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Background Health care data allow for the study and surveillance of chronic diseases such as diabetes. The objective of this study was to identify and validate optimal algorithms for diabetes cases within health care administrative databases for different research purposes, populations, and data sources. Methods We linked health care administrative databases from Ontario, Canada to a reference standard of primary care electronic medical records (EMRs). We then identified and calculated the performance characteristics of multiple adult diabetes case definitions, using combinations of data sources and time windows. Results The best algorithm to identify diabetes cases was the presence at any time of one hospitalization or physician claim for diabetes AND either one prescription for an anti-diabetic medication or one physician claim with a diabetes-specific fee code [sensitivity 84.2%, specificity 99.2%, positive predictive value (PPV) 92.5%]. Use of physician claims alone performed almost as well: three physician claims for diabetes within one year was highly specific (sensitivity 79.9%, specificity 99.1%, PPV 91.4%) and one physician claim at any time was highly sensitive (sensitivity 93.6%, specificity 91.9%, PPV 58.5%). Conclusions This study identifies validated algorithms to capture diabetes cases within health care administrative databases for a range of purposes, populations and data availability. These findings are useful to study trends and outcomes of diabetes using routinely-collected health care data. Electronic supplementary material The online version of this article (10.1186/s12913-018-3148-0) contains supplementary material, which is available to authorized users.

Multidrug-resistant tuberculosis (MDR-TB) is an emerging problem in many parts of the world, and levels of MDR-TB among new TB patients are increasing in sub-Saharan Africa. We reviewed the prevalence and molecular epidemiology of MDR-TB in East Africa, including Burundi, Kenya, Rwanda, Tanzania, and Uganda. In 16 epidemiologic surveys, the prevalence of MDR among new cases ranges from 0.4% in Tanzania to 4.4% in Uganda, and among recurrent cases ranges from 3.9% in Tanzania to 17.7% in Uganda. There is a gap of 5,948 cases between the estimated number of MDR-TB cases in East Africa and the number actually diagnosed. The only confirmed risk factors for MDR-TB are prior treatment for TB and refugee status. HIV has not been reported as a risk factor, and there are no reports of statistical association between spoligotype and drug resistance pattern. Increased capacity for diagnosis and treatment of MDR-TB is needed, with an emphasis on recurrent TB cases and refugees.

BACKGROUND Treatment protocols and prices of antiretroviral therapy (ART) have changed over time. Yet, limited data exist to evaluate the impact of these changes on patient outcomes and treatment costs in resource-poor settings. METHODS We compared patient-level data on outcomes, utilization, and cost for the first 2 years of ART for a cohort of adult patients initiating ART in 2003-2004 and a cohort initiating ART in 2006-2008 at the Haitian Group for the Study of Kaposi's Sarcoma and Opportunistic Infections clinic (GHESKIO) in Port-au-Prince, Haiti. Costs were measured from the health center perspective. Multivariate analyses were conducted to account for the potential impact of differences in disease severity at baseline. RESULTS With the exclusion of patients who transferred care, 92% (167/181) of patients in the 2006-2008 cohort and 75% (150/200) in the 2003-2004 cohort were alive and in care at the end of the study period. The mean cost per patient for the 2-year study period was US$723 for the 2006-2008 cohort vs. US$1191 for the 2003-2004 cohort, a cost difference of US$468 (P < 0.0001). The mean cost per patient alive and in care at the end of the 2-year study period was US$744 for the 2006-2008 cohort vs. US$1489 for the 2003-2004 cohort (P < 0.0001). CONCLUSIONS HIV treatment outcomes in Haiti have improved over time while treatment costs declined by over 50% per patient alive and in care at the end of the 2-year study period. The major drivers in the reduction of treatment costs were the lower price of ART, lower costs for laboratory testing, and lower overhead costs.

Background Despite the increased availability of anti-retroviral therapy, in-hospital HIV mortality remains high in sub-Saharan Africa. Reports from Senegal, Malawi, and Tanzania show rates of in-hospital, HIV-related mortality ranging from 24.2% to 44%. This mixed methods review explored the potential causes of preventable in-hospital mortality associated with HIV infections in sub-Saharan Africa in the anti-retroviral era. Results Based on our experience as healthcare providers in Africa and a review of the literature we identified 5 health systems failures which may cause preventable in-hospital mortality, including: 1) late presentation of HIV cases, 2) low rates of in-hospital HIV testing, 3) poor laboratory capacity which limits CD4 T-cell testing and the diagnosis of opportunistic infections, 4) delay in initiation of anti-retroviral therapy in-hospital, and 5) problems associated with loss to follow-up upon discharge from hospital. Conclusion Our findings, together with the current available literature, should be used to develop practical interventions that can be implemented to reduce in-hospital mortality.