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Background: Queensland, Australia has been successful in containing the COVID-19 pandemic. Underpinning that response has been a highly effective virus containment strategy which relies on identification, isolation, and contact tracing of cases. The dramatic emergence of the COVID-19 pandemic rendered traditional paper-based systems for managing contact tracing no longer fit for purpose. A rapid digital transformation of the public health contact tracing system occurred to support this effort., Objectives: The objectives of the digital transformation were to shift legacy systems (paper or standalone electronic systems) to a digitally enabled public health system, where data are centered around the consumer rather than isolated databases. The objective of this paper is to outline this case study and detail the lessons learnt to inform and give confidence to others contemplating digitization of public health systems in response to the COVID-19 pandemic., Methods: This case study is set in Queensland, Australia. Universal health care is available. A multidisciplinary team was established consisting of clinical informaticians, developers, data strategists, and health information managers. An agile "pair-programming" approach was undertaken to application development and extensive change efforts were made to maximize adoption of the new digital workflows. Data governance and flows were changed to support rapid management of the pandemic., Results: The digital coronavirus application (DCOVA) is a web-based application that securely captures information about people required to quarantine and creates a multiagency secure database to support a successful containment strategy., Conclusion: Most of the literature surrounding digital transformation allows time for significant consultation, which was simply not possible under crisis conditions. Our observation is that staff was willing to adopt new digital systems because the reason for change (the COVID-19 pandemic) was clearly pressing. This case study highlights just how critical a unified purpose, is to successful, rapid digital transformation., Competing Interests: None declared., (Thieme. All rights reserved.)

The Australian Commission for Safety and Quality in Health Care has created the National Safety and Quality Health Service standards that all hospitals must address in order to remain accredited. This case study details the first known digitisation of the 10 national quality and safety standards mandated in a quaternary integrated digital hospital. A team of clinical informaticians, information technology experts and clinicians was assembled. Data were chosen and the data were then extracted and validated and presented (often in near real time) in an easily consumable dashboard format with appropriate governance to allow clinicians and executives to monitor the quality and safety standards across the hospital. All 10 standards were defined and extracted contemporaneously from the digital hospital for every patient, every time. This is in stark contrast with traditional retrospective point prevalence surveys. This case study details the first known fully digital accreditation in a sophisticated integrated digital hospital. Digitisation of hospital quality and safety to produce real-time data is the future of clinical redesign to improve patient care.

