCdss. Conclusion We made substantial enhancements to our earlier prototype CDSS with the updated ASCCP guidelines and performed a thorough evaluation in a nonclinical setting to improve the accuracy of the CDSS. The CDSS will be further refined as it is utilized in the practice.
KW - ambulatory care information systems
KW - clinical decision support system
KW - electronic health records
KW - knowledge delivery
KW - knowledge management
KW - testing and evaluation of health information technology
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U2 - 10.1055/s-0037-1617451
DO - 10.1055/s-0037-1617451
M3 - Article
C2 - 29365341
AN - SCOPUS:85052615022
SN - 1869-0327
VL - 9
SP - 62
EP - 71
JO - Applied clinical informatics
JF - Applied clinical informatics
IS - 1
ER -