ABSTRACTIntroductionSouth Africa has the largest antiretroviral therapy (ART) programme in the world, with universal access available through the public health system. Yet, gaps in coverage persist. In the Western Cape (WC), an estimated 200,000 people living with HIV are not currently on ART—many of whom are known to the health services. Exploring how people who are not on ART differ from those who are on ART may help guide more effective strategies for re‐engagement and retention in care.MethodsWe conducted a cross‐sectional analysis of routine person‐level data from the WC Provincial Health Data Centre, including adults (≥15 years) known to be living with HIV who accessed public services between October 2022 and September 2024. ART status was inferred from visit and dispensing records. Relative risks (RRs) of current disengagement were estimated using multivariable log‐binomial regression on 25 imputed data sets, adjusting for sex, age, years since diagnosis, diagnosis setting and baseline CD4 count.ResultsOf 494,071 adults included, 131,368 (27%) were currently disengaged from ART. Those at elevated risk included men (aRR 1.20, 95% CI 1.19–1.21), younger people aged 15–24 years (aRR 1.54, 95% CI 1.51–1.57), those with CD4 >500 cells/mm3 at diagnosis (aRR 1.26, 95% CI 1.24–1.28) and individuals diagnosed in hospital (aRR 1.41, 95% CI 1.39–1.43) or during pregnancy (aRR 1.20, 95% CI 1.18–1.22). However, the majority of those disengaged were not from these groups, proportionally representing the underlying population living with HIV. Model discrimination was poor (AUC 0.614), indicating that these characteristics do not reliably identify those disengaged.ConclusionsMost disengaged individuals are from larger, lower‐risk demographic groups and would be missed by interventions targeting higher‐risk demographics. Whole‐population strategies that address common barriers to retention through more inclusive, person‐centred care offer the greatest potential to improve ART coverage.

Background: Burnout among healthcare providers is a critical occupational and system-level challenge globally, with particularly high prevalence reported in Saudi Arabia. Home Health Care (HHC) settings present unique stressors, including isolation, emotional burden, and complex care environments, which exacerbate caregiver burnout and threaten care quality. Objectives: This study aims to (1) synthesize evidence on burnout prevalence and determinants among healthcare providers in Saudi Arabia, (2) contextualize risks within HHC systems, and (3) develop a national burnout reduction strategy aligned with Saudi Ministry of Health (MOH) transformation and Data Center of Excellence (DCoE) models. Methods: A narrative synthesis of peer-reviewed studies, systematic reviews, and national surveys was conducted. Evidence was integrated into a policy-oriented framework incorporating workforce, organizational, and digital health dimensions. Results: Burnout prevalence among healthcare workers in Saudi Arabia reaches up to 77%, with high levels of emotional exhaustion (58%), depersonalization (72%), and low personal accomplishment (66%) [1]. Key drivers include workload, lack of supervisory support, emotional strain, and system pressures. HHC settings amplify these risks through isolation, chronic care exposure, and logistical challenges. Evidence shows burnout negatively impacts patient safety, job satisfaction, and workforce retention [2–4]. Conclusion: Burnout in Saudi HHC is a systemic risk requiring integrated intervention. A national strategy combining workforce optimization, organizational reforms, and real-time analytics through a DCoE is essential for sustainable healthcare transformation under Vision 2030.

