Push or pull? Digital notification platform implementation reduces dysglycaemia.

Pushing selected information to clinicians, as opposed to the traditional method of clinicians pulling information from an electronic medical record, has the potential to improve care. A digital notification platform was designed by clinicians and implemented in a tertiary hospital to flag dysglycaemia. There were 112 patients included in the study, and the post-implementation group demonstrated lower rates of dysglycaemia (2.5% vs 1.1%, P = 0.038). These findings raise considerations for information delivery methods for multiple domains in contemporary healthcare.

Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In this implementation study, such an artificial intelligence algorithm was coupled with a multidisciplinary discharge facilitation team on weekend shifts. This approach was implemented in a tertiary hospital, and then compared to a historical cohort from the same time the previous year. There were 3990 patients included in the study. There was a significant increase in the proportion of inpatients who received weekend discharges in the intervention group compared to the control group (median 18%, IQR 18-20%, vs median 14%, IQR 12% to 17%, P = 0.031). There was a corresponding higher absolute number of weekend discharges during the intervention period compared to the control period (P = 0.025). The studied intervention was associated with an increase in weekend discharges and economic analyses support this approach as being cost-effective. Further studies are required to examine the generalizability of this approach to other centers.

Campaign Disaster Response - What Makes It Different.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic has seen health systems adapt and change in response to local and international experiences. This study describes the experiences and learnings by the Central Adelaide Local Health Network (CALHN) in managing a campaign style, novel public health disaster response. METHODS: Disaster preparedness has focused on acute impact, mass casualty incidents. In early 2020, CALHNs largest hospital the Royal Adelaide Hospital (RAH) was appointed as the state primary COVID-19 adult receiving hospital. Between the period of February 1, 2020, when the first COVID-19 positive patient was admitted, through to December 31, 2020, the RAH had admitted 146 inpatients with COVID-19, 118 admitted to our hospital in the home service, 18 patients admitted to Intensive Care, and 4 patients died while inpatients. During this time CALHN has sustained an active (physical and virtual) Network Incident Command Centre (NICC) supported by a Network Incident Management Team (NIMT). RESULTS: This study describes our key lessons learnt in relation to the management of a campaign style disaster response including the importance of disaster preparedness, fatigue management, and communication. Also described, were the challenges of operating in a command model and the role of exercising and education and an overview of our operating rhythm, how we built capability, and lessons management. CONCLUSIONS: Undertaking a longer duration disaster response, relating to the COVID-19 pandemic has shown that, although traditional disaster principles still are important, there are many nuances that need to be considered to retain a proportionate response. Our key lessons have revolved around the key tenants of disaster management, communication, capability, and governance.

Hospital design features that optimise pandemic response.

The COVID-19 pandemic has changed forever how we plan, respond to, and deliver health care. The lived experience of hospital infrastructure design to support a pandemic is currently not well described in the literature. Much of what is known covers generic elements of hospital design and/or assumptions about in-built disaster design features. The Central Adelaide Local Health Network became a key stakeholder in South Australia's response when the Royal Adelaide Hospital (RAH) became the designated receiving hospital for the state. Preparation for a pandemic commenced back in 2007 when a new build for the RAH was announced. Several disaster response infrastructure design features were incorporated into the RAH design specifications to provide a resilient facility that could respond to any type of disaster event while continuing to provide core clinical services. Key pandemic design elements included patient room design, pandemic air handling capability, and a 7-step scalability function. We describe these key elements based on real-time experience along with the key lessons learnt as the pandemic response evolved with the aim of guiding future hospital building design to not only support the more frequent time-limited disasters but, more specifically, a pandemic response. The RAH capitalised on its key design features to support its pandemic response and contributed to the overall success of South Australia's pandemic response.

Nonlinear Modelling for Predicting Patient Presentation Rates for Mass Gatherings.

