The Impact of Digital Hospitals on Patient and Clinician Experience: Systematic Review and Qualitative Evidence Synthesis

BACKGROUND

The digital transformation of health care is advancing rapidly. A well-accepted framework for health care improvement is the Quadruple Aim: improved clinician experience, improved patient experience, improved population health, and reduced health care costs. Hospitals are attempting to improve care by using digital technologies, but the effectiveness of these technologies is often only measured against cost and quality indicators, and less is known about the clinician and patient experience.

OBJECTIVE

This study aims to conduct a systematic review and qualitative evidence synthesis to assess the clinician and patient experience of digital hospitals.

METHODS

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) guidelines were followed. The PubMed, Embase, Scopus, CINAHL, and PsycINFO databases were searched from January 2010 to June 2022. Studies that explored multidisciplinary clinician or adult inpatient experiences of digital hospitals (with a full electronic medical record) were included. Study quality was assessed using the Mixed Methods Appraisal Tool. Data synthesis was performed narratively for quantitative studies. Qualitative evidence synthesis was performed via (1) automated machine learning text analytics using Leximancer (Leximancer Pty Ltd) and (2) researcher-led inductive synthesis to generate themes.

RESULTS

A total of 61 studies (n=39, 64% quantitative; n=15, 25% qualitative; and n=7, 11% mixed methods) were included. Most studies (55/61, 90%) investigated clinician experiences, whereas few (10/61, 16%) investigated patient experiences. The study populations ranged from 8 to 3610 clinicians, 11 to 34,425 patients, and 5 to 2836 hospitals. Quantitative outcomes indicated that clinicians had a positive overall satisfaction (17/24, 71% of the studies) with digital hospitals, and most studies (11/19, 58%) reported a positive sentiment toward usability. Data accessibility was reported positively, whereas adaptation, clinician-patient interaction, and workload burnout were reported negatively. The effects of digital hospitals on patient safety and clinicians' ability to deliver patient care were mixed. The qualitative evidence synthesis of clinician experience studies (18/61, 30%) generated 7 themes: inefficient digital documentation, inconsistent data quality, disruptions to conventional health care relationships, acceptance, safety versus risk, reliance on hybrid (digital and paper) workflows, and patient data privacy. There was weak evidence of a positive association between digital hospitals and patient satisfaction scores.

CONCLUSIONS

Clinicians' experience of digital hospitals appears positive according to high-level indicators (eg, overall satisfaction and data accessibility), but the qualitative evidence synthesis revealed substantive tensions. There is insufficient evidence to draw a definitive conclusion on the patient experience within digital hospitals, but indications appear positive or agnostic. Future research must prioritize equitable investigation and definition of the digital clinician and patient experience to achieve the Quadruple Aim of health care.

Addressing complexity when developing an education program for the implementation of a stroke Electronic Medical Record (EMR) enhancement

BACKGROUND

Digital interventions in health services often fail due to an underappreciation of the complexity of the implementation. This study develops an approach to address complexity through an evidenced-based, theory-driven education and implementation program for an Electronic Medical Record (EMR) digital enhancement for acute stroke care.

METHODS

An action research approach was used to design, develop, and execute the education and implementation program over several phases, with iterative changes over time. The study involved collaboration with multiple statewide and local key stakeholders and was conducted across two tertiary teaching hospitals and a regional hospital in Australia.

RESULTS

Insights were gained over five phases. Phase 1 involved a review of evidence that supported blended learning strategies for the education and training of staff end-users. In Phase 2, contextual assessment was conducted via observation of study sites, providing awareness of local context variability and insight into key implementation considerations. The Non-adoption, Abandonment, Scale-Up, Spread and Sustainability (NASSS) framework assisted in Phase 3 to identify and manage the key domains of complexity. Phase 4 involved the design of the program which included group-based training and an e-learning package, endorsed and evaluated by key leaders. Throughout implementation in Phase 5, further barriers were identified, and iterative changes were tailored to each context.

CONCLUSIONS

The NASSS framework, combined with a multi-phased approach employing blended learning techniques, context evaluations, and iterative modifications, can serve as a model for generating theory-driven and evidence-based education strategies that adresss the complexity of the implementation process and context.

The typing is on the wall: Australia's healthcare future needs a digitally capable workforce

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 (1) 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.

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.

PREVIDE: A Qualitative Study to Develop a Decision-Making Framework (PREVention decIDE) for Noncommunicable Disease Prevention in Healthcare Organisations

Noncommunicable diseases (NCDs), including obesity, remain a significant global public health challenge. Prevention and public health innovation are needed to effectively address NCDs; however, understanding of how healthcare organisations make prevention decisions is immature. This study aimed to (1) explore how healthcare organisations make decisions for NCD prevention in Queensland, Australia (2) develop a contemporary decision-making framework to guide NCD prevention in healthcare organisations. Cross-sectional and qualitative design, comprising individual semi-structured interviews. Participants (n = 14) were recruited from two organisations: the state public health care system (CareQ) and health promotion/disease prevention agency (PrevQ). Participants held executive, director/manager or project/clinical lead roles. Data were analysed in two phases (1) automated content analysis using machine learning (Leximancer v4.5) (2) researcher-led interpretation of the text analytics. Final themes were consolidated into a proposed decision-making framework (PREVIDE, PREvention decIDE) for NCD prevention in healthcare organisations. Decision-making was driven by four themes: Data, Evidence, Ethics and Health, i.e., data, its quality and the story it tells; traditional and non-traditional sources of evidence; ethical grounding in fairness and equity; and long-term value generated across multiple determinants of health. The strength of evidence was directly proportional to confidence in the ethics of a decision. PREVIDE can be adapted by public health practitioners and policymakers to guide real-world policy, practice and investment decisions for obesity prevention and with further validation, other NCDs and priority settings (e.g., healthcare).

Reflections on statistical significance and practical importance in information systems research

This is an invited commentary on a paper by Sen et al. (forthcoming). I explain how their paper provides a useful reminder of the need to communicate the practical importance of statistical findings more effectively and more often. I also explain how their recommendations address just a small piece of the issue of practical importance. I describe how we must keep the whole issue in mind and I provide examples from my editorial role at MIS Quarterly.

The Effect of the Electronic Health Record on Interprofessional Practice: A Systematic Review

BACKGROUND

 Interprofessional practice and teamwork are critical components to patient care in a complex hospital environment. The implementation of electronic health records (EHRs) in the hospital environment has brought major change to clinical practice for clinicians which could impact interprofessional practice.

OBJECTIVES

 The aim of the study is to identify, describe, and evaluate studies on the effect of an EHR or modification/enhancement to an EHR on interprofessional practice in a hospital setting.

METHODS

 Seven databases were searched including PubMed, Scopus, Web of Science, CINAHL, Cochrane, EMBASE, and ACM Digital Library until November 2021. Subject heading and title/abstract searches were undertaken for three search concepts: "interprofessional" and "electronic health records" and "hospital, personnel." No date limits were applied. The search generated 5,400 publications and after duplicates were removed, 3,255 remained for title/abstract screening. Seventeen studies met the inclusion criteria and were included in this review. Risk of bias was quantified using the Quality Assessment Tool for Studies with Diverse Designs. A narrative synthesis of the findings was completed based on type of intervention and outcome measures which included: communication, coordination, collaboration, and teamwork.

RESULTS

 The majority of publications were observational studies and of low research quality. Most studies reported on outcomes of communication and coordination, with few studies investigating collaboration or teamwork. Studies investigating the EHR demonstrated mostly negative or no effects on interprofessional practice (23/31 outcomes; 74%) in comparison to studies investigating EHR enhancements which showed more positive results (20/28 outcomes; 71%). Common concepts identified throughout the studies demonstrated mixed results: sharing of information, visibility of information, closed-loop feedback, decision support, and workflow disruption.

CONCLUSION

 There were mixed effects of the EHR and EHR enhancements on all outcomes of interprofessional practice, however, EHR enhancements demonstrated more positive effects than the EHR alone. Few EHR studies investigated the effect on teamwork and collaboration.

Precision Public Health for Non-communicable Diseases: An Emerging Strategic Roadmap and Multinational Use Cases

Non-communicable diseases (NCDs) remain the largest global public health threat. The emerging field of precision public health (PPH) offers a transformative opportunity to capitalize on digital health data to create an agile, responsive and data-driven public health system to actively prevent NCDs. Using learnings from digital health, our aim is to propose a vision toward PPH for NCDs across three horizons of digital health transformation: Horizon 1—digital public health workflows; Horizon 2—population health data and analytics; Horizon 3—precision public health. This perspective provides a high-level strategic roadmap for public health practitioners and policymakers, health system stakeholders and researchers to achieving PPH for NCDs. Two multinational use cases are presented to contextualize our roadmap in pragmatic action: ESP and RiskScape (USA), a mature PPH platform for multiple NCDs, and PopHQ (Australia), a proof-of-concept population health informatics tool to monitor and prevent obesity. Our intent is to provide a strategic foundation to guide new health policy, investment and research in the rapidly emerging but nascent area of PPH to reduce the public health burden of NCDs.