BackgroundIncreasing suicidal thoughts and behaviors (STB) among adolescents raise social concerns and have a well-recognized association with sexual abuse (SA). However, research regarding the mechanisms explaining the association between SA and STB remains limited.ObjectiveThis study aims to examine the chained mediating effects of negative life events (NLE) and internet addiction (IA) between SA and STB among adolescents in China.MethodsThis cross-sectional study used data from the Science Database of the People Mental Health survey conducted between March 2013 and December 2022 by the National Population Health Data Center of the National Research Institute for Family Planning. Through stratified sampling, 20,893 adolescents were recruited from 16 Chinese provinces. After excluding samples with missing relevant variables, 10,664 (55.89%; aged 16-17.9 y; n=5826, 54.63% women) adolescents were included in the final analysis. STB was the outcome variable, with NLE and IA as mediators, all assessed via a questionnaire that was uniformly administered by trained investigators in school settings. The Pearson χ2 test was used to analyze the association between SA and STB. Using a combination of multiple linear regression and bootstrap testing, the study constructed a chain mediation model to explore how SA influences STB in adolescents through NLE and IA.ResultsThe scores for SA, NLE, IA, and STB were 1.330 (SD 1.714), 51.960 (SD 23.822), 34.88 (SD 13.852), and 0.690 (SD 1.396), respectively. Multiple linear regression analysis indicated SA was associated with NLE (β=2.382, 95% CI 2.112‐2.653; P<.001), IA (β=1.094, 95% CI 0.939‐1.249; P<.001), and STB (β=0.135, 95% CI 0.119‐0.151; P<.001). Mediation analysis revealed a significant direct association between SA and STB (74.81%; β=0.101, 95% CI 0.085‐0.117; P<.001). Indirect effects constituted 25.19% of the total association (β=0.034, 95% CI 0.029‐0.040; P<.001), comprised of 3 specific pathways: via NLE (11.85%; β=0.016, 95% CI 0.012‐0.020; P<.001), via IA (10.37%; β=0.014, 95% CI 0.010‐0.018; P<.001), and via the sequential pathway through NLE and then IA (2.96%; β=0.004, 95% CI 0.003‐0.006; P<.001).ConclusionsUnlike previous research that examined them separately, this study reveals the chain mediation mechanism of NLE and IA in the relationship between SA and STB, providing a new research perspective on the complex evolution from early adversity to extreme outcomes. This research also provided clear direction and scientific evidence for the development of comprehensive suicide prevention strategies. Future efforts should focus on the prevention of SA and trauma intervention while simultaneously strengthening adolescents’ cognitive reappraisal of negative events and guiding their online behavior.

Depression and anxiety are highly prevalent and often co-occurring mental health issues among adolescents, with comorbidity leading to poorer outcomes and additional challenges. Left-behind adolescents-a unique group experiencing disrupted parent-child relationships and limited social support-may face a higher risk of such comorbidity. Yet, few studies have examined the depression-anxiety network in this population. Latent profile analysis (LPA) identified subgroups with similar symptom patterns, and network analysis visualized the structure of comorbidities. Network comparison tests evaluated differences across subgroups. Based on the "Science Database of People Mental Health" managed by the National Population Health Data Center (China), a total of 3,205 left-behind adolescents (1,538 males; 1,667 females) were included. The Patient Health Questionnaire-9 and the Generalized Anxiety Disorder Scale-7 were used to assess depression and anxiety among left-behind adolescents. Three distinct profiles were identified: high-comorbidity (8.2%), moderate-comorbidity (28.7%), and low-comorbidity (63.1%). Network structures and global strength differed significantly between subgroups. "Restlessness" was the central bridge symptom in the high-comorbidity group, while "Nervousness" was central in the moderate- and low-comorbidity groups. These findings suggest tailored interventions targeting subgroup-specific bridge symptoms-such as restlessness or nervousness-may improve outcomes for left-behind adolescents with comorbid depression and anxiety.

Tuberculosis (TB) patients who are diagnosed but not registered and initiated on TB treatment are categorised as initial loss to follow-up (ILTFU). ILTFU is a key driver of morbidity and mortality associated with TB and is a contributing factor to high TB transmission rates. LINKEDin was a quasi-experimental study which evaluated two specific interventions for reducing ILTFU in three high-TB burden provinces in South Africa, conducted from October 2018 to December 2020. As part of LINKEDin, we undertook a micro-costing from the healthcare provider perspective using an activity-based costing approach. Cost estimates included the cost of the operation of an integrated provincial health data centre in the Western Cape, apportioned to the TB activities it supported in the province. Cost estimates were linked to intervention outcomes to understand the incremental cost of the intervention per additional patient linked to care compared to rates of ILTFU in the absence of the interventions. Sensitivity analyses were conducted to account for uncertainty in the intervention outcomes, and for periods where the implementation of the intervention was interrupted due to COVID-19 related disruptions. Costing data were collected between August 2020 and March 2021. The total cost of implementing the LINKEDin intervention in the WC and KZN was $7 534.42 per month. The cost of implementing LINKEDin in the Western Cape accounted for 56% the total cost of the intervention – 8% from the operations of the PHDC and 48% from the cost of running the intervention – while only 44% of the total cost was accounted for by the intervention run in KwaZulu-Natal. The primary cost driver of the interventions were staff salaries, with the cost of data extraction and in-hospital activities low relative to primary healthcare (PHC)-based follow-up activities. In terms of cost effectiveness, the LINKEDin interventions in KZN was cost $377.28 per additional person linked to care, and $243.62 in the WC, per additional person linked to care. In the Western Cape, systematically tracking persons with TB using an automated system proved highly cost efficient compared to the more labour intense approach adopted in KwaZulu-Natal. Optimising the curation and management of data and increasing the effectiveness of tracing systems and processes can result in cost-savings.

Tuberculosis (TB) patients who are diagnosed but not registered and initiated on TB treatment are categorised as initial loss to follow-up (ILTFU). ILTFU is a key driver of morbidity and mortality associated with TB and is a contributing factor to high TB transmission rates. LINKEDin was a quasi-experimental study which evaluated two specific interventions for reducing ILTFU in three high-TB burden provinces in South Africa, conducted from October 2018 to December 2020. As part of LINKEDin, we undertook a micro-costing from the healthcare provider perspective using an activity-based costing approach. Cost estimates included the cost of the operation of an integrated provincial health data centre in the Western Cape, apportioned to the TB activities it supported in the province. Cost estimates were linked to intervention outcomes to understand the incremental cost of the intervention per additional patient linked to care compared to rates of ILTFU in the absence of the interventions. Sensitivity analyses were conducted to account for uncertainty in the intervention outcomes, and for periods where the implementation of the intervention was interrupted due to COVID-19 related disruptions. Costing data were collected between August 2020 and March 2021. The total cost of implementing the LINKEDin intervention in the WC and KZN was $7 534.42 per month. The cost of implementing LINKEDin in the Western Cape accounted for 56% the total cost of the intervention - 8% from the operations of the PHDC and 48% from the cost of running the intervention - while only 44% of the total cost was accounted for by the intervention run in KwaZulu-Natal. The primary cost driver of the interventions were staff salaries, with the cost of data extraction and in-hospital activities low relative to primary healthcare (PHC)-based follow-up activities. In terms of cost effectiveness, the LINKEDin interventions in KZN was cost $377.28 per additional person linked to care, and $243.62 in the WC, per additional person linked to care. In the Western Cape, systematically tracking persons with TB using an automated system proved highly cost efficient compared to the more labour intense approach adopted in KwaZulu-Natal. Optimising the curation and management of data and increasing the effectiveness of tracing systems and processes can result in cost-savings.

Pediatric tuberculosis (TB) remains a major public health concern in high-burden settings like the Western Cape (WC), South Africa. We analyzed geographic differences in TB burden among children and young adolescents, described temporal trends, and quantified gaps in the TB care cascade. We conducted a population-based descriptive study of pediatric TB episodes recorded in the Provincial Health Data Centre (PHDC) from 2017 to 2023, stratified by 5-year age groups. We assessed HIV status, drug resistance status, microbiological testing, disease classification, place of diagnosis, and TB treatment outcomes. Reporting gaps were estimated by comparing PHDC-recorded episodes with national notifications. Incidence rates of diagnosis were calculated using mid-year population estimates. In 2023, TB incidence rates of diagnosis in the WC were 722.4, 189.1, and 171.2 per 100 000 population for ages 0 to 4, 5 to 9, and 10 to 14years. Children aged 0 to 4years accounted for 68.9% of pediatric TB episodes. In the Cape Winelands district in 2023, TB incidence of diagnosis among 0- to 4-year-olds was double that of adults in the district and 2 to 4 times higher than 0- to 4-year-olds in other districts. We found high levels of underreporting (20.6%) and initial loss to follow-up (17.9%) among children and young adolescents diagnosed with TB between 2017 and 2023. Our findings highlight geographic variation in pediatric TB burden in the WC, emphasizing the need to address local drivers to inform targeted interventions. Gaps in the pediatric TB care cascade remain major concerns. Strengthening integrated data systems beyond TB treatment registers could improve surveillance, health system planning, and patient outcomes.

BackgroundThe COVID-2019 pandemic has led to changes in lifestyles, including sedentary behaviour, sleep duration and physical activity, which have further implications for people’s mental health. However, teachers are an important group whose mental health is often overlooked.ObjectiveWe aimed to investigate the relationship between sedentary behaviour, sleep duration and physical activity on teachers’ mental health during the COVID-19 pandemic in China.MethodsThis is a cross-sectional study targeting teachers from 10 schools in Sichuan Province with data sourced from the National Population Health Data Center. We used one-way analyses and multifactorial logistic regression and with model adjustment to explore the factors associated with teachers’ mental health. Subgroup analyses were used to further explore the magnitude of the effects of sedentary time, sleep duration and physical activity on teachers’ mental health.ResultsThe data suggest that reduced sedentary time (p = 0.016; p = 0.000) and adequate sleep (p = 0.040; p = 0.000) are related to anxiety and depression, whereas frequency of physical activity (p = 0.002) may be related to depression. Further analyses found that high frequency of physical activity in the context of long sedentary time and short sleep duration may be associated with anxiety and depression.ConclusionIntegrated behavioural interventions (sedentary behaviour, sleep duration and physical activity) are potential targets for the prevention and intervention of negative emotions in teachers. However, there is a lack of 24-h behavioural movement guidelines that are more specific to particular groups such as teachers, which is a gap that needs to be addressed in the future.

Objective.This study aimed to evaluate the prevalence and distribution of oral cancer and potentially malignant disorders among older adults in each region of Thailand, based on screening data between 2020 and 2024.Methods.Oral cancer screening data of patients aged 60 years between October 2020 and July 2024 were obtained from (1) the Health Data Center (community screening) and ( 2) Cancer Registry reports and Thai Cancer Base (hospital screening).Descriptive statistics were provided, and spatial analysis was performed.Results.Of 1 614 549 older adults screened, 540 (0.03%) had signs suggestive of oral cancer or potentially malignant disorders.The highest prevalence was observed among individuals aged 60 to 65 years.The incidence of oral cancer reached 8 per 100 000 among men and 4 per 100 000 among women.Tongue cancer was the most prevalent, followed by cancer of the floor of the mouth and lip cancer.The highest incidences of oral cancer were reported in the central and southern regions. Conclusions.Although the prevalence of oral cancer and potentially malignant disorders was low, the screening programme facilitates early intervention.Dental health education, regular oral evaluation, and effective referral may reduce late-stage diagnoses, while region-specific surveillance and data-informed planning support efficient resource allocation.

We described and compared infectious-cause hospitalisation outcomes among children born without HIV in the Western Cape (WC), South Africa, during the WHO Option B+ (2013-2015) and universal ART (2016-2018) eras by exposure to maternal HIV and ART. Retrospective cohort. Using data from the WC Provincial Health Data Centre, we described rates, causes and risk factors of infectious-cause hospitalisations, up to age 3 years, among children born at a public WC health facility. We compared rates of and risk factors for admission, in children exposed to maternal HIV and uninfected (HEU) and children HIV unexposed and uninfected (HUU), in the neonatal, postneonatal (age >28 days to ≤12 months), and age >12-36 month periods using mixed-effects Poisson regression. Regression models were adjusted for maternal age and suburb of residence. We included 398 334 mother-child pairs, 17.2% children HEU and 82.8% HUU. Infectious-cause hospitalisation, between birth and age 3 years, occurred in 11.5% vs. 10.9% of children HEU and HUU, respectively. Children HEU experienced higher rates of hospitalisation than children HUU, irrespective of maternal ART history, during the neonatal period (adjusted incidence rate ratios, aIRRs: 1.34-1.66) and postneonatal period (aIRRs: 1.13-1.42), but not during the >12-36 month period. Among children HEU, maternal viral load (VL) ≥1000/ml vs. <1000/ml during pregnancy was associated with higher admission rates during the postneonatal period (aIRR = 1.15; 95% CI: 1.06-1.25). Irrespective of timing of maternal ART start, children HEU vs. HUU had higher rates of infectious-cause hospitalisation during the first year of life, but not thereafter.

NAT2 rapid acetylator phenotype and increased risk of tuberculosis retreatment: A TB cohort study in Northern Thailand.

Children with multidrug-resistant (MDR)/rifampicin-resistant (RR) tuberculosis (TB) are an important but neglected group in cost-effectiveness research. Digital health information systems enable new approaches to health-service cost analysis. The Provincial Health Data Centre (PHDC) in the Western Cape, South Africa, collates disparate health system data including hospital inpatient and outpatient data, medications, laboratory tests, and primary health care utilisation. A health-service cost analysis used anonymised, integrated PHDC data for children treated for MDR/RR-TB between 2018 and 2021. Health-service utilisation was costed using local unit prices, and total per-patient costs were summarised by key patient and disease characteristics (age, sex, resistance profile, site of disease, and HIV status) and reported in 2021 USD. A log-linear regression model identified cost drivers, and alternative parametric distributions were fitted to total costs to assess distributional fit. There was significant total cost variation across the 271 children in the data sample (median US$7576; interquartile range 2725-22,986). Regression analysis indicates younger age, extrapulmonary disease site, living with HIV, and treatment duration had significant impact on costs; impact of resistance profile was significant but subject to modelling assumptions. The distribution of total per-patient costs fitted a gamma distribution (α = 0.93, β = 14,496). Treatment for MDR/RR-TB in children remains costly for health systems. Utilising routinely collected, real-world data from an established health information system enables accurate and representative insights to overall costs and major cost drivers. Costs were highly skewed, with a small proportion of patients incurring very high costs. This cost analysis can assist in decision making and programme development at local and international levels and as an input to secondary analysis.

Uncontrolled hypertension is an important public health issue and one of the leading contributor to global disease and mortality. The objective of this study was to determine the factors associated with uncontrolled hypertension among adults aged 35 years or older in Narathiwat province who had undergone hypertension screening for at least one year. Data were obtained from the Health Data Center of the national health database system from October 2012 to September 2022. A total of 43,015 adults were diagnosed with hypertension. Among them, 14,696 adults had uncontrolled hypertension, while 28,319 had achieved controlled blood pressure. Descriptive statistics and multiple logistic regression were employed to analyze the data. The overall prevalence of uncontrolled hypertension was 65.84%. The results showed that an uncontrolled hypertension was prevalent among older adults with aged more than 55 years, those who were single, those with no formal education, the unemployed, smokers, underweight adults, those who had been under care for a longer period, and those who had complications of diabetes mellitus. Therefore, this is suggested to raise awareness and encourage a healthy lifestyle to prevent or control hypertension.

To provide a reference for the initial diagnosis of clinical prostate cancer, we identified predictors and established a risk prediction model by analyzing a national Chinese prostate tumor dataset. Average value was used to interpolate the data from a prostate cancer dataset provided by the National Population Health Data Center of China. Factor screening was performed using the Kruskal–Wallis test and binary logistic regression. A multicollinearity analysis was performed on the variables. Cleaned data were divided into training and test datasets. Seven machine learning models and the 3 traditional clinical models were constructed. The top 3 models in terms of predictive efficacy were fused using a voting method. Accuracy, precision, F1 score, and area under the receiver operating characteristic curve metrics were used to evaluate the model. Feature importance analysis was used to determine the importance of the variables in each model. The study included 2213 cases: 1107 in the training set and 1106 in the test set. The prostate cancer model was established using back propagation neural network, random forest, and extreme gradient boosting algorithms and achieved an accuracy of 0.74, sensitivity of 0.78, F1 score of 0.77, and area under the curve of 0.80. The 5 key predictors of prostate cancer were the percentage of free prostate cancer-specific antigen, and the levels of inorganic phosphorus, apolipoprotein A1, free prostate cancer-specific antigen, and total prostate cancer-specific antigen. There was no high correlation among the variables. Our model based on fusing multiple models was good at assessing the risk of prostate cancer. This model could assist urologists in making appropriate treatment choices.

