Australian Refined Diagnosis Related Groups Research Articles

Impact of COVID-19 on inpatient care related to skin conditions

The COVID-19 pandemic significantly affected our society and healthcare system. This study aims to evaluate the effects of COVID-19 on the number of hospitalized patients with dermatological diseases in Croatia, as well as the number of these patients treated surgically and conservatively, before (2017-2019) and during the pandemic (2020-2021). This is a retrospective, comparative study of the hospital admission rate for patients with skin, subcutaneous tissue, and breast disorders both before and during the pandemic. This study used data from the Croatian Institute of Public Health (CIPH) and the Croatian Health Insurance Fund (CHIF). Inpatient data for the CHIF data collection were categorized using the Australian Refined Diagnosis Related Groups (AR-DRGs). All hospital admissions for dermatology patients at all non-specialized hospitals in Croatia were tracked during two periods, before (2017-2019) and during the pandemic (2020-2021). The average number of dermatology patients in all hospitals fell by 29% during the pandemic. The overall number of dermatological patients admitted to hospitals fell by 32% in 2020 and by 26% in 2021 when compared to the number of patients admitted each year on average over the preceding 3 years. Additionally, there was an average 22% fall in surgical procedures performed during the pandemic. The only exception for surgical procedures is Major Breast Reconstruction for which is noted an increase, as also for Malignant Breast Disorders, Minor Complexity and Major Skin Disorders, Minor Complexity in a group of non-surgically treated patients. Examining the all consequences of the Croatian dermatological patient care interruption will require more investigation. Reduced access to medical care during the pandemic is anticipated to lead to later illness diagnosis, a later start to treatment, a poorer disease prognosis, as well as higher medical expenditures.

Fracture liaison service utilising an emergency department information system to identify patients effectively reduce re-fracture rate is cost-effective and cost saving in Western Australia.

ObjectivesTo assess the benefits of the Emergency Department Information System (EDIS)‐linked fracture liaison service (FLS).MethodsPatients identified through EDIS were invited to attend an FLS at the intervention hospital, the Sir Charles Gairdner Hospital (SCGS‐FLS). The intervention group was compared to usual care. Retrospective control (RC) at this hospital determined historical fracture risk (SCGH‐RC). Prospective control (PC) was from a comparator, Fremantle Hospital (FH‐PC). The main outcome measures were cost‐effectiveness from a health system perspective and quality of life by EuroQOL (EQ‐5D). Bottom‐up cost of medical care, against the cost of managing recurrent fracture (weighted basket), was determined from the literature and 2013/14 Australian Refined Diagnosis Related Groups (AR‐DRG) prices. Mean incremental cost‐effectiveness ratios were simulated from 5000 bootstrap iterations. Cost‐effectiveness acceptability curves were generated.ResultsThe SCGH‐FLS program reduced absolute re‐fracture rates versus control cohorts (9.2–10.2%), producing an estimated cost saving of AUD$750,168–AUD$810,400 per 1000 patient‐years in the first year. Between‐groups QALYs differed with worse outcomes in both control groups (p < 0.001).The SCGH‐FLS compared with SCGH‐RC and FH‐PC had a mean incremental cost of $8721 (95% CI −$1218, $35,044) and $8974 (95% CI −$26,701, $69,929), respectively, per 1% reduction in 12‐month recurrent fracture risk. The SCGH‐FLS compared with SCGH‐RC and FH‐PC had a mean incremental cost of $292 (95% CI −$3588, $3380) and −$261 (95% CI −$1521, $471) per EQ‐5D QALY gained at 12 months respectively. With societal willingness to pay of $16,000, recurrent fracture is reduced by 1% in >80% of patients.ConclusionsThis simple and easy model of identification and intervention demonstrated efficacy in reducing rates of recurrent fracture and was cost‐effective and potentially cost saving.

Clinical factors associated with increased length of stay and readmission in patients with medication-related hospital admissions: a retrospective study.

Adverse drug events (ADEs) remain a key contributor to hospitalisations, resulting in long hospital stays and readmissions. Information pertaining to the specific medications and clinical factors associated with these outcomes is limited. Hence, a better understanding of these factors and their relationship to ADEs is required. To investigate medications involved, clinical manifestations of ADE-related hospitalisations, and their association with length of stay and readmission. A retrospective medical record review of patients admitted to a major, tertiary referral hospital in NSW, Australia, from January 2019 to August 2020 was conducted. ADEs were identified using Australian Refined Diagnosis Related Group (AR-DRG) codes: X40, X61, X62 and X64. Medications were classified per the Anatomical Therapeutic Chemical (ATC) classification system and clinical symptoms were classified per the International Classification of Disease (ICD) 9-CM. Logistic regression was performed to assess the relationship between medication and presentation classes with length of stay (≥2 days vs<2 days) and readmission. There were 125 patients who met inclusion criteria (median age=64 [interquartile range, 45-75] years; 53.6% male). Anti-thrombotic agents, opioids, antidepressants, antipsychotics, insulins and NSAIDs were the most implicated pharmacological classes. Neurological medications and falls were associated with a length of stay ≥2 days (adjusted odds ratio [aOR] 3.92, 95% confidence interval [CI] 1.48-10.33 and aOR 3.24, 95% CI 1.05-10.06, respectively). Neurological medications and neurological and cognitive disorders were associated with an increased likelihood of 90-day readmission (aOR 2.63, 95% CI 1.05-6.57 and aOR 3.20, 95% CI 1.17-8.75, respectively). This study identified neurological medications as high-risk for increased length of stay and readmission in those hospitalised due to ADEs. This highlights the need for judicious prescribing and monitoring of these medications.

Modelling the cost of place of birth: a pathway analysis

BackgroundIn New South Wales (NSW), Australia there are three settings available for women at low risk of complications to give birth: home, birth centre and hospital. Between 2000 and 2012, 93.6% of babies were planned to be born in hospital, 6.0% in a birth centre and 0.4% at home. Availability of alternative birth settings is limited and the cost of providing birth at home or in a birth centre from the perspective of the health system is unknown.ObjectivesThe objective of this study was to model the cost of the trajectories of women who planned to give birth at home, in a birth centre or in a hospital from the public sector perspective.MethodsThis was a population-based study using linked datasets from NSW, Australia. Women included met the following selection criteria: 37-41 completed weeks of pregnancy, spontaneous onset of labour, and singleton pregnancy at low risk of complications. We used a decision tree framework to depict the trajectories of these women and Australian Refined-Diagnosis Related Groups (AR-DRGs) were applied to each trajectory to estimate the cost of birth. A scenario analysis was undertaken to model the cost for 30 000 women in one year.Findings496 387 women were included in the dataset. Twelve potential outcome pathways were identified and each pathway was costed using AR-DRGs. An overall cost was also calculated by place of birth: $AUD4802 for homebirth, $AUD4979 for a birth centre birth and $AUD5463 for a hospital birth.ConclusionThe findings from this study provides some clarity into the financial saving of offering more options to women seeking an alternative to giving birth in hospital. Given the relatively lower rates of complex intervention and neonatal outcomes associated with women at low risk of complications, we can assume the cost of providing them with homebirth and birth centre options could be cost-effective.

Weighted activity unit effect: evaluating the cost of diagnosis-related group coding.

