High-cost gene therapies strain the sustainability of healthcare budgets. Despite the potential long-term savings promised by certain gene therapies, realizing these savings faces challenges due to uncertainties regarding the treatment’s durability and a lesser-discussed factor: the true potential for cost offset. Our study aims to assess the cost-offset uncertainty for US Medicaid regarding recently approved gene therapies in hemophilia A and B.

The analysis used 2018 to 2022 Colorado Department of Health Care Policy & Financing data to determine direct costs of standard of care (factor replacement therapy or emicizumab). Cost-simulation models over five- and ten-year time horizons estimated Colorado Medicaid costs if patients switched to gene therapy (valoctocogene roxaparvovec or etranacogene dezaparvovec) versus maintaining standard of care. Patients were included if aged 18 and over with ICD-10-CM codes D66 (hemophilia A) and D67 (hemophilia B). In the base case, severe hemophilia A was defined as requiring greater than or equal to six yearly factor VIII or emicizumab claims and moderate/severe hemophilia B requiring greater than or equal to four factor IX replacement therapy claims annually.

Annual standard-of-care costs were USD426,000 (SD USD353,000) for hemophilia A and USD546,000 (SD USD542,000) for hemophilia B. Valoctocogene roxaparvovec (hemophilia A) had incremental costs of USD880,000 at five years and −USD481,000 at 10 years. Sensitivity analysis revealed a 23 percent chance of break-even within five years and 48 percent within 10 years. Etranacogene dezaparvovec (hemophilia B) showed incremental costs of USD429,000 at five years and −USD2,490,000 at 10 years. Simulation indicated a 32 percent chance of break-even within five years and 59 percent within 10 years. Varying eligibility (≥4 to ≥15 standard-of-care claims) notably affected break-even; for example, valoctocogene roxaparvovec: 40 percent to 77 percent chance of break-even in 10 years.

Our study highlights significant cost variation in the standard of care of patients eligible for gene therapies, adding to the uncertainty surrounding cost estimation and highlighting the importance of addressing this factor in risk-sharing agreements. The impact of varying eligibility criteria on cost offsets emphasizes the importance of carefully defining eligibility when using real-world data in the context of health technology assessment.

Lack of evidence regarding safety and effectiveness at market entry is driving the need to consider adopting a lifecycle approach to evaluating medical devices, but it is unclear what lifecycle evaluation means. This research sought to explore the tacit meanings of “lifecycle” and “lifecycle evaluation” as embodied within evaluation models/frameworks used for medical devices.

Drawing on qualitative evidence synthesis methods and using an inductive approach, novel methods were developed to identify, appraise, analyze, and synthesize lifecycle evaluation models used for medical devices. Data was extracted (including purpose; audience; characterization; outputs; timing; and type of model) from key texts for coding, categorization, and comparison, exploring embodied meaning across four broad perspectives.

Fifty-two models were included in the synthesis. They demonstrated significant heterogeneity of meaning, form, scope, timing, and purpose. The “lifecycle” may represent a single stage, a series of stages, a cycle of innovation, or a system. “Lifecycle evaluation” focuses on the overarching goal of the stakeholder group, and may use a single or repeated evaluation to inform decision-making regarding the adoption of health technologies (Healthcare), resource allocation (Policymaking), investment in new product development or marketing (Trade and Industry), or market regulation (Regulation). The adoption of a lifecycle approach by regulators has resulted in the deferral of evidence generation to the post-market phase.

Using a “lifecycle evaluation” approach to inform reimbursement decision-making must not be allowed to further jeopardize evidence generation and patient safety by accepting inadequate evidence of safety and effectiveness for reimbursement decisions.

Patients with amputation need a safe and comfortable connection with the prothesis. Traditional sockets may lead to skin tearing, pain, and limitation of movement. Osseointegrated protheses connected to residual bone may have a positive impact on patients’ quality of life. Our research question: Are there economic and organizational benefits from the introduction of a direct skeletal attachment (DSA) procedure, as well as clinical benefits?

