| | Category | SOFT | P29 | Cloud-based Data Preparation for Medical Observational |
| | Research |
| | Abstract | The future of healthcare lies in endeavors such as precision medicine |
| | where treatment options, clinical decisions, and preventive techniques |
| | are tailored to patients based on their exact characteristics. For these |
| | advancements to be made possible, clinical data collected from the |
| | health records of patients in medical facilities must be obtained for |
| | analytics and observational research. |
| | |
| | Electronic health records (EHRs) are the optimal source of data for |
| | medical observational studies, but, unfortunately, current practices for |
| | retrieving relevant EHRs lack automation and efficiency. Clinical data |
| | mining is a complex endeavor due to the lack of standardization and |
| | structure in the natural text comprising health records. In addition, |
| | stringent patient privacy requirements at various organizational levels |
| | further complicate procedures for preparing data for observational |
| | studies. |
| | |
| | An autonomous, decentralized, privacy-enabled architecture |
| | incorporating a novel semantic similarity algorithm is created for |
| | automated EHR retrieval in this project. The semantic similarity |
| | algorithm has high values of precision and recall, indicating that clinical |
| | records relevant to an observational study’s specifications are |
| | retrieved. Furthermore, the addition and removal of data-contributing |
| | medical facilities does not impact data retrieval at other nodes. |
| | Sensitive information present in the EHRs such as a patient's social |
| | security number and name is identified and removed before retrieval |
| | via an ontology-guided approach. This project promises to reduce the |
| | time required for data preparation for observational research from |
| | months to minutes. |
| | |
| | Bibliography | P. Buitelaar, "Ontology-based Information Extraction and Integration |
| | from Heterogeneous Data Sources," International Journal of Human- |
| | Computer Studies, vol.66, no.11, pp. 759-788, 2008."Paxata Give |
| | Analysts Valuable Time Back for Analytics." Ventana Research, n.d. |