Background Patient-Generated Health Data (PGHD) in remote monitoring programs is a promising source of precise, personalized data, encouraged by expanding growth in the health technologies market. However, PGHD utilization in clinical settings is low. One of the critical challenges that impedes confident clinical use of PGHD is that these data are not managed according to any recognized approach for data quality assurance. Objective This article aims to identify the PGHD management and quality challenges that such an approach must address, as these are expressed by key PGHD stakeholder groups. Materials and Methods In-depth interviews were conducted with 20 experts who have experience in the use of PGHD in remote patient monitoring, including: healthcare providers, health information professionals within clinical settings, and commercial providers of remote monitoring solutions. Participants were asked to describe PGHD management processes in the remote monitoring programs in which they are involved, and to express their perspectives on PGHD quality challenges during the data management stages. Results The remote monitoring programs in the study did not follow clear PGHD management or quality assurance approach. Participants were not fully aware of all the considerations of PGHD quality. Digital health literacy, wearable accuracy, difficulty in data interpretation, and lack of PGHD integration with electronic medical record systems were among the key challenges identified that impact PGHD quality. Conclusion Co-development of PGHD quality guidelines with relevant stakeholders, including patients, is needed to ensure that quality remote monitoring data from wearables is available for use in more precise and personalized patient care.

Background The COVID-19 pandemic has accelerated the uptake of digital health innovations due to the availability of various technologies and the urgent health care need for treatment and prevention. Although numerous studies have investigated digital health adoption and the associated challenges and strategies during the pandemic, there is a lack of evidence on the impact on the nursing workforce. Objective This study aims to identify the impact of digital health transformation driven by COVID-19 on nurses. Methods The online software Covidence was used to follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Relevant scientific health and computing databases were searched for papers published from January 2020 to November 2021. Using the 8D sociotechnical approach for digital health in health care systems, the papers were analyzed to identify gaps in applying digital health in nursing practice. Results In total, 21 papers were selected for content analysis. The analysis identified a paucity of research that quantifies the impact of the digital health transformation on nurses during the pandemic. Most of the initiatives were teleconsultation, followed by tele–intensive care unit (tele-ICU), and only 1 (5%) study explored electronic medical record (EMR) systems. Among the sociotechnical elements, the human-related factor was the most explored and the system measurement was the least studied item. Conclusions The review identified a significant gap in research on how implementing digital health solutions has impacted nurses during the COVID-19 pandemic. This gap needs to be addressed by further research to provide strategies for empowering the nursing workforce to be actively involved in digital health design, development, implementation, use, and evaluation.

Background The ubiquity of health wearables and the consequent production of patient-generated health data (PGHD) are rapidly escalating. However, the utilization of PGHD in routine clinical practices is still low because of data quality issues. There is no agreed approach to PGHD quality assurance; therefore, realizing the promise of PGHD requires in-depth discussion among diverse stakeholders to identify the data quality assurance challenges they face and understand their needs for PGHD quality assurance. Objective This paper reports findings from a workshop aimed to explore stakeholders’ data quality challenges, identify their needs and expectations, and offer practical solutions. Methods A qualitative multi-stakeholder workshop was conducted as a half-day event on the campus of an Australian University located in a major health care precinct, namely the Melbourne Parkville Precinct. The 18 participants had experience of PGHD use in clinical care, including people who identified as health care consumers, clinical care providers, wearables suppliers, and health information specialists. Data collection was done by facilitators capturing written notes of the proceedings as attendees engaged in participatory design activities in written and oral formats, using a range of whole-group and small-group interactive methods. The collected data were analyzed thematically, using deductive and inductive coding. Results The participants’ discussions revealed a range of technical, behavioral, operational, and organizational challenges surrounding PGHD, from the time when data are collected by patients to the time data are used by health care providers for clinical decision making. PGHD stakeholders found consensus on training and engagement needs, continuous collaboration among stakeholders, and development of technical and policy standards to assure PGHD quality. Conclusions Assuring PGHD quality is a complex process that requires the contribution of all PGHD stakeholders. The variety and depth of inputs in our workshop highlighted the importance of co-designing guidance for PGHD quality guidance.

Background:By providing sports organizations with electronic records and instruments that can be accessed at any time or place, specialized care can be offered to athletes regardless of injury location, and this makes the follow-up from first aid through to full recovery more efficient.Objectives:The aim of this study was to develop an electronic personal health record for professional Iranian athletes.Patients and Methods:First, a comparative study was carried out on the types of professional athletes’existing handheld and electronic health information management systems currently being used in Iran and leading countries in the field of sports medicine including; Australia, Canada and the United States. Then a checklist was developed containing a minimum dataset of professional athletes’ personal health records and distributed to the people involved, who consisted of 50 specialists in sports medicine and health information management, using the Delphi method. Through the use of data obtained from this survey, a basic paper model of professional athletes' personal health record was constructed and then an electronic model was created accordingly.Results:Access to information in the electronic record was through a web-based, portal system. The capabilities of this system included: access to information at any time and location, increased interaction between the medical team, comprehensive reporting and effective management of injuries, flexibility and interaction with financial, radiology and laboratory information systems.Conclusions:It is suggested that a framework should be created to promote athletes’ medical knowledge and provide the education necessary to manage their information. This would lead to improved data quality and ultimately promote the health of community athletes.

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Background Patient-generated health data (PGHD) collected from innovative wearables are enabling health care to shift to outside clinical settings through remote patient monitoring (RPM) initiatives. However, PGHD are collected continuously under the patient’s responsibility in rapidly changing circumstances during the patient’s daily life. This poses risks to the quality of PGHD and, in turn, reduces their trustworthiness and fitness for use in clinical practice. Objective Using a sociotechnical health informatics lens, we developed a data quality management (DQM) guideline for PGHD captured from wearable devices used in RPM with the objective of investigating how DQM principles can be applied to ensure that PGHD can reliably inform clinical decision-making in RPM. Methods First, clinicians, health information specialists, and MedTech industry representatives with experience in RPM were interviewed to identify DQM challenges. Second, these stakeholder groups were joined by patient representatives in a workshop to co-design potential solutions to meet the expectations of all the stakeholders. Third, the findings, along with the literature and policy review results, were interpreted to construct a guideline. Finally, we validated the guideline through a Delphi survey of international health informatics and health information management experts. Results The guideline constructed in this study comprised 19 recommendations across 7 aspects of DQM. It explicitly addressed the needs of patients and clinicians but implied that there must be collaboration among all stakeholders to meet these needs. Conclusions The increasing proliferation of PGHD from wearables in RPM requires a systematic approach to DQM so that these data can be reliably used in clinical care. The developed guideline is an important next step toward safe RPM.

BACKGROUND Patient-Generated Health Data (PGHD) collected from innovative wearables are enabling healthcare to shift to outside clinical settings through Remote Patient Monitoring (RPM) initiatives. However, PGHD are collected continuously under the patient’s responsibilities in rapidly changing circumstances during the patient’s daily life. This poses risks to the quality of PGHD and, in turn, reduces their trustworthiness and fitness for use in clinical practice. OBJECTIVE Using a socio-technical health informatics lens, this research aimed to investigate how Data Quality Management (DQM) principles can be applied to ensure that PGHD from wearables can reliably inform clinical decision making in RPM. METHODS First, clinicians, health information specialists and MedTech industry representatives with experience in RPM were interviewed to identify DQM challenges. Second, those groups were joined by patients in a workshop to co-design potential solutions to meet the expectations of all stakeholders. Third, the findings along with literature and policy review results, were interpreted to construct a guideline. Finally, we validated the guideline through a Delphi survey of international health informatics and health information management experts. RESULTS The resulting guideline comprised 19 recommendations across seven aspects of DQM. It explicitly addressed the needs of patients and clinicians but implied that there must be collaboration among all stakeholders, to meet these needs. CONCLUSIONS The increasing proliferation of PGHD from wearables in RPM requires a systematic approach to DQM so that these data can be reliably used in clinical care. The developed guideline is a significant next step toward safe RPM.

BACKGROUND The COVID-19 pandemic has accelerated the uptake of digital health innovations due to the availability of various technologies and the urgent healthcare need for treatment and prevention. While numerous studies investigated digital health adoption and the associated challenges and strategies during the pandemic, there is a lack of evidence on the impact on the nursing workforce. OBJECTIVE This study aimed to identify the impact of digital health transformation driven by COVID-19 on nurses. METHODS Online Covidence® software was used to follow the PRISMA protocol. Relevant scientific health and computing databases were searched for papers published between January 2020 to November 2021. Using the 8-dimensional sociotechnical approach for digital health in healthcare systems, the papers were analysed to identify gaps in applying digital health in nursing practice. RESULTS 21 papers were selected for content analysis. The analysis identified a paucity of research that quantifies the impact of the digital health transformation on nurses during the pandemic. Most of the initiatives were teleconsultation, followed by tele-ICU and only one study explored EMR systems. Among the sociotechnical elements, the human-related factor was the most explored and the system measurement was the least studied item. CONCLUSIONS The review identified a significant gap in research on how implementing digital health solutions has impacted nurses during the COVID-19 pandemic. This gap needs to be addressed by further research to provide strategies for empowering the nursing workforce to be actively involved in digital health design, development, implementation, use and evaluation.