The Patient-Centered Outcomes Research Network Antibiotics and Childhood Growth Study: Implementing Patient Data Linkage.

The Patient-Centered Outcomes Research Network Antibiotics and Childhood Growth Study: Implementing Patient Data Linkage.

Canterberry, Melanie;Kaul, Alan F;Goel, Satyender;Lin, Pi-I Debby;Block, Jason P;Nair, Vinit P;Ma, Qianli;Carton, Thomas W;
population health management 2019
283
canterberry2019thepopulation

Abstract

PCORnet, the Patient-Centered Outcomes Research Network, is comprised of health systems and health plans that transform electronic health records (EHRs) and claims data to a common data model (CDM) to facilitate real-world clinical research. Because patients receive health care in multiple care delivery settings, linking health records across systems and health plan claims would provide a more comprehensive and accurate picture of health care for patients. The current study expanded on a PCORnet Antibiotics and Childhood Growth (ABX) study to (1) identify and implement a privacy-preserving patient linkage solution among a clinical data research network and a health plan network within the ABX Study, and (2) assess overlap in prescribed and dispensed antibiotics and additional data gained from claims among the linked patients. This manuscript describes the linkage process and resulting overlap analysis. The authors identified 549 patients from the EHR record study cohort who had claims records with the health plan. Sixty percent (n = 329) of patients had consistent antibiotic exposure data across the 2 sources, indicating antibiotic exposure (44.3%) or nonexposure (15.7%). Among total antibiotic prescribing records, 43.1% had a matched claims record for dispensing within 60 days. Among antibiotic dispense records 26.5% were not associated with a prescribing record in the linked health systems. These findings showcase the feasibility of linking health plan claims data to PCORnet CDM in a privacy-preserving manner while also demonstrating continued gaps in data that may occur. The study highlights the importance of combining multiple health data sources for comprehensive clinical research.

Citation

ID: 89978
Ref Key: canterberry2019thepopulation
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
89978
Unique Identifier:
10.1089/pop.2019.0089
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet