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Finding the perfect data governance environment is an elusive target. It’s important to govern to the least extent necessary in order to achieve the greatest common good. With the three data governance cultures, authoritarian, tribal, and democratic, the latter is best for a balanced, productive governance strategy.
The Triple Aim of data governance is: 1) ensuring data quality, 2) building data literacy, and 3) maximizing data exploitation for the organization’s benefit. The overall strategy should be guided by these three principles under the guidance of the data governance committee.
Data governance committees need to be sponsored at the executive board and leadership level, with supporting roles defined for data stewards, data architects, database and systems administrators, and data analysts. Data governance committees need to avoid the most common failure modes: wandering, technical overkill, political infighting, and bureaucratic red tape.
Healthcare organizations that are undergoing analytics adoption will also go through six phases of data governance including: 1) establishing the tone for becoming a data-driven organization, 2) providing access to data, 3) establishing data stewards, 4) establishing a data quality program, 5) exploiting data for the benefit of the organization, 6) the strategic acquisition of data to benefit the organization.
As U.S. healthcare moves into its next stage of evolution, the organizations that will survive and thrive will be those who most effectively acquire, analyze, and utilize their data to its fullest extent. Such is the mission of data governance.
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