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PM&R and HERL Teams Discuss a Roadmap to Reduce Information Inequities in Disability via Digital Health and NLP

December 7, 2022

In November 2022, experts from the University of Pittsburgh Department of Physical Medicine and Rehabilitation and the Human Engineering Research Laboratories (team recognized below) published, “A roadmap to reduce information inequities in disability with digital health and natural language processing” in PLOS Digital Health

People with disabilities disproportionately experience negative health outcomes. Purposeful analysis of information on all aspects of the experience of disability across individuals and populations can guide interventions to reduce health inequities in care and outcomes. Such an analysis requires more holistic information on individual function, precursors and predictors, and environmental and personal factors than is systematically collected in current practice.

In this study, the team identifies three key information barriers to more equitable information:

  1. A lack of information on contextual factors that affect a person’s experience of function.
  2. Underemphasis of the patient’s voice, perspective, and goals in the electronic health record.
  3. A lack of standardized locations in the electronic health record to record observations of function and context.

Through analysis of rehabilitation data, they have identified ways to mitigate these barriers through the development of digital health technologies to better capture and analyze information about the experience of function. The team proposes three directions for future research on using digital health technologies, particularly natural language processing (NLP), to facilitate capturing a more holistic picture of a patient’s unique experience:

  1. Analyzing existing information on function in free text documentation.
  2. Developing new NLP-driven methods to collect information on contextual factors.
  3. Collecting and analyzing patient-reported descriptions of personal perceptions and goals.

Multidisciplinary collaboration between rehabilitation experts and data scientists to advance these research directions will yield practical technologies to help reduce inequities and improve care for all populations.

Research Team

Denis R. Newman-Griffis, PhD

Brad E. Dicianno, MD

Amy J. Houtrow, MD, PhD, MPH

Max B. Hurwitz, DO

Gina P. McKernan, PhD