Development and testing of the QDis-MH checklist for discharge letters from specialised mental healthcare: a stakeholder-centred study.

BACKGROUND: The 'discharge letter' is the mandatory written report sent from specialists in the specialist services to general practitioners (GPs) on patient discharge. Clear recommendations from relevant stakeholders for contents of discharge letters and instruments to measure the quality of discharge letters in mental healthcare are needed. The objectives were to (1) detect which information relevant stakeholders defined as important to include in discharge letters from mental health specialist services, (2) develop a checklist to measure the quality of discharge letters and (3) test the psychometric properties of the checklist. METHODS: We used a stepwise multimethod stakeholder-centred approach. Group interviews with GPs, mental health specialists and patient representatives defined 68 information items with 10 consensus-based thematic headings relevant to include in high-quality discharge letters. Information items rated as highly important by GPs (n=50) were included in the Quality of Discharge information-Mental Health (QDis-MH) checklist. The 26-item checklist was tested by GPs (n=18) and experts in healthcare improvement or health services research (n=15). Psychometric properties were assessed using estimates of intrascale consistency and linear mixed effects models. Inter-rater and test-retest reliability were assessed using Gwet's agreement coefficient (Gwet's AC1) and intraclass correlation coefficients. RESULTS: The QDis-MH checklist had satisfactory intrascale consistency. Inter-rater reliability was poor to moderate, and test-retest reliability was moderate. In descriptive analyses, mean checklist scores were higher in the category of discharge letters defined as 'good' than in 'medium' or 'poor' letters, but differences did not reach statistical significance. CONCLUSIONS: GPs, mental health specialists and patient representatives defined 26 information items relevant to include in discharge letters in mental healthcare. The QDis-MH checklist is valid and feasible. However, when using the checklist, raters should be trained and the number of raters kept to a minimum due to questionable inter-rater reliability.

Measuring implementation: development of the implementation process assessment tool (IPAT).

BACKGROUND: Implementation science comprises a large set of theories suggesting interacting factors at different organisational levels. Development of literature syntheses and frameworks for implementation have contributed to comprehensive descriptions of implementation. However, corresponding instruments for measuring these comprehensive descriptions are currently lacking. The present study aimed to develop an instrument measuring care providers' perceptions of an implementation effort, and to explore the instrument's psychometric properties. METHODS: Based on existing implementation literature, a questionnaire was designed with items on individual and team factors and on stages of change in an implementation process. The instrument was tested in a Norwegian study on implementation of evidence based practices for psychosis. Item analysis, factor structure, and internal consistency at baseline were examined. RESULTS: The 27-item Implementation Process Assessment Tool (IPAT) revealed large variation between mean score of the items. The total scale scores were widely dispersed across respondents. Internal consistency for the total scale was high (Cronbach's alpha: .962), and all but one item contributed positively to the construct. The results indicated four underlying constructs: individual stages for behavioural change, individual activities and perceived support, collective readiness and support, and individual perceptions of the intervention. CONCLUSIONS: The IPAT appears to be a feasible instrument for investigating the implementation process from the perspective of those making the change. It can enable examination of the relative importance of factors thought to be essential for implementation outcomes. It may also provide ongoing feedback for leaders tailoring support for teams to improve implementation. However, further research is needed to detect the instrument's properties later in the implementation process and in different contexts. TRIAL REGISTRATION: ClinicalTrials.gov code NCT03271242 (retrospective registered September 5, 2017).