Screening for important unwarranted variation in clinical practice: a triple-test of processes of care, costs and patient outcomes

Objective: Unwarranted variation in clinical practice is a target for quality improvement in health care, but there is no consensus on how to identify such variation or to assess the potential value of initiatives to improve quality in these areas. This study illustrates the use of a triple test, namely the comparative analysis of processes of care, costs and outcomes, to identify and assess the burden of unwarranted variation in clinical practice. Methods: Routinely collected hospital and mortality data were linked for patients presenting with symptoms suggestive of acute coronary syndromes at the emergency departments of four public hospitals in South Australia. Multiple regression models analysed variation in re-admissions and mortality at 30 days and 12 months, patient costs and multiple process indicators. Results: After casemix adjustment, an outlier hospital with statistically significantly poorer outcomes and higher costs was identified. Key process indicators included admission patterns, use of invasive diagnostic procedures and length of stay. Performance varied according to patients’ presenting characteristics and time of presentation. Conclusions: The joint analysis of processes, outcomes and costs as alternative measures of performance inform the importance of reducing variation in clinical practice, as well as identifying specific targets for quality improvement along clinical pathways. Such analyses could be undertaken across a wide range of clinical areas to inform the potential value and prioritisation of quality improvement initiatives.Andrew Partington, Derek P. Chew, David Ben-Tovim, Matthew Horsfall, Paul Hakendorf and Jonathan Karno

Hospital Event Simulation Model: Arrivals to Discharge

MODSIM2015 was held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium (DORS 2015).Many Australian public hospitals operate under strict resource constraints. Arguably, this is manifested in higher incidence of ambulance ramping and patient flow congestion episodes, which has led to an increase in public complaints and, possibly, sub-optimal health outcomes for patients. Consequently, there is a well accepted need to make best use of all available information and domain knowledge to ensure that hospital resources and expertise are utilised more efficiently, for the benefit of patients. The latter is not a simple task since hospital operations involve complex interactions among many groups of health professionals utilising limited physical facilities and equipment. This is further complicated by the inherent variability of patient responses to treatments. Indeed, the stochastic nature of the demand process, as well as uncertainty in durations of medical treatments and patient recovery, lead to probabilistically distributed bed availability. Fortunately, in Australia, hospitals are ”data rich” in the sense that reliable records of patient journeys have been kept for many years. While older data may reflect procedures and priorities that are no longer in place, data from recent years may be regarded as quite robust, especially in cities that have not experienced major demographic changes. Thus there is an opportunity to apply modern tools of mathematical, statistical and simulation modelling to enhance our understanding of key processes that influence a hospital’s operations. The understanding so obtained can then be used to assist hospital staff in devising operational procedures that are likely to minimise disruption without adversely impacting the public service provided to the patient population. In this paper we outline the Hospital Event Simulation Model: Arrivals to Discharge (HESMAD) to describe the patterns of patient flows within the Flinders Medical Centre, an urban teaching hospital. The logical design of HESMAD was developed through extensive consultation with colleagues from the hospital. In particular, patients within HESMAD are not modelled as identical entities, rather, they are assigned different attribute values such as mode of arrival, triage category and division to reflect the typical profile of all patients. Patients go through a set of physical units and process modules that model various physical areas, processes, interactions and behaviours within the hospital to replicate a wide spectrum of patient journeys. Hospital and patient data from 2012 to 2013 were used to fit various probability distributions, for instance the waiting times for treatment or discharges. The model allows for a realistic representation of patient flows, at a level of resolution that was deemed appropriate by the hospitals data management experts. The model has been validated against historical data and through consultation with health care and hospital experts. Within space limitation we provide an outline and a brief discussion of HESMAD’s structure, features, capabilities, design decisions and development. In addition, we provide a brief case study demonstrating the potential applicability of HESMAD for ’what if’ analyses of hospital interventions. While all discussions are specific to the Flinders Medical Centre, the methodology used within HESMAD is generic enough to apply to other public hospitals in Australia.D. Ben-Tovim, J. Filar, P. Hakendorf, S. Qin, C. Thompson and D. War

Association of BMI with overall survival in patients with mCRC who received chemotherapy versus EGFR and VEGF-targeted therapies

