B524--Sole Source Procurement - FY24 BAM Causal Modeling
Closed Special Notice Posted
- Solicitation number
- 36C24524Q0429
- Agency
- Veterans Integrated Service Network 5 Veterans Health Administration, Department of Veterans Affairs
- Responses due
- Set-aside
- No set-aside
Opportunity facts
- NAICS code
- 541715 Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
- Points of contact
-
- Robert O'Keefe Jr. robert.okeefejr@va.gov (410) 642-2411
Notice details come from SAM.gov. Updated .
About this opportunity
The Department of Veterans Affairs (VA) has issued a Special Notice announcing a sole source procurement for the computation of Best Approximating Models (BAM) estimates of causal associations between the presence of health professions trainees and clinical workload produced in VA teaching care settings. This data is necessary to support the VA's Office of Academic Affiliations in computing health professions trainees' contribution to workload, which is required to determine the VA's performance in its education mission.
The sole source contractor identified is Professor Steven Henley of Martingale Research Corporation, who is certified as the sole expert with the necessary data, analytic skills, experience, and software to efficiently specify, estimate, and assess the statistical performance of four models within the limited 6-month timeframe and budget. Solicitation No. 36C24524Q0429 will be issued as a firm-fixed-price contract with a 12-month period of performance. The government anticipates the solicitation response and Independent Cost Estimate will justify fair and reasonable pricing, and is requesting that any additional information or a copy of the solicitation be obtained by contacting Robert O'Keefe Jr.
Notice text
Special Notice
Special Notice
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Special Notice
Special Notice
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This intent to sole source announcement is posted in accordance with FAR 5.2Â - Synopses of Proposed Contract Actions.
Background
Compute Best Approximating Models (BAM) estimates of causal associations between the presence of health professions trainees and clinical workload produced in VA teaching care settings. Such associations are necessary for Office of Academic Affiliations (OAA) to compute health professions trainees contribution to workload required to compute academic performance metrics needed to determine VA s performance in its education mission.
Unique Qualifications
Professor Steven Henley of Martingale Research Corporation is the only entity: (1) with the data and analytic skills and experience, as evidenced by a substantial peer reviewed scientific publication record, in applying causal modeling in health professions education and (2) has developed and tested software to compute the 12-step Best Approximating Models technology as evidenced by being a National Institute of Health s Small Business Innovation Research program awardee, who can efficiently within the limited budget amount and within the six-month time frame specify, estimate, and assess the statistical performance of four models needed to estimate physician residents/fellows contributed outpatient care workload by program specialty from de-identified VA CDW files.
Office of Academic Affiliations certifies that Professor Steven Henley of Martingale Research Corporation is the sole source expert for computing Best Approximating Modeling in Health Professional Education.
Award information -
Solicitation No. 36C24524Q0429 will be presented to the contractor in accordance with the sole source authority at FAR 6.302-1 as a firm-fixed-price contract. The Government anticipates the solicitation response and Independent Cost Estimate to be comparable with the follow-on contract to justify fair and reasonable pricing. The period of performance shall be for one base year following date of award. Not to exceed 12 months.
If anyone requests additional information or would like to obtain a copy of the solicitation, please contact: Robert O Keefe Jr. Robert.Okeefejr@va.gov
Attachments
| File | Type | Posted |
|---|---|---|
| 36C24524Q0429.docx | DOCX document |
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