Analysis of cost outliers within APR-DRGs in a Belgian general hospital: two complementary approaches

The funding of specialised paediatric palliative care in Switzerland: a conceptualisation and modified Delphi study on obstacles and priorities

BACKGROUND

Effective funding models are key for implementing and sustaining critical care delivery programmes such as specialised paediatric palliative care (SPPC). In Switzerland, funding concerns have frequently been raised as primary barriers to providing SPPC in dedicated settings. However, systematic evidence on existing models of funding as well as primary challenges faced by stakeholders remains scarce.

AIMS

The present study's first aim was to investigate and conceptualise the funding of hospital-based consultative SPPC programmes in Switzerland. Its second aim was to identify obstacles to and priorities for funding these programmes sustainably.

METHODS

 A 4-step process, including a document analysis, was used to conceptualise the funding of hospital-based consultative SPPC programmes in Switzerland. In consultation with a purposefully selected panel of experts in the subject, a 3-round modified Delphi study was conducted to identify funding-relevant obstacles and priorities regarding SPPC.

RESULTS

Current funding of hospital-based consultative specialised paediatric palliative care programmes is complex and fragmented, combining funding from public, private and charitable sources. Overall, 21 experts participated in the first round of the modified Delphi study, 19 in round two and 15 in round three. They identified 23 obstacles and 29 priorities. Consensus (>70%) was obtained for 12 obstacles and 22 priorities. The highest level of consensus (>90%) was achieved for three priorities: the development of financing solutions to ensure long-term funding of SPPC programmes; the provision of funding and support for integrated palliative care; and sufficient reimbursement of inpatient service costs in the context of high-deficit palliative care patients.

CONCLUSION

Decision- and policy-makers hoping to further develop and expand SPPC in Switzerland should be aware that current funding models are highly complex and that SPPC funding is impeded by many obstacles. Considering the steadily rising prevalence of children with life-limiting conditions and the proven benefits of SPPC, improvements in funding models are urgently needed to ensure that the needs of this highly vulnerable population are adequately met.

Healthcare Costs and Health Status: Insights from the SHARE Survey

The substantial rise in hospital costs over recent years is associated with the rapid increase in the older age population. This study addresses an empirical gap in the literature concerning the determinants of high hospital costs in a group of older patients in Europe. The objective of the study is to examine the association of patient health status with in-hospital costs among older people across European countries. We used the data from the Survey of Health, Ageing and Retirement in Europe (SHARE) database. The analysis included 9671 patients from 18 European countries. We considered socio-demographic, lifestyle and clinical variables as possible factors influencing in-hospital costs. Univariate and multivariable logistic regression analyses were used to determine the determinants of in-hospital costs. To benchmark the hospital costs across European countries, we used the cost-outlier methodology. Rates of hospital cost outliers among older people varies from 5.80 to 12.65% across Europe. Factors associated with extremely high in-patient costs differ among European countries. In most countries, they include the length of stay in the hospital, comorbidities, functional mobility and physical activity. The treatment of older people reporting heart attack, diabetes, chronic lung disease and cancer are more often connected with cost outliers. The risk of being a cost outlier increased by 20% with each day spent in the hospital. We advocate that including patient characteristics in the reimbursement system could provide a relatively simple strategy for reducing hospitals' financial risk connected with exceptionally costly cases.

The Influence of the Rural Transitions Nurse Program for Veterans on Healthcare Utilization Costs

BACKGROUND

The Veterans Affairs (VA) Healthcare System Rural Transitions Nurse Program (TNP) addresses barriers veterans face when transitioning from urban tertiary VA hospitals to home. Previous clinical evaluations of TNP have shown that enrolled veterans were more likely to follow up with their primary care provider within 14 days of discharge and experience a significant reduction in mortality within 30 days compared to propensity-score matched controls.

OBJECTIVE

Examine changes from pre- to post-hospitalization in total, inpatient, and outpatient 30-day healthcare utilization costs for TNP enrollees compared to controls.

