Publications by authors named "David Ben-Tovim"

36 Publications

Hospital's instability wedges.

Health Syst (Basingstoke) 2018 Sep 28;9(3):202-211. Epub 2018 Sep 28.

Adelaide Medical School, University of Adelaide, Australia.

In this study, we define a hospital congestion episode as a situation where the number of new patients needing admission is greater than the number of available beds in the hospital, and investigate the likelihood that the current day's midnight occupancy will exceed any specified threshold level. We demonstrate that this measure of risk exhibits a characteristic sensitivity phenomenon that we have named as hospital's instability wedge. In particular, it is seen that frequently even small changes in the numbers of patients admitted or discharged can dramatically change the risk of exceeding the threshold, thereby changing the risk of subsequent congestion episodes. While this finding captures a salient difficulty of operating a modern public hospital, it also opens up an opportunity for monitoring and alleviating the above defined risk with only small changes in admission, discharge, and cancellation rates. A case study with recent patient journey data from Flinders Medical Centre in South Australia is presented.
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http://dx.doi.org/10.1080/20476965.2018.1524407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476524PMC
September 2018

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

Aust Health Rev 2017 Mar;41(1):104-110

School of Public Health, University of Adelaide, Level 7, 178 North Terrace, Adelaide, SA 5044, Australia. Email.

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. What is known about the topic? Variation in clinical practice is a long-standing issue that has been analysed from many different perspectives. It is neither possible nor desirable to address all forms of variation in clinical practice: the focus should be on identifying important unwarranted variation to inform actions to reduce variation and improve quality. What does this paper add? This paper proposes the comparative analysis of processes of care, costs and outcomes for patients with similar diagnoses presenting at alternative hospitals, using linked, routinely collected data. This triple test of performance indicators extracts maximum value from routine data to identify priority areas for quality improvement to reduce important and unwarranted variations in clinical practice. What are the implications for practitioners? The proposed analyses need to be applied to other clinical areas to demonstrate the general application of the methods. The outputs can then be validated through the application of quality improvement initiatives in clinical areas with identified important and unwarranted variation. Validated frameworks for the comparative analysis of clinical practice provide an efficient approach to valuing and prioritising actions to improve health service quality.
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http://dx.doi.org/10.1071/AH15101DOI Listing
March 2017

Identifying risk factors and patterns for unplanned readmission to a general medical service.

Aust Health Rev 2015 Feb;39(1):56-62

Objective: To identify factors and patterns associated with 7- and 28-day readmission for general medicine patients at a tertiary public hospital.

Methods: A retrospective observational study was conducted using an administrative database at a general medicine service in a tertiary public hospital between 1 January 2007 and 31 December 2011. Demographic and clinical factors, as well as readmission patterns, were evaluated for the association with 7- and 28-day readmission.

Results: The study cohort included 13 802 patients and the 28-day readmission rate was 10.9%. In multivariate analysis, longer hospital stay of the index admission (adjusted relative risk (ARR) 1.34), Charlson index ≥ 3 (ARR 1.28), discharge against medical advice (ARR 1.87), active malignancy (ARR 1.83), cardiac failure (ARR 1.48) and incomplete discharge summaries (ARR 1.61) were independently associated with increased risk of 28-day readmission. Patients with diseases of the respiratory system, neurological or genitourinary disease, injury and unclassifiable conditions were likely to be readmitted within 7 days. Patients with circulatory and respiratory disease were likely to be readmitted with the same system diagnosis.

Conclusion: Readmission of general medicine patients within 28 days is relatively common and is associated with clinical factors and patterns. Identification of these risk factors and patterns will enable the interventions to reduce potentially preventable readmissions.
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http://dx.doi.org/10.1071/ah14025DOI Listing
February 2015

Why do older people with multi-morbidity experience unplanned hospital admissions from the community: a root cause analysis.

BMC Health Serv Res 2015 Nov 27;15:525. Epub 2015 Nov 27.

Discipline of General Practice, Flinders University, GPO Box 2100, Adelaide, 5001, South Australia.

