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Data liquidity in health information systems
1Clinical Research Directorate/CMRP, SAIC-Frederick, Inc, NCI-Frederick, MD, USA. paul.courtney@nih.gov
Cancer Journal (Sudbury, Mass.)
|July 30, 2011
Summary
This study defines data liquidity in health information technology, aiming to ensure the right data reaches the right person at the right time. It identifies key system properties and metrics for assessing data liquidity in healthcare.
Area of Science:
- Health Information Technology
- Data Management
- Healthcare Quality Improvement
Background:
- The Institute of Medicine's "Crossing the Quality Chasm" (2001) and the National Committee on Vital and Health Statistics' "Information for Health" (2001) reports highlighted the need for improved health information systems.
- These reports underscored the goal of delivering the right data to the right person at the right time, a concept now recognized as data liquidity.
- Despite its recognized importance in health information technology, a clear characterization of data liquidity and its contributing system properties is lacking.
Purpose of the Study:
- To explore and define the concept of data liquidity within health information technology.
- To identify specific properties of health information systems and their components that influence data liquidity.
- To propose assessable metrics for quantifying data liquidity to ground the concept in measurable terms.
Main Methods:
- Review of recent research and work related to health information systems and data management.
- Analysis of system properties and component characteristics relevant to data flow and accessibility.
- Exploration of potential metrics for evaluating data liquidity.
Main Results:
- Identification of key system properties that contribute to or detract from data liquidity.
- Proposal of a framework for understanding and assessing data liquidity in health information technology.
- Highlighting the need for measurable indicators to operationalize the concept of data liquidity.
Conclusions:
- Data liquidity is a critical, yet not fully defined, property of health information technology systems.
- Understanding system and component properties is essential for improving data liquidity.
- Developing quantifiable metrics will enable better assessment and enhancement of data liquidity in healthcare.
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