The impact of pay-for-performance on the workload of family practices in Estonia

Qual Prim Care. 2014;22(2):109-14.

Abstract

Background: The quality system in Estonia is a payfor-performance scheme, rewarding family doctors for the quality of care they provide. This study examines the impact of the quality system on the workload of family doctors in Estonia.

Aim: The aim of this study was to explore differences in the workload of family doctors participating in the clinical quality system and those not participating.

Methods: The study was conducted using a database from the Estonian Health Insurance Fund, which consists of health-related data for 96% of the Estonian population. The study compared the workload of Estonian family physicians in two groups: those participating in the quality system and those not.

Results: During the observation period 2005-2011, the proportion of family doctors participating in the clinical quality system increased from 48.2% to 69.2%. The total number of visits in primary care increased also and there was a difference in workload between the two groups. Doctors participating in the quality system performed more primary (initial) and secondary (follow-up) visits. The number of visits per doctor was also higher for those participating in the quality system. There was a shift to visits carried out by nurses, which showed an increased workload for nurses in the quality system during the observation period compared with a stable workload for those outside the system. The number of home visits decreased in both groups.

Conclusion: Pay-for-performance had a notable impact on the workload of the primary care team and its members. Paying more attention to detecting chronic diseases in their early stages, recalling patients for general health check-ups and immunising children may have an effect on health status, but also requires increased staff levels.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Estonia
  • Family Practice / statistics & numerical data*
  • General Practitioners / statistics & numerical data
  • Humans
  • Nurses / statistics & numerical data
  • Reimbursement, Incentive / statistics & numerical data*
  • Workload / statistics & numerical data*