Background: Increasing demand for hospital services by older people is a major concern for Australian health care providers. To date there has been little in-depth research that encompasses contextual and systems factors contributing to hospital admissions. The objective of this study was to determine the reasons why older patients experienced unplanned hospital admissions to a major public hospital.

Methods: A retrospective qualitative study using a Root Cause Analysis (RCA) methodology was conducted in a major public hospital in Adelaide, South Australia and surrounding community. Community dwelling older people admitted to the hospital who were well enough to give informed consent and be interviewed were invited to take part in the study. With patients consent, family members, general practitioners (GPs) and specialists were also interviewed and patient hospital records reviewed. Using a purposive sampling technique to obtain maximum variability, thirty-six older people (aged 70 years and older) participated in the study. GPs (n = 17), family members (n = 14), and other healthcare providers (n = 12) involved in their care were also interviewed. Cases were then analysed according to a standardized protocol to determine the root cause of admission. Root causes were then assigned to broader categories using thematic analysis.

Results: The root causes of unplanned admissions were identified and categorised into six causal groups: a consequence of minimal care, progression of disease, home care accessibility, high complexity, clinical error, and delayed care-seeking by the patient.

Conclusions: RCA can be effectively applied to determine the causes of unplanned hospital admissions although the process is time consuming. Four categories of admission (minimal care, clinical error, home care access, delayed care-seeking) were deemed potentially preventable. This methodology and classification approach may assist in designing interventions to prevent future hospitalisations in this high-risk population.
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http://dx.doi.org/10.1186/s12913-015-1170-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662024PMC
November 2015

Predicting admission of patients by their presentation to the emergency department.

Emerg Med Australas 2014 Aug 16;26(4):361-7. Epub 2014 Jun 16.

Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, Adelaide, South Australia, Australia.

Objective: The present study aims to determine the importance of certain factors in predicting the need of hospital admission for a patient in the ED.

Methods: This is a retrospective observational cohort study between January 2010 and March 2012. The characteristics, including blood test results, of 100,123 patients who presented to the ED of a tertiary referral urban hospital, were incorporated into models using logistic regression in an attempt to predict the likelihood of patients' disposition on leaving the ED. These models were compared with triage nurses' prediction of patient disposition.

Results: Patient age, their initial presenting symptoms or diagnosis, Australasian Triage Scale category, mode of arrival, existence of any outside referral, triage time of day and day of the week were significant predictors of the patient's disposition (P < 0.001). The ordering of blood tests for any patient and the extent of abnormality of those tests increased the likelihood of admission. The accuracy of triage nurses' admission prediction was similar to that offered by a model that used the patients' presentation characteristics. The addition of blood tests to that model resulted in only 3% greater accuracy in prediction of patient disposition.

Conclusions: Certain characteristics of patients as they present to hospital predict their admission. The accuracy of the triage nurses' prediction for disposition of patients is the same as that afforded by a model constructed from these characteristics. Blood test results improve disposition accuracy only slightly so admission decisions should not always wait for these results.
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http://dx.doi.org/10.1111/1742-6723.12252DOI Listing
August 2014

More questions than answers in Mid Staffs mortality investigation.

BMJ 2013 Mar 5;346:f1173; discussion f1203. Epub 2013 Mar 5.

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http://dx.doi.org/10.1136/bmj.f1173DOI Listing
March 2013

Psychosocial risk factors which may differentiate between women with Functional Voice Disorder, Organic Voice Disorder and a Control group.

Int J Speech Lang Pathol 2013 Dec 17;15(6):547-63. Epub 2012 Oct 17.

Flinders University , Adelaide, SA , Australia.

