Impact of digital health on the quadruple aims of healthcare: A correlational and longitudinal study (Digimat Study).

BACKGROUND: Digital healthcare aims to deliver on the quadruple aim: enhance patient experiences, improve population health, reduce costs and improve provider experiences. Despite large investments, it is unclear how advancing digital health enables these healthcare aims. OBJECTIVE: Our objectives were to: 1) measure the correlation between digital capability and health system outcomes mapped to the quadruple aim, and 2) measure the longitudinal impact of electronic medical record implementations upon health system outcomes. MATERIALS AND METHODS: We undertook two studies: 1) Digital health correlational study investigating the association among healthcare system capability and healthcare aims, and 2) Digital hospital longitudinal study investigating outcomes pre and post electronic medical record implementation. RESULTS: Digital health capability was associated with lower staff turnover. Digitising healthcare services was associated with decreased medication errors, decreased nosocomial infections, increased hospital activity, and a transient increase in staff leave. DISCUSSION: These results suggest positive impacts on the population health and healthcare costs aim, minimal impacts on the provider experience aim and no observed impacts to the patient experience aim. CONCLUSION: These findings should provide confidence to healthcare decision-makers investing in digital health.

Perceived Impact of Digital Health Maturity on Patient Experience, Population Health, Health Care Costs, and Provider Experience: Mixed Methods Case Study.

BACKGROUND: Health care organizations understand the importance of new technology implementations; however, the best strategy for implementing successful digital transformations is often unclear. Digital health maturity assessments allow providers to understand the progress made toward technology-enhanced health service delivery. Existing models have been criticized for their lack of depth and breadth because of their technology focus and neglect of meaningful outcomes. OBJECTIVE: We aimed to examine the perceived impacts of digital health reported by health care staff employed in health care organizations across a spectrum of digital health maturity. METHODS: A mixed methods case study was conducted. The digital health maturity of public health care systems (n=16) in Queensland, Australia, was examined using the quantitative Digital Health Indicator (DHI) self-assessment survey. The lower and upper quartiles of DHI scores were calculated and used to stratify sites into 3 groups. Using qualitative methods, health care staff (n=154) participated in interviews and focus groups. Transcripts were analyzed assisted by automated text-mining software. Impacts were grouped according to the digital maturity of the health care worker's facility and mapped to the quadruple aims of health care: improved patient experience, improved population health, reduced health care cost, and enhanced provider experience. RESULTS: DHI scores ranged between 78 and 193 for the 16 health care systems. Health care systems in the high-maturity category (n=4, 25%) had a DHI score of ≥166.75 (the upper quartile); low-maturity sites (n=4, 25%) had a DHI score of ≤116.75 (the lower quartile); and intermediate-maturity sites (n=8, 50%) had a DHI score ranging from 116.75 to 166.75 (IQR). Overall, 18 perceived impacts were identified. Generally, a greater number of positive impacts were reported in health care systems of higher digital health maturity. For patient experiences, higher maturity was associated with maintaining a patient health record and tracking patient experience data, while telehealth enabled access and flexibility across all digital health maturity categories. For population health, patient journey tracking and clinical risk mitigation were reported as positive impacts at higher-maturity sites, and telehealth enabled health care access and efficiencies across all maturity categories. Limited interoperability and organizational factors (eg, strategy, policy, and vision) were universally negative impacts affecting health service delivery. For health care costs, the resource burden of ongoing investments in digital health and a sustainable skilled workforce was reported. For provider experiences, the negative impacts of poor usability and change fatigue were universal, while network and infrastructure issues were negative impacts at low-maturity sites. CONCLUSIONS: This is one of the first studies to show differences in the perceived impacts of digital maturity of health care systems at scale. Higher digital health maturity was associated with more positive reported impacts, most notably in achieving outcomes for the population health aim.

Digital Health Data Quality Issues: Systematic Review.

BACKGROUND: The promise of digital health is principally dependent on the ability to electronically capture data that can be analyzed to improve decision-making. However, the ability to effectively harness data has proven elusive, largely because of the quality of the data captured. Despite the importance of data quality (DQ), an agreed-upon DQ taxonomy evades literature. When consolidated frameworks are developed, the dimensions are often fragmented, without consideration of the interrelationships among the dimensions or their resultant impact. OBJECTIVE: The aim of this study was to develop a consolidated digital health DQ dimension and outcome (DQ-DO) framework to provide insights into 3 research questions: What are the dimensions of digital health DQ? How are the dimensions of digital health DQ related? and What are the impacts of digital health DQ? METHODS: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a developmental systematic literature review was conducted of peer-reviewed literature focusing on digital health DQ in predominately hospital settings. A total of 227 relevant articles were retrieved and inductively analyzed to identify digital health DQ dimensions and outcomes. The inductive analysis was performed through open coding, constant comparison, and card sorting with subject matter experts to identify digital health DQ dimensions and digital health DQ outcomes. Subsequently, a computer-assisted analysis was performed and verified by DQ experts to identify the interrelationships among the DQ dimensions and relationships between DQ dimensions and outcomes. The analysis resulted in the development of the DQ-DO framework. RESULTS: The digital health DQ-DO framework consists of 6 dimensions of DQ, namely accessibility, accuracy, completeness, consistency, contextual validity, and currency; interrelationships among the dimensions of digital health DQ, with consistency being the most influential dimension impacting all other digital health DQ dimensions; 5 digital health DQ outcomes, namely clinical, clinician, research-related, business process, and organizational outcomes; and relationships between the digital health DQ dimensions and DQ outcomes, with the consistency and accessibility dimensions impacting all DQ outcomes. CONCLUSIONS: The DQ-DO framework developed in this study demonstrates the complexity of digital health DQ and the necessity for reducing digital health DQ issues. The framework further provides health care executives with holistic insights into DQ issues and resultant outcomes, which can help them prioritize which DQ-related problems to tackle first.

