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Digital transformation in healthcare improves the safety of health systems. Within our health service, a new digital hospital has been established and two wards from a neighbouring paper-based hospital transitioned into the new digital hospital. This created an opportunity to evaluate the impact of complete digital transformation on medication safety. Here we discuss the impact of transition from a paper-based to digital hospital on voluntarily reported medication incidents and prescribing errors. This study utilises an interrupted time-series design and takes place across two wards as they transition from a paper to a digital hospital. Two data sources are used to assess impacts on medication incidents and prescribing errors: (1) voluntarily reported medication incidents and 2) a chart audit of medications prescribed on the study wards. The chart audit collects data on procedural, dosing and therapeutic prescribing errors. There are 588 errors extracted from incident reporting software during the study period. The average monthly number of errors reduces from 12.5 pre- to 7.5 post-transition (p < 0.001). In the chart audit, 5072 medication orders are reviewed pre-transition and 3699 reviewed post-transition. The rates of orders with one or more error reduces significantly after transition (52.8% pre- vs. 15.7% post-, p < 0.001). There are significant reductions in procedural (32.1% pre- vs. 1.3% post-, p < 0.001), and dosing errors (32.3% pre- vs. 14% post-, p < 0.001), but not therapeutic errors (0.6% pre- vs. 0.7% post-, p = 0.478). Transition to a digital hospital is associated with reductions in voluntarily reported medication incidents and prescribing errors. [ABSTRACT FROM AUTHOR]

Background: Global action to reduce obesity prevalence requires digital transformation of the public health sector to enable precision public health (PPH). Useable data for PPH of obesity is yet to be identified, collated and appraised and there is currently no accepted approach to creating this single source of truth. This scoping review aims to address this globally generic problem by using the State of Queensland (Australia) (population > 5 million) as a use case to determine (1) availability of primary data sources usable for PPH for obesity (2) quality of identified sources (3) general implications for public health policymakers. Methods: The Preferred Reporting Items for Systematic Review and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Unique search strategies were implemented for 'designed' (e.g. surveys) and 'organic' (e.g. electronic health records) data sources. Only primary sources of data (with stratification to Queensland) with evidence-based determinants of obesity were included. Primary data source type, availability, sample size, frequency of collection and coverage of determinants of obesity were extracted and curated into an evidence map. Data source quality was qualitatively assessed. Results: We identified 38 primary sources of preventive data for obesity: 33 designed and 5 organic. Most designed sources were survey (n 20) or administrative (n 10) sources and publicly available but generally were not contemporaneous (> 2 years old) and had small sample sizes (10-100 k) relative to organic sources (> 1 M). Organic sources were identified as the electronic medical record (ieMR), wearables, environmental (Google Maps, Crime Map) and billing/claims. Data on social, biomedical and behavioural determinants of obesity typically co-occurred across sources. Environmental and commercial data was sparse and interpreted as low quality. One organic source (ieMR) was highly contemporaneous (routinely updated), had a large sample size (5 M) and represented all determinants of obesity but is not currently used for public health decision-making in Queensland. Conclusions: This review provides a (1) comprehensive data map for PPH for obesity in Queensland and (2) globally translatable framework to identify, collate and appraise primary data sources to advance PPH for obesity and other noncommunicable diseases. Significant challenges must be addressed to achieve PPH, including: using designed and organic data harmoniously, digital infrastructure for high-quality organic data, and the ethical and social implications of using consumer-centred health data to improve public health. [ABSTRACT FROM AUTHOR]

Digital transformation of Australian hospitals is occurring rapidly. Although the clinical community has had limited ability to influence high-level decision making and investments into digital health technologies, as these technologies increasingly transform the way patients are cared for, the clinical community must influence the digital health agenda and be an integral part of the decision-making process. This case study details the process and lessons learnt during the development of the state-wide consensus statement detailing the clinical requirements for digital health initiatives to form the Queensland Digital Health Clinical Charter. To the best of our knowledge, Queensland is the first Australian jurisdiction to create a Digital Clinical Charter to be specifically referenced in the investment in and governance of digital health in hospitals. By developing this clinical charter for digital health, and in articulating the needs of clinicians, a clinical framework will be added to both the decision-making process around the investments in digital health and the definition and realisation of the expected benefits from these sizable investments. What is known about the topic?: Digital transformation of healthcare is occurring rapidly. The clinical community has had limited ability to influence high-level decision making and investments into these digital health technologies. Tension currently exists between the clinical community who must use the new digital technologies and the technical groups that govern the introduction of the new technologies. This tension can be manifest as clinicians refusing to adopt new systems, safety concerns and an inability to reach consensus on direction. There are few peer reviewed publications addressing this tension between the clinical community and technical providers. What does this paper add?: This paper is the first attempt to create a list of clinical requirements for digital transformation that crosses professional streams and is endorsed by the state-wide executive leadership team to inform the acquisition and governance of digital health technologies. What are the implications for practitioners?: Clinicians can feel excluded and marginalised during the decision-making process for new digital technologies, despite the fact that they are often using these technologies to deliver hands-on care to patients. This charter clearly articulates the requirements of clinicians for digital transformation and has been endorsed by the executive leadership team of Queensland Health. The charter adds a clinical framework to be referenced during the decision-making process around the investments in digital health, and the definition and realisation of the expected benefits from these sizable investments. As the digital landscape in public hospitals evolves, clinicians are becoming increasingly reliant upon digital technologies. It is critical that clinicians have a strong effect on technology acquisition and governance to maximise the quality and efficiency of the care they provide. [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]

