Notice of Intent University of Maryland Data Specialist

Notice of Intent -University of Maryland, Baltimore

NAICS Code:  541990- All Other Professional, Scientific and Technical Services ($19.5 Average Annual Receipts)

Product Service Code:  AN12 Health Research & Development Services; Health Care Services; Applied Research

Place of Performance: Bethesda, MD 20892

POTS:  25-008693

Description:

This is a notice of intent, not a request for a quotation. A solicitation document will not be issued, and quotations will not be requested.

The National Institutes of Health, Office of Purchasing and Contracts on behalf of the Critical Care Medicine Department (CCMD), Clinical Epidemiology Section (CES) intends to award a firm fixed priced award for a one-year base period of performance to University of Maryland in Baltimore (UMB) School of Medicine on a sole source basis to provide one data specialist to perform data programming and analytical skills.

Proposed Contractor:

University of Maryland School of Medicine

655 West Baltimore Street

Baltimore, Maryland 21201

The Critical Care Medicine Department (CCMD), Clinical Epidemiology Section (CES) requires expeditious analysis of data curated from two data sources, Epic Cosmos, and the University of Maryland Medical Systems (UMMS) Clinical Data Repository.  The University of Maryland in Baltimore has the necessary analytical and computational resources which cannot be acquired elsewhere.  These services are not currently being performed.

The University of Maryland in Baltimore will provide an experienced data specialist  responsible for the informatics needs related to the project “Machine learning to optimize antibiotic selection in hospital-onset sepsis”.  This work has been selected as one of the eleven projects funded as part of the 2024 NIH Director’s Challenge Awards.   This work will require a comprehensive understanding of two data sources, Epic Cosmos, and the University of Maryland Medical Systems Clinical Data Repository, both of which this candidate has worked with previously.  The University of Maryland in Baltimore is the only academic facility in the area which has access and familiarity of these data sources which are necessary for the proposed project.

The specific responsibilities of the data specialist will include building algorithms to identify clinical syndromes in large datasets, curation of large datasets and generation of deidentified syndromic inpatient registries from large healthcare datasets, evaluating the effectiveness of implementation, and the modifying of approach based on feedback and outcomes.

This acquisition is being conducted using policies unique to the Federal Acquisition Regulation (FAR) Part 13 – Simplified Acquisition Procedures, Subpart 13.106-1(b)(1), For purchases not exceeding the simplified acquisition threshold (SAT), contracting officers may solicit from one source if the contracting officer determines that the circumstance of the contract action deem only one source reasonably available.  Contracts awarded using FAR Part 13-Simplified Acquisition Procedures are exempt from the requirements of FAR Part 6-Competition Requirements.

Interested Parties:

Interested parties capable of providing the same or similar products or services described in this notice may submit a capability statement outlining their capability to perform the described work.  Capability Statements must be received within the time set forth in this synopsis to be considered by the Government. The determination to compete this proposed contract based on responses to this notice is solely within the discretion of the Government. Information received will normally be considered solely for the purpose of determining whether to conduct a competitive procurement.

Comments:

Comments to this announcement, referencing this posting number, may be submitted to the CC, Office of Purchasing and Contracts, prior to the closing date specified in this announcement, electronically to the attention of Shasheshe Goolsby, Lead Contract Specialist, shasheshe.goolsby@nih.gov by the due date September 27, 2025, and time marked in this notice.