Objective The aim of the present study was to determine the effects of hospital-based eHealth technologies on quality, safety and efficiency of care and clinical outcomes. Methods Systematic reviews and reviews of systematic reviews of eHealth technologies published in PubMed/Medline/Cochrane Library between January 2010 and October 2015 were evaluated. Reviews of implementation issues, non-hospital settings or remote care or patient-focused technologies were excluded from analysis. Methodological quality was assessed using a validated appraisal tool. Outcome measures were benefits and harms relating to electronic medical records (EMRs), computerised physician order entry (CPOE), electronic prescribing (ePrescribing) and computerised decision support systems (CDSS). Results are presented as a narrative overview given marked study heterogeneity. Results Nineteen systematic reviews and two reviews of systematic reviews were included from 1197 abstracts, nine rated as high quality. For EMR functions, there was moderate-quality evidence of reduced hospitalisations and length of stay and low-quality evidence of improved organisational efficiency, greater accuracy of information and reduced documentation and process turnaround times. For CPOE functions, there was moderate-quality evidence of reductions in turnaround times and resource utilisation. For ePrescribing, there was moderate-quality evidence of substantially fewer medications errors and adverse drug events, greater guideline adherence, improved disease control and decreased dispensing turnaround times. For CDSS, there was moderate-quality evidence of increased use of preventive care and drug interaction reminders and alerts, increased use of diagnostic aids, more appropriate test ordering with fewer tests per patient, greater guideline adherence, improved processes of care and less disease morbidity. There was conflicting evidence regarding effects on in-patient mortality and overall costs. Reported harms were alert fatigue, increased technology interaction time, creation of disruptive workarounds and new prescribing errors. Conclusion eHealth technologies in hospital settings appear to improve efficiency and appropriateness of care, prescribing safety and disease control. Effects on mortality, readmissions, total costs and patient and provider experience remain uncertain. What is known about the topic? Healthcare systems internationally are undertaking large-scale digitisation programs with hospitals being a major focus. Although predictive analyses suggest that eHealth technologies have the potential to markedly transform health care delivery, contemporary peer-reviewed research evidence detailing their benefits and harms is limited. What does this paper add? This narrative overview of 19 systematic reviews and two reviews of systematic reviews published over the past 5 years provides a summary of cumulative evidence of clinical and organisational effects of contemporary eHealth technologies in hospital practice. EMRs have the potential to increase accuracy and completeness of clinical information, reduce documentation time and enhance information transfer and organisational efficiency. CPOE appears to improve laboratory turnaround times and decrease resource utilisation. ePrescribing significantly reduces medication errors and adverse drug events. CDSS, especially those used at the point of care and integrated into workflows, attract the strongest evidence for substantially increasing clinician adherence to guidelines, appropriateness of disease and treatment monitoring and optimal medication use. Evidence of effects of eHealth technologies on discrete clinical outcomes, such as morbid events, mortality and readmissions, is currently limited and conflicting. What are the implications for practitioners? eHealth technologies confer benefits in improving quality and safety of care with little evidence of major hazards. Whether EMRs and CPOE can affect clinical outcomes or overall costs in the absence of auxiliary support systems, such as ePrescribing and CDSS, remains unclear. eHealth technologies are evolving rapidly and the evidence base used to inform clinician and managerial decisions to invest in these technologies must be updated continually. More rigorous field research using appropriate evaluation methods is needed to better define real-world benefits and harms. Customisation of eHealth applications to the context of patient-centred care and management of highly complex patients with multimorbidity will be an ongoing challenge.

Background: Digital health offers unprecedented opportunities to enhance health service delivery across vast geographic regions. However, these benefits can only be realized with effective capabilities and clinical leadership of the rural healthcare workforce. Little is known about how rural healthcare workers acquire skills in digital health, how digital health education or training programs are evaluated and the barriers and enablers for high quality digital health education and training. Objective: To conduct a scoping review to identify and synthesize existing evidence on digital health education and training of the rural healthcare workforce. Inclusion criteria: Sources that reported digital health and education or training in the healthcare workforce in any healthcare setting outside metropolitan areas. Methods: We searched for published and unpublished studies written in English in the last decade to August 2023. The databases searched were PubMed, Embase, Scopus, CINAHL and Education Resources Information Centre. We also searched the grey literature (Google, Google Scholar), conducted citation searching and stakeholder engagement. The JBI Scoping Review methodology and PRISMA guidelines for scoping reviews were used. Results: Five articles met the eligibility criteria. Two case studies, one feasibility study, one micro-credential and one fellowship were described. The mode of delivery was commonly modular online learning. Only one article described an evaluation, and findings showed the train-the-trainer model was technically and pedagogically feasible and well received. A limited number of barriers and enablers for high quality education or training of the rural healthcare workforce were reported across macro (legal, regulatory, economic), meso (local health service and community) and micro (day-to-day practice) levels. Conclusions: Upskilling rural healthcare workers in digital health appears rare. Current best practice points to flexible, blended training programs that are suitably embedded with interdisciplinary and collaborative rural healthcare improvement initiatives. Future work to advance the field could define rural health informatician career pathways, address concurrent rural workforce issues, and conduct training implementation evaluations. Review registration number: Open Science Framework: https://doi.org/10.17605/OSF.IO/N2RMX. [ABSTRACT FROM AUTHOR]

Digital health technologies are a proposed solution to improve healthcare delivery and reduce pressures on the healthcare system, but these technologies are new to much of the health workforce. This perspective paper highlights lessons learned from the global experience of rapid digital transformation of health workforces, including fostering a culture of learning, ensuring accreditation and recognition, and adopting a transdisciplinary approach. Evidence-based actions are proposed to address recommendations to (i) ensure foundational workforce digital health capability and (2) build specialist digital health career pathways. Australia must take a national approach and strategically leverage strong collaborations across sectors including healthcare, education and government to ensure a consistent, regulated and sustainable digital workforce capability. [ABSTRACT FROM AUTHOR]