Although a raised body mass index (BMI) is associated with increased risk of colorectal cancer (CRC) and recurrence after adjuvant treatment, data in the metastatic setting is limited. We compared overall survival (OS) across BMI groups for metastatic CRC, and specifically examined the effect of BMI within the group of patients treated with targeted therapies (TT). Retrospective data were obtained from the South Australian Registry for mCRC from February 2006 to October 2012. The BMI at first treatment was grouped as underweight <18.5 kg/m(2) , Normal = 18.5 to <25 kg/m(2) , Overweight = 25 to <30 kg/m(2) , Obese I = 30 to <35 kg/m(2) , Obese II ≥35 kg/m(2) . Of 1174 patients, 42 were underweight, 462 overweight, 175 Obese I, and 77 Obese II. The OS was shorter for patients who were underweight and overweight compared to normal (OS 13.7 and 22.3 vs. 24.1 months, respectively, hazard ratio [HR] 2.21 and 1.23). The adjusted median OS was longer for normal versus overweight or obese I patients receiving chemotherapy + targeted therapy (35.7 vs 25.1 or 22.8 months, HR 1.59 and 1.63, respectively) with no difference in OS for chemotherapy alone. On breakdown by type of targeted therapy, overweight and obese I patients had a poorer outcome with Bevacizumab. The BMI is predictive of a poorer outcome for underweight and overweight patients in the whole population. Of those receiving chemotherapy and targeted therapy, BMI is an independent predictor for OS for overweight and obese I patients, specifically for those treated with Bevacizumab. Patients who are overweight or obese (group I) may be a target group for lifestyle and nutrition advice to improve OS with TT.Gargi S. Patel, Shahid Ullah, Carol Beeke, Paul Hakendorf, Robert Padbury, Timothy J. Price and Christos S. Karapeti

Factors influencing early and late readmissions in Australian hospitalised patients and investigating role of admission nutrition status as a predictor of hospital readmissions: a cohort study

Objectives: Limited studies have identified predictors of early and late hospital readmissions in Australian healthcare settings. Some of these predictors may be modifiable through targeted interventions. A recent study has identified malnutrition as a predictor of readmissions in older patients but this has not been verified in a larger population. This study investigated what predictors are associated with early and late readmissions and determined whether nutrition status during index hospitalisation can be used as a modifiable predictor of unplanned hospital readmissions. Design: A retrospective cohort study. Setting: Two tertiary-level hospitals in Australia. Participants: All medical admissions ≥18 years over a period of 1 year. Outcomes: Primary objective was to determine predictors of early (0–7 days) and late (8–180 days) readmissions. Secondary objective was to determine whether nutrition status as determined by malnutrition universal screening tool (MUST) can be used to predict readmissions. Results: There were 11 750 (44.8%) readmissions within 6 months, with 2897 (11%) early and 8853 (33.8%) late readmissions. MUST was completed in 16.2% patients and prevalence of malnutrition during index admission was 31%. Malnourished patients had a higher risk of both early (OR 1.39, 95% CI 1.12 to 1.73) and late readmissions (OR 1.23, 95% CI 1.06 to 128). Weekend discharges were less likely to be associated with both early (OR 0.81, 95% CI 0.74 to 0.91) and late readmissions (OR 0.91, 95% CI 0.84 to 0.97). Indigenous Australians had a higher risk of early readmissions while those living alone had a higher risk of late readmissions. Patients ≥80 years had a lower risk of early readmissions while admission to intensive care unit was associated with a lower risk of late readmissions. Conclusions: Malnutrition is a strong predictor of unplanned readmissions while weekend discharges are less likely to be associated with readmissions. Targeted nutrition intervention may prevent unplanned hospital readmissions.Yogesh Sharma, Michelle Miller, Billingsley Kaambwa, Rashmi Shahi, Paul Hakendorf, Chris Horwood, Campbell Thompso

A general medical short-stay unit is not more efficient than a traditional model of care

