8 Steps To Becoming A Data-Driven Healthcare Organization


data driven healthcare organizationsToday’s healthcare industry is driven by a continuous stream of data. The quantity and availability of data have transformed decision-making and opened up new opportunities to better serve patients.

While the technology exists, many healthcare organizations struggle with data capture due to inconsistent processes or procedures, or a general lack of governance. Becoming “data-driven” can provide a competitive advantage and enable healthcare organizations to develop long-term value.

How To Become A Data-Driven Healthcare Organization In 2021 And Beyond

Data-driven healthcare organizations share similar characteristics. They have a proven history of making decisions based on data rather than intuition. They also plan and execute strategies to invest in the future development of data to improve healthcare operations. Data-driven healthcare organizations make it a priority to increase the data literacy level of employees to ensure that the workforce as a whole uses analytical thinking to make decisions.

Here are eight steps for becoming a data-driven healthcare organization.

1. Identify Your Organization’s Data Maturity

Data maturity refers to the extent to which a business is using its data. The higher the data maturity level, the more an organization uses data to inform its processes and procedures. Data maturity is generally broken down into stages, starting with organizations that are just getting started with their data strategy. The stages of maturity then progress to the top level which consists of innovators who use data to create algorithms and remain a step ahead of the competition.

2. Determine Which Analytics Align With Your Business Goals

businessman analyzing the dataIt is common for healthcare organizations to interact with data across a wide range of business departments. From heart rate monitors to security cameras, data is generated by all types of technology commonly found in healthcare facilities.

Organizations that want to become more data-driven must determine which analytics best align with their business goals. These insights can help organizations discover new business opportunities and gain a better understanding of their patients, networks and influences.

3. Analyze Strengths And Weaknesses Of Your Current Data Structure

Before a data structure is changed, it is important to thoroughly analyze any existing data structure to determine where improvements can be made. Data structures are a means of managing large amounts of data efficiently for uses such as internet indexing services and large databases. There are many different types of data structures.It’s important to assess the strengths and weaknesses of the structure to determine if a different solution would be better suited for the organization.

4. Utilize A Centralized EHR Software Solution

Electronic health records (EHRs) are commonly used to improve healthcare processes and better serve patients. However, not all EHR software is created equal. EHR complexities like time-consuming operations, frequent errors and difficulty of use can have the opposite effect of the software intention and slow down operations. It’s critical to have a centralized EHR software solution that can handle the features and integrations that modern healthcare facilities need to be successful.

5. Integrate Strong Data Sources And Algorithms

While it is easy to create large amounts of data, it is not always so easy to harness its insights. Data integration plays a major role in becoming a more data-driven healthcare organization. This process involves combining data from various sources to help business leaders analyze and make wiser decisions.

6. Encourage Employees To Contribute Their Own Ideas For Metrics

Creating a data-driven culture in an organization requires the entire workforce to play a role in sustaining an organization with data at its core. Allow employees to contribute their own ideas and strategies for metrics. By getting employees involved in the process, it can help create a shift in mindset and establish practices that are more likely to stick.

7. Eliminate Any Overlapping Data Silos

data silos written on book coverData silos refer to collections of data held by a group that are not fully or easily accessible by other groups. It is common for these collections of data to overlap, resulting in duplicate and often inconsistent records. This can significantly impact efficiency. Take the initiative to eliminate overlapping data silos and possibly break them down over time.

8. Ensure Reduction Of Data Entry Errors

Data entry errors can slow down efficiency and create confusion between departments. There are many ways to reduce common data entry issues, such as training employees on the importance of data, hiring sufficient staff, providing a good work environment and updating systems on a regular basis.

Refine Your Healthcare Organization’s Data Maturity With Hartman IT Consultants

Becoming a data-driven healthcare organization can have countless benefits, such as improved productivity, reduced operational costs and increased revenue. To learn more about how to refine your healthcare organization’s data maturity, contact the IT consultants at Hartman Executive Advisors today.


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