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In 2017, The Ottawa Hospital initiated a unique‐in‐Canada quality improvement initiative by opening a novel, multi‐specialist limb‐preservation clinic. We sought to describe the structure, processes, and initial outcomes of the clinic and evaluate whether it is achieving its mandate of providing high‐quality wound clinical care, education, and research. We conducted a descriptive prospective cohort study alongside a nested study of 162 clinic patients requiring serial assessments. There have been 1623 visits, mostly (72.2%) from outpatients. During 17.8% of visits, patients were evaluated by >1 specialist. Therapies provided most often included negative‐pressure wound therapy (32.7%), biological wound dressings (21.6%), and total contact casting (18.5%). Furthermore, 1.2% underwent toe/ray amputations or skin grafting in clinic and 22.8% were initiated on antimicrobials. Mixed‐effects models suggested that mean wound volumes for those requiring serial assessments decreased by 1.6 (95% confidence interval = −0.86 to −2.27) cm3 between visits. The clinic provided seven rotations to vascular surgery, infectious diseases, dermatology, and palliative care physicians; three nursing preceptorships; and two educational workshops. It also initiated provincial and national vascular health and wound care research initiatives. This study may be used to guide development of other limb‐preservation clinics and programmes. Findings support that our programme is achieving its mandate. [ABSTRACT FROM AUTHOR]

Background We have designed a prospective adverse event (AE) surveillance method. We performed this study to evaluate this method's performance in several hospitals simultaneously. Objectives To compare AE rates obtained by prospective AE surveillance in different hospitals and to evaluate measurement factors explaining observed variation. Methods We conducted a multicentre prospective observational study. Prospective AE surveillance was implemented for 8 weeks on the general medicine wards of five hospitals. To determine if population factors may have influenced results, we performed mixed-effects logistic regression. To determine if surveillance factors may have influenced results, we reassigned observers to different hospitals midway through surveillance period and reallocated a random sample of events to different expert review teams. Results During 3560 patient days of observation of 1159 patient encounters, we identified 356 AEs (AE risk per encounter=22%). AE risk varied between hospitals ranging from 9.9% of encounters in Hospital D to 35.8% of encounters in Hospital A. AE types and severity were similar between hospitals--the most common types were related to clinical procedures (45%), hospital-acquired infections (21%) and medications (19%). Adjusting for age and comorbid status, we observed an association between hospital and AE risk. We observed variation in observer behaviour and moderate agreement between clinical reviewers, which could have influenced the observed rate difference. Conclusion This study demonstrated that it is possible to implement prospective surveillance in different settings. Such surveillance appears to be better suited to evaluating hospital safety concerns within rather than between hospitals as we could not definitively rule out whether the observed variation in AE risk was due to population or surveillance factors. [ABSTRACT FROM AUTHOR]

Background: Health systems are recommended to capture routine patient sociodemographic data as a key step in providing equitable person‐centred care. However, collection of this information has the potential to cause harm, especially for vulnerable or potentially disadvantaged patients. Objective: To identify harms perceived or experienced by patients, their families, or health‐care providers from collection of sociodemographic information during routine health‐care visits and to identify best practices for when, by whom and how to collect this information. Search Strategy: We searched OVID MEDLINE, PubMed "related articles" via NLM and healthevidence.org to the end of January 2018 and assessed reference lists and related citations of included studies. Inclusion Criteria: We included studies reporting on harms of collecting patient sociodemographic information in health‐care settings. Data Extraction and Synthesis: Data on study characteristics and types of harms were extracted and summarized narratively. Main Results: Eighteen studies were included; 13 provided patient perceptions or experiences with the collection of these data and seven studies reported on provider perceptions. Five reported on patient recommendations for collecting sociodemographic information. Patients and providers reported similar potential harms which were grouped into the following themes: altered behaviour which may affect care‐seeking, data misuse or privacy concerns, discomfort, discrimination, offence or negative reactions, and quality of care. Patients suggested that sociodemographic information be collected face to face by a physician. Discussion and Conclusions: Overall, patients support the collection of sociodemographic information. However, harms are possible, especially for some population subgroups. Harms may be mitigated by providing a rationale for the collection of this information. [ABSTRACT FROM AUTHOR]