IntroductionMass gatherings are common in Australia. The interplay of variables, including crowd density and behavior, weather, and the consumption of alcohol and other drugs, can pose a unique set of challenges to attendees' well-being. On-site health services are available at most mass gatherings and reduce the strain on community health facilities. In order to efficiently plan and manage these services, it is important to be able to predict the number and type of presenting problems at mass gatherings.ProblemThere is a lack of reliable tools to predict patient presentations at mass gatherings. While a number of factors have been identified as having an influence on attendees' health, the exact contribution of these variables to patient load is poorly understood. Furthermore, predicting patient load at mass gatherings is an inherently nonlinear problem, due to the nonlinear relationships previously observed between patient presentations and many event characteristics. METHODS: Data were collected at 216 Australian mass gatherings and included event type, crowd demographics, and weather. Nonlinear models were constructed using regression trees. The full data set was used to construct each model and the model was then used to predict the response variable for each event. Nine-fold cross validation was used to estimate the error that may be expected when applying the model in practice. RESULTS: The mean training errors for total patient presentations were very high; however, the distribution of errors per event was highly skewed, with small errors for the majority of events and a few large errors for a small number of events with a high number of presentations. The error was five or less for 40% of events and 15 or less for 85% of events. The median error was 6.9 presentations per event. CONCLUSION: This study built on previous research by undertaking nonlinear modeling, which provides a more realistic representation of the interactions between event variables. The developed models were less useful for predicting patient presentation numbers for very large events; however, they were generally useful for more typical, smaller scale community events. Further research is required to confirm this conclusion and develop models suitable for very large international events.Arbon P, Bottema M, Zeitz K, Lund A, Turris S, Anikeeva O, Steenkamp M. Nonlinear modelling for predicting patient presentation rates for mass gatherings. Prehosp Disaster Med. 2018;33(4):362-367.

Patient Presentation Trends at 15 Mass-Gathering Events in South Australia.

IntroductionMass gatherings are complex events that present a unique set of challenges to attendees' health and well-being. There are numerous factors that influence the number and type of injuries and illnesses that occur at these events, including weather, event and venue type, and crowd demographics and behavior.ProblemWhile the impact of some factors, such as weather conditions and the availability of alcohol, on patient presentations at mass gatherings have been described previously, the influence of many other variables, including crowd demographics, crowd behavior, and event type, is poorly understood. Furthermore, a large number of studies reporting on the influence of these variables on patient presentations are based on anecdotal evidence at a single mass-gathering event. METHODS: Data were collected by trained fieldworkers at 15 mass gatherings in South Australia and included event characteristics, crowd demographics, and weather. De-identified patient records were obtained from on-site health care providers. Data analysis included the calculation of patient proportions in each variable category, as well as the total number of patient presentations per event and the patient presentation rate (PPR). RESULTS: The total number of expected attendees at the 15 mass gatherings was 303,500, of which 146 presented to on-site health care services. The majority of patient presentations occurred at events with a mean temperature between 20°C and 25°C. The PPR was more than double at events with a predominantly male crowd compared to events with a more equal sex distribution. Almost 90.0% of patient presentations occurred at events where alcohol was available. CONCLUSION: The results of the study suggest that several weather, crowd, and event variables influence the type and number of patient presentations observed at mass-gathering events. Given that the study sample size did not allow for these interactions to be quantified, further research is warranted to investigate the relationships between alcohol availability, crowd demographics, crowd mobility, venue design, and injuries and illnesses.Anikeeva O, Arbon P, Zeitz K, Bottema M, Lund A, Turris S, Steenkamp M. Patient presentation trends at 15 mass-gathering events in South Australia. Prehosp Disaster Med. 2018;33(4):368-374.

Principles of capacity management, applied in the mental health context.

