Best Practices to Fