Addressing the information deficit in global health: lessons from a digital acute care platform in Sri Lanka.

Lack of investment in low-income and middle-income countries (LMICs) in systems capturing continuous information regarding care of the acutely unwell patient is hindering global efforts to address inequalities, both at facility and national level. Furthermore, this of lack of data is disempowering frontline staff and those seeking to support them, from progressing setting-relevant research and quality improvement. In contrast to high-income country (HIC) settings, where electronic surveillance has boosted the capability of governments, clinicians and researchers to engage in service-wide healthcare evaluation, healthcare information in resource-limited settings remains almost exclusively paper based. In this practice paper, we describe the efforts of a collaboration of clinicians, administrators, researchers and healthcare informaticians working in South Asia, in addressing the inequality in access to patient information in acute care. Harnessing a clinician-led collaborative approach to design and evaluation, we have implemented a national acute care information platform in Sri Lanka that is tailored to priorities of frontline staff. Iterative adaptation has ensured the platform has the flexibility to integrate with legacy paper systems, support junior team members in advocating for acutely unwell patients and has made information captured accessible to diverse stakeholders to improve service delivery. The same platform is now empowering clinicians to participate in international research and drive forwards improvements in care. During this journey, we have also gained insights on how to overcome well-described barriers to implementation of digital information tools in LMIC. We anticipate that this north-south collaborative approach to addressing the challenges of health system implementation in acute care may provide learning and inspiration to other partnerships seeking to engage in similar work.

Inequalities in the prevalence of diabetes mellitus and its risk factors in Sri Lanka: a lower middle income country.

BACKGROUND: Explorations into quantifying the inequalities for diabetes mellitus (DM) and its risk factors are scarce in low and lower middle income countries (LICs/LMICs). The aims of this study were to assess the inequalities of DM and its risk factors in a suburban district of Sri Lanka. METHODS: A sample of 1300 participants, (aged 35-64 years) randomly selected using a stratified multi-stage cluster sampling method, were studied employing a cross sectional descriptive design. The socioeconomic indicators (SEIs) of the individual were education level and occupational category, and at the household level, the household income, social status level and area deprivation level. DM was diagnosed if the fasting plasma glucose was ≥126 and a body mass index (BMI) of > 27.5 kg/m2 was considered high. Asian cut-off values were used for high waist circumference (WC). Validated tools were used to assess the diet and level of physical activity. The slope index of inequality (SII), relative index of inequality (RII) and concentration index (CI) were used to assess inequalities. RESULTS: The prevalence of DM and its risk factors (at individual or household level) showed no consistent relationship with the three measures of inequality (SII, RII and CI) of the different indices of socio economic status (education, occupation, household income, social status index or area unsatisfactory basic needs index). The prevalence of diabetes showed a more consistent pro-rich distribution in females compared to males. Of the risk factors in males and females, the most consistent and significant pro-rich relationship was for high BMI and WC. In males, the significant positive relationship with high BMI for SII ranged from 0.18 to 0.35, and RII from 1.56 to 2.25. For high WC, the values were: SII from 0.13 to 0.27 and RII from 1.9 to 3.97. In females the significant positive relationship with high BMI in SII ranged from 0.13 to 0.29, and RII from 2.3 to 4.98. For high WC the values were: SII from 028 to 0.4 and RII 1.99 to 2.39. Of the other risk factors, inadequate fruit intake showed a consistent significant pro-poor distribution only in males using SII (- 0.25 to - 0.36) and in both sexes using CI. Smoking also showed a pro-poor distribution in males especially using individual measures of socio-economic status (i.e. education and occupation). CONCLUSIONS: The results show a variable relationship between socioeconomic status and prevalence of diabetes and its risk factors. The inequalities in the prevalence of diabetes and risk factors vary depending on gender and the measures used. The study suggests that measures to prevent diabetes should focus on targeting specific factors based on sex and socioeconomic status. The priority target areas for interventions should include prevention of obesity (BMI and central obesity) specifically in more affluent females. Males who have a low level of education and in non-skilled occupations should be especially targeted to reduce smoking and increase fruit intake.

Traumatic brain injury (TBI) outcomes in an LMIC tertiary care centre and performance of trauma scores.

