Yes / Background: A Personal Health Record (PHR) is an electronic record that individuals use to manage and share their health information, e.g. data from their medical records and data collected by apps. However, engagement with their record can be low if people do not find it beneficial to their health, wellbeing or interactions with health and other services. We have explored the beliefs potential users have about a PHR, how it could be made personally relevant, and barriers to its use. Methods: A qualitative design comprising eight focus groups, each with 6–8 participants. Groups included adults with long-term health conditions, young people, physically active adults, data experts, and members of the voluntary sector. Each group lasted 60–90 min, was audio recorded and transcribed verbatim. We analysed the data using thematic analysis to address the question “What are people’s beliefs about making a Personal Health Record have relevance and impact?” Results: We found four themes. Making it work for me is about how to encourage individuals to actively engage with their PHR. I control my information is about individuals deciding what to share and who to share it with. My concerns is about individuals’ concerns about information security and if and how their information will be acted upon. Potential impact shows the potential benefits of a PHR such as increasing self-efficacy, uptake of health-protective behaviours, and professionals taking a more holistic approach to providing care and facilitating behaviour change. Conclusions: Our research shows the functionality that a PHR requires in order for people to engage with it. Interactive functions and integration with lifestyle and health apps are particularly important. A PHR could increase the effectiveness of behaviour change apps by specifying evidence-based behaviour change techniques that apps should incorporate. A PHR has the potential to increase health-protective behaviours and facilitate a more person-driven health and social care system. It could support patients to take responsibility for self-managing their health and treatment regimens, as well as helping patients to play a more active role when care transfers across boundaries of responsibility. / Leeds Informatics Board

京都大学 / 新制・論文博士 / 博士(医学) / 乙第13600号 / 論医博第2310号 / 新制||医||1072(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 村井 俊哉, 教授 佐藤 俊哉, 教授 永井 洋士 / 学位規則第4条第2項該当 / Doctor of Medical Science / Kyoto University / DFAM

Through significant federal investment and incentives, Electronic Health Records have become ubiquitous in modern hospitals. Over the past decade, these computer support systems have provided healthcare operations with new safety nets, and efficiency increases, but also introduce new problems when they suddenly go offline. These downtime events are chaotic and dangerous for patients. With the safety systems clinicians have become accustomed to offline, patients are at risk from errors and delays. This work applies the Macroergonomic methodology to facilitate an exploratory study into the issues related to patient care during downtime events. This work uses data from existing sources within the hospital, such as the electronic health record itself. Data collection mechanisms included interviews, downtime paper reviews, and workplace observations. The triangulation of data collection mechanisms facilitated a thorough exploration of the issues of downtime. The Macroergonomic Analysis and Design (MEAD) methodology was used to guide the analysis of the data, and identify variances and shifts in responsibility due to downtime. The analysis of the data supports and informs developing potential intervention strategies to enable hospitals to better cope with downtime events. Within MEAD, the assembled data is used to inform the creation of a simulation model which was used to test the efficacy of the intervention strategies. The results of the simulation testing are used to determine the specific parameters of the intervention suggestions as they relate to the target hospitals. The primary contributions of this work are an exploratory study of electronic health record downtime and impacts to patient safety, and an adaptation of the Macroergonomic Analysis and Design methodology, employing multiple data collection methods and a high-fidelity simulation model. The methodology is intended to guide future research into the downtime issue, and the direct findings can inform the creation of better downtime contingency strategies for the target hospitals, and possibly to offer some generalizability for all hospitals. / Ph. D. / Hospitals experience periodic outages of their computerized work support systems from a variety of causes. These outages can range from partial communication and or access restrictions to total shutdown of all computer systems. Hospitals operating during a computerized outage or downtime are potentially unable to access computerized records, procedures and conduct patient care activities which are facilitated by computerized systems. Hospitals are in need of a means to cope with the complications of downtime and the loss of computerized support systems without risking patient care. This dissertation assesses downtime preparedness and planning through the application of Macroergonomics which has incorporated discrete event simulation. The results provide a further understanding of downtime risks and deficiencies in current planning approaches. The study enhances the application of Macroergonomics and demonstrates the value of discrete event simulation as a tool to aid in Macroergonomic evaluations. Based on the Macroergonomic Analysis and Design method, downtime improvement strategies are developed and tested, demonstrating their potential efficacy over baseline. Through this dissertation, the deficiencies in current contingency plans are examined and exposed and further the application of Macroergonomics in healthcare.

