"The Doctor Needs to Know": Acceptability of Smartphone Location Tracking for Care Coordination

Geofencing in location-based behavioral research: Methodology, challenges, and implementation

This manuscript presents a novel geofencing method in behavioral research. Geofencing, built upon geolocation technology, constitutes virtual fences around specific locations. Every time a participant crosses the virtual border around the geofenced area, an event can be triggered on a smartphone, e.g., the participant may be asked to complete a survey. The geofencing method can alleviate the problems of constant location tracking, such as recording sensitive geolocation information and battery drain. In scenarios where locations for geofencing are determined by participants (e.g., home, workplace), no location data need to be transferred to the researcher, so this method can ensure privacy and anonymity. Given the widespread use of smartphones and mobile Internet, geofencing has become a feasible tool in studying human behavior and cognition outside of the laboratory. The method can help advance theoretical and applied psychological science at a new frontier of context-aware research. At the same time, there is a lack of guidance on how and when geofencing can be applied in research. This manuscript aims to fill the gap and ease the adoption of the geofencing method. We describe the current challenges and implementations in geofencing and present three empirical studies in which we evaluated the geofencing method using the Samply application, a tool for mobile experience sampling research. The studies show that sensitivity and precision of geofencing were affected by the type of event, location radius, environment, operating system, and user behavior. Potential implications and recommendations for behavioral research are discussed.

Informing Acceptability and Feasibility of Digital Phenotyping for Personalized HIV Prevention among Marginalized Populations Presenting to the Emergency Department

For marginalized populations with ongoing HIV epidemics, alternative methods are needed for understanding the complexities of HIV risk and delivering prevention interventions. Due to lack of engagement in ambulatory care, such groups have high utilization of drop-in care. Therefore, emergency departments represent a location with those at highest risk for HIV and in highest need of novel prevention methods. Digital phenotyping via data collected from smartphones and other wearable sensors could provide the innovative vehicle for examining complex HIV risk and assist in delivering personalized prevention interventions. However, there is paucity in exploring if such methods are an option. This study aimed to fill this gap via a cross-sectional psychosocial assessment with a sample of N=85 emergency department patients with HIV risk. Findings demonstrate that although potentially feasible, acceptability of digital phenotyping is questionable. Technology-assisted HIV prevention needs to be designed with the target community and address key ethical considerations.

"It closes the gap when the ball is dropped": patient perspectives of a novel smartphone app for regional care coordination after hospital encounters

BACKGROUND

Despite the broad adoption of electronic health records (EHRs) for inpatient and outpatient care, and wide availability of EHR-linked portals, these tools are not always effective in informing primary care teams about patients' emergency department (ED) visits or inpatient admissions, leading to persistent gaps in care coordination. The objective of this study was to understand how patients with limited patient portal use in a safety net setting engaged with a smartphone app that used location tracking to detect and notify care teams about patients' hospital use in order to stimulate care coordination and follow-up care.

METHODS

We recruited English- and Spanish-speaking adults at high risk of hospital use from a Federally Qualified Health Center (FQHC). The app detected when patients visited the hospital and asked them to confirm a hospital visit. When confirmed, the app notified the primary care team about the visit, and the care team followed up with patients according to the FQHC protocols for care coordination. We collected qualitative data on app experience from participants who used the app for four months and used a general inductive approach to identify recurring themes.

RESULTS

Participants generally reported a positive app experience, as it helped solve the problem of poor follow-up care. "I liked the goal of the app…Ultimate goal of it was comforting", recounted one participant when describing her app experience. Participants thought the app push notifications could be refined and the app itself could be modernized. Participants also suggested improvements to the push notifications they received from the app and the visit information they entered into the app for care teams to receive. Some participants also suggested improvements to the FQHC's care coordination workflows facilitated by the app, like an immediate connection to the patient's primary care team.

CONCLUSIONS

The app was well received by low-income patients at high risk of ED/inpatient visits. Future research is needed to determine feasibility of implementation in other settings.

GPS Mobile Health Intervention Among People Experiencing Homelessness: Pre-Post Study

BACKGROUND

People experiencing homelessness are at risk for gaps in care after an emergency department (ED) or hospital visit, which leads to increased use, poor health outcomes, and high health care costs. Most people experiencing homelessness have a mobile phone of some type, which makes mobile health (mHealth) interventions a feasible way to connect a person experiencing homelessness with providers.

OBJECTIVE

This study aims to investigate the accuracy, acceptability, and preliminary outcomes of a GPS-enabled mHealth (GPS-mHealth) intervention designed to alert community health paramedics when people experiencing homelessness are in the ED or hospital.