Objective The aim of the paper was to describe a suite of capacity management principles that have been applied in the mental health setting that resulted in a significant reduction in time spent in two emergency departments (ED) and improved throughput. Methods The project consisted of a multifocal change approach over three phases that included: (1) the implementation of a suite of fundamental capacity management activities led by the service and clinical director; (2) a targeted Winter Demand Plan supported by McKinsey and Co.; and (3) a sustainability of change phase. Descriptive statistics was used to analyse the performance data that was collected through-out the project. Results This capacity management project has resulted in sustained patient flow improvement. There was a reduction in the average length of stay (LOS) in the ED for consumers with mental health presentations to the ED. At the commencement of the project, in July 2014, the average LOS was 20.5h compared with 8.5h in December 2015 post the sustainability phase. In July 2014, the percentage of consumers staying longer than 24h was 26% (n=112); in November and December 2015, this had reduced to 6% and 7 5% respectively (less than one consumer per day). Conclusion Improving patient flow is multifactorial. Increased attendances in public EDs by people with mental health problems and the lengthening boarding in the ED affect the overall ED throughput. Key strategies to improve mental health consumer flow need to focus on engagement, leadership, embedding fundamentals, managing and target setting. What is known about the topic? Improving patient flow in the acute sector is an emerging topic in the health literature in response to increasing pressures of access block in EDs. What does this paper add? This paper describes the application of a suite of patient flow improvement principles that were applied in the mental health setting that significantly reduced the waiting time for consumers in two EDs. What are the implications for practitioners? No single improvement will reduce access block in the ED for mental health consumers. Reductions in waiting times require a concerted, multifocal approach across all components of the acute mental health journey.

Developing an evaluation framework for clinical redesign programs: lessons learnt.

Purpose The purpose of this paper is to present lessons learnt through the development of an evaluation framework for a clinical redesign programme - the aim of which was to improve the patient journey through improved discharge practices within an Australian public hospital. Design/methodology/approach The development of the evaluation framework involved three stages - namely, the analysis of secondary data relating to the discharge planning pathway; the analysis of primary data including field-notes and interview transcripts on hospital processes; and the triangulation of these data sets to devise the framework. The evaluation framework ensured that resource use, process management, patient satisfaction, and staff well-being and productivity were each connected with measures, targets, and the aim of clinical redesign programme. Findings The application of business process management and a balanced scorecard enabled a different way of framing the evaluation, ensuring measurable outcomes were connected to inputs and outputs. Lessons learnt include: first, the importance of mixed-methods research to devise the framework and evaluate the redesigned processes; second, the need for appropriate tools and resources to adequately capture change across the different domains of the redesign programme; and third, the value of developing and applying an evaluative framework progressively. Research limitations/implications The evaluation framework is limited by its retrospective application to a clinical process redesign programme. Originality/value This research supports benchmarking with national and international practices in relation to best practice healthcare redesign processes. Additionally, it provides a theoretical contribution on evaluating health services improvement and redesign initiatives.

Discharge timeliness and its impact on hospital crowding and emergency department flow performance.

OBJECTIVE: The objective of this research is to identify optimal inpatient discharge time targets to help hospitals reduce crowding, improve patient flow through the ED and balance staff workload. METHODS: Fifteen months of emergency and inpatient records from a large quaternary teaching hospital were used to reconstruct patient pathways from hospital presentation to discharge. Discrete event simulation was used to assess operationally realistic discharge scenarios on flow performance. Main output measures included National Emergency Access Target (NEAT) performance (an ED performance metric), time spent waiting for a bed, hospital length of stay (LOS) and occupancy. RESULTS: Similar levels of improvement in NEAT performance (16%), and reductions in average bed occupancy (1.5%) and inpatient bed wait time (25%) were observed across the simulation that discharged 80% patients before 11 a.m. and one that spread the target between 10 a.m. and 2 p.m. Individual inpatient wards returned potential improvements in NEAT performance (median 10%, interquartile range (IQR) 7%), and reductions in hospital LOS (median 1%, IQR 1%) and average occupancy (median 1%, IQR 2%) across the discharge scenarios. CONCLUSIONS: Conventional discharge targets like '80% by 11 a.m.' and others that spread targets across the day to balance staff workload freed up the equivalent of nine available beds for incoming patient flow, significantly reducing time spent waiting for an inpatient bed, hospital LOS and occupancy, and delivering much needed improvements in NEAT performance. While different strategies and workload distributions may suit individual hospital services, the study makes a strong case for improving 'early in the day' discharge timeliness to deliver better ED flow.

