Incorporating adherence in a health-economic evaluation is challenging. A novel conceptual framework was developed that captures the multi-dimensional aspect of adherence in a health-economic model, by considering the case of pain medication in chronic non-malignant pain management. A one-year micro-simulation model was built. Realistic dosing profiles (combining dose-taking and dose-timing information) were obtained from electronically compiled dosing histories gathered in the Aardex/Pharmionic database. Probability and timing of dosing depended on time of intake during the day, day of the week, whether or not a previous dosage was taken and number of days on treatment. The effect of dosages taken on pain was modelled via a Pharmacokinetic‑Pharmacodynamic (PK‑PD) model. The PK model translated dosages taken into drug concentration levels. Drug concentration levels influenced the amount of pain a patient experienced, quantified by the PD model. Quality of life (QoL) values were obtained by assigning a utility value to the pain intensity a patient experienced. Dosages taken by the patient contributed to medication costs. Work productivity losses due to pain exacerbations, based on a pain survey, were included. The model simulated 1,000 unique patients to generate stable results, comparing realistic dosing profiles with an optimal dosing profile for a four times daily (QID) regimen. The realistic QID regimen had 14% lower average drug concentration levels and more than 3.5 fold higher standard deviation in concentration levels than the optimal regimen. Due to lower average concentration levels and higher fluctuation, this translated into patients experiencing 37% higher average pain intensity, an 8% decrease in QoL, and total additional costs of ~$1277 annually. This study provided a conceptual framework to model the health-economic impact of dosing variations based on actual dosing information in a realistic and intuitive way. This novel concept can also be applied to other disease areas to assess pharmaco-economic outcomes.