METHODS

This study was a pre-post design with baseline and 4-month postenrollment assessments. People experiencing homelessness, taking at least 2 medications for chronic conditions, scoring at least 10 on the Patient Health Questionnaire-9, and having at least 2 ED or hospital visits in the previous 6 months were eligible. Participants were issued a study smartphone with a GPS app programmed to alert a community health paramedic when a participant entered an ED or hospital. For each alert, community health paramedics followed up via telephone to assess care coordination needs. Participants also received a daily email to assess medication adherence. GPS alerts were compared with ED and hospital data from the local health information exchange (HIE) to assess accuracy. Paired t tests compared scores on the Patient Health Questionnaire-9, Medical Outcomes Study Social Support Survey, and Adherence Starts with Knowledge-12 adherence survey at baseline and exit. Semistructured exit interviews examined the perceptions and benefits of the intervention.

RESULTS

In total, 30 participants were enrolled; the mean age was 44.1 (SD 9.7) years. Most participants were male (20/30, 67%), White (17/30, 57%), and not working (19/30, 63%). Only 19% (3/16) of the ED or hospital visit alerts aligned with HIE data, mainly because of patients not having the smartphone with them during the visit, the smartphone being off, and gaps in GPS technology. There was a significant difference in depressive symptoms between baseline (mean 16.9, SD 5.8) and exit (mean 12.7, SD 8.2; t₁₉=2.9; P=.009) and a significant difference in adherence barriers between baseline (mean 2.4, SD 1.4) and exit (mean 1.5, SD 1.5; t₁₇=2.47; P=.03). Participants agreed that the app was easy to use (mean 4.4/5, SD 1.0, with 5=strongly agree), and the email helped them remember to take their medications (mean 4.6/5, SD 0.6). Qualitative data indicated that unlimited smartphone access allowed participants to meet social needs and maintain contact with case managers, health care providers, family, and friends.

CONCLUSIONS

mHealth interventions are acceptable to people experiencing homelessness. HIE data provided more accurate ED and hospital visit information; however, unlimited access to reliable communication provided benefits to participants beyond the study purpose of improving care coordination.

Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study

INTRODUCTION

Cough is a common symptom of COVID-19 and other respiratory illnesses. However, objectively measuring its frequency and evolution is hindered by the lack of reliable and scalable monitoring systems. This can be overcome by newly developed artificial intelligence models that exploit the portability of smartphones. In the context of the ongoing COVID-19 pandemic, cough detection for respiratory disease syndromic surveillance represents a simple means for early outbreak detection and disease surveillance. In this protocol, we evaluate the ability of population-based digital cough surveillance to predict the incidence of respiratory diseases at population level in Navarra, Spain, while assessing individual determinants of uptake of these platforms.

METHODS AND ANALYSIS

Participants in the Cendea de Cizur, Zizur Mayor or attending the local University of Navarra (Pamplona) will be invited to monitor their night-time cough using the smartphone app Hyfe Cough Tracker. Detected coughs will be aggregated in time and space. Incidence of COVID-19 and other diagnosed respiratory diseases within the participants cohort, and the study area and population will be collected from local health facilities and used to carry out an autoregressive moving average analysis on those independent time series. In a mixed-methods design, we will explore barriers and facilitators of continuous digital cough monitoring by evaluating participation patterns and sociodemographic characteristics. Participants will fill an acceptability questionnaire and a subgroup will participate in focus group discussions.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the ethics committee of the Centre Hospitalier de l'Université de Montréal, Canada and the Medical Research Ethics Committee of Navarre, Spain. Preliminary findings will be shared with civil and health authorities and reported to individual participants. Results will be submitted for publication in peer-reviewed scientific journals and international conferences.

TRIAL REGISTRATION NUMBER

NCT04762693.

Issues in Child and Adolescent Inpatient Assessment and Evaluation After Discharge: Protocol for App Development and a Randomized Controlled Trial

Background

New methods are needed for collecting data of in- and outpatients and for improving outpatient compliance after discharge. Mobile technologies, such as smartphone apps, have shown promising results, (eg, helping unwell people by offering support and resources). Screening for the condition, including comorbidities, is a vital part of psychiatric care. Comorbid conditions, especially in emergency evaluation, are often missed, leading to inaccurate diagnosis and treatment. One way of improving diagnostic accuracy is to use a structured diagnostic process. Digitalized screening and follow-up have the advantage of making administration and scoring easier and less time consuming, thereby increasing response rate. To address these problems, we decided to create a smartphone app called The Blue App. The Blue App was developed through 6 steps, described in the manuscript.

Objective

The aim of this paper is to describe (1) the development of The Blue App and (2) 2 planned research studies to evaluate the app.

Methods

Two studies will be performed. Study 1 has a descriptive design, mapping comorbidities before and after the introduction of The Blue App. Study 2 has a randomized controlled design, measuring compliance with outpatient treatments as well as depressive symptoms, rated as changes in Montgomery-Åsberg Depression Scale scores during a 1-year follow-up.

Results

We have described app development. Data collection for Study 1 started in autumn 2017. Study 2 will start in autumn 2018. We expect to have enrolled the 150 patients in Study 2 by December 2019. Final results will be published in a scientific journal.

Conclusions

A technically advanced and easy-to-use Web-based mobile phone app corresponding to the unit’s needs was developed, and 2 studies are planned to evaluate its usefulness.

International Registered Report Identifier (IRRID)

RR1-10.2196/10121