The goal of this K99/R00 award is to apply methods from biomedical informatics, operations research, and computer science to develop, implement, and evaluate stimulation and optimization tools for improving clinical processes. This is an important topic because electronic health record (EHR) systems have potential to improve quality and cost of health care, yet providers have raised concerns that EHR implementation has negatively impacted real-world productivity and efficiency. Methods for improving workflow based on automated time-motion data collection will have significant real-world impact. This proposal involves two phases: (A) K99 training and mentored research phase, which will include training in advanced operations research and analytics techniques at Oregon Health & Science University (OHSU) and Portland State University. Under the mentorship of two experienced informaticians and clinicians, a statistician, and a systems engineer, this training will be applie to research in improving clinical workflows. The K99 phase of research will focus on studying ophthalmology outpatient clinic workflows and the first two Specific Aims of the overall project: (SA#1) Develop tools for automated time-motion workflow data collection tools based on EHR timestamps and indoor positioning systems and (SA#2) Create simulation models to improve the efficiency of clinical workflow and validate these models by testing them in ophthalmology outpatient clinics. Ophthalmology will be an ideal clinical domain for performing these initial workflow studies because it is a fast-paced ambulatory specialty that includes medical and surgical patients, imaging tests, multiple examination stages (e.g., before & after eye dilation), and multiple ancillary staff members (e.g., technicians, photographers). (B) R00 research phase and transition to independence. The R00 phase of research will focus on the third Specific Aim of the overall project: (SA#3) Develop, implement, and evaluate data collection, simulation, and modeling techniques to broader inpatient and outpatient medical domains. This will generalize methods from the mentored project phase by collecting EHR data (e.g., surgery type, length of inpatient stay, demographics) to create probability density functions representing patient demand for resources. These data will be used to develop simulation models for different scheduling strategies based on patient classifications, and to evaluate them in the clinical setting. This project will benefit from a PI who has a strong background in mathematics and computer science, from an outstanding collaborative team of mentors with complementary experience across all areas of the proposed project, and from an outstanding academic informatics environment at OHSU.
Electronic health record (EHR) systems are rapidly transforming the process of health care delivery, including the secondary use of massive amounts of data collected during their use. This study will focus on using this data to improve clinical processes. The study will analyze clinical workflow in high-volume outpatient ophthalmology clinics using secondary EHR data and positioning data, create simulation models to optimize efficiency based on these data, and apply these methods to medical domains outside of ophthalmology. The study will provide generalizable tools for improving clinic processes that may impact all practicing physicians in the future.
| Hribar, Michelle R; Huang, Abigail E; Goldstein, Isaac H et al. (2018) Data-Driven Scheduling for Improving Patient Efficiency in Ophthalmology Clinics. Ophthalmology : |
| Hribar, Michelle R; Chiang, Michael F (2018) Response to Letter: Secondary use of electronic health record data for clinical workflow analysis. J Am Med Inform Assoc 25:920 |
| Hribar, Michelle R; Read-Brown, Sarah; Goldstein, Isaac H et al. (2018) Secondary use of electronic health record data for clinical workflow analysis. J Am Med Inform Assoc 25:40-46 |
| Goldstein, Isaac H; Hribar, Michelle R; Read-Brown, Sarah et al. (2018) Association of the Presence of Trainees With Outpatient Appointment Times in an Ophthalmology Clinic. JAMA Ophthalmol 136:20-26 |
| Goldstein, Isaac H; Hribar, Michelle R; Sarah, Read-Brown et al. (2017) Quantifying the Impact of Trainee Providers on Outpatient Clinic Workflow using Secondary EHR Data. AMIA Annu Symp Proc 2017:760-769 |
| Read-Brown, Sarah; Hribar, Michelle R; Reznick, Leah G et al. (2017) Time Requirements for Electronic Health Record Use in an Academic Ophthalmology Center. JAMA Ophthalmol 135:1250-1257 |
| Hribar, Michelle R; Read-Brown, Sarah; Reznick, Leah et al. (2017) Evaluating and Improving an Outpatient Clinic Scheduling Template Using Secondary Electronic Health Record Data. AMIA Annu Symp Proc 2017:921-929 |
