| Literature DB >> 34588840 |
Hussain A Al-Omar1,2,3, Ibrahim A Aljuffali4,5, Oriol Solà-Morales6.
Abstract
OBJECTIVES: Capacity building exercises are important to increase understanding of healthcare processes by key stakeholders, and to facilitate open discussions to build consensus. This study explored the views of a multi-stakeholder group of local Saudi experts on possible value elements that could be important for health technology assessment (HTA) processes and methods regarding pharmaceutical products in Saudi Arabia ('value drivers').Entities:
Keywords: Saudi Arabia; capacity building; health technology assessment; pharmaceutical products; policy
Year: 2021 PMID: 34588840 PMCID: PMC8463512 DOI: 10.1016/j.jsps.2021.08.001
Source DB: PubMed Journal: Saudi Pharm J ISSN: 1319-0164 Impact factor: 4.330
Value driver descriptions.
| Value driver | Description |
|---|---|
| Process and outcomes | |
| Patients | Include patients in the HTA process |
| Industry | Include industry (or their representative) in the HTA process |
| Thresholds | Define explicit efficiency ICER thresholds for the acceptance of a new technology |
| Collaboration | Require collaboration between institutions rather than centralizing the work in one agency |
| Appraisal Assessment | Separation of the Appraisal and the Assessment, by two independent bodies |
| Binding | Make HTA evaluations binding for authorities |
| Evaluation criteria | |
| Efficacy | Clear definition of the marginal benefit of the technology/drug |
| Safety | Clear definition of the safety profile of the technology/drug |
| Quality of life (QoL) | Requirement to include QoL data in the submission |
| End of Life (EoL) | Considering EoL to deserve a differentiated set of evaluation criteria |
| Special Groups | Definition of specific acceptability rules for special groups |
| Rare | Define those special groups as having a rare disease |
| Ultra-Rare | Narrow the rare special group to a subset |
| Curable | Have specific criteria for those diseases that are curable |
| Communicable | Have specific criteria for those diseases that are communicable |
| Innovation | Explicitly recognize innovation as part of the potential benefit |
| Sources of data | |
| Randomized controlled trial (RCT) | Only look at submissions backed by an RCT |
| Real-world evidence (RWE) | Include real-world data (RWD) in the HTA submissions to validate the trial data |
| Epidemiology | Include epidemiological data in the submission |
| Modelling | Require modelling of the results beyond the clinical trial |
| Cost/quality-adjusted life year (QALY) | Cost/QALY (and ICER) calculations required in the submission |
| Gross domestic product (GDP)/research and development (RnD) | Assess and reward the implication of the manufacturer on the GDP and/or local RnD contribution |
EoL, end of life; GDP, gross domestic product; HTA, health technology assessment; ICER, incremental cost-effectiveness ratio; RCT, randomized controlled trial; RnD, research and development; RWE/D, real-world evidence/data; QALY, quality-adjusted life-year; QoL, quality of life.
Demographics and professional history of workshop participants.
| Male | 28/43 (65.1) |
| Female | 15/43 (34.9) |
| 25–34 | 12/42 (28.6) |
| 35–44 | 18/42 (42.9) |
| 45–54 | 11/42 (26.2) |
| ≥55 | 1/42 (2.4) |
| Pharmacist | 20/40 (50.0) |
| Economist | 9/40 (22.5) |
| Physician | 7/40 (17.5) |
| Finance | 1/40 (2.5) |
| Other | 3/40 (7.5) |
| Yes | 12/33 (36.4) |
| No | 21/33 (63.6) |
| Clinical Pharmacist | 11/39 (28.2) |
| Chair/member of pharmacy and therapeutic committees (PTCs) | 10/39 (25.6) |
| Academic professor | 9/39 (23.1) |
| Policy maker | 6/39 (15.4) |
| Key opinion leader (in a specific therapy area) | 5/39 (12.8) |
| Payer | 3/39 (7.7) |
| Regulator | 3/39 (7.7) |
| Researcher/member of research agencies | 3/39 (7.7) |
| Clinical guideline expert | 2/39 (5.1) |
| Health authority official | 2/39 (5.1) |
| Physician | 2/39 (5.1) |
| Medical insurance | 1/39 (2.6) |
| Other | 16/39 (41.0) |
| Government | 18/32 (56.3) |
| Private | 8/32 (25.0) |
| Authority | 3/32 (9.4) |
| Other | 3/32 (9.4) |
Fig. 1Results from HTA and value framework polling questions. aThis question was populated using participant responses from a previous open-ended question, ‘In your view, what is the major challenge to implementing HTA in Saudi Arabia?’ HTA, health technology assessment.
