Healthcare reform: it is getting personal

Area of Science:

• Healthcare innovation
• Medical informatics
• Systems biology

Background:

• Healthcare reform necessitates cost reduction and improved care delivery.
• Personalized medicine offers a pathway to new, patient-centered care models.
• Existing care models often lack coordination and continuous patient engagement.

Purpose of the Study:

• To outline the role of personalized medicine in transforming healthcare delivery.
• To highlight the integration of 'big science' omics and systems biology in defining disease networks.
• To emphasize the potential of electronic health records and deep analytics in personalized care.

Main Methods:

• Applying systems biology approaches to understand disease networks.
• Utilizing 'big science' omics data (genomics, proteomics, etc.).
• Integrating electronic health records with deep analytics for genotype-phenotype correlation.

Main Results:

• Identification of optimal care models through clinical effectiveness research.
• Reduction of care variation in patient populations.
• Generation of detailed phenotypic and genotypic data for personalized treatment strategies.

Conclusions:

• Personalized medicine, supported by omics and big data analytics, is crucial for future healthcare.
• Coordinated, team-based care with the patient at the center is a key outcome.
• Overcoming technical, economic, and societal hurdles is vital for successful implementation.