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AcuStaf Nurse Labor Mgmt System

Awarded
GS35F0408XFederal

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The Department of Veterans Affairs Network Contracting Office 6 awarded contract GS35F0408X 36C24626F0054 to AcuStaf Development Corp on January 9, 2026, for the implementation of the AcuStaf automated electronic labor management system at the Durham VA Medical Center in North Carolina. The contract, valued at 83,776.00 dollars, falls under NAICS code 541519. The system is designed to automate nurse scheduling and staffing processes across VISN 6, utilizing objective and variable data to support staffing assignments and match nursing competencies with patient care needs. Key deliverables of the system include automated staffing workflows, decision support tools for nurse placement, self-scheduling options for staff, and the generation of data for outcome measurements. The project is managed by Contracting Officer Byron Brown, with performance centered at the Durham VAMC. The award was processed without a specific set-aside and does not utilize Recovery Act funds.

General Info

Contract Value

$83,776

NAICS

541519 - Other Computer Related Services

Place of Performance

NC, 27705, USA

Set-Aside

NONE

Awardee

AcuStaf

Award Issued Date

Documents

1

GS35F0408X 36C24626F0054 - AcuStaf Nurse Labor Mgmt System

DOCX, Low priorityaward
Low

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PhaseAwarded
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Awarded

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Organization & Contact Information

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AgencyDepartment Of Veterans Affairs → 246-NETWORK Contracting Office 6 (36C246)
Contacts1 person available
OfficeHAMPTON, VA, 23667, USA
Office AddressHAMPTON, VA, 23667, USA
Contacts

Full Description

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The Durham VAMC requires the Acustaf automated /electronic labor management system for nurse scheduling and tracking. The Acustaf system is utilized throughout VISN 6. The system automates scheduling and staffing processes; provides decision support for staff assignments based on the objective and variable data as opposed to the best estimates; improves patient care by matching nursing competency to required needs. It allows self-scheduling options for nursing staff and data for outcome measurements.

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