Background Patient-generated health data (PGHD) have been largely collected through mobile health (mHealth) apps and wearable devices. PGHD can be especially helpful in mental health, as patients’ illness history and symptom narratives are vital to developing diagnoses and treatment plans. However, the extent to which clinicians use mental health–related PGHD is unknown. Objective A mixed methods study was conducted to understand clinicians’ perspectives on PGHD and current mental health apps. This approach uses information gathered from semistructured interviews, workflow analysis, and user-written mental health app reviews to answer the following research questions: (1) What is the current workflow of mental health practice and how are PGHD integrated into this workflow, (2) what are clinicians’ perspectives on PGHD and how do they choose mobile apps for their patients, (3) and what are the features of current mobile apps in terms of interpreting and sharing PGHD? Methods The study consists of semistructured interviews with 12 psychiatrists and clinical psychologists from a large academic hospital. These interviews were thematically and qualitatively analyzed for common themes and workflow elements. User-posted reviews of 56 sleep and mood tracking apps were analyzed to understand app features in comparison with the information gathered from interviews. Results The results showed that PGHD have been part of the workflow, but its integration and use are not optimized. Mental health clinicians supported the use of PGHD but had concerns regarding data reliability and accuracy. They also identified challenges in selecting suitable apps for their patients. From the app review, it was discovered that mHealth apps had limited features to support personalization and collaborative care as well as data interpretation and sharing. Conclusions This study investigates clinicians’ perspectives on PGHD use and explored existing app features using the app review data in the mental health setting. A total of 3 design guidelines were generated: (1) improve data interpretation and sharing mechanisms, (2) consider clinical workflow and electronic health record integration, and (3) support personalized and collaborative care. More research is needed to demonstrate the best practices of PGHD use and to evaluate their effectiveness in improving patient outcomes.
Background Clinician burnout is a prevalent issue in healthcare, with detrimental implications in healthcare quality and medical costs due to errors. The inefficient use of health information technologies (HIT) is attributed to having a role in burnout. Objective This paper seeks to review the literature with the following two goals: (1) characterize and extract HIT trends in burnout studies over time, and (2) examine the evidence and synthesize themes of HIT's roles in burnout studies. Methods A scoping literature review was performed by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with two rounds of searches in PubMed, IEEE Xplore, ACM, and Google Scholar. The retrieved papers and their references were screened for eligibility by using developed inclusion and exclusion criteria. Data were extracted from included papers and summarized either statistically or qualitatively to demonstrate patterns. Results After narrowing down the initial 945 papers, 36 papers were included. All papers were published between 2013 and 2020; nearly half of them focused on primary care (n = 16; 44.4%). The most commonly studied variable was electronic health record (EHR) practices (e.g., number of clicks). The most common study population was physicians. HIT played multiple roles in burnout studies: it can contribute to burnout; it can be used to measure burnout; or it can intervene and mitigate burnout levels. Conclusion This scoping review presents trends in HIT-centered burnout studies and synthesizes three roles for HIT in contributing to, measuring, and mitigating burnout. Four recommendations were generated accordingly for future burnout studies: (1) validate and standardize HIT burnout measures; (2) focus on EHR-based solutions to mitigate clinician burnout; (3) expand burnout studies to other specialties and types of healthcare providers, and (4) utilize mobile and tracking technology to study time efficiency.
Objective Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery. Materials and Methods We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies. Results We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6). Discussion The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data. Conclusions RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data.
