As a healthcare consulting firm, we look at data governance and data management due to the growing relevance and dependence on healthcare analytics.
The healthcare analytics industry is growing at a rapid pace and is making great progress. As each day passes, we are becoming increasingly reliant on data-driven analyses and processes. There is certainly no shortage of data currently and, as the years go by, the amount we will utilize continues to increase.
Though data management can be overwhelming, the healthcare industry is now beginning to use and realize its strength and true potential. It is universally agreed that to manage data for business use, the data needs to be formatted in a standard and consistent framework. More than ever, the healthcare industry is challenged with the task of gathering data from multiple sources and is faced with the question of how to use this gigantic data set to drive operational efficiencies to improve outcomes.
We need to first develop a shared understanding of how value is defined for the healthcare industry to establish a culture of value measurement in healthcare. It is only by doing this that the value can be accurately measured, analyzed, managed, and monitored. At the heart of these activities is data.
A chain of trust and liability must be created for data so both its creators and the consumers are confident about it, and are happy to use it from the source. Decisions based on inaccurate information can lead to serious problems. Data used at odds with the intent of collection can also lead to erroneous decisions. The accumulated data must be sensibly brought together and integrated practically for timely and reliable information.
The data chain of trust from source to integration needs to be clearly understood and well documented. The resulting integrated view can then be considered the source of reliability for information to support the reporting, measurement, and the analytics needs of an organization.
Another factor to consider for data is that it is time sensitive. The longer the procedure takes, the less valuable and relevant the accompanying data becomes. It is important for a firm to have the required data readily available for analytics to create the best result, so that the analysis can be produced promptly to help decision makers take timely decisions. Therefore, the longer it takes to collect all the data and perform the analysis, the less effective the action becomes for the use.
Thus, the major missing blocks for successful data analytics are good data governance and management.
Data governance is the core component of data management. The DAMA Dictionary of Data Management defines it as “the exercise of authority, control, and shared decision making (planning, monitoring, and enforcement) over the management of data assets.”
Data governance requires a clear understanding of the challenges and a strategy for addressing them. Those who observe, extract, and record data facts must see value in the effort. Knowing your own data and leveraging it to continuously improve quality is the key to accomplishments.
The formal structures and disciplines which compose data governance are responsible for creating the framework for solving problems, as well as sustaining consistent, accurate, reliable data, and information chattels across the healthcare industry.
As the healthcare industry transitions to value-based payment models, the stage is set for further advanced analytics – an essential component to achieving value-based outcomes.
Healthcare reform is a catalyst to which data governance is an essential accelerate. The standards to which healthcare is required to be accountable can only be achieved and sustained in an environment which embraces and promotes formal data governance for the various operations in the industry.