Value in psoriasis (IRIS) trial: implementing value-based healthcare in psoriasis management - a 1-year prospective clinical study to evaluate feasibility and value creation.

INTRODUCTION: Currently, the healthcare sector is under tremendous financial pressure, and many acknowledge that a dramatic shift is required as the current system is not sustainable. Furthermore, the quality of care that is delivered varies strongly. Several solutions have been proposed of which the conceptual framework known as value-based healthcare (VBHC) is further explored in this study for psoriasis. Psoriasis is a chronic inflammatory skin disease, which is associated with a high disease burden and high treatment costs. The objective of this study is to investigate the feasibility of using the VBHC framework for the management of psoriasis. METHODS AND ANALYSIS: This is a prospective clinical study in which new patients attending the psoriasis clinic (PsoPlus) of the Ghent University Hospital will be followed up during a period of 1 year. The main outcome is to determine the value created for psoriasis patients. The created value will be considered as a reflection of the evolution of the value score (ie, the weighted outputs (outcomes) divided by weighted inputs (costs)) obtained using data envelopment analysis. Secondary outcomes are related to comorbidity control, outcome evolution and treatment costs. In addition, a bundled payment scheme will be determined as well as potential improvements in the treatment process. A total of 350 patients will be included in this trial and the study initiation is foreseen on 1 March 2023. ETHICS AND DISSEMINATION: This study has been approved by the Ethics Committee of the Ghent University Hospital. The findings of this study will be disseminated by various means: (1) publication in one or more peer-reviewed dermatology and/or management journals, (2) (inter)national congresses, (3) via the psoriasis patient community and (4) through the research team's social media channels. TRIAL REGISTRATION NUMBER: NCT05480917.

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.

Variability in hospital treatment costs: a time-driven activity-based costing approach for early-stage invasive breast cancer patients.

OBJECTIVES: Using a standardised diagnostic and generic treatment path for breast cancer, and the molecular subtype perspective, we aim to measure the impact of several patient and disease characteristics on the overall treatment cost for patients. Additionally, we aim to generate insights into the drivers of cost variability within one medical domain. DESIGN, SETTING AND PARTICIPANTS: We conducted a retrospective study at a breast clinic in Belgium. We used 14 anonymous patient files for conducting our analysis. RESULTS: Significant cost variations within each molecular subtype and across molecular subtypes were found. For the luminal A classification, the cost differential amounts to roughly 166%, with the greatest treatment cost amounting to US$29 780 relative to US$11 208 for a patient requiring fewer medical activities. The major driver for these cost variations relates to disease characteristics. For the luminal B classification, a cost difference of roughly 242% exists due to both disease-related and patient-related factors. The average treatment cost for triple negative patients amounted to US$26 923, this is considered to be a more aggressive type of cancer. The overall cost for HER2-enriched is driven by the inclusion of Herceptin, thus this subtype is impacted by disease characteristics. Cost variability across molecular classifications is impacted by the severity of the disease, thus disease-related factors are the major drivers of cost. CONCLUSIONS: Given the cost challenge in healthcare, the need for greater cost transparency has become imperative. Through our analysis, we generate initial insights into the drivers of cost variability for breast cancer. We found evidence that disease characteristics such as severity and more aggressive cancer forms such as HER2-enriched and triple negative have a significant impact on treatment cost across the different subtypes. Similarly, patient factors such as age and presence of gene mutation contribute to differences in treatment cost variability within molecular subtypes.

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.

Due time driven surgery scheduling.

In many hospitals there are patients who receive surgery later than what is medically indicated. In one of Europe's largest hospitals, the University Hospital Leuven, this is the case for approximately every third patient. Serving patients late cannot always be avoided as a highly utilized OR department will sometimes suffer capacity shortage, occasionally leading to unavoidable delays in patient care. Nevertheless, serving patients late is a problem as it exposes them to an increased health risk and hence should be avoided whenever possible. In order to improve the current situation, the delay in patient scheduling had to be quantified and the responsible mechanism, the scheduling process, had to be better understood. Drawing from this understanding, we implemented and tested realistic patient scheduling methods in a discrete event simulation model. We found that it is important to model non-elective arrivals and to include elective rescheduling decisions made on surgery day itself. Rescheduling ensures that OR related performance measures, such as overtime, will only loosely depend on the chosen patient scheduling method. We also found that capacity considerations should guide actions performed before the surgery day such as patient scheduling and patient replanning. This is the case as those scheduling strategies that ensure that OR capacity is efficiently used will also result in a high number of patients served within their medically indicated time limit. An efficient use of OR capacity can be achieved, for instance, by serving patients first come, first served. As applying first come, first served might not always be possible in a real setting, we found it is important to allow for patient replanning.

On the use of planning models in the operating theatre: results of a survey in Flanders.

This paper presents an overview of the operating theatre planning and scheduling practice of hospitals in Flanders (Belgium). An electronic survey was sent to 95 hospitals in which surgeries are performed, which eventually resulted in a response set of 52 hospitals (55%). The questionnaire did not only focus on issues related to the elective (inpatient and outpatient) planning and scheduling process, but also questioned how hospitals currently deal with the occurrence of non-elective surgeries (urgencies and emergencies). We indicate what goals health managers try to achieve and how this planning is established. We furthermore pay attention to some possible disruptions to the schedule and the corresponding anticipatory methods. Despite the proliferation of computerized planning and scheduling procedures proposed by the scientific community, the implementation rate of satisfying technological planning or evaluation systems still seems to be low. In order to increase the operating theatre efficiency, a closer cooperation between the academic institutions and the practitioners should be encouraged.

Capacity of clinical pathways--a strategic multi-level evaluation tool.

In this paper we strategically evaluate the efficiency of clinical pathways and their complex interdependencies with respect to joint resource usage and patient throughput. We propose a discrete-event simulation approach that allows for the simultaneous evaluation of multiple clinical pathways and the inherent uncertainty (resource, duration and arrival) that accompanies medical processes. Both the consultation suite and the surgery suite may be modeled and examined in detail by means of sensitivity or scenario analyses. Since each medical facility can somehow be represented as a combination of clinical pathways, i.e. they are conceptually similar, the simulation model is generic in nature. Next to the formulation of the model, we illustrate its applicability by means of a case study that was conducted in a Belgian hospital.

Visualizing the demand for various resources as a function of the master surgery schedule: a case study.

This paper presents a software system that visualizes the impact of the master surgery schedule on the demand for various resources throughout the rest of the hospital. The master surgery schedule can be seen as the engine that drives the hospital. Therefore, it is very important for decision makers to have a clear image on how the demand for resources is linked to the surgery schedule. The software presented in this paper enables schedulers to instantaneously view the impact of, e.g., an exchange of two block assignments in the master surgery schedule on the expected resource consumption pattern. A case study entailing a large Belgian surgery unit illustrates how the software can be used to assist in building better surgery schedules.