Firstly, a systematic literature review was carried out on PubMed and Scopus, and the Critical Appraisal Skills Programme (CASP) tool was applied to assess the evidence’s quality. A health technology assessment (HTA) evaluation was conducted (EUnetHTA, 2016), adopting the perspective of a public hospital in Italy, comparing two scenarios—traditional and innovative—related to traditional protheses and the DSA approach. Seven experts (orthopedic surgery, physical medicine, and rehabilitation and physiotherapy) were involved for the administration of a qualitative questionnaire. For the economic evaluation, a cost-effectiveness analysis and budget impact analysis were defined. Finally, a multiple-criteria decision analysis was performed.

The literature search yielded 314 citations published until December 2022: eight were eligible for analysis. Three were the system analysed: ‘OPRA’, ‘ISP’ and ‘OPL’. The efficacy of the systems is linked to a better distribution of bone stress: an increase in bone mineral density was recorded near the implants (respectively 28%, 27%, and 18% – after 60 months). The safety of DSA depends on the design and integrity of the connection between tissues and implant. The impact on the budget is an increase of 27 percent in costs for each patient treated. Concerning the social and ethical implications, DSA results in the preferable approach (1.48 vs 0.34), as it can limit social costs (0.29 vs −0.29).

The comparative evaluation was carried out using a scoring method: the main advantages related to innovative prostheses are based on effectiveness and safety, as well as social impact and organizational impact, especially due to the ability of the prostheses to reduce the risk of adverse events and long rehabilitation, with important clinical benefits and organizational savings for the hospital management.

Telemedicine may improve healthcare access and efficiency if it demands less clinician time than usual care. We sought to describe the degree to which telemedicine trials assess the effect of telemedicine on clinicians’ time and to discuss how including the time needed to treat (TNT) in health technology assessment (HTA) could affect the design of telemedicine services and studies.

We conducted a scoping review by searching clinicaltrials.gov using the search term “telemedicine” and limiting results to randomized trials or observational studies registered between January 2012 and October 2023. We then reviewed trial registration data to determine if any of the outcomes assessed in the trials measured effect on clinicians’ time.

We found 113 studies and of these 78 studies of telemedicine met the inclusion criteria and were included. Nine (12 percent) of the 78 studies had some measure of clinician time as a primary outcome, and 11 (14 percent) as a secondary outcome. Four studies compared direct measures of TNT with telemedicine versus usual care, but no statistically significant difference was found. Of the sixteen studies including indirect measures of clinician time, thirteen found no significant effects, two found a statistically significant reduction, and one found a statistically significant increase.

This scoping review found that clinician time is not commonly measured in studies of telemedicine interventions. Attention to telemedicine’s TNT in clinical studies and HTAs of telemedicine in practice may bring attention to the organization of clinical workflows and increase the value of telemedicine.

Healthcare regionalization is the movement of responsibility of health care towards a regional body. It has been introduced in many countries and exists in many forms across high-, middle- and low-income countries. Supporters of regionalization purport that a more actively managed system, with better coordination and integration, could lead to improved quality and patient-centered care. However, evidence for this is unclear.

Systematic searches combining terms for regionalization and patient-centered care in MEDLINE identified 5,765 titles for review. Three levels of screening were conducted by two independent reviewers: title only, abstract and title, and full-paper review. Rapid-realist synthesis methodology was used to gather a deeper understanding of the relationship between healthcare regionalization and patient-centered care, seeking to identify potential mechanisms and the context in which these operate. We also sought to determine whether novel methodologies such as this can be used by health technology assessment (HTA) bodies in an efficient manner that produces results directly applicable to decision-makers.

Studies from high-income countries, including Canada, New Zealand, Australia, and Italy, were included. The realist synthesis identified mechanisms by which whole healthcare-system regionalization can help or hinder the rollout of patient-centered care. Mechanisms were classified in relation to specific dimensions of patient-centered care including access and “patient as person.” Facilitators to the use of rapid-realist review in health policy include similarity of screening, searching, and extraction to traditional systematic review. Barriers include the scope of the literature considered relevant, length of time to familiarize with the method, and presentation of the findings in an accessible way for policymakers.

This is the first realist synthesis of the relationship between whole healthcare-system regionalization and patient-centered care. Regionalization may help or hinder achievement of patient-centered care. Policymakers should note barriers to, and facilitators of, patient-centered care in the context of large-scale health system reform. Rapid-realist review has applications for HTA, particularly in the exploration of non-standard interventions.

