The Rwandan Ministry of Health supports a countrywide installation of the Open Medical Record System (OpenMRS) to improve clinical recordkeeping and patient care. However, electronic medical records also can be a valuable source of data for observational and experimental studies. We describe the challenges and lessons learned when reusing OpenMRS data in Rwanda for global HIV epidemiology research.
Background Substance use is common among people living with HIV and has been associated with suboptimal HIV treatment outcomes. Integrating substance use services into HIV care is a promising strategy to improve patient outcomes. Methods We report on substance use education, screening, and referral practices from two surveys of HIV care and treatment sites participating in the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium. HIV care and treatment sites participating in IeDEA are primarily public-sector health facilities and include both academic and community-based hospitals and health facilities. A total of 286 sites in 45 countries participated in the 2014–2015 survey and 237 sites in 44 countries participated in the 2017 survey. We compared changes over time for 147 sites that participated in both surveys. Results In 2014–2015, most sites (75%) reported providing substance use-related education on-site (i.e., at the HIV clinic or the same health facility). Approximately half reported on-site screening for substance use (52%) or referrals for substance use treatment (51%). In 2017, the proportion of sites providing on-site substance use-related education, screening, or referrals increased by 9%, 16%, and 8%, respectively. In 2017, on-site substance use screening and referral were most commonly reported at sites serving only adults (compared to only children/adolescents or adults and children/adolescents; screening: 86%, 37%, and 59%, respectively; referral: 76%, 47%, and 46%, respectively) and at sites in high-income countries (compared to upper middle income, lower middle income or low-income countries; screening: 89%, 76%, 68%, and 45%, respectively; referral: 82%, 71%, 57%, and 34%, respectively). Conclusion Although there have been increases in the proportion of sites reporting substance use education, screening, and referral services across IeDEA sites, gaps persist in the integration of substance use services into HIV care, particularly in relation to screening and referral practices, with reduced availability for children/adolescents and those receiving care within resource-constrained settings.
Observational studies are critical tools in clinical research and public health response, but challenges arise in ensuring the data produced by these studies are scientifically robust and socially valuable. Resolving these challenges requires careful attention to prioritising the most valuable research questions, ensuring robust study design, strong data management practices, expansive community engagement, and access and benefit sharing of results and research materials. This paper opens with a discussion of how well-designed observational studies contribute to biomedical evidence and provides examples from across the clinical literature of how these methods generate hypotheses for future research and uncover otherwise unattainable insights by providing examples from across the clinical literature. Then, we present obstacles that remain in ensuring observational studies are optimally designed, conducted and communicated.
Electronic health record (EHR) data are increasingly used for biomedical research, but these data have recognized data quality challenges. Data validation is necessary to use EHR data with confidence, but limited resources typically make complete data validation impossible. Using EHR data, we illustrate prospective, multiwave, two-phase validation sampling to estimate the association between maternal weight gain during pregnancy and the risks of her child developing obesity or asthma. The optimal validation sampling design depends on the unknown efficient influence functions of regression coefficients of interest. In the first wave of our multiwave validation design, we estimate the influence function using the unvalidated (phase 1) data to determine our validation sample; then in subsequent waves, we re-estimate the influence function using validated (phase 2) data and update our sampling. For efficiency, estimation combines obesity and asthma sampling frames while calibrating sampling weights using generalized raking. We validated 996 of 10,335 mother-child EHR dyads in six sampling waves. Estimated associations between childhood obesity/asthma and maternal weight gain, as well as other covariates, are compared to naïve estimates that only use unvalidated data. In some cases, estimates markedly differ, underscoring the importance of efficient validation sampling to obtain accurate estimates incorporating validated data.
Tuberculosis (TB) is the leading cause of death among PLHIV and multidrug-resistant-TB (MDR-TB) is associated with high mortality. We examined the management for adult PLHIV coinfected with MDR-TB at ART clinics in lower income countries. Between 2019 and 2020, we conducted a cross-sectional survey at 29 ART clinics in high TB burden countries within the global IeDEA network. We used structured questionnaires to collect clinic-level data on the TB and HIV services and the availability of diagnostic tools and treatment for MDR-TB. Of 29 ART clinics, 25 (86%) were in urban areas and 19 (66%) were tertiary care clinics. Integrated HIV-TB services were reported at 25 (86%) ART clinics for pan-susceptible TB, and 14 (48%) clinics reported full MDR-TB services on-site, i.e. drug susceptibility testing [DST] and MDR-TB treatment. Some form of DST was available on-site at 22 (76%) clinics, while the remainder referred testing off-site. On-site DST for second-line drugs was available at 9 (31%) clinics. MDR-TB treatment was delivered on-site at 15 (52%) clinics, with 10 individualizing treatment based on DST results and five using standardized regimens alone. Bedaquiline was routinely available at 5 (17%) clinics and delamanid at 3 (10%) clinics. Although most ART clinics reported having integrated HIV and TB services, few had fully integrated MDR-TB services. There is a continued need for increased access to diagnostic and treatment options for MDR-TB patients and better integration of MDR-TB services into the HIV care continuum.