OBJECTIVES: To assess the efficiency of a short-stay unit (SSU) for undifferentiated medical patients and evaluate its effect on the overall efficiency of a general medicine department. DESIGN, SETTING AND PATIENTS: Retrospective study of all general medical patients admitted to the SSU at Flinders Medical Centre, South Australia, during its 5 years of operation (2005-2009), compared with 4 years before its institution and 2 years after its closure. MAIN OUTCOME MEASURES: Relative stay index (RSI); inhospital mortality; readmissions within 7 and 28 days. RESULTS: 23 790 general medical patients were admitted overall, and 10 764 of these (45.2%) were admitted to the SSU. The RSI for the SSU during its years of operation was 0.79, compared with 1.34 for the long-stay unit. The overall RSI for the department did not improve during those years and was not significantly different to the periods before or after. CONCLUSIONS: We found no evidence that an SSU for undifferentiated medical patients creates bed capacity. It does, however, appear to be safe.Patrick T Russell, Paul Hakendorf, Campbell H Thompso

Inter-hospital lateral transfer does not increase length of stay

Objective: The aim of the present study was to assess the effect of an inter-hospital transfer on efficiency and quality of in-patient care. Methods: A retrospective cohort study from 2010 to 2012 inclusive was conducted in two tertiary-referral urban hospitals within a single area healthcare network. The study included 14 571 acutely unwell patients admitted to a general medical service. The main outcome measures were length of in-patient stay, relative stay index, readmission rate within 7 and 28 days of discharge and in-hospital mortality rate. Results: Compared with patients who were transferred to a long-stay ward within the original hospital (n = 3465), transferred patients (n = 1531) were older (71 vs 80 years, respectively; P < 0.001) but suffered less comorbidity (Charlson index 0.84 vs 1.22, respectively; P < 0.001). Transferred patients spent a shorter time in hospital (5.69 vs 6.25 days; P < 0.001) and were less likely to be re-admitted within 7 days (1.5% vs 4.0%; P < 0.001) or 28 days (6.3% vs 9.3%; P < 0.001) than patients who were not transferred. Mortality was lower in the transferred patients (1.1% vs 4.1%). Conclusion: Appropriate patients for inter-hospital transfer can be selected within 24 h of arrival at an index hospital. The efficiency of their care at the receiving hospital appears not to be compromised. The present study provides support for inter-hospital transfer as a strategy to optimise regional bed capacity.Patrick Russell , Paul Hakendorf and Campbell Thompso

Characteristics favouring a delayed disposition decision in the emergency department

BACKGROUND: The working hours of a hospital affects efficiency of care within the emergency department (ED). Understanding the influences on ED time intervals is crucial for process redesign to improve ED patient flow. AIM: To assess characteristics that affect patients' transit through an ED. METHODS: Retrospective cohort study from 2004 to 2010 of 268 296 adult patients who presented to the ED of an urban tertiary-referral Australian teaching hospital. RESULTS: After adjustment for Australasian Triage Scale (ATS) category, every decade increase in age meant patients spent an additional 2 min in the ED waiting to be seen (P < 0.001) and an extra 29-min receiving treatment (P < 0.001). For every additional 10 patients in the ED, the 'waiting time' (WT) phase duration increased by 20 min (P < 0.001) and the 'Assessment and Treatment Time' (ATT) phase duration increased by 26 min (P < 0.001). When patients arrived outside working hours, the WT phase duration increased by 20 min (P < 0.001). When seen outside working hours, the ATT phase duration increased by 34.5 min (P < 0.001). CONCLUSION: Extrinsic to the patients themselves and in addition to ED overcrowding, the working hours of the hospital affected efficiency of care within the ED. Not only should the whole of the hospital be involved in improving efficient and safe transit of patients through an ED, but the whole of the day and every day of the week deserve attention.L. Perimal-Lewis, P. H. Hakendorf and C. H. Thompso

