SBIR/STTR Research Award

Using advanced natural language processing to facilitate documentation of meaningful use and quality payment compliance

Award identifier 29a8f3e7bbb1d353b5c5f87f8f8208fda3a41bcde77653b172911d1d132afaaeAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$149,953

Program and phase

STTR · Phase I

Award year

2018

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Safermed, LLC
Proposal award date
2018-09-12
Contract end date
2019-05-31
UEI
RFD6L39J3TW4
Solicitation number
PA18-575
Topic code
NLM

Research abstract

PROJECT SUMMARY The Center for Medicare and Medicaid Services Quality Payment Program is designed to motivate healthcare providers to adhere to best practices in clinical healthcare and patient safetyUnfortunatelyextracting quality measures data from the clinical record is burdensome and as suchparticipation among clinical healthcare providers is suboptimalOur aim is to develop a system to facilitate automatic extraction of quality dataThis will reduce the burden of data collection and help remove the barrier to participation that keeps more providers from participating in the programThe proposed projecttitledUsing advanced natural language processing to facilitate documentation of meaningful use and quality payment complianceaims to develop novel natural language processing methods to recognize key elements from the clinical notes to enable proper documentation of meaningful use and compliance with quality paymentWe envision this to be an effective research partnership that leverages the complementary assets of SaferMDa small business unitand the University of Michigana non profit research institutionto develop and evaluate a prototype tool to extract clinical quality measures dataand increase participation in the Quality Payment Program PROJECT NARRATIVE The proposed projecttitledUsing advanced natural language processing to facilitate documentation of meaningful use and quality payment complianceaims to develop novel natural language processing methods to recognize key elements from the clinical notes to enable proper documentation of meaningful use and compliance with quality paymentThe project will develop algorithms to identify fields relevant for quality measures and develop tools to extract and analyze these data elements from large sets of radiology reportsFinallythe proposed work will initiate the extracted measures into existing quality service offerings by SaferMDSuccessful completion of this project will advance the tools available for CMS clients to achieve higher adherence and compliance to the quality payment initiatives and help public health officials and policy developers advance the meaningful use of electronic health records

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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