Systematic review of health economic evaluations published in Lebanon: summary of current practice, a critical appraisal, and recommendations for future studies.

INTRODUCTION

Health technology assessment is emerging in Lebanon, with an increased interest in health economic evaluations (EEs). Despite the importance of the methodological quality of EEs, no study has examined this issue in Lebanon.

OBJECTIVE

As only methodologically robust health EE can meaningfully inform decision making, this study systematically reviews and critically appraises published full EEs in Lebanon, formulating recommendations to strengthen the quality and consistency of future evaluations within the Lebanese context.

METHODS

We searched for full model- and trial-based EEs and cost-minimization analyses (CMAs) on NHSEED, Medline, EMBASE, and CINAHL without language or time restrictions. We followed PRISMA guidelines, narratively synthesized the characteristics, methods, and results of studies, and critically appraised them using CHEC for trial-based evaluations and CMA and CHEC-Extended for model-based evaluations.

RESULTS

Eight studies, published 2012-2025, were included: five model-based, two trial-based, and one CMA. Assessed technologies included screening/vaccination programs, diagnostic tools, nutrition education, e-mental health interventions, and early versus delayed treatment of hepatitis C. Methodological inconsistencies pertained mostly to discounting rates and willingness-to-pay thresholds. Suboptimal quality pertained mainly to model-based evaluations conducted by Lebanese researchers. Common pitfalls included the perspective being unclear; the identification, measurement, and valuation of costs and outcomes; model validation and calibration; sensitivity analyses; and discounting. The trial-based and CMA met more than 80 percent of the criteria.

CONCLUSION

We identified a limited number of published full EEs in Lebanon and highlighted their major shortcomings. Future work should scale up high-quality EEs in Lebanon, particularly modeling studies, to inform resource allocation.