An Audio Personal Health Library of Clinic Visit Recordings for Patients and Their Caregivers (HealthPAL): User-Centered Design Approach.

BACKGROUND: Providing digital recordings of clinic visits to patients has emerged as a strategy to promote patient and family engagement in care. With advances in natural language processing, an opportunity exists to maximize the value of visit recordings for patients by automatically tagging key visit information (eg, medications, tests, and imaging) and linkages to trustworthy web-based resources curated in an audio-based personal health library. OBJECTIVE: This study aims to report on the user-centered development of HealthPAL, an audio personal health library. METHODS: Our user-centered design and usability evaluation approach incorporated iterative rounds of video-recorded sessions from 2016 to 2019. We recruited participants from a range of community settings to represent older patient and caregiver perspectives. In the first round, we used paper prototypes and focused on feature envisionment. We moved to low-fidelity and high-fidelity versions of the HealthPAL in later rounds, which focused on functionality and use; all sessions included a debriefing interview. Participants listened to a deidentified, standardized primary care visit recording before completing a series of tasks (eg, finding where a medication was discussed in the recording). In the final round, we recorded the patients' primary care clinic visits for use in the session. Findings from each round informed the agile software development process. Task completion and critical incidents were recorded in each round, and the System Usability Scale was completed by participants using the digital prototype in later rounds. RESULTS: We completed 5 rounds of usability sessions with 40 participants, of whom 25 (63%) were women with a median age of 68 years (range 23-89). Feedback from sessions resulted in color-coding and highlighting of information tags, a more prominent play button, clearer structure to move between one's own recordings and others' recordings, the ability to filter recording content by the topic discussed and descriptions, 10-second forward and rewind controls, and a help link and search bar. Perceived usability increased over the rounds, with a median System Usability Scale of 78.2 (range 20-100) in the final round. Participants were overwhelmingly positive about the concept of accessing a curated audio recording of a clinic visit. Some participants reported concerns about privacy and the computer-based skills necessary to access recordings. CONCLUSIONS: To our knowledge, HealthPAL is the first patient-centered app designed to allow patients and their caregivers to access easy-to-navigate recordings of clinic visits, with key concepts tagged and hyperlinks to further information provided. The HealthPAL user interface has been rigorously co-designed with older adult patients and their caregivers and is now ready for further field testing. The successful development and use of HealthPAL may help improve the ability of patients to manage their own care, especially older adult patients who have to navigate complex treatment plans.

Integrated vs nonintegrated treatment for perinatal opioid use disorder: retrospective cohort study.

BACKGROUND: Pregnant women with opioid use disorder and their infants often experience worse perinatal outcomes than women without opioid use disorder, including longer hospitalizations after delivery and a higher risk for preterm delivery. Integrated treatment models, which combine addiction treatment and maternity care, represent an innovative approach that is widely endorsed, however, limited studies have compared the outcomes between integrated and standard, nonintegrated programs from real-world programs. OBJECTIVE: This study aimed to evaluate the perinatal and substance use outcomes for pregnant women with opioid use disorder receiving coordinated, colocated obstetrical care and opioid use disorder treatment (integrated treatment) and to compare it with those of women receiving obstetrical care and opioid use disorder treatment in distinct programs of care (nonintegrated treatment). STUDY DESIGN: In this observational, retrospective cohort study, we abstracted the perinatal and opioid use disorder treatment data from the records of pregnant women with opioid use disorder (n=225) who delivered at a rural, academic medical center from 2015 to 2017. The women either received integrated (n=92) or nonintegrated (n=133) opioid use disorder treatment and obstetrical care. Using inverse probability weighted regression models to adjust for a potential covariate imbalance, we evaluated the impact of the treatment model on the risk for preterm delivery and positive meconium or umbilical cord toxicology screens. We explored whether the number of obstetrical visits mediated this relationship by using a quasi-Bayesian Monte Carlo algorithm. RESULTS: Women receiving integrated treatment were less likely to deliver prematurely (11.8% vs 26.6%; P<.001) and their infants had shorter hospitalizations (6.5±4.8 vs 10.7±16.2 days). Using a robust inverse probability weighted model showed that receiving integrated treatment was associated with a 74.7% decrease in the predicted probability of preterm delivery (average treatment effect, -0.19; standard error, 0.14; P<.001). There were no differences in the risk for a positive meconium or umbilical cord toxicology screen, a marker for second and third trimester substance use, between women receiving integrated treatment and those receiving coordinated treatment (29.4% vs 34.6%; P=.41), however, integrated treatment was associated with significantly lower rates of positive maternal urine toxicology screens at the time of delivery (35.9% vs 74.4%; P<.001). CONCLUSION: Among a cohort of rural pregnant women with opioid use disorder, receiving integrated obstetrical care and opioid use disorder treatment was associated with a reduced risk for preterm birth, a lower risk for positive maternal urine toxicology screen at the time of delivery, and shorter infant hospitalization. This relationship was mediated by the number of obstetrical visits attended during pregnancy, suggesting that increased engagement with obstetrical care through integration of services may contribute to improved perinatal outcomes.

Natural language processing for automated annotation of medication mentions in primary care visit conversations.

OBJECTIVES: The objective of this study is to build and evaluate a natural language processing approach to identify medication mentions in primary care visit conversations between patients and physicians. MATERIALS AND METHODS: Eight clinicians contributed to a data set of 85 clinic visit transcripts, and 10 transcripts were randomly selected from this data set as a development set. Our approach utilizes Apache cTAKES and Unified Medical Language System controlled vocabulary to generate a list of medication candidates in the transcribed text and then performs multiple customized filters to exclude common false positives from this list while including some additional common mentions of the supplements and immunizations. RESULTS: Sixty-five transcripts with 1121 medication mentions were randomly selected as an evaluation set. Our proposed method achieved an F-score of 85.0% for identifying the medication mentions in the test set, significantly outperforming existing medication information extraction systems for medical records with F-scores ranging from 42.9% to 68.9% on the same test set. DISCUSSION: Our medication information extraction approach for primary care visit conversations showed promising results, extracting about 27% more medication mentions from our evaluation set while eliminating many false positives in comparison to existing baseline systems. We made our approach publicly available on the web as an open-source software. CONCLUSION: Integration of our annotation system with clinical recording applications has the potential to improve patients' understanding and recall of key information from their clinic visits, and, in turn, to positively impact health outcomes.