DESIGN

Quantitative analyses modeling the changes in cost via multivariable linear mixed-effects models to determine the association between TNP enrollment and changes in these costs.

PARTICIPANTS

Veterans meeting TNP eligibility criteria who were discharged home following an inpatient hospitalization at one of the 11 implementation sites from April 2017 to September 2019.

INTERVENTION

The four-step TNP transitional care intervention.

MAIN MEASURES

Changes in 30-day total, inpatient, and outpatient healthcare utilization costs were calculated for TNP enrollees and controls.

KEY RESULTS

Among 3001 TNP enrollees and 6002 controls, no statistically significant difference in the change in total costs (p = 0.65, 95% CI: (- $675, $350)) was identified. However, on average, the increase in inpatient costs from pre- to post-hospitalization was approximately $549 less for TNP enrollees (p = 0.02, 95% CI: (- $856, - $246)). The average increase in outpatient costs from pre- to post-hospitalization was approximately $421 more for TNP enrollees compared to controls (p = 0.003, 95% CI: ($109, $671)).

CONCLUSIONS

Although we found no difference in change in total costs between veterans enrolled in TNP and controls, TNP was associated with a smaller increase in direct inpatient medical costs and a larger increase in direct outpatient medical costs. This suggests a shifting of costs from the inpatient to outpatient setting.

Analyzing Hospital High Length of Stay Outliers in Turkey

Purpose: The aim of this study is to examine length of stay (LOS) outliers by analyzing hospital administrative database. Material and Methods: The Turkish Ministry of Health DRG grouper database was utilized to obtain hospital administrative data on discharges for 15 training and research hospitals in 2012. For each diagnosis-related group (DRG), the geometric mean plus two standard deviations were calculated to identify outliers. Analyses were conducted using descriptive statistics and logistic regression using generalized estimating equations (GEE). Results: High LOS outliers found to be 4.4 % of the cases, they were responsible for 24.50 percent of all discharge days. Alcohol, drug use disorders, burns, and diseases of the ear, nose, mouth, and throat were the factors that had the greatest impact on high LOS outliers, according to the multivariate model. Conclusion: A quarter of all inpatient days are made up of LOS outliers. Burns, neonate cases, and alcohol/drug use issues should all be carefully evaluated. In order to improve clinical quality and effectively manage hospital resources, hospital administrators and health policy makers should take length of stay outliers into consideration.

Association between nursing cost and patient outcomes in intensive care units: A retrospective cohort study of Belgian hospitals

INTRODUCTION

Hospitals with better nursing resources report more favourable patient outcomes with almost no difference in cost as compared to those with worse nursing resources. The aim of this study was to assess the association between nursing cost per intensive care unit bed and patient outcomes (mortality, readmission, and length of stay).

METHODOLOGY

This was a retrospective cohort study using data collected from the intensive care units of 17 Belgian hospitals from January 01 to December 31, 2018. Hospitals were dichotomized using median annual nursing cost per bed. A total of 18,235 intensive care unit stays were included in the study with 5,664 stays in the low-cost nursing group and 12,571 in the high-cost nursing group.

RESULTS

The rate of high length of stay outliers in the intensive care unit was significantly lower in the high-cost nursing group (9.2% vs 14.4%) compared to the low-cost nursing group. Intensive care unit readmission was not significantly different in the two groups. Mortality was lower in the high-cost nursing group for intensive care unit (9.9% vs 11.3%) and hospital (13.1% vs 14.6%) mortality. The nursing cost per intensive care bed was different in the two groups, with a median [IQR] cost of 159,387€ [140,307-166,690] for the low-cost nursing group and 214,032€ [198,094-230,058] for the high-cost group. In multivariate analysis, intensive care unit mortality (OR = 0.80, 95% CI: 0.69-0.92, p < 0.0001), in-hospital mortality (OR = 0.82, 95% CI: 0.72-0.93, p < 0.0001), and high length of stay outliers (OR = 0.48, 95% CI: 0.42-0.55, p < 0.0001) were lower in the high-cost nursing group. However, there was no significant effect on intensive care readmission between the two groups (OR = 1.24, 95% CI: 0.97-1.51, p > 0.05).

CONCLUSIONS

This study found that higher-cost nursing per bed was associated with significantly lower intensive care unit and in-hospital mortality rates, as well as fewer high length of stay outliers, but had no significant effect on readmission to the intensive care unit. .

Cost-effectiveness of Dabigatran Compared With Rivaroxaban for Prevention of Stroke and Systemic Embolism in Patients With Atrial Fibrillation in China

PURPOSE

In China, dabigatran and rivaroxaban are the only approved non-vitamin K antagonist oral anticoagulants for the treatment of atrial fibrillation (AF). The goal of this article was to assess the cost-effectiveness of dabigatran versus rivaroxaban for the prevention of stroke and systemic embolism in Chinese patients with AF from the perspective of the Chinese health care system.

METHODS

A Markov model was constructed to estimate the cost-effectiveness of dabigatran versus rivaroxaban. Clinical events were modeled for a lifetime horizon, based on clinical efficacy data from indirect treatment comparisons. The weighted average of the most recent prices of these 2 drugs was used as the drug acquisition cost. Other costs, including follow-up costs and event costs, were collected by using a survey from a panel of local experts. Utility inputs (health state utilities, clinical event disutilities, and event history utility) were obtained from published literature. Sensitivity analyses that included scenario analyses and a probabilistic sensitivity analysis were conducted to examine the robustness of the economic model.

FINDINGS

Over a lifetime, patients treated with dabigatran experienced fewer ischemic strokes (2.14 dabigatran vs 2.61 rivaroxaban) and fewer intracranial hemorrhage (0.48 vs 0.94) per 100 patient-years. In the base case analysis, dabigatran had an incremental cost of ¥28,128 but with higher life years (10.38 vs 10.14) and quality-adjusted life years (QALYs) (7.95 vs 7.70). The resulting incremental cost-effectiveness ratio of ¥112,910 per QALY gained and net monetary benefit of ¥12,214 versus rivaroxaban showed that dabigatran was a cost-effective alternative to rivaroxaban. Extensive sensitivity analyses indicated that the results were robust over a wide range of inputs. The probabilistic sensitivity analysis indicated that dabigatran was cost-effective in 84.2% of the 10,000 Monte Carlo simulations compared with rivaroxaban.

IMPLICATIONS

Dabigatran reduced the occurrence of clinical events and increased QALYs compared with rivaroxaban. The use of dabigatran for the prevention of stroke and systemic embolism is a cost-effective option compared with rivaroxaban among patients with AF in China.

Using machine learning approaches to predict high-cost chronic obstructive pulmonary disease patients in China

The accurate identification and prediction of high-cost Chronic obstructive pulmonary disease (COPD) patients is important for addressing the economic burden of COPD. The objectives of this study were to use machine learning approaches to identify and predict potential high-cost patients and explore the key variables of the forecasting model, by comparing differences in the predictive performance of different variable sets. Machine learning approaches were used to estimate the medical costs of COPD patients using the Medical Insurance Data of a large city in western China. The prediction models used were logistic regression, random forest (RF), and extreme gradient boosting (XGBoost). All three models had good predictive performance. The XGBoost model outperformed the others. The areas under the ROC curve for Logistic Regression, RF and XGBoost were 0.787, 0.792 and 0.801. The precision and accuracy metrics indicated that the methods achieved correct and reliable results. The results of this study can be used by healthcare data analysts, policy makers, insurers, and healthcare planners to improve the delivery of health services.

Bullying Victimization and Suicide Attempt Among Adolescents Aged 12-15 Years From 48 Countries

OBJECTIVE

Adolescent suicide is a global public health problem. Bullying is a risk factor for suicidality in adolescence; however, global data on its association with suicide attempts are lacking, and data from low- and middle-income countries and non-Western settings are scarce. Thus, this study assessed the association between bullying victimization and suicide attempts using data from 48 countries (predominantly low- and middle-income countries) across multiple continents.