Activity-based funding (ABF) is a means of healthcare reimbursement, where hospitals are allocated funding based on the number and mix of clinical activity. The ABF model is based solely on Australian refined diagnosis-related group (AR-DRG) classifications of hospital encounters. Each AR-DRG is allocated a weighted activity unit (WAU) translating to cost value to determine ongoing funding allocations for each hospital annually. We explored cost consequences of AR-DRG coding variances within our Medical Oncology department over a 6-month period. All inpatient encounters for medical oncology from 1 January to 30 June 2014 were identified and paired with actual AR-DRG coding sheets submitted by the hospital coders. Inpatient charts were manually reviewed by a Medical Oncology Registrar to capture any changes or additional AR-DRGs, which were subsequently evaluated for total WAU value variance. Applying 1 WAU = $4676 as per the 2014 Queensland model, cost consequences were calculated. A total of 116 encounters was identified for 72 patients. Of 116 patients, 95 (81%) had additional diagnoses captured, leading to an AR-DRG and WAU change in 26 encounters. The total reimbursement variance for this period was $143 404.07. Cost consequences resulted from: (i) use of abbreviations in clinical notes unable to be coded; and (ii) diagnoses not documented despite treatment delivered as per medication charts. Clinical note documentation ultimately determines the future funding of our healthcare system. Appropriate communication and education of medical staff and hospital coders are vital to ensure precise documentation and accurate AR-DRG coding for optimal and appropriate reimbursement in this funding model.

An Australian study of long-term hospital admissions and costs comparing patients with unintentional burns and uninjured people

BackgroundThe objective of this study was to describe and quantify the long-term hospital service use (HSU) after burn injury and associated costs in a population-based cohort of patients with unintentional burns and compare with uninjured people. MethodsThis retrospective population-based cohort study analysed de-identified linked health administrative data of all unintentional burns patients (n = 10,460) between 2000 and 2012 in Western Australia and a matched uninjured comparison cohort (n = 42,856). HSU after burn injury (annual admission counts and cumulative length of stay) was examined. HSU costs were based on the Australian Refined Diagnosis Related Groups (AR-DRGs) code on each record. Generalised linear models were used to examine and quantify associations between burn injury and long-term HSU and associated costs. ResultsThere were 48,728 hospitalisations after burn occurring within the study period in the burn cohort; in the uninjured comparison cohort, there were 53,244 post-study index hospitalisations. Of those in the burn cohort, 63.9% (n = 6828) had a further hospitalisation after burn injury; this compared with 40.4% (n = 17,297) in the uninjured cohort. After adjustment for socio-demographic and pre-existing health conditions the burn cohort had 2.48 times the hospitalisation rate compared to the uninjured cohort (95% CI: 2.33–2.65). The cost of post-index hospitalisations in the burn cohort totalled to $AUS248.3 million vs $AUS240.8 million in the uninjured cohort. After adjustment, the burn cohort had hospital costs 2.77 times higher than the uninjured controls (95% CI: 2.58–2.98). ConclusionsAfter adjustment for covariates, burn patients experienced greater hospital use for a prolonged period after the initial injury compared with uninjured people. The mean cost per episode of care was generally higher for members of the burn cohort compared to the uninjured cohort indicating either more complicated admissions or admissions for more expensive conditions.

A new clinical complexity model for the Australian Refined Diagnosis Related Groups

BackgroundThe Australian Refined Diagnosis Related Groups (AR-DRG) underwent a major review in 2014 with changes implemented in Version 8.0 of the classification. The core to the changes was the development of a new methodology to estimate the Diagnosis Complexity Level (DCL) and to aggregate the complexity level of individual diagnoses to the complexity of an entire episode, resulting in an Episode Clinical Complexity Score (ECCS). This paper provides an overview of the new methodology and its application in Version 8.0. MethodThe AR-DRG V8.0 refinement project was overseen by a Classifications Clinical Advisory Group and a Diagnosis Related Groups (DRG) Technical Group. Admitted Patient Care National Minimum Dataset and the National Hospital Cost Data Collection were used for complexity modelling and analysis. ResultIn total, Version 8.0 comprised 807 DRGs, including 3 error DRGs. Of the 321 Adjacent DRGs (ADRGs) that had a split, 315 ADRGs used ECCS as the only splitting variable while the remaining 6 ADRGs used splitting variables other than ECCS: 2 used age and 4 used transfer. Discussion and conclusionA new episode clinical complexity (ECC) model was developed and introduced in AR-DRG V8.0, replacing the original model introduced in the 1990s. Clear AR-DRG structure principles were established for revising the system. The new complexity model is conceptually based and statistically derived, and results in an improved relationship with actual variations in resource use due to episode complexity.

The surgical burden of disease and perioperative mortality in patients admitted to hospitals in Victoria, Australia: a population-level observational study

ObjectivesComprehensive reporting of surgical disease burden and outcomes are vital components of resilient health systems but remain under-reported. The primary objective was to identify the Victorian surgical burden of disease...

Costs and consequences of an intervention-based program to reduce hospital-acquired pressure injuries in one health district in Australia.

Objectives The aims of this study were to determine the costs of hospital-acquired pressure injuries (HAPIs) in one local health district in Australia and compare the costs and consequences of an intervention-based program with current practice to reduce HAPI incidence and prevalence. Methods A retrospective cost-consequence analysis was conducted using HAPI incidence rate per occupied bed days, point prevalence rates, Australian Refined-Diagnosis Related Group (AR-DRG) costs and the costs of the program to reduce the HAPI rate. Data were analysed for two phases: preprogram implementation (1 June 2015-1 June 2016) and postprogram implementation (1 August 2016-31 July 2017). Results The HAPI intervention-based program resulted in a 51.4% reduction in the incidence of HAPI (from 1.46 per occupied bed day in 2014 to 0.71 per occupied bed day in 2017) and a 71.6% reduction in the prevalence of HAPI (from 6.7% in 2014 to 1.9% in 2017). The occurrence of HAPI added an average cost of A$3332 per episode, such that the overall program, including implementation, reduced costs by A$837387. The greatest cost reduction was due to the cessation of washable and disposable underpads. The largest contributor to the cost of HAPI prevention was for education and training regarding HAPI prevention initiatives. Conclusions The HAPI intervention-based program halved the incidence and substantially reduced the prevalence of HAPI, with a 23.1% cost saving compared with the previous approach to preventing HAPIs. What is known about the topic? HAPIs are costly to the individual, the organisation and health system. The prevention of HAPIs is a priority in Australia. There is limited research on the economic effect of HAPIs and the costs and consequences for hospitals of implementation strategies to reduce their incidence. What does this paper add? This paper informs health policy and decision makers about the costs and consequences for a local health district of a program to reduce and prevent HAPIs. This paper reports the economic effect of HAPIs, including hospital episode costs per HAPI and length of stay, on one local health district. What are the implications for practitioners? This cost-consequence analysis has shown that the program to reduce HAPIs resulted in a reduction in expenditure and positive patient outcomes. Such a program is potentially transferable to other healthcare settings.

A review of the complexity adjustment in the Korean Diagnosis-Related Group (KDRG).

The Korean Diagnosis-Related Groups (KDRG) was revised in 2003, modifying the complexity adjustment mechanism of the Australian Refined Diagnosis-Related Groups (AR-DRGs). In 2014, the Complication and Comorbidity Level (CCL) of the existing AR-DRG system was found to have very little correlation with cost. Based on the Australian experience, the CCL for KDRG version 3.4 was reviewed. Inpatient claim data for 2011 were used in this study. About 5,731,551 episodes, which had one or no complication and comorbidity (CC) and met the inclusion criteria, were selected. The differences of average hospital charges by the CCL were analysed in each Adjacent Diagnosis-Related Group (ADRG) using analysis of variance followed by Duncan's test. The patterns of differences were presented with R 2 in three patterns: The CCL reflected the complexity well (VALID); the average charge of CCL 2, 3, 4 was greater than CCL 0 (PARTIALLY VALID); the CCL did not reflect the complexity (NOT VALID). A total of 114 (19.03%), 190 (31.72%) and 295 (49.25%) ADRGs were included in VALID, PARTIALLY VALID and NOT VALID, respectively. The average R 2 for hospital charge of CCL was 4.94%. The average R 2 in VALID, PARTIALLY VALID and NOT VALID was 4.54%, 5.21%, and 4.93%, respectively. The CCL, the first step of complexity adjustment using secondary diagnoses, exhibited low performance. If highly accurate coding data and cost data become available, the performance of secondary diagnosis as a variable to reflect the case complexity should be re-evaluated. Lack of reviewing the complexity adjustment mechanism of the KDRG since 2003 has resulted in outdated CC lists and levels that no longer reflect the current Korean healthcare system. Reliable cost data (vs. charge) and accurate coding are essential for accuracy of reimbursement.

