A critical analysis of discovery health's claims-based risk adjustment of mortality rates in South African private sector hospitals

In 2019, Discovery Health published a risk adjustment model to determine standardised mortality rates across South African private hospital systems, with the aim of contributing towards quality improvement in the private healthcare sector. However, the model suffers from limitations due to its design and its reliance on administrative data. The publication's aim of facilitating transparency is unfortunately undermined by shortcomings in reporting. When designing a risk prediction model, patient-proximate variables with a sound theoretical or proven association with the outcome of interest should be used. The addition of key condition-specific clinical data points at the time of hospital admission will dramatically improve model performance. Performance could be further improved by using summary risk prediction scores such as the EUROSCORE II for coronary artery bypass graft surgery or the GRACE risk score for acute coronary syndrome. In general, model reporting should conform to published reporting standards, and attempts should be made to test model validity by using sensitivity analyses. In particular, the limitations of machine learning prediction models should be understood, and these models should be appropriately developed, evaluated and reported.

Perceptions of Door-to-Door HIV Counselling and Testing in Botswana

Prevalence of HIV infection in Botswana is among the highest in the world; at 23.9 of 15 - 49-year-olds. Most HIV testing is conducted in voluntary counselling and testing centres or medical settings. Improved access to testing is urgently needed. This qualitative study assessed and documented community perceptions about the concept of door-to-door HIV counselling and rapid testing in two of the highest-prevalence districts of Botswana. Community members associated many positive benefits with home-based; door-to-door HIV testing; including convenience; confidentiality; capacity to increase the number of people tested; and opportunities to increase knowledge of HIV transmission; prevention and care through provision of correct information to households. Community members also saw the intervention as increasing opportunities to engage and influence family members and to role model positive behaviours. Participants also perceived social risks and dangers associated with home-based testing including the potential for conflict; coercion; stigma; and psychological distress within households. Community members emphasised the need for individual and community preparation; including procedures to protect confidentiality; provisions for psychological and social support; and links to appropriate services for HIV-positive persons