Acute mental health care according to recent mental health legislation Part II. Activity-based costing

Objective: This is the second of three reports on the follow-up review of mental health care at Helen Joseph Hospital (HJH). Objectives for the review were to provide realistic estimates of cost for unit activities and to establish a quality assurance cycle that may facilitate cost centre management. Method: The study described and used activity-based costing (ABC) as an approach to analyse the recurrent cost of acute in-patient care for the financial year 2007-08. Fixed (e.g. goods and services, staff salaries) and variable recurrent costs (including laboratory’, ‘pharmacy’) were calculated. Cost per day, per user and per diagnostic group was calculated. Results: While the unit accounted for 4.6% of the hospital’s total clinical activity (patient days), the cost of R8.12 million incurred represented only 2.4% of the total hospital expenditure (R341.36 million). Fixed costs constituted 90% of the total cost. For the total number of 520 users that stayed on average 15.4 days, the average cost was R1,023.00 per day and R15748.00 per user. Users with schizophrenia accounted for the most (35%) of the cost, while the care of users with dementia was the most expensive (R23,360.68 per user). Costing of the application of World Health Organization norms for acute care staffing for the unit, projected an average increase of 103% in recurrent costs (R5.1 million), with the bulk (a 267% increase) for nursing. Conclusion: In the absence of other guidelines, aligning clinical activity with the proportion of the hospital’s total budget may be an approach to determine what amount should be afforded to acute mental health in-patient care activities in a general regional hospital such as HJH. Despite the potential benefits of ABC, its continued application will require time, infrastructure and staff investment to establish the capacity to maintain routine annual cost analyses for different cost centres.Key words: Cost analysis; Activity-based costing; Acute mental health care; Recurrent cost; Fixed and variable cost; Cost centre management; Hospital expenditur

A call to action: Temporal trends of COVID-19 deaths in the South African Muslim community

Letter by Omar on letter by Jassat et al. (Jassat W, Brey Z, Parker S, et al. A call to action: Temporal trends of COVID-19 deaths in the South African Muslim community. S Afr Med J 2021;111(8):692-694. https://doi.org/10.7196/SAMJ.2021.v111i8.15878); and response by Jassat et al

Sentinel seroprevalence of SARS-CoV-2 in Gauteng Province, South Africa, August - October 2020

Background. Estimates of prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) for tracking the COVID-19 epidemic are lacking for most African countries.Objectives. To determine the prevalence of antibodies against SARS-CoV-2 in a sentinel cohort of patient samples received for routine testing at tertiary laboratories in Johannesburg, South Africa.Methods. This sentinel study was conducted using remnant serum samples received at three National Health Laboratory Service laboratories in the City of Johannesburg (CoJ) district. Collection was from 1 August to 31 October 2020. We extracted accompanying laboratory results for glycated haemoglobin (HbA1c), creatinine, HIV, viral load and CD4 T-cell count. An anti-SARS-CoV-2 targeting the nucleocapsid (N) protein of the coronavirus with higher affinity for IgM and IgG antibodies was used. We reported crude as well as population-weighted and test-adjusted seroprevalence. Multivariate logistic regression analysis was used to determine whether age, sex, HIV and diabetic status were associated with increased risk for seropositivity.Results. A total of 6 477 samples were analysed, the majority (n=5 290) from the CoJ region. After excluding samples with no age or sex stated, the model population-weighted and test-adjusted seroprevalence for the CoJ (n=4 393) was 27.0% (95% confidence interval (CI) 25.4 - 28.6). Seroprevalence was highest in those aged 45 - 49 years (29.8%; 95% CI 25.5 - 35.0) and in those from the most densely populated areas of the CoJ. Risk for seropositivity was highest in those aged 18 - 49 years (adjusted odds ratio (aOR) 1.52; 95% CI 1.13 - 2.13; p=0.0005) and in samples from diabetics (aOR 1.36; 95% CI 1.13 - 1.63; p=0.001).Conclusions. Our study conducted between the first and second waves of the pandemic shows high levels of current infection among patients attending public health facilities in Gauteng Province

COVID-19 hospital admissions and mortality among healthcare workers in South Africa, 2020–2021

AVAILABILITY OF DATA AND MATERIALS : The datasets generated and/or analyzed during this current study are available in the repository of the National Institute of Communicable Diseases. The data can be made available on request, which may be directed to [email protected]. Those requesting data will need to sign a data access agreement. The request will require approval by the National Department of Health.OBJECTIVES : This study describes the characteristics of admitted HCWs reported to the DATCOV surveillance system, and the factors associated with in-hospital mortality in South African HCWs. METHODS : Data from March 5, 2020 to April 30, 2021 were obtained from DATCOV, a national hospital surveillance system monitoring COVID-19 admissions in South Africa. Characteristics of HCWs were compared with those of non-HCWs. Furthermore, a logistic regression model was used to assess factors associated with in-hospital mortality among HCWs. RESULTS : In total, there were 169 678 confirmed COVID-19 admissions, of which 6364 (3.8%) were HCWs. More of these HCW admissions were accounted for in wave 1 (48.6%; n = 3095) than in wave 2 (32.0%; n = 2036). Admitted HCWs were less likely to be male (28.2%; n = 1791) (aOR 0.3; 95% CI 0.3–0.4), in the 50–59 age group (33.1%; n = 2103) (aOR 1.4; 95% CI 1.1–1.8), or accessing the private health sector (63.3%; n = 4030) (aOR 1.3; 95% CI 1.1–1.5). Age, comorbidities, race, wave, province, and sector were significant risk factors for COVID-19-related mortality. CONCLUSION : The trends in cases showed a decline in HCW admissions in wave 2 compared with wave 1. Acquired SARS-COV-2 immunity from prior infection may have been a reason for reduced admissions and mortality of HCWs despite the more transmissible and more severe beta variant in wave 2.DATCOV is funded by the National Institute for Communicable Diseases (NICD) and the South African National Government.http://www.elsevier.com/locate/ijregihj2023School of Health Systems and Public Health (SHSPH