IntroductionRetention on antiretroviral therapy (ART) is a prerequisite for adherence and subsequent treatment success. Measuring retention is also easily implementable at facility and population levels, making it pragmatic to monitor ART programme success. However, despite its ubiquitous global use, there is little consistency in the measurement of retention.MethodsThis study retrospectively applied six measures of retention to one cohort of adults (initiating ART after 01‐09‐2016, with ≥1 year of observation time to database closure on 30‐09‐2022), in a low‐resource, high HIV‐burden setting in South Africa. Using routine healthcare data from the Western Cape's Provincial Health Data Centre, loss to follow‐up (LTFU), fixed‐point retention, visit constancy, visit gaps, treatment interruptions and medication possession ratio (MPR) were described over 5 years from initiation. Individuals were considered “continuously retained” if they did not experience attrition throughout their observed follow‐up. Measures were compared using the proportion misassigned and Cohen's Kappa statistic.ResultsThe median age of the cohort (n = 68,888) was 31 years (interquartile range [IQR] 26–38) at initiation, with 69% (47,631/68,888) female, and a median observed follow‐up of 4 years (IQR 3–5). Across different measures, retention was low, and declined over time. There was variable overlap; the proportion continuously retained throughout their observed follow‐up ranged from 60% (41,268/68,888 not LTFU) to 32% (22,381/68,888 MPR ≥80%). Retention by all measures was strongly associated with viral suppression.ConclusionsBy all measures, large proportions of people in this setting were considered out of ART care during 5 years of observed follow‐up time from initiation. This makes retention a critical target for intervention to improve population‐level viral suppression and achieve epidemic control. Measuring longitudinal retention revealed that most people disengaged from ART care at some point after initiation. Certain measures of retention (e.g. treatment interruptions) identified people in and out of care with more granularity, whereas blunter measures (e.g. LTFU) misassigned individuals’ retention status and missed patterns of retention over time as people cycled in and out of care between points of measurement. Ultimately, the choice of measure depends on the purpose of the evaluation and on the data available, but, where possible, more granular measures are recommended.

Sepsis remains a leading cause of morbidity and mortality worldwide, with disproportionately high burdens in low- and middle-income countries (LMICs) such as Thailand. Conventional clinical scoring tools, including qSOFA, often demonstrate limited accuracy in early sepsis detection, particularly in resource-constrained environments. This study addresses the urgent need for reliable, scalable, and interpretable predictive models by evaluating the performance of machine learning specifically Random Forest (RF) using hospital datasets from both tertiary and district hospitals in Thailand. The findings reveal that the RF model significantly outperformed logistic regression and qSOFA, achieving an AUROC of 0.89 and AUPRC of 0.76 in tertiary hospitals, and maintaining strong accuracy (AUROC 0.83, AUPRC 0.69) in district hospitals where fewer variables were available. Feature importance analysis highlighted systolic blood pressure, respiratory rate, oxygen saturation, and WBC count as the most influential predictors, aligning with established sepsis pathophysiology. Crucially, the model’s interpretability enhanced clinician trust and facilitated its potential integration into Thailand’s Universal Coverage Scheme and Health Data Center. These results demonstrate that lightweight, interpretable AI solutions can improve diagnostic accuracy and healthcare equity in LMIC settings. Thailand’s experience provides a transferable model for broader global health applications, illustrating how AI can support early sepsis detection, reduce mortality, and strengthen national health system resilience.

Seasonal changes in time policy, such as switching between Standard Time (SDT) and Daylight Saving Time (DST), have been adopted by many countries, including the United States. While transitioning between SDT and DST has notable acute negative population health impacts, the chronic impact of these time policies on health has not been well evaluated. To estimate the impact of permanent SDT or DST on health, we modeled the circadian impact of SDT, DST, and Biannual Shifting (BAS) across a year in the contiguous, continental United States. We find that BAS produces a greater burden on the circadian system as compared to either permanent SDT or DST. Chronotype as well as location (latitude and location within time zones) impact this burden. Analyzing these data relative to county-level health data (Centers for Disease Control and Prevention Places dataset), we find that, under idealized light exposure conditions and after controlling for health and socioeconomic factors, there would be a decrease in the prevalence of both obesity [[Formula: see text]0.78% ([Formula: see text]0.06% to [Formula: see text]1.49%)] and stroke [[Formula: see text]0.09% ([Formula: see text]0.04% to [Formula: see text]0.14%)] under SDT compared with the current policy. The prevalence of both obesity [[Formula: see text]0.51% ([Formula: see text]0.09% to [Formula: see text]0.93%)] and stroke [[Formula: see text]0.07% ([Formula: see text]0.04% to [Formula: see text]0.09%)] would also decrease under permanent DST, though to a lesser degree. Our data, reflecting the impact of time policy on circadian burden and subsequent health benefits, support the cessation of BAS.

