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It is frequently stated in the scientific literature, official reports and the press that 80% of Asian and African populations use traditional medicine (TM) to meet their healthcare needs; however, this statistic was first reported in 1983. This study aimed to update knowledge of the prevalence of TM use and the characteristics of those who access it, to inform health policy-makers as countries seek to fulfil the WHO TM strategy 2014–23 and harness TM for population health. Prevalence of reported use of TM was studied in 35 334 participants of the WHO-SAGE, surveyed 2007–10. TM users were compared with users of modern healthcare in univariate and multivariate analyses. Characteristics examined included age, sex, geography (urban/rural), income quintile, education, self-reported health and presence of specific chronic conditions. This study found TM use was highest in India, 11.7% of people reported that their most frequent source of care during the previous 3 years was TM; 19.0% reported TM use in the previous 12 months. In contrast <3% reported TM as their most frequent source of care in China, Ghana, Mexico, Russia and South Africa; and <2% reported using TM in the previous year in Ghana, Mexico, Russia and South Africa. In univariate analyses, poorer, less educated and rural participants were more likely to be TM-users. In the China multivariate analysis, rurality, poor self-reported health and presence of arthritis were associated with TM use; whereas diagnosed diabetes, hypertension and cataracts were less prevalent in TM users. In Ghana and India, lower income, depression and hypertension were associated with TM use. In conclusion, TM use is less frequent than commonly reported. It may be unnecessary, and perhaps futile, to seek to employ TM for population health needs when populations are increasingly using modern medicine.

The effect of many cost effective policy and service interventions cannot be detected at the level of the patient. This new framework could help improve the design (especially choice of primary end point) and interpretation of evaluative studies

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Objective To conduct a nationwide study of associations between removal of all ovarian tissue versus conservation of at least one ovary at the time of hysterectomy and important health outcomes (ischaemic heart disease, cancer, and all cause mortality). Study design and setting Retrospective analysis of the English Hospital Episode Statistics database linked to national registers of deprivation indices and of deaths. Participants 113 679 patients aged 35-45 who had had a hysterectomy for benign conditions between April 2004 and March 2014. Exposures Bilateral ovarian removal versus no removal or unilateral ovarian removal (ovarian conservation). Main outcome measures Hospital admissions for ischaemic heart disease, cancer, or attempted suicide; deaths, overall and from heart disease, cancer, or suicide. Statistical adjustments were made using Cox regression and propensity score matching for potential confounders. Results A third of patients had bilateral ovarian removal. Patients in the ovarian conservation group were less likely to be admitted for ischaemic heart disease after hysterectomy than were those in the bilateral removal group (adjusted hazard ratio 0.85, 95% confidence interval 0.77 to 0.93; P=0.001). They were also less likely to have a cancer related post-hysterectomy admission (adjusted hazard ratio 0.83, 0.78 to 0.89; P<0.001). A significant difference in all cause mortality was also seen: 0.60% (456/76 581) of patients with ovarian conservation compared with 1.01% (376/37 098) of patients with bilateral removal. Again, this difference in favour of ovarian conservation was significant (adjusted hazard ratio 0.64, 0.55 to 0.73; P<0.001). Fewer deaths related specifically to heart disease (adjusted hazard ratio 0.50, 0.28 to 0.90; P=0.02) and to cancer (0.54, 0.45 to 0.65; P<0.001) occurred in the ovarian conservation group than in the bilateral removal group. No significant difference between groups was found relating to suicide (attempted or completed). The results after propensity score matching were essentially unchanged. Conclusion Patients who had ovarian conservation had a significantly lower hazard of all cause mortality compared with those who had bilateral ovarian removal and also had lower death rates from ischaemic heart disease and cancer. Consistent with this observation, admissions to hospital for both ischaemic heart disease and cancer were also lower in the ovarian conservation group than in the bilateral removal group. Although removal of both ovaries protects against subsequent development of ovarian cancer, premenopausal women should be advised that this benefit comes at the cost of an increased risk of cardiovascular disease and of other (more prevalent) cancers and higher overall mortality.

Risk-adjustment schemes are used to monitor hospital performance, on the assumption that excess mortality not explained by case mix is largely attributable to suboptimal care. We have developed a model to estimate the proportion of the variation in standardised mortality ratios (SMRs) that can be accounted for by variation in preventable mortality. The model was populated with values from the literature to estimate a predictive value of the SMR in this context—specifically the proportion of those hospitals with SMRs among the highest 2.5% that fall among the worst 2.5% for preventable mortality. The extent to which SMRs reflect preventable mortality rates is highly sensitive to the proportion of deaths that are preventable. If 6% of hospital deaths are preventable (as suggested by the literature), the predictive value of the SMR can be no greater than 9%. This value could rise to 30%, if 15% of deaths are preventable. The model offers a ‘reality check’ for case mix adjustment schemes designed to isolate the preventable component of any outcome rate.

Systematic reviews of interventions are typically used to evaluate the effects of treatments, one indication at a time. Here, we argue that, with due attention to methodological caveats, much can be learned by comparing the effects of a given treatment across many related indications.

BackgroundWe developed a method to estimate the expected cost-effectiveness of a service intervention at the design stage and ‘road-tested’ the method on an intervention to improve patient handover of care between hospital and community.MethodThe development of a nine-step evaluation framework:1. Identification of multiple endpoints and arranging them into manageable groups;2. Estimation of baseline overall and preventable risk;3. Bayesian elicitation of expected effectiveness of the planned intervention;4. Assigning utilities to groups of endpoints;5. Costing the intervention;6. Estimating health service costs associated with preventable adverse events;7. Calculating health benefits;8. Cost-effectiveness calculation;9. Sensitivity and headroom analysis.Results    Literature review suggested that adverse events follow 19% of patient discharges, and that one-third are preventable by improved handover (ie, 6.3% of all discharges). The intervention to improve handover would reduce the incidence of adverse events by 21% (ie, from 6.3% to 4.7%) according to the elicitation exercise. Potentially preventable adverse events were classified by severity and duration. Utilities were assigned to each category of adverse event. The costs associated with each category of event were obtained from the literature. The unit cost of the intervention was €16.6, which would yield a Quality Adjusted Life Year (QALY) gain per discharge of 0.010. The resulting cost saving was €14.3 per discharge. The intervention is cost-effective at approximately €214 per QALY under the base case, and remains cost-effective while the effectiveness is greater than 1.6%.ConclusionsWe offer a usable framework to assist in ex ante health economic evaluations of health service interventions.