Health records changed over time in the countries, and also Türkiye passed from paper versions to personal health records (PHR) and put patients at the center of the system by allowing them to become the master of their health data. Presenting the current state of the e-Nabız application nationwide in Turkey, and to evaluate the benefits of patients' online access to electronic health records and the system's interoperability. A descriptive observational study. In the Turkish PHR system (e-Nabız), services to patients to manage their health are categorized and analyzed within the scope of national digital health services. In addition, the data validation in the e-Nabız within itself has been systematically expressed. The Turkish PHR system allows users to use 30 different services for treatment, prevention, health promotion, and health-related and interrelated areas. Moreover, some statistics regarding the categories specified in the e-Nabız system are included. Today, data is flowing from 28,608 system-integrated health facilities and 39 e-Nabız integrated public institutions. In addition, 4.5 billion transactions are done by people by 2023 and 220 million users are queried by physicians to reach patients' labs and results. Plus, the e-Nabız is adopted by 82% of the Türkiye population. There is no universal model for the content of the PHR. Given its importance to the patient, the content evolved and will continue to grow over the years. With the advent of coronavirus disease 2019, the system is equipped with three new services. The importance of these services over time and in the future has been demonstrated with increasing momentum.

Cesarean section (CS) rates continue to rise globally because of various factors. Medically unnecessary cesarean operations have no benefit to the mother or child’s health. Since the World Health Organization (WHO) has determined that the acceptable CS rate should not be more than 10-15%, it also stated the use of a classification system to compare different patient groups and facilities. Turkey has the highest CS rates globally and has been rising over the years. This study aims to assess CS rates between 2018 and 2023 using National Health Data and to analyze them according to the Robson classification system and WHO reference values to discuss possible measures against increasing rates. In this study, we assessed the rates of CSs between 2018 and 2023; the CS rate including all 5-years and analysis of CS rates for each Robson group as advocated by WHO. Also, another assessment was done of the facilities where the CSs were applied (Public, private, or university hospitals). The total number of births recorded between 2018 and2023 was 6.161.976. The overall CS rate was 57.55%. The number of total CS operations was 3.546.049. The primary CS rate was 28.83% (N:1.776.503). Significant differences were observed between the public and private centers for each Robson group. The CS rates of Groups 1-4 are obviously higher than expected. The CSs of these groups cumulatively affect the rates of other groups. Nulliparous women have CSs mostly in private hospitals. There is a need for improvements in the health system in this regard for better maternal and child health.

Objective: The artificial intelligence competition in healthcare was organized for the first time at the annual aviation, space, and technology festival (TEKNOFEST), Istanbul/Türkiye, in September 2021. In this article, the data set preparation and competition processes were explained in detail; the anonymized and annotated data set is also provided via official website for further research. Materials and Methods: Data set recorded over the period covering 2019 and 2020 were centrally screened from the e-Pulse and Teleradiology System of the Republic of Türkiye, Ministry of Health using various codes and filtering criteria. The data set was anonymized. The data set was prepared, pooled, curated, and annotated by 7 radiologists. The training data set was shared with the teams via a dedicated file transfer protocol server, which could be accessed using private usernames and passwords given to the teams under a nondisclosure agreement signed by the representative of each team. Results: The competition consisted of 2 stages. In the first stage, teams were given 192 digital imaging and communications in medicine images that belong to 1 of 3 possible categories namely, hemorrhage, ischemic, or non-stroke. Teams were asked to classify each image as either stroke present or absent. In the second stage of the competition, qualifying 36 teams were given 97 digital imaging and communications in medicine images that contained hemorrhage, ischemia, or both lesions. Among the employed methods, Unet and DeepLabv3 were the most frequently observed ones. Conclusion: Artificial intelligence competitions in healthcare offer good opportunities to collect data reflecting various cases and problems. Especially, annotated data set by domain experts is more valuable. Cite this article as: Koç U, Akçapınar Sezer E, Alper Özkaya Y, et al. Artificial intelligence in healthcare competition (TEKNOFEST-2021): Stroke data set. Eurasian J Med., 2022;54(3):248-258.

Background: A novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) occurred in China in December 2019 and has spread globally. In this study, we aimed to describe the clinical characteristics and outcomes of hospitalized older adults with coronavirus disease 2019 (COVID-19) in Turkey. Methods: We retrospectively analyzed the clinical data of hospitalized patients aged ≥ 60 years with confirmed COVID-19 from March 11, 2020 to May 27, 2020 using nationwide health database. Results: In this nationwide cohort, a total of 16,942 hospitalized older adults with COVID-19 were enrolled, of whom 8,635 (51%) were women. Mean age was 71.2 ± 8.5 years, ranging from 60 to 113 years. Mortality rate before and after curfew was statistically different (32.2% vs. 17.9%; p < .001, respectively). Through multivariate analysis of the causes of death in older patients, we found that male gender, diabetes mellitus, heart failure, dementia, were all significantly associated with mortality in entire cohort. In addition to abovementioned risk factors, in patients aged between 60 and 79 years, hypertension, chronic kidney disease and cancer and in patients 80 years of age and older malnutrition were also associated with increased risk of mortality. Conclusions: In addition to the results of previous studies with smaller sample size, our results confirmed the age-related relationship between specific comorbidities and COVID-19–related mortality.

The aim of our study, in light of the World Health Organization Multi-Country Survey (WHO-MCS) data examining the data of the Ministry of Health for the year 2022, comparing the cesarean sections (C/S) performed in the Republic of Turkey (TR) with the WHO-MCS data, and comparing the number of cesarean sections applied more than the reference values. According to the database of the Turkish Ministry of Health, in 2022, 1166175 deliveries took place in the Republic of Turkey, and 706370 (60.5%) cesarean section deliveries were recorded as 365764 (51%) primary C/S. Using the Ministry of Health registration system based on the Robson classification. The number and rate of C/S operations performed per birth in 2022 in TR (n=706370; 60.50%) were found to be significantly higher when compared to the number and rate of C/S on a global scale (n=246062; 21.10%), (p<0.001). When cesarean section operations performed in the Ministry of Health hospitals, private institutions, foundation universities, public universities and other public unit hospitals were compared with WHO MCS reference values and C/S ratios, 44.2% versus 24.7% (p=0.05), versus 77.4%, versus 34.2% (p<0.001), 74.3% versus 29.5% (p<0.001), 75% versus 35.8% (p<0.001), 69.3% versus 35.9% (p<0.001). The amount of cesarean sections performed according to the total number of births in the Turkish Republic is relatively high and its cost nearly 1 billion 750 million TL.