Early economic evaluation of an intervention to improve uptake of the NHS England Diabetes Prevention Programme.

BACKGROUND: Despite reported increases in referral numbers, a large proportion of those with prediabetes still decline participation in the NHS England Diabetes Prevention Programme (NDPP). The aim of this study was to explore whether investment in interventions to improve uptake of the programme has the potential to be cost-effective. METHODS: An early cost-utility analysis was conducted using a Markov model parameterized based on secondary data sources. We explored different uptake scenarios and the impact that this had on the maximum allowable intervention price based on cost-effectiveness at the UK NICE willingness to pay threshold of £20,000 (US$ 25,913). Value of information analyses were conducted to explore the potential value of further research to resolve uncertainty at each uptake level. RESULTS: As uptake levels increase, the maximum allowable intervention price and overall expected value of removing decision uncertainty increases. For 5 percentage and 50 percentage points increase in uptake levels, the maximum allowable intervention price is £41.86 (US$ 54.23) and £418.59 (US$ 542.34) per person, and the overall expected value of removing decision uncertainty are £361,818,839 (US$ 468,786,625) and £1,468,712,316 (US$ 1,902,921,063) respectively. CONCLUSION: There is headroom for investment in interventions that improve uptake to the NDPP, thereby allowing the programme itself to be delivered in a manner that remains cost-effective.

Modelling of hypothetical SARS-CoV-2 point of care tests for routine testing in residential care homes: rapid cost-effectiveness analysis.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19), which at the time of writing (January 2021) was responsible for more than 2.25 million deaths worldwide and over 100,000 deaths in the UK. SARS-CoV-2 appears to be highly transmissible and could rapidly spread in residential care homes. OBJECTIVE: The work undertaken aimed to estimate the clinical effectiveness and cost-effectiveness of viral detection point-of-care tests for detecting SARS-CoV-2 compared with laboratory-based tests in the setting of a hypothetical care home facility for elderly residents. PERSPECTIVE/SETTING: The perspective was that of the NHS in 2020. The setting was a hypothetical care home facility for elderly residents. Care homes with en suite rooms and with shared facilities were modelled separately. METHODS: A discrete event simulation model was constructed to model individual residents and simulate the spread of SARS-CoV-2 once it had entered the residential care facility. The numbers of COVID-19-related deaths and critical cases were recorded in addition to the number of days spent in isolation. Thirteen strategies involving different hypothetical SARS-CoV-2 tests were modelled. Recently published desirable and acceptable target product profiles for SARS-CoV-2 point-of-care tests and for hospital-based SARS-CoV-2 tests were modelled. Scenario analyses modelled early release from isolation based on receipt of a negative SARS-CoV-2 test result and the impact of vaccination. Incremental analyses were undertaken using both incremental cost-effectiveness ratios and net monetary benefits. RESULTS: Cost-effectiveness results depended on the proportion of residential care facilities penetrated by SARS-CoV-2. SARS-CoV-2 point-of-care tests with desirable target product profiles appear to have high net monetary benefit values. In contrast, SARS-CoV-2 point-of-care tests with acceptable target product profiles had low net monetary benefit values because of unnecessary isolations. The benefit of allowing early release from isolation depended on whether or not the facility had en suite rooms. The greater the assumed efficacy of vaccination, the lower the net monetary benefit values associated with SARS-CoV-2 point-of-care tests, when assuming that a vaccine lowers the risk of contracting SARS-CoV-2. LIMITATIONS: There is considerable uncertainty in the values for key parameters within the model, although calibration was undertaken in an attempt to mitigate this. Some degree of Monte Carlo sampling error persists because of the timelines of the project. The example care home simulated will also not match those of decision-makers deciding on the clinical effectiveness and cost-effectiveness of introducing SARS-CoV-2 point-of-care tests. Given these limitations, the results should be taken as indicative rather than definitive, particularly the cost-effectiveness results when the relative cost per SARS-CoV-2 point-of-care test is uncertain. CONCLUSIONS: SARS-CoV-2 point-of-care tests have considerable potential for benefit for use in residential care facilities, but whether or not this materialises depends on the diagnostic accuracy and costs of forthcoming SARS-CoV-2 point-of-care tests. FUTURE WORK: More accurate results would be obtained when there is more certainty on the diagnostic accuracy of and the reduction in time to test result associated with SARS-CoV-2 point-of-care tests when used in the context of residential care facilities, the proportion of care home penetrated by SARS-CoV-2 and the levels of immunity once vaccination is administered. These parameters are currently uncertain. FUNDING: This report was commissioned by the National Institute for Health Research (NIHR) Evidence Synthesis programme as project number 132154. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 39. See the NIHR Journals Library website for further project information.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19). SARS-CoV-2 is highly infectious, and this can cause problems in care homes, where the virus can spread quickly. Laboratory-based tests can determine whether or not someone has SARS-CoV-2, but these tests are not perfect and can take a long time to provide a result. Point-of-care tests that can be performed quickly in the care home to detect SARS-CoV-2 are being developed and they may have much shorter times to get a result than laboratory-based tests, although with worse accuracy. The benefit of quicker tests is that decisions to put residents into or release them from isolation can be made sooner, reducing the risk of spreading SARS-CoV-2 and reducing time in isolation. The disadvantage of reduced accuracy is that wrong decisions could be made, resulting in either unnecessary isolation or increased spread of SARS-CoV-2. A computer model was built to explore the impact of using SARS-CoV-2 point-of-care tests for residents of care homes. The model estimated the number of SARS-CoV-2 infections, deaths due to COVID-19 and days in isolation. Strategies were run using different values, including the time to get a test result back, the accuracy of tests, the proportion of care homes where there is a case of SARS-CoV-2, whether residents were isolated individually or in groups and how well vaccines work. The results of the model indicated that point-of-care tests could be good if there was a large decrease in the time to get a test result back, if accuracy was high and if vaccination protection was moderate. However, the accuracy and speed of future point-of-care tests is uncertain. When newer SARS-CoV-2 tests are available, the model will allow an estimate of the clinical effectiveness and cost-effectiveness of the tests to be made.

