Usability of a Digital Registry to Promote Secondary Prevention for Peripheral Artery Disease Patients.

OBJECTIVE: To evaluate usability of a quality improvement tool that promotes guideline-based care for patients with peripheral arterial disease (PAD). PATIENTS AND METHODS: The study was conducted from July 19, 2018, to August 21, 2019. We compared the usability of a PAD cohort knowledge solution (CKS) with standard management supported by an electronic health record (EHR). Two scenarios were developed for usability evaluation; the first for the PAD-CKS while the second evaluated standard EHR workflow. Providers were asked to provide opinions about the PAD-CKS tool and to generate a System Usability Scale (SUS) score. Metrics analyzed included time required, number of mouse clicks, and number of keystrokes. RESULTS: Usability evaluations were completed by 11 providers. SUS for the PAD-CKS was excellent at 89.6. Time required to complete 21 tasks in the CKS was 4 minutes compared with 12 minutes for standard EHR workflow (median, P = .002). Completion of CKS tasks required 34 clicks compared with 148 clicks for the EHR (median, P = .002). Keystrokes for CKS task completion was 8 compared with 72 for EHR (median, P = .004). Providers indicated that overall they found the tool easy to use and the PAD mortality risk score useful. CONCLUSIONS: Usability evaluation of the PAD-CKS tool demonstrated time savings, a high SUS score, and a reduction of mouse clicks and keystrokes for task completion compared to standard workflow using the EHR. Provider feedback regarding the strengths and weaknesses also created opportunities for iterative improvement of the PAD-CKS tool.

Evaluation of the effect of decision support on the efficiency of primary care providers in the outpatient practice.

BACKGROUND: Clinical decision support (CDS) for primary care has been shown to improve delivery of preventive services. However, there is little evidence for efficiency of physicians due to CDS assistance. In this article, we report a pilot study for measuring the impact of CDS on the time spent by physicians for deciding on preventive services and chronic disease management. METHODS: We randomly selected 30 patients from a primary care practice, and assigned them to 10 physicians. The physicians were requested to perform chart review to decide on preventive services and chronic disease management for the assigned patients. The patients assignment was done in a randomized crossover design, such that each patient received 2 sets of recommendations-one from a physician with CDS assistance and the other from a different physician without CDS assistance. We compared the physician recommendations made using CDS assistance, with the recommendations made without CDS assistance. RESULTS: The physicians required an average of 1 minute 44 seconds, when they were they had access to the decision support system and 5 minutes when they were unassisted. Hence the CDS assistance resulted in an estimated saving of 3 minutes 16 seconds (65%) of the physicians' time, which was statistically significant (P < .0001). There was no statistically significant difference in the number of recommendations. CONCLUSION: Our findings suggest that CDS assistance significantly reduced the time spent by physicians for deciding on preventive services and chronic disease management. The result needs to be confirmed by performing similar studies at other institutions.

Automated recommendation for cervical cancer screening and surveillance.

Because of the complexity of cervical cancer prevention guidelines, clinicians often fail to follow best-practice recommendations. Moreover, existing clinical decision support (CDS) systems generally recommend a cervical cytology every three years for all female patients, which is inappropriate for patients with abnormal findings that require surveillance at shorter intervals. To address this problem, we developed a decision tree-based CDS system that integrates national guidelines to provide comprehensive guidance to clinicians. Validation was performed in several iterations by comparing recommendations generated by the system with those of clinicians for 333 patients. The CDS system extracted relevant patient information from the electronic health record and applied the guideline model with an overall accuracy of 87%. Providers without CDS assistance needed an average of 1 minute 39 seconds to decide on recommendations for management of abnormal findings. Overall, our work demonstrates the feasibility and potential utility of automated recommendation system for cervical cancer screening and surveillance.

Clinical decision support with automated text processing for cervical cancer screening.

OBJECTIVE: To develop a computerized clinical decision support system (CDSS) for cervical cancer screening that can interpret free-text Papanicolaou (Pap) reports. MATERIALS AND METHODS: The CDSS was constituted by two rulebases: the free-text rulebase for interpreting Pap reports and a guideline rulebase. The free-text rulebase was developed by analyzing a corpus of 49 293 Pap reports. The guideline rulebase was constructed using national cervical cancer screening guidelines. The CDSS accesses the electronic medical record (EMR) system to generate patient-specific recommendations. For evaluation, the screening recommendations made by the CDSS for 74 patients were reviewed by a physician. RESULTS AND DISCUSSION: Evaluation revealed that the CDSS outputs the optimal screening recommendations for 73 out of 74 test patients and it identified two cases for gynecology referral that were missed by the physician. The CDSS aided the physician to amend recommendations in six cases. The failure case was because human papillomavirus (HPV) testing was sometimes performed separately from the Pap test and these results were reported by a laboratory system that was not queried by the CDSS. Subsequently, the CDSS was upgraded to look up the HPV results missed earlier and it generated the optimal recommendations for all 74 test cases. LIMITATIONS: Single institution and single expert study. CONCLUSION: An accurate CDSS system could be constructed for cervical cancer screening given the standardized reporting of Pap tests and the availability of explicit guidelines. Overall, the study demonstrates that free text in the EMR can be effectively utilized through natural language processing to develop clinical decision support tools.