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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 health-records 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. Cohen's/Fleiss’ kappa coefficients (κ) were used to measure agreements between the sources. While 3768 (65%) of the 5795 inpatient-level records contained a discharge summary, less than 835 (15%) of diagnoses were coded using ICD-10 codes. Despite most of the records having correct patient identifiers [κ: 0.92; 95% confidence interval (CI) 0.91–0.93], significant inconsistencies were observed between the registers, patient folders and discharge summaries for some data elements: attending physician’s signature (κ: 0.71; 95% CI 0.67–0.75); results of the investigation (κ: 0.71; 95% CI 0.69–0.74); patient’s age (κ: 0.72; 95% CI 0.70–0.74); and discharge diagnosis (κ: 0.92; 95% CI 0.90–0.94). The strength of agreement for all elements was statistically significant (P-value ≤ 0.001). The absence of coded inpatient diagnoses and identified data inaccuracies indicates that existing routine health information systems in public-sector hospitals in the NHI pilot districts are not yet able to sufficiently support reimbursements and resource management. Institutional capacity is needed to undertake diagnostic coding, improve data quality and ensure that a standard discharge summary is completed for every inpatient.

Objectives: Routine health information systems (RHISs) provide data that are vital for planning and monitoring individual health. Data from RHISs could also be used for purposes for which they were not originally intended, provided that the data are of sufficient quality. For example, morbidity data could be used to inform burden of disease estimations, which serve as important evidence to prioritize interventions and promote health. The objective of this study was to identify and assess published quantitative assessments of data quality related to patient morbidity in RHISs in use in South Africa. Materials and Methods: We conducted a review of literature published between 1994 and 2014 that assessed the quality of data in RHISs in South Africa. World Health Organization (WHO) data quality components were used as the assessment criteria. Results Of 420 references identified, 11 studies met the inclusion criteria. The studies were limited to tuberculosis and HIV. No study reported more than 3 WHO data quality components or provided a quantitative assessment of quality that could be used for burden of disease estimation. Discussion: The included studies had limited geographical focus and evaluated different source data at different levels of the information system. All studies reported poor data quality. Conclusion: This review confirmed concerns about the quality of data in RHISs, and highlighted the need for a comprehensive evaluation of the quality of patient-level morbidity data in RHISs in South Africa.

Objectives: To assess the clinical, occupational and financial outcomes of a new Clinical Aviation Medicine Service (CAMS) for UK military personnel. Methods: Consecutive patients over a 2 year period were included. Predictors of flying restrictions at referral and final outcome following consultation were modelled using logistic regression. National Health Service (NHS) Payment by Results tariffs and Defence capitation data were used to assess the financial impact of the service. Results: Eight hundred and sixteen new referrals (94.5% male, median age 45 years (range 19–75)) were received and 1025 consultations performed. Cardiovascular disease was the commonest reason for referral. CAMS clinical activity cost at NHS tariff was £453 310 representing a saving of £316 173 (£137 137 delivery cost). In total, 310/816 (38%) patients had employment restrictions on referral and 49.0% of this group returned to full employment following their initial consultation. Compared with cardiology, general medicine and respiratory patients were more likely to have been occupationally restricted prior to referral (50 vs. 35%, OR 1.81; 95% CI 1.18–2.76, P values=0.006 and 53 vs. 35%, OR 2.12; 95% CI 1.15–3.90, P values = 0.016, respectively). Overall 581/816 (71.2%) of patients returned to unrestricted employment while 98/816 (12.0%) were unable to continue in any aircrew role. The service saved 7000 lost working days per year at an estimated occupational saving of ∼£1 million per annum. Conclusions: This bespoke service has allowed rapid, occupationally relevant clinical care to be delivered with both time and financial savings. The model may have significant occupational and financial relevance for other environmental and occupational medical organizations.