Integrating Early Economic Evaluation into Target Product Profile development for medical tests: advantages and potential applications.

Target Product Profiles (TPPs) outline the characteristics that new health technologies require to address an unmet clinical need. To date, published TPPs for medical tests have focused on infectious diseases, mostly in the context of low- and middle-income countries. Recently, there have been calls for a broader use of TPPs as a mechanism to ensure that diagnostic innovation is aligned with clinical needs, yet the methodology underpinning TPP development remains suboptimal. Here, we propose that early economic evaluation (EEE) should be integrated within the TPP methodology to create a more rigorous framework for the development of "fit-for-purpose" tests. We discuss the potential benefits that EEE could bring to the core activities underpinning TPP development-scoping, drafting, consensus building, and updating-and argue that using EEE to help inform TPPs provides a more objective, evidence-based, and transparent approach to defining test specifications.

Modelling of hypothetical SARS-CoV-2 point-of-care tests on admission to hospital from A&E: rapid cost-effectiveness analysis.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019. At the time of writing (October 2020), the number of cases of COVID-19 had been approaching 38 million and more than 1 million deaths were attributable to it. SARS-CoV-2 appears to be highly transmissible and could rapidly spread in hospital wards. OBJECTIVE: The work undertaken aimed to estimate the clinical effectiveness and cost-effectiveness of viral detection point-of-care tests for detecting SARS-CoV-2 compared with laboratory-based tests. A further objective was to assess occupancy levels in hospital areas, such as waiting bays, before allocation to an appropriate bay. PERSPECTIVE/SETTING: The perspective was that of the UK NHS in 2020. The setting was a hypothetical hospital with an accident and emergency department. METHODS: An individual patient model was constructed that simulated the spread of disease and mortality within the hospital and recorded occupancy levels. Thirty-two strategies involving different hypothetical SARS-CoV-2 tests were modelled. Recently published desirable and acceptable target product profiles for SARS-CoV-2 point-of-care tests were modelled. Incremental analyses were undertaken using both incremental cost-effectiveness ratios and net monetary benefits, and key patient outcomes, such as death and intensive care unit care, caused directly by COVID-19 were recorded. RESULTS: A SARS-CoV-2 point-of-care test with a desirable target product profile appears to have a relatively small number of infections, a low occupancy level within the waiting bays, and a high net monetary benefit. However, if hospital laboratory testing can produce results in 6 hours, then the benefits of point-of-care tests may be reduced. The acceptable target product profiles performed less well and had lower net monetary benefits than both a laboratory-based test with a 24-hour turnaround time and strategies using data from currently available SARS-CoV-2 point-of-care tests. The desirable and acceptable point-of-care test target product profiles had lower requirement for patients to be in waiting bays before being allocated to an appropriate bay than laboratory-based tests, which may be of high importance in some hospitals. Tests that appeared more cost-effective also had better patient outcomes. LIMITATIONS: There is considerable uncertainty in the values for key parameters within the model, although calibration was undertaken in an attempt to mitigate this. The example hospital simulated will also not match those of decision-makers deciding on the clinical effectiveness and cost-effectiveness of introducing SARS-CoV-2 point-of-care tests. Given these limitations, the results should be taken as indicative rather than definitive, particularly cost-effectiveness results when the relative cost per SARS-CoV-2 point-of-care test is uncertain. CONCLUSIONS: Should a SARS-CoV-2 point-of-care test with a desirable target product profile become available, this appears promising, particularly when the reduction on the requirements for waiting bays before allocation to a SARS-CoV-2-infected bay, or a non-SARS-CoV-2-infected bay, is considered. The results produced should be informative to decision-makers who can identify the results most pertinent to their specific circumstances. FUTURE WORK: More accurate results could be obtained when there is more certainty on the diagnostic accuracy of, and the reduction in time to test result associated with, SARS-CoV-2 point-of-care tests, and on the impact of these tests on occupancy of waiting bays and isolation bays. These parameters are currently uncertain. FUNDING: This report was commissioned by the National Institute for Health Research (NIHR) Evidence Synthesis programme as project number 132154. This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 21. See the NIHR Journals Library website for further project information.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19). SARS-CoV-2 is highly infectious, and this can cause problems in hospitals, where the virus can spread quickly. Laboratory-based tests can determine whether or not a patient has SARS-CoV-2, but these tests are not perfect and can require a considerable time to provide a result. Point-of-care tests to detect SARS-CoV-2 are being developed that may have much shorter times to a test result, although these are likely to be less accurate than laboratory-based tests. The benefit of quicker tests is that a decision to put a patient in a SARS-CoV-2-infected bay or in a non-SARS-CoV-2-infected bay can be made sooner, limiting contact between patients with SARS-CoV-2 and patients without SARS-CoV-2 and reducing the risk of infection transmission. The disadvantage of reduced accuracy is that some patients may be allocated to the wrong bay, increasing the risk of SARS-CoV-2 infection. A computer model was built to explore the impact of using SARS-CoV-2 point-of-care tests for people admitted to hospital. This model estimated the number of infections and deaths due to COVID-19, the costs of testing, and the number of people waiting to be put in an appropriate bay. Strategies were run using different values, including the time to get a test result, the accuracy of tests and whether or not staff who do not have symptoms should be tested. The results of the model indicated that point-of-care tests could be good if there was a large reduction in the time to get a test result and if accuracy was high. However, it is not certain whether or not such tests will become available. When newer SARS-CoV-2 tests are available, the model will allow an estimate of the clinical effectiveness and cost-effectiveness of the test to be made.

The future for diagnostic tests of acute kidney injury in critical care: evidence synthesis, care pathway analysis and research prioritisation.

BACKGROUND: Acute kidney injury (AKI) is highly prevalent in hospital inpatient populations, leading to significant mortality and morbidity, reduced quality of life and high short- and long-term health-care costs for the NHS. New diagnostic tests may offer an earlier diagnosis or improved care, but evidence of benefit to patients and of value to the NHS is required before national adoption. OBJECTIVES: To evaluate the potential for AKI in vitro diagnostic tests to enhance the NHS care of patients admitted to the intensive care unit (ICU) and identify an efficient supporting research strategy. DATA SOURCES: We searched ClinicalTrials.gov, The Cochrane Library databases, Embase, Health Management Information Consortium, International Clinical Trials Registry Platform, MEDLINE, metaRegister of Current Controlled Trials, PubMed and Web of Science databases from their inception dates until September 2014 (review 1), November 2015 (review 2) and July 2015 (economic model). Details of databases used for each review and coverage dates are listed in the main report. REVIEW METHODS: The AKI-Diagnostics project included horizon scanning, systematic reviewing, meta-analysis of sensitivity and specificity, appraisal of analytical validity, care pathway analysis, model-based lifetime economic evaluation from a UK NHS perspective and value of information (VOI) analysis. RESULTS: The horizon-scanning search identified 152 potential tests and biomarkers. Three tests, Nephrocheck® (Astute Medical, Inc., San Diego, CA, USA), NGAL and cystatin C, were subjected to detailed review. The meta-analysis was limited by variable reporting standards, study quality and heterogeneity, but sensitivity was between 0.54 and 0.92 and specificity was between 0.49 and 0.95 depending on the test. A bespoke critical appraisal framework demonstrated that analytical validity was also poorly reported in many instances. In the economic model the incremental cost-effectiveness ratios ranged from £11,476 to £19,324 per quality-adjusted life-year (QALY), with a probability of cost-effectiveness between 48% and 54% when tests were compared with current standard care. LIMITATIONS: The major limitation in the evidence on tests was the heterogeneity between studies in the definitions of AKI and the timing of testing. CONCLUSIONS: Diagnostic tests for AKI in the ICU offer the potential to improve patient care and add value to the NHS, but cost-effectiveness remains highly uncertain. Further research should focus on the mechanisms by which a new test might change current care processes in the ICU and the subsequent cost and QALY implications. The VOI analysis suggested that further observational research to better define the prevalence of AKI developing in the ICU would be worthwhile. A formal randomised controlled trial of biomarker use linked to a standardised AKI care pathway is necessary to provide definitive evidence on whether or not adoption of tests by the NHS would be of value. STUDY REGISTRATION: The systematic review within this study is registered as PROSPERO CRD42014013919. FUNDING: The National Institute for Health Research Health Technology Assessment programme.