Digital disruption and transformation of health care is occurring rapidly. Concurrently, a global syndemic of preventable chronic disease is crippling healthcare systems and accelerating the effect of the COVID-19 pandemic. Healthcare investment is paradoxical; it prioritises disease treatment over prevention. This is an inefficient break--fix model versus a person-centred predict--prevent model. It is easy to reward and invest in acute health systems because activity is easily measured and therefore funded. Social, environmental and behavioural health determinants explain,70% of health variance; yet, we cannot measure these community data contemporaneously or at population scale. The dawn of digital health and the digital citizen can initiate a precision prevention era, where consumer-centred, real-time data enables a new ability to count and fund population health, making disease prevention 'matter'. Then, precision decision making, intervention and policy to target preventable chronic disease (e.g. obesity) can be realised. We argue for, identify barriers to, and propose three horizons for digital health transformation of population health towards precision prevention of chronic disease, demonstrating childhood obesity as a use case. Clinicians, researchers and policymakers can commence strategic planning and investment for precision prevention of chronic disease to advance a mature, valuebased model that will ensure healthcare sustainability in Australia and globally. [ABSTRACT FROM AUTHOR]

Successful implementation of digital health programs is imperative as it is becoming increasingly clear that digital solutions will underpin modern health care. These projects are often supported by large budgets and if not implemented successfully, the quality, safety, and efficiency of patient care may be compromised. Failure rates for the implementation of large, complex healthcare software platforms in digital health programs have been persistently high. Although several factors may contribute to the failure of such projects, the majority have been reported to fail largely due to poor project management. Nevertheless, little is known about the optimal project management approaches for digital health projects, with many health services reliant on external advisory companies and contractors for advice. Although publication bias makes it difficult to reliably study and understand global trends for the failure of digital health projects, examination of media reports and published literature indicates that this is a global phenomenon affecting digital health projects in North America, Europe and Australasia. In this article, our aim is to examine the literature for evidence underpinning current project management approaches used when implementing commercial, off-the-shelf healthcare information technology solutions, including complex healthcare software in large digital health programs in hospitals or across health systems, and evaluate the suitability of current project management approaches to deliver these projects. This starts to build an important evidence base for hospitals and health services considering digital transformation projects. [ABSTRACT FROM AUTHOR]

Objective: This study aims to assist hospitals contemplating digital transformation by assessing the reported qualitative effects of rapidly implementing an integrated eHealth system in a large Australian hospital and determining whether existing literature offers a reliable framework to assess the effects of digitisation. Methods: A qualitative, single-site case study was performed using semistructured interviews supplemented by focus groups, observations and documentation. In all, 92 individuals across medical, nursing, allied health, administrative and executive roles provided insights into the eHealth system, which consisted of an electronic medical record, computerised decision support, computerised physician order entry, ePrescribing systems and wireless device integration. These results were compared against a known framework of the effects of hospital digitisation. Results: Diverse, mostly positive, effects were reported, largely consistent with existing literature. Several new effects not reported in literature were reported, namely: (1) improvements in accountability for care, individual career development and time management; (2) mixed findings for the availability of real-time data; and (3) positive findings for the secondary use of data. Conclusions: The overall positive perceptions of the effects of digitisation should give confidence to health services contemplating rapid digital transformation. Although existing literature provides a reliable framework for impact assessment, new effects are still emerging, and research and practice need to shift towards understanding how clinicians and hospitals can maximise the benefits of digital transformation. What is known about the topic?: Hospitals outside the US are increasingly becoming engaged in eHealth transformations. Yet, the reported effects of these technologies are diverse and mixed with qualitative effects rarely reported. What does this paper add?: This study provides a qualitative assessment of the effects of an eHealth transformation at a large Australian tertiary hospital. The results provide renewed confidence in the literature because the findings are largely consistent with expectations from prior systematic reviews of impacts. The qualitative approach followed also resulted in the identification of new effects, which included improvements in accountability, time management and individual development, as well as mixed results for real-time data. In addition, substantial improvements in patient outcomes and clinician productivity were reported from the secondary use of data within the eHealth systems. What are the implications for practitioners?: The overall positive findings in this large case study should give confidence to other health services contemplating rapid digital transformation. To achieve substantial benefits, hospitals need to understand how they can best leverage the data within these systems to improve the quality and efficiency of patient care. As such, both research and practice need to shift towards understanding how these systems can be used more effectively. [ABSTRACT FROM AUTHOR]

Objective: In an era of rapid digitisation of Australian hospitals, practical guidance is needed in how to successfully implement electronic medical records (EMRs) as both a technical innovation and a major transformative change in clinical care. The aim of the present study was to develop a checklist that clearly and comprehensively defines the steps that best prepare hospitals for EMR implementation and digital transformation. Methods: The checklist was developed using a formal methodological framework comprised of: literature reviews of relevant issues; an interactive workshop involving a multidisciplinary group of digital leads from Queensland hospitals; a draft document based on literature and workshop proceedings; and a review and feedback from senior clinical leads. Results: The final checklist comprised 19 questions, 13 related to EMR implementation and six to digital transformation. Questions related to the former included organisational considerations (leadership, governance, change leaders, implementation plan), technical considerations (vendor choice, information technology and project management teams, system and hardware alignment with clinician workflows, interoperability with legacy systems) and training (user training, post-go-live contingency plans, roll-out sequence, staff support at point of care). Questions related to digital transformation included cultural considerations (clinically focused vision statement and communication strategy, readiness for change surveys), management of digital disruption syndromes and plans for further improvement in patient care (post-go-live optimisation of digital system, quality and benefit evaluation, ongoing digital innovation). Conclusion: This evidence-based, field-tested checklist provides guidance to hospitals planning EMR implementation and separates readiness for EMR from readiness for digital transformation. What is known about the topic?: Many hospitals throughout Australia have implemented, or are planning to implement, hospital wide electronic medical records (EMRs) with varying degrees of functionality. Few hospitals have implemented a complete end-to-end digital system with the ability to bring about major transformation in clinical care. Although the many challenges in implementing EMRs have been well documented, they have not been incorporated into an evidence-based, field-tested checklist that can practically assist hospitals in preparing for EMR implementation as both a technical innovation and a vehicle for major digital transformation of care. What does this paper add?: This paper outlines a 19-question checklist that was developed using a formal methodological framework comprising literature review of relevant issues, proceedings from an interactive workshop involving a multidisciplinary group of digital leads from hospitals throughout Queensland, including three hospitals undertaking EMR implementation and one hospital with complete end-to-end EMR, and review of a draft checklist by senior clinical leads within a statewide digital healthcare improvement network. The checklist distinguishes between issues pertaining to EMR as a technical innovation and EMR as a vehicle for digital transformation of patient care. What are the implications for practitioners?: Successful implementation of a hospital-wide EMR requires senior managers, clinical leads, information technology teams and project management teams to fully address key operational and strategic issues. Using an issues checklist may help prevent any one issue being inadvertently overlooked or underemphasised in the planning and implementation stages, and ensure the EMR is fully adopted and optimally used by clinician users in an ongoing digital transformation of care. [ABSTRACT FROM AUTHOR]