Clinical data auditing often requires validating the contents of clinical research databases against source documents available in health care settings. Currently available data audit software, however, does not provide features necessary to compare the contents of such databases to source data in paper medical records. This work enumerates the primary weaknesses of using paper forms for clinical data audits and identifies the shortcomings of existing data audit software, as informed by the experiences of an audit team evaluating data quality for an international research consortium. The authors propose a set of attributes to guide the development of a computer-assisted clinical data audit tool to simplify and standardize the audit process.
Abstract Introduction “Treat All” – the treatment of all people with HIV , irrespective of disease stage or CD 4 cell count – represents a paradigm shift in HIV care that has the potential to end AIDS as a public health threat. With accelerating implementation of Treat All in sub‐Saharan Africa ( SSA ), there is a need for a focused agenda and research to identify and inform strategies for promoting timely uptake of HIV treatment, retention in care, and sustained viral suppression and addressing bottlenecks impeding implementation. Methods The Delphi approach was used to develop consensus around research priorities for Treat All implementation in SSA . Through an iterative process (June 2017 to March 2018), a set of research priorities was collectively formulated and refined by a technical working group and shared for review, deliberation and prioritization by more than 200 researchers, implementation experts, policy/decision‐makers, and HIV community representatives in East, Central, Southern and West Africa. Results and discussion The process resulted in a list of nine research priorities for generating evidence to guide Treat All policies, implementation strategies and monitoring efforts. These priorities highlight the need for increased focus on adolescents, men, and those with mental health and substance use disorders – groups that remain underserved in SSA and for whom more effective testing, linkage and care strategies need to be identified. The priorities also reflect consensus on the need to: (1) generate accurate national and sub‐national estimates of the size of key populations and describe those who remain underserved along the HIV ‐care continuum; (2) characterize the timeliness of HIV care and short‐ and long‐term HIV care continuum outcomes, as well as factors influencing timely achievement of these outcomes; (3) estimate the incidence and prevalence of HIV ‐drug resistance and regimen switching; and (4) identify cost‐effective and affordable service delivery models and strategies to optimize uptake and minimize gaps, disparities, and losses along the HIV ‐care continuum, particularly among underserved populations. Conclusions Reflecting consensus among a broad group of experts, researchers, policy‐ and decision‐makers, PLWH , and other stakeholders, the resulting research priorities highlight important evidence gaps that are relevant for ministries of health, funders, normative bodies and research networks.
Drug-drug interaction systems exhibit low signal-to-noise ratios because of the amount of clinically insignificant or inaccurate information they contain. MEDLINE represents a respected source of peer-reviewed biomedical citations that potentially might serve as a valuable source of drug-drug interaction information, if relevant articles could be pinpointed effectively and efficiently. We evaluated the classification capability of Support Vector Machines as a method for locating articles about drug interactions. We used a corpus of "positive" and"negative" drug interaction citations to generate datasets composed of MeSH terms, CUI-tagged title and abstract text, and stemmed text words. The study showed that automated classification techniques have the potential to perform at least as well as PubMed in identifying drug-drug interaction articles.
Drug resistance threatens tuberculosis (TB) control, particularly among human immunodeficiency virus (HIV) infected persons.To describe practices in the prevention and management of drug-resistant TB under antiretroviral therapy (ART) programs in lower-income countries.We used online questionnaires to collect program-level data on 47 ART programs in Southern Africa (n = 14), East Africa (n = 8), West Africa (n = 7), Central Africa (n = 5), Latin America (n = 7) and the Asia-Pacific (n = 6 programs) in 2012. Patient-level data were collected on 1002 adult TB patients seen at 40 of the participating ART programs.Phenotypic drug susceptibility testing (DST) was available in 36 (77%) ART programs, but was only used for 22% of all TB patients. Molecular DST was available in 33 (70%) programs and was used in 23% of all TB patients. Twenty ART programs (43%) provided directly observed therapy (DOT) during the entire course of treatment, 16 (34%) during the intensive phase only, and 11 (23%) did not follow DOT. Fourteen (30%) ART programs reported no access to second-line anti-tuberculosis regimens; 18 (38%) reported TB drug shortages.Capacity to diagnose and treat drug-resistant TB was limited across ART programs in lower-income countries. DOT was not always implemented and drug supplies were regularly interrupted, which may contribute to the global emergence of drug resistance.
This paper provides a description of the MyCap data collection platform, utilization metrics, and vignettes associated with use from diverse research institutions. MyCap is a participant-facing mobile application for survey data collection and the automated administration of active tasks (activities performed by participants using mobile device sensors under semi-controlled conditions). Launched in 2018, MyCap is a no-code solution for research teams conducting longitudinal studies, integrates tightly with REDCap and is available at no cost to research teams at academic, nonprofit, or government organizations. MyCap has been deployed at multiple research institutions with application usage logged across 135 countries in 2021. Vignettes demonstrate that MyCap empowered research teams to explore and implement novel methods of information collection and use. MyCap's integration with REDCap provides a comprehensive data collection ecosystem and is best suited for longitudinal studies with frequent requests for information from participants.
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