This study aimed to explore psychosocial factors contributing to the development of functional voice disorders (FVD) and those differentiating between organic voice disorders (OVD) and a non-voice-disordered control group. A case-control study was undertaken of 194 women aged 18-80 years diagnosed with FVD (n = 73), OVD (n = 55), and controls (n = 66). FVD women were allocated into psychogenic voice disorder (PVD) (n = 37) and muscle tension voice disorder (MTVD) (n = 36) for sub-group analysis. Dependent variables included biographical and voice assessment data, the number and severity of life events and difficulties and conflict over speaking out (COSO) situations derived from the Life Events and Difficulties Schedule (LEDS), and psychological traits including emotional expressiveness scales. Four psychosocial components differentiated between the FVD and control group accounting for 84.9% of the variance: severe events, moderate events, severe COSO, and mild COSO difficulties. Severe events, severe and mild COSO difficulties differentiated between FVD and OVD groups, accounting for 80.5% of the variance. Moderate events differentiated between PVD and MTVD sub-groups, accounting for 58.9% of the variance. Psychological traits did not differentiate between groups. Stressful life events and COSO situations best differentiated FVD from OVD and control groups. More refined aetiological studies are needed to differentiate between PVD and MTVD.
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http://dx.doi.org/10.3109/17549507.2012.721397DOI Listing
December 2013

Evaluating the effects of variation in clinical practice: a risk adjusted cost-effectiveness (RAC-E) analysis of acute stroke services.

BMC Health Serv Res 2012 Aug 21;12:266. Epub 2012 Aug 21.

Discipline of Public Health, The University of Adelaide, South Australia, Australia.

Background: Methods for the cost-effectiveness analysis of health technologies are now well established, but such methods may also have a useful role in the context of evaluating the effects of variation in applied clinical practice. This study illustrates a general methodology for the comparative analysis of applied clinical practice at alternative institutions--risk adjusted cost-effectiveness (RAC-E) analysis--with an application that compares acute hospital services for stroke patients admitted to the main public hospitals in South Australia.

Methods: Using linked, routinely collected data on all South Australian hospital separations from July 2001 to June 2008, an analysis of the RAC-E of services provided at four metropolitan hospitals was undertaken using a decision analytic framework. Observed (plus extrapolated) and expected lifetime costs and survival were compared across patient populations, from which the relative cost-effectiveness of services provided at the different hospitals was estimated.

Results: Unadjusted results showed that at one hospital patients incurred fewer costs and gained more life years than at the other hospitals (i.e. it was the dominant hospital). After risk adjustment, the cost minimizing hospital incurred the lowest costs, but with fewer life-years gained than one other hospital. The mean incremental cost per life-year gained of services provided at the most effective hospital was under $20,000, with an associated 65% probability of being cost-effective at a $50,000 per life year monetary threshold.

Conclusions: RAC-E analyses can be used to identify important variation in the costs and outcomes associated with clinical practice at alternative institutions. Such data provides an impetus for further investigation to identify specific areas of variation, which may then inform the dissemination of best practice service delivery and organisation.
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http://dx.doi.org/10.1186/1472-6963-12-266DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3526450PMC
August 2012

Applying risk adjusted cost-effectiveness (RAC-E) analysis to hospitals: estimating the costs and consequences of variation in clinical practice.

Health Econ 2013 Jun 30;22(6):631-42. Epub 2012 Apr 30.

School of Population Health and Clinical Practice, University of Adelaide, Adelaide, Australia.

Cost-effectiveness analysis is well established for pharmaceuticals and medical technologies but not for evaluating variations in clinical practice. This paper describes a novel methodology--risk adjusted cost-effectiveness (RAC-E)--that facilitates the comparative evaluation of applied clinical practice processes. In this application, risk adjustment is undertaken with a multivariate matching algorithm that balances the baseline characteristics of patients attending different settings (e.g., hospitals). Linked, routinely collected data are used to analyse patient-level costs and outcomes over a 2-year period, as well as to extrapolate costs and survival over patient lifetimes. The study reports the relative cost-effectiveness of alternative forms of clinical practice, including a full representation of the statistical uncertainty around the mean estimates. The methodology is illustrated by a case study that evaluates the relative cost-effectiveness of services for patients presenting with acute chest pain across the four main public hospitals in South Australia. The evaluation finds that services provided at two hospitals were dominated, and of the remaining services, the more effective hospital gained life years at a low mean additional cost and had an 80% probability of being the most cost-effective hospital at realistic cost-effectiveness thresholds. Potential determinants of the estimated variation in costs and effects were identified, although more detailed analyses to identify specific areas of variation in clinical practice are required to inform improvements at the less cost-effective institutions.
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http://dx.doi.org/10.1002/hec.2828DOI Listing
June 2013

The efficient price: an opportunity for funding reform.

