Virtual Toxicology Service decreases the average length of stay of poisoned patients and saves bed days.

OBJECTIVE: We aimed to assess the impact a Virtual Toxicology Service had on the ALOS of poisoned patients. METHODS: This single-centre before-after study compares the ALOS of poisoned patients (diagnosis-related group X62, poisoning/toxic effects of drugs and other substances) following the introduction of a Virtual Toxicology Service in 2020. RESULTS: The ALOS decreased from 0.89 days in the 2-year pre-intervention period to 0.62 days in the 3-year post-intervention period, with a potential bed saving of 703 days. CONCLUSION: The introduction of a Virtual Toxicology Service appeared to be associated with a decreased ALOS of poisoned patients.

Patient flow in emergency departments: a comprehensive umbrella review of solutions and challenges across the health system.

BACKGROUND: Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient flow. METHODS: An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classified findings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/throughput/output (I/T/O) model of ED patient flow and synthesised intervention outcomes based on the Quadruple Aim framework. RESULTS: The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient flow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignificant outcomes. The majority of interventions for enhancing ED patient flow were primarily related to the 'within-ED' phase of the patient journey. Fewer interventions were identified for the 'post-ED' phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the 'pre-ED' phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efficiency, and enhance staff satisfaction. CONCLUSIONS: This study found that there was a wide range of interventions used to address patient flow, but the effectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efficiency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the effectiveness of interventions outside the ED in improving ED patient flow. It is essential to develop interventions that relate to all three phases of patient flow: pre-ED, within-ED, and post-ED.

Modelling a two-stream emergency department segregation and admission system from COVID-19 early rapid antigen testing: A pilot study.

OBJECTIVE: Many factors influence patient flow through an ED, including streaming, treatment spaces and staff resources. This pilot study explored and compared real time patient flow using a single-stream system versus varying configurations of possible two-stream systems using computer simulation. METHODS: Simulation modelling was used to assess the delay in treatment of a rapid-antigen-tested-based, two-stream model for patient flow through ED during the peak phase of the COVID pandemic. RESULTS: Modelling two-stream configuration for all patients (minimum time to be seen for both COVID-positive and COVID-negative patients) showed that in the case study ED, a two-stream system and linked changes in bed configuration for managing the risks of infection can impact delays in treatment. CONCLUSIONS: Data-driven modelling within specific clinical settings can inform the (in)efficiency of patient flow processes and help clinicians and managers make evidence-based decisions about patient transition through EDs. This can assist with reconfiguration of ED patient streaming particularly during periods of unique need, such as the recent COVID-19 pandemic.

Forecasting emergency department waiting time using a state space representation.

The provision of waiting time information in emergency departments (ED) has become an increasingly popular practice due to its positive impact on patient experience and ED demand management. However, little scientific attention has been given to the quality and quantity of waiting time information presented to patients. To improve both aspects, we propose a set of state space models with flexible error structures to forecast ED waiting time for low acuity patients. Our approach utilizes a Bayesian framework to generate uncertainties associated with the forecasts. We find that the state-space models with flexible error structures significantly improve forecast accuracy of ED waiting time compared to the benchmark, which is the rolling average model. Specifically, incorporating time-varying and correlated error terms reduces the root mean squared errors of the benchmark by 10%. Furthermore, treating zero-recorded waiting times as unobserved values improves forecast performance. Our proposed model has the ability to provide patient-centric waiting time information. By offering more accurate and informative waiting time information, our model can help patients make better informed decisions and ultimately enhance their ED experience.

Introduction of QScript real-time prescription monitoring system was associated with a fall in pregabalin poisoning presentations to a clinical toxicology unit.

OBJECTIVE: To investigate the impact of QScript implementation on pregabalin-related poisoning presentations to the ED. METHODS: This is a retrospective review of pregabalin-related poisoning presentations to a tertiary Australian ED in the 4 years prior to, and 1 year following the introduction of QScript real-time prescription monitoring system. RESULTS: Pregabalin-related poisoning presentations fell by 28% from an average of 98 presentations annually over the 4 years prior to QScript implementation to 71 in 2022. The severity of poisonings was similar over the periods. CONCLUSIONS: The introduction of QScript was associated with a reduction in pregabalin-related poisoning presentations.

Defining emergency medicine.

The COVID-19 pandemic has led to the development of alternative means of accessing unplanned care in order to avoid unnecessary ED presentations and hospital admissions. We explore the definition of emergency medicine, which patients are better served by accessing unplanned hospital care via alternative pathways, and the concept of emergency care completion.

Effect of computed tomography scanner location on time-to-computed tomography in the emergency department: A before and after study.

OBJECTIVES: To compare time metrics associated with a temporary disruption to ED computed tomography (CT) scanner location from adjacent to the ED with direct access from resuscitation rooms, to a location remote to the ED. METHODS: A retrospective before and after study was conducted in a public metropolitan ED with over 66 000 presentations annually. Time-to-CT metrics, operational time metrics and ED length of stay were extracted and analysed from presentations between October 2020 and January 2021. RESULTS: There were 3031 CT scans during the study period. Overall, the disruption was associated with a significant 27-36 min delay (P < 0.01) in time-to-CT start; these delays were also observed in a subset of trauma patients. In a subset of presumed stroke patients, time-to-brain perfusion was significantly delayed by up to 10 min (P < 0.01). There was a 14% (P < 0.01) greater demand for operational services and a time imposition of up to 8 min (P < 0.01) to transport patients to or from CT scanning when the CT scanner was located away from the ED. ED length of stay was consistent at all time points. CONCLUSION: Although rapid, proximate access to CT scanning is often considered desirable in terms of the management of trauma and other time-critical emergencies, the wider time and resource implications demonstrated in this study suggest a potential broader benefit to co-located CT scanning in ED. Our experience could be considered in future re-design of EDs.