The purpose of this study is to evaluate the validity of the standard approach in expert judgment for evaluating precision medicines, in which experts are required to estimate outcomes as if they did not have access to diagnostic information, whereas in fact, they do.

Fourteen clinicians participated in an expert judgment task to estimate the cost and medical outcomes of the use of exome sequencing in pediatric patients with intractable epilepsy in Thailand. Experts were randomly assigned to either an “unblind” or “blind” group; the former was provided with the exome sequencing results for each patient case prior to the judgment task, whereas the latter was not provided with the exome sequencing results. Both groups were asked to estimate the outcomes for the counterfactual scenario, in which patients had not been tested by exome sequencing.

Our study did not show significant results, possibly due to the small sample size of both participants and case studies.

A comparison of the unblind and blind approach did not show conclusive evidence that there is a difference in outcomes. However, until further evidence suggests otherwise, we recommend the blind approach as preferable when using expert judgment to evaluate precision medicines because this approach is more representative of the counterfactual scenario than the unblind approach.

This study examined the application, feasibility, and validity of supervised learning models for text classification in appraisals for rare disease treatments (RDTs) in relation to uncertainty, and analyzed differences between appraisals based on the classification results.

We analyzed appraisals for RDTs (n = 94) published by the National Institute for Health and Care Excellence (NICE) between January 2011 and May 2023. We used Naïve Bayes, Lasso, and Support Vector Machine models in a binary text classification task (classifying paragraphs as either referencing uncertainty in the evidence base or not). To illustrate the results, we tested hypotheses in relation to the appraisal guidance, advanced therapy medicinal product (ATMP) status, disease area, and age group.

The best performing (Lasso) model achieved 83.6 percent classification accuracy (sensitivity = 74.4 percent, specificity = 92.6 percent). Paragraphs classified as referencing uncertainty were significantly more likely to arise in highly specialized technology (HST) appraisals compared to appraisals from the technology appraisal (TA) guidance (adjusted odds ratio = 1.44, 95 percent CI 1.09, 1.90, p = 0.004). There was no significant association between paragraphs classified as referencing uncertainty and appraisals for ATMPs, non-oncology RDTs, and RDTs indicated for children only or adults and children. These results were robust to the threshold value used for classifying paragraphs but were sensitive to the choice of classification model.

Using supervised learning models for text classification in NICE appraisals for RDTs is feasible, but the results of downstream analyses may be sensitive to the choice of classification model.

In the era of cardiovascular-kidney-metabolic syndrome, thorough evaluation of medicines with multiple treatment effects/indications demands a multifaceted modeling philosophy, despite the requirement of health technology assessment (HTA) models to focus on one disease. Using Cardiff, a model previously built for type 2 diabetes (T2D), we illustrate the changes needed to capture contemporary, holistic, patient-centered decision-making, and argue that HTA bodies should revise their approach.

The upgraded model enables therapy selection and escalation determined by HbA1c thresholds, cardiovascular risk (QRISK3), comorbidities (established cardiovascular or chronic kidney disease), and weight (body mass index ≥35 kg/m2). Risk factor trajectories were updated by incorporating UKPDS-90 equations and other relevant data sources. Clinical outcomes were predicted using new risk equations incorporating cardiovascular outcomes trial data whenever possible. The updated model was applied to assess quality-adjusted life years (QALYs) and lifetime costs in newly diagnosed T2D patients in the UK, modeled via a conventional glycemic-centric approach versus a multifactorial treatment algorithm. Extrapolation to the national level utilized estimates of annual incidence.

The updated treatment algorithm captured and quantified the impact of nuanced comorbidity management called for in guidelines. In a cohort of newly diagnosed T2D patients, 81 percent initiated an SGLT2 inhibitor within five years, predominantly due to increasing cardiovascular risk, versus zero percent when escalation was dictated by HbA1c alone. Broad, early use of SGLT2 inhibitors resulted in an additional 0.73 predicted QALYs and GBP10,757 (USD13,600) in predicted lifetime cost savings per patient versus a “traditional” approach. Cost savings were primarily due to avoided renal events; extrapolation to the national level predicted cost savings to the payer of GBP2.8 billion (USD3.5 billion), which traditional models cannot capture.

