Health solutions
Pharmaceuticals
Pharmaceuticals
We support pharmaceutical firms and medical affairs sections in medical device companies in Japan, working to develop real-world evidence. We draft research design to advise on the selection of appropriate real-world data, draft forms for protocol/ethics committees, analyze data, and develop materials for academic conferences. We develop, identify, select, propose, and assess the most appropriate analytic methods for given research questions.
Milliman pharmaceuticals solutions
Health economics & outcome research
Through analyses of real-world data including health insurance claims, administrative information, and electronic health records, we perform research regarding actual treatment status and medical costs, and compare outcomes of different treatment types.
Health technology assessment or cost-effectiveness analyses
We perform analyses in compliance with the guidelines of the Central Social Insurance Medical Council.
Development of real-world evidence
Our consultants, especially those with the Certified Medical Publication Professional (CMPP) qualification, develop research papers on analyses of real-world data.
License assessment portfolio management of pre-marketing medicines
We assess value (risks and returns) of each individual pipeline by projecting the number of patients, shares, prices, and probability of market launch. We assess the value of the overall portfolio by evaluating values of several pipelines.
Assessment of omnichannel marketing programs
We will propose programs to more effectively launch omnichannel marketing by analyzing client behaviors of each channel including optimization of channel mix and provision of personalized value added information to enhance client engagement.
Planning new healthcare business strategies
We broadly assist companies trying to launch new healthcare businesses. This includes brainstorming, feasibility studies, proof of concept, and development of business plans.
Support of decision making through modeling simulations
We develop data-based models and reflect causal structures to them to make simulations for all options to assist in management decisions.
Research
Articles originally published by the National Center for Biotechnology Information and published by Milliman Insight.
Health Economics & Outcome Research
- Comparison of zonisamide with non-levodopa, anti-Parkinson's disease drugs in the incidence of Parkinson's disease-relevant symptoms.
- Persistence of oral antidiabetic treatment for type 2 diabetes characterized by drug class, patient characteristics and severity of renal impairment: A Japanese database analysis
Development of Real World Evidence
- Comparison of zonisamide with non-levodopa, anti-Parkinson's disease drugs in the incidence of Parkinson's disease-relevant symptoms.
- Persistence of oral antidiabetic treatment for type 2 diabetes characterized by drug class, patient characteristics and severity of renal impairment: A Japanese database analysis.
- Persistence rates and medical costs of biological therapies for psoriasis treatment in Japan: a real-world data study using a claims database.
License Assessment Portfolio Management of Pre-marketing Medicines
- Projection of share over time after launch using machine learning and RWD, and its utilization.
Planning of New Healthcare Business Strategies
- Will a proposed policy in Japan, Health Gold License, work?: Estimation of medical cost saved by medical check-ups.
- Projection of share over time after launch using machine learning and RWD, and its utilization.
- Does health business pay off as an investment?
Support of Decision Making through Modeling Simulations
- Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography.
- Medical claim cost impact of improved diabetes control for medicare and commercially insured patients with type 2 diabetes.
- Association Between Class if Antidiabetic Drug And Incidence of Myocardial Infarction In Patients with Type 2 Diabetes Melitus: A Proportional Hazard Analysis Using Deep Learning For Risk Adjustment.
- Comparison of medicines after risk adjustments for patients with type-2 diabetes in US health insurance claims data using machine learning of cardiac infarction occurrence rate.
- Development of a predictive model of hemoglobin A1C based on statistical machine learning using clinical data.
- Life insurance risks: Observations on Solvency II and the modeling of capital needs
- Test calculation of effect of promotion of early detection and early treatment of type-C hepatitis virus infection.
- Effect on medical cost reduction of recommendation of visit of doctors for hypertensive individuals who have not visited doctors.
- Effect on medical cost reduction of recommendation of visit of doctors for individuals with diabetes who have not visited doctors.
Contact us
We’re passionate about partnering with people to solve complex problems. Let’s chat about what’s going on with your business and how we can help.