Title
Prof. Dr.
Last Name
Geissler
First name
Alexander
Email
alexander.geissler@unisg.ch
ORCID
Phone
+41 71 224 30 17
Homepage
Google Scholar
1 - 3 of 3
-
PublicationService-, needs-, and quality-based hospital capacity planning – The evolution of a revolution in SwitzerlandMost developed countries spend a large amount of their health budget on hospital capacities and inpatient services. However, those capacities and services are often not comprehensively planned what leads to vague service delivery steering and non-need driven hospital facilities. Switzerland is different as the planning procedure was completely reformed in 2012 and is further refined in 2021/2022. The Canton of Zurich, the frontrunner in Switzerland, has made a comprehensive update of its hospital capacity planning model for acute, psychiatric, and rehabilitative care. The result of this model is the hospital list. This list includes all hospitals which fulfil predefined quality, efficiency, and need requirements. Hospitals on the list receive a mandate to provide inpatient treatments for specific and selected service groups (n=196), clustered in three areas (acute care, psychiatry, rehabilitation). The underlying health care policy process is transparent and is characterized by a high participation of all relevant actors. The building blocks of the planning model are a classification system of service groups, different quality and efficiency requirements attached to these groups, and an analysis of current and future need for health care. Hospitals which are willing to perform services must apply and demonstrate that the requirements are fulfilled. The Canton then decides needs-based which hospital can deliver which services.
-
PublicationDefining minimum volume thresholds to increase quality of care: a new patient-oriented approach using mixed integer programmingA positive relationship between treatment volume and outcome quality has been demonstrated in the literature and is thus evident for a variety of procedures. Consequently, policy makers have tried to translate this so-called volume–outcome rela-tionship into minimum volume regulation (MVR) to increase the quality of care—yet with limited success. Until today, the effect of strict MVR application remains unclear as outcome quality gains cannot be estimated adequately and restrictions to application such as patient travel time and utilization of remaining hospital capacity are not considered sufficiently. Accord-ingly, when defining MVR, its effectiveness cannot be assessed. Thus, we developed a mixed integer programming model to define minimum volume thresholds balancing utility in terms of outcome quality gain and feasibility in terms of restricted patient travel time and utilization of hospital capacity. We applied our model to the German hospital sector and to four surgical procedures. Results showed that effective MVR needs a minimum volume threshold of 125 treatments for cholecystectomy, of 45 and 25 treatments for colon and rectum resection, respectively, of 32 treatments for radical prostatectomy and of 60 treatments for total knee arthroplasty. Depending on procedure type and incidence as well as the procedure’s complication rate, outcome quality gain ranged between 287 (radical prostatectomy) and 977 (colon resection) avoidable complications (11.7% and 11.9% of all complications). Ultimately, policy makers can use our model to leverage MVR’s intended benefit: concentrating treatment delivery to improve the quality of care.
-
PublicationThe impact of quality on hospital choice. Which information affects patients’ behavior for colorectal resection or knee replacement?Quality competition among hospitals, induced by patients freely choosing their hospital in a price regulated market, can only be realized if quality differences between hospitals are transparent, understandable, and thus influence patients’ hospital choice. We use data from ~145,000 German patients and ~ 900 hospitals for colorectal resections and knee replacements to investigate whether patients value quality and specialization when choosing their hospital. Using a random utility choice model, we estimate patients’ marginal utilities, willingness to travel and change in hospital demand for quality improvements. Patients respond to service quality and specialization and thus, quality competition seems to be present. Colorectal resection patients are willing to travel longer for more specialized hospitals (+9% for procedure volume, +9% for certification). Knee replacement patients travel longer for hospitals with better service quality (+6%) and higher procedure volume (+12%). However, clinical quality indicators, often difficult to access and interpret, barely play a role in patients’ hospital choice. Furthermore, we find that competition on quality for colorectal resection is rather local, whereas for knee replacement we observe regional competition patterns.Type:Journal:Volume:Issue: