Understanding Gaps Between Daily Living and Clinical Settings in Chronic Disease Management: Qualitative Study

Assessing patient work system factors for medication management during transition of care among older adults: an observational study

OBJECTIVE

To develop and evaluate measures of patient work system factors in medication management that may be modifiable for improvement during the care transition from hospital to home among older adults.

DESIGN, SETTINGS AND PARTICIPANTS

Measures were developed and evaluated in a multisite prospective observational study of older adults (≥65 years) discharged home from medical units of two US hospitals from August 2018 to July 2019.

MAIN MEASURES

Patient work system factors for managing medications were assessed during hospital stays using six capacity indicators, four task indicators and three medication management practice indicators. Main outcomes were assessed at participants' homes approximately a week after discharge for (1) Medication discrepancies between the medications taken at home and those listed in the medical record, and (2) Patient experiences with new medication regimens.

RESULTS

274 of the 376 recruited participants completed home assessment (72.8%). Among capacity indicators, most older adults (80.6%) managed medications during transition without a caregiver, 41.2% expressed low self-efficacy in managing medications and 18.3% were not able to complete basic medication administration tasks. Among task indicators, more than half (57.7%) had more than 10 discharge medications and most (94.7%) had medication regimen changes. Having more than 10 discharge medications, more than two medication regimen changes and low self-efficacy in medication management increased the risk of feeling overwhelmed (OR 2.63, 95% CI 1.08 to 6.38, OR 3.16, 95% CI 1.29 to 7.74 and OR 2.56, 95% CI 1.25 to 5.26, respectively). Low transportation independence, not having a home caregiver, low medication administration skills and more than 10 discharge medications increased the risk of medication discrepancies (incidence rate ratio 1.39, 95% CI 1.01 to 1.91, incidence rate ratio 1.73, 95% CI 1.13 to 2.66, incidence rate ratio 1.99, 95% CI 1.37 to 2.89 and incidence rate ratio 1.91, 95% CI 1.24 to 2.93, respectively).

CONCLUSIONS

Patient work system factors could be assessed before discharge with indicators for increased risk of poor patient experience and medication discrepancies during older adults' care transition from hospital to home.

Assessing Mobility in Patients With Glioblastoma Using Digital Phenotyping-Piloting the Digital Assessment in Neuro-Oncology

BACKGROUND AND OBJECTIVES

Digital phenotyping (DP) enables objective measurements of patient behavior and may be a useful tool in assessments of quality-of-life and functional status in neuro-oncology patients. We aimed to identify trends in mobility among patients with glioblastoma (GBM) using DP.

METHODS

A total of 15 patients with GBM enrolled in a DP study were included. The Beiwe application was used to passively collect patient smartphone global positioning system data during the study period. We estimated step count, time spent at home, total distance traveled, and number of places visited in the preoperative, immediate postoperative, and late postoperative periods. Mobility trends for patients with GBM after surgery were calculated by using local regression and were compared with preoperative values and with values derived from a nonoperative spine disease group.

RESULTS

One month postoperatively, median values for time spent at home and number of locations visited by patients with GBM decreased by 1.48 h and 2.79 locations, respectively. Two months postoperatively, these values further decreased by 0.38 h and 1.17 locations, respectively. Compared with the nonoperative spine group, values for time spent at home and the number of locations visited by patients with GBM 1 month postoperatively were less than control values by 0.71 h and 2.79 locations, respectively. Two months postoperatively, time spent at home for patients with GBM was higher by 1.21 h and locations visited were less than nonoperative spine group values by 1.17. Immediate postoperative values for distance traveled, maximum distance from home, and radius of gyration for patients with GBM increased by 0.346 km, 2.24 km, and 1.814 km, respectively, compared with preoperative values.

CONCLUSIONS

:Trends in patients with GBM mobility throughout treatment were quantified through the use of DP in this study. DP has the potential to quantify patient behavior and recovery objectively and with minimal patient burden.

Consumer Health Informatics for Racial and Ethnic Minoritized Communities: Minor Progress, Major Opportunities

OBJECTIVE

By reducing barriers to accessing health services and by supporting health management, consumer health informatics has the potential to reduce health disparities. Yet, technologies are still being designed without considerations for racial and ethnic minoritized populations. This paper reviews consumer health informatics research within this population to assess for whom and how such technologies are being designed.

METHODS

We searched four databases from January 2020- December 2021 for literature focused on consumer health informatics and racial and ethnic minoritized populations. We extracted information about the study population, geographic location, stage of the design lifecycle, culturally tailored approaches, community engagement strategies, and considerations for the social determinants of health.

RESULTS

Twenty articles were included in the review. Most of the included literature were original research articles that tested health management interventions focused on one racial or ethnic minoritized population primarily within a confined geographic area within the United States. Seven studies described the extent to which an intervention was culturally tailored, including modifying the content, interface, functionality, and platform. Community engagement strategies varied, but few articles employed robust approaches. Lastly, seven studies detailed considerations for the social determinants of health, including providing hardware to access interventions and incorporating information about community-based resources within an intervention.

CONCLUSIONS

There has been moderate progress in consumer health informatics focused on racial and ethnic minoritized populations and many opportunities remain for these technologies to be used as an approach to address health disparities. Future research should utilize community engagement strategies to design interventions that are attune to multiple racial and ethnic minoritized populations across geographic regions in addition to numerous intersectional identities and multiple co-morbidities.

Opportunities and Challenges of Integrating Food Practice into Clinical Decision-Making

BACKGROUND

Food practice plays an important role in health. Food practice data collected in daily living settings can inform clinical decisions. However, integrating such data into clinical decision-making is burdensome for both clinicians and patients, resulting in poor adherence and limited utilization. Automation offers benefits in this regard, minimizing this burden resulting in a better fit with a patient's daily living routines, and creating opportunities for better integration into clinical workflow. Although the literature on patient-generated health data (PGHD) can serve as a starting point for the automation of food practice data, more diverse characteristics of food practice data provide additional challenges.

OBJECTIVES

We describe a series of steps for integrating food practices into clinical decision-making. These steps include the following: (1) sensing food practice; (2) capturing food practice data; (3) representing food practice; (4) reflecting the information to the patient; (5) incorporating data into the EHR; (6) presenting contextualized food practice information to clinicians; and (7) integrating food practice into clinical decision-making.

METHODS

We elaborate on automation opportunities and challenges in each step, providing a summary visualization of the flow of food practice-related data from daily living settings to clinical settings.

RESULTS

We propose four implications of automating food practice hereinafter. First, there are multiple ways of automating workflow related to food practice. Second, steps may occur in daily living and others in clinical settings. Food practice data and the necessary contextual information should be integrated into clinical decision-making to enable action. Third, as accuracy becomes important for food practice data, macrolevel data may have advantages over microlevel data in some situations. Fourth, relevant systems should be designed to eliminate disparities in leveraging food practice data.

CONCLUSION

Our work confirms previously developed recommendations in the context of PGHD work and provides additional specificity on how these recommendations apply to food practice.