BACKGROUND: This study evaluates post-ICU outcomes of patients admitted with moderate and severe Traumatic Brain Injury (TBI) in a tertiary neurocritical care unit in an low middle income country and the performance of trauma scores: A Severity Characterization of Trauma, Trauma and Injury Severity Score, Injury Severity Score and Revised Trauma Score in this setting. METHODS: Adult patients directly admitted to the neurosurgical intensive care units of the National Hospital of Sri Lanka between 21st July 2014 and 1st October 2014 with moderate or severe TBI were recruited. A telephone administered questionnaire based on the Glasgow Outcome Scale Extended (GOSE) was used to assess functional outcome of patients at 3 and 6 months after injury. The economic impact of the injury was assessed before injury, and at 3 and 6 months after injury. RESULTS: One hundred and one patients were included in the study. Survival at ICU discharge, 3 and 6 months after injury was 68.3%, 49.5% and 45.5% respectively. Of the survivors at 3 months after injury, 43 (86%) were living at home. Only 19 (38%) patients had a good recovery (as defined by GOSE 7 and 8). Three months and six months after injury, respectively 25 (50%) and 14 (30.4%) patients had become "economically dependent". Selected trauma scores had poor discriminatory ability in predicting mortality. CONCLUSIONS: This observational study of patients sustaining moderate or severe TBI in Sri Lanka (a LMIC) reveals only 46% of patients were alive at 6 months after ICU discharge and only 20% overall attained a good (GOSE 7 or 8) recovery. The social and economic consequences of TBI were long lasting in this setting. Injury Severity Score, Revised Trauma Score, A Severity Characterization of Trauma and Trauma and Injury Severity Score, all performed poorly in predicting mortality in this setting and illustrate the need for setting adapted tools.

A survey on socioeconomic determinants of diabetes mellitus management in a lower middle income setting.

BACKGROUND: Information on socioeconomic determinants in the management of diabetes mellitus is scarce in lower middle income countries. The aim of this study is to describe the socioeconomic determinants of management and complications of diabetes mellitus in a lower middle income setting. METHODS: Cross sectional descriptive study on a stratified random sample of 1300 individuals was conducted by an interviewer administered questionnaire, clinical examinations and blood investigations. A single fasting venous blood sugar of ≥126 mg/dl was considered diagnostic of new diabetics and poor control of diabetes mellitus as HbA1C > 6.5 %. RESULTS: There were 202 (14.7 %) with diabetes mellitus. Poor control was seen in 130 (90.7 %) while 71 (49.6 %) were not on regular treatment. Highest proportions of poor control and not on regular medication were observed in estate sector, poorest social status category and poorest geographical area. The annual HbA1C, microalbuminuria, retinal and neuropathy examination were performed in less than 6.0 %. Social gradient not observed in the management lapses. Most (76.6 %) had accessed private sector while those in estate (58.1 %) accessed the state system. The microvascular complications of retinopathy, neuropathy and microalbuminuria observed in 11.1 %, 79.3 % and 54.5 % respectively. Among the macrovascular diseases, angina, ischaemic heart disease and peripheral arterial disease seen in 15.5 %, 15.7 % and 5.5 % respectively. These complications do not show a social gradient. CONCLUSIONS: Diabetes mellitus patients, irrespective of their socioeconomic status, are poorly managed and have high rates of complications. Most depend on the private healthcare system with overall poor access to care in the estate sector.

A cross sectional survey on social, cultural and economic determinants of obesity in a low middle income setting.

INTRODUCTION: Obesity is an increasing problem in South Asian countries and Sri Lanka is no exception. The socioeconomic determinants of obesity in Sri Lanka, and in neighbouring countries are inadequately described. Aim was to describe social, cultural and economic determinants of obesity in a representative sample from Kalutara District in Sri Lanka. METHODS: This was a cross sectional descriptive study conducted among adults aged 35-64 years. A representative sample was selected using stratified random cluster sampling method from urban, rural and plantation sectors of Kalutara District. Data were collected using a pre-tested questionnaire. A body mass index of 23.01 kg/m(2)-27.50 kg/m(2) was considered as overweight and ≥27.51 kg/m(2) as obese. Waist circumference (WC) of ≥ 90 cm and ≥80 cm was regarded as high for men and women respectively. Significance of prevalence of obesity categories across different socio-economic strata was determined by chi square test for trend. RESULTS: Of 1234 adults who were screened, age and sex adjusted prevalence of overweight, obesity and abdominal obesity (high WC) were 33.2% (male 27.3%/female 38.7%), 14.3% (male 9.2%/female 19.2%) and 33.6% (male 17.7%/female 49.0%) respectively. The Muslims had the highest prevalence of all three obesity categories. Sector, education, social status quintiles and area level deprivation categories show a non linear social gradient while income shows a linear social gradient in all obesity categories, mean BMI and mean WC. The differences observed for mean BMI and mean WC between the lowest and highest socioeconomic groups were statistically significant. CONCLUSION: There is a social gradient in all three obesity categories with higher prevalence observed in the more educated, urban, high income and high social status segments of society. The higher socioeconomic groups are still at a higher risk of all types of obesity despite other public health indicators such as maternal and infant mortality displaying an established social gradient.