Medical Informatics Decision Assistance and Support (MIDAS)
Navy SBIR 2015.1 - Topic N151-069
ONR - Ms. Lore-Anne Ponirakis - [email protected]
Opens: January 15, 2015 - Closes: February 25, 2015 6:00am ET

N151-069 TITLE: Medical Informatics Decision Assistance and Support (MIDAS)

TECHNOLOGY AREAS: Information Systems, Biomedical, Human Systems

ACQUISITION PROGRAM: Defense Health Program (DHP) or Marine Corps Systems Command

OBJECTIVE: Develop and demonstrate a modeling and simulation-based technology, capable of running on a handheld device, which provides an unambiguous interpretation of health status, pre- and/or post- injury, to medical information consumers within and outside military medical channels.

DESCRIPTION: The continued conflict in Afghanistan and the aftermath of Iraq, combined with emerging challenges across multiple continents, has led to increased demands for medical treatment, both on the battlefield and across the whole continuum of care to the warfighter. These drivers have, in turn, led to greater demands on the medical community to assimilate increasing amounts of information across a range of patient care levels, across a spectrum of caregivers, and at a variety of locations. This explosion of information, and in the number of individuals who participate in generating and using this information, carries with it a greater risk for misinterpretation, miscoding and mishandling. To avoid these risks, there is a critical need to optimize the acquisition, storage, retrieval, and use of healthcare- related information for each patient in order to ensure consistent and timely care [1]. The increasingly large data sets that represent an individual patient�s health status, coupled with the growing number of practitioners who may be assisting in the treatment, require decision support tools that support rapid and accurate pattern classification and hypothesis testing. As well, more effective ways of storing and retrieving patient histories are needed to ensure effective diagnosis and treatment. Modeling and simulation technologies provide the basis for aggregating, analyzing, representing, and making forecasts from large quantities of healthcare data, making them accessible in multiple ways to the many individuals supporting a patient�s care [2].

Handheld devices such as cell phones, smart phones, and personal data assistants (PDAs) provide an effective source for collecting, analyzing, and widely disseminating healthcare information, due in large part to their significantly expanded computational processing capability [3]. The infrastructure for developing software applications that can exploit these advances is also rapidly maturing; the FDA estimates over 500 million individuals will be using a healthcare app by 2015 [4]. Moreover, the types of information collectable by current mobile devices have expanded to include: high resolution pictures; video; text; geographic location; and, in most cases, text-based annotations. Combined, these developments should enable current mobile devices to perform complex analyses based on diverse, and often times incomplete, data sets enabling improved healthcare access, availability, and effectiveness for caregivers.

This topic is requesting development of Medical Informatics Decision Assistance and Support (MIDAS) technologies which, by merging advances in computer science, information technology, and information science, will provide:
� Data acquisition tools that capture and combine all relevant healthcare information (e.g., images, paper documents, proteomic/genomic data, etc.) into a common repository to allow access via searches and queries
� Visualization and analysis tools that allow users to integrate and interact with the data to generate and test new diagnoses and treatment methodologies
� Applications to detect novel patterns, predict adverse events and conditions, and to optimize treatment plans
� Platform independence to allow distribution, portability, and interoperability between different systems
� Data warehousing, archiving, and retrieval to support continuum of care and electronic health record data exchange

The output from MIDAS technologies should enable medical practitioners across the healthcare treatment continuum to better understand the medical status of a patient; to easily include treatment and diagnosis approaches while better understanding proximate and distal risk factors; and to develop effective courses of action.

PHASE I: Required Phase I deliverables will include determining technical feasibility for handheld applications that can provide simple, easy-to-use interfaces for aggregating, analyzing, representing, and making forecasts from large quantities of healthcare data that are input and used by multiple medical practitioners for use in the operational setting. Develop an initial concept design and model key elements as well as a detailed outline of success criteria. A final report will be generated including system performance metrics and plans for Phase II, if awarded. Ensuring an �open design� to allow integration with other Military Health System�s information systems will be considered a critical performance metric. Phase II plans should include key component technological milestones and plans for at least one operational test and evaluation. Phase I should also include the processing and submission of all required human subjects use protocols should these be required. Due to the long review times involved, human subject research is strongly discouraged during Phase I.

PHASE II: Required Phase II deliverables will include the construction, demonstration and validation of a prototype MIDAS system based on results from Phase I. All appropriate engineering testing will be performed along with a critical design review to finalize the design. Additional deliverables include: 1) a working prototype of the sensor, 2) drawings and specification for its construction, and 3) test data on its performance collected in one or more simulated operational settings, in accordance with the demo success criteria developed in Phase I.

PHASE III: Provide support in transitioning the technology for Marine Corps use. In accordance with the Phase III development plan, the company will extend the scope use to a wider range of platforms that are included within the Marine Corps Trusted Handheld program. The small business will provide support for test and validation and qualify the system for Marine Corps use. The small business will transition a package to the Marine Corps that includes user training package � e.g. user manual, training materials.

PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: This technology will have broad application in commercial as well as military settings. It will provide military medical practitioners across the healthcare treatment continuum with tools to better understand the medical status of a patient, in order to easily include treatment and diagnosis approaches while better understanding proximate and distal risk factors, and to develop effective courses of action which will significantly improve their performance and increase the rates of survivability for medical casualties. Commercially, this technology should allow for similar types of improvements in emergency rooms and trauma centers.

REFERENCES:
1. Haux, Reinhold (2010). "Medical informatics: Past, present, future". International Journal of Medical Informatics 79: 599�610.

2. Anderson, J. G. (2002). "A Focus on Simulation in Medical Informatics." Journal of the American Medical Information Association 9(5): 554�556 (see all articles in this special issue).

3. Uti, N. V., Fox, R. (2010). Testing the Computational Capabilities of Mobile Device Processors: Some Interesting Benchmark Results. Computer and Information Science, ACIS International Conference on, pp. 477-481, 2010 IEEE/ACIS 9th International Conference on Computer and Information Science.

4. U.S. Food and Drug Administration. (2013). Keeping Up with Progress in Mobile Medical Apps. Retrieved from http://www.fda.gov/ForConsumers/ConsumerUpdates/ucm368634.htm/ 15 Aug 2014.

5. Anhøj J., Møldrup C. (2004). Feasibility of collecting diary data from asthma patients through mobile phones and SMS (short message service): response rate analysis and focus group evaluation from a pilot study. J Med Internet Res 6(4):e42.

KEYWORDS: Mobile Device; Applications; Medical Informatics; Data Collection; Forecasting; Military Health System; Medical Readiness

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