Michelle R. Hribar

Developing an easy-to-use tablet computer application for assessing patient-reported outcomes in patients with cancer.

BackgroundIn order to be practically useful, computer applications for patients with cancer must be easily usable by people with limited computer literacy and impaired vision or dexterity. We describe the usability development process for an application that collects quality of life and symptom information from patients with cancer.MethodsUsability testing consisted of user testing with cancer patients to identify initial design problems and a survey to compare the computer applications ease of use between elderly and younger patients.ResultsIn user-testing phase, seven men aged 56 to 77 with prostate cancer were observed using the application and interviewed afterwards identifying several usability concerns. Sixty patients with breast, gastrointestinal, or prostate cancer participated in the ease of use survey, with 40% (n = 24) aged 65 or older. Younger patients reported significantly higher scores than elderly patients (14.0 vs. 10.8, p = .001), even when prior computer and touch screen use was controlled.ConclusionElderly users reported lower ease of use scores than younger users; however, their average rating was quite high—10.8 on a scale of −16 to +16. It may be unrealistic to expect elderly or less computer literate users to rate any application as positively as younger, more computer savvy users—perhaps it is enough that they rate the application positively and can use it without undue difficulties. We hope that our process can serve as a model for how to bridge the fields of computer usability and healthcare.

Secondary use of electronic health record data for clinical workflow analysis

Objective Outpatient clinics lack guidance for tackling modern efficiency and productivity demands. Workflow studies require large amounts of timing data that are prohibitively expensive to collect through observation or tracking devices. Electronic health records (EHRs) contain a vast amount of timing data - timestamps collected during regular use - that can be mapped to workflow steps. This study validates using EHR timestamp data to predict outpatient ophthalmology clinic workflow timings at Oregon Health and Science University and demonstrates their usefulness in 3 different studies. Materials and Methods Four outpatient ophthalmology clinics were observed to determine their workflows and to time each workflow step. EHR timestamps were mapped to the workflow steps and validated against the observed timings. Results The EHR timestamp analysis produced times that were within 3 min of the observed times for >80% of the appointments. EHR use patterns affected the accuracy of using EHR timestamps to predict workflow times. Discussion EHR timestamps provided a reasonable approximation of workflow and can be used for workflow studies. They can be used to create simulation models, analyze EHR use, and quantify the impact of trainees on workflow. Conclusion The secondary use of EHR timestamp data is a valuable resource for clinical workflow studies. Sample timestamp data files and algorithms for processing them are provided and can be used as a template for more studies in other clinical specialties and settings.

Time requirements for electronic health record use in an academic ophthalmology center

Importance Electronic health record (EHR) systems have transformed the practice of medicine. However, physicians have raised concerns that EHR time requirements have negatively affected their productivity. Meanwhile, evolving approaches toward physician reimbursement will require additional documentation to measure quality and cost of care. To date, little quantitative analysis has rigorously studied these topics. Objective To examine ophthalmologist time requirements for EHR use. Design, Setting, and Participants A single-center cohort study was conducted between September 1, 2013, and December 31, 2016, among 27 stable departmental ophthalmologists (defined as attending ophthalmologists who worked at the study institution for ≥6 months before and after the study period). Ophthalmologists who did not have a standard clinical practice or who did not use the EHR were excluded. Exposures Time stamps from the medical record and EHR audit log were analyzed to measure the length of time required by ophthalmologists for EHR use. Ophthalmologists underwent manual time-motion observation to measure the length of time spent directly with patients on the following 3 activities: EHR use, conversation, and examination. Main Outcomes and Measures The study outcomes were time spent by ophthalmologists directly with patients on EHR use, conversation, and examination as well as total time required by ophthalmologists for EHR use. Results Among the 27 ophthalmologists in this study (10 women and 17 men; mean [SD] age, 47.3 [10.7] years [median, 44; range, 34-73 years]) the mean (SD) total ophthalmologist examination time was 11.2 (6.3) minutes per patient, of which 3.0 (1.8) minutes (27% of the examination time) were spent on EHR use, 4.7 (4.2) minutes (42%) on conversation, and 3.5 (2.3) minutes (31%) on examination. Mean (SD) total ophthalmologist time spent using the EHR was 10.8 (5.0) minutes per encounter (range, 5.8-28.6 minutes). The typical ophthalmologist spent 3.7 hours using the EHR for a full day of clinic: 2.1 hours during examinations and 1.6 hours outside the clinic session. Linear mixed effects models showed a positive association between EHR use and billing level and a negative association between EHR use per encounter and clinic volume. Each additional encounter per clinic was associated with a decrease of 1.7 minutes (95% CI, -4.3 to 1.0) of EHR use time per encounter for ophthalmologists with high mean billing levels (adjusted R2 = 0.42; P = .01). Conclusions and Relevance Ophthalmologists have limited time with patients during office visits, and EHR use requires a substantial portion of that time. There is variability in EHR use patterns among ophthalmologists.

Association of the Presence of Trainees With Outpatient Appointment Times in an Ophthalmology Clinic

Importance Physicians face pressure to improve clinical efficiency, particularly with electronic health record (EHR) adoption and gradual shifts toward value-based reimbursement models. These pressures are especially pronounced in academic medical centers, where delivery of care must be balanced with medical education. However, the association of the presence of trainees with clinical efficiency in outpatient ophthalmology clinics is not known. Objective To quantify the association of the presence of trainees (residents and fellows) and efficiency in an outpatient ophthalmology clinic. Design, Setting, and Participants This single-center cohort study was conducted from January 1 through December 31, 2014, at an academic department of ophthalmology. Participants included 49 448 patient appointments with 33 attending physicians and 40 trainees. Exposures Presence vs absence of trainees in an appointment or clinic session, as determined by review of the EHR audit log. Main Outcomes and Measures Patient appointment time, as determined by time stamps in the EHR clinical data warehouse. Linear mixed models were developed to analyze variability among clinicians and patients. Results Among the 33 study physicians (13 women [39%] and 20 men [61%]; median age, 44 years [interquartile range, 39-53 years]), appointments with trainees were significantly longer than appointments in clinic sessions without trainees (mean [SD], 105.0 [55.7] vs 80.3 [45.4] minutes; P < .001). The presence of a trainee in a clinic session was associated with longer mean appointment time, even in appointments for which the trainee was not present (mean [SD], 87.2 [49.2] vs 80.3 [45.4] minutes; P < .001). Among 33 study physicians, 3 (9%) had shorter mean appointment times when a trainee was present, 1 (3%) had no change, and 29 (88%) had longer mean appointment times when a trainee was present. Linear mixed models showed the presence of a resident was associated with a lengthening of appointment time of 17.0 minutes (95% CI, 15.6-18.5 minutes; P < .001), and the presence of a fellow was associated with a lengthening of appointment time of 13.5 minutes (95% CI, 12.3-14.8 minutes; P < .001). Conclusions and Relevance Presence of trainees was associated with longer appointment times, even for patients not seen by a trainee. Although numerous limitations to this study design might affect the interpretation of the findings, these results highlight a potential challenge of maintaining clinical efficiency in academic medical centers and raise questions about physician reimbursement models.