Background: Health service providers must understand their digital health capability if they are to drive digital transformation in a strategic and informed manner. Little is known about the assessment and benchmarking of digital maturity or capability at scale across an entire jurisdiction. The public health care system across the state of Queensland, Australia has an ambitious 10-year digital transformation strategy., Objective: The aim of this research was to evaluate the digital health capability in Queensland to inform digital health strategy and investment., Methods: The Healthcare Information and Management Systems Society Digital Health Indicator (DHI) was used via a cross-sectional survey design to assess four core dimensions of digital health transformation: governance and workforce; interoperability; person-enabled health; and predictive analytics across an entire jurisdiction simultaneously. The DHI questionnaire was completed by each health care system ( n  = 16) within Queensland in February to July 2021. DHI is scored 0 to 400 and dimension score is 0 to 100., Results: The results reveal a variation in DHI scores reflecting the diverse stages of health care digitization across the state. The average DHI score across sites was 143 (range 78-193; SD35.3) which is similar to other systems in the Oceania region and global public systems but below the global private average. Governance and workforce was on average the highest scoring dimension (x̅= 54), followed by interoperability (x̅ = 46), person-enabled health (x̅ = 36), and predictive analytics (x̅ = 30)., Conclusion: The findings were incorporated into the new digital health strategy for the jurisdiction. As one of the largest single simultaneous assessments of digital health capability globally, the findings and lessons learnt offer insights for policy makers and organizational managers., Competing Interests: A.P. and L.J. are employees of HIMSS, the organization who developed the DHI. Remaining authors declare that they have no conflict of interest in the research., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Movement of emergency patients across the emergency department (ED)-inpatient ward interface influences compliance with National Emergency Access Targets (NEAT). Uncertainty exists as to how best measure patient flow, NEAT compliance and patient mortality across this interface., Objective: To compare the association of NEAT with new and traditional markers of patient flow across the ED-inpatient interface and to investigate new markers of mortality and NEAT compliance across this interface., Methods: Retrospective study of consecutive emergency admissions to a tertiary hospital (January 2012 to June 2014) using routinely collected hospital data. The practical access number for emergency (PANE) and inpatient cubicles in emergency (ICE) are new measures reflecting boarding of inpatients in ED; traditional markers were hospital bed occupancy and ED attendance numbers. The Hospital Standardised Mortality Ratio (HSMR) for patients admitted via ED (eHSMR) was correlated with inpatientNEAT compliance rates. Linear regression analyses assessed for statistically significant associations (expressed as Pearson R coefficient) between all measures and inpatient NEAT compliance rates., Results: PANE and ICE were inversely related to inpatient NEAT compliance rates (r = 0.698 and 0.734 respectively, P < 0.003 for both); no significant relation was seen with traditional patient flow markers. Inpatient NEAT compliance rates were inversely related to both eHSMR (r = 0.914, P = 0.0006) and all-patient HSMR (r = 0.943, P = 0.0001)., Conclusions: Traditional markers of patient flow do not correlate with inpatient NEAT compliance in contrast to two new markers of inpatient boarding in ED (PANE and ICE). Standardised mortality rates for both emergency and all patients show a strong inverse relation with inpatient NEAT compliance.

Introduction: Amiodarone is a widely used anti-arrhythmic drug. A common long-term complication is amiodarone-induced thyrotoxicosis (AIT). We examined retrospectively the efficacy of anti-thyroid drugs with or without prednisolone and the role of surgical thyroidectomy in the treatment of AIT in a single centre, in an iodine-replete region of Australia., Methods: A retrospective audit of patients with AIT was performed between 2002-2012 at this centre. Twenty-seven patients, mean age 60.9 ± 2.3 years were identified. Medical therapy (anti-thyroid drugs, prednisolone) was commenced according to the treating endocrinologist. The main outcomes were time to euthyroidism and number proceeding to thyroidectomy., Results: Of 11 patients commenced on anti-thyroid drugs alone, seven (64%) required the addition of prednisolone. Baseline free T4 was significantly higher in those ultimately treated with prednisolone (58.4 ± 6.3pmol/L) versus those not (31.7 ± 3.4pmol/L, P<0.05). Although similar results were seen with free T3, the difference was not significant (P=0.06). In patients with baseline free T4 <30pmol/L, 75% (3/4) achieved euthyroidism without prednisolone. Neither the use of prednisolone nor continuation of amiodarone significantly influenced time to euthyroidism. Eleven patients (41%) proceeded to surgical thyroidectomy, which was undertaken by an experienced surgical team without significant complications and no mortality., Conclusion: Patients with AIT generally required glucocorticoids. Mild disease (free T4 <30pmol/L) may be successfully treated with anti-thyroid drugs alone. Surgical thyroidectomy is a safe and effective treatment for those refractive to medical therapy., (Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.)