Health data is highly sensitive, and one of the most targeted segments of data in recent cyber-attacks. In the development of the National Electronic Health Record (NEHR), the health data exchanged in FHIR format between electronic medical records and the NEHR had to be secured. A SMART on FHIR standard based authentication tool was developed and implemented in the Ministry of Health data centre in Sri Lanka. The developed solution was released as an open-source tool that can be implemented to secure FHIR based data exchange. The complexity of the SMART on FHIR standard, and the lack of financial and technical capacity poses a long-term challenge to maintain a novel tool for implementation of the standard based authentication to protect FHIR data exchange.

Background: Chronic kidney disease (CKD) poses a growing global health concern, particularly in low- and middle-income countries. In Thailand, CKD affects 4.6% to 17.5% of the population, with diabetic nephropathy and hypertension being the primary causes of end-stage renal disease (ESRD). To mitigate this, the Ministry of Public Health introduced CKD clinic policies in 2016 to slow progression in stages 1 to 4. The ESCORT-2 study demonstrated the effectiveness of integrated care, prompting nationwide adoption. The present study assessed the policy impact using 12 clinical performance indicators. Materials and Methods: Data from CKD stage 3 to 4 patients were retrieved from Roi Et Province’s Health Data Center between January 2014 and December 2021. Interrupted time series (ITS) analysis evaluated performance trends before and after policy implementation, stratified by hospital level. Results: Following policy implementation, significant improvements were observed in four key indicators, 1) the proportion of CKD patients receiving angiotensin converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARBs) increased from 43.46% by 7.95% (95% CI 4.41 to 11.49), 2) statin use rose from 39.78% by 3.51% (95% CI 0.063 to 6.95), 3) the percentage of patients with estimated glomerular filtration rate (eGFR) decline to less than 5 mL/minute/1.73 m²/year improved from 55.31% by 13.93% (95% CI 0.19 to 27.67), 4) urine protein to creatinine ratio (UPCR) testing increased from 2.10% by 9.64% (95% CI 0.31 to 18.98). Post-policy linear trend analysis also showed modest increases in ACEi/ARB use, potassium monitoring, statin prescription, and intact parathyroid hormone (iPTH) testing. Conclusion: The implementation of the kidney disease clinic policy has positively influenced the care of patients with chronic kidney disease. Continuing of this policy would benefit patients with chronic kidney disease.

South Africa is a high tuberculosis (TB) burdened country. People who are newly diagnosed with TB must link to a TB treatment facility and be registered in the electronic TB notification system for ongoing care. Delayed linkage to care increases the risk of disease progression, mortality, and ongoing TB transmission. We describe lessons from a systematic tracing process aimed to support linkage to care for people diagnosed with TB. The study used the Western Cape Provincial Health Data Centre (PHDC) to identify persons newly diagnosed with TB (January-December 2020) who were not recorded as linked to care after routine linking efforts, in one peri-urban health sub-district in Cape Town, South Africa. A systematic tracing process was followed, including visits to primary health care (PHC) facilities, and home visits for those with no evidence of linkage at PHC level. Descriptive statistics were used to analyse quantitative data. Lessons learned during the process were documented. Within the PHDC, 406 persons diagnosed with TB had no evidence of being linked to TB care. Verification at PHC facilities found that 153/406 (38%) had linked to care. We traced 219 persons; of which107 (49%) could not be found. Overall, the PHDC showed 76% linkage among those traced and found and 72% among those not found. Lessons learned include the need for improved; (i) record keeping enabling the allocation of resources to patients who are truly lost to follow up, (ii) communication to improve patient understanding of timely treatment initiation and (iii) interpersonal relationships to encourage trust. The systematic tracing process was useful to understand the complexities around delayed linkage to care. To reduce ILTFU, we recommend, improving accuracy and timely recording of TB data, updating patient contact details regularly and strengthening interpersonal relations and communication between patients and healthcare workers.