METHOD

Data from the Global School-based Student Health Survey were analyzed. Data on past 12-month suicide attempts and past 30-day bullying victimization were collected. Multivariable logistic regression and meta-analysis with random effects were conducted to assess the associations.

RESULTS

The final sample consisted of 134,229 adolescents 12 to 15 years of age. The overall prevalences of suicide attempts and bullying victimization were 10.7% and 30.4%, respectively. After adjustment for sex, age, and socioeconomic status, bullying victimization was significantly associated with higher odds for a suicide attempt in 47 of the 48 countries studied, with the pooled odds ratio being 3.06 (95% CI 2.73-3.43). A larger number of days bullied in the past month was dose-dependently associated with higher odds for suicide attempts. The past-year prevalence of suicide attempts ranged from 5.9% for the "no bullying" group up to 32.7% for the "being bullied for 20 to 30 days/month" group (odds ratio 5.51, 95% CI 4.56-6.65).

CONCLUSION

Bullying victimization could be an important risk factor of suicide attempts among adolescents globally. Thus, there is an urgent need to implement effective and evidence-based interventions to address bullying to prevent suicides and suicide attempts among adolescents worldwide.

Development of clinical value unit method for calculating patient costs

The objective of the study was to develop the clinical value unit method of allocating indirect costs to patient costs using clinical factors. The method was tested to determine whether it is a more reliable alternative to using the length of stay and marginal mark-up allocation method. The method developed used data from a Polish specialist hospital. The study involved 4,026 patients grouped into nine diagnosis-related groups (DRG). The study methodology involved a three stage approach: (a) identification of correlates of patient costs, (b) a comparison of the costs calculated using the clinical value unit method with the alternative methods: length of stay and marginal mark-up methods, and (c) an estimation of the cost homogeneity of the DRGs. The study showed that length of stay cost allocation method may underestimate the proportion of indirect costs in patient costs for a short in-patient stay and overestimate the cost for the patients with a long stay. The total costs estimated using the marginal mark-up method were higher than those estimated with length of stay method. For most surgical procedures, the mean indirect costs are higher using clinical value unit method than when using length of stay or marginal mark-up method. In all medical procedure cases, the mean indirect costs calculated using the clinical value unit method are in the range between marginal mark-up and length of stay method. We also show that in all DRGs except one, that the coefficient of homogeneity for clinical value unit is higher than for length of stay or marginal mark-up method. We conclude that the clinical value unit method of cost allocation is a more precise and reliable alternative than the other methods.

Identification of hospital cost drivers using sparse group lasso

Public hospital spending consumes a large share of government expenditure in many countries. The large cost variability observed between hospitals and also between patients in the same hospital has fueled the belief that consumption of a significant portion of this funding may result in no clinical benefit to patients, thus representing waste. Accurate identification of the main hospital cost drivers and relating them quantitatively to the observed cost variability is a necessary step towards identifying and reducing waste. This study identifies prime cost drivers in a typical, mid-sized Australian hospital and classifies them as sources of cost variability that are either warranted or not warranted-and therefore contributing to waste. An essential step is dimension reduction using Principal Component Analysis to pre-process the data by separating out the low value 'noise' from otherwise valuable information. Crucially, the study then adjusts for possible co-linearity of different cost drivers by the use of the sparse group lasso technique. This ensures reliability of the findings and represents a novel and powerful approach to analysing hospital costs. Our statistical model included 32 potential cost predictors with a sample size of over 50,000 hospital admissions. The proportion of cost variability potentially not clinically warranted was estimated at 33.7%. Given the financial footprint involved, once the findings are extrapolated nationwide, this estimation has far-reaching significance for health funding policy.

Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center

Principles

Case weights of Diagnosis Related Groups (DRGs) are determined by the average cost of cases from a previous billing period. However, a significant amount of cases are largely over- or underfunded. We therefore decided to analyze earning outliers of our hospital as to search for predictors enabling a better grouping under SwissDRG.

Methods

28,893 inpatient cases without additional private insurance discharged from our hospital in 2012 were included in our analysis. Outliers were defined by the interquartile range method. Predictors for deficit and profit outliers were determined with logistic regressions. Predictors were shortlisted with the LASSO regularized logistic regression method and compared to results of Random forest analysis. 10 of these parameters were selected for quantile regression analysis as to quantify their impact on earnings.

Results

Psychiatric diagnosis and admission as an emergency case were significant predictors for higher deficit with negative regression coefficients for all analyzed quantiles (p<0.001). Admission from an external health care provider was a significant predictor for a higher deficit in all but the 90% quantile (p<0.001 for Q10, Q20, Q50, Q80 and p = 0.0017 for Q90). Burns predicted higher earnings for cases which were favorably remunerated (p<0.001 for the 90% quantile). Osteoporosis predicted a higher deficit in the most underfunded cases, but did not predict differences in earnings for balanced or profitable cases (Q10 and Q20: p<0.00, Q50: p = 0.10, Q80: p = 0.88 and Q90: p = 0.52). ICU stay, mechanical and patient clinical complexity level score (PCCL) predicted higher losses at the 10% quantile but also higher profits at the 90% quantile (p<0.001).

Conclusion

We suggest considering psychiatric diagnosis, admission as an emergencay case and admission from an external health care provider as DRG split criteria as they predict large, consistent and significant losses.

Impact of alternative approaches to assess outlying and influential observations on health care costs

The distributions of medical costs are often skewed to the right because small numbers of patients use large amounts of health care resources. Using data from a study of colon cancer costs, we show, by example, the impact and magnitude of outliers and influential observations on health care costs and compared the effects of statistical costing methods for addressing the disproportionate influence of outliers and influential observations. We used data from a retrospective cohort study of 3,842 elderly veterans with colon cancer who were enrolled in and used health care from, both the Department of Veterans Affairs and Medicare in 1999–2004. After calculating the average colon cancer episode cost and distribution for the full cohort, we used box-plot methods, Winsorization, DFBETAs, and Cook's distance to identify and assess or adjust the outlying and/or influential observations. The number of observations identified as outlying and/or influential ranged from 13 when the predicted DFBETA measurement was greater than 0.15 and the observation was a qualified box-plot outlier to 384 cases using the Winsorization method at the 5th and 95th percentiles. Average costs of colon cancer episodes using these methods were similar. The method of choice from the results of this particular analysis can be conditionally based on whether the purpose is to control only for influential observations or to simultaneously control for outliers and influential observations. Understanding how estimates could change with each approach is important in assessing the impact of a particular method on the results.

What can we learn from international comparisons of costs by DRG?

OBJECTIVES

The objective of this study was to compare costs data by diagnosis related group (DRG) between Belgium and Switzerland. Our hypotheses were that differences between countries can probably be explained by methodological differences in cost calculations, by differences in medical practices and by differences in cost structures within the two countries.

METHODS

Classifications of DRG used in the two countries differ (AP-DRGs version 1.7 in Switzerland and APR-DRGs version 15.0 in Belgium). The first step of this study was to transform Belgian summaries into Swiss AP-DRGs. Belgian and Swiss data were calculated with a clinical costing methodology (full costing). Belgian and Swiss costs were converted into US$ PPP (purchasing power parity) in order to neutralize differences in purchasing power between countries.

RESULTS

The results of this study showed higher costs in Switzerland despite standardization of cost data according to PPP. The difference is not explained by the case-mix index because this was similar for inliers between the two countries. The length of stay (LOS) was also quite similar for inliers between the two countries. The case-mix index was, however, higher for high outliers in Belgium, as reflected in a higher LOS for these patients. Higher costs in Switzerland are thus probably explained mainly by the higher number of agency staff by service in this country or because of differences in medical practices.

