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Diabetes-related foot ulcers (DFUs) affect around 20 million people annually and are a leading cause of the global disability burden (1). DFUs are complex to treat, take months to heal, result in poorer quality of life, and place patients at high risk of hospitalization and amputation. Thus, understanding the influence that different factors have on healing of DFUs is vital. Various demographic, comorbidity, limb, ulcer, and treatment-related factors associated with healing of DFUs have been identified from cohorts attending mostly metropolitan tertiary centers (2–4). However, very few studies have prospectively investigated the influence that these and other factors have on healing in more real-world DFU cohorts attending geographically diverse secondary and tertiary centers. Therefore, we aimed to investigate the influence of 34 factors on healing in a large real-world DFU cohort. We prospectively examined 4,832 consecutive patients with DFU(s) that presented for their first visit to 1 of 65 secondary or tertiary diabetic foot services, across 15 of 17 regions in Queensland (Australia), between July 2011 and December 2017. A DFU was defined as a full-thickness wound below the ankle on a person with diabetes. For DFU clinical and research purposes, foot-related health professionals using the Queensland High Risk Foot Form (QHRFF) directly examined each patient clinically at their first (and subsequent) visit for 4 demographic, 9 comorbidity, 6 limb, 3 ulcer, and 12 treatment factors (5). For those with multiple DFUs, we used the most severe score for each factor and the combined ulcer size from all DFUs (5). Factors from the first visit were used as the baseline. Subsequent visit examinations determined if the DFU(s) healed, …

Aims\ud To investigate factors independently associated with time-to-(being)-ulcer-free, time-varying effects and predict adjusted ulcer-free probabilities, in a large prospective cohort with diabetes-related foot ulcers (DFU) followed-up for 24 months.\ud Methods\ud Patients presenting with DFU(s) to 65 Diabetic Foot Services across Queensland, Australia, between July-2011 and December-2017 were included. Demographic, comorbidity, limb, ulcer, and treatment factors were captured at presentation. Patients were followed-up until ulcer-free (all DFU(s) healed), amputation, death or two years. Factors associated with time-to-ulcer-free were investigated using both Cox proportional hazards and flexible parametric survival models to explore time-varying effects and plot predicted adjusted ulcer-free probability graphs. \ud Results\ud Of 4,709 included patients (median age 63 years, 69.5% male), median time-to-ulcer-free was 112 days (IQR:40->730), with 68.4% ulcer-free within two years. Factors independently associated with longer time-to-ulcer-free were each year of age younger than 60 years, living in a regional or remote area, smoking, neuropathy, peripheral artery disease (PAD), ulcer size >1cm2, deep ulcer and mild infection (all p

Background Diabetes-related foot ulcers (DFU) take months to heal, reduce patient’s quality-of-life, and induce large healthcare expenditure. Various factors have been identified to influence DFU healing at fixed periods, however, data on factors associated with time-to-healing is scarce. Methods Patients presenting with DFU to Diabetic Foot Services across Queensland, Australia between July 2011 and December 2017 were included and had their demographics, disease history and treatments examined at baseline. Outcome of interest was healing of all ulcers within two-year follow-up time. Time-to-healing and associated factors were examined using flexible parametric survival models, which easily enabled including time-varying coefficients and predicting proportions healed. Results Of 4,709 included patients (median age 63 years, 69.5% male, 10.5% Indigenous), median time-to-healing was 112 days, and 68% healed within two years. Younger age ( Conclusions This study identified novel and confirmatory factors influencing time-to-healing over 24 months in a large real-world cohort of people with diabetes-related foot ulcers. Visualizing the adjusted predicted proportion healed revealed the influence each factor had on healing rates over time. Key messages Flexible parametric survival model provided flexibility in investigating time-varying effects and outcome prediction in those with diabetes-related foot ulcer healing.

Background Implementation of guideline-based care for diabetes-related foot ulcers (DFU) in clinical practice is typically sub-optimal. We aimed to evaluate the cost-effectiveness of implementing different incremental increases in guideline-based care scenarios, compared with current practice, using discrete event simulation models. Methods The costs and effectiveness of current practice (identified as 30% receiving guideline-based care, remainder (70%) non-guideline-based care) were compared with seven hypothetical scenarios of implementing incremental increases in guideline-based care (40%, 50%, 60%, 70%, 80%, 90%, 100%) and evaluated using discrete event simulation models, including important events of disease history and parameterised by a large DFU cohort. Incremental cost-effectiveness ratio for each scenario was calculated and compared to willingness-to-pay of AUD28,000 per quality-adjusted life-years (QALY). Probability sensitivity analysis was conducted to incorporate parameter uncertainty by 2,000 random simulations. Results Under a three-year time-horizon, the seven scenarios (40%-100% guideline-based care) were estimated to incrementally save $901-$1843 (AUD 2020) and provide 0.017-0.056 more QALY per person, with all scenarios being cost-saving & more effective than current practice (30% guideline-based care). From probability sensitivity analyses we were increasingly confident (69.7%-89.8% confident) that implementing increased incremental scenarios (40%-100% guideline-based care) would be cost-effective compared with current practice (59.8%-73.4% confident). Conclusions All scenarios incrementally increasing guideline-based care were evaluated to be cost-saving and more effective than current practice according to this discrete event simulation modelling based on a large real-world cohort. Key messages Our findings support the cost-effectiveness of implementing any incremental increase in guideline-based care compared to current practice.

In addition to affecting quality of life, diabetic foot ulcers (DFUs) impose an economic burden on both patients and the health system. This study developed a Markov model to analyse the cost-effectiveness of implementing optimal care in comparison with the continuation of usual care for diabetic patients at high risk of DFUs in the Australian setting. The model results demonstrated overall 5-year cost savings (AUD 9100·11 for those aged 35–54, $9391·60 for those aged 55–74 and $12 394·97 for those aged 75 or older) and improved health benefits measured in quality-adjusted life years (QALYs) (0·13 QALYs, 0·13 QALYs and 0·16 QALYs, respectively) for high-risk patients receiving optimal care for DFUs compared with usual care. Total cost savings for Australia were estimated at AUD 2·7 billion over 5 years. Probabilistic sensitivity analysis showed that optimal care always had a higher probability of costing less and generating more health benefits. This study provides important evidence to inform Australian policy decisions on the efficient use of health resources and supports the implementation of evidence-based optimal care in Australia. Furthermore, this information is of great importance for comparable developed countries that could reap similar benefits from investing in these well-known evidence-based strategies.

In addition to affecting quality of life, diabetic foot ulcers (DFUs) impose an economic burden on both patients and the health system. This study developed a Markov model to analyse the cost‐effectiveness of implementing optimal care in comparison with the continuation of usual care for diabetic patients at high risk of DFUs in the Australian setting. The model results demonstrated overall 5‐year cost savings (AUD 9100·11 for those aged 35–54, $9391·60 for those aged 55–74 and $12 394·97 for those aged 75 or older) and improved health benefits measured in quality‐adjusted life years (QALYs) (0·13 QALYs, 0·13 QALYs and 0·16 QALYs, respectively) for high‐risk patients receiving optimal care for DFUs compared with usual care. Total cost savings for Australia were estimated at AUD 2·7 billion over 5 years. Probabilistic sensitivity analysis showed that optimal care always had a higher probability of costing less and generating more health benefits. This study provides important evidence to inform Australian policy decisions on the efficient use of health resources and supports the implementation of evidence‐based optimal care in Australia. Furthermore, this information is of great importance for comparable developed countries that could reap similar benefits from investing in these well‐known evidence‐based strategies.

Objective There is a paucity of research on patients presenting with uninfected diabetic foot ulcers (DFU) that go on to develop infection. We aimed to investigate the incidence and risk factors for developing infection in a large regional cohort of patients presenting with uninfected DFUs. Methods We performed a secondary analysis of data collected from a validated prospective state-wide clinical diabetic foot database in Queensland (Australia). Patients presenting for their first visit with an uninfected DFU to a Diabetic Foot Service in one of thirteen Queensland regions between January 2012 and December 2013 were included. Socio-demographic, medical history, foot disease history, DFU characteristics and treatment variables were captured at the first visit. Patients were followed until their DFU healed, or if their DFU did not heal for 12-months, to determine if they developed a foot infection in that period. Results Overall, 853 patients were included; mean(standard deviation) age 62.9(12.8) years, 68.0% male, 90.9% type 2 diabetes, 13.6% indigenous Australians. Foot infection developed in 342 patients for an overall incidence of 40.1%; 32.4% incidence in DFUs healed

Methods Data on all primary diabetes foot-related admissions in Queensland from 2005-2010 was obtained using diabetes foot-related ICD-10-AM (hospital discharge) codes. Queensland diabetes foot-related admission incidences were calculated using general population data from the Australian Bureau of Statistics. Furthermore, diabetes foot-related sub-group admissions were analysed. Chi-squared tests were used to assess changes in admissions over time.

Background Lower extremity amputation (LEA) results in significant hospitalisation, rehabilitation, morbidity and mortality. In 2004, 3,400 LEAs, with an average length of stay of 26 days, were performed in Australia for diabetic foot complications alone. However, diabetic foot complications are commonly recognised as the most common cause of “non-traumatic” LEA internationally. Unfortunately, there seems to be a paucity of Australian data on total numbers and causes of all LEAs. This retrospective audit aimed to evaluate underlying primary indications for LEA at a major Australian tertiary hospital.

Objective. The aim of this paper is to report the clinical practice changes resulting from strategies to standardise diabetic foot clinical management in three diverse ambulatory service sites in Queensland, Australia. Methods. Multifaceted strategies were implemented in 2008, including: multidisciplinary teams, clinical pathways, clinical training, clinical indicators, and telehealth support. Prior to the intervention, none of the aforementioned strategies were used, except one site had a basic multidisciplinary team. A retrospective audit of consecutive patient records from July 2006 to June 2007 determined baseline clinical activity (n = 101). A clinical pathway teleform was implemented as a clinical activity analyser in 2008 (n = 327) and followed up in 2009 (n = 406). Pre- and post-implementation data were analysed using Chi-square tests with a significance level set at P

Objectives: To examine the relation between treatment intensity and level of risk in routine hospital care of patients with acute coronary syndromes (ACS), and to identify independent predictors of use or omission for each of eight evidence-based treatments. Design: Retrospective cohort study of patients fulfilling case definition for ACS in whom absolute risk of adverse outcomes was quantified (as low, moderate, or high risk) using formal prediction rules, and for whom treatment eligibility was determined using expertagreed criteria. Participants and setting: 3912 consecutive or randomly selected patients admitted to 21 hospitals in Queensland, Australia between 1 August 2001 and 31 December 2005. Results: The proportions of eligible patients receiving treatment varied inversely with risk level in regard to reperfusion therapies of fibrinolytic therapy or primary angioplasty (low risk, 88.3%; moderate risk, 61.9%; high risk, 18.2%; P < 0.001), heparin (91.4%; 83.7%; 72.8%; P < 0.001) and early invasive intervention (33.6%; 24.0%; 18.5%; P

Methods Data on all Queensland diabetes-related lower extremity amputation admissions from 2005-2010 was obtained using diabetes amputation-related ICD-10-AM (hospital discharge) codes. Queensland diabetes amputation incidences were calculated for both general and diabetes populations using population data from the Australian Bureau of Statistics and National Diabetes Services Scheme respectively. Chi-squared tests were used to assess changes in amputation incidence over time.

The aim of this study was to test the effectiveness of digital pen and paper technology (DP&PT) to capture clinical pathway variance data in real time and at the point of care for patients on an arthroplasty pathway. This study was conducted across multiple departments providing orthopaedic services in a public health care facility. Treating clinicians were required to record variance data on a predefined coded template, and these data were uploaded to a database for analysis and reporting. The information could be represented in a web-based user interface for immediate review. User acceptance, length of stay (LOS), accuracy of data, and reliability of the DP&PT hardware were measured. User acceptance was high; LOS reduced; and the data and hardware were, respectively, found to be accurate and robust. This technology provides a dependable, real-time solution to transform handwritten clinical data into a digital format. The data available will help inform clinicians of areas for clinical practice improvement, and provide ongoing monitoring of care processes for patients on a clinical pathway. Future studies should aim to assess if using this method to capture variance data is a more efficient and effective means of informing clinical decision making than retrospective review processes.

Results Overall, 2,034 people presented with a foot ulcer in 2012. Mean age was 63(±14) years and 67.8% were male. Co-morbidities included 85% had diabetes, 49.7% hypertension, 39.2% dyslipidaemia, 25.6% cardiovascular disease, 13.7% kidney disease and 12.2% smoking. Foot ulcer types included 51.6% neuropathic, 17.8% neuroischaemic, 7.2% ischaemic, 6.6% post-surgical and 16.8% other; whilst 31% were infected. Clinical indicator results revealed 98% had their wound categorised, 51% received non-removable offloading, median ulcer healing time was 6-weeks and 37% had ulcer recurrence. Conclusion This paper details the largest foot ulcer database reported in Australia. People presenting with foot ulcers appear predominantly older, male with several co-morbidities. Encouragingly it appears most patients are receiving best practice care. These results may be a factor in the significant reduction of Queensland diabetes foot-related hospitalisations and amputations recently reported.