4 Steps To Improve Healthcare Decision-making
How can healthcare organizations effectively improve decision-making?
Healthcare organizations are drowning in data and starving for value. And yet, the needed information is siloed in isolated source systems.
This is a barrier to limitless data-driven decision making. Therefore, it is crucial to liberate data through an integrated approach.
Below are 4 steps to follow when following this method.
1- Making data easily accessible
Reconsidering the organization’s data management is the first step to accelerate an improved decision-making process. Changing the tools adopted and shifting to those who fit the budget, needs, and business objectives of the organization will improve data accessibility. Once the data is discoverable, it will be useful for the stakeholders’ needs. In the process of improving access to data, the users will also be empowered. Their skills will be broadened, and their data interpretation will be more accurate.
2- Enhancing data understanding
Making the data accessible is not beneficial on its own. The possibility for business users or data stakeholders to misinterpret or misrepresent data is high. That is why it is significant to make sure that the capabilities of the data are well communicated. When data is understood, working with it becomes easier and will be used correctly. Holding workshops, building an internal knowledge base are some of the ways to enhance data understanding.
3- Standardizing data
Data needs to be internally consistent, accessible, reliable, and timely. Data standardization is key to decision-making. Collecting and transforming data in common formats, based on predefined standards, and clear definitions is advocated. This will ensure progress and inclusivity within the organization. In return, valuable insights are derived with improved analytics.
4- Maintaining data
Data maintenance is essential to ensure better decision-making. If the data quality is poor, risk of inaccuracy and bad business outcomes is higher. Investing a significant amount of time and effort to clean and sharpen the data is required before digging deeper into it. Once the data is complete, enriched, formatted, and verified, stakeholders can safely start taking actions that will lead to informed decisions.
It is then crucial to liberate data to foster an improved data-driven decision-making environment. By doing so, insightful reports become available to users whenever and wherever needed. However, this would generate a high volume of report requests that no BI team can sustain.
Therefore, a self-service BI approach is preferred to achieve these benefits.