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Payment for performance (P4P): any future in Italy?

Silvana Castaldi1, Annalisa Bodina, Luciana Bevilacqua

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Pay for Performance (P4P) programs can be implemented in Italy's Lombardy Region. Successful implementation requires standardized electronic data collection and further assessment of clinical conditions and financial incentives.

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Area of Science:

  • Health Services Research
  • Healthcare Management
  • Quality Improvement

Background:

  • Pay for Performance (P4P) programs utilize financial incentives to enhance healthcare quality and efficiency.
  • Growing concerns about healthcare quality and resource scarcity in Italy highlight the potential of P4P programs.
  • This study assesses the feasibility of implementing P4P programs in Italy's Lombardy Region using existing data.

Purpose of the Study:

  • To evaluate the implementability of Pay for Performance (P4P) programs in the Lombardy Region, Italy.
  • To determine if existing data sets are sufficient for P4P program implementation.
  • To identify key considerations for launching a P4P program in the region.

Main Methods:

  • Identified 13 quality measures across four clinical conditions (AMI, HF, stroke, hip/knee replacement) based on international literature.
  • Collected data from hospital discharge records (SDO) and discharge letters from three institutions.
  • Utilized Principal ICD-9-CM codes and discharge dates for patient identification and SAS for data analysis.

Main Results:

  • Data availability was sufficient to calculate most quality parameters for the studied hospitals.
  • Inpatient mortality data was missing for two hospitals, and smoking cessation advice data for one.
  • The existing data infrastructure largely supports the calculation of performance metrics.

Conclusions:

  • Implementation of Pay for Performance (P4P) programs is feasible in the Lombardy Region.
  • Uniform, electronic data collection is crucial for P4P program initiation.
  • Further assessment is needed regarding included clinical conditions, quality thresholds, and incentive structures.