The effects of data entry structure on patients’ perceptions of information quality in Health Information Exchange (HIE)

Perspectives of Patients With Chronic Diseases on Future Acceptance of AI-Based Home Care Systems: Cross-Sectional Web-Based Survey Study

BACKGROUND

Artificial intelligence (AI)-based home care systems and devices are being gradually integrated into health care delivery to benefit patients with chronic diseases. However, existing research mainly focuses on the technical and clinical aspects of AI application, with an insufficient investigation of patients' motivation and intention to adopt such systems.

OBJECTIVE

This study aimed to examine the factors that affect the motivation of patients with chronic diseases to adopt AI-based home care systems and provide empirical evidence for the proposed research hypotheses.

METHODS

We conducted a cross-sectional web-based survey with 222 patients with chronic diseases based on a hypothetical scenario.

RESULTS

The results indicated that patients have an overall positive perception of AI-based home care systems. Their attitudes toward the technology, perceived usefulness, and comfortability were found to be significant factors encouraging adoption, with a clear understanding of accountability being a particularly influential factor in shaping patients' attitudes toward their motivation to use these systems. However, privacy concerns persist as an indirect factor, affecting the perceived usefulness and comfortability, hence influencing patients' attitudes.

CONCLUSIONS

This study is one of the first to examine the motivation of patients with chronic diseases to adopt AI-based home care systems, offering practical insights for policy makers, care or technology providers, and patients. This understanding can facilitate effective policy formulation, product design, and informed patient decision-making, potentially improving the overall health status of patients with chronic diseases.

Use of Health Information Exchange in the Continuity of Care as Viewed by Patients and Nurses: A Cross-Sectional Study

Patients' attitudes toward sharing their personal health information are critical for implementation of health information exchange. Nurses contribute significantly to information sharing within the care continuum in hospitals and community. This study aimed to examine the awareness and readiness of patients with chronic illness and nurses to the use health information exchange. A cross-sectional study was conducted among 314 inpatients with a chronic illness, 110 nurses working in internal wards, and 55 contact nurses working in a large health maintenance organization. The findings showed that the mean level of awareness was low across all three groups. Contact nurses expressed more positive attitudes than internal ward nurses or patients and were more willing than patients to share information with healthcare workers. Knowledge, attitudes, and being a nurse predicted the intention to share information with medical healthcare providers and with agents not involved in direct care. Before implementation of a health information exchange system, it is important to raise awareness, readiness, and intention to use it among the public, nurses, and other medical staff. Policy makers should organize national campaigns under the auspices of the Ministry of Health to present the advantages and provide detailed information about the system.

Factors influencing patients' opt-in intention of exchanging health information

Introduction

Health information exchange (HIE) exhibits tremendous benefits in improving the quality of healthcare and reducing healthcare costs. However, it also poses challenges related to data security, data privacy, patient engagement, etc.

Objective

This study aimed to explore the factors affecting patients' opt-in intention to HIE by using an empirical study based on the theory of planned behavior.

Methods

A Web-based survey was conducted involving 501 valid participants in China (69% validity rate).

Results

Information sensitivity and perceived HIE transparency affected the patients' opt-in intention to HIE through the mediation of perceived behavior control and trust in HIE. Information sensitivity negatively influenced perceived behavior control (-0.551, P < 0.001) and trust in HIE (-0.489, P < 0.001). Perceived transparency of HIE positively influenced perceived behavior control (0.396, P < 0.001) and trust in HIE (0.471, P < 0.001). Moreover, patients' opt-in intention to HIE can be positively affected by perceived HIE transparency (0.195, P < 0.001) and trust in HIE (0.294, P < 0.001). In addition, the moderating effect of health status was positive and significant between trust in HIE and opt-in intention to HIE but not between the perceived behavior control and opt-in intention to HIE.

Conclusion

This study contributes to the theory of planned behavior and enriches the literature on HIE efforts. HIE administrators should design personalized health services on the basis of these different health statuses to successfully achieve patients' opt-in intention to HIE.

