Veterans Like Mine_Cognitive Support for Therapeutic Decision Making

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DESCRIPTION (provided by applicant): This project will support the commitment of the VA to improve the care of Veterans via the priority area of health informatics. We propose to develop and implement a novel cognitive support and population-analytic system, called Veterans Like Mine (VLMine), to aid clinicians in providing care to Veterans. The clinical focus of this project is on therapeutic management in infectious diseases in order to maximize synergy with our other CREATE projects, leverage our extensive work validating national microbiology data, and capitalize on the depth of our research team in clinical infectious diseases. Physicians accrue questions about patient care every two to three outpatient encounters, yet more than half of these questions remain unanswered. Currently available resources such as practice guidelines from national associations, PubMed and UpToDate among others are often not adequately detailed or specific enough to provide guidance on individual patient problems. VLMine is planned to serve as an expansive information resource and clinical decision support system that is adaptable to new problems and applicable in any clinical domain. Its anticipated use is in situations that trigger concerns or questions on the part of the clinician because they are unfamiliar, complex, or uncertain. The research aims of this proposal are: (1) Retrieve and analyze population data relevant to therapeutic decisionsat the individual patient level; (2) Execute and display case-matched population inquiries of Veterans Like Mine (VLMine) and (3) Conduct a demonstration study of VLMine for infectious disease clinicians. We also propose an exploratory aim: Extend VLMine to strengthen bridge between experience and evidence. These aims will achieve the following objectives: retrieve data about other patients similar to the individual patient at hand present information to clinicians to facilitate management of diagnostic uncertainty, assessment of treatment options, and prediction of outcomes; provide an interface to promote information foraging, sense-making, and analytic reasoning and provide guidance about therapeutic management by addressing knowledge and experience gaps only partially filled by other information resources. This project will build on the informatics methods that the PI, co-investigators and research team have developed under current VA HSR&D funding and used across multiple research projects to extract information on individual patients and large cohorts of Veterans across the VA. The project will use VA Informatics and Computing Infrastructure (VINCI) as a platform to access national VA data from the Central Data Warehouse (CDW) including administrative data, microbiology results, pharmacy data and clinical text notes. Our partners include Office of Informatics and Analytics, Corporate Data Warehouse, Patient Care Services, the Healthcare Transformation HI2 initiative, and VINCI; they strongly back the development of case-matched population inquiries proposed in this project. This is an opportune time for VA to advance applications of Big Data. VLMine will constitute a new kind of informatics resource, a type that does not currently exist. VLMine will provide VA clinicians access to information which draws upon the collective experience of other clinicians. Processing data from all facilities, it will generate summaries of treatments and outcomes relevant to individual patient care. As both an analytic framework and user environment, VLMine has the potential to transform how clinicians process information and acquire new knowledge.