Hospital occupancy and discharge strategies: a simulation-based study

Background: Increasing demand for hospital services has resulted in more arrivals to emergency department (ED), increased admissions, and, quite often, access block and ED congestion, along with patients’ dissatisfaction. Cost constraints limit an increase in the number of hospital beds, so alternative solutions need to be explored. Aims: To propose and test different discharge strategies, which, potentially, could reduce occupancy rates in the hospital, thereby improving patient flow and minimising frequency and duration of congestion episodes. Methods: We used a simulation approach using HESMAD (Hospital Event Simulation Model: Arrivals to Discharge) – a sophisticated simulation model capturing patient flow through a large Australian hospital from arrival at ED to discharge. A set of simulation experiments with a range of proposed discharge strategies was carried out. The results were tabulated, analysed and compared using common hospital occupancy indicators. Results: Simulation results demonstrated that it is possible to reduce significantly the number of days when a hospital runs above its base bed capacity. In our case study, this reduction was from 281.5 to 22.8 days in the best scenario, and reductions within the above range under other scenarios considered. Conclusion: Some relatively simple strategies, such as 24‐h discharge or discharge/relocation of long‐staying patients, can significantly reduce overcrowding and improve hospital occupancy rates. Shortening administrative and/or some treatment processes have a smaller effect, although the latter could be easier to implement.Shaowen Qin, Campbell Thompson, Tim Bogomolov, Dale Ward, Paul Hakendor

Mortality and its predominant causes in a large cohort of patients with biopsy-determined inflammatory myositis

BACKGROUND: There is a paucity of literature on the patterns and predictors of mortality in idiopathic inflammatory myopathies (IIM). AIMS: To determine the patterns and predictors of mortality in a South Australian cohort of patients with biopsy-proven IIM. METHODS: The living/ deceased status (and for deceased patients the causes of death) of patients with histologically-determined IIM was determined from the Births, Deaths and Marriages Registry. Standardized mortality ratios (SMR) were generated compared with the age/gender matched South Australian population. The effect of presence/ absence of the components of the Bohan and Peter criteria on risk ratios (RR) for mortality were determined. The effect of comorbidities and autoantibodies on mortality were investigated. RESULTS: The SMR for mortality in IIM was 1.75 and was significantly increased in all disease subgroups, being highest in patients with dermatomyositis (2.40). Dominant causes of death were cardiovascular disease (31%), infections (22%) and malignancy (11%). Risk factors for death were age at time of biopsy (hazard ratio 1.05), ischemic heart disease (RR 2.97, p < 0.0001), proximal weakness at diagnosis (RR 1.8, p = 0.03), definite diagnosis of IIM per the Bohan and Peter criteria (RR 2.14, p < 0.0001), and the absence of autoantibodies (Risk ratio 1.9, p < 0.001). CONCLUSIONS: Patients with IIM are at 75% increased risk for mortality, and cardiovascular diseases account for the commonest causes of death. This study suggests a thorough cardiovascular evaluation of these patients is indicated, and raises the possibility that targeted interventions such as the use of aspirin or statins may improve outcomes in IIM.Vidya Limaye, Paul Hakendorf, Richard J. Woodman, Peter Blumbergs and Peter Roberts-Thomso

Incidence and prevalence of idiopathic inflammatory myopathies in South Australia: a 30-year epidemiologic study of histology-proven cases

Aim:  To describe the epidemiology of biopsy-proven idiopathic inflammatory myopathies (IIM) in South Australia (SA). Methods:  Cases of IIM were ascertained by review of all muscle biopsy reports from the Neuropathology Laboratory, Hanson Institute (wherein all adult muscle biopsies in SA are reported) from 1980 to 2009. Clinical correlation of these patients by review of medical records was undertaken. SA population denominator numbers were obtained from the Australian Bureau of Statistics. Results:  Three hundred and fifty-two biopsy-proven cases of IIM were identified between 1980 and 2009. The overall annual incidence of IIM appeared to be rising with a mean incidence of eight cases per million population (95% CI: 7.2–8.9). This corresponded with an increasing annual incidence of inclusion body myositis (IBM) (prevalence of 50.5 cases per million population in 2009, 95% CI: 40.2–62.7). A female preponderance was noted in both dermatomyositis (DM) (F : M = 2.75 : 1.00) and polymyositis (PM) (F : M = 1.55 : 1.00) but gender distribution was almost equal in IBM (F : M = 1.1 : 1.0). Mean age at diagnosis for IBM (67.5 years) was higher than for DM (55.1 years) and PM (59.0 years). A higher proportion of DM patients reported living in urban dwellings and DM patients tended to be predominantly professionals. Conclusions:  In SA there is an increasing incidence of IBM and the prevalence is one of the highest reported to date. This may reflect an increase in the number of biopsies performed, improved histological techniques or a genuine increase in incidence.Ju Ann Tan, Peter J. Roberts-Thomson, Peter Blumbergs, Paul Hakendorf, Sally R. Cox and Vidya Limay