Health Outcomes and Biomedical Informatics 2022

Integrating Patient Reported Outcomes for Patient-Centered Pain Care

Faculty Mentor’s Name: Dr. Christopher Harle
Email: charle@ufl.edu
Phone Number: (352) 294-5797
Project Category: Clinical
International Component or Travel: No

Research Project Description:

The U.S. faces dual public health crises of widespread chronic pain and opioid overdoses. Over 75,000 people die annually from opioid overdoses. Most patients with chronic pain first turn to primary care clinicians, who must decide among myriad treatment options based on relative risks and benefits, medical history, and patient goals. Unfortunately, primary care clinicians lack usable tools to help them partner with their patients in choosing pain treatment options that best meet their patients’ complex needs. Thus, primary care clinicians and patients would benefit from patient-centered clinical decision support (CDS) built into their Electronic Health Record (EHR). Such CDS systems can help organize and deliver the most relevant and useful information to busy clinicians, so that they can focus on collaboratively choosing the best treatment options with their patients.

The objective of this project is to study the implementation of an existing CDS tool for pain shared treatment decision making into UF Health primary care practices EHRs. Our specific aims are to: (1) Adapt the CDS tool (called Pain Manager), for implementation in eight UF Health primary care clinics (2): Evaluate the effect of tailored implementation support on Pain Manager’s use in shared decision making; and (3) Establish the feasibility and obtain preliminary data in preparation for a multi-site pragmatic trial targeting the effectiveness of Pain Manager and tailored implementation support on shared decision making and patient-reported pain and physical function.

Medical students’ involvement with the project will be geared towards their interests. Potential opportunities included assisting with interviews and training activities targeted toward both patients and primary care clinicians, contributing to qualitative and quantitative analysis of study results, and disseminating study findings at scientific meetings and in peer-reviewed publications. The student will be co-mentored by Dr. Christopher Harle and Dr. Ramzi Salloum.

Funding: Agency for Healthcare Research and Quality

Publications:
Militello LG, Hurley RW, Cook RL, Danielson EC, DiIulio J, Downs SM, Anders S, Harle CA. Primary care clinicians’ beliefs and strategies for managing chronic pain in an era of a national opioid epidemic. Journal of General Internal Medicine. 2020 35(12): 3442-3548.

Harle CA, Diiulio J, Downs SM, Danielson EC, Anders S, Cook RL, Hurley RW, Mamlin BW, Militello LG. Decision-Centered Design of Patient Information Visualizations to Support Chronic Pain Care. Applied Clinical Informatics. 2019 10(4): 719-7

Computable social factor phenotyping using EHR and HIE data

Faculty Mentor’s Name: Dr. Chris Harle
Email: charle@ufl.edu
Phone Number: (352) 294-5797
Project Category: Clinical
International Component or Travel: No

Research Project Description:

Social risk factors, such as transportation needs, housing needs, and food insecurity, increase healthcare utilization and negatively affect health outcomes. Especially as health systems become more financially responsible for outcomes, they can benefit from processes that identify patients’ social risk factors and connect patients to appropriate services. Today, most health systems attempt to measure patients’ social risk factors, but such data collection is typically fraught with operational and conceptual difficulties. Some health systems implement screening questionnaires in their electronic health records (EHRs). However, data collection represents an additional burden on healthcare providers and patients in the clinic, and patients may decline to answer sensitive questions. Both of these factors contribute to uncertainty surrounding the reliability and validity of these questionnaires.

Our specific aims are to: 1) Assess the validity and reliability of questionnaires, clinical notes, and structured EHR data for identifying social risk factors in individual patients compared to a validated reference measurement of social risk factors, and 2) Assess the ability of these separate methods for measuring social risk factors in predicting health outcomes, and 3) Compare potential bias across patient gender, race, ethnicity, and age in using questionnaires, clinical notes, and structured EHR data to assess social risk factors. We expect this project will lead to more valid and implementable approaches to patient social factor measurement. The proposed research is significant because it directly addresses the challenges organizations face in addressing patients’ social risks and will provide key inputs to support organizations efforts at achieving a learning health system.

Medical students’ involvement with the project can be geared towards their interests. Potential opportunities included assisting with primary data collection at CHFM UF Health primary care clinics, conducting annotation on clinic notes to identify the inclusion of social factors, contributing to qualitative analysis of study results, and disseminating study findings at scientific meetings and in peer-reviewed publications.