The cost of a first and second hospital-wide accreditation in Flanders, Belgium.

BACKGROUND: Hospital accreditation is a popular and widely used quality control and improvement instrument. Despite potential benefits, ques-tions are raised whether it constitutes appropriate use of hospitals' limited financial resources. OBJECTIVE: This study aims to calculate the cost of preparing for and undergoing a first and second accreditation by the Joint Commission International or Qualicor Europe in acute-care hospitals. METHOD: All (n = 53) acute-care hospitals in Flanders (Belgium) were invited to participate and report on the costs in preparing for and undergoing a first and/or second accreditation cycle. To measure costs, a questionnaire with six domains and 90 questions was developed based on literature review, policy documents and a multidisciplinary expert group. All costs were recalculated to 2020 euro to correct for inflation and reported as medians with interquartile range. RESULTS: A total of 25 hospitals (47%) participated in the study. Additional investments and direct operational costs for a first accreditation cycle amounted to 879.45 euro (interquartile range: 794.81) per bed and 3.8 full-time equivalent (FTE) per hospital additional new staff members were recruited for coordination and implementation of the trajectory. A second accreditation survey costed remarkably less with a total cost of extra investments and direct operational cost of 222.88 euro (interquartile range: 244.04) per bed and less investment in additional staff (1.50 FTE). Most of the costs were situated in consulting costs and investments in infrastructure. The median total extra cost (direct operational cost and additional investments) amounted to 0.2% of the hospital's operating income for a first accreditation cycle and 0.05% for a second cycle. CONCLUSION: A first accreditation cycle requires a strong financial commitment of hospitals, as many costs result from the preparation in the years prior to an accreditation survey. A second survey is less expensive for hospitals, but still requires a considerable effort in terms of budget and staff. Policy makers should be aware of these significant costs as hospitals are operating with public resources and budget is scarce. The identification of these costs is a necessary building block to evaluate cost-effectiveness of accreditation versus other quality improvement systems and the continuation of these accreditation systems and their costs needs further study and a thorough debate.

Variability drivers of treatment costs in hospitals: A systematic review.

OBJECTIVES: Studies on variability drivers of treatment costs in hospitals can provide the necessary information for policymakers and healthcare providers seeking to redesign reimbursement schemes and improve the outcomes-over-cost ratio, respectively. This systematic literature review, focusing on the hospital perspective, provides an overview of studies focusing on variability in treatment cost, an outline of their study characteristics and cost drivers, and suggestions on future research methodology. METHODS: We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Cochrane Handbook for Systematic Reviews of Interventions. We searched PubMED/MEDLINE, Web of Science, EMBASE, Scopus, CINAHL, Science direct, OvidSP and Cochrane library. Two investigators extracted and appraised data for citation until October 2020. RESULTS: 90 eligible articles were included. Patient, treatment and disease characteristics and, to a lesser extent, outcome and institutional characteristics were identified as significant variables explaining cost variability. In one-third of the studies, the costing method was classified as unclear due to the limited explanation provided by the authors. CONCLUSION: Various patient, treatment and disease characteristics were identified to explain hospital cost variability. The limited transparency on how hospital costs are defined is a remarkable observation for studies wherein cost variability is the main focus. Recommendations relating to variables, costs, and statistical methods to consider when designing and conducting cost variability studies were provided.

Activity-based cost analysis of laboratory tests in clinical chemistry.

OJECTIVES: Since health care budgets are limited and must be allocated efficiently, there is an economic pressure to reduce the costs of health care interventions. This study aims to investigate the cost of testing within a Clinical Chemistry laboratory. METHODS: This study was conducted in the Clinical Chemistry laboratory of the University Hospital UZ Brussel, Belgium, in which 156 tests were included and an average cost per test was calculated for the year 2018. Activity-based costing (ABC) was applied, using a top-down perspective. Costs were first allocated to different activity centers and subsequently to different tests. Number of tests, parameters, analyzers and time estimates were used as activity cost drivers. RESULTS: The blood glucose test on the point-of-care testing (POCT) analyzer Accu Chek Inform II had the lowest unit cost (€0.92). The determination of methanol, ethanol and isopropanol on the GC-FID (7820A) is the test with the highest unit cost (€129.42). In terms of average cost per test per activity center, core laboratory (€3.37) scored lowest, followed consecutively by POCT (€3.49), diabetes (€22.09), toxicology (€31.52), metabolic disorder (€41.53) and cystic fibrosis (€86.02). The cost per test was mainly determined by staff (57%), costs of support services (23%) and reagents (14%). CONCLUSIONS: High-volume and automated tests have lower unit costs, as is the case with the core laboratory. ABC provides the ability to identify high average cost tests that can benefit from optimizations, such as focusing on automation or outsourcing low-volume tests that can benefit from economies of scale.

