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

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.

PROMs and PREMs in routine perinatal care: mixed methods evaluation of their implementation into integrated obstetric care networks.

BACKGROUND: In the transition towards value-based healthcare, patient-reported outcome and experience measures (PROM and PREM) are recommended by international collaborations and government programs to guide clinical practice and quality improvement. For many conditions, using PROM/PREM over the complete continuum of care requires implementation across care organizations and disciplines. Along PROM/PREM implementation in obstetric care networks (OCN), we aimed to evaluate implementation outcomes and the processes influencing these outcomes in the complex context of care networks across the continuum of perinatal care. METHODS: Three OCN in the Netherlands implemented PROM/PREM in routine practice, using an internationally developed outcomes set with care professionals and patient advocates. Their aim was to use PROM/PREM results individually to guide patient-specific care decisions and at group-level to improve quality of care. The implementation process was designed following the principles of action research: iteratively planning implementation, action, data generation and reflection to refine subsequent actions, involving both researchers and care professionals. During the one-year implementation period in each OCN, implementation outcomes and processes were evaluated in this mixed-methods study. Data generation (including observation, surveys and focus groups) and analysis were guided by two theoretical implementation frameworks: the Normalization Process Theory and Proctor's taxonomy for implementation outcomes. Qualitative findings were supplemented with survey data to solidify findings in a broader group of care professionals. RESULTS: Care professionals in OCN found the use of PROM/PREM acceptable and appropriate, recognized their benefits and felt facilitated in their patient-centered goals and vision. However, feasibility for daily practice was low, mainly due to IT issues and time constraints. Hence PROM/PREM implementation did not sustain, but strategies for future PROM/PREM implementation were formulated in all OCN. Processes contributing positively to implementation outcomes were internalization (understand the value) and initiation (driven by key-participants), whereas challenges in relational integration (maintain confidence) and reconfiguration (refine activities) affected implementation negatively. CONCLUSION: Although implementation did not sustain, network-broad PROM/PREM use in clinic and quality improvement matched professionals' motivation. This study provides recommendations to implement PROM/PREM meaningfully in practice in ways that support professionals in their drive towards patient-centered care. In order for PROM/PREM to fulfill their potential for value-based healthcare, our work highlights the need for sustainable IT infrastructures, as well as an iterative approach to refine their complex implementation into local contexts.

Understanding the Mismatch Between Coaches' and Players' Perceptions of Exertion.

A mismatch between the training exertion intended by a coach and the exertion perceived by players is well established in sports. However, it is unknown whether coaches can accurately observe exertion of individual players during training. Furthermore, the discrepancy in coaches' and players' perceptions has not been explained. PURPOSE: To determine the relation between intended and observed training exertion by the coach and perceived training exertion by the players and establish whether on-field training characteristics, intermittent endurance capacity, and maturity status explain the mismatch. METHODS: During 2 mesocycles of 4 wk (in November and March), rating of intended exertion (RIE), rating of observed exertion (ROE), and rating of perceived exertion (RPE) were monitored in 31 elite young soccer players. External and internal training loads were objectively quantified with accelerometers (PlayerLoad) and heart-rate monitors (TRIMPmod). Results of an interval shuttle-run test (ISRT) and age at peak height velocity (APHV) were determined for all players. RESULTS: RIE, ROE, and RPE were monitored in 977 training sessions. The correlations between RIE and RPE (r = .58; P < .01) and between ROE and RPE (r = .64; P < .01) were moderate. The mean difference between RIE and RPE was -0.31 ± 1.99 and between ROE and RPE was -0.37 ± 1.87. Multilevel analyses showed that PlayerLoad and ISRT predicted RIE and ROE. CONCLUSION: Coaches base their intended and observed exertion on what they expect players will do and what they actually did on the field. When doing this, they consider the intermittent endurance capacity of individual players.