Use of a capacity audit tool in a mental health setting.

OBJECTIVE: This paper reports on a pilot applying the capacity audit tool (CAT) in a mental health environment and what the tool reveals regarding mental health in-patient capacity issues. METHODS: The CAT was modified to create an electronic mental health-relevant tool to audit acute in-patient capacity. This tool was then piloted across nine bedded units, within a single Local Health Network, covering a total of 153 mental health beds. RESULTS: The application of the mental health CAT resulted in 100% compliance in completion. The findings revealed that 16% (25 beds) of the 153 beds surveyed were occupied by patients who did not need to occupy the bed or the bed was vacant. Of these 25 beds, 10 had patients awaiting transfer to another facility or service, nine were empty and six were occupied by patients ready for discharge but for whom there were delays. CONCLUSION: The CAT was successfully applied to the mental health setting and identified a set of opportunities to improve processes and practices to reduce the identified delays or barriers in order to improve patient flow.

Understanding the patient journey to the Emergency Department - A South Australian study.

BACKGROUND: To determine patients' points of contact prior to or decision making processes before presenting to an Emergency Department for treatment. To obtain data that may inform future exploration of targeted Emergency Department avoidance strategies. METHOD: All patients presenting to two metropolitan Emergency Departments over a 24h period were surveyed. Where information was unattainable, it was sought from computerised Patient Administration Systems used by each Emergency Department. A descriptive analysis of the results was undertaken. RESULTS: Three hundred and thirty two patients presented over the 48 h survey period. Results showed that 200 (60.2%) were self-referred, 65 patients (19.6%) contacted their general practitioner, 22 (6.6%) were transferred from other hospitals and 3 patients (0.9%) contacted the National Healthdirect Australia triage hotline prior to presenting to the Emergency Department. CONCLUSION: The study showed 39.8% had sought advice from other health care professionals prior to presenting to the Emergency Department and that 60.2% of patients were self-referred. This study has not revealed any new pathways that warrant targeting for Emergency Department avoidance strategies. The focus still needs to target primary care referrals, ambulance service transports and smaller hospital transfers.

Using capacity alert calls to reduce overcrowding in a major public hospital.

OBJECTIVE: To investigate the efficacy of capacity alert calls in reducing acute hospital overcrowding through addressing rising occupancy, high patient throughput and increased access block. METHODS: Retrospective analysis of 24 months of in-patient, emergency department, and capacity alert call log data from a large metropolitan public hospital in Australia. The analysis explored statistical differences in patient flow parameters between capacity alert call days and other days including a control case set of days with statistically similar levels of occupancy. RESULTS: The study identified a significant (P<0.05) reduction in occupancy, patient throughput and access block on capacity alert call days. Capacity alert call days reversed rising occupancy trends, with 6 out of 7 flow parameters reporting significant improvement (P<0.05) over the 48 h following the call. Only 3 of these 7 flow parameters were significantly improved 48 h after control case days, confirming value in the alert mechanism and that the results are not a regression toward the mean phenomenon. CONCLUSIONS Escalation processes that alert and engage the whole hospital in tackling overcrowding can successfully deliver sustained improvements in occupancy, patient throughput and access block. The findings support and validate the use of capacity alert escalation calls to manage overcrowding, but suggest the need to improve the consistency of trigger mechanisms and the efficiency of the processes initiated by the capacity alert call.

Probability of severe adverse events as a function of hospital occupancy.

A unique application of regression modeling is described to compare hospital bed occupancy with reported severe adverse events amongst inpatients. The probabilities of the occurrence of adverse events as a function of hospital occupancy are calculated using logistic and multinomial regression models. All models indicate that higher occupancy rates lead to an increase in adverse events. The analysis identified that at an occupancy level of 100%, there is a 22% chance of one severe event occurring and a 28% chance of at least one severe event occurring. This modeling contributes evidence toward the management of hospital occupancy to benefit patient outcomes.