CONCLUSIONS

It is possible to make international comparisons but only if there is standardization of the case-mix between countries and only if comparable accountancy methodologies are used. Harmonization of DRGs groups, nomenclature and accountancy is thus required.

Factors influencing hospital high length of stay outliers

Background

The study of length of stay (LOS) outliers is important for the management and financing of hospitals. Our aim was to study variables associated with high LOS outliers and their evolution over time.

Methods

We used hospital administrative data from inpatient episodes in public acute care hospitals in the Portuguese National Health Service (NHS), with discharges between years 2000 and 2009, together with some hospital characteristics. The dependent variable, LOS outliers, was calculated for each diagnosis related group (DRG) using a trim point defined for each year by the geometric mean plus two standard deviations. Hospitals were classified on the basis of administrative, economic and teaching characteristics. We also studied the influence of comorbidities and readmissions. Logistic regression models, including a multivariable logistic regression, were used in the analysis. All the logistic regressions were fitted using generalized estimating equations (GEE).

Results

In near nine million inpatient episodes analysed we found a proportion of 3.9% high LOS outliers, accounting for 19.2% of total inpatient days. The number of hospital patient discharges increased between years 2000 and 2005 and slightly decreased after that. The proportion of outliers ranged between the lowest value of 3.6% (in years 2001 and 2002) and the highest value of 4.3% in 2009. Teaching hospitals with over 1,000 beds have significantly more outliers than other hospitals, even after adjustment to readmissions and several patient characteristics.

Conclusions

In the last years both average LOS and high LOS outliers are increasing in Portuguese NHS hospitals. As high LOS outliers represent an important proportion in the total inpatient days, this should be seen as an important alert for the management of hospitals and for national health policies. As expected, age, type of admission, and hospital type were significantly associated with high LOS outliers. The proportion of high outliers does not seem to be related to their financial coverage; they should be studied in order to highlight areas for further investigation. The increasing complexity of both hospitals and patients may be the single most important determinant of high LOS outliers and must therefore be taken into account by health managers when considering hospital costs.

Study on TCM Syndrome Identification Modes of Coronary Heart Disease Based on Data Mining

Coronary heart disease (CHD) is one of the most important types of heart disease because of its high incidence and high mortality. TCM has played an important role in the treatment of CHD. Syndrome differentiation based on information from traditional four diagnostic methods has met challenges and questions with the rapid development and wide application of system biology. In this paper, methods of complex network and CHAID decision tree were applied to identify the TCM core syndromes of patients with CHD, and to establish TCM syndrome identification modes of CHD based on biological parameters. At the same time, external validation modes were also constructed to confirm the identification modes.

Comparison of cost-weights scales methodologies in the perspective of a financing system based on pathologies

OBJECTIVES

Objectives of this article are to evaluate the possibility to create a CW scale by pathology on the basis of cost data from Belgian hospitals, to compare several methodologies to create this CW scale, and to evaluate the financial impact of a modification of the financing system on hospitals' income.

METHODS

CW scales were elaborated according to various methodologies in order to isolate the scale allowing the most adequate financing system, i.e. approaching the real costs as much as possible. Twelve scales were created. They vary according to the type of data used, according to DRGs and severities of illness included within the scale, and according to the variable used in order to isolate outliers.

RESULTS

For a similar case-mix, Hospitals H2 and H5 would see their financing increased through a prospective system based on the selected CW scale (No. 6). This modification would generate a reduction in financing going from -1 to -9% according to hospitals.

CONCLUSIONS

The cost database created made it possible to create a CW scale according to a technique which could constitute the first step of a PPS if advantages of a such financing system were established. In the Belgian context, it would be probably judicious to envisage regional databases allowing diversified methodological approaches whose results would be confronted, discussed, and coordinated at the federal level.