Data sources for precision public health of obesity: a scoping review, evidence map and use case in Queensland, Australia

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-12939-x.

Applying and Extending the Theory of Effective Use in a Business Intelligence Context

The benefits that organizations accrue from information systems depend on how effectively the systems are used. Yet despite the importance of knowing what it takes to use information systems effectively, little theory on the topic exists. One recent and largely untested exception is the theory of effective use (TEU). We report on a contextualization, extension, and test of TEU in the business intelligence (BI) context, a context of considerable importance in which researchers have called for such studies. We used a mixed methods, three-phase approach involving instrument development (n = 218), a two-wave cross-sectional survey (n = 437), and three sets of follow-up interviews (n = 33). The paper contributes by (1) showing how TEU can be contextualized, operationalized, and extended, (2) demonstrating that many of TEU’s predictions hold in the BI context while also revealing ways to improve the theory, and (3) offering practical insights that executives can draw on to improve the use of BI in their organizations.

Digital health and precision prevention: shifting from disease-centred care to consumer-centred health

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, value-based model that will ensure healthcare sustainability in Australia and globally.

The Role of Electronic Medical Records in Reducing Unwarranted Clinical Variation in Acute Health Care: Systematic Review

BACKGROUND

The use of electronic medical records (EMRs)/electronic health records (EHRs) provides potential to reduce unwarranted clinical variation and thereby improve patient health care outcomes. Minimization of unwarranted clinical variation may raise and refine the standard of patient care provided and satisfy the quadruple aim of health care.

OBJECTIVE

A systematic review of the impact of EMRs and specific subcomponents (PowerPlans/SmartSets) on variation in clinical care processes in hospital settings was undertaken to summarize the existing literature on the effects of EMRs on clinical variation and patient outcomes.

METHODS

Articles from January 2000 to November 2020 were identified through a comprehensive search that examined EMRs/EHRs and clinical variation or PowerPlans/SmartSets. Thirty-six articles met the inclusion criteria. Articles were examined for evidence for EMR-induced changes in variation and effects on health care outcomes and mapped to the quadruple aim of health care.

RESULTS

Most of the studies reported positive effects of EMR-related interventions (30/36, 83%). All of the 36 included studies discussed clinical variation, but only half measured it (18/36, 50%). Those studies that measured variation generally examined how changes to variation affected individual patient care (11/36, 31%) or costs (9/36, 25%), while other outcomes (population health and clinician experience) were seldom studied. High-quality study designs were rare.

CONCLUSIONS

The literature provides some evidence that EMRs can help reduce unwarranted clinical variation and thereby improve health care outcomes. However, the evidence is surprisingly thin because of insufficient attention to the measurement of clinical variation, and to the chain of evidence from EMRs to variation in clinical practices to health care outcomes.

From benefits idealisation to value optimisation: application in the digital health context

Objective This study investigated evidence for the approach known as 'benefits management' (BM) used in many digital hospital initiatives. Methods A qualitative narrative overview was conducted on the BM literature and compared with a qualitative systematic overview of electronic medical record (EMR) implementation literature. Results Twenty-five articles on BM and 12 literature reviews on EMR implementation were examined. The BM approach does not have strong support in the literature and does not support all the needs of large EMR implementations. Conclusion The current BM approach provides an inadequate basis for managing and reporting on the outcomes that ensue from a digital hospital initiative. A shift is needed from benefits idealisation to value optimisation. What is known about the topic? Health services are under increasing pressure to demonstrate that the benefits anticipated from digital health investments have been realised. What does this paper add? This paper informs the practice of benefits governance in EMR implementations. The results reveal inadequacies in current BM models and practice that are currently enshrined in policy despite a lack of evidence. What are the implications for practitioners? Health service leaders must be willing to question the governance of benefits from health service transformations using more evidence-based approaches to increase the value obtained from investments in digital transformation.

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.

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.

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.

Patient Portals Facilitating Engagement With Inpatient Electronic Medical Records: A Systematic Review

Background

Engaging patients in the delivery of health care has the potential to improve health outcomes and patient satisfaction. Patient portals may enhance patient engagement by enabling patients to access their electronic medical records (EMRs) and facilitating secure patient-provider communication.

Objective

The aim of this study was to review literature describing patient portals tethered to an EMR in inpatient settings, their role in patient engagement, and their impact on health care delivery in order to identify factors and best practices for successful implementation of this technology and areas that require further research.

