Dataset Information

Childhood cancers in a section of the South African private health sector: Analysis of medicines claims data.

ABSTRACT: Background:Although childhood cancers are rare, increases in incidence have been observed in recent times. There is a paucity of data on the current incidence of childhood cancers in South Africa. Aim:This study described the epidemiology of childhood cancers in a section of the private health sector of South Africa, using medicines claims data. Setting:This study was designed on a nationally representative medicine claims database. Method:A longitudinal open-cohort study employing children younger than 19 years and diagnosed with cancers between 2008 and 2017 was conducted using medicine claims data from a South African Pharmaceutical Benefit Management company. Cases were identified using International Classification of Diseases, Tenth Revision (ICD-10) diagnostic codes C00 to C97, together with a medicine claim reimbursed from oncology benefits. Crude incidence rates were calculated per million persons younger than 19 years on the database and standardised using the Segi 1960 world population. Temporal trends in incidence rates, analysed using the joinpoint regression, were reported as annual percentage changes (APCs). Results:Overall, 173 new cases of childhood cancers were identified in the database, translating into an age-standardised incidence rate (ASR) of 82.3 per million. Annual incidence of cancer decreased from 76.7 per million in 2008 to 58.2 per million in 2017. More incident cases were identified in males (68.8%). The highest proportion of incident cases was recorded for leukaemias (39.9%), the 5-9 year age group (34.1%) and the Gauteng Province (49.7%). Conclusion:The incidence of childhood cancers decreased over time in the section of the private health sector studied. Leukaemias were the major drivers of childhood cancer incidence.

SUBMITTER: Otoo MN

PROVIDER: S-EPMC7564764 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Childhood cancers in a section of the South African private health sector: Analysis of medicines claims data.

Otoo Marianne N MN Lubbe Martie S MS Steyn Hanlie H Burger Johanita R JR

Health SA = SA Gesondheid 20200930

<h4>Background</h4>Although childhood cancers are rare, increases in incidence have been observed in recent times. There is a paucity of data on the current incidence of childhood cancers in South Africa.<h4>Aim</h4>This study described the epidemiology of childhood cancers in a section of the private health sector of South Africa, using medicines claims data.<h4>Setting</h4>This study was designed on a nationally representative medicine claims database.<h4>Method</h4>A longitudinal open-cohort ...[more]

PMID: 33101715

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Project description:BackgroundThe use of opioids is increasing globally, but data from low- and middle-income countries on opioid-related mental and behavioural disorders (hereafter referred to as opioid-related disorders) are scarce. This study examines the incidence of opioid-related disorders, opioid agonist use, and excess mortality among persons with opioid-related disorders in South Africa's private healthcare sector.MethodsWe analysed longitudinal data of beneficiaries (≥ 11 years) of a South African medical insurance scheme using reimbursement claims from Jan 1, 2011, to Jul 1, 2020. Beneficiaries were classified as having an opioid-related disorder if they received an opioid agonist (buprenorphine or methadone) or an ICD-10 diagnosis for harmful opioid use (F11.1), opioid dependence or withdrawal (F11.2-4), or an unspecified or other opioid-related disorder (F11.0, F11.5-9). We calculated adjusted hazard ratios (aHR) for factors associated with opioid-related disorders, estimated the cumulative incidence of opioid agonist use after receiving an ICD-10 diagnosis for opioid dependence or withdrawal, and examined excess mortality among beneficiaries with opioid-related disorders.ResultsOf 1,251,458 beneficiaries, 1286 (0.1%) had opioid-related disorders. Between 2011 and 2020, the incidence of opioid-related disorders increased by 12% (95% CI 9%-15%) per year. Men, young adults in their twenties, and beneficiaries with co-morbid mental health or other substance use disorders were at increased risk of opioid-related disorders. The cumulative incidence of opioid agonist use among beneficiaries who received an ICD-10 diagnosis for opioid dependence or withdrawal was 18.0% (95% CI 14.0-22.4) 3 years after diagnosis. After adjusting for age, sex, year, medical insurance coverage, and population group, opioid-related disorders were associated with an increased risk of mortality (aHR 2.28, 95% CI 1.84-2.82). Opioid-related disorders were associated with a 7.8-year shorter life expectancy.ConclusionsThe incidence of people diagnosed with or treated for an opioid-related disorder in the private sector is increasing rapidly. People with opioid-related disorders are a vulnerable population with substantial psychiatric comorbidity who often die prematurely. Evidence-based management of opioid-related disorders is urgently needed to improve the health outcomes of people with opioid-related disorders.

Project description:BackgroundThe use of government health data for secondary purposes, such as monitoring the quality of hospital services, researching the health needs of populations, and testing how well new treatments work, is increasing. This increase in the secondary uses of health data has led to increased interest in what the public thinks about data sharing, in particular, the possibilities of sharing with the private sector for research and development. Although international evidence demonstrates broad public support for the secondary use of health data, this support does not extend to sharing health data with the private sector. If governments intend to share health data with the private sector, knowing what the public thinks will be important. This paper reports a national survey to explore public attitudes in Australia toward sharing health data with private companies for research on and development of therapeutic drugs and medical devices.ObjectiveThis study aims to explore public attitudes in Australia toward sharing government health data with the private sector.MethodsA web-based survey tool was developed to assess attitudes about sharing government health data with the private sector. A market research company was employed to administer the web-based survey in June 2019.ResultsThe survey was completed by 2537 individuals residing in Australia. Between 51.8% and 57.98% of all participants were willing to share their data, with slightly fewer in favor of sharing to improve health services (51.99%) and a slightly higher proportion in favor of sharing for research and development (57.98%). There was a preference for opt-in consent (53.44%) and broad support for placing conditions on sharing health information with private companies (62% to 91.99%). Wide variability was also observed in participants' views about the extent to which the private sector could be trusted and how well they would behave if entrusted with people's health information. In their qualitative responses, the participants noted concerns about private sector corporate interests, corruption, and profit making and expressed doubt about the Australian government's capacity to manage data sharing safely. The percentages presented are adjusted against the Australian population.ConclusionsThis nationally representative survey provides preliminary evidence that Australians are uncertain about sharing their health data with the private sector. Although just over half of all the respondents supported sharing health data with the private sector, there was also strong support for strict conditions on sharing data and for opt-in consent and significant concerns about how well the private sector would manage government health data. Addressing public concern about sharing government health data with the private sector will require more and better engagement to build community understanding about how agencies can collect, share, protect, and use their personal data.

Project description:BACKGROUND:South Africa's divided healthcare system is believed to be inequitable as the population serviced by each sector and the treatment received differs while annual healthcare expenditure is similar. The appropriateness of treatment received and in particular the cost of the same treatment between the sectors remains debatable and raises concerns around equitable healthcare. Colorectal cancer places considerable pressure on the funders, yet treatment utilization data and the associated costs of non-communicable diseases, in particular colorectal cancer, are limited for South Africa. Resources need to be appropriately managed while ensuring equitable healthcare is provided regardless of where the patient is able to receive their treatment. Therefore the aim of this study was to determine the cost of colorectal cancer treatment in a privately insured patient population in order to compare the costs and utilization to a previously published public sector patient cohort. METHODS:Private sector costs were determined using de-identified claim-based data for all newly diagnosed CRC patients between 2012 and 2014. The costs obtained from this patient cohort were compared to previously published public sector data for the same period. The costs compared were costs incurred by the relevant sector funder and didn't include out-of-pocket costs. RESULTS:The comparison shows private sector patients gain access to more of the approved regimens (12 vs. 4) but the same regimens are more costly, for example CAPOX costs approximately €150 more per cycle. The cost difference between 5FU and capecitabine monotherapy is less than €30 per cycle however, irinotecan is cheaper in comparison to oxaliplatin in the private sector (FOLFOX approx. €500 vs. FOLFIRI aprox. €460). Administrative costs account for up to 45% of total costs compared to the previously published data of these costs totaling < 15% of the full treatment cost in South Africa's public healthcare system. CONCLUSION:This comparison highlights the disparities between sectors while illustrating the need for further research to improve resource management to attain equitable healthcare.

Project description:BackgroundStunting during childhood has long-term consequences on human capital, including decreased physical growth, and lower educational attainment, cognition, workforce productivity and wages. Previous research has quantified the costs of stunting to national economies however beyond a few single-country datasets there has been a limited number of which have used diverse datasets and have had a dedicated focus on the private sector, which employs nearly 90% of the workforce in many low- and middle-income countries (LMICs). We aimed to examine (i) the impact of childhood stunting on income loss of private sector workforce in LMICs; (ii) to quantify losses in sales to private firms in LMICs due to childhood stunting; and (iii) to estimate potential gains (benefit-cost ratios) if stunting levels are reduced in select high prevalence countries.MethodsThis multiple-methods study engaged multi-disciplinary technical advisers, executed several literature reviews, used innovative statistical methods, and implemented health and labor economic models. We analyzed data from seven longitudinal datasets (up to 30+ years of follow-up; 1982-2016; Peru, Ethiopia, India, Vietnam, Philippines, Tanzania, Brazil), 108 private firm datasets (spanning 2008-2020), and many global datasets including Joint Malnutrition Estimates, and World Development Indicators to produce estimates for 120+ LMICs (with estimates up to 2021). We studied the impact of childhood stunting on adult cognition, education, and height as pathways to wages/productivity in adulthood. We employed cloud-based artificial intelligence (AI) platforms, and conducted comparative analyses using three analytic approaches: traditional frequentist statistics, Bayesian inferential statistics and machine learning. We employed labour and health economic models to estimate wage losses to the private sector worker and firm revenue losses due to stunting. We also estimated benefit-cost ratios for countries investing in nutrition-specific interventions to prevent stunting.FindingsAcross 95 LMICs, childhood stunting costs the private sector at least US$135.4 billion in sales annually. Firms from countries in Latin America and the Caribbean and East Asia and Pacific regions had the greatest losses. Totals sales losses to the private sector accumulated to 0.01% to 1.2% of national GDP across countries. Sectors most affected by childhood stunting were manufacturing (non-metallic mineral, fabricated metal, other), garments and food sectors. Sale losses were highest for larger sized private firms. Across regions (representing 123 LMICs), US$700 million (Middle East and North Africa) to US$16.5 billion (East Asia and Pacific) monthly income was lost among private sector workers. Investing in stunting reduction interventions yields gains from US$2 to US$81 per $1 invested annually (or 100% to 8000% across countries). Across sectors, the highest returns were in elementary occupations (US$46) and the lowest were among agricultural workers (US$8). By gender, women incurred a higher income penalty from childhood stunting and earned less than men; due to their relatively higher earnings, the returns for investing in stunting reduction were consistently higher for men across most countries studied.InterpretationChildhood stunting costs the private sector in LMICs billions of dollars in sales and earnings for the workforce annually. Returns to nutrition interventions show that there is an economic case to be made for investing in childhood nutrition, alongside a moral one for both the public and private sector. This research could be used to motivate strong public-private sector partnerships to invest in childhood undernutrition for benefits in the short and long-term.

Dataset Information

Childhood cancers in a section of the South African private health sector: Analysis of medicines claims data.

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Childhood cancers in a section of the South African private health sector: Analysis of medicines claims data.

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