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24 Sep 2007:
Over the next five to ten years, IBM predicts that the healthcare industry will experience radical shifts brought about by the following trends and technology innovations:
SECURE SHARING OF PATIENT DATA
United States privacy legislation such as Sarbanes-Oxley is enforced to protect against the mistreatment -- intentional or unintentional -- of confidential patient data. IBM's Hippocratic Database (HDB) is a privacy-enabled database designed to support the information usage and disclosure policies of government regulations. HDB active enforcement implements cell-level information disclosure policies and pushes policy enforcement down to the database layer, protecting the privacy of information without impeding its flow. Additionally, IBM's Interoperable Health Information Infrastructure (IHII) and Eclipse Open Healthcare Framework (EOHF) securely facilitate sharing of medical information between healthcare professionals, providers and patients. Built with an open source framework, the technology creates a simple method for the server and client applications to "talk" to each other. For example, a patient can upload personal health records that his or her provider can view, or a doctor can quickly access and view a patient's lab tests, medical history and other medical records.
FULLY INFORMED DIAGNOSIS
In current clinical practice, physicians diagnose based on evidence from a single patient and their own prior experience. What if physicians could leverage the experience of their peers who have treated similar patients? What if they could exploit diagnostic patterns from similar patient statistics? Advanced AnaLytics for Information Management (AALIM), IBM's Diagnostic Decision Support for Cardiologists, is a system that analyzes multiple modalities to identify similar patient records to aid diagnostic decision support. It then aggregates their associated disease labels to form statistical summaries, and sophisticated feature extraction and search techniques help to find similar patients based on a disease-specific analysis of their heart sounds, ECGs, and echocardiogram videos. All data is made anonymous to protect patient privacy. Decision support tools such as AALIM can help physicians make more informed diagnoses in the future, thereby leading to improved quality of care for patients.
SPEEDING DRUGS TO MARKET
IBM's Business Information Services On the Network (BISON) platform will offer two applications -- Chemical Search Engine and Business Insights Workbench (BIW) -- for the Healthcare, Life Sciences and Pharmaceutical industries, designed to enhance drug research and development. These applications will enable users to sift through valuable Intellectual Property buried deep in patents using advanced analytics, reducing the time and cost associated with the creation of new therapeutic drugs and ultimately improving patient care. This technology also leverages Blue Gene, which has enabled researchers to build chemical and bio-annotators that extract biomarkers and other entities from the entire US Patent Corpus in less than five minutes. This performance capability, equivalent to approximately 310 high-end Linux servers, has opened the door to perform sophisticated text analytics on very large volumes of data consisting of millions of documents.
STEMMING THE SPREAD OF PANDEMICS
IBM's Spatiotemporal Epidemiological Modeler (STEM) will help scientists and public health officials create and use spatial and temporal models of emerging pandemics. These models could aid in understanding, and potentially limiting or even preventing, the spread of infectious diseases and pandemics. IBM recently contributed STEM code to the Eclipse open source foundation and will continue to contribute this code to enable the prevention of disease spreading. Additionally, IBM's Public Health Affinity Domain (PHAD), a standards based, interoperable infrastructure can be paired with the STEM code to enable scientists and public health officials to query clinics, hospitals, lab systems and other stakeholders for anonymous data categorized by disease. They would then be able to create and use models of infectious diseases to further pandemic response and avoidance. For example, de-identified data could be pulled from an electronic health record and submitted in a report from an emergency room to a public health organization about a specific illness. The interoperability component of this infrastructure would give access to a broader set of data in order to paint a complete picture of the health of a population with real-time information that could enable public health officials to better predict and avoid the spread of pandemics.
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