Real-world data for precision public health of noncommunicable diseases: a scoping review.

BACKGROUND: Global public health action to address noncommunicable diseases (NCDs) requires new approaches. NCDs are primarily prevented and managed in the community where there is little investment in digital health systems and analytics; this has created a data chasm and relatively silent burden of disease. The nascent but rapidly emerging area of precision public health offers exciting new opportunities to transform our approach to NCD prevention. Precision public health uses routinely collected real-world data on determinants of health (social, environmental, behavioural, biomedical and commercial) to inform precision decision-making, interventions and policy based on social position, equity and disease risk, and continuously monitors outcomes - the right intervention for the right population at the right time. This scoping review aims to identify global exemplars of precision public health and the data sources and methods of their aggregation/application to NCD prevention. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) was followed. Six databases were systematically searched for articles published until February 2021. Articles were included if they described digital aggregation of real-world data and 'traditional' data for applied community, population or public health management of NCDs. Real-world data was defined as routinely collected (1) Clinical, Medication and Family History (2) Claims/Billing (3) Mobile Health (4) Environmental (5) Social media (6) Molecular profiling (7) Patient-centred (e.g., personal health record). Results were analysed descriptively and mapped according to the three horizons framework for digital health transformation. RESULTS: Six studies were included. Studies developed population health surveillance methods and tools using diverse real-world data (e.g., electronic health records and health insurance providers) and traditional data (e.g., Census and administrative databases) for precision surveillance of 28 NCDs. Population health analytics were applied consistently with descriptive, geospatial and temporal functions. Evidence of using surveillance tools to create precision public health models of care or improve policy and practice decisions was unclear. CONCLUSIONS: Applications of real-world data and designed data to address NCDs are emerging with greater precision. Digital transformation of the public health sector must be accelerated to create an efficient and sustainable predict-prevent healthcare system.

Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review.

BACKGROUND: Digital health in hospital settings is viewed as a panacea for achieving the "quadruple aim" of health care, yet the outcomes have been largely inconclusive. To optimize digital health outcomes, a strategic approach is necessary, requiring digital maturity assessments. However, current approaches to assessing digital maturity have been largely insufficient, with uncertainty surrounding the dimensions to assess. OBJECTIVE: The aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals. METHODS: A systematic literature review was conducted of peer-reviewed literature (published before December 2020) investigating maturity models used to assess the digital maturity of hospitals. A total of 29 relevant articles were retrieved, representing 27 distinct maturity models. The articles were inductively analyzed, and the maturity model dimensions were extracted and consolidated into a maturity model framework. RESULTS: The consolidated maturity model framework consisted of 7 dimensions: strategy; information technology capability; interoperability; governance and management; patient-centered care; people, skills, and behavior; and data analytics. These 7 dimensions can be evaluated based on 24 respective indicators. CONCLUSIONS: The maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement.

Implementing two nurse practitioner models of service at an Australian male prison: A quality assurance study.

AIMS AND OBJECTIVES: To examine the quality and safety of nurse practitioner services of two newly implemented nurse practitioner models of care at a correctional facility. BACKGROUND: Nurse practitioners could help to meet the physical and mental health needs of Australia's growing prison population; however, the nurse practitioner role has not previously been evaluated in this context. DESIGN: A quality assurance study conducted in an Australian prison where a primary health nurse practitioner and a mental health nurse practitioner were incorporated into an existing primary healthcare service. The study was guided by Donabedian's structure, processes and outcomes framework. METHODS: Routinely collected information included surveys of staff attitudes to the implementation of the nurse practitioner models (n = 21 staff), consultation records describing clinical processes and time use (n = 289 consultations), and a patient satisfaction survey (n = 29 patients). Data were analysed descriptively and compared to external benchmarks where available. RESULTS: Over the two-month period, the nurse practitioners provided 289 consultations to 208 prisoners. The presenting problems treated indicated that most referrals were appropriate. A significant proportion of consultations involved medication review and management. Both nurse practitioners spent more than half of their time on individual patient-related care. Overall, multidisciplinary team staff agreed that the nurse practitioner services were necessary, safe, met patient need and reduced treatment delays. CONCLUSIONS: Findings suggest that the implementation of nurse practitioners into Australian correctional facilities is acceptable and feasible and has the potential to improve prisoners' access to health services. Structural factors (e.g., room availability and limited access to prisoners) may have reduced the efficiency of the nurse practitioners' clinical processes and service implementation. RELEVANCE TO CLINICAL PRACTICE: Results suggest that nurse practitioner models can be successfully integrated into a prison setting and could provide a nursing career pathway.

Moving Faster than the COVID-19 Pandemic: The Rapid, Digital Transformation of a Public Health System.

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.

Managing the Digital Disruption Associated with COVID-19-Driven Rapid Digital Transformation in Brisbane, Australia.