The modernized Cardiff model incorporates multifactorial prescribing guidelines and contemporary evidence around cardio-renal protection and is more adept at modeling costs and outcomes of multidimensional antidiabetic treatments; traditional glucose-centric modeling methods may introduce bias. Economic modeling and HTA processes must adapt to follow the complexities of modern disease management and remain relevant as healthcare systems address the cardiovascular-kidney-metabolic syndrome epidemic.

Multiple myeloma (MM) is a challenging hematological malignancy, primarily treated with autologous stem cell transplantation (ASCT). However, relapse or refractoriness is inevitable, necessitating alternative treatments. This study evaluates ciltacabtagene autoleucel (Carvykti®), a novel therapy, against a second ASCT, using an efficiency frontier approach to assess its therapeutic value and cost-effectiveness.

We conducted a comparative analysis using data from CARTITUDE-1 clinical trials and a Brazilian real-world cohort (2002 to 2015) of MM patients treated under SUS (Brazilian Healthcare System). We estimated survival curves and area under the curve (AUC) for both interventions over 48 months and projected the curves for a 10-year horizon using parametric distributions. Cost-effectiveness was assessed by calculating the incremental cost per month of survival. Efficiency frontier methodology was employed to determine a proportional price for ciltacabtagene autoleucel, based on the cost and median survival benefits compared to the second ASCT.

Ciltacabtagene autoleucel demonstrated a 7.27 percent increase in AUC for overall survival over 48 months compared to the second ASCT. The incremental cost was BRL54,219.15 (USD11,133.30) per month of survival. Over a 10-year horizon, the estimated cost for ciltacabtagene autoleucel was significantly higher than that for the second ASCT. Using the efficiency frontier approach, the cost of ciltacabtagene autoleucel should not exceed BRL228,226.42 (USD46,863.74), considering its survival benefit and cost of production.

Ciltacabtagene autoleucel demonstrates significant anti-tumor activity in relapsed/refractory MM, with a notable survival advantage. Efficiency frontier analysis suggests a maximum justified cost, providing a framework for pricing decisions. This study highlights the importance of balancing innovation with cost-effectiveness in healthcare decision-making.

Qualitative methods allow in-depth exploration of patient experiences and can provide context for healthcare decision making. Frameworks for patient-based evidence in health technology assessment (HTA) are expanding; yet, how extensively qualitative methods are currently used is unclear. This review characterized the extent and quality of qualitative data submitted to National Institute for Health and Care Excellence (NICE) and Canadian Agency for Drugs and Technologies in Health (CADTH) for HTA.

NICE and CADTH submissions from September 2019 to August 2021 were reviewed. Submission characteristics and features of patient-based evidence included within submissions were extracted. The quality of qualitative reporting was assessed using the CASP checklist.

Patient-based evidence was included in 83/107 NICE and 119/124 CADTH submissions. A small proportion described qualitative data collection (NICE=14; CADTH=24) and analysis (NICE=6; CADTH=9) methods. One-to-one interviews were the most common data collection method, and thematic analysis was exclusively used. Thirty-three percent of NICE submissions scored >7 yes responses on CASP, versus 78 percent of CADTH submissions.

Although patient-based evidence was common in the submissions reviewed, only 14/107 NICE and 24/124 CADTH submissions involved formal qualitative data collection. Use of formal analysis methods was even rarer and reporting tended to be brief. At present, there is little guidance about qualitative evidence most likely to be informative and therefore to potentially impact decision making. Ensuring, however, that qualitative data are collected and analyzed in a systematic, rigorous way will maximize their usefulness and ensure that patient voices are clearly heard.

Increasingly in Ireland, there are specific criteria attached to reimbursement approval for new medicines. Health technology assessment (HTA) identifies where uncertainty is greatest in relation to clinical and cost-effectiveness evidence and budget impact estimates; our health technology management (HTM) approach uses these outputs from HTA to design protocols to manage these uncertainties in the post-reimbursement phase.

A bespoke managed access protocol (MAP) is developed for each medicine reimbursed under this approach, informed by uncertainties highlighted in the HTA, directions from the decision-maker, and relevant particulars arising from commercial negotiations. Individual patient reimbursement applications are submitted via an online application system linked directly to the national pharmacy claims system. Pharmacists review the applications and approve reimbursement support where the patient meets the reimbursement criteria. The process is adaptive, allowing expansion of the criteria to include previously excluded patient cohorts, and the addition of new indications. It can also work across differing reimbursement arrangements (hospital/primary care).