Yes / Interoperability within different healthcare systems (clinics/hospitals/pharmacies) remains an issue of further research due to a barrier in sharing of the patient’s Electronic Health Record (EHR) information. To solve this problem, cross healthcare system collaboration is required. This paper proposes an interoperability framework that enables a pharmacist to access an electronic version of the patient’s prescription from the doctor using a RESTFul API with ease. Semantic technology standards like Web Ontology Language (OWL), RDF (Resource Description Framework) and SPARQL (SPARQL Protocol and RDF Query Language) were used to implement the framework using JENA semantic framework tool to demonstrate how interoperability is achieved between a pharmacy and a clinic JENA was used to generate the ontology models for the pharmacy called pharmacy.rdf and clinic called clinic.rdf. The two models contain all the information from the two isolated systems. The JENA reasoner was used to merge the two ontology models into a single model.rdf file for easy querying with SPARQL. The model.rdf file was uploaded into a triple store database created using FUSEKI server. SPARQL Endpoint generated from FUSEKI was used to query the triple store database using a RESTFul API. The system was able to query the triple store database and output the results containing the prescription name and its details in JSON and XML formats which can be read by both machines and humans. / Supported by a Institutional Links grant, ID 261865161, under the Newton-Ristekdikti Fund partnership. The grant is funded by the UK Department for Business, Energy and Industrial Strategy and Indonesia Ministry of Research, Technology and Higher Education and delivered by the British Council.

Yes / Purpose: To identify a minimum list of metrics of international relevance to public health, research and service development which can be extracted from practice management systems and electronic patient records in primary optometric practice. Methods: A two stage modified Delphi technique was used. Stage 1 categorised metrics that may be recorded as being part of a primary eye examination by their importance to research using the results from a previous survey of 40 vision science and public health academics. Delphi stage 2 then gauged the opinion of a panel of 7 vision science academics and achieved consensus on contentious metrics and methods of grading/classification. Results: A consensus regarding inclusion and response categories was achieved for nearly all metrics. A recommendation was made of 53 metrics which would be appropriate in a minimum data set. Conclusions: This minimum data set should be easily integrated into clinical practice yet allow vital data to be collected internationally from primary care optometry. It should not be mistaken for a clinical guideline and should not add workload to the optometrist. A pilot study incorporating an additional Delphi stage prior to implementation is advisable to refine some response categories. / This work was supported by the College of Optometrists.

Yes / frailty is an especially problematic expression of population ageing. International guidelines recommend routine identification of frailty to provide evidence-based treatment, but currently available tools require additional resource. Objectives: to develop and validate an electronic frailty index (eFI) using routinely available primary care electronic health record data. Study design and setting: retrospective cohort study. Development and internal validation cohorts were established using a randomly split sample of the ResearchOne primary care database. External validation cohort established using THIN database. Participants: patients aged 65–95, registered with a ResearchOne or THIN practice on 14 October 2008. Predictors: we constructed the eFI using the cumulative deficit frailty model as our theoretical framework. The eFI score is calculated by the presence or absence of individual deficits as a proportion of the total possible. Categories of fit, mild, moderate and severe frailty were defined using population quartiles. Outcomes: outcomes were 1-, 3- and 5-year mortality, hospitalisation and nursing home admission. Statistical analysis: hazard ratios (HRs) were estimated using bivariate and multivariate Cox regression analyses. Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was assessed using pseudo-R2 estimates. Results: we include data from a total of 931,541 patients. The eFI incorporates 36 deficits constructed using 2,171 CTV3 codes. One-year adjusted HR for mortality was 1.92 (95% CI 1.81–2.04) for mild frailty, 3.10 (95% CI 2.91–3.31) for moderate frailty and 4.52 (95% CI 4.16–4.91) for severe frailty. Corresponding estimates for hospitalisation were 1.93 (95% CI 1.86– 2.01), 3.04 (95% CI 2.90–3.19) and 4.73 (95% CI 4.43–5.06) and for nursing home admission were 1.89 (95% CI 1.63–2.15), 3.19 (95% CI 2.73–3.73) and 4.76 (95% CI 3.92–5.77), with good to moderate discrimination but low calibration estimates. Conclusions: the eFI uses routine data to identify older people with mild, moderate and severe frailty, with robust predictive validity for outcomes of mortality, hospitalisation and nursing home admission. Routine implementation of the eFI could enable delivery of evidence-based interventions to improve outcomes for this vulnerable group.

Yes / We compare the performance of logistic regression with several alternative machine learning methods to estimate the risk of death for patients following an emergency admission to hospital based on the patients’ first blood test results and physiological measurements using an external validation approach. We trained and tested each model using data from one hospital (n=24696) and compared the performance of these models in data from another hospital (n=13477). We used two performance measures – the calibration slope and area under the curve (AUC). The logistic model performed reasonably well – calibration slope 0.90, AUC 0.847 compared to the other machine learning methods. Given the complexity of choosing tuning parameters of these methods, the performance of logistic regression with transformations for in-hospital mortality prediction was competitive with the best performing alternative machine learning methods with no evidence of overfitting. / Health Foundation; National Institute for Health Research (NIHR) Yorkshire and Humberside Patient Safety Translational Research Centre (NIHR YHPSTRC)