Flexing bed stock: a hospital capacity management case study.

As hospitals struggle to meet rising demand for their services, efficient capacity management is critical to the success of their efforts. A popular strategy employed by hospitals to meet the variability in demand for their services is to 'flex' their capacity, i.e. to vary the number of available staffed beds to suit demand on a regular basis. This study uses data from a large tertiary hospital in South Australia to analyze the efficacy of their flexing protocols and the impact of flexing capacity on overcrowding. We also analyze the impact of variation in occupancy on patient flow parameters and compare this to previous studies conducted on similar sized Australian hospitals that do not flex capacity. Our findings reveal that flexing capacity helps the hospital spend less time over critical occupancy levels, and that the hospital does not show the signs of performance decline exhibited by hospitals that do not flex capacity. Areas for improvements in the flexing protocol and possible strategies are also identified. The findings support the use of flexing capacity as an efficient protocol and will serve as a useful guide for services seeking to improve existing capacity management protocols.

Does hospital occupancy impact discharge rates?

OBJECTIVE: To understand what impact hospital inpatient occupancy levels have on patient throughput by analysing one hospital's occupancy levels and the rate of patient discharge. METHODS: A four-stage model was fit to hospital admission and separation data and used to analyse the per-capita separation rate according to the patient load and the impact of hospital over-census actions. RESULTS: Per-capita separation rates are significantly higher on days when the hospital declares an over-census due to emergency department crowding. Per-capita separation rates are also higher or lower on days with 8-10% higher or lower patient loads, respectively, but the response is not nearly as strong as the response to an over-census declaration, and is limited to patients with an elapsed stay of 10 days or more. Within the medical division there is an increase in per-capita separation rates on over-census days, but no significant difference in per-capita release rates for different patient loads. Within the surgical division there is no significant difference in per-capita separation rates on over-census days compared with other days, but the patient load does make a significant difference. CONCLUSION: Staff do discharge a greater proportion of long-stay patients when the hospital is experiencing high demand and a lower proportion when occupancy is low, but the reasons driving those changes remains unclear.

Understanding the drivers on medical workloads: an analysis of spectators at the Australian Football League.

OBJECTIVE: The present study was designed to further understand the psychosocial drivers of crowds impacting on the demand for healthcare. This involved analysing different spectator crowds for medical usage at mass gatherings; more specifically, did different football team spectators (of the Australian Football League) generate different medical usage rates. METHODS: In total, 317 games were analysed from 10 venues over 2 years. Data were analysed by the ANOVA and Pearson correlation tests. RESULTS; Spectators who supported different football teams generated statistically significant differences in patient presentation rates (PPR) (F15, 618=1.998, P=0.014). The present study confirmed previous findings that there is a positive correlation between the crowd size and PPR at mass gatherings but found a negative correlation between density and PPR (r = -0.206, n=317, P<0.0005). CONCLUSIONS: The present study has attempted to scientifically explore psychosocial elements of crowd behaviour as a driver of demand for emergency medical care. In measuring demand for emergency medical services there is a need to develop a more sophisticated understanding of a variety of drivers in addition to traditional metrics such as temperature, crowd size and other physical elements. In this study we saw that spectators who supported different football teams generated statistically significant differences in PPR. What is known about this topic? Understanding the drivers of emergency medical care is most important in the mass gathering setting. There has been minimal analysis of psychological 'crowd' variables. What does this paper add? This study explores the psychosocial impact of supporting a different team on the PPR of spectators at Australian Football League matches. The value of collecting and analysing these types of data sets is to support more balanced planning, better decision support and knowledge management, and more effective emergency medical demand management. What are the implications for practitioners? This information further expands the body of evidence being created to understand the drivers of emergency medical demand and usage. In addition, it supports the planning and management of emergency medical and health-related requirements by increasing our understanding of the effect of elements of 'crowd' that impact on medical usage and emergency healthcare.

The ebbs and flows of changing acute bed capacity delays.

