ArticleBMC health services research2022
Cyclic workflow to improve implementation of learning points from morbidity and mortality meetings.
Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMorbidity and mortality meetings (M&MMs) are organized in most hospital departments with an educational purpose to learn from adverse events (AEs) to improve patient care. M&MMs often lack effectiveness due to unsuccessful systematic follow-up of areas of improvement. This can have an effect on improving patient safety and care. Therefore, a new strategy that focuses on implementing areas of improvement into daily practice is necessary. The study aim is to see if we could improve the implementation of meeting outcomes from the M&MM by using a cyclic workflow, and which factors are important to achieve its implementation.
methodsThis prospective study took place at the department of gynecologic oncology of a university hospital. Research was conducted with a participatory action research (PAR) approach using 10 consecutive M&MMs in 2019 and 2020. The cyclical workflow consisted of an action list based on the PDCA-cycle, a check of the implementation of areas for improvement at the next M&MM and regular monitoring of tasks. Each M&MM was observed and each professional with an assigned task was interviewed and gave their informed consent. Thematic content analysis was performed with the program Atlas.ti 8.4.20.
resultsOut of the 39 tasks that resulted from 10 M&MMs, 37 (94.8%) followed all the steps in the PDCA-cycle and were implemented. In total, 16 interviews were conducted with consultants, nurses, registrars and residents. Five main factors were important to achieve follow-up of areas for improvement: organizational culture, motivation, commitment, communication to mobilize employees and skills. Repetition of the cyclic workflow at the M&MM and an external person who reminded professionals of their assigned task(s) was important to change habits and motivate professionals.
conclusionCyclical tools can support the implementation of areas for improvement to optimize the M&MM. A M&MM with an organizational culture where attendees can discuss openly and freely may motivate attendees to take on tasks successfully. A positive stimulant to reach commitment of professionals is team participation. Integrating new habits of reflection may lead to a deeper level of learning from the PDCA-cycle and of the M&MM. Creating a learning environment outside of the M&MM may support professionals to take on actions and engage in improvement practices. Future research may focus on including a comparative analysis to show a success rate of the implementation of learning points from the M&MM more clearly.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.