Data Governance Best Practices

 

Data is very important in the healthcare industry. In every area of a healthcare organization has data flow from surgical records to insurance claims, payment receipts, patient demographics, pharmacy inventory etc. Every area of the healthcare industry relies on an endless stream of data flowing in order for the system to function. Data management evolved with the advent of technology which ushered in electronic records. Data previously was stored in paper records, files, and boxes which made it almost impossible to manage. Issues like missing document, misfiling of a document or illegible handwritings served as a hindrance to data scientists who could use data from patient history to predict the future of patient care. https://www.healthcatalyst.com/healthcare-data-governance-practices  

Data governance can, therefore, be defined as the practice of managing data assets throughout their lifecycle to ensure that they meet organizational quality and integrity standards.  Data governance is geared towards making sure that users can trust their data, which is especially important when making patient care decisions.

As part of a comprehensive data governance program, users are held accountable for creating high-quality data and using that data in a secure, ethical, authorized manner. In the healthcare industry, health information management professionals are often responsible for developing and overseeing data governance principles that improve the consistency, reliability, and usability of data assets while optimizing EHR interfaces to eliminate unnecessary or duplicate steps for end-users and eradicate problematic workarounds. The goal of these activities is to improve staff efficiency, foster an environment of accountability, and create a standardized, interoperable pool of big data that can be used for organizational improvements and higher quality clinical decision-making.

The Sanders Philosophy of Data Governance

A health practitioner called Sanders says that his philosophy of data governance is to make the data as lean as possible. Healthcare organizations should govern the smallest possible data in order to achieve the greater common good. When healthcare organization governs too much data too soon, it leads to unnecessary constraints in data and wasted manpower and labor. Some data do not need governing right away and should be kept aside until the appropriate time when it’s needed. Pairing the data governance function with overseeing the development and evolution of an enterprise data warehouse (EDW) gives the data governance committee something tangible to govern. Bind no data before its time, and govern no data before its time.

Developing A Good Data Governance Strategy

In order to develop a good data governance plan, healthcare organizations must first recognize the need in order to know where to start which is better at the top.Healthcare organizations that commit to making governance a top priority on every rung of the corporate ladder are more likely to see success and to adequately support their health information management staff during the process. Involving organizational leaders can help jumpstart the development of a cross-departmental information governance team.  Providers should clearly define their information governance goals and create measurable benchmarks to gauge executed progress.  Each member of the governance team should have a set of well-understood tasks and responsibilities and should be given the opportunity to provide input, listen to feedback from their peers, and work across departmental lines to achieve their objectives.

These principles should be communicated clearly across the organization, and members of the data governance leadership team should take the time to explain the project in detail to staff members, answer any questions, and ensure widespread buy-in for improvement activities. Healthcare organizations should also include opportunities for continued monitoring and ongoing improvement as they create their data governance strategies.  End-users should receive regular training and reminders about optimal data integrity and data entry practices, and organizations should conduct frequent internal audits and assessments to ensure they are maintaining a high level of data quality.

These activities will ensure that healthcare providers are prepared to utilize their growing big data resources for generating actionable insights and that they are being mindful of patient safety and care quality as they optimize their assets for the future of value-based care.

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