Human Factors and Organizational Issues in Health Informatics: Innovations and Opportunities

OBJECTIVE

Human factors and ergonomics (HF/E) frameworks and methods are becoming embedded in the health informatics community. There is now broad recognition that health informatics tools must account for the diverse needs, characteristics, and abilities of end users, as well as their context of use. The objective of this review is to synthesize the current nature and scope of HF/E integration into the health informatics community.

METHODS

Because the focus of this synthesis is on understanding the current integration of the HF/E and health informatics research communities, we manually reviewed all manuscripts published in primary HF/E and health informatics journals during 2020.

RESULTS

HF/E-focused health informatics studies included in this synthesis focused heavily on EHR customizations, specifically clinical decision support customizations and customized data displays, and on mobile health innovations. While HF/E methods aimed to jointly improve end user safety, performance, and satisfaction, most HF/E-focused health informatics studies measured only end user satisfaction.

CONCLUSION

HF/E-focused health informatics researchers need to identify and communicate methodological standards specific to health informatics, to better synthesize findings across resource intensive HF/E-focused health informatics studies. Important gaps in the HF/E design and evaluation process should be addressed in future work, including support for technology development platforms and training programs so that health informatics designers are as diverse as end users.

Predictors of electronic health management information system for improving the quality of care for women and people with disabilities

The electronic Hospital management Information System (eHMIS) can improve care for vulnerable patients, help collect important disability and maternal health data, and improve the hospital’s overall data management. This study assessed the use of HMIS and factors influencing the usage and behavioral intentions to use the eHMIS at the Comprehensive Community Based Rehabilitation in Tanzania (CCBRT). We investigated both clinical and non-clinical staff (n=69) using tablets and online surveys, with a rate of return of 71.9%. The ICT staff were also interviewed to supplement data from the survey. The survey questionnaire was guided by the updated Information System Success (ISS) model. Most health workers (81.2%) used the eHMIS several times a day to support different decision-making activities. The better educated personnel were more likely to enter data more effectively into eHMIS as compared to their counterparts. Among six predictors, self-efficacy positively influenced self-reported use and user satisfaction of HMIS, while service quality negatively affected self-reported use of eHMIS. The system quality positively influenced health workers to be satisfied with the eHMIS, and user satisfaction positively influenced continued usage intention of the eHMIS. Both user satisfaction and continued usage intention were positively related to individual impact of eHMIS. Individual impact had positive effects on organizational impact of eHMIS. This is a comprehensive study conducted in Tanzania regarding the implementation of eHMIS, and factors influencing post-adoptive use of HMIS to improve quality of care of women and people with disabilities.

Trends in Clinical Information Systems Research in 2019

Objective : To give an overview of recent research and to propose a selection of best papers published in 2019 in the field of Clinical Information Systems (CIS).

Method : Each year, we apply a systematic process to retrieve articles for the CIS section of the IMIA Yearbook of Medical Informatics. For six years now, we use the same query to find relevant publications in the CIS field. Each year we retrieve more than 2,000 papers. As CIS section editors, we categorize the retrieved articles in a multi-pass review to distill a pre-selection of 15 candidate best papers. Then, Yearbook editors and external reviewers assess the selected candidate best papers. Based on the review results, the IMIA Yearbook Editorial Committee chooses the best papers during the selection meeting. We used text mining, and term co-occurrence mapping techniques to get an overview of the content of the retrieved articles.

Results : We carried out the query in mid-January 2020 and retrieved a de-duplicated result set of 2,407 articles from 1,023 different journals. This year, we nominated 14 papers as candidate best papers, and three of them were finally selected as best papers in the CIS section. As in previous years, the content analysis of the articles revealed the broad spectrum of topics covered by CIS research.

Conclusions : We could observe ongoing trends, as seen in the last years. Patient benefit research is in the focus of many research activities, and trans-institutional aggregation of data remains a relevant field of work. Powerful machine-learning-based approaches, that use readily available data now often outperform human-based procedures. However, the ethical perspective of this development often comes too short in the considerations. We thus assume that ethical aspects will and should deliver much food for thought for future CIS research.