Primary care practice characteristics associated with team functioning in primary care settings in Canada: A practice-based cross-sectional survey.

Team-based care is recognized as a foundational building block of high-performing primary care. The purpose of this study was to identify primary care practice characteristics associated with team functioning and examine whether there is relationship between team composition or size and team functioning. We sought to answer the following research questions: (1) are primary care practice characteristics associated with team functioning; and (2) does team composition or size influence team functioning. This cross-sectional correlational study was conducted in Fraser East, British Columbia, Eastern Ontario Health Unit, Ontario and Central Zone, Nova Scotia in Canada. Data were collected from primary care practices using an organization survey and the Team Climate Inventory (TCI) as a measure team functioning. The independent variables of interest were: physicians' payment model, internal clinic meetings to discuss clinical issues, care coordination through informal and ad hoc exchange, care coordination through electronic medical records and sharing clinic mission, values and objectives among health professionals. Potentially confounding variables were as follows: team size, composition, and practice panel size. A total of 63 practices were included in these analyses. The overall mean score of team climate was 73 (SD: 10.75) out of 100. Regression analyses showed that care coordination through human interaction and sharing the practice's mission, values, and objectives among health professionals were positively associated with higher functioning teams. Care coordination through electronic medical records and larger team size were negatively associated with team climate. This study provides baseline data on what practice characteristics are associated with highly functioning teams in Canada.

Hospital nurse-staffing models and patient- and staff-related outcomes.

BACKGROUND: Nurses comprise the largest component of the health workforce worldwide and numerous models of workforce allocation and profile have been implemented. These include changes in skill mix, grade mix or qualification mix, staff-allocation models, staffing levels, nursing shifts, or nurses' work patterns. This is the first update of our review published in 2011. OBJECTIVES: The purpose of this review was to explore the effect of hospital nurse-staffing models on patient and staff-related outcomes in the hospital setting, specifically to identify which staffing model(s) are associated with: 1) better outcomes for patients, 2) better staff-related outcomes, and, 3) the impact of staffing model(s) on cost outcomes. SEARCH METHODS: CENTRAL, MEDLINE, Embase, two other databases and two trials registers were searched on 22 March 2018 together with reference checking, citation searching and contact with study authors to identify additional studies. SELECTION CRITERIA: We included randomised trials, non-randomised trials, controlled before-after studies and interrupted-time-series or repeated-measures studies of interventions relating to hospital nurse-staffing models. Participants were patients and nursing staff working in hospital settings. We included any objective reported measure of patient-, staff-related, or economic outcome. The most important outcomes included in this review were: nursing-staff turnover, patient mortality, patient readmissions, patient attendances at the emergency department (ED), length of stay, patients with pressure ulcers, and costs. DATA COLLECTION AND ANALYSIS: We worked independently in pairs to extract data from each potentially relevant study and to assess risk of bias and the certainty of the evidence. MAIN RESULTS: We included 19 studies, 17 of which were included in the analysis and eight of which we identified for this update. We identified four types of interventions relating to hospital nurse-staffing models:- introduction of advanced or specialist nurses to the nursing workforce;- introduction of nursing assistive personnel to the hospital workforce;- primary nursing; and- staffing models.The studies were conducted in the USA, the Netherlands, UK, Australia, and Canada and included patients with cancer, asthma, diabetes and chronic illness, on medical, acute care, intensive care and long-stay psychiatric units. The risk of bias across studies was high, with limitations mainly related to blinding of patients and personnel, allocation concealment, sequence generation, and blinding of outcome assessment.The addition of advanced or specialist nurses to hospital nurse staffing may lead to little or no difference in patient mortality (3 studies, 1358 participants). It is uncertain whether this intervention reduces patient readmissions (7 studies, 2995 participants), patient attendances at the ED (6 studies, 2274 participants), length of stay (3 studies, 907 participants), number of patients with pressure ulcers (1 study, 753 participants), or costs (3 studies, 617 participants), as we assessed the evidence for these outcomes as being of very low certainty. It is uncertain whether adding nursing assistive personnel to the hospital workforce reduces costs (1 study, 6769 participants), as we assessed the evidence for this outcome to be of very low certainty. It is uncertain whether primary nursing (3 studies, > 464 participants) or staffing models (1 study, 647 participants) reduces nursing-staff turnover, or if primary nursing (2 studies, > 138 participants) reduces costs, as we assessed the evidence for these outcomes to be of very low certainty. AUTHORS' CONCLUSIONS: The findings of this review should be treated with caution due to the limited amount and quality of the published research that was included. We have most confidence in our finding that the introduction of advanced or specialist nurses may lead to little or no difference in one patient outcome (i.e. mortality) with greater uncertainty about other patient outcomes (i.e. readmissions, ED attendance, length of stay and pressure ulcer rates). The evidence is of insufficient certainty to draw conclusions about the effectiveness of other types of interventions, including new nurse-staffing models and introduction of nursing assistive personnel, on patient, staff and cost outcomes. Although it has been seven years since the original review was published, the certainty of the evidence about hospital nurse staffing still remains very low.