Objective This study aimed to understand how a metaverse-based (virtual) workspace can be used to support the communication and collaboration in an academic health informatics lab. Materials and Methods A survey of lab members (n = 14) was analyzed according to a concurrent triangulation mixed methods design. The qualitative survey data were organized according to the Capability, Opportunity, Motivation, Behavior (COM-B) model and combined to generate personas that represent the overall types of lab members. Additionally, scheduled work hours were analyzed quantitatively to complement the findings of the survey feedback. Results Four personas, representative of different types of virtual workers, were developed using the survey responses. These personas reflected the wide variety of opinions about virtual work among the participants and helped to categorize the most common feedback. The Work Hours Schedule Sheet analysis showed the low number of possible collaboration opportunities that were utilized compared to the number available. Discussion We found that informal communication and co-location were not supported by the virtual workplace as we had originally planned. To solve this issue, we offer 3 design recommendations for those looking to implement their own virtual informatics lab. First, labs should establish common goals and norms for virtual workplace interactions. Second, labs should carefully plan the virtual space layout to maximize communication opportunities. Finally, labs should work with their platform of choice to address technical limitations for their lab members to improve user experience. Future work includes a formal, theory-guided experiment with consideration on ethical and behavioral impact.
BACKGROUND Patient-generated health data (PGHD) has been largely collected through mobile-based health applications (mHealth apps) and wearable devices. PGHD can be especially helpful in mental health, since patients’ illness history and symptom narratives are vital to developing diagnoses and treatment plans. However, the extent of clinicians’ use of mental health-related PGHD is unknown. OBJECTIVE A mixed-method study was conducted to understand clinicians’ perspectives on PGHD and current mental health apps. This approach built on information gathered from semi-structured interviews, workflow analysis, and user-written mental health app reviews to answer the following research questions: 1) What is the current workflow of mental health practice and how is PGHD integrated in this workflow? 2) What are physician perspectives on PGHD and how do they choose mobile apps for their patients? 3) What are the features of current mobile apps in terms of interpreting and sharing PGHD? METHODS The study consisted of semi-structured interviews with 12 psychiatrists and clinical psychologists from a large academic hospital. These interviews were then thematically and qualitatively analyzed for common themes and workflow elements. App-user reviews were then analyzed to understand app features and their usability in comparison to the information gathered from interviews. RESULTS The results showed that PGHD has been part of the workflow, but its integration and use are not optimized. Mental health clinicians supported the use of PGHD but also identified challenges in selecting suitable apps for their patients. From the app review, it was shown that mHealth apps had limited features to support personalization and collaborative care and had data interpretation and sharing issues. Based on the findings, design implications were discussed with the goal of improving PGHD use within and mHealth app design for mental health practice. CONCLUSIONS The study showed that PGHD has not been used optimally in mental health practices. Clinicians expressed concerns regarding how PGHD may be used to improve workflow and how it may be integrated with current EHR systems. Moreover, mental health clinicians also faced challenges in helping their patients choosing appropriate apps. Finally, several design implications were identified from the results of the app review that will be used to drive future research regarding PGHD use in mental health. CLINICALTRIAL None
BACKGROUND User needs assessments have become increasingly essential in the development of mobile health technology but may be hindered by time and resource restraints. Analyzing online health forum data may provide a substitute for in-person assessments and could provide the data necessary to inform mobile-based application development. OBJECTIVE : A feasibility study was conducted to determine whether forum posts on Alzheimer's disease could 1) help identify patient and caregiver needs to inform application design and 2) determine whether these needs can be identified automatically by classic text clustering methods. METHODS Posts on an Alzheimer's disease forum were collected and subsequently analyzed through a manual thematic coding process and used to generate user personas. The personas were compared and contrasted with personas collected through in-person interviews. Concurrently, the posts were clustered using hierarchical clustering algorithms. An external evaluation was conducted to compare the automatic and manual clusters. RESULTS A total of 413 forum posts were collected. The thematic coding process yielded three themes and nine subthemes with a high level of agreement between coders. The themes helped inform four distinct user personas. The external evaluation showed fair to substantial scores for the similarity between the automatic and manual labels. CONCLUSIONS Forum posts can be useful in understanding patients and caregiver needs. The personas based on the forum posts can provide a broader view of user needs, while the personas generated from the in-person interviews support developing a deeper understanding of user needs. Automated clustering algorithms achieved a fair performance in clustering the forum posts to match the manually derived themes. More research is needed to improve the clustering algorithm performance to facilitate user needs assessment in mobile app development. CLINICALTRIAL N/A
Introduction: Heart failure (HF) is among the most common reasons for hospital admissions, presenting a significant cost burden to the medical system. Patients are monitored at the hospital but often go home without enough long-term management. Chronic care involving consistent symptom monitoring and patient-provider communication is essential to HF management. Though careful management can improve patient quality of life and reduce hospital readmission costs, it may be time consuming and expensive. To address this, we created a SMS text-based platform, EpxHeartFailure (EpxHF), which allows for remote patient monitoring. Our novel platform seeks to improve chronic care management by simplifying patient self-care and patient-provider communication. The goal of this low-cost intervention is to gain patient and provider acceptability and improve patient symptom stability. Methods: We conducted a retrospective review of a commercial implementation of EpxHF. Data was collected from patients over a 30-week trial period. EpxHF prompted patients to self-report body weight and symptoms of dyspnea/pedal edema (DPE), orthopnea, and edema compared to the previous day. Weight gain (>5lbs over 1 week) plus 1 other worsening symptom triggered an alert (text or call) to the patient’s provider. Providers could then contact the patient and initiate follow up care. The intervention modified message frequency to parallel each patient’s symptom stability and sent providers bimonthly triaged reports that prioritized the most unstable patients. Patients were also asked a question adapted from Kansas City Cardiomyopathy Questionnaire (KCCQ) to assess quality of life and how often a patient’s symptoms interfere with daily functioning (0 - never, 5- all the time). Results: One-hundred seventy patients in St. Louis were enrolled onto EpxHF at hospitals using care managers within risk sharing and capacitated value models. A total of 3244 texts were sent, 87 alerts were generated, and 99 communications between providers and patients were documented following alerts. The average patient engagement rate was 81%, indicating acceptability. Normalized data for DPE, orthopnea, and excessive weight gain on a scale of -1 to +1 (+1 representing symptom improvement, 0 no change, -1 worsening symptoms) indicated a clear trend of improvement on a weekly basis (avg for all patients: 0.24 DPE, 0.21 orthopnea, 0.07 excessive weight gain). At week 30, the average KCCQ score decreased by 1.38 from baseline (95% CI: 1.299-1.467), which indicates an increase in perceived quality of life. Discussion: The results demonstrate the ability of the system to engage patients, track their symptomatology and improve quality of life. EpxHF is a cost-effective tool that uses basic texting technology to help providers monitor HF patient’s fluctuating symptoms, with the goal of enabling medical intervention before a HF exacerbation occurs.
BACKGROUND Health literacy is the ability to make informed decisions using health information. As health data and information availability increases due to online clinic notes and patient portals, it is important to understand how health literacy relates to social determinants of health and the place of informatics in mitigating disparities. OBJECTIVE This systematic literature review aims to examine the role of health literacy in interactions with social determinants of health and to identify feasible health literacy-based interventions that address low patient understanding of health information to improve clinic note sharing efficacy. METHODS The review examined two databases, Scopus and PubMed, for English language articles relating to health literacy and social determinants of health. We conducted a quantitative analysis of study characteristics and qualitative synthesis to determine roles of health literacy and interventions. RESULTS The results (n=43) were analyzed quantitatively and qualitatively for study characteristics, role of health literacy, and interventions. A majority (n=30) identified a correlate role for health literacy in relation to social determinants of health, but others noted that health literacy could also be a mediator (n=5), a result of social determinants of health (n=5), or considered a modifiable social determinant of health (n=2). CONCLUSIONS The multivariable nature of health literacy indicates that it could form the basis for many interventions to combat low patient understandability, including interventions using informatics-based solutions. Health literacy is a crucial, multidimensional skill in supporting patient understanding of health materials. Designing interventions aimed at improving health literacy or addressing poor health literacy in patients can help increase comprehension of health information, including the information contained in clinic notes that are shared with patients.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.