Quality Improvement with Outcome Data in Integrated Obstetric Care Networks: Evaluating Collaboration and Learning Across Organizational Boundaries with an Action Research Approach

Int J Integr Care. 2023 May 26;23(2):21. doi: 10.5334/ijic.7035. eCollection 2023 Apr-Jun.

Abstract

Introduction: Patient-reported outcome and experience measures (PROM and PREM) are used to guide individual care and quality improvement (QI). QI with patient-reported data is preferably organized around patients, which is challenging across organisations. We aimed to investigate network-broad learning for QI with outcome data.

Methods: In three obstetric care networks using individual-level PROM/PREM, a learning strategy for cyclic QI based on aggregated outcome data was developed, implemented and evaluated. The strategy included clinical, patient-reported, and professional-reported data; together translated into cases for interprofessional discussion. This study's data generation (including focus groups, surveys, observations) and analysis were guided by a theoretical model for network collaboration.

Results: The learning sessions identified opportunities and actions to improve quality and continuity of perinatal care. Professionals valued the data (especially patient-reported) combined with in-dept interprofessional discussion. Main challenges were professionals' time constraints, data infrastructure, and embedding improvement actions. Network-readiness for QI depended on trustful collaboration through connectivity and consensual leadership. Joint QI required information exchange and support including time and resources.

Conclusions: Current fragmented healthcare organization poses barriers for network-broad QI with outcome data, but also offers opportunities for learning strategies. Furthermore, joint learning could improve collaboration to catalyse the journey towards integrated, value-based care.

Keywords: collaboration; integrated care; interprofessional learning; patient-reported outcome measures; perinatal care; value-based healthcare.

Grants and funding

This work was supported by ZonMW [grant number 516012516]. ZonMW was not involved in study design, data collection, analysis, and interpretation of data, writing the report, and decision to submit the article for publication.