Is the routine health information system ready to support the planned national health insurance scheme in South Africa?

Implementation of a National Health Insurance (NHI) in South Africa requires a reliable, standardized health information system that supports Diagnosis-Related Groupers for reimbursements and resource management. We assessed the quality of inpatient health records, the availability of standard discharge summaries and coded clinical data and the congruence between inpatient health records and discharge summaries in public-sector hospitals to support the NHI implementation in terms of reimbursement and resource management. We undertook a cross-sectional healthrecords review from 45 representative public hospitals consisting of seven tertiary, 10 regional and 28 district hospitals in 10 NHI pilot districts representing all nine provinces. Data were abstracted from a randomly selected sample of 5795 inpatient health records from the surgical, medical, obstetrics and gynaecology, paediatrics and psychiatry departments. Quality was assessed for 10 pre-defined data elements relevant to NHI reimbursements, by comparing information in source registers, patient folders and discharge summaries for patients admitted in March and July 2015

HIV and pre-neoplastic and neoplastic lesions of the cervix in South Africa: a case-control study

BACKGROUND: Cervical cancer and infection with human immunodeficiency virus (HIV) are both major public health problems in South Africa. The aim of this study was to determine the risk of cervical pre-cancer and cancer among HIV positive women in South Africa. METHODS: Data were derived from a case-control study that examined the association between hormonal contraceptives and invasive cervical cancer. The study was conducted in the Western Cape (South Africa), from January 1998 to December 2001. There were 486 women with invasive cervical cancer, 103 control women with atypical squamous cells of undetermined significance (ASCUS), 53 with low-grade squamous intraepithelial lesions (LSIL), 50 with high-grade squamous intraepithelial lesions (HSIL) and 1159 with normal cytology. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using multiple logistic regression. RESULTS: The adjusted odds ratios associated with HIV infection were: 4.4 [95% CI (2.3 – 8.4) for ASCUS, 7.4 (3.5 – 15.7) for LSIL, 5.8 (2.4 – 13.6) for HSIL and 1.17 (0.75 – 1.85) for invasive cervical cancer. HIV positive women were nearly 5 times more likely to have high-risk human papillomavirus infection (HR-HPV) present compared to HIV negative women [OR 4.6 (95 % CI 2.8 – 7.5)]. Women infected with both HIV and high-risk HPV had a more than 40 fold higher risk of SIL than women infected with neither of these viruses. CONCLUSION: HIV positive women were at an increased risk of cervical pre-cancer, but did not demonstrate an excess risk of invasive cervical cancer. An interaction between HIV and HR-HPV infection was demonstrated. Our findings underscore the importance of developing locally relevant screening and management guidelines for HIV positive women in South Africa

Drinking patterns vary by gender, age and country-level income: Cross-country analysis of the International Alcohol Control Study

INTRODUCTION AND AIMS: Gender and age patterns of drinking are important in guiding country responses to harmful use of alcohol. This study undertook cross-country analysis of drinking across gender, age groups in some high-and middle-income countries. DESIGN AND METHODS: Surveys of drinkers were conducted in Australia, England, Scotland, New Zealand, St Kitts and Nevis (high-income), Thailand, South Africa, Mongolia and Vietnam (middle-income) as part of the International Alcohol Control Study. Drinking pattern measures were high-frequency, heavier-typical quantity and higher-risk drinking. Differences in the drinking patterns across age and gender groups were calculated. Logistic regression models were applied including a measure of country-level income. RESULTS: Percentages of high-frequency, heavier-typical quantity and higher-risk drinking were greater among men than in women in all countries. Older age was associated with drinking more frequently but smaller typical quantities especially in high-income countries. Middle-income countries overall showed less frequent but heavier typical quantities; however, the lower frequencies meant the percentages of higher risk drinkers were lower overall compared with high-income countries (with the exception of South Africa). DISCUSSION AND CONCLUSIONS: High-frequency drinking was greater in high-income countries, particularly in older age groups. Middle-income countries overall showed less frequent drinking but heavier typical quantities. As alcohol use becomes more normalised as a result of the expansion of commercial alcohol it is likely frequency of drinking will increase with a likelihood of greater numbers drinking at higher risk levels

Level of agreement between objectively determined body composition and perceived body image in 6- To 8-year-old South African children- To Body Composition-Isotope Technique study

To assess the level of agreement between body size self-perception and actual body size determined by body mass index (BMI) z-score and body fatness measured by the deuterium dilution method (DDM) in South African children aged 6-8 years. A cross-sectional sample of 202 children (83 boys and 119 girls) aged 6-8 years from the Body Composition-Isotope Technique study (BC-IT) was taken. Subjective measures of body image (silhouettes) were compared with the objective measures of BMI z-score and body fatness measured by the DDM. The World Health Organization BMI z-scores were used to classify the children as underweight, normal, overweight, or obese. DDM-measured fatness was classified based on the McCarthy centile curves set at 2nd, 85th and 95th in conjunction with fatness cut-off points of 25% in boys and 30% in girls. Data were analyzed using SPSS v26. Of 202 children, 32.2%, 55.1%, 8.8%, and 2.4% perceived their body size as underweight, normal, overweight, and obese, respectively. Based on BMI z-score, 18.8%, 72.8%, 6.9%, and 1.5% were classified as underweight, normal, overweight, and obese, respectively. Body fatness measurement showed that 2.5%, 48.0%, 21.8%, and 29.7% were underweight, normal weight, overweight, and obese, respectively