What work has to be done to implement collaborative care for depression? Process evaluation of a trial utilizing the Normalization Process Model

协作护理 卫生服务研究 医疗保健 定性研究 医学 心理健康 干预(咨询) 过程(计算) 定性性质 护理部 焦点小组 卫生行政 心理学 公共卫生 计算机科学 精神科 社会学 机器学习 经济 操作系统 经济增长 社会科学 人类学
作者
Linda Gask,Peter Bower,Karina Lovell,Diane Escott,Janine Archer,Simon Gilbody,Annette Lankshear,Angela E Simpson,David Richards
出处
期刊:Implementation Science [BioMed Central]
卷期号:5 (1) 被引量:70
标识
DOI:10.1186/1748-5908-5-15
摘要

There is a considerable evidence base for 'collaborative care' as a method to improve quality of care for depression, but an acknowledged gap between efficacy and implementation. This study utilises the Normalisation Process Model (NPM) to inform the process of implementation of collaborative care in both a future full-scale trial, and the wider health economy. Application of the NPM to qualitative data collected in both focus groups and one-to-one interviews before and after an exploratory randomised controlled trial of a collaborative model of care for depression. Findings are presented as they relate to the four factors of the NPM (interactional workability, relational integration, skill-set workability, and contextual integration) and a number of necessary tasks are identified. Using the model, it was possible to observe that predictions about necessary work to implement collaborative care that could be made from analysis of the pre-trial data relating to the four different factors of the NPM were indeed borne out in the post-trial data. However, additional insights were gained from the post-trial interview participants who, unlike those interviewed before the trial, had direct experience of a novel intervention. The professional freedom enjoyed by more senior mental health workers may work both for and against normalisation of collaborative care as those who wish to adopt new ways of working have the freedom to change their practice but are not obliged to do so. The NPM provides a useful structure for both guiding and analysing the process by which an intervention is optimized for testing in a larger scale trial or for subsequent full-scale implementation.
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