OBJECTIVES: The diffusion of innovative drugs in clinical practice is often characterized by non-adoption or slow adoption, failing to produce expected clinical and economic gains on the regional or national levels. The research aims to examine the impact of institutional factors, price of the drug, and characteristics of prescribers on the speed of innovative drugs‘ adoption by doctors.

METHODS: A comparative analysis and empirical research were conducted. A unique dataset, compiled from the records of Lithuania's national health authorities and the National Registry Center on prescriptions and prescribers in 2019-2021 was used for the research. Out of 100 newly registered in 2018-2019 biological and chemical drugs, ten drugs were selected for the analysis: abemaciclib, apalutamide, durvalumab (oncology); erenumab and fremanezumab (migraine); ertugliflozin (type II diabetes), benralizumab (asthma), emicizumab (hereditary genetic disease); ocrelizumab (multiple sclerosis), upadacitinib (inflammatory arthritis). Prescriptions' data was matched with records for doctors' characteristics and morbidity indicators.

RESULTS: Data revealed that the drugs’ inclusion into the health insurance compensation scheme presented major barriers for their adoption irrespective of the therapeutic area. Significant levels of prescriptions and prescribers' clustering in major cities and major healthcare institutions was observed for the selected drugs. Also, data confirmed that the more expensive the drug, the slower its adoption. Doctor's gender was found irrelevant. Doctors in their fifties were faster than younger doctors and specialty doctors were relatively faster than doctors with other licenses in prescribing innovative drugs.

CONCLUSIONS: Institutional factors and price play a critical role in defining the speed of innovation diffusion in healthcare. Also, data suggests potential geographically defined inequality of Lithuanian doctors’ knowledge about innovative drugs or their confidence to prescribe them. A further expert survey would help to cover qualitative factors not covered by statistical data and suggest potential policy instruments to improve innovation diffusion and patients' access to innovative treatments.