Implementing the patient care collaborative model in three general internal medicine units: a mixed-methods healthcare improvement initiative.

BACKGROUND: As part of the scale-up of the Patient Care Collaborative (PCC) at our institution, we explored staff perceptions and patient outcomes at different levels of model implementation in three general internal medicine units. METHODS: We conducted a mixed-methods embedded experimental healthcare improvement initiative. In the qualitative strand, we conducted five focus group discussions. In the quantitative strand, we used hospital administrative data to compare outcomes (falls per 1000, median length of stay in days and resource use measured as resource intensity weights (RIW), before and after the implementation of the PCC, using χ2 tests, Wilcoxon's rank sum tests and interrupted time series analyses. RESULTS: Staff showed considerable knowledge and acceptance of the PCC but expressed mixed feelings with regards to patient safety, workload, communication and teamwork. Staff perceptions varied by level of implementation of the PCC. A number of falls (overall) in the full implementation phase were not significantly different from the preimplementation phase (227 per 1000 vs 200 per 1000; p=0.449), but the number of moderate to severe falls dropped (12 vs 2 per 1000); p<0.001). Median length of stay (5 vs 6 days; p<0.001) and resource use were lower (0.1 vs 0.4; p<0.001) in the full implementation phase compared with the preimplementation phase. The trend analyses showed differences across units. CONCLUSIONS: The PCC was moderately well adopted. Perceptions of the PCC among staff and patient outcomes are likely linked to the levels of implementation. The PCC resulted in improved safety, shorter hospital stays and lower costs of care.

Effect of computer-generated tailored feedback on glycemic control in people with diabetes in the community: a randomized controlled trial.

OBJECTIVE: It is unknown whether computer-generated, patient-tailored feedback leads to improvements in glycemic control in people with type 2 diabetes. RESEARCH DESIGN AND METHODS: We recruited people with type 2 diabetes aged ≥ 40 years with a glycated hemoglobin (A1C) ≥ 7%, living in Hamilton, Canada, who were enrolled in a community-based program (Diabetes Hamilton) that provided regular evidence-based information and listings of community resources designed to facilitate diabetes self-management. After completing a questionnaire, participants were randomly allocated to either receive or not receive periodic computer-generated, evidence-based feedback on the basis of their questionnaire responses and designed to facilitate improved glycemic control and diabetes self-management. The primary outcome was a change in A1C after 1 year. RESULTS: A total of 465 participants (50% women, mean age 62 years, and mean A1C 7.83%) were randomly assigned, and 12-month A1C values were available in 96% of all participants, at which time the A1C level had decreased by an absolute amount of 0.24 and 0.15% in the intervention and control groups, respectively. The difference in A1C reduction for the intervention versus control group was 0.09% (95% CI -0.08 to 0.26; P = 0.3). No between-group differences in measures of quality of life, diabetes self-management behaviors, or clinical outcomes were observed. CONCLUSIONS: Providing computer-generated tailored feedback to registrants of a generic, community-based program that supports diabetes self-management does not lead to lower A1C levels or a better quality of life than participation in the community-based program (augmented by periodic A1C testing) alone.