Background: Urgent, unplanned hospital readmissions are increasingly being used to gauge the quality of care. We reviewed urgent readmissions to determine which were potentially avoidable and compared rates of all-cause and avoidable readmissions., Methods: In a multicentre, prospective cohort study, we reviewed all urgent readmissions that occurred within six months among patients discharged to the community from 11 teaching and community hospitals between October 2002 and July 2006. Summaries of the readmissions were reviewed by at least four practising physicians using standardized methods to judge whether the readmission was an adverse event (poor clinical outcome due to medical care) and whether the adverse event could have been avoided. We used a latent class model to determine whether the probability that each readmission was truly avoidable exceeded 50%., Results: Of the 4812 patients included in the study, 649 (13.5%, 95% confidence interval [CI] 12.5%-14.5%) had an urgent readmission within six months after discharge. We considered 104 of them (16.0% of those readmitted, 95% CI 13.3%-19.1%; 2.2% of those discharged, 95% CI 1.8%-2.6%) to have had a potentially avoidable readmission. The proportion of patients who had an urgent readmission varied significantly by hospital (range 7.5%-22.5%; χ(2) = 92.9, p < 0.001); the proportion of readmissions deemed avoidable did not show significant variation by hospital (range 1.2%-3.7%; χ(2) = 12.5, p < 0.25). We found no association between the proportion of patients who had an urgent readmission and the proportion of patients who had an avoidable readmission (Pearson correlation 0.294; p = 0.38). In addition, we found no association between hospital rankings by proportion of patients readmitted and rankings by proportion of patients with an avoidable readmission (Spearman correlation coefficient 0.28, p = 0.41)., Interpretation: Urgent readmissions deemed potentially avoidable were relatively uncommon, comprising less than 20% of all urgent readmissions following hospital discharge. Hospital-specific proportions of patients who were readmitted were not related to proportions with a potentially avoidable readmission.

Background: An abdominal aortic aneurysm (AAA) that is identified when the abdomen is imaged for some other reason is known as an incidental AAA. No population-based studies have assessed the management of incidental AAAs. The objective of this study was to measure the completeness of radiographic monitoring of incidental AAAs by means of a population-based analysis., Methods: We linked a cohort of patients with incidental AAA (defined as a previously unidentified aortic enlargement exceeding 30 mm in diameter found in an imaging study performed for another reason) to various population-based databases. We followed the patients to elective repair or rupture of the aneurysm, death or 31 Mar. 2009. We used evidence-based monitoring guidelines to calculate the proportion of observation time during which each incidental AAA was incompletely monitored. We used negative binomial regression to determine the association of patient-related factors with this outcome., Results: For the period between January 1996 and September 2008, we identified 191 patients with incidental AAA (mean diameter 37.6 mm, 95% confidence interval [CI] 36.6-38.6 mm; median follow-up 4.4 [range 0.6-12.7] years). Fifty-six of these patients (29.3%) had no radiographic monitoring of the aneurysm. Overall, patients spent one-fifth of their time with incomplete monitoring of the AAA (median 19.4%, interquartile range 0.3%-44.0%). Factors independently associated with incomplete monitoring included older age (relative rate [change in proportion of time with incomplete monitoring] [RR] 1.27, 95% CI 1.10-1.47, per decade), larger size (RR 1.65, 95% CI 1.38-2.01, per 10-mm increase) and detection of the aneurysm while the patient was in hospital or the emergency department (RR 1.34, 95% CI 1.00-1.79). Comorbidities were not associated with monitoring., Interpretation: Radiographic monitoring of incidental AAAs was incomplete, and almost one-third of patients underwent no monitoring at all. Incomplete monitoring did not appear to be related to patients' comorbidity.

Objective: To comprehensively describe the populations, interventions, and outcomes of interactive voice response system (IVRS) clinical trials., Methods: We identified studies using MEDLINE (1950-2008) and EMBASE (1980-2008). We also identified studies using hand searches of the Science Citation Index and the reference lists of included articles. Included were randomized and controlled clinical trials that examined the effect of an IVRS intervention on clinical end points, measures of disease control, process adherence, or quality-of-life measures. Continuous and dichotomous outcomes were meta-analyzed using mean difference and median effects methodology, respectively., Results: Forty studies (n = 106,959 patients) met inclusion criteria. Of these studies, 25 used an IVRS intervention aimed at encouraging adherence with recommended tests, treatments, or behaviors; the remaining 15 used an IVRS for chronic disease management. Three studies reported clinical end points, which could not be statistically pooled. In 6 studies that reported objective clinical measures of disease control (glycosylated hemoglobin, total cholesterol, and serum glucose), the IVRS was associated with nonsignificant improvements. In 14 studies that measured objective process adherence outcomes, the median effect was 7.9% (25th-75th percentile: 2.8%, 19.5%). For the 16 studies that assessed patient-reported measures of disease control and the 11 studies that assessed patient-reported process adherence outcomes, approximately one-third of the outcomes significantly favored the IVRS group., Conclusion: IVRS interventions, which enable patients to interact with computer databases via telephone, have shown a significant benefit in adherence to various processes of care. Future IVRS studies should include clinically relevant outcomes.