BackgroundRoutine Data Quality Assessments (RDQAs) were developed to measure and improve facility-level electronic medical record (EMR) data quality. We assessed if RDQAs were associated with improvements in data quality in KenyaEMR, an HIV care and treatment EMR used at 341 facilities in Kenya.MethodsRDQAs assess data quality by comparing information recorded in paper records to KenyaEMR. RDQAs are conducted during a one-day site visit, where approximately 100 records are randomly selected and 24 data elements are reviewed to assess data completeness and concordance. Results are immediately provided to facility staff and action plans are developed for data quality improvement. For facilities that had received more than one RDQA (baseline and follow-up), we used generalized estimating equation models to determine if data completeness or concordance improved from the baseline to the follow-up RDQAs.Results27 facilities received two RDQAs and were included in the analysis, with 2369 and 2355 records reviewed from baseline and follow-up RDQAs, respectively. The frequency of missing data in KenyaEMR declined from the baseline (31% missing) to the follow-up (13% missing) RDQAs. After adjusting for facility characteristics, records from follow-up RDQAs had 0.43-times the risk (95% CI: 0.32–0.58) of having at least one missing value among nine required data elements compared to records from baseline RDQAs. Using a scale with one point awarded for each of 20 data elements with concordant values in paper records and KenyaEMR, we found that data concordance improved from baseline (11.9/20) to follow-up (13.6/20) RDQAs, with the mean concordance score increasing by 1.79 (95% CI: 0.25–3.33).ConclusionsThis manuscript demonstrates that RDQAs can be implemented on a large scale and used to identify EMR data quality problems. RDQAs were associated with meaningful improvements in data quality and could be adapted for implementation in other settings.

Background The use of routine immunization data by health care professionals in low- and middle-income countries remains an underutilized resource in decision-making. Despite the significant resources invested in developing national health information systems, systematic reviews of the effectiveness of data use interventions are lacking. Applying a realist review methodology, this study synthesized evidence of effective interventions for improving data use in decision-making. Methods We searched PubMed, POPLINE, Centre for Agriculture and Biosciences International Global Health, and African Journals Online for published literature. Grey literature was obtained from conference, implementer, and technical agency websites and requested from implementing organizations. Articles were included if they reported on an intervention designed to improve routine data use or reported outcomes related to data use, and targeted health care professionals as the principal data users. We developed a theory of change a priori for how we expect data use interventions to influence data use. Evidence was then synthesized according to data use intervention type and level of the health system targeted by the intervention. Results The searches yielded 549 articles, of which 102 met our inclusion criteria, including 49 from peer-reviewed journals and 53 from grey literature. A total of 66 articles reported on immunization data use interventions and 36 articles reported on data use interventions for other health sectors. We categorized 68 articles as research evidence and 34 articles as promising strategies. We identified ten primary intervention categories, including electronic immunization registries, which were the most reported intervention type (n = 14). Among the research evidence from the immunization sector, 32 articles reported intermediate outcomes related to data quality and availability, data analysis, synthesis, interpretation, and review. Seventeen articles reported data-informed decision-making as an intervention outcome, which could be explained by the lack of consensus around how to define and measure data use. Conclusions Few immunization data use interventions have been rigorously studied or evaluated. The review highlights gaps in the evidence base, which future research and better measures for assessing data use should attempt to address.

Female genital mutilation or cutting (FGM/C) is a traditional practice that affects a significant portion of women in sub-Saharan Africa, Egypt, areas of the Middle East and some countries in Asia. While clinical and epidemiological studies have established a close association between inflammation and carcinogenesis, particularly in epithelial cancers, the relationship between FGM/C and cervical cancer is not well known. We performed a secondary analysis using combined data from six research studies conducted in and around Dakar, Senegal from 1994 to 2012. Study subjects included both asymptomatic women who presented to outpatient clinics but were screened for cervical cancer, and women with cancer symptoms who were referred for cervical cancer treatment. We used unconditional logistic regression to estimate adjusted pooled odds ratios (ORs) and 95% confidence intervals (CI) for associations between FGM/C and (1) Invasive cervical cancer (ICC) and (2) noninvasive cervical abnormalities. After adjusting for confounding, women with ICC were 2.50 times more likely to have undergone FGM/C than women without cervical abnormalities (95% CI, 1.28-4.91). Restricting to HPV-positive women increased the strength of the association (OR = 4.23; 95% CI 1.73-10.32). No significant associations between FGM/C and noninvasive cervical abnormalities were observed, except in commercial sex workers with FGM/C (OR = 2.01; 95% CI 1.19-3.40). The potential increased risk for ICC suggested by our study warrants further examination. Study results may impact cancer prevention efforts in populations where FGM/C is practiced and draw awareness to the additional health risks associated with FGM/C.

An assessment of global health collaborations highlights the advantages of synergies between global health research and training programs.