Public policymakers are increasingly engaged in participatory model building processes, such as group model building. Understanding the impacts of policymaker participation in these processes on policymakers is important given that their decisions often have significant influence on the dynamics of complex systems that affect health. Little is known about the extent to which the impacts of participatory model building on public policymakers have been evaluated or the methods and measures used to evaluate these impacts.

A scoping review protocol was developed with the objectives of: (1) scoping studies that have evaluated the impacts of facilitated participatory model building processes on public policymakers who participated in these processes; and (2) describing methods and measures used to evaluate impacts and the main findings of these evaluations. The Joanna Briggs Institute’s Population, Concept, Context framework was used to formulate the article identification process. Seven electronic databases—MEDLINE (Ovid), ProQuest Health and Medical, Scopus, Web of Science, Embase (Ovid), CINAHL Complete and PsycInfo—will be searched. Identified articles will be screened according to inclusion and exclusion criteria and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist for scoping reviews will be used and reported. A data extraction tool will collect information across three domains: study characteristics, methods and measures, and findings. The review will be conducted using Covidence, a systematic review data management platform.

The scoping review produced will generate an overview of how public policymaker engagement in participatory model building processes has been evaluated. Findings will be disseminated through peer-reviewed publications and to communities of practice that convene policymakers in participatory model building processes. This review will not require ethics approval because it is not human subject research.

Paramedic assessment data have not been used for research on avoidable calls. Paramedic impression codes are designated by paramedics on responding to a 911/999 medical emergency after an assessment of the presenting condition. Ambulatory care sensitive conditions (ACSCs) are non-acute health conditions not needing hospital admission when properly managed. This study aimed to map the paramedic impression codes to ACSCs and mental health conditions for use in future research on avoidable 911/999 calls.

Mapping paramedic impression codes to existing definitions of ACSCs and mental health conditions.

East Midlands Region, UK and Southern Ontario, Canada.

Expert panel from the UK-Canada Emergency Calls Data analysis and GEospatial mapping (EDGE) Consortium.

Mapping was iterative first identifying the common ACSCs shared between the two countries then identifying the respective clinical impression codes for each country that mapped to those shared ACSCs as well as to mental health conditions. Experts from the UK-Canada EDGE Consortium contributed to both phases and were able to independently match the codes and then compare results. Clinical impression codes for paramedics in the UK were more extensive than those in Ontario. The mapping revealed some interesting inconsistencies between paramedic impression codes but also demonstrated that it was possible.

This is an important first step in determining the number of ASCSs and mental health conditions that paramedics attend to, and in examining the clinical pathways of these individuals across the health system. This work lays the foundation for international comparative health services research on integrated pathways in primary care and emergency medical services.

To assess the survival predictivity of baseline blood cell differential count (BCDC), discretised according to two different methods, in adults visiting an emergency room (ER) for illness or trauma over 1 year.

Retrospective cohort study of hospital records.

Tertiary care public hospital in northern Italy.

11 052 patients aged >18 years, consecutively admitted to the ER in 1 year, and for whom BCDC collection was indicated by ER medical staff at first presentation.

Survival was the referral outcome for explorative model development. Automated BCDC analysis at baseline assessed haemoglobin, mean cell volume (MCV), red cell distribution width (RDW), platelet distribution width (PDW), platelet haematocrit (PCT), absolute red blood cells, white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils and platelets. Discretisation cut-offs were defined by benchmark and tailored methods. Benchmark cut-offs were stated based on laboratory reference values (Clinical and Laboratory Standards Institute). Tailored cut-offs for linear, sigmoid-shaped and U-shaped distributed variables were discretised by maximally selected rank statistics and by optimal-equal HR, respectively. Explanatory variables (age, gender, ER admission during SARS-CoV2 surges and in-hospital admission) were analysed using Cox multivariable regression. Receiver operating curves were drawn by summing the Cox-significant variables for each method.

Of 11 052 patients (median age 67 years, IQR 51–81, 48% female), 59% (n=6489) were discharged and 41% (n=4563) were admitted to the hospital. After a 306-day median follow-up (IQR 208–417 days), 9455 (86%) patients were alive and 1597 (14%) deceased. Increased HRs were associated with age >73 years (HR=4.6, 95% CI=4.0 to 5.2), in-hospital admission (HR=2.2, 95% CI=1.9 to 2.4), ER admission during SARS-CoV2 surges (Wave I: HR=1.7, 95% CI=1.5 to 1.9; Wave II: HR=1.2, 95% CI=1.0 to 1.3). Gender, haemoglobin, MCV, RDW, PDW, neutrophils, lymphocytes and eosinophil counts were significant overall. Benchmark-BCDC model included basophils and platelet count (area under the ROC (AUROC) 0.74). Tailored-BCDC model included monocyte counts and PCT (AUROC 0.79).

Baseline discretised BCDC provides meaningful insight regarding ER patients’ survival.

Community Paramedicine (CP) is increasingly being used to provide chronic disease management for vulnerable populations in the community. CP@clinic took place in social housing buildings to support cardiovascular health and diabetes management for older adults. The purpose of this study was to examine participant perceptions of their experience with CP@clinic as well as potential ongoing programme benefits.

This descriptive qualitative study used focus groups to understand resident experiences of the CP@clinic programme. Groups were facilitated by experienced moderators using a semistructured guide. An inductive coding approach was used with at least two researchers taking part in each step of the analysis process.

Community-based social housing buildings in Ontario, Canada.

Forty-one participants from four CP@clinic sites took part in a focus group. Convenience sampling was used with anyone having taken part in a CP@clinic session being eligible to attend the focus group.

Analysis yielded six themes across two broad areas: timely access to health information and services, support to achieve personal health goals, better understanding of healthcare system (Personal Benefits); and sense of community, comfortable and familiar place to talk about health, facilitated communication between healthcare professionals (Programme Structure). Participants experienced discernible health changes that motivated their participation. CP@clinic was viewed as a programme that created connections within the building and outside of it. Participants were enthusiastic for the continuation of the programme and appreciated the consistent support to meet their health goals.

CP@clinic was successful in creating a supportive and friendly environment to facilitate health behavioural changes. Ongoing implementation of CP@clinic would allow residents to continue to build their chronic disease management knowledge and skills.

Trial registration number: NCT02152891, Clinicaltrials.gov.