BackgroundIn health, organizational participatory research (OPR) refers to health organization members participating in research decisions, with university researchers, throughout a study. This non-academic partner contribution to the research may take the form of consultation or co-construction. A drawback of OPR is that it requires more time from all those involved, compared to non-participatory research approaches; thus, understanding the added value of OPR, if any, is important. Thus, we sought to assess whether the OPR approach leads to benefits beyond what could be achieved through traditional research.MethodsWe identified, selected, and appraised OPR health literature, and at each stage, two team members independently reviewed and coded the literature. We used quantitative content analysis to transform textual data into reliable numerical codes and conducted a logistic regression to test the hypothesis that a co-construction type OPR study yields extra benefits with a greater likelihood than consultation-type OPR studies.ResultsFrom 8873 abstracts and 992 full text papers, we distilled a sample of 107 OPR studies. We found no difference between the type of organization members’ participation and the likelihood of exhibiting an extra benefit. However, the likelihood of an OPR study exhibiting at least one extra benefit is quadrupled when the impetus for the study comes from the organization, rather than the university researcher(s), or the organization and the university researcher(s) together (OR = 4.11, CI = 1.12–14.01). We also defined five types of extra benefits.ConclusionsThis review describes the types of extra benefits OPR can yield and suggests these benefits may occur if the organization initiates the OPR. Further, this review exposes a need for OPR authors to more clearly describe the type of non-academic partner participation in key research decisions throughout the study. Detailed descriptions will benefit others conducting OPR and allow for a re-examination of the relationship between participation and extra benefits in future reviews.Electronic supplementary materialThe online version of this article (10.1186/s13012-017-0648-y) contains supplementary material, which is available to authorized users.

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Clinical trials suggest less hepatotoxicity and better adherence with 4 months rifampin (4R) versus 9 months isoniazid (9H) for treating latent tuberculosis infection (LTBI). Our objectives were to compare frequencies of severe hepatic adverse events and treatment completion, and direct health system costs of LTBI regimens 4R and 9H, in the general population of the province of Quebec, Canada, using provincial health administrative data.Our retrospective cohort included all patients starting rifampin or isoniazid regimens between 2003 and 2007. We estimated hepatotoxicity from hospitalisation records, treatment completion from community pharmacy records and direct costs from billing records and fee schedules. We compared rifampin to isoniazid using logistic (hepatotoxicity), log-binomial (completion), and gamma (costs) regression, with adjustment for age, co-morbidities and other confounders.10 559 individuals started LTBI treatment (9684 isoniazid; 875 rifampin). Rifampin patients were older with more baseline co-morbidities. Severe hepatotoxicity risk was higher with isoniazid (n=15) than rifampin (n=1), adjusted OR=2.3 (95% CI: 0.3–16.1); there were two liver transplants and one death with isoniazid and none with rifampin. Overall, patients without co-morbidities had lower hepatotoxicity risk (0.1% versus 1.0%). 4R completion (53.5%) was higher than 9H (36.9%), adjusted RR=1.5 (95% CI: 1.3–1.7). Mean costs per patient were lower for rifampin than isoniazid: adjusted cost ratio=0.7 (95% CI: 0.5–0.9).Risk of severe hepatotoxicity and direct costs were lower, and completion was higher, for 4R than 9H, after adjustment for age and co-morbidities. Severe hepatotoxicity resulted in death or liver transplant in three patients receiving 9H, compared with no patients receiving 4R.

With their longitudinal patient relationships, primary care physicians and their care teams are uniquely situated to promote preventive medicine, including cancer screening. A confluence of forces is driving the demand for the personalization of cancer screening recommendations. Recommendations are increasingly based on individual patient preferences, medical history, genetic and environmental risk factors, and level of interaction with the healthcare system. Current examples include choices between colonoscopy, fecal testing, and emerging tests for colorectal cancer (CRC) screening; the use of genetic information and availability of home self-testing in cervical cancer screening; the integration of multiple risk factors and patient preferences to decide the intensity and length of breast cancer screening; and the issues of smoking cessation and competing priorities when deciding whether or not to pursue lung cancer screening. These changes will inevitably increase the burden on primary care of providing high-quality cancer screening to their patients. To address, primary care physicians need access to continuously updated evidence reviews including prioritization of strongly supported recommendations, training in shared decision-making and tools for preference diagnosis, and an electronic health record (EHR) and reimbursement model that allow for population health management and team-based care. Only by reinforcing cancer screening in primary care can we ensure that personalized cancer screening is accessible and evidence-based.

BackgroundHospitalization is the most costly health system component of tuberculosis (TB) control programs. Our objectives were to identify how frequently patients are hospitalized, and the factors associated with hospitalizations and length-of-stay (LOS) of TB patients in a large Canadian city.MethodsWe extracted data from the Montreal TB Resource database, a retrospective cohort of all active TB cases reported to the Montreal Public Health Department between January 1996 and May 2007. Data included patient demographics, clinical characteristics, and dates of treatment and hospitalization. Predictors of hospitalization and LOS were estimated using logistic regression and Cox proportional hazards regression, respectively.ResultsThere were 1852 active TB patients. Of these, 51% were hospitalized initially during the period of diagnosis and/or treatment initiation (median LOS 17.5 days), and 9.0% hospitalized later during treatment (median LOS 13 days). In adjusted models, patients were more likely to be hospitalized initially if they were children, had co-morbidities, smear-positive symptomatic pulmonary TB, cavitary or miliary TB, and multi- or poly-TB drug resistance. Factors predictive of longer initial LOS included having HIV, renal disease, symptomatic pulmonary smear-positive TB, multi- or poly-TB drug resistance, and being in a teaching hospital.ConclusionsWe found a high hospitalization rate during diagnosis and treatment of patients with TB. Diagnostic delay due to low index of suspicion may result in patients presenting with more severe disease at the time of diagnosis. Earlier identification and treatment, through interventions to increase TB awareness and more targeted prevention programs, might reduce costly TB-related hospital use.