BACKGROUND: The COVID-19 pandemic has forced rapid digital transformation of many health systems. These innovations are now entering the literature, but there is little focus on the resulting disruption. OBJECTIVE: We describe the implementation of digital innovations during the COVID-19 response of Australia's largest health service, Metro North (in Brisbane, Queensland), the challenges of the subsequent digital disruption, how these were managed, and lessons learned. METHODS: Prior to the COVID-19 pandemic, the Australian state of Queensland created the Queensland Digital Clinical Charter, which provides guidance for the development of digital health programs. The guidelines utilize three horizons: digitizing workflows, leveraging digital data to transform clinical care, and reimagining new and innovative models of care. The technical response to COVID-19 in Metro North is described across these horizons. The rapid digital response caused significant disruption to health care delivery; management of the disruption and the outcomes are detailed. This is a participatory action research project, with members of the research team assisting with leading the implementation project informing the case report content. RESULTS: Several digital innovations were introduced across Metro North during the COVID-19 response. This resulted in significant disruption creating digital hypervigilance, digital deceleration, data discordance, and postdigital "depression." Successful management of the digital disruption minimized the negative effects of rapid digital transformation, and contributed to the effective management of the pandemic in Queensland. CONCLUSION: The rapid digital transformation in Metro North during COVID-19 was successful in several aspects; however, ongoing challenges remain. These include the need to improve data sharing and increase interoperability. Importantly, the innovations need to be evaluated to ensure that Metro North can capitalize on these changes and incorporate them into long-term routine practice. Moving forward, it will be essential to manage not only the pandemic, but increasingly, the resultant digital disruption.

Psychosocial factors significantly predict driving self-regulation in Australian older adults.

AIMS: This study aimed to investigate: (i) whether attitudes and beliefs about driving predict older adults' driving self-regulation, and how much variance in self-regulation can be explained by these factors; and (ii) if driving confidence is controlled, whether attitudes and beliefs remain significant independent predictors of driving self-regulation. METHOD: The present study examined the psychosocial factors that underlie driving self-regulation in 277 older adults within Australia. Participants completed standardised questionnaires about their driving, attitudes, belief and use of driving self-regulation. RESULTS: Driving confidence, affective and instrumental attitude, and perceived behavioural control were all significant predictors of driving self-regulation. The combination of these factors accounted for 56% of the variance in driving self-regulation. CONCLUSION: Driving self-regulation is a complex behaviour influenced by a wide range of psychosocial factors. Improved understanding of these factors could inform strategies to improve older driver safety and influence the advice that people receive.

Toward the Multilevel Older Person's Transportation and Road Safety Model: A New Perspective on the Role of Demographic, Functional, and Psychosocial Factors.

OBJECTIVES: Self-regulation refers to the practice of using self-imposed restrictions to protect oneself from situations that are, or are perceived to be, unsafe. Within the driving context, self-regulation refers the compensatory practices that some older adults adopt to restrict their driving to situations in which they feel safe. However, the way in which demographic, functional, and psychosocial factors, and the interactions between these factors, influence older adults' driving self-regulation is not well understood. Improving this understanding could lead to new ways of considering the mobility concerns faced by older drivers. METHOD: A systematic review of the current literature was conducted to explore this issue. Twenty-nine empirical studies investigating the factors associated with older adults' self-regulatory driving behaviors were examined. RESULTS: The review findings were used to construct the Multilevel Older Persons Transportation and Road Safety (MOTRS) model. The MOTRS model proposes that individual and environmental factors such as age, gender, and the availability of alternative transportation predict older adults' practice of driving-related self-regulation. However, these variables influence self-regulation through psychosocial variables such as driving confidence, affective attitude, and instrumental attitude toward driving. DISCUSSIONS: The MOTRS model extends previous attempts to model older adults' driving by focusing on a novel target, driving self-regulation, and by including a wider range of predictors identified on the basis of the systematic literature review. This focus enables consideration of broader mobility issues and may inform new strategies to support the mobility of older adults.

The development, factor structure and psychometric properties of driving self-regulation scales for older adults: Has self-regulation evolved in the last 15 years?

The term driving self-regulation is typically used to describe the practice of drivers who avoid driving in situations that they regard as unsafe because of perceived physical impairment. Older adults report using this strategy to improve safety while retaining mobility. Self-regulation is typically assessed using the driving avoidance items from the driving habits questionnaire (DHQ) and the driver mobility questionnaire (DMQ-A). However, the psychometric properties of these measures are not well understood. Using data from 277 older drivers, exploratory factor analysis was used to test the homogeneity of three driving self-regulation scales: the DHQ, DMQ-A, and an extended DMQ-A. Good internal consistency for each of the scales was identified (all αs≥.9). A one factor solution was identified for two of the measures (DHQ, DMQ-A) and a two factor solution accounting for over 70% of the score variance was identified for the third measure. The two factors assessed situations that may be avoided while driving because of the "external" (e.g., weather-related) or "internal" (e.g., passenger-related) driving environments, respectively. The findings suggest that the interpretation of an overall summated scale score, or single-item interpretations, may not be appropriate. Instead, driving self-regulation may be a multifaceted construct comprised of distinct dimensions that have not been identified previously but can be reliably measured. These data have implications for our understanding of driving self-regulation by older adults and the way in which this behavior is measured.

The relationship between cognitive ability, insight and self-regulatory behaviors: findings from the older driver population.

Self-regulation is often promoted as a coping strategy that may allow older drivers to drive safely for longer. Self-regulation depends upon drivers making an accurate assessment of their own ability and having a willingness to practice self-regulatory behaviors to compensate for changes in ability. The current study explored the relationship between older drivers' cognitive ability, their driving confidence and their use of self-regulation. An additional study aim was to explore the relationship between these factors and older drivers' interest in driving programs. Seventy Australian drivers aged 65 years and over completed a questionnaire about their driving and a brief screening measure of cognitive ability (an untimed Clock Drawing Test). While all participants reported high levels of confidence regarding their driving ability, and agreed that they would continue driving in the foreseeable future, a notable proportion performed poorly on the Clock Drawing Test. Compared to older drivers who successfully completed the Clock Drawing Test, those who failed the cognitive test were significantly less likely to report driving self-regulation, and showed significantly less interest in being involved in driving programs. Older drivers with declining cognitive abilities may not be self-regulating their driving. This group also appears to be unlikely to self-refer to driving programs.