Funding Source
National Library of Medicine (NLM), R01LM012815

Project Period: 9/7/2017 - 8/31/2021

Dartmouth College Project Staff: William Haslett, PhD; Michelle Dannenberg, MPH; Craig Ganoe, MS; Jesse Schoonmaker, MD, MPH; Wambui Moraa Onsando, MD, MPH; Kyra Bonasia, PhD; James Finora; Lisa Oh; Martha Bruce, PhD; Glyn Elwyn, MBBCh, PhD; James O’Malley, PhD; Amar Das, MD, PhD

Patient Partners: Sheri Piper; Roger Arend

Project Summary
Patients are beginning to audio record visits and clinics are now offering this service. When patients receive a clinic recording, 71% listen and 68% share it with a caregiver, resulting in improved understanding and self-­management. Nonetheless, unstructured recordings are difficult to navigate. Personal health libraries (PHLs) may help patients organize health information, yet current PHLs do not facilitate clinic ­recordings. The objective of this project is to further develop our existing ORALS recording platform and create a PHL, HealthPAL, that integrates clinic audio-­recordings, using data science methods to link medical terms from the recording to trustworthy patient resources, which can then be retrieved, organized, edited and shared by patients. The specific aims are: Aim 1 Identify health information seeking needs and strategies of older adults with multimorbidity and their caregivers; Aim 2 Develop an Audio-­PHL using data science methods to securely analyze clinic visit recordings and make this information accessible and understandable for patients; and Aim 3 Demonstrate the usability and use of an Audio-­PHL in older adults with multimorbidity and caregivers. We hypothesize: (1) The Audio-­PHL will surpass acceptable usability metrics in older adults and caregivers and (2) natural language processing (NLP) methods developed for the Audio-­PHL will accurately identify key visit information (e.g. medication) and connect it to credible patient resources. The development of the Audio-­PHL follows a user-centered design model. In Aim 1, we will use participatory design activities with 48 end-­users to inform Audio-­PHL design. In Aim 2, the Audio-­PHL will be created in iterative cycles informed by findings from Aim 1. In Aim 3, extensive usability evaluation will be conducted in human-computer interaction (HCI) laboratory settings to ensure Audio-­PHL surpasses acceptable usability metrics.

Field testing of the Audio-­PHL will follow via a three-arm, patient-­randomized pilot trial with older adults (n=45) with multimorbidity from primary care. Participants in the intervention arms will receive access to an audio-based PHL with either 1) a clinic visit recording where key information is annotated and hyperlinks to trustworthy health information are provided (HealthPAL), 2) a clinic visit recording without annotations or hyperlinks, or 3) the third group of participants will receive usual care (control) with no recordings. Usability metrics and satisfaction will be assessed at one-­month. Preliminary data on the impact of an Audio-­PHL on patient ability to seek, find and use health information with high confidence, patient activation, and caregiver confidence will also be gathered. The research is innovative because it will provide patients and caregivers secure access to a PHL based on clinic-­recordings that uses data science methods to organize visit information and connect it to trusted resources. The results are expected to have a major positive impact because they will provide proof-­of-­principle for the use of an Audio-­PHL that utilizes the benefits of clinic recordings through the novel application of data science methods, to improve health outcomes for older adults with multimorbidity through greater knowledge and confidence in their ability to self-­manage.