Aust Health Rev 2011 Nov;35(4):501-6

Discipline of Public Health, University of Adelaide, Adelaide, SA 5005, Australia.

Objective: Proposed Australian healthcare reforms describe a move towards partial Commonwealth funding of public hospitals, whereby hospitals will be paid an 'efficient price' for each separation, incorporating both the costs and benefits of services. This paper describes a potential approach to setting the efficient price using risk adjusted cost-effectiveness (RAC-E) analysis.

Methods: RAC-E analysis uses a decision analytic framework to estimate lifetime costs and survival for individual patients, which are standardised by comparing observed and expected values. Analysis of standardised costs and effects at different hospitals identifies efficient hospitals, from which efficient prices can be defined.

Results: A RAC-E analysis of services for stroke patients at the four main public hospitals in South Australia demonstrates the need to account for costs and benefits in identifying efficient hospitals. The hospital with the best patient outcomes incurred additional costs relative to less effective hospitals. If an investment of AU$14760 to gain an additional life year in stroke patients is deemed to be a cost-effective use of resources, then the most effective hospital is also the most efficient hospital.

Conclusions: The applied RAC-E analysis demonstrates a framework for comparing the economic efficiency of care provided at different hospitals, which provides a basis for defining the efficient price and appropriate funding incentives to achieve better patient outcomes.
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http://dx.doi.org/10.1071/AH10966DOI Listing
November 2011

Timeliness in discharge summary dissemination is associated with patients' clinical outcomes.

J Eval Clin Pract 2013 Feb 17;19(1):76-9. Epub 2011 Oct 17.

Department of General Medicine, Flinders Medical Centre, Flinders University, Bedford Park, Adelaide, South Australia, Australia.

Rationale, Aims And Objectives: To determine the relation of the readmission rate of general medical patients to either the existence of a discharge summary or the timeliness of its dispatch.

Methods: This was a retrospective study on discharge summaries of all discharges from the general medical service at a tertiary referral teaching hospital from January 2005 to December 2009. The main outcome measures were readmission rate to hospital within 7 or 28 days of discharge

Results: A total of 16 496 patient admissions were included in the analysis. Of these discharges, 3397 (20.6%) patients did not have a summary completed within a week of discharge. There were significant linear trends between patients' readmission rates within 7 (P < 0.001) or 28 days (P < 0.001) and categories reflecting the delay in dispatch of their discharge summaries. The absence of a discharge summary was associated with a 79% increase in the rate of readmission within 7 days [95% confidence interval (CI) 42 to 124% increase; P < 0.001] and a 37% increased rate of readmission within 28 days (95% CI 17 to 61% increase; P < 0.001). If aged less than 80 years, the absence of a discharge summary was associated with a 127% increase in readmission rate within 7 days (95% CI 72 to 202% increase; P < 0.001) and a 55% increase within 28 days (95% CI 25 to 91% increase; P < 0.001) after discharge.

Conclusions: Delayed transmission or absence of a discharge summary is associated with readmission of the patient; more so in patients less than 80 years old. If no summary is generated by 7 days after discharge, the rate of readmission within 7 or 28 days after discharge is indistinguishable from no summary being written at all.
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http://dx.doi.org/10.1111/j.1365-2753.2011.01772.xDOI Listing
February 2013

Stability of plasma creatinine concentrations in acute complex long-stay admissions to a general medical service.

Clin Med (Lond) 2010 Dec;10(6):540-3

University of Adelaide, Australia.

