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Related Experiment Video

Updated: May 27, 2026

Micro-scale Engineering for Cell Biology
04:42

Micro-scale Engineering for Cell Biology

Published on: October 1, 2007

Introduction.

C Daniel Mullins1, Robert J Sanchez

  • 1Pharmaceutical Health Services Research Department, University of Maryland School of Pharmacy, 220 Arch St, 12th Floor, Baltimore, MD 21201, USA. dmullins@rx.umaryland.edu

Journal of Managed Care Pharmacy : JMCP
|November 15, 2011
PubMed
Summary
This summary is machine-generated.

This study outlines best practices for comparative effectiveness research (CER) using real-world data (RWD). It addresses data infrastructure, statistical challenges, patient-reported outcomes, and payer involvement for robust CER.

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Last Updated: May 27, 2026

Micro-scale Engineering for Cell Biology
04:42

Micro-scale Engineering for Cell Biology

Published on: October 1, 2007

Area of Science:

  • Health Services Research
  • Biostatistics
  • Health Economics

Background:

  • The Patient Protection and Affordable Care Act spurred significant interest in comparative effectiveness research (CER).
  • This work focuses on best practices for conducting and reporting CER utilizing real-world data (RWD).

Discussion:

  • Addresses data and infrastructure needs for CER with RWD.
  • Identifies statistical challenges in nonrandomized studies and proposes solutions.
  • Highlights the value of patient-reported outcomes (PROs) and incorporating observational data into randomized controlled trials.
  • Emphasizes the importance of including payers in industry-sponsored CER.

Key Insights:

  • Suggests best practices for CER using RWD, covering study design, data management, and analysis.
  • Discusses infrastructural requirements, including data standards, quality assurance, and privacy.
  • Explores statistical methodologies for nonrandomized data and the integration of PROs.
  • Recommends collaborative approaches involving payers for comprehensive CER.

Outlook:

  • Further development of methods is needed for answering complex CER questions.
  • Continued refinement of RWD utilization and analytical techniques will enhance CER.
  • Integration of diverse data sources and stakeholder perspectives will advance patient-centered outcomes research.