Does the pharmacy expenditure of patients always correspond with their morbidity burden? Exploring new approaches in the interpretation of pharmacy expenditure

Background

The computerisation of primary health care (PHC) records offers the opportunity to focus on pharmacy expenditure from the perspective of the morbidity of individuals. The objective of the present study was to analyse the behaviour of pharmacy expenditure within different morbidity groups. We paid special attention to the identification of individuals who had higher values of pharmacy expenditure than their morbidity would otherwise suggest (i.e. outliers).

Methods

Observational study consisting of 75,574 patients seen at PHC centres in Zaragoza, Spain, at least once in 2005. Demographic and disease variables were analysed (ACG^® 8.1), together with a response variable that we termed 'total pharmacy expenditure per patient'. Outlier patients were identified based on boxplot methods, adjusted boxplot for asymmetric distributions, and by analysing standardised residuals of tobit regression models.

Results

The pharmacy expenditure of up to 7% of attendees in the studied PHC centres during one year exceeded expectations given their morbidity burden. This group of patients was responsible for up to 24% of the total annual pharmacy expenditure. There was a significantly higher number of outlier patients within the low-morbidity band which matched up with the higher variation coefficient observed in this group (3.2 vs. 2.0 and 1.3 in the moderate- and high-morbidity bands, respectively).

Conclusions

With appropriate validation, the methodologies of the present study could be incorporated in the routine monitoring of the prescribing profile of general practitioners. This could not only enable evaluation of their performance, but also target groups of outlier patients and foster analyses of the causes of unusually high pharmacy expenditures among them. This interpretation of pharmacy expenditure gives new clues for the efficiency in utilisation of healthcare resources, and could be complementary to management interventions focused on individuals with a high morbidity burden.

[Identification of pharmacy cost outliers in primary care]

OBJECTIVE

To identify pharmacy cost outlier patients in Primary Care, describing epidemiological differences between normal users and outliers; and to study the explanatory power of risk adjustment tools based on Adjusted Clinical Groups (ACG) as regards the variability of pharmacy expenditure for both groups of patients.

DESIGN

Observational, retrospective study.

SETTING

23 health centres located in the regions of Aragon, Catalonia and the Balearic Islands.

PARTICIPANTS

The study sample consisted of 286,450 patients who were seen at least once in 2005.

MEASUREMENTS

Variables related to demographic features, pharmacy cost, and case-mix (ACG 7.1) were collected. Pharmacy cost outliers were selected according to the inter-quartile range method. A linear regression model was developed to measure the explanatory power of ACG. This same model was applied stratifying the population by variables of the physician, the health centre and the region.

RESULTS

One out of ten patients was classified as an outlier. This group was responsible for 60% of the total pharmacy expenditure. These outlier patients were 26.3 years older than normal users and had a higher comorbidity. The explanatory power of the ACG classification system was markedly lower -3% vs. 26.4% for normal users-.

CONCLUSIONS

Further research should be done on factors causing a lack of adequacy of ACG among pharmacy outlier patients. Although it could be thought that social circumstances might play a role in the clinical state of patients, it is more likely that the applied trimming method does not allow outliers with justifiable clinical reasons for higher costs to be distinguished from those without them.

Trastuzumab treatment of early stage breast cancer is cost-effective from the perspective of the Belgian health care authorities

Trastuzumab (Herceptin, Roche) is a recombinant, humanized monoclonal antibody directed against the neu-HER2 protein, since May 2002 reimbursed in Belgium for the treatment of metastatic HER2+ breast cancer and since June 2007 also in adjuvant therapy of HER2+ early stage breast cancer. The purpose of this study was to estimate the cost-effectiveness from the Belgian health care payer perspective of reimbursing trastuzumab in the Latter indication. A Markov state transition model was designed to adequately capture the natural history and course of disease for early stage breast cancer patients, and to simulate cost and disease progression over a life time perspective. The model estimates differences in outcomes for patients treated with adjuvant trastuzumab during 1 year compared to current therapy, and captures cost consequences and health benefits of trastuzumab treatment. Health benefits were expressed in terms of quality-adjusted life years gained, and future benefits were discounted at 1.5%. Costs were calculated from the perspective of the Belgian authorities' health care budget, and future costs were discounted at 3%. Where relevant, the costs per Markov state were obtained from the IMS Hospital Disease database. Additionally, an expert opinion analysis on resource use during the follow-up of treated early breast cancer patients provided the cost estimates for states with minor or without hospital costs. The incremental cost-effectiveness ratio based on a life time simulation was estimated at Euro 10,315 per quality-adjusted life year gained. It can be concluded that trastuzumab treatment of HER2+ early stage breast cancer patients is cost-effective from the perspective of the Belgian health care authorities.