Assessment of glomerular filtration rate (GFR) is essential for calculating safe dosages of renally cleared drugs. Formulae for estimating reliable GFRs assume that plasma creatinine concentrations are stable. This study evaluates the variability of plasma creatinine (PCr) concentrations in patients admitted acutely to hospital. From 2,293 newly admitted patients, those in whom a subsequent clinically significant change (> 20%) in PCr had occurred were identified. Median age was 81.1 years. Median baseline PCr was 90 umol/l (eGFR 60 ml/min). In total, 46.3% of the patients had a PCr that varied > 20% from baseline three to seven days following admission. A 10-year increase in age increased the odds of a rise in PCr over the next week by 11.1% (odds ratio = 1.11, 95% confidence interval = 1.03, 1.20; p = 0.007). Overall, baseline creatinine was a poor predictor of subsequent variation in PCr. GFR formulae for calculating renally-cleared drug dosages should be used with caution in elderly patients admitted acutely to hospital.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4951856PMC
http://dx.doi.org/10.7861/clinmedicine.10-6-540DOI Listing
December 2010

Aviation and patient safety. Send in the marines?

BMJ 2011 Feb 8;342:d801. Epub 2011 Feb 8.

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http://dx.doi.org/10.1136/bmj.d801DOI Listing
February 2011

The selection of acute medical admissions for a short-stay unit.

Intern Emerg Med 2011 Aug 14;6(4):321-7. Epub 2010 Dec 14.

Department of General Medicine, Flinders Medical Centre and Flinders University, Flinders Drive, Bedford Park, Adelaide, SA, 5042, Australia.

Objective of this study is to evaluate the selection of patients to be admitted to a hospital medical short-stay unit (SSU) where acute medical admissions with a predicted length of stay of between 24 and 72 h are managed. This is a retrospective observational study evaluating outcomes of all admissions to the medical SSU between January 2005 and December 2008. Factors that influence inappropriate allocation of patients to the SSU or alternative longer stay medical units were evaluated. Length of stay (LOS), mortality, Charlson score, admission to intensive care unit (ICU) (from the SSU), discharge diagnosis, and 7-day readmission rate were analysed. Over 4 years, 45% of the general medical inpatient take, 9,125 admission episodes, were managed by the medical SSU. On an average, 72% of these admissions to the SSU stayed fewer than 72 h. After excluding in-hospital deaths, there were 8,381 admissions to the general medical unit discharged within 72 h, and 77% of these were managed by the SSU during the study period. Inappropriate admissions to the SSU (LOS more than 72 h) tended to be older patients with more complex medical comorbidities. Other factors contributing to prolonged stay in the SSU included weekend admissions, and transfers to the ICU. The 7-day readmission rate was low at 3%; the all-cause hospital mortality for patients admitted to the medical SSU was 2% despite a 32% increase in workload in the medical SSU over these 4 years. In the context of fixed resources and a steeply increasing patient workload, a large proportion of general medical patients can be managed in a medical SSU with the majority being discharged home within 72 h while keeping all-cause in-hospital mortality and readmission rates low. More accurate identification of appropriate patients on admission by using a physiological clinical score and addressing operational issues particularly on weekends could lead to a more efficient SSU.
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http://dx.doi.org/10.1007/s11739-010-0490-6DOI Listing
August 2011

Routine use of administrative data for safety and quality purposes--hospital mortality.

Med J Aust 2010 10;193(S8):S100-3

Flinders Medical Centre, Adelaide, SA, Australia.

Worldwide, current practice is to report hospital mortality using the hospital standardised mortality ratio (HSMR). An HSMR is generated by comparing an indirectly standardised expected mortality rate against a hospital's observed mortality rate. A hospital's HSMR can be compared with the overall outcomes for all hospitals in a population, or with peer hospitals. HSMRs should be used as screening tools that alert institutions to the need for further investigation, rather than as definitive measures of the quality of care provided by individual hospitals. HSMRs are computed from existing hospital administrative data sources, which are fit for such a purpose. The addition of clinical or physiological data does not, at present, add to the discriminative powers of the risk adjustment models used to adjust HSMR values for differences in hospitals' casemixes. There has been concern that HSMRs may be too variable over time for individual values to be interpretable. A study of HSMR outcomes in Australian hospitals confirmed earlier reports of the stability of the measure. Considerable progress has been made with developing Australian HSMRs for use as routine measures to improve the safety and quality of Australian hospital care.
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http://dx.doi.org/10.5694/j.1326-5377.2010.tb04022.xDOI Listing
October 2010

Hospital mortality ratios. Death is final: getting the balance right.