Beyond DRG: The effect of socio-economic indicators on inpatient resource allocation in Australia

Financing in Australia's public hospital works through the Australian Refined Diagnosis Related Groups (AR-DRGs) with separations to specific DRG groups based on medical diagnosis or surgical procedure, patient's age, mode of separation, clinical complexity and complications. This paper aims at assessing how the AR-DRGs reflect the efficiency and equity of the hospitals resource allocation. Using administrative data of all acute public hospital admissions and length of stay (LOS) as a proxy for hospital costs, this paper showed that patients’ socio-economic (SES) characteristics are a strong determinant of health care utilization. Our results revealed that the lower the SES, the longer the LOS and hence more utilization of the inpatient resources. Therefore, omitting SES from the risk adjusters list and solely focusing on DRG- based compensation penalizes hospitals catering to lower SES populations. Our findings further support the idea of smaller/remote hospitals based on block funding.

Cost analysis of the CTLB Study, a multitherapy antenatal education programme to reduce routine interventions in labour

ObjectiveTo assess whether the multitherapy antenatal education ‘CTLB’ (Complementary Therapies for Labour and Birth) Study programme leads to net cost savings.DesignCost analysis of the CTLB Study, using analysis of outcomes...

Pricing the national health insurance scheme in Qatar – opportunities and challenges

Background In 2013, Qatar introduced a national health insurance scheme, called “Seha.” Stage 1 of the scheme covered women aged 12 years and older for health care and maternity services. Stage 2 was launched in 2014, and covered all Qatari nationals for a much broader set of services. In the future, Stages 3 and 4 will extend coverage to all non-Qatari residents within the country as well as visitors. The National Health Insurance Company (NHIC) manages Seha, with a Third-Party Administrator (TPA) contracted to manage provider claims. The Supreme Council of Health (SCH) acts as the scheme’s overall regulator, and is responsible for activities such as specifying coverage and approving pricing. A range of steps was taken to prepare for Seha’s launch. SCH mandated clinical coding using ICD-10AM, and hospitals recruited and/or trained clinical coders to use this system. The Australian Refined Diagnosis Related Groups (AR-DRGs) tool was adopted, and public sector hospitals embarked on the clinical costing of their services. In Stage 1, SCH decided to use a bundled payment method for health care services. AR-DRGs were chosen for pricing acute inpatient care, using 76 AR-DRGs relevant for women and maternity services. A modification of the Australian Tier 2 classification was adopted for specialist medical services, using 9 classes relevant to women’s health. In addition, a primary health classification was adopted based on 4 levels of complexity. Mammography and MRI were unbundled from the specialist and primary care service, but other imaging, laboratory, and pharmacy services were bundled into the price. Although this was not included in Stage 1, previous work had also recommended the adoption of Urgency Related Groups (URGs) classification for emergency care. Stage 1 was implemented with a limited network including both private and public hospitals. The launch of Seha involved providing information to prospective providers and conducting subsequent sessions to assist in operationalizing the price schedule and business rules. Seha’s challenges for Stage 2 included: pricing a much wider range of services than were included in Stage 1; expanding the scheme to a wider range of providers, including “stand alone” providers (i.e. those without the capacity to provide ancillary services); and addressing the limited availability of activity and cost information from the private sector.

Incidence and burden of hospital-treated sports injury in people aged 15+ years in Victoria, Australia, 2004-2010: Future epidemic of osteoarthritis?