Fig. 2Value drivers that should NOT be included in an HTA process For each value driver, participants were asked to ‘opt out’ if they did not think that it should be considered as a possible value element in Saudi Arabian HTA assessments. GDP, gross domestic product; HTA, health technology assessment; QALY, quality-adjusted life year; RCT, randomized controlled trial; RnD, research and development; RWE, real-world evidence.
Fig. 3Mean acceptability and feasibility for each value driver If participants did not ‘opt out’ of a certain value driver, they were asked to score the value driver on feasibility and acceptability (1–10; low–high). Feasibility was defined as whether the relevant data were likely to be available and/or accessible to support a given value driver in the HTA process. Acceptability was a measure of whether the participant felt that the value driver would be acceptable to all stakeholder parties (in this case, acceptability of the value driver was not a personal assessment). EoL, end of life; GDP, gross domestic product; HTA, health technology assessment; QALY, quality-adjusted life year; QoL, quality of life; RCT, randomized controlled trial; RnD, research and development; RWE, real-world evidence.
Value driver acceptability and feasibility voting results.
| Patients | 26 | 7.8 (2.2) | 27 | 5.9 (2.6) |
| Industry | 18 | 7.1 (2.5) | 18 | 7.8 (2.1) |
| Thresholds | 26 | 6.1 (2.5) | 29 | 5.0 (2.6) |
| Collaboration | 26 | 7.7 (2.4) | 27 | 7.2 (2.1) |
| Appraisal Assessment | 26 | 8.1 (2.1) | 26 | 7.9 (2.1) |
| Binding | 24 | 7.5 (2.1) | 25 | 7.3 (2.3) |
| Efficacy | 32 | 9.3 (1.2) | 35 | 9.0 (1.3) |
| Safety | 33 | 9.4 (1.1) | 34 | 8.7 (1.6) |
| QoL | 30 | 7.2 (2.5) | 28 | 5.2 (2.8) |
| EoL | 22 | 6.5 (2.8) | 23 | 5.5 (2.6) |
| Special groups | 27 | 8.3 (2.0) | 28 | 7.3 (1.9) |
| Rare | 31 | 7.2 (2.6) | 32 | 6.4 (2.6) |
| Ultra-rare | 30 | 7.0 (2.9) | 31 | 5.8 (2.9) |
| Curable | 29 | 8.8 (1.5) | 30 | 7.3 (2.3) |
| Communicable | 26 | 8.6 (1.7) | 27 | 7.7 (2.0) |
| Innovation | 22 | 7.7 (2.4) | 23 | 7.0 (2.0) |
| RCTs | 27 | 8.4 (2.1) | 29 | 6.9 (2.4) |
| RWE | 21 | 8.7 (1.7) | 22 | 5.8 (2.7) |
| Epidemiology | 31 | 8.1 (1.9) | 31 | 6.3 (2.5) |
| Modelling | 24 | 7.6 (1.9) | 25 | 6.6 (2.6) |
| Cost/QALY | 27 | 7.9 (1.9) | 30 | 6.8 (2.6) |
| GDP/RnD | 13 | 7.8 (2.2) | 14 | 6.4 (2.1) |
If participants did not ‘opt out’ of a certain value driver, they were asked to score the value driver on feasibility and acceptability (1–10; low–high). Feasibility was defined as whether the relevant data were likely to be available and/or accessible to support a given value driver in the HTA process. Acceptability was a measure of whether the participant felt that the value driver would be acceptable to all stakeholder parties (in this case, acceptability of the value driver was not a personal assessment). EoL, end of life; GDP, gross domestic product; QALY, quality-adjusted life year; QoL, quality of life; RCT, randomized controlled trial; RnD, research and development; RWE, real-world evidence; SD, standard deviation.