The MAP for liraglutide for weight management confines reimbursement to patients with a body mass index greater than or equal to 35 kg/m², prediabetes, and high risk for cardiovascular disease. Phase I reimbursement support lasts for six months; patients not attaining greater than or equal to five percent weight loss are deemed non-responders as per the HTA, and reimbursement support is discontinued. The MAP for dupilumab confined reimbursement support to adults with refractory moderate-to-severe atopic dermatitis, where cost-effectiveness was plausible in the HTA. The MAP for calcitonin-gene-related-peptides monoclonal antibodies confines reimbursement support to patients with chronic migraine, refractory to at least three prophylactic treatments, where cost-effectiveness was plausible in the HTA.

Across these MAPs, over 3,000 patients accessed novel treatments for chronic illnesses in September 2023. HTM provides an effective mechanism to facilitate access to high-cost medicines for targeted patient groups, while providing increased oversight and budgetary certainty. Key to acceptance is utilization of HTA outputs to implement evidence-based HTM measures targeting specific uncertainties as highlighted in the HTA report.

This study aims to gain insight into each attribute as presented in the value of implantable medical devices, quantify attributes’ strength and their relative importance, and identify the determinants of stakeholders’ preferences.

A mixed-methods design was used to identify attributes and levels reflecting stakeholders’ preference toward the value of implantable medical devices. This design combined literature reviewing, expert’s consultation, one-on-one interactions with stakeholders, and a pilot testing. Based on the design, six attributes and their levels were settled. Among 144 hypothetical profiles, 30 optimal choice sets were developed, and healthcare professionals (decision-makers, health technology assessment experts, hospital administrators, medical doctors) and patients as stakeholders in China were surveyed. A total of 134 respondents participated in the survey. Results were analyzed by mixed logit model and conditional logit model.

The results of the mixed logit model showed that all the six attributes had a significant impact on respondents’ choices on implantable medical devices. Respondents were willing to pay the highest for medical devices that provided improvements in clinical safety, followed by increased clinical effectiveness, technology for treating severe diseases, improved implement capacity, and innovative technology (without substitutes).

The findings of DCE will improve the current evaluation on the value of implantable medical devices in China and provide decision-makers with the relative importance of the criteria in pricing and reimbursement decision-making of implantable medical devices.

In the last decade, artificial intelligence (AI) has been increasingly applied in health technology assessment (HTA) to accelerate evidence synthesis, optimize resources allocation, and guarantee timely delivery of trustworthy technologies in health. The aim of the present scoping review is to map AI models applied in HTA, and technical characteristics of AI-based automation and semi-automation applied in HTA.

A search strategy containing core expressions “AI” and “HTA” and correlated terms was conducted in nine specialized databases (health and informatics) in February 2022. Inclusion criteria were publications testing AI models applied in HTA. Study selection was performed by independent pairs, with consensus meetings. No filters were applied. Data on year and country of publication, HTA phase, subsets of AI (e.g., machine learning [ML], neural networks), type of algorithm (e.g., support vector machine [SVM], K-nearest neighbors), and performance scale were extracted. Data were analyzed as descriptive frequency statistics. Used metrics will be presented narratively.

Sixty-one publications were included. The first study identified was published in 2006, and since then the number of publications has been consistently growing, with 11 publications in the year 2021. Canada, USA, and the UK concentrate 72 percent of publications (44 in 61) equally distributed. The most common HTA phase was the evidence synthesis, with 59 studies (96%). The main task performed was study screening/selection (66.6%). The majority of ML models (80.9%) contained two learning nodes or fewer, and applied SVM and decision-tree-based algorithms. Inter-rater agreement, accuracy, and 95 percent recall were the most common scales observed.

Although recent developments in AI applied to HTA show increasing potentiality, studies are concentrated in the study selection phase of evidence synthesis. Many areas need further development, such as horizon scanning and policymaking processes. Additionally, studies reporting time gain and economic gain outcomes are scarce and should be considered for the development of future studies in the field.

In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test – the PinPoint test – to triage and prioritize patients urgently referred with suspected urological cancers.

Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained.

Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain.

Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.

