The Data COUNTS™ (Collect Data Once, Use Numerous Times)

Description This is a Request for Information (RFI). This is NOT a solicitation for proposals, proposal abstracts, or questions. The purpose of this RFI is to obtain knowledge and information for project planning purposes. The Government does not intend to award a contract on the basis of the RFI or otherwise pay for the information requested. Responses will be treated as information only and not as a proposal. The NIH seeks information on technologies and capabilities to further the objectives of the Data COUNTS program. The Data COUNTS (Collect Data Once, Use Numerous Times) effort is built on collaboration between patients and advocates, government, health systems, technology companies, and the private sector. The Data COUNTS program enables the NIH s Real-World Data initiative and will provide high quality, standardized data that is provenanced and available through approved access to the research community. The contemplated capability will initially perform requested and approved extraction from Healthcare Partner EMR systems and should be modular and extensible to other authorized source systems such as laboratory information systems, pharmacy information systems, picture archiving and communication systems, vendor-neutral archives, and specialty systems. The Data COUNTS program requires that source data, and source provenance metadata, permissions, and source ontology fields will be preserved without modification or loss. This program will not create or standardize ontology mappings. Technical Requirements of Interest: Address availability and technologies that enable the following features: A durable, Healthcare Partner Leave Behind Technology capability that remains at the Healthcare Partner site after contract completion and can be operated by trained staff without ongoing involvement. The technology should be available and free for use by Healthcare Partners while in the Data COUNTS program. Describe any installation and configuration documentation, operational runbooks, site-controlled credential-transfer procedures, documented dependencies, major-release update procedures, and training that enable independent site operations. Deep query for approved extraction from Healthcare Partner electronic medical records (EMR) systems and other authorized source systems. Capture timestamps and provenance for all data at extraction and maintain an immutable provenance chain. The architecture consumes a machine-readable, version-controlled, authorized, and approved Data Request Specification defining cohort logic, requested source systems, data domains and fields, date range, full or incremental extraction mode, refresh cadence, and applicable authorization and permission rules. Describe how the solution validates data availability against the specification, identifies unavailable or ambiguous fields, avoids silent substitutions, associates the request identifier with each batch and output, and supports reproducible reruns when source data have not changed. An initial automated data quality check validating completeness, uniqueness, data types, date sequencing, and records-per-patient. All anomalies must be reported before any permitted corrections are applied. Sourced data will not be modified De-identification per 45 CFR 164.514(b): remove all 18 direct identifiers; document a consistent de-identification pathway; and apply a per-patient date-shifting specification that preserves temporal order. Privacy Preserving Record Linkage (PPRL) tokenization capabilities for cross-site linkage using an approved, on-premises within the institutional trust boundary PPRL platform that generates consistent, irreversible patient tokens. Describe validation and Healthcare Partner approval before the first live transmission. Describe how token consistency is achieved across independently deployed, site-local PPRL instances, without introducing a shared trust boundary outside the Healthcare Partner site. Describe how the solution preserves a…