Benchmark cost or previous year's cost model - experiences from Switzerland:
On top, the systems to be implemented in Germany show crucial elements of managed care as known from the anglo-saxon area and other european neighbours. Thus Robert Seitz and Dominik Graf von Stillfried define the term 'managed care' in their article "Fundamentals of managed care" as follows: Patients are led to certain places of service provision, to chosen suppliers, or their utilisation is governed directly via definite guidelines and indirectly by financial incentives respectively. The suppliers are "guided" indirectly per remuneration modes and financial incentives, or directly through preliminaries about the spectre of supply and the modalities of service provision (12).
Taking a look at the nowadays even perennial experiences with managed care in Switzerland show some important exercised fundamentals of medical billing in morbidity-orientated remuneration structures (1,3).
In 1990, Swiss health insurance companies started to establish their own Health Maintenance Organizations (HMOs), at which physicians took up services as employees of the HMOs. The achievements in stabilising the costs in the Swiss health care system were remarkable. Thus, only a short time after their establishment, the first HMOs succeeded in meeting or even going below budget allowances (6). This economically overly successful implementation of funds-innate HMO-surgeries was followed by self-governing general practioner's network models (Wintimed doctors, since 1994) including bonus/malus regulations and the Medi-X-group surgeries (Medi-X-Zürich since 1998) that are specialist-orientated to a greater extent and counting on trans-disciplinary and -institutional integrative cooperation of their members. The Medi-X-group surgeries work contractually on the basis of capitation fees for the insurances, whereas capitation and budget contracts respectively encompass a full acceptance of the morbidity risk of the treated patient by the supplier. To limit risks for the suppliers, the group of high-risk patients is covered additionally by a special insurance (Grossoversicherung). A preferably exact mapping of the clientele's risk structure is of vital importance to the contracting parties with these capitation contracts (6,3).
Two methods are used in Switzerland as a calculation basis for negotiations between health and care insurance providers and service providers, which are partially alternative, partially parallel and complementary in mapping morbidity and costs structures of the service providers, and which on that basis calculate a medical total budget.
On the one hand, the so-called previous year's cost model is applied, for which a total budget is agreed upon with the health insurance companies on the basis of the patient structure of the preceding year. Based on this total budget, the bonus/malus regulations are declared for excessing or going below the budget respectively. The advantages of this system lie in its already mapping the morbidity structure (of the previous year) and with it allow for a relatively simple and secure updating of patients' morbidity structure. Its disadvatanges result from the danger of excluding high-risk profile patients (13) and from the lack of stimulus for the following years, since a savings potential once exhausted cannot lead to further bonus regulations (6).
On the other hand, the second model applied is based on the so-called benchmark cost model, which draws morbidity and risk structures from external reference to comparable service providers and, like that, enables the calculation of the budget. The advantages of this model are the comparability of different service providers and the abated risk of excluding patients. Disadvantages lie in the very costly calculation of a reference model (3).
Though, both models adopted in Switzerland are predicated on combined budgets for the service suppliers, i.e. a direct linkage of medical remuneration with occasioned services like medications, medical and other devices as well as hospitalisation.
Identify high-risk patients:
A detailled risk stratification depending on concomitance and severity code of co-morbidities would guarantee for the patient
to receive exactly those medical supplies and measures corresponding with his personal needs. Hence it is a matter of the "individualisation" of
medicine based on individual diagnoses of secondary disorders and complications. Health economists utilize computer simulations for this purpose,
which are supposed to predict a disease's course. But the systems currently available are essentially built on data and results of literary sources
at hand. Simulation models including definite outcome results from real patient data are nearly undetectable at least for the middle-european
area up to now.
Following Künzi (8), for evaluating the real supply quality only that structure and process data is to be used, for which an alteration is proven to have effected a better outcome.
In 2000, within the scope of the treaty of quality advancement (Vertrag zur Qualitätsförderung, in: Schweizer Krankenversicherungsordnung), the santésuisse (the trade association of Swiss health insurance companies) and H+ (the Swiss spital association) performed a survey to define quality indicators, within which 6 quality indicators were analysed respecting their meaning for quality value, the degree to which transferability to patient groups can be generalised, the validity of measurement methods, the representation of case-mix, and the interpretability (10,5).
The FoQual-study subsequently reaches the conclusion that out of these 6 audited indicators only the quality in coding the diagnoses (completeness, accurateness and plausibility) has crucial influence on the quality of supply.
Conclusion:
From this viewpoint, future standard benefit volumes including defined risk classes and relative weights are by all means to be welcomed and will, apart from a more just monetary estimation of medical services, serve to provide the patient with the adequate and fit for demand bundle of measures.
Literature:
- Baur R., Hunger W., Kämpf K., Stock J.; Evaluation neuer Formen der Krankenversicherung. Synthesebericht Nr. 1/98 BSV: Beiträge zur Sozialen Sicherheit
- Bierwirth R. A., Kron P., Lippmann-Grob B., Funke K., Leinhos B., Grüneberg M., Huptas H., Weich K., Münscher C., Potthoff F.: Die TEMPO-Studie: Kostenanalyse in der diabetologischen Schwerpunktpraxis und Definition diabetesspezifischer Risikoprofile; Diabetes- & Stoffwechsel 12/2003, 83-94
- Bührer, A.: Grundlagen zur finanziellen Erfolgsbemessung in Managed Care Systemen. Schweizer Ärztezeitung (2000;81:Nr 21 1040- 1045
- Eckpunkte der Konsensverhandlung zur Gesundheitsreform, Homepage des Bundesministeriums für Gesundheit und soziale Sicherung
- http://www.bmgs.bund.de/deu/gra/themen/gesundheit/eck.cfm
- FoQual: Die Qualität der Gesundheitsversorgung in den Schweizer Spitälern: Analyse von sechs Indikatoren. September 2000.
- Huber F., Marti C., Götschi A.S., Weber A.: Managed Care in der Schweiz; Schweizer Ärztezeitschrift (2002), 83: Nr 48; 2629-2632
- Künzi B.: Ergebnisqualität bei chronischen Krankheiten messen und verbessern; Managed Care (2001) 5, 22-24
- Münscher C., Potthoff F. et al. DRG's für die ambulante Diabetologie?! Risikoprofilanalysen bei Typ-2 Diabetikern in der Diabetologischen Schwerpunktpraxis. Rotenburg/F.: AkPro (2003)
- Nocera S.: Rationierung- Begriffsbestimmung und Konzepte; Managed Care (2001) 6, 8-12
- Schenker M.: Die Qualität der Qualitätsmessung; Managed Care (2002) 2, 15-16
- Seitz R., König H.-H., Stillfried v.D.: Grundlagen von Managed Care in Managed Care von Arnold, Lauterbach und Preuß S.325- 340, Schattauer Verlag 1997, ISBN 3-7945-1747-4
- Weber A., Cottini G.: Kostenvorteile dank Risikoselektion?; Schweizer Zeitschrift Managed Care (1998) 14 - 7