Health+Data+Stewardship+(HIT+Stewardship)


 * Term: **Health Data Stewardship (HIT Stewardship)

For comparison between normal StandardStewardship and HIT Stewardship: "**Data stewardship** is the management and oversight of an organization's data assets to help provide business users with high-quality data that is easily accessible in a consistent manner."
 * Description: **


 * Health Data Stewardship** is the responsibility to "ensure the knowledgeable and appropriate use of data derived from individuals' personal health information. These uses include (but are not limited to) data collection, viewing, storage, exchange, aggregation, and analysis."

One of the key tenants of HIT Stewardship is accountability, which generally becomes associated with a named "data steward" who has the assigned role of ensuring that health data is used appropriately. Health data stewardship also supports using health information to improve society's understanding of health while still maintaining the privacy of each person.

Adoption and applications of HIT Stewardship have gained momentum due to the large increase in electronic health data due to EHR/EMR adoption, as well as other Meaningful Use standards. Other reasons for the increased applications of HIT Stewardship include: better recognition of advantages of healthcare information, the "big data boom", other technology adoptions, and an increased awareness of mistakes caused by misused health data.
 * Applications: **

Who should apply and practice health data stewardship? Anyone and everyone who collects, stores, views, exchanges, analyzes, aggregates, or by any means uses electronic health information and data. Specifically, these primarily consist of: healthcare organizations, clinicians, payers, information exchanges, vendors, data mining companies, researchers, caregivers, and more.

Application Practices: 1) Transparency about data use 2) Clear purpose for use of data 3) Allow individuals to access their own data 4) Security and privacy safeguards 5) De-identification (anonymous data) 6) Data Quality & Integrity 7) Limits on use 8) Limits on disclosure 9) Oversight
 * 10) Accountability & Enforcement Remedies**

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Big Data Business Intelligence Data Governance
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