General Practice and Primary Care - Theses

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    Development of a Data Quality Management Guideline for Patient Generated Health Data in Remote Patient Monitoring
    Abdolkhani, Robab ( 2021)
    Abstract: Patient-Generated Health Data (PGHD) collected from innovative medical and consumer wearable technologies are enabling healthcare to shift from inside clinical settings to outside of them through Remote Patient Monitoring (RPM) initiatives. RPM enables continuous monitoring of patients while they are mobile outside the clinical environment and has the potential to empower patients in their health self-management and improve their clinical outcomes. However, PGHD are being collected on an ongoing basis under the patient’s or caregiver’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. This issue is limiting the use of such data in RPM, to project-oriented and short-term services that are not incorporated into clinical workflows as part of routine clinical practices. Although there are Data Quality Management (DQM) guidelines for the clinical data routinely collected inside clinical settings, no systematic approach exists to assure the quality of PGHD, whether captured from medical or consumer wearables, so that these data offer the basis for safe patient care. This thesis aimed to address this problem, using a socio-technical health informatics lens to investigate cow can DQM assure that PGHD from medical or consumer wearables are fit for use in clinical care. Following a recognised guideline development process, using five qualitative studies, this thesis developed a DQM guideline for PGHD that stakeholders can use to enhance the value of these data in routine clinical practice. PGHD stakeholders who have experience in RPM were involved in two studies: first, in-depth interviews to identify DQM challenges; and second, a workshop to co-design potential solutions to meet the needs and expectations of stakeholder groups. Next, findings from these two studies, along with results from a preliminary and updated literature review, and a policy review, were interpreted to construct the guideline. The resulting DQM guideline for PGHD comprised 19 recommendations across seven aspects of data quality: accessibility, accuracy, completeness, consistency, interpretability, relevancy, and timeliness. The guideline explicitly addressed the needs of key PGHD stakeholders - patients and clinicians - and it implied that there must be collaboration among all stakeholders, to meet these needs. The final qualitative study in this thesis validated the guideline by seeking experts’ opinion on its likely contribution to the safety and quality of care in RPM. Using the Delphi method, the guideline was distributed via an online survey among international health informatics and health information experts. There was consensus that the guideline’s recommendations are essential to delivering safe and high-quality RPM services. The increasing proliferation of PGHD from health wearables in RPM requires a systematic approach to enable the reliability of these data for use in clinical care. This thesis provided early, significant steps toward practising DQM of PGHD for incorporation into routine clinical practices.