gms | German Medical Science

19. Deutscher Kongress für Versorgungsforschung

Deutsches Netzwerk Versorgungsforschung e. V.

30.09. - 01.10.2020, digital

It probably worked: a Bayesian approach to evaluating Israel’s 2013 hospital reform

Meeting Abstract

  • Martin Siegel - Technische Universität Berlin, FG Empirische Gesundheitsökonomie, Berlin, Deutschland; BerlinHECOR
  • Ruth Waitzberg - The Smokler Center for Health Policy Research, Israel; Technische Universität Berlin, Management im Gesundheitswesen, Berlin, Deutschland
  • Wilm Quentin - Technische Universität Berlin, Management im Gesundheitswesen, Berlin, Deutschland
  • Reinhard Busse - BerlinHECOR; Technische Universität Berlin, Management im Gesundheitswesen, Berlin, Deutschland
  • Dan Greenberg - Ben-Gurion University of the Negev, Israel

19. Deutscher Kongress für Versorgungsforschung (DKVF). sine loco [digital], 30.09.-01.10.2020. Düsseldorf: German Medical Science GMS Publishing House; 2020. Doc20dkvf093

doi: 10.3205/20dkvf093, urn:nbn:de:0183-20dkvf0932

Veröffentlicht: 25. September 2020

© 2020 Siegel et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Background and current state of (inter)national research: Israel changed its reimbursement scheme in hospital care from per-diem to procedure-specific lump sum payments for a set of elective procedures in 2013. The aim was to decrease waiting times by incentivizing hospitals to treat more patients in less time.

Research questions and objectives: This study evaluates the effect of this reform on annual case numbers and on patients’ length of stay (LoS) in hospitals.

Methods or hypothesis: We use administrative data from Israel’s Ministry of Health on 14 medical procedures in three medical fields for the years 2005-2016. We employ a duration analysis framework to estimate the probability that the reform decreased patients’ LoS. We then use the absolute changes in the numbers of patients treated per year to assess whether annual changes after the reform differ from those before the reform. We opt for a Bayesian estimation approach, which allows us to add a different perspective to the interpretation of policy impact analyses that goes beyond a merely dichotomous decision over hypotheses.

Results: A total of n=83,318 cases were included in our analysis. The point estimates derived from the posterior distributions of the time ratios suggest that LoS decreased after the reform for 12 out of 14 procedures. The estimated decreases vary considerably between different procedures, ranging from 2.5% to 20%. Adding the Bayesian perspective, our analysis yields a probability of over 95% to observe a shorter LoS after the reform in 1 out of 5 surgical procedures, in 6 out of 7 urological procedures and in 1 out of 2 gynecological procedures. Somewhat surprisingly, only two procedures yield a probability of over 95% to observe an increase in absolute changes in case numbers. We interpret these high probabilities analogously to p-values such that a probability of over 95% to have a shorter LoS after the reform roughly corresponds to a significant effect with a p-value below 5% (when testing against a one-sided null hypothesis).

Discussion: LoS decreased with a high probability in 8 out of 14 procedures after this policy change, but the extent varied considerably between procedures and across medical fields. Finding a clear effect on the numbers of patients treated in only two procedures is somewhat surprising in the light of the decreased LoS. A potential explanation may be that hospitals increase the lengths of stay after procedures which may still be paid per-diem, or shift their efforts to procedures with more lucrative lump-sum reimbursements.

Practical implications: We speculate that balancing economic and medical considerations depends on the particularities of the medical procedures under consideration and may lead to different responses in different medical fields.