Artificial intelligence (AI) technologies are becoming more widespread in daily life, including in health and care settings. AI is being developed for use in many areas, including diagnostics, treatment planning, and patient monitoring. There are new challenges and additional considerations when performing a health technology assessment (HTA) for AI use in healthcare.

Health Technology Wales has developed additional guidance and a checklist of considerations for researchers to use when undertaking an HTA on AI. These documents were created as a result of involvement in discussions with healthcare services around AI; attendance at meetings and training sessions with government, healthcare, and academic institutions; and observations from undertaking our first HTAs investigating AI technologies.

We identified seven main areas to consider: (i) the AI model being used and its training datasets; (ii) clarity on where in the clinical pathway the AI sits and whether this is appropriate for the local healthcare service; (iii) clear identification of the target patient population and whether there are gaps in the evidence base for subgroups; (iv) who uses the AI and the training required; (v) possible barriers and inequities in usage, particularly if the AI is patient facing; (vi) ongoing monitoring of the AI model; and (vii) data security and usability.

HTA assessment of AI presents new challenges for HTA bodies. Additional outcomes for assessment (including user acceptability) may be required, and an awareness of background information that allows for contextualization of the technology and clear indication of its usefulness in the local healthcare setting is key. The development of guidance related to AI technologies may enable rigorous evaluation.

Innovative pricing and payment schemes have been proposed to address the affordability issues raised by new health technologies or the uncertainty about their long-term safety and effectiveness. As part of the Horizon Europe project HI-PRIX, we investigated the nature, scope, and impact of these arrangements.

We undertook a PRISMA-ScR-compliant review in PubMed, Web of Science, and Scopus, from 2010 to 2023. We also searched health technology assessment (HTA) agency websites. The search strategy was structured around two blocks: “pricing/payment schemes,” and “innovativeness.” Studies illustrating pricing/payment schemes with sufficient level of details to explain their functioning were selected, also through a nested evaluation of an artificial-intelligence-powered tool for systematic reviews. These schemes were classified according to several criteria, such as their purpose, nature, governance, product category, data collection needs, foreseen distribution of risk, and implementation challenges. The study protocol was published in PROSPERO (CRD42023444824).

“Innovative payment and pricing schemes” were defined as arrangements that go beyond price per unit of the technology, simple price/volume agreements, or expenditure caps. Seventy innovative schemes were identified, of which 25 were only illustrated theoretically, while 45 have been implemented in practice. So far, 170 real cases of implementation have been identified. The schemes target pharmaceuticals, vaccines, and/or medical devices. Whether designed to incorporate unique features of a given technology, or to address specific challenges, the schemes can be classified by different value drivers, including type of technology, therapeutic indication, or timeline of the agreement.

Available pricing and payment schemes have the potential to offer a comprehensive toolkit to policymakers facing reimbursement and access decisions, highlighting that it is not the scheme per se that is innovative, rather its application/use in a given context or for a given challenge. The catalog populates the Pay for Innovation Observatory, a publicly available repository.

In response to the Omicron surge in early 2022, the HTA Philippines evaluated the acceptability of Filipinos in using self-administered antigen tests (SAAgTs) as part of COVID-19 HTAs in the Philippines.

Scoping review from literature databases was initially conducted to identify preset codes in the use of SAAgT. Preset codes were used to establish the questions for focus group discussions (FGDs). Semi-structured questionnaires were created through Delphi technique. FGDs with four stakeholder groups (i.e., nine healthcare workers [HCWs], seven representatives of at-risk groups, six economic frontliners, and seven representatives of micro–small–medium-sized enterprises) were conducted.

Discomfort in being a target of stigma and being prescribed an “illness identity” when suspected or confirmed COVID-19-positive, along with lack of confidence to perform self-test, caused hesitancy in self-testing among participants. The need for subsidies for test kits from the government or employers was emphasized to increase its accessibility. Having a designated access point and reporting system for SAAgT was highlighted to avoid nepotism (padrino system attributed to debt of gratitude), inequitable distribution, and lapses in reporting. A participatory approach to education was perceived as crucial to reduce any misconceptions associated with the use of SAAgT.

All FGD groups expressed favorable reviews on the implementation of SAAgT because it can potentially reduce the burden of health facility-administered tests. These findings were considered by the HTA Council in the recommendation of SAAgT as part of the overarching national strategies for the diagnosis and screening of COVID-19.