BMJ 2010 May 25;340:c2741. Epub 2010 May 25.

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http://dx.doi.org/10.1136/bmj.c2741DOI Listing
May 2010

Outcomes of establishing an acute assessment unit in the general medical service of a tertiary teaching hospital.

Med J Aust 2010 Apr;192(7):384-7

Department of General Medicine, Flinders Medical Centre and Flinders University, Adelaide, SA, Australia.

Objective: To evaluate the impact of an acute assessment unit (AAU) on length of hospital stay (LOS), emergency department (ED) waiting times, direct discharge rate, unplanned readmission rate and all-cause hospital mortality of general medical patients.

Design And Setting: Retrospective comparison of data for general medical patients admitted to a tertiary teaching hospital in Adelaide, South Australia, before and after the establishment of an AAU (reference years, 2003 [before] and 2006 [after]).

Main Outcome Measures: Mean LOS, ED waiting times and all-cause hospital mortality during calendar years 2003 (pre-establishment) and 2006 (post-establishment).

Results: Following the establishment of an AAU, the mean LOS shortened (from 6.8 days in 2003 to 5.7 days in 2006; P < 0.001) despite a 50.5% increase in the number of admissions (from 2652 to 3992). The number of admitted patients waiting in the ED more than 8 hours for a hospital bed decreased (from 28.7% to 17.9%; P < 0.001), as did the number waiting more than 12 hours (from 20.2% to 10.4%; P < 0.001). The rates of unplanned readmission within 7 and 28 days did not change. The all-cause hospital mortality for general medical admissions was 4.6% in 2003 v 3.7% in 2006 (P = 0.056).

Conclusion: The establishment of an AAU within the general medical service coincided with decreases in both LOS and ED waiting times, despite a 50% increase in admissions. This structural reform in the process of acute medical care may have contributed to the improvement in these key health care performance indices without compromising the quality of patient care.
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http://dx.doi.org/10.5694/j.1326-5377.2010.tb03560.xDOI Listing
April 2010

Measurement for improvement: a survey of current practice in Australian public hospitals.

Med J Aust 2008 Jul;189(1):35-40

Clinical Epidemiology and Health Service Evaluation Unit, Royal Melbourne Hospital, Melbourne, VIC, Australia.

Objective: To identify patient safety measurement tools in use in Australian public hospitals and to determine barriers to their use.

Design: Structured survey, conducted between 4 March and 19 May 2005, designed to identify tools, and to assess current use of, levels of satisfaction with, and barriers to use of tools for measuring the domains and subdomains of: organisational capacity to provide safe health care; patient safety incidents; and clinical performance.

Participants And Setting: Hospital executives, managers and clinicians from a nationwide random sample of Australian public hospitals stratified by state and hospital peer grouping.

Main Outcome Measures: Tools used by hospitals within the three domains and their subdomains; patient safety tools and processes identified by individuals at these hospitals; satisfaction with the tools; and barriers to their use.

Results: Eighty-two of 167 invited hospitals (49%) responded. The survey ascertained a comprehensive list of patient safety measurement tools that are in current use for measuring all patient safety domains. Overall, there was a focus on use of processes rather than quantitative measurement tools. Approximately half the 182 individual respondents from participating hospitals reported satisfaction with existing tools. The main reported barriers were lack of integrated supportive systems, resource constraints and inadequate access to robust measurement tools validated in the Australian context. Measurement of organisational capacity was reported by 50 (61%), of patient safety incidents by 81 (99%) and of clinical performance by 81 (99%).

Conclusion: Australian public hospitals are measuring the safety of their health care, with some variation in measurement of patient safety domains and their subdomains. Improved access to robust tools may support future standardisation of measurement for improvement.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01893.xDOI Listing
July 2008

Health services under siege: the case for clinical process redesign.

Med J Aust 2008 03;188(S6):S9-13

Health Services Performance Improvement, NSW Health, Sydney, NSW, Australia.