Predicting Patient Deterioration: A Review of Tools in the Digital Hospital Setting.

BACKGROUND: Early warning tools identify patients at risk of deterioration in hospitals. Electronic medical records in hospitals offer real-time data and the opportunity to automate early warning tools and provide real-time, dynamic risk estimates. OBJECTIVE: This review describes published studies on the development, validation, and implementation of tools for predicting patient deterioration in general wards in hospitals. METHODS: An electronic database search of peer reviewed journal papers from 2008-2020 identified studies reporting the use of tools and algorithms for predicting patient deterioration, defined by unplanned transfer to the intensive care unit, cardiac arrest, or death. Studies conducted solely in intensive care units, emergency departments, or single diagnosis patient groups were excluded. RESULTS: A total of 46 publications were eligible for inclusion. These publications were heterogeneous in design, setting, and outcome measures. Most studies were retrospective studies using cohort data to develop, validate, or statistically evaluate prediction tools. The tools consisted of early warning, screening, or scoring systems based on physiologic data, as well as more complex algorithms developed to better represent real-time data, deal with complexities of longitudinal data, and warn of deterioration risk earlier. Only a few studies detailed the results of the implementation of deterioration warning tools. CONCLUSIONS: Despite relative progress in the development of algorithms to predict patient deterioration, the literature has not shown that the deployment or implementation of such algorithms is reproducibly associated with improvements in patient outcomes. Further work is needed to realize the potential of automated predictions and update dynamic risk estimates as part of an operational early warning system for inpatient deterioration.

Predicting waiting time to treatment for emergency department patients.

BACKGROUND: The current systems of reporting waiting time to patients in public emergency departments (EDs) has largely relied on rolling average or median estimators which have limited accuracy. This study proposes to use machine learning (ML) algorithms that significantly improve waiting time forecasts. METHODS: By implementing ML algorithms and using a large set of queueing and service flow variables, we provide evidence of the improvement in waiting time predictions for low acuity ED patients assigned to the waiting room. In addition to the mean squared prediction error (MSPE) and mean absolute prediction error (MAPE), we advocate to use the percentage of underpredicted observations. The use of ML algorithms is motivated by their advantages in exploring data connections in flexible ways, identifying relevant predictors, and preventing overfitting of the data. We also use quantile regression to generate time forecasts which may better address the patient's asymmetric perception of underpredicted and overpredicted ED waiting times. RESULTS: Using queueing and service flow variables together with information on diurnal fluctuations, ML models outperform the best rolling average by over 20 % with respect to MSPE and quantile regression reduces the number of patients with large underpredicted waiting times by 42 %. CONCLUSION: We find robust evidence that the proposed estimators generate more accurate ED waiting time predictions than the rolling average. We also show that to increase the predictive accuracy further, a hospital ED may decide to provide predictions to patients registered only during the daytime when the ED operates at full capacity, thus translating to more predictive service rates and the demand for treatments.

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.

Emergency medicine's COVID future: Facing the triple challenge after flattening the curve.

After successfully avoiding the situations experienced by some countries, Australasian EDs now face a future in which the ongoing threat of COVID-19 is added to the traditional challenges in providing quality emergency care. The contribution of emergency medicine to the national containment strategy adds a new dimension to the demands placed on emergency medicine in Australia and similarly, to the elimination strategy employed in New Zealand. These demands will best be met by a considered, planned and resourced approach that will challenge traditional measures of 'ED efficiency'.

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.

Digital transformation of the emergency department-inpatient interface (EDii): integration for future innovation.

As the focus of clinicians and government shifts from speciality-based care to system-based key performance indicators such as the National Emergency Access Target (NEAT) or the 4-h rule, integration between emergency department (ED) and inpatient clinical workflows and information systems is becoming increasingly necessary. Such system measures drive the implementation of integrated electronic medical records (ieMR) to digitally integrate these workflows. The objective of this case study was to describe the impact of digital transformation of the ED-in-patient interface (EDii) of a large tertiary hospital on process measures and clinical outcomes for patients requiring emergency admission to hospital. Data were collected from routine clinical and administrative information systems to measure process and clinical outcome measures, including ED length of stay, compliance with the 4-h rule and in-patient mortality between 28 November 2014 and 28 February 2017. The 4-h rule compliance for all patients, as well as for the EDii group (admitted to hospital excluding short stay ward), declined after digitisation. There were 55 fewer deaths in the postintervention group (15% relative reduction; P = 0.02) and a 10% relative reduction in adjusted mortality as measured by the Hospital Standardised Mortality Ratio for emergency patients (eHSMR), which did not reach statistical significance. Digital deceleration in ED performance did occur with an ieMR rollout, but worsening of key patient outcomes was not observed.

Queensland Digital Health Clinical Charter: a clinical consensus statement on priorities for digital health in hospitals.

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.

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.

Going digital: a checklist in preparing for hospital-wide electronic medical record implementation and digital transformation.

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.

Digital transformation of hospital quality and safety: real-time data for real-time action.

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

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.