Purpose: Previous sports injury is a known risk factor for subsequent osteoarthritis, but population-based rates of sports injury are unknown. Osteoarthritis places a large burden on health care systems. Any increase in the incidence of joint-related sports injuries is likely to further increase this burden. Therefore a greater understanding of the rate and burden of sports injury, is urgently required if a potential future epidemic of OA is to be avoided. The aims of this study were to: i) describe the trends in the population incidence and burden of all hospital-treated sports injury in Victoria, Australia in adults aged 15+ years; ii) determine the incidence of sports-relates lower limb and knee injuries as a subset of these injuries; and iii) quantify their population health burden in terms of direct hospital treatment cost and length of stay. Methods: Health sector data relating to people aged 15+ years, for the calendar years 2004-2010 inclusive, was extracted from the Victorian Admitted Episodes Dataset and Victorian Emergency Minimum Dataset. Data relating to sports injuries were identified using International Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modifications (ICD-10-AM) diagnosis codes S70-S99, which included injuries to the hip, thigh, knee, lower leg, ankle, foot and toes. Knee and lower leg injuries, as a subset of all lower limb injuries were identified using the codes S80-S89; while dislocation, sprain or strain of the joints and ligaments of the knee were identified using the code S83. Rates of sports participation were collected from annual Exercise, Recreation and Sport Surveys. Trends in injury frequency and rates were determined. Economic burden was calculated as the average Victorian cost per Australian Refined Diagnosis Related Group (AR-DRG) for the relevant year for each admission. Results: Between the dates January 2004 and December 2010 there were 165,496 hospital treated sports injuries in people aged 15+ years in Victoria, Australia. Of these, 59,399 (35.9% of all sports injury cases) were lower limb injuries, 29,430 (17.8%) were injuries to the knee and lower leg and 11,749 (7.1%) were knee dislocations, strains and sprains. The overall annual rate of hospital treated sports injuries increased by 24% (p=0.001) over the 7-years. The annual rate of lower limb sports injuries increased by 26% (p=0.001) over the 7-years. The associated accumulated economic burden was $265 million for all sports injuries and $110 million for lower limb injuries over the 7-years. Conclusions: Previous sports injury is an important known risk factor for the development of osteoarthritis. Assuming a direct correlation between sports injury rates and the subsequent development of OA, it could be expected that this could lead to an increase in the population-level incidence of sports-related OA cases in coming decades. Importantly, a large number of sports injuries do not present at hospitals, and are instead managed by general practitioners, sports physicians and sports physiotherapists through primary referral. This suggests that our findings are a very conservative estimate, and the overall burden of sports injury is likely to be much greater than reported within the current study. The findings of this study have direct implications of the planning of health services to deal with more OA patients in the future. Population-wide preventive strategies that reduce the risk of sports injury are urgently required in order to reduce the future health care system burden of osteoarthritis and other conditions secondary to sports injury.

The cost of systemic therapy for metastatic colorectal carcinoma in Slovenia: discrepancy analysis between cost and reimbursement.

Background.The aim of the study was to estimate the direct medical costs of metastatic colorectal cancer (mCRC) treated at the Institute of Oncology Ljubljana and to question the healthcare payment system in Slovenia.Methods.Using an internal patient database, the costs of mCRC patients were estimated in 2009 by examining (1) mCRC direct medical related costs, and (2) the cost difference between payment received by Slovenian health insurance and actual mCRC costs. Costs were analysed in the treatment phase of the disease by assessing the direct medical costs of hospital treatment with systemic therapy together with hospital treatment of side effects, without assessing radiotherapy or surgical treatment. Follow-up costs, indirect medical costs, and nonmedical costs were not included.Results.A total of 209 mCRC patients met all eligibility criteria. The direct medical costs of mCRC hospitalization with systemic therapy in Slovenia for 2009 were estimated as the cost of medications (cost of systemic therapy + cost of drugs for premedication) + labor cost (the cost of carrying out systemic treatment) + cost of lab tests + cost of imaging tests + KRAS testing cost + cost of hospital treatment due to side effects of mCRC treatment, and amounted to €3,914,697. The difference between the cost paid by health insurance and actual costs, estimated as direct medical costs of hospitalization of mCRC patients treated with systemic therapy at the Institute of Oncology Ljubljana in 2009, was €1,900,757.80.Conclusions.The costs paid to the Institute of Oncology Ljubljana by health insurance for treating mCRC with systemic therapy do not match the actual cost of treatment. In fact, the difference between the payment and the actual cost estimated as direct medical costs of hospitalization of mCRC patients treated with systemic therapy at the Institute of Oncology Ljubljana in 2009 was €1,900,757.80. The model Australian Refined Diagnosis Related Groups (AR-DRG) for cost assessment in oncology being currently used is probably one of the reasons for the discrepancy between pay-outs and actual costs. We propose new method for more precise cost assessment in oncology.