OBJECTIVE: This case study provides a summary of changes in acute hospital bed delays that have occurred over a 4-year period as identified through a Capacity Audit process. BACKGROUND: Royal Adelaide Hospital (RAH) designed a Capacity Audit process and tool that provides a systematic method to evaluate factors limiting access to inpatient bed capacity. The aim of the audit is to improve understanding of bed capacity by identifying key causes of delay for hospital inpatients and quantify the most frequent causes of blocked bed capacity. This can then be used to underpin targeted improvement work. The Capacity Audit has been undertaken at the RAH over three cycles. METHOD: The Capacity Audit involves a survey of every open and staffed bed, identifying how the bed is being used: for acute care or treatment, if there was a delay to the patient for discharge, or if the bed was unavailable. The first and second cycle of the audit (2007-2008) involved a twice-daily survey over a 2-week period and the third audit cycle in 2010 occurred once daily for 1 week. RESULTS: On average, 620 beds were surveyed daily with an audit compliance rate ranging from 85-97%. This process has revealed almost 75% of beds are used positively for care. Of the remaining 25% of hidden capacity identified, non-clinical discharge delays account for 10% of total beds surveyed. Waiting for post-acute beds has consistently remained the main cause of acute bed delay. CONCLUSION: The Capacity Audit process and tool has been used to track progress, trends and change resulting from service improvement efforts, and to provide the evidence to commence strategies to reduce the hidden capacity issues. This case study has shown that whilst overall bed stock usage for positive care has not changed significantly there are various ebbs and flows over time in relation to the reasons for bed delays.

What are the core elements of patient-centred care? A narrative review and synthesis of the literature from health policy, medicine and nursing.

AIM: To identify the common, core elements of patient-centred care in the health policy, medical and nursing literature. BACKGROUND: Healthcare reform is being driven by the rhetoric around patient-centred care yet no common definition exists and few integrated reviews undertaken. DESIGN: Narrative review and synthesis. DATA SOURCES: Key seminal texts and papers from patient organizations, policy documents, and medical and nursing studies which looked at patient-centred care in the acute care setting. Search sources included Medline, CINHAL, SCOPUS, and primary policy documents and texts covering the period from 1990-March 2010. REVIEW METHODS: A narrative review and synthesis was undertaken including empirical, descriptive, and discursive papers. Initially, generic search terms were used to capture relevant literature; the selection process was narrowed to seminal texts (Stage 1 of the review) and papers from three key areas (in Stage 2). RESULTS: In total, 60 papers were included in the review and synthesis. Seven were from health policy, 22 from medicine, and 31 from nursing literature. Few common definitions were found across the literature. Three core themes, however, were identified: patient participation and involvement, the relationship between the patient and the healthcare professional, and the context where care is delivered. CONCLUSION: Three core themes describing patient-centred care have emerged from the health policy, medical, and nursing literature. This may indicate a common conceptual source. Different professional groups tend to focus on or emphasize different elements within the themes. This may affect the success of implementing patient-centred care in practice.

Patients' views of patient-centred care: a phenomenological case study in one surgical unit.

AIMS: To report a study of patients' views of patient-centred care. The study aimed to explore patients' understanding and conceptualization of patient-centred care and link it to existing literature on the topic. BACKGROUND: Patient-centred care currently lacks a widely accepted definition, with much of the literature based on definitions formulated by health professionals and researchers. DESIGN: Qualitative research study grounded in phenomenology. METHODS: Interpersonal interviews were conducted with ten participants who were patients in a surgical ward in a large metropolitan hospital in South Australia in 2010. RESULTS/FINDINGS: Participants were unfamiliar with the concept of patient-centred care, but despite this, were able to describe what the term meant to them and what they wanted from their care. Patients equated the type and quality of care they received with the staff that provided it and themes of connectedness, involvement and attentiveness were prevalent in their descriptions of what they wanted from their care. CONCLUSION: Ensuring that patients have a voice in the definition and conceptualization of patient-centred care is essential and further and regular consultation with patients about their needs and priorities will ensure an integrated approach to patient-centred care.