Variability in Hospital Costs of Adult Spinal Deformity Care.

STUDY DESIGN: Retrospective, single-center analysis. OBJECTIVE: To calculate the total clinical hospital cost of the Adult Spinal Deformity (ASD) care trajectory, to explain cost variability by patient and surgery characteristics, and to identify areas of process improvement opportunities. SUMMARY OF BACKGROUND DATA: ASD is associated with a high financial and clinical burden on society. ASD care thus requires improved insights in costs and its drivers as a critical step toward the improvement of value, i.e., the ratio between delivered health outcome and associated costs. METHODS: Patient characteristics and surgical variables were collected following ethical approval in a cohort of 139 ASD patients, treated between December, 2014 and January, 2018. Clinical hospital costs were calculated, including all care activities, from initial consultation to 1 year after initial surgery (excl. overhead) in a university hospital setting. Multiple linear regression analysis was performed to analyze the impact of patient and surgical characteristics on clinical costs. RESULTS: 75.5% of the total clinical hospital cost (&OV0556;27,865) was incurred during initial surgery with costs related to the operating theatre (80.3%), nursing units (11.9%), and intensive care (2.9%) being the largest contributors. 57.5% of the variation in total cost could be explained in order of importance by surgical invasiveness, age, coronary disease, single or multiple-staged surgery, and mobility status. Revision surgery, unplanned surgery due to complications, was found to increase average costs by 87.6% compared with elective surgeries (&OV0556; 44,907 (± &OV0556; 23,429) vs. &OV0556; 23,944 (± &OV0556; 7302)). CONCLUSION: This study identified opportunities for process improvement by calculating the total clinical hospital costs. In addition, it identified patient and treatment characteristics that predict 57.5% of cost variation, which could be taken into account when developing a payment system. Future research should include outcome data to assess variation in value. LEVEL OF EVIDENCE: 4.

A haemovigilance team provides both significant financial and quality benefits in a University Hospital.

BACKGROUND: Haemovigilance is the process of surveillance of blood transfusion procedures including unexpected hazards and reactions during the transfusion pathway in both donors and recipients. The haemovigilance team aims to increase blood transfusion safety and to decrease both morbidity and mortality in donors and recipients. The team collects data about transfusion reactions and incidents, instructs the involved health workers and assures the tracing of blood components. The haemovigilance team at the University Hospitals Leuven has played a pioneering role in the development of haemovigilance in Belgium Although the literature about safety and quality improvements by haemovigilance systems is abundant, there are no published data available measuring their financial impact in a hospital. Therefore, we studied the costs and returns of the haemovigilance team at the University Hospitals Leuven. MATERIAL AND METHODS: This study has a descriptive explorative design. Research of the current costs and returns of the haemovigilance team were based upon data from the Medical Administration of the hospital. Data were analyzed descriptively. RESULTS: The haemovigilance team of the University Hospitals Leuven is financially viable: the direct costs are covered by the annual financial support of the National Public Health Service. The indirect returns come from two important tasks of the haemovigilance team itself: correction of the electronic registration of administered blood component and improvement of the return of conform preserved blood components to the blood bank. DISCUSSION: Besides safety and quality improvement, which are obviously their main goals, the haemovigilance team also implies a financial benefit for the hospital.

Early versus late parenteral nutrition in ICU patients: cost analysis of the EPaNIC trial.

