Three Key Steps to Maintaining Top-Notch Data Governance

Three Key Steps to Maintaining Top-Notch Data Governance

Today, data is the most valuable currency of all. Data is knowledge, and knowledge is power. Data lasts longer than any CEO, piece of equipment, or business. It is the single longest lasting asset in any organization, and this is especially the case for the field of healthcare.

Data governance is a relatively new body of practice and knowledge in corporations, especially in healthcare. As of right now, the field is still in its infancy, and there is plenty of misinformation and misunderstanding about the subject. Many people in the healthcare industry react to this uncertainty by either using way too much data governance, or way too little. There a few different aspects to understand to maximize the potential of data governance, such as:

●    Data Quality & Access
●    Analytic Prioritization
●    Master Data Management

Let’s take a more in-depth look at these three crucial aspects of successful data governance.

1. Data Quality & Access

Ensuring and overseeing your data quality is the single most important thing successful data governance will do for you. If your data is low quality, it will have wide-reaching negative effects on the timeliness and accuracy of the decision-making of your organization. You need to make sure your data governance committee can react swiftly to this problem and work to enact the necessary changes required in your source data systems. Significant changes in the workflow must also be made.

Data quality is essentially a combination of three different factors. The timeliness, validity, and completeness of the data all combine to make up the overall quality of the data. Your data governance committee should have capable leaders overseeing each of these variables within the chain of data quality.

Providing access to your data also needs to be one of the main concerns of your committee. Making sure all the people involved in your enterprise, including members of the community, patients, and external stakeholders, is one of the biggest functions of data governance. In the past, the trend has been to keep data secret and restrict access to it, but healthcare is evolving and this primitive way of hoarding data is quickly dying out. Nowadays most effective organizations combine both their data governance committees and their information security committees to force them to balance tension and streamline their decision-making process.

2. Analytic Prioritization

All data is not created equal. Some data is more valuable than other data. Because of this, you need to have a strategic plan in place for prioritizing certain types of data over others. Your data governance committee should be instrumental in helping develop this plan for the C-level suite and needs to have an active role in making sure the requirements of the plan are correctly implemented.

Of course, there will always be too many priorities to balance one-hundred percent effectively, but your data governance committee should put something like a 60/40 rule in place. Sixty percent of analytic resources need to be dedicated to the centrally managed priorities from the top-down, and forty percent of the analytic resources should be devoted to the tactical needs of business units, departments, research, and clinical service lines.

3. Master Data Management

Your data governance committee will eventually mature to become the main steward in not only defining master data management but encouraging the utilization of it and resolving conflicts within it as well. As the committee progresses, its role in master data management will also extend to industry and regional standards like CPT, SNOMED, ICD, LOINC, and others. Local data standards will also be included within this role such as department codes and facility codes.

Not only will these coded data standards be covered, but analytic algorithms will also be developed by using regular algorithms to bind the data together. These analytic algorithms should be used consistently throughout your organization for purposes such as defining the criteria for readmission, determining length of stay, identifying patient cohorts, and setting up patients in accountable care arrangements with providers.

In Conclusion

Effective implementation of healthcare data governance in your organization will become more and more critical as years pass. You don’t want to be one of the last organizations with a data governance committee, still hoarding your data, and waiting ages for decisions to be made regarding your data. Low-quality data is a huge problem for healthcare organizations, and unless you set up a data governance committee,  you will be dealing with loads of low-quality data which will clog up your entire process, slowing it down and creating more stress than is necessary for everybody.

Follow the three key steps to successful data governance laid out in this article; and you will be well on your way to a clean, efficient method of governing your data. With the guidelines, you will be able to successfully find a happy balance between over-governing, and under-governing your data, and your organization will be all the more efficient for it.