Background In Ghana, there are issues with the diagnosis of typhoid fever; these include delays in diagnosis, concerns about the accuracy of current tests, and lack of availability. These issues highlight the need for the development of a rapid, accurate, and easily accessible diagnostic test. The aim of this study was to conduct an early economic analysis of a hypothetical rapid test for typhoid fever diagnosis in Ghana and identify the necessary characteristics of the test for it to be cost effective in Ghana. Methods An early cost-utility analysis was conducted using a decision tree parameterized with secondary data sources, with reasonable assumptions made for unknown parameters. The patient population considered is individuals presenting with symptoms suggestive of typhoid fever at a healthcare facility in Ghana; a time horizon of 180 days and the Ghanaian national health service perspective were adopted for the analysis. Extensive sensitivity analysis was undertaken, including headroom analysis. Results The results here show that for a hypothetical test to perform better than the existing test (Widal) in terms of QALYs gained and cost effectiveness, it is necessary for it to have a high specificity (at least 70%) and should not be priced more than US$4. The overall value of conducting research to reduce uncertainty (over 5 years) is US$3287. Conclusion The analysis shows the potential for the hypothetical test to replace the Widal test and the market potential of developing a new test in the Ghanaian setting.

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There is little specific guidance on the implementation of cost-effectiveness modelling at the early stage of test development. The aim of this study was to review the literature in this field to examine the methodologies and tools that have been employed to date. Areas Covered: A systematic review to identify relevant studies in established literature databases. Five studies were identified and included for narrative synthesis. These studies revealed that there is no consistent approach in this growing field. The perspective of patients and the potential for value of information (VOI) to provide information on the value of future research is often overlooked. Test accuracy is an essential consideration, with most studies having described and included all possible test results in their analysis, and conducted extensive sensitivity analyses on important parameters. Headroom analysis was considered in some instances but at the early development stage (not the concept stage). Expert commentary: The techniques available to modellers that can demonstrate the value of conducting further research and product development (i.e. VOI analysis, headroom analysis) should be better utilized. There is the need for concerted efforts to develop rigorous methodology in this growing field to maximize the value and quality of such analysis.

The two settings in Ghana have different care pathways and any cost-effectiveness analysis should consider the alternative pathways separately. This study demonstrated that framework analysis is a qualitative methodology that is likely to be accessible and feasible across a wide range of health economic settings.

Background Breast cancer clinics across the UK have long been struggling to cope with high demand. Novel risk prediction tools – such as the PinPoint test – could help to reduce unnecessary clinic referrals. Using early data on the expected accuracy of the test, we explore the potential impact of PinPoint on: (a) the percentage of patients meeting the two-week referral target, and (b) the number of clinic ‘overspill’ appointments generated (i.e. patients having to return to the clinic to complete their required investigations). Methods A simulation model was built to reflect the annual flow of patients through a single UK clinic. Due to current uncertainty around the exact impact of PinPoint testing on standard care, two primary scenarios were assessed. Scenario 1 assumed complete GP adherence to testing, with only non-referred cancerous cases returning for delayed referral. Scenario 2 assumed GPs would overrule 20% of low-risk results, and that 10% of non-referred non-cancerous cases would also return for delayed referral. A range of sensitivity analyses were conducted to explore the impact of key uncertainties on the model results. Service reconfiguration scenarios, removing individual weekly clinics from the clinic schedule, were also explored. Results Under standard care, 66.3% (95% CI: 66.0 to 66.5) of patients met the referral target, with 1,685 (1,648 to 1,722) overspill appointments. Under both PinPoint scenarios, > 98% of patients met the referral target, with overspill appointments reduced to between 727 (707 to 746) [Scenario 1] and 886 (861 to 911) [Scenario 2]. The reduced clinic demand was sufficient to allow removal of one weekly low-capacity clinic [N = 10], and the results were robust to sensitivity analyses. Conclusion The findings from this early analysis indicate that risk prediction tools could have the potential to alleviate pressure on cancer clinics, and are expected to have increased utility in the wake of heightened pressures resulting from the COVID-19 pandemic. Further research is required to validate these findings with real world evidence; evaluate the broader clinical and economic impact of the test; and to determine outcomes and risks for patients deemed to be low-risk on the PinPoint test and therefore not initially referred.