Abstract
Background/Aims Starting in January 2014, millions of currently uninsured Californians will be able to purchase health insurance on the California Health Insurance Exchange (HIE). For planning purposes, it is important to estimate disease burden and demands for services in uninsured populations. The Archimedes Model is a trial-validated, clinically detailed simulation model of human physiology, disease progression, and healthcare delivery. The Archimedes Model synthesizes evidence from hundreds of data sources to create virtual patients that are representative of the US population, in terms of demographic distribution, disease progression, clinical outcomes, patient and provider behaviors; office visits and hospital admissions; tests and treatments; care delivery protocols; compliance; and costs. Kaiser Permanente and Archimedes collaborated to develop a capability based on the Archimedes Model to forecast disease burden and healthcare utilization in uninsured populations for each of the 18 California Health Insurance Exchange pricing regions.
Methods We used data from 20 diverse California and US surveys and databases as inputs into the Archimedes Model to create realistic individuals that closely match the uninsured populations in each pricing region, with respect to demographics, socioeconomic status, and medical conditions. Within the Archimedes Model, the relationships between biomarkers, medication adherence and usage, disease progression, clinical outcomes, care processes and healthcare utilizations are well-established and carefully validated against many independent datasets. We use the Archimedes Model to combine datasets with overlapping information and to fill in the missing information for uninsured Californians, then forecast the clinical outcomes and health utilizations in the next 10 years for this population as well as the benefits and costs of different prevention and disease management strategies.
Results We created 19 datasets that are representative of the pricing regions on the Health Insurance Exchange and cover a wide range of outcomes and conditions, including diabetes, cardiovascular diseases, cancers, COPD, asthma, childbirths and mental health.
Conclusions Health plans and insurers can use the information provided by the datasets for resource allocation and capacity planning. Local officials will able to use these datasets measure today’s health of their communities and forecast tomorrow’s health.