INTRODUCTION: The EPaNIC randomized controlled multicentre trial showed that postponing initiation of parenteral nutrition (PN) in ICU-patients to beyond the first week (Late-PN) enhanced recovery, as compared with Early-PN. This was mediated by fewer infections, accelerated recovery from organ failure and reduced duration of hospitalization. Now, the trial's preplanned cost analysis (N = 4640) from the Belgian healthcare payers' perspective is reported. METHODS: Cost data were retrieved from individual patient invoices. Undiscounted total healthcare costs were calculated for the index hospital stay. A cost tree based on acquisition of new infections and on prolonged length-of-stay was constructed. Contribution of 8 cost categories to total hospitalization costs was analyzed. The origin of drug costs was clarified in detail through the Anatomical Therapeutic Chemical (ATC) classification system. The potential impact of Early-PN on total hospitalization costs in other healthcare systems was explored in a sensitivity analysis. RESULTS: ICU-patients developing new infection (24.4%) were responsible for 42.7% of total costs, while ICU-patients staying beyond one week (24.3%) accounted for 43.3% of total costs. Pharmacy-related costs represented 30% of total hospitalization costs and were increased by Early-PN (+608.00 EUR/patient, p = 0.01). Notably, costs for ATC-J (anti-infective agents) (+227.00 EUR/patient, p = 0.02) and ATC-B (comprising PN) (+220.00 EUR/patient, p = 0.006) drugs were increased by Early-PN. Sensitivity analysis revealed a mean total cost increase of 1,210.00 EUR/patient (p = 0.02) by Early-PN, when incorporating the full PN costs. CONCLUSIONS: The increased costs by Early-PN were mainly pharmacy-related and explained by higher expenditures for PN and anti-infective agents. The use of Early-PN in critically ill patients can thus not be recommended for both clinical (no benefit) and cost-related reasons. TRIAL REGISTRATION: ClinicalTrials.gov NCT00512122.

Analysis of healthcare resource utilization with intensive insulin therapy in critically ill patients.

OBJECTIVE: To perform an analysis of healthcare resource utilization with intensive insulin therapy, which has recently been shown to reduce morbidity and mortality rates of mechanically ventilated critically ill patients in a surgical intensive care unit. DESIGN: A post hoc cost analysis. SETTING: Surgical intensive care unit. PATIENTS: Patients were 1548 mechanically ventilated patients admitted to a surgical intensive care unit. INTERVENTIONS: A post hoc cost analysis was conducted based on data collected prospectively as part of a large randomized controlled trial. The analysis performed was a healthcare resource utilization analysis in which the cost of hospitalization in the intensive care unit was determined based on length of stay and the frequency of crucial cost-generating morbid events occurring in the intensive and conventional insulin treatment groups. Sensitivity analyses were performed to evaluate the robustness of the findings. Discounting of costs was not performed as treatment was limited to the intensive care stay and follow-up was not continued beyond hospitalization. MEASUREMENTS AND MAIN RESULTS: In the intensive treatment group, total treatment cost was 109,838 Euros (144 Euros per patient). In the conventional treatment group, total treatment cost was 56,359 Euros (72 Euros per patient). The excess cost of intensive insulin therapy was 72 Euros per patient. The total hospitalization cost in the intensive treatment group was 6,067,237 Euros (7931 Euros per patient) compared with 8,275,394 Euros (10,569 Euros per patient) in the conventional treatment group. The excess cost of intensive care unit hospitalization in the conventional vs. intensive treatment group was 2638 Euros per patient. These intensive care unit benefits were not offset by additional costs for care on regular wards. CONCLUSIONS: Intensive insulin therapy, which reduces morbidity and mortality rates of mechanically ventilated patients admitted to a surgical intensive care unit, is associated with substantial cost savings compared with conventional insulin therapy.

Economic consequence of local control with radiotherapy: cost analysis of internal mammary and medial supraclavicular lymph node radiotherapy in breast cancer.

PURPOSE: To investigate the financial implications of radiotherapy (RT) to the internal mammary and medial supraclavicular lymph node chain (IM-MS) in postoperative breast cancer. METHODS AND MATERIALS: A cost-effectiveness and cost-utility analysis were performed, using Markov models, comparing the early and delayed costs and effects of IM-MS during a 20-year time span from a societal viewpoint. The outcome estimates were based on Level I evidence from postoperative RT literature and the cost estimates on the standard practice of the Leuven University Hospitals, with the RT costs derived from an activity-based costing program developed in the department. RESULTS: On the basis of the assumptions of the model and seen during a 20-year time span, primary treatment including IM-MS RT results in a cost savings (approximately 10,000) compared with a strategy without RT. Because IM-MS RT also results in better clinical effectiveness and greater quality of life, the treatment with IM-MS dominates the approach without IM-MS. Sensitivity analyses confirmed the robustness of these results in all tested circumstances. Although threshold values were found for the cost of IM-MS, the cost at relapse, and the quality of life after treatment, these were substantially different from the baseline estimates, indicating that it is very unlikely that omitting IM-MS would become superior. CONCLUSION: This ex-ante cost evaluation of IM-MS RT showed that the upfront costs of locoregional RT are easily compensated for by avoiding the costs of treating locoregional and distant relapse at a later stage. The cost-sparing effect of RT should, however, be evaluated for a sufficiently long time span and is most specifically found in tumors with a rather slow natural history and a multitude of available systemic treatments at relapse, such as breast cancer.

CHART in lung cancer: economic evaluation and incentives for implementation.

BACKGROUND AND PURPOSE: To investigate the financial consequences and the impact on daily implementation of CHART in lung cancer. PATIENTS AND METHODS: A cost-effectiveness and cost-utility analysis were performed using Markov models, comparing the early and delayed costs and effects of CHART for NSCLC over a 4-year time span from a societal viewpoint. The outcome estimates were based on the CHART literature, the cost estimates on the standard practice of the Leuven University Hospitals, the radiotherapy costs being derived from an activity-based costing (ABC) programme developed in the department. RESULTS: The additional societal cost per life-year gained was 9164 Euro, the incremental cost per quality-adjusted life-year 11,576 Euro. Sensitivity analyses confirmed the robustness of these results, the incremental cost-utility ratio remaining well under 20,000 Euro/QALY in all tested circumstances. The threshold analyses found the results of the study to be sensitive to the cost of CHART and to the quality of life after treatment. More specifically, standard treatment would become the optimal treatment if CHART would have a higher cost or would result in more long-term side effects. CONCLUSION: CHART should not be denied to patients with NSCLC on the basis of clinical or economic arguments. Other factors such as socio-economical, institutional, practical departmental and physician-bound barriers most probably explain the lack of implementation into daily practice.

The economic implications of non-adherence after renal transplantation.

BACKGROUND: The economic impact of therapeutic non-adherence in chronic diseases has rarely been examined using qualitative standards for economic evaluation. This study illustrates the impact of non-adherence on the cost utility of renal transplantation versus haemodialysis from the societal perspective and examines the scope for adherence-enhancing interventions. METHODS: Long-term costs and outcomes in adherent and non-adherent renal transplant patients were simulated in a Markov model. The cost (euros, year 2000 values) and outcome data that were imputed in the model were derived from a prospective study in renal transplantation candidates performed in 2002. Probabilities of adverse events, graft rejection, graft loss and death in adherent and non-adherent renal transplant patients were derived from literature. RESULTS: Compared with dialysis, renal transplantation offers a better outcome in both adherent and non-adherent patients. Lifetime costs after transplantation in the adherent patient group are higher than lifetime dialysis costs and lifetime costs in the non-adherent patient group, mainly because adherent patients live longer after transplantation. Long-term outcomes after transplantation are better for adherent than for non-adherent patients. The mean cost per QALY gained in adherent patients relative to non-adherent patients was euro 35 021 per QALY (95% CI 26 959, 46 620). CONCLUSION: Compared with established healthcare interventions, such as haemodialysis, renal transplantation can be considered a cost-effective therapy for patients with end-stage renal disease, even if patients are non-adherent after transplantation. The low incremental cost per QALY calculated in this model for adherent renal transplant patients, suggests there may be scope for adherence-enhancing interventions (provided that such interventions with a sufficiently high effectiveness exist or can be developed). As the findings are based on simulated long-term costs and outcomes, they should not be considered as precise estimates of the impact of non-adherence. This study is rather meant as an illustration of how non-adherence may impact on the results of cost-effectiveness analyses.

