For over a decade the term “Big data” has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, “Big data” no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as “data analytics” and “data science” have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises “Big Advances,” significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set “Big data” analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.

ObjectivesThe objectives of our study were (1) to investigate the association between gender of the general practitioner (GP) and the quality of primary care in Hungary with respect to process indicators for GP performance and (2) to assess the size of the gender impact.Study designA nation-wide cross-sectional study was performed in 2016.Setting and participantsThe study covered all general medical practices in Hungary (n=4575) responsible for the provision of primary healthcare (PHC) for adults. All GPs in their private practices are solo practitioners.Main outcome measuresMultilevel logistic regression models were used to analyse the association between GP gender and process indicators of PHC, and attributable proportion (AP) was calculated.Results48% of the GPs (n=2213) were women in the study. The crude rates of care provided by female GPs were significantly higher for seven out of eight evaluated indicators than those provided by male GPs. Adjusted for practice, physician and patient factors, GP gender was associated with the haemoglobin A1c (HbA1c) measurement: OR=1.18, 95% CI (1.14 to 1.23); serum creatinine measurement: OR=1.14, 95% CI (1.12 to 1.17); lipid measurement: OR=1.14, 95% CI (1.11 to 1.16); eye examination: OR=1.06, 95% CI (1.03 to 1.08); mammography screening: OR=1.05, 95% CI (1.03 to 1.08); management of patients with chronic obstructive pulmonary disease: OR=1.05, 95% CI (1.01 to 1.09) and the composite indicator: OR=1.08, 95% CI (1.07 to 1.1), which summarises the number of care events and size of target populations of each indicator. The AP at the specific indicators varied from 0.97% (95% CI 0.49% to 1.44%) of influenza immunisation to 8.04% (95% CI 7.4% to 8.67%) of eye examinations.ConclusionFemale GP gender was an independent predictor of receiving higher quality of care. The actual size of the gender effect on the quality of services seemed to be notable. Factors behind the gender effect should receive more attention in quality improvement particularly in countries where the primary care is organised around solo practices.

Following a successful Human Papilloma Virus (HPV) vaccination pilot in 2013–2015 in Kitui county, Kenya introduced the HPV vaccine in October 2019 with a goal to immunize approximately 800,000 girls annually against HPV. Our study assessed the knowledge, attitudes, and practice of affected groups towards HPV infection and vaccination in two counties of Kenya. Semi-structured interviews from children aged between nine and thirteen years and key informants comprising of parents, head teachers, community leaders and health workers involved in HPV vaccination in health facilities from Mombasa and Tana-River counties were conducted. Content was analyzed thematically and coded for emerging themes using the QRS Nvivo 12 Plus software package. From our findings, a significant proportion of participants, especially children, have limited knowledge of the subject. Vaccination of boys was opposed by most participants. Parents and the community members are not in favor of HPV vaccination, as compared to the other groups. A similar pattern of inadequate knowledge and strongly opposed attitudes was observed in Tana-River and Mombasa. Active community involvement in primary prevention strategies may promote the uptake of the vaccine which can be achieved by robust awareness, modifying the negative beliefs about HPV vaccine and encouraging the perceptibility of HPV vaccination.

The performance of general practitioners (GPs) is frequently assessed without considering the factors causing variability among general medical practices (GMPs). Our cross-sectional national-based study was performed in Hungary to evaluate the influence of GMP characteristics on performance indicators. The relationship between patient’s characteristics (age, gender, education) and GMP-specific parameters (practice size, vacancy of GP’s position, settlement type, and county of GMP) and the quality of care was assessed by multilevel logistic regression models. The variations attributable to physicians were small (from 0.77% to 17.95%). The education of patients was associated with 10 performance indicators. Practicing in an urban settlement mostly increased the quality of care for hypertension and diabetes care related performance indicators, while the county was identified as one of the major determinants of variability among GPs’ performance. Only a few indicators were affected by the vacancy and practice size. Thus, the observed variability in performance between GPs partially arose from demographic characteristics and education of patients, settlement type, and regional location of GMPs. Considering the real effect of these factors in evaluation would reflect better the personal performance of GPs.

This work was designed to investigate antithrombotic drug utilization and its link with the socioeconomic characteristics of specific population groups in Hungary by a comparative analysis of data for prescriptions by general practitioners and the redeemed prescriptions for antithrombotic drugs. Risk analysis capabilities were applied to estimate the relationships between socioeconomic status, which was characterized by quintiles of a multidimensional composite indicator (deprivation index), and mortality due to thromboembolic diseases as well as antithrombotic medications for the year 2016 at the district level in Hungary. According to our findings, although deprivation is a significant determinant of mortality due to thromboembolic diseases, clusters can be identified that represent exemptions to this rule: an eastern part of Hungary, consisting of two highly deprived counties, had significantly lower mortality than the country average; by contrast, the least-deprived northwestern part of the country, consisting of five counties, had significantly higher mortality than the country average. The fact that low socioeconomic status in general and poor adherence to antithrombotic drugs irrespective of socioeconomic status were associated with increased mortality indicates the importance of more efficient control of preventive medication and access to healthcare in all districts of the country to reduce mortality due to thromboembolic diseases.