Objective: The transition to digital hospitals is fast-moving. Although US hospitals are further ahead than some others in implementing eHealth technologies, their early experiences are not necessarily generalisable to contemporary healthcare because both the systems and technologies have been rapidly evolving. It is important to provide up-to-date assessments of the evidence available. The aim of this paper is to provide an assessment of the current literature on the effects to be expected from hospital implementations of eHealth technologies. Methods: A narrative review was conducted of systematic reviews investigating the effects of eHealth technologies (clinical decision support systems (CDSS), computerised provider order entry (CPOE), ePrescribing, electronic medical records (EMRs)) published between November 2015 and August 2017 and compared the findings with those of a previous narrative review that examined studies published between January 2010 and October 2015. The same search strategy and selection criteria were used in both studies. Results: Of the seven relevant articles, three (42.9%) examined the effects of more than one eHealth system: only two (28.6%) studies were high quality, three (42.9%) were of intermediate quality and two (28.6%) were of low quality. We identified that EMRs are largely associated with conflicting findings. Previous reviews suggested that CPOE are associated with significant positive results of cost savings, organisational efficiency gains, less resource utilisation and improved individual performance. However, these effects were not investigated in the more recent reviews, and only mixed findings for communication between clinicians were reported. Similarly, for ePrescribing, later reviews reported limited evidence of benefits, although when coupled with CDSS, more consistent positive findings were reported. Conclusion: This overview can help inform other hospitals in Australia and elsewhere of the likely effects resulting from eHealth technologies. The findings suggest that the effects of these systems are largely mixed, but there are positive findings, which encourage ongoing digital transformation of hospital practice. What is known about the topic?: Governments are increasingly devoting substantial resources towards implementing eHealth technologies in hospital practice with the goals of improving clinical and financial outcomes. Yet, these outcomes are yet to be fully realised in practice and conflicting findings are often reported in the literature. What does this paper add?: This paper extends a previous narrative review of systematic reviews and categorises the effects of eHealth technologies into a typology of outcomes to enable overall findings to be reported and comparisons to be made. In doings so, we synthesise 7 years of eHealth effects. Mixed results are largely reported for EMRs, with many benefits being compromised by practices stemming from resistance to EMRs. Limited evidence of effectiveness exists for CPOE and ePrescribing. CDSS are associated with the most consistent positive findings for clinician- and hospital-level effects. We observed renewed interest in the literature for the effect of eHealth technologies on communication both between clinicians and with patients. Other new insights have emerged relating to effects on clinical judgement, changing practice and staff retention. What are the implications for practitioners?: eHealth technologies have the potential to positively affect clinical and financial outcomes. However, these benefits are not guaranteed, and mixed results are often reported. This highlights the need for hospitals and decision makers to clearly identify and act on the drivers of successful implementations if eHealth technologies are to facilitate the creation of new, more effective models of patient care in an increasingly complex healthcare environment. [ABSTRACT FROM AUTHOR]

Background: Machine learning (ML) is a subset of Artificial Intelligence (AI) that is used to predict and potentially prevent adverse patient outcomes. There is increasing interest in the application of these models in digital hospitals to improve clinical decision-making and chronic disease management, particularly for patients with diabetes. The potential of ML models using electronic medical records (EMR) to improve the clinical care of hospitalised patients with diabetes is currently unknown.Objective: The aim was to systematically identify and critically review the published literature examining the development and validation of ML models using EMR data for improving the care of hospitalised adult patients with diabetes.Methods: The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines were followed. Four databases were searched (Embase, PubMed, IEEE and Web of Science) for studies published between January 2010 to January 2022. The reference lists of the eligible articles were manually searched. Articles that examined adults and both developed and validated ML models using EMR data were included. Studies conducted in primary care and community care settings were excluded. Studies were independently screened and data was extracted using Covidence® systematic review software. For data extraction and critical appraisal, the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) was followed. Risk of bias was assessed using the Prediction model Risk Of Bias Assessment Tool (PROBAST). Quality of reporting was assessed by adherence to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guideline. The IJMEDI checklist was followed to assess quality of ML models and the reproducibility of their outcomes. The external validation methodology of the studies was appraised.Results: Of the 1317 studies screened, twelve met inclusion criteria. Eight studies developed ML models to predict disglycaemic episodes for hospitalized patients with diabetes, one study developed a ML model to predict total insulin dosage, two studies predicted risk of readmission, and one study improved the prediction of hospital readmission for inpatients with diabetes. All included studies were heterogeneous with regard to ML types, cohort, input predictors, sample size, performance and validation metrics and clinical outcomes. Two studies adhered to the TRIPOD guideline. The methodological reporting of all the studies was evaluated to be at high risk of bias. The quality of ML models in all studies was assessed as poor. Robust external validation was not performed on any of the studies. No models were implemented or evaluated in routine clinical care.Conclusions: This review identified a limited number of ML models which were developed to improve inpatient management of diabetes. No ML models were implemented in real hospital settings. Future research needs to enhance the development, reporting and validation steps to enable ML models for integration into routine clinical care. [ABSTRACT FROM AUTHOR]