The construct and concurrent validity of the EQ-5D in a renal transplant population.

OBJECTIVES: Cost-utility analysis in renal transplant populations requires the use of a generic instrument for health status measurement that generates a single value for health. Such instruments should be widely applicable in diverse patient populations and their validity should be established. The aim of this study was to explore the validity of the EQ-5D in renal transplant patients. METHODS: The EQ-5D was compared with the Short-Form 36 Health Survey (SF-36), the modified transplant symptom occurrence and symptom distress (MTSOSD) scale, the short-form Beck Depression Inventory (BDI), and the State Trait Anxiety Inventory (STAI). Construct and concurrent validity were tested on cross-sectional data of 350 patients. RESULTS: Construct validity is good for some but not all EQ-5D dimensions, and the EQ-5D discriminates well among groups of patients with different health states according to the SF-36, MTSOSD scale, BDI, and STAI and between patients and the general public. Concurrent validity is good, as shown by the correspondence of EQ-5D and SF-36 results. CONCLUSION: It is concluded that the EQ-5D is a valid instrument for the measurement of health status in renal transplant patients.

Re-scaling social preference data: implications for modelling.

As applied in cost-utility analysis, generic health status indexes require that full health and dead are valued as 1 and 0, respectively. When social preference weights for health states are obtained using a visual analogue scale (VAS), their raw scores often lie on a scale with different endpoints (such as "best" and "worst" health). Re-scaling individual raw scores to a 0-1 scale leads to the exclusion of respondents who fail to value dead or full health. This study examined alternative approaches that do not impose such strict exclusion criteria. The impact of a different timing of re-scaling (before or after aggregation) and a different measure of central tendency (median or mean) is measured. Data from a postal valuation survey (n=722) conducted in Belgium are used. The following models are considered: (a) re-scaling values for EQ-5D health states on a within-respondent basis and using mean re-scaled values as proxies for social preference values, (b) using median re-scaled values as proxies for social preference values, (c) computing the median raw VAS values and then re-scale, and (e) re-scaling mean raw VAS values. Exclusion rates, health state rankings and valuations and incremental value differences between pairs of states are computed for each model. Models that use a different timing of re-scaling, are compared ceteris paribus to evaluate the importance of timing of re-scaling and models that use a different measure of central tendency are compared ceteris paribus to evaluate the importance of the measure of central tendency. The exclusion rates are above 20% in the models that re-scale valuations before aggregation and less than 5% in the models that re-scale after aggregation. Health state valuations are found to be different in all two by two comparisons. Although in some comparisons the incremental values are statistically significantly different between models, they are never clinically significantly different. Differences in health state rankings were larger between the models that use a different measure of central tendency than between the models that re-scale at a different time. This study shows that, for the data sample used, the choice of the measure of central tendency is more important for the social health status preference values than the timing of re-scaling. Using median original valuations in the analysis of EQ-5D valuation data is theoretically appealing because it builds on the "median voter" model and has the advantage of a lower respondent exclusion rate. Further analysis, on other data samples, will have to confirm the current findings.

Activity-based costing: a practical model for cost calculation in radiotherapy.

PURPOSE: The activity-based costing method was used to compute radiotherapy costs. This report describes the model developed, the calculated costs, and possible applications for the Leuven radiotherapy department. METHODS AND MATERIALS: Activity-based costing is an advanced cost calculation technique that allocates resource costs to products based on activity consumption. In the Leuven model, a complex allocation principle with a large diversity of cost drivers was avoided by introducing an extra allocation step between activity groups and activities. A straightforward principle of time consumption, weighed by some factors of treatment complexity, was used. The model was developed in an iterative way, progressively defining the constituting components (costs, activities, products, and cost drivers). RESULTS: Radiotherapy costs are predominantly determined by personnel and equipment cost. Treatment-related activities consume the greatest proportion of the resource costs, with treatment delivery the most important component. This translates into products that have a prolonged total or daily treatment time being the most costly. The model was also used to illustrate the impact of changes in resource costs and in practice patterns. CONCLUSION: The presented activity-based costing model is a practical tool to evaluate the actual cost structure of a radiotherapy department and to evaluate possible resource or practice changes.

Health professionals' perceptions of health status after renal transplantation: a comparison with transplantation candidates' expectations.

BACKGROUND: Renal transplantation is frequently considered superior to other renal replacement therapy in terms of survival and quality-of-life outcome. In this study, it was examined whether physicians and nurses have accurate perceptions of health status after renal transplantation (RTX) and whether renal transplant candidates have realistic expectations about posttransplant quality of life. METHODS: A comparative descriptive design was used for the comparison of physicians' and nurses' perceived and patients' expected and actual health status after RTX. Health status perceptions were measured by means of the EQ-5D self-report questionnaire. RTX candidates (n=107) were followed longitudinally from November 1999 until July 2001. Transplant patients (n=29) were surveyed 14 days and 4, 8, and 12 months after discharge from hospital. All physicians and nurses (n=123) had regular contact with dialysis or RTX patients. RESULTS: Physicians' and nurses' perceptions of health status after RTX were significantly lower than patients' expectations. Transplant nurses' and physicians' valuations were closer to patients' actual health status after transplantation than valuations of nurses on the dialysis or nephrology ward or at the outpatient clinic. CONCLUSIONS: RTX candidates frequently have higher expectations about their quality of life after transplantation than physicians and nurses who have regular contact with renal transplant patients. Physicians' and nurses' perceptions are closer to the actual health state after transplantation than patients' expectations. Thus, physicians and nurses are a reliable source of information for patients about the health state they can expect after transplantation.

A typology for provider payment systems in health care.

A typology to classify provider payment systems from an incentive point of view is developed. We analyse the way, how these systems can influence provider behaviour and, a fortiori, contribute to attain the general objectives of health care, i.e. quality of care, efficiency and accessibility. The first dimension of the typology indicates whether there is a link between the provider's income and his activity. In variable systems, the provider has an ability to influence his earnings, contrary to fixed systems. The second dimension indicates whether the provider's payments are related to his actual costs or not. In retrospective systems, the provider's own costs are the basis for reimbursement ex post whereas in prospective systems payments are determined ex ante without any link to the real costs of the individual provider. These different characteristics are likely to influence provider behaviour in different ways. Furthermore the most frequently used criteria to determine the provider's income are discussed: per service, per diem, per case, per patient and per period. Also a distinction is made between incentives at the level of the individual provider (micro-level) and the sponsor (macro-level). Finally, the potential interactions when several payment systems are used simultaneously are discussed. This typology is useful to classify and compare different types of payment systems as prevailing in different countries, and provides a useful framework for future research of health care payment systems.

A review of the literature on the economics of noncompliance. Room for methodological improvement.

Therapeutic noncompliance is a major issue in health care, having important negative consequences for clinical outcome as well as for health-care costs. This paper reviews the literature on the economics of therapeutic noncompliance, identifies methodological shortcomings and formulates recommendations for future economic research in this area. Medication noncompliance was explored more extensively, as the majority of articles dealt exclusively with this aspect of therapy. Eighteen studies were assessed according to their definition and measurement of medication noncompliance, study design, and identification and valuation of costs and outcomes. Very diverse designs and often invalid methods for calculating costs were found. Medication noncompliance is often ill-defined and measured in an inaccurate way. The economic consequences of therapeutic noncompliance have rarely been investigated according to the standard principles of good economic evaluation. Six studies examined both costs and consequences of noncompliance in a cost-outcome description or a cost-benefits, cost-effectiveness or cost-utility analysis. Eight studies dealt with the economic value of compliance-enhancing interventions. In general, studies on the economic consequences of noncompliance lack methodological rigour and fail to meet qualitative standards. There is a clear need for more and better research on the impact of noncompliance, on the cost-effectiveness of interventions and the potential of compliance-enhancing interventions to improve patient outcomes and/or reduce health-care costs.