*Public health services are struggling to cope with rising demand. *Strain on health services manifests as longer waiting lists for surgery, queuing in the emergency departments, increased rates of adverse events, and delays in discharge, particularly for older patients. *Traditional responses are not resolving these problems. *Analysis shows that the day-to-day system processes underlying clinical care are poorly designed and do not produce a well planned, well coordinated patient journey. *Numerous disconnections along the continuum of care have a cumulative effect in obstructing patient flow and causing frustration for patients and staff. *Rigorous clinical process redesign methods can significantly improve performance, even in the face of rising demand.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01667.xDOI Listing
March 2008

Implementing and sustaining transformational change in health care: lessons learnt about clinical process redesign.

Med J Aust 2008 03;188(S6):S32-5

NSW Health, Sydney, NSW, Australia.

*Clinical process redesign has enabled significant improvements in the delivery of health care services in emergency departments and elective surgery programs in New South Wales and at Flinders Medical Centre in South Australia, with tangible benefits for patients and staff. *The principles used in clinical process redesign are not new; they have been applied in other industries with significant gains for many years, but have only recently been introduced into health care systems. *Through experience with clinical process redesign, we have learnt much about the factors critical to the success of implementing and sustaining this process in the health care setting. *The key elements for success are leadership by senior executives, clinical leadership, team-based problem solving, a focus on the patient journey, access to data, ambitious targets, strong performance management, and a process for maintaining improvement.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01672.xDOI Listing
March 2008

Redesigning care at the Flinders Medical Centre: clinical process redesign using "lean thinking".

Med J Aust 2008 03;188(S6):S27-31

Flinders Medical Centre, Adelaide, SA, Australia.

*The Flinders Medical Centre (FMC) Redesigning Care program began in November 2003; it is a hospital-wide process improvement program applying an approach called "lean thinking" (developed in the manufacturing sector) to health care. *To date, the FMC has involved hundreds of staff from all areas of the hospital in a wide variety of process redesign activities. *The initial focus of the program was on improving the flow of patients through the emergency department, but the program quickly spread to involve the redesign of managing medical and surgical patients throughout the hospital, and to improving major support services. *The program has fallen into three main phases, each of which is described in this article: "getting the knowledge"; "stabilising high-volume flows"; and "standardising and sustaining". *Results to date show that the Redesigning Care program has enabled the hospital to provide safer and more accessible care during a period of growth in demand.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01671.xDOI Listing
March 2008

Clinical process redesign for unplanned arrivals in hospitals.

Med J Aust 2008 03;188(S6):S18-22

Health Services Performance Improvement, NSW Health, Sydney, NSW, Australia.

*Emergency department performance had been deteriorating in NSW Health facilities and at Flinders Medical Centre before a fundamentally new approach involving a redesign method, additional bed capacity and more rigorous hospital performance management was applied. *Redesign was undertaken in over 60 hospitals in New South Wales. *Numerous disconnections and misalignments in the process of care delivery have been uncovered during the diagnostic phase of this redesign. *Solutions addressed the entire patient journey through the hospital, to produce smoother patient flow along the continuum of care. *To achieve a sustained improvement in performance, numerous solutions must be simultaneously implemented in each hospital. *With this multipronged approach, a turnaround in NSW emergency access performance has been achieved in the face of rising demand for services; the improvement has continued over 3 years. *This article reports on our findings from system-wide redesign for unplanned hospital attendances.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01669.xDOI Listing
March 2008

Patient journeys: the process of clinical redesign.

Med J Aust 2008 03;188(S6):S14-7

Flinders Medical Centre, Adelaide, SA, Australia.

*Clinical process redesign is a successful improvement method that has been used to increase access to health services in 60 public hospitals across New South Wales, and at Flinders Medical Centre (FMC) in South Australia. *The method focuses on the patient journey as the primary improvement locus, and uses process mapping to identify the value-adding steps in that journey; it involves redesign teams identifying and eliminating non-value-adding steps to improve flow and reduce delays in access to emergency and elective care. *The method engages clinicians, managers, patients and carers, and delivers real gains in health care delivery. *This article outlines the clinical process redesign programs being used by NSW Health and at FMC.
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http://dx.doi.org/10.5694/j.1326-5377.2008.tb01668.xDOI Listing
March 2008

Development of a modified diagnostic classification system for voice disorders with inter-rater reliability study.