Methods

A systematic search for articles in the PubMed, CINAHL, and Embase databases was conducted using keywords associated with patient engagement, electronic health records, and patient portals and their respective subject headings in each database. Articles for inclusion were evaluated for quality using A Measurement Tool to Assess Systematic Reviews (AMSTAR) for systematic review articles and the Quality Assessment Tool for Studies with Diverse Designs for empirical studies. Included studies were categorized by their focus on input factors (eg, portal design), process factors (eg, portal use), and output factors (eg, benefits) and by the valence of their findings regarding patient portals (ie, positive, negative, or mixed).

Results

The systematic search identified 58 articles for inclusion. The inputs category was addressed by 40 articles, while the processes and outputs categories were addressed by 36 and 46 articles, respectively: 47 articles addressed multiple themes across the three categories, and 11 addressed only a single theme. Nineteen articles had high- to very high-quality, 21 had medium quality, and 18 had low- to very low-quality. Findings in the inputs category showed wide-ranging portal designs; patients’ privacy concerns and lack of encouragement from providers were among portal adoption barriers while information access and patient-provider communication were among facilitators. Several methods were used to train portal users with varying success. In the processes category, sociodemographic characteristics and medical conditions of patients were predictors of portal use; some patients wanted unlimited access to their EMRs, personalized health education, and nonclinical information; and patients were keen to use portals for communicating with their health care teams. In the outputs category, some but not all studies found patient portals improved patient engagement; patients perceived some portal functions as inadequate but others as useful; patients and staff thought portals may improve patient care but could cause anxiety in some patients; and portals improved patient safety, adherence to medications, and patient-provider communication but had no impact on objective health outcomes.

Conclusions

While the evidence is currently immature, patient portals have demonstrated benefit by enabling the discovery of medical errors, improving adherence to medications, and providing patient-provider communication, etc. High-quality studies are needed to fully understand, improve, and evaluate their impact.

The Philosopher's Corner: Questioning Assumptions in the Information Systems Discipline

A healthy characteristic of any research field is a willingness to question its own assumptions. In this essay, I discuss Treiblmaier's proposal to question the epistemological and methodological assumptions of the Information Systems field. Treiblmaier's proposal is thoughtful and provocative and reflects his deep knowledge of the topic and his strong desire for an alternative epistemological and methodological future for our field. Drawing on Feyerabend, Treiblmaier recommends that IS researchers adopt epistemological anarchism, methodological anarchism, and "anything goes" as a guiding principle. I argue against all of these viewpoints. I argue that epistemological anarchism will not foster research progress, methodological anarchism will not lead to major new insights, and "anything goes" as a guiding principle will not benefit the field. Despite disagreeing with Treiblmaier's main recommendations, I highlight several points that I agree are important for the field to address.

Uniting emergency and inpatient clinicians across the ED-inpatient interface: The last frontier?

Unwell patients in the ED requiring inpatient admission must negotiate the interface between the ED and inpatient wards. Despite its importance and scale, this ED-inpatient interface (EDii) is poorly characterised. The aim of this paper is to clearly define the EDii and to describe its importance to (i) the patient: delays to admission and errors in communication across the EDii can increase adverse outcomes; (ii) the hospital: poor EDii function reduces hospital efficiency and effectiveness; and (iii) the healthcare system: half of all hospital inpatient admissions occur via the EDii and so EDii affects system-wide performance. The EDii can be defined as the dynamic, transitional phase of patient care in which responsibility for, and delivery of care, is shared between ED and inpatient hospital services. The EDii is characterised by a complex interplay of patient, hospital and system factors. A clear definition of the EDii and an understanding of its importance will assist future research and interventions to improve patient outcomes.

Individual differences and usage behavior

A critical assumption of the Technology Acceptance Model (TAM) is that its belief constructs - perceived ease of use (PEOU) and perceived usefulness (PU) - fully mediate the influence of external variables on IT usage behavior. If this assumption is true, researchers can effectively "assume away" the effects of broad categories of external variables, those relating to the specific task, the technology, and user differences. One recent study did indeed find that belief constructs fully mediated individual differences, and its authors suggest that further studies with similar results could pave the way for simpler acceptance models that ignore such differences. To test the validity of these authors' results, we conducted a similar study to determine the effect of staff seniority, age, and education level on usage behavior. Our study involved 106 professional and administrative staff in the IT division of a large manufacturing company who voluntarily use email and word processing. We found that these individual user differences have significant direct effects on both the frequency and volume of usage. These effects are beyond the indirect effects as mediated through the TAM belief constructs. Thus, rather than corroborating the recent study, our findings underscore the importance of users' individual differences and suggest that TAM's belief constructs are accurate but incomplete predictors of usage behavior.