Extreme regression models for characterizing high-cost patients

OBJECTIVE

Healthcare cost distribution generally presents a high level of skewness, with a relatively small number of subjects accounting for a large portion of healthcare expenditures. Information on factors that predict high expenditures is of interest in healthcare planning. The aim of this paper was to inspect the behaviour of extreme regression (ER) models.

METHODS

We performed a simple simulation study, based on the LogNormal distribution, to assess the performance of ER in the special cases of heterogeneity and strong asymmetry of the cost variable. We then discussed the application of ER models to the analysis of three data sets of diabetes, lung cancer and myocardial infarction patients.

RESULTS

The ER showed to be able to cope fairly well with skewed distribution but under the condition that all observations have strictly positive costs.

CONCLUSION

The main advantage of the ER model is to unify these approaches in a unique framework, where the estimation of the cut-offs and the production of the prediction rules are performed simultaneously for a continuous response variable. The final model can thus be analysed at any desiderate quantile of the cost distribution, avoiding the need of pre-specifying any cut-off.

Economic burden associated with the management of cervical cancer, cervical dysplasia and genital warts in Belgium

OBJECTIVE

Human papillomavirus (HPV) infections can lead to cervical intraepithelial neoplasia (CIN) lesions, cervical cancer (CC) and genital warts (GWs). This study intended to assess the annual cost of CC, CIN and GW management in Belgium.

METHOD

A retrospective study using a Belgian Hospital Disease Database (for yearly hospital cost of CC and GW patients) and a clinical expert survey were performed to assess the medical management of CC, CIN and GW patients. Belgian official sources were used to estimate the annual costs of management of CC, CIN and GW patients both from a healthcare payer perspectives (HCPP) and a societal perspective.

RESULTS

Based on the 667 patients diagnosed annually in Belgium with CC and an annual cost per patient of euro9,716, the total annual cost of CC is euro6.5 million (HCPP). The 10,495 estimated CIN 1, 2 and 3 patients led to an annual cost of euro1.97 million (HCPP). The 7,989 estimated annual number of diagnosed GW patients led to an estimated annual cost of euro2.53 million (HCPP).

CONCLUSION

HPV-related diseases represent an important burden on Belgian society, especially when considering that the estimates in this study are probably underestimations, as the management costs of other HPV-related diseases (vulvar, vaginal, penile, oropharyngeal (pre-) cancers, recurrent respiratory papillomatosis etc.) are not included in this analysis.

Prospective casemix-based funding, analysis and financial impact of cost outliers in all-patient refined diagnosis related groups in three Belgian general hospitals

This study examined the impact of cost outliers in term of hospital resources consumption, the financial impact of the outliers under the Belgium casemix-based system, and the validity of two "proxies" for costs: length of stay and charges. The cost of all hospital stays at three Belgian general hospitals were calculated for the year 2001. High resource use outliers were selected according to the following rule: 75th percentile +1.5 xinter-quartile range. The frequency of cost outliers varied from 7% to 8% across hospitals. Explanatory factors were: major or extreme severity of illness, longer length of stay, and intensive care unit stay. Cost outliers account for 22-30% of hospital costs. One-third of length-of-stay outliers are not cost outliers, and nearly one-quarter of charges outliers are not cost outliers. The current funding system in Belgium does not penalize hospitals having a high percentage of outliers. The billing generated by these patients largely compensates for costs generated. Length of stay and charges are not a good approximation to select cost outliers.