Which one? A suggested approach for evaluating digital health maturity models.

Background: Digital health maturity models allow healthcare organizations to evaluate digital health capability and to develop roadmaps for improving patient care through technology. There are many models available commercially for healthcare providers to use to assess their digital health maturity. Currently, there are limited evidence-based methods to assess the quality, utility, and efficacy of maturity models to select the most appropriate model for the given context. Objective: To develop a framework to assess digital maturity models and facilitate recommendations for digital maturity model selection. Methods: A systematic, consultative, and iterative process was used. Literature analyses and a stakeholder needs analysis (n = 23) was conducted to develop content and design considerations. These considerations were incorporated into the initial version of the framework developed by researchers in a design workshop. External stakeholder review (n = 20) and improvements strengthened and finalized the framework. Results: The criteria of the framework include assessment of healthcare context, feasibility, integrity, completeness and actionability. Users can compare model performance in order to select the most appropriate model for their context. Conclusion: The framework provides healthcare stakeholders with a consistent and objective methodology to compare digital health maturity models, informing approaches to choosing a suitable model. This is a critical step as healthcare evolves towards a digital health system focused on improving the quality of care, reducing costs and improving the provider and consumer experience.

Evaluating Digital Health Capability at Scale Using the Digital Health Indicator.

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.

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.

Online health communities, contributions to caregivers and resilience of older adults.

The aim of this paper is twofold. Firstly, to investigate the potential benefits of online health communities (OHCs) for informal caregivers by conducting a systematic literature review. Secondly, to identify the relationship between the potential benefits of OHCs and resilience factors of older adults. Performing a thematic analysis, we identified the potential benefits of OHCs for informal caregivers of older adults, including two salient themes: (a) caregivers sharing and receiving social support and (b) self and moral empowerment of caregivers. Then, we uncovered how these potential benefits can support resilience of older adults. Our findings show that sharing and receiving of social support by informal caregivers, and self and moral empowerment of informal caregivers in OHCs, can support four resilience factors among older adults, including self-care, independence, altruism and external connections. This review enables a better understanding of OHCs and Gerontology, and our outcomes also challenge the way healthcare and aged-care service providers view caregivers and older adults. Furthermore, the identified gap and opportunities would provide avenues for further research in OHCs.

Surveying perceptions of the early impacts of an integrated electronic medical record across a hospital and healthcare service.

Objective This study provides insights into the reported early impacts of the digital transformation of a large Australian hospital and healthcare service (HHS) by surveying staff perceptions of an integrated electronic medical record (ieMR). Methods The information systems success model was used as a tool to evaluate perceptions of system quality, information quality, individual benefits and expected organisational benefits of the ieMR soon after its introduction at the HHS. A questionnaire was distributed to staff in all five hospitals in the HHS immediately after implementation. Overall staff perceptions were examined, in addition to how perceptions differed by site and profession. Results Overall, staff held mildly positive early perceptions of system quality, information quality, individual benefits and expected organisational benefits. These views were largely consistent across sites. In terms of professions, allied health held more positive perceptions, followed by administrative and nursing professionals. Medical professionals held negative perceptions, but were neutral regarding their future expectations. Conclusion On average, staff viewed the ieMR mildly positively immediately after implementation (despite significant changes to work practices), but differences exist across professional groups. What is known about the topic? Hospitals globally are in the midst of a digital transformation. Yet, reported impacts are mixed and there have been few studies of the effects of comprehensive electronic medical record (EMR) implementations. What does this paper add? This paper evaluates a comprehensive EMR immediately after go-live. We found positive early perceptions of system quality, information quality, individual benefits and expected organisational benefits. We also found that perceptions of medical professionals were largely negative, but they were neutral in terms of their future expectations. What are the implications for practitioners? Health services may be unsure of the effect of implementing a comprehensive EMR because of conflicting reports in the literature, some touting major benefits, others stressing major costs. Our results paint a middle-ground picture immediately after implementation. Staff perceptions are mildly positive on average, which is reassuring given the results were obtained during the early disruptive period after implementation.

Digitising an Australian university hospital: qualitative analysis of staff-reported impacts.

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.

Effects of eHealth on hospital practice: synthesis of the current literature.

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.