Guiding equitable prioritisation of COVID-19 vaccine distribution and strategic deployment in South Africa to enhance effectiveness and access to vulnerable communities and prevent waste

BACKGROUND. In South Africa (SA), >2.4 million cases of COVID 19 and >72 000 deaths were recorded between March 2020 and 1 August 2021, affecting the country’s 52 districts to various extents. SA has committed to a COVID 19 vaccine roll-out in three phases, prioritising frontline workers, the elderly, people with comorbidities and essential workers. However, additional actions will be necessary to support efficient allocation and equitable access for vulnerable, access-constrained communities. OBJECTIVES. To explore various determinants of disease severity, resurgence risk and accessibility in order to aid an equitable, effective vaccine roll-out for SA that would maximise COVID 19 epidemic control by reducing the number of COVID 19 transmissions and resultant deaths, while at the same time reducing the risk of vaccine wastage. METHODS. For the 52 districts of SA, 26 COVID 19 indicators such as hospital admissions, deaths in hospital and mobility were ranked and hierarchically clustered with cases to identify which indicators can be used as indicators for severity or resurgence risk. Districts were then ranked using the estimated COVID 19 severity and resurgence risk to assist with prioritisation of vaccine roll-out. Urban and rural accessibility were also explored as factors that could limit vaccine roll-out in hard-to-reach communities. RESULTS. Highly populated urban districts showed the most cases. Districts such as Buffalo City, City of Cape Town and Nelson Mandela Bay experienced very severe first and second waves of the pandemic. Districts with high mobility, population size and density were found to be at highest risk of resurgence. In terms of accessibility, we found that 47.2% of the population are within 5 km of a hospital with ≥50 beds, and this percentage ranged from 87.0% in City of Cape Town to 0% in Namakwa district. CONCLUSIONS. The end goal is to provide equal distribution of vaccines proportional to district populations, which will provide fair protection. Districts with a high risk of resurgence and severity should be prioritised for vaccine roll-out, particularly the major metropolitan areas. We provide recommendations for allocations of different vaccine types for each district that consider levels of access, numbers of doses and cold-chain storage capability.The American people through the United States Agency for International Development (USAID).http://www.samj.org.zadm2022Human Nutritio

Understanding the differential impacts of COVID-19 among hospitalised patients in South Africa for equitable response

BACKGROUND : There are limited in-depth analyses of COVID-19 differential impacts, especially in resource-limited settings such as South Africa (SA). OBJECTIVES : To explore context-specific sociodemographic heterogeneities in order to understand the differential impacts of COVID-19. METHODS : Descriptive epidemiological COVID-19 hospitalisation and mortality data were drawn from daily hospital surveillance data, National Institute for Communicable Diseases (NICD) update reports (6 March 2020 - 24 January 2021) and the Eastern Cape Daily Epidemiological Report (as of 24 March 2021). We examined hospitalisations and mortality by sociodemographics (age using 10-year age bands, sex and race) using absolute numbers, proportions and ratios. The data are presented using tables received from the NICD, and charts were created to show trends and patterns. Mortality rates (per 100 000 population) were calculated using population estimates as a denominator for standardisation. Associations were determined through relative risks (RRs), 95% confidence intervals (CIs) and p-values <0.001. RESULTS : Black African females had a significantly higher rate of hospitalisation (8.7% (95% CI 8.5 - 8.9)) compared with coloureds, Indians and whites (6.7% (95% CI 6.0 - 7.4), 6.3% (95% CI 5.5 - 7.2) and 4% (95% CI 3.5 - 4.5), respectively). Similarly, black African females had the highest hospitalisation rates at a younger age category of 30 - 39 years (16.1%) compared with other race groups. Whites were hospitalised at older ages than other races, with a median age of 63 years. Black Africans were hospitalised at younger ages than other race groups, with a median age of 52 years. Whites were significantly more likely to die at older ages compared with black Africans (RR 1.07; 95% CI 1.06 - 1.08) or coloureds (RR 1.44; 95% CI 1.33 - 1.54); a similar pattern was found between Indians and whites (RR 1.59; 95% CI 1.47 - 1.73). Women died at older ages than men, although they were admitted to hospital at younger ages. Among black Africans and coloureds, females (50.9 deaths per 100 000 and 37 per 100 000, respectively) had a higher COVID-19 death rate than males (41.2 per 100 000 and 41.5 per 100 000, respectively). However, among Indians and whites, males had higher rates of deaths than females. The ratio of deaths to hospitalisations by race and gender increased with increasing age. In each age group, this ratio was highest among black Africans and lowest among whites. CONCLUSION : The study revealed the heterogeneous nature of COVID-19 impacts in SA. Existing socioeconomic inequalities appear to shape COVID-19 impacts, with a disproportionate effect on black Africans and marginalised and low socioeconomic groups. These differential impacts call for considered attention to mitigating the health disparities among black Africans.University of Johannesburghttp://www.samj.org.zadm2022Psycholog