Logoped Phoniatr Vocol 2007 ;32(3):99-112

Department of Psychiatry, Flinders University, and Clinical Epidemiology, Flinders Medical Centre, South Australia, Australia.

Diversity in nomenclature and on-going dilemmas over the conceptual bases for the classification of voice disorders make it virtually impossible for the collation and accurate comparison of evidence-based data across different clinical settings. This has significant implications for treatment outcome studies. The first aim of this study was to develop a modified diagnostic classification system for voice disorders with clearly defined operational guidelines by which we might reliably distinguish voice disorders from one another. The second aim was to establish the face validity and reliability of the system as an effective diagnostic tool for the allocation of patients to different diagnostic groups for clinical and research purposes. After the Diagnostic Classification System for Voice Disorders (DCSVD) had been developed, it was used in an inter-rater reliability study for the independent assessment of 53 new consecutive patients referred to the Voice Analysis Clinics of three tertiary hospitals. There were three raters present for the assessment and diagnostic allocation of each patient. The high levels of inter-rater reliability suggest this may be a robust classification system that has good face validity and even at this early stage, strong construct validity.
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http://dx.doi.org/10.1080/14015430701431192DOI Listing
February 2008

The South Australian couples sildenafil study: double-blind, parallel-group randomized controlled study to examine the psychological and relationship consequences of sildenafil use in couples.

J Sex Med 2007 Jul;4(4 Pt 2):1126-35

The Queen Elizabeth Hospital--Psychiatry, Adelaide, Australia.

Introduction: The South Australian Couples Sildenafil (SACS) study sought to look more closely at the role of sexual functioning in couples by exploring the impact of treatment for erectile dysfunction (ED) with sildenafil.

Aim: The SACS study investigated the individual and dyadic impact of the drug sildenafil (Viagra) on couples over a 6-month period.

Main Outcome Measures: A range of outcome measures were utilized including the Dyadic Adjustment Scale (DAS), the International Index of Erectile Function (IIEF), and the Erectile Dysfunction Inventory of Treatment Satisfaction.

Methods: Couples were recruited through the use of local media and general practitioners. Couples were randomly allocated to placebo or active drug with the option of using up to one study tablet per day for 6 months. Couples were reviewed at 2 weeks, 4 weeks, 8 weeks, 3 months, and 6 months.

Results: There were 108 couples who were eligible for the study with the eventual analysis including 49 couples in the active treatment group and 47 in the placebo group with similar demographic and background profiles found in both groups. A large number of psychosocial, quality-of-life, and sexual measures were recorded at the end of the trial for both male subjects and their female partners. Predictably, the erectile response in the active treatment group showed a significant improvement as measured by the IIEF although no change was found between the active and placebo groups in relationship functioning as measured by the DAS scores.

Conclusions: The SACS study found no difference between treatment arms with regard to relationship functioning after the use of sildenafil for ED. Potential contributing factors to a "no change" result are discussed. The SACS study adds to the available literature on psychological and interpersonal factors in the treatment of ED which have not been sufficiently investigated until recently.
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http://dx.doi.org/10.1111/j.1743-6109.2007.00536.xDOI Listing
July 2007

Lean thinking across a hospital: redesigning care at the Flinders Medical Centre.

Aust Health Rev 2007 Feb;31(1):10-5

Flinders Medical Centre, Bedford Park, Adelaide, SA 5042, Australia.

Lean thinking is a method for organising complex production processes so as to encourage flow and reduce waste. While the principles of lean thinking were developed in the manufacturing sector, there is increasing interest in its application in health care. This case history documents the introduction and development of Redesigning Care, a lean thinking-based program to redesign care processes across a teaching general hospital. Redesigning Care has produced substantial benefits over the first two-and-a-half years of its implementation, making care both safer and more accessible. Redesigning Care has not been aimed at changing the specifics of clinical practice. Rather, it has been concerned with improving the flow of patients through clinical and other systems. Concepts that emerged in the manufacturing sector have been readily translatable into health care. Lean thinking may play an important role in the reform of health care in Australia and elsewhere.
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February 2007