Digital transformation is evolving, and it is driving at the helm of the digital evolution. The amount of information accessible to us has revolutionized the way we gather information. Mobile technology and the immediate and ubiquitous access to information has changed how we engage with services including healthcare. Digital technology and digital transformation have afforded people the ability to self-manage in different ways than face-to-face and paper-based methods through different technologies. This study focuses on exploring the use of the most commonly used digital health technologies in the healthcare sector and how it affects physicians’ daily routine practice. The study presents findings from a qualitative methodology involving semi-structured, personal interviews with physicians from Sweden and a physician from Spain. The interviews capture what physicians feel towards digital transformation, digital health technologies and how it affects their work. In a field where a lack of information regarding how physicians work is affected by digital health technologies, this study reveals a general aspect of how reality looks for physicians. A new way of conducting medicine and the changed role of the physician is presented along with the societal implications for physicians and the healthcare sector. The findings demonstrate that physicians’ role, work and the digital transformation in healthcare on a societal level are important in shaping the future for the healthcare industry and the role of the physician in this future. / Den digitala transformationen växer och den drivs vid rodret för den digitala utvecklingen. Mängden information som är tillgänglig för oss har revolutionerat hur vi samlar in information. Mobila tekniker och den omedelbara och allmänt förekommande tillgången till information har förändrat hur vi tillhandahåller oss tjänster inklusive inom vården. Digital teknik och digital transformation har gett människor möjlighet att kontrollera sig själv och sin egen hälsa på olika sätt än ansikte mot ansikte och pappersbaserade metoder genom olika tekniker. Denna studie fokuserar på att utforska användningen av de vanligaste digitala hälsoteknologierna inom hälso- och sjukvårdssektorn och hur det påverkar läkarnas dagliga rutin. Studien presenterar resultat från en kvalitativ metod som involverar semistrukturerade, personliga intervjuer med läkare från Sverige och en läkare från Spanien. Intervjuerna fångar vad läkare tycker om digital transformation, digital hälsoteknik och hur det påverkar deras arbete. I ett fält där brist på information om hur läkare arbetar påverkas av digital hälsoteknik avslöjar denna studie en allmän aspekt av hur verkligheten ser ut för läkare. Ett nytt sätt att bedriva medicin och läkarens förändrade roll presenteras tillsammans med de samhälleliga konsekvenserna för läkare och vårdsektorn. Resultaten visar att läkarnas roll, arbete och den digitala transformationen inom hälso- och sjukvården på samhällsnivå är viktiga för att utforma framtiden för vårdindustrin och läkarens roll i framtiden.

Information Systems (IS) innovations in healthcare sector are seen as panacea to control burgeoning demand on healthcare resources and lack of streamlining in care delivery. Two particular manifestations of such innovations are telehealth and electronic records in its two forms: the electronic medical records and the electronic health records. Deployment efforts concerning both of these IS-innovations have encountered a rough terrain and have been slow. Problems are also faced while evaluating the effectiveness of innovations on health and care delivery outcomes through strategies such as randomised controlled trials- particularly in case of telehealth. By taking these issues into account, this research investigates the issues that affect IS innovation deployment and its evaluation. The strategy adopted in this research was informed by recursive philosophy and theoretical perspectives within IS that strived to expound this recursive relationship. It involved conducting two longitudinal case studies that are qualitative in nature. The first study involved telehealth deployment and its evaluation in the UK, while the second case study involved the deployment of electronic medical/health records in the US. Data was collected through focus group discussions, interviews and online discussion threads; and was analysed thematically. The results of this research indicate that there are nine issues that arise and affect the deployment and evaluation of IS innovation in healthcare; and these are design, efficiency and effectiveness, optimality and equity, legitimacy, acceptance, demand and efficacy, expertise, new interaction patterns, and trust. These issues are attributes of relationships between the IS innovation, context of healthcare and the user. The significance of these attributes varies during the deployment and evaluation process, and due to iterative nature of IS innovation. This research further indicates that all the attributes have either direct or indirect impact on work practices of the user.

This thesis portrays a research study undertaken to explore the unknown concept of electronic interprofessional documentation. Academic literature largely centers on multidisciplinary electronic documentation yet clinicians provide care using an integrated interprofessional model. Current design of electronic health records (EHRs) continue to propagate a deluge of data resulting from disparate siloed documentation. End users report challenges with finding data. Additionally, care planning and decision making are delayed. To bridge the gap between electronic design and interprofessional delivery of care, more understanding of shared documentation is required. The provenance of the design of this study is based on the concept of common ground and the framework for complex diverse data. Common ground is a shared communication space within a team with a shared purpose (Cioffi, Wilkes, Cummings, Warne, & Harrison, 2010). The framework for complex diverse data posits that data must be linked to other interconnected data; linked data enables connection of diverse pieces and insight-sharing within a team. A descriptive qualitative study was designed to answer the research question: What are the common data elements between disciplines? A case scenario of a patient with a fractured hip was created; participants generated clinical notes based on the video and patient record. The clinical notes were coded and results indicated numerous diverse common data elements. These were analyzed and major findings such as categories appropriate for use by all disciplines on admission and design implications for care planning throughout an acute care stay were identified. Further, as disciplines and care team members do have different documentation patterns, it is suggested attendance to differences in the entry of data yet maintaining a common ground in the display of patient information is vital. Finally suggestions such as duplicate checking for documentation through a common care plan that tracks assessments and completed interventions alongside planned interventions are made. Creation of a standardized interprofessional terminology is key in building the road leading to interprofessional electronic documentation. / Graduate