Medical device companies
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 analytics 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 .
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.
Development of medical insurance products
We provide comprehensive support to clients on private medical insurance, including concept planning, market studies, future projections, development of assumed rates, pricing calculations, development of filing materials, and negotiations with administrative agencies.
Planning new healthcare business strategies
We broadly assist companies trying to launch new healthcare businesses, including brainstorming, feasibility studies, proof of concept, and development of business plans.
Predicting healthcare demands supporting regional initiatives
We support decision making regarding healthcare policies, such as those for regional healthcare initiatives, through the development of various health economics and assessment methodologies/quantitative evidence. This includes the development of healthcare demands in line with the actual situation in the region and optimization of healthcare resource allocations.
Assessment of data health plans
Using predictive models, we assess healthcare business return on investment and cost-effectiveness.
Improving hospital management
Using Milliman Hospital Performance Index (HPI), we calculate cash flows of each disease group and assist in shortening the length of hospitalization.
Support of decision making through modeling simulations
We will develop data-based models and reflect causal structures to make simulations for each option to assist 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.
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?
Assessment of Data Health Plans
- 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.
- Example of Analysis Utilizing Real World Data: Medical Cost Reduction by Advising Untreated-Hypertension Patients to Visit Doctors.
Improvement of Hospitals Management
- Application of Bayesian Network Model to Hospital Risk Management.
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.
- 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.
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