A cost model of capecitabine versus continuous infusional 5-fluorouracil (CI5FU) as chemosensitization during long course radiotherapy in the neoadjuvant treatment of rectal cancer: From the perspective of the Australian health care system.

688 Background: Recent phase III clinical trials have shown that the use of capecitabine with long course radiotherapy in the neoadjuvant treatment of rectal cancer provides equivalent outcomes to the traditionally used CI5FU. In the Australian health system the dispensed price of capecitabine is higher; however CI5FU administration requires a peripherally inserted central catheter (PICC). This analysis was designed to test the comparative cost of capecitabine over CI5FU from the perspective of the Australian healthcare system. Methods: We determined fully itemised direct treatment costs for the administration of neoadjuvant long course chemoradiotherapy with each of capecitabine and CI5FU. A decision analytic model was then used to compare potential clinical adverse events with the respective agents. Clinical probabilities were derived from published studies and the management of adverse events costed using Australian refined diagnosis-related group (AR-DRG) coding. The results of the decision analytic model were integrated with the drug administration costs to produce an inclusive discriminating cost for capecitabine versus CI5FU. Results: The total cost to the Australian healthcare system for the administration of CI5FU was $2,110 per patient, compared with $1,170 for capecitabine. The costs of managing treatment complications were similar: mean $174 per patient for CI5FU and $72 for capecitabine. The integrated discriminating cost difference was a mean saving of $1,042 per patient with prescription of capecitabine. The presented base-case model utilised higher capecitabine costs where input data could vary, and hence in all sensitivity analyses capecitabine continued to demonstrate cost savings (minimum $286 and maximum $1,975 per patient) over CI5FU. Conclusions: Capecitabine is a cost effective alternative to CI5FU. Considering also the expected lower indirect costs with oral therapy, use of capecitabine in chemoradiotherapy for rectal cancer is economically superior.

Cost Effectiveness of Eplerenone in Patients with Chronic Heart Failure

Chronic heart failure (CHF) remains an important cause of morbidity and mortality worldwide. Currently, there are no cost-effectiveness studies of eplerenone use in patients with New York Heart Association (NYHA) class II CHF. We sought to evaluate the cost effectiveness of eplerenone compared with placebo in patients with chronic systolic heart failure and NYHA class II symptoms. A 10-year Markov model with yearly cycles was constructed to evaluate the cost effectiveness of eplerenone compared with placebo, based on data from the EMPHASIS-HF (Eplerenone in Mild Patients Hospitalization And Survival Study in Heart Failure) study. The model classified subjects into two health states: 'Alive with CHF' and 'Dead'. Information about the cost of disease was derived from Australian Refined Diagnosis-Related Groups (AR-DRG) data. The cost of eplerenone was taken from the Australian Pharmaceutical Benefit Scheme. Utility data were derived from published sources, and a 5 % annual discount rate was applied to future costs and benefits. Over 10 years, and compared with placebo, the model predicted that eplerenone would lead to a saving of 0.5 life-years (discounted) and 0.4 quality-adjusted life-years (QALYs) per person. The net cost was (in Australian dollars [$A]) $A6,117 (discounted) per person. These equated to incremental cost-effectiveness ratios of $A12,024 per life-year saved and $A16,700 per QALY saved. Sensitivity analyses indicated that these results were robust. Eplerenone may represent a cost-effective strategy for preventing morbidity and mortality among patients with chronic systolic heart failure and NYHA class II symptoms.

Variations in car crash-related hospitalization costs amongst young adults in New South Wales, Australia

BackgroundThis study aims to examine factors associated with variation in crash-related hospitalization costs for young adults in New South Wales (NSW), Australia with a particular focus on types of vehicle occupant, rurality of residence and socioeconomic status (SES). MethodsData on patients aged 17–25 years, admitted to public hospitals due to a crash during July 2000–June 2007 were extracted from the NSW Health Admission Collection database. The hospitalization cost of each admission was calculated based on published charges for specific Australian Refined-Diagnosis Related Groups (AR-DRG). Multivariable analyses using generalized estimating equations were used to estimate costs by vehicle occupant type (driver, passenger and other occupants), rurality of residence (urban, regional and rural areas) and SES (low, moderate and high SES areas). ResultsDuring 2000–2007, there were 11,892 crash-related hospitalizations involving young adults, aged 17–25 years, in NSW. These cost the health sector about A$87.6 million or on average, A$7363 per hospitalization (mean length of stay (LOS) 5.3 days). Compared to drivers, passengers had significantly longer LOS (<0.01) as well as higher hospitalization costs (p=0.04). Regional and rural young adults had significantly longer LOS and higher hospitalization costs compared to urban young adults (p<0.05). Compared with young adults from high SES areas, young adults from moderate SES areas had significantly higher costs (p=0.02), whilst the higher costs for young adults of low SES areas was borderline significant (p=0.06), although differences in LOS by SES were not significant. ConclusionAnnually, young adults’ crashes in NSW were estimated to cost the health sector at least A$14.6 million between 2001 and 2007. The higher hospitalization costs and LOS for young adults living in regional and rural vs. urban areas, and those living in moderate and low SES vs. high SES areas partly reflects the severity of these crashes and challenges for treatment. Based on these findings, a strong economic argument can be made for targeting prevention strategies to young people living in rural and low SES areas. The area variations in costs also suggest some scope for policy makers to consider potentially more efficient ways of targeting both treatment and preventative programmes.

Do AR-DRGs Adequately Describe the Trauma Patient Episode in New South Wales, Australia?

The use of Diagnosis Related Groups (DRGs) may not be an accurate tool to provide reimbursement for trauma services. This study aimed to determine whether Australian Refined Diagnosis Related Groups (AR-DRGs) adequately describe the trauma patient episode and to identify AR-DRG groupings where reimbursement was not commensurate with actual cost. The AR-DRG allocated costs and actual costs of a sample of 206 trauma patient episodes were reviewed during a three-month period. Of the AR-DRG groups identified in the patient episodes, 62.8% were not commensurate with actual cost incurred, equating to an overall loss of $113,921 from under-funded acute trauma patient episodes over a three-month period. Assault-related penetrating trauma, traffic-related and sport-related incidents were all inadequately reimbursed using AR-DRGs compared with the actual cost of treatment. Cases involving female patients, patients aged 45 years or less and those with moderate injuries were similarly underfunded. AR-DRGs are not adequate to describe the extent of injuries experienced by trauma patients and there is a need to investigate alternative funding models for trauma services.

Trialling diagnosis-related groups classification in the Iranian health system: a case study examining the feasibility of introducing casemix

This paper examines the quality of routinely collected information in an Iranian hospital in a trial of casemix classification. Australian Refined Diagnosis Related Groups (AR-DRG) were used to classify patient episodes. There were 327 DRGs identified, of which 20% had only 1 case. The grouper program identified invalid records for 4% of total separations. Approximately 4.5% of cases were classified into error DRGs and 3.4% were ungroupable. No complication and comorbidity effects were identified with 93% of total cases. R2 (variance in length of stay explained) was 44% for untrimmed cases, increasing to 63%, 57% and 58% after trimming by L3H3, IQR and 10th-95th percentile methods respectively.