Four Critical Phases for Effective Healthcare Data Governance

Data drives healthcare improvement and is an imperative resource for navigating a changing healthcare landscape. It allows healthcare organizations to evaluate how care is delivered and funded, how patients are engaged and educated, and how payers and providers can work together to improve value. Buthealthcare data is complex, and it can be difficult to leverage. A principle-based approach to data, through good data governance practices, can bridge the gap. Data governance allows organizations to maximize the value of their data to improve outcomes.

Defining Healthcare Data Governance

医疗保健数据治理是将数据作为战略资产进行管理的原则。它为数据通过人员、流程和技术的编排来支持组织优先级铺平了道路。通过加强决策制定，数据治理帮助组织领导人改善临床、运营和财务结果。重要的是，数据治理是一项持续的、全企业范围的跨职能工作，旨在优化数据，使患者、工作人员和社区受益。

Data governance cannot serve as an end to itself—governance for governance’s sake. It will fail if approached with the “one and done” mentality of a one-time event. And it cannot be restricted to the IT department in the organizational hierarchy.

Today’s Healthcare Challenges and Data Governance

Organizations urgently need data governance to confront today’s challenges. By ensuring that people have access to the right data and information at the right time and in the right format to make clinical and business decisions, data governance shows the value of organizational investment in data. However, too often, organizations face:

• An inability to respond to new analytic use cases and requirements.
• Poor or unknown data quality; data that is siloed, inaccurate, inconsistent, unstandardized, etc.
• 冗长而不准确的决策周期。
• Inconsistent analytic results from different sources attempting to answer the same question.
• A lack of accountability or process for fixing data quality problems.

Each of these issues has negative implications for organizations and their patients. Through better data governance, organizations can overcome financial risks, operational inefficiencies, and safety concerns to return value to the entire system—patients included.

Tomorrow’s Healthcare Imperatives and Data Governance

Eventually, data governance will enable even more transformation. By maximizing the value of data through good governance practices, organizations will be able to see and use all of the factors that affect a patient’s health, such as incorporating socioeconomic and wearable data into the hospital data ecosystem.

The shift tovalue-based caredrives the need for reliable data that measure cost of care, margin, and productivity across the continuum of care. It also necessitates the ability for leaders to evaluate the expected return on investments to improve specific healthcare outcomes. Done well, data governance is an accelerant to transformation. It allows organizations to achieve the breadth and speed of integration required by healthcare reform, powered by clinical and technical innovations, and vital for improving the cost and quality of care for patients and communities.

Four Phases of Healthcare Data Governance

Strong data governance is built from four phases, all enabling improved decision-making from the boardroom to the bedside.

Data Governance Phase One: Elevate

有效的数据治理的第一个阶段是通过制定与组织优先级一致的愿景和议程来提高治理的重要性。其目标是将对数据的感知从一种昂贵的技术转变为一种有价值的资源。

As with any collaborative effort, it’s best to begin with a shared understanding of the goals and to define a limited, achievable, and strategically targeted scope for the work. Using an incremental approach, so organizations can work on what matters most first, this step promotes executive buy-in by defining expected outcomes and demonstrating how they relate to the clinical and business activities central to the organization’s strategic direction.

Data Governance Phase Two: Establish

构建一个组织结构来完成数据治理任务有助于建立良好的治理实践。管理数据是一项影响整个系统中许多组的工作。组织起来，召集合适的人员和团队，这对任何新计划的成功都很重要。

An organization’s approach to data governance must overcome substantial complexities. Often governance decisions sit at the intersection of competing priorities (financial vs. clinical vs. operational). The governance team must be curated with this cross-functionality in mind. Additionally, resources for data governance are likely limited, especially at first. Ensuring the right people in the right groups will help make the most of what’s available.

最后，组织有不同的需求，没有统一的、“一刀切”的数据治理资源结构化模板。只有在制定了数据治理的高层议程之后，领导者才必须着手建立团队。将人们组织在最需要做的工作周围，而不是建立团队，然后寻找工作，将有助于指引方向。

Data Governance Phase Three: Execute

Create prioritized data governance projects, with people and resource assignments, to execute the governance mandate. The Data Governance Committee, created in phase two, should sponsor a set of discrete projects with unambiguous goals to support disciplined focus on the work. This project-portfolio approach helps break the work into manageable units that can be phased over time, and it allows for different people to be called upon to support different projects in the data governance portfolio.

Data Governance Phase Four: Extend

Ensure data investments and efforts will last and extend throughout the entire organization into the future. Establishing a set of practices to continually support and improve data governance work is important to ensure ongoing relevance and value for the data governance portfolio and to uphold the gains made early.

Data governance opportunities are seemingly endless, but people’s time, energy, and focus are limited. Looking forward, organizations can bring new energy and fresh perspectives into the governance work that help build and continue the momentum for achievement. Continued investment in data governance also helps to nurture a data-driven culture, reinforcing desired behaviors across the organization.

Principles of Effective Healthcare Data Governance

Each data governance phase must incorporate four core principles to support success, regardless of its specific structures or leadership:

Stakeholder engagement:组织必须超越IT部门，让临床、运营和财务利益相关者意识到数据是一种战略资产，强调其支持从董事会到临床更好的决策的价值。

Shared understanding: Promote the goals and accomplishments of data governance across the organization and nurture a data-driven culture.

Alignment: Ensure that data governance clearly supports the priorities and strategies of the organization, serves the needs of users throughout the data life cycle, and balances polarities (apparent conflicts).

Focus:组织领导者应该思考精益，做最重要的事情，然后随着项目的推进进行调整。在实现最大公共利益所需的最小程度上管理数据是很重要的。

Effective Healthcare Data Governance Requires Ongoing Transformation

Successful data governance is not a one-time event. These steps cannot be a one-off effort because healthcare is continuing to evolve and change; healthcare organizations must be able to react. As an ongoing and iterative process, data governance is responsive to changing circumstances, and enables leaders to re-balance priorities to manage conflict. Finally, data governance efforts must be promoted by leaders, throughout the organization, who emphasize a data-driven culture and thinking of data as an asset to the organization’s goals and improvement.

Additional Reading

你想了解更多关于这个话题吗?Here is an article we suggest:

Effective Healthcare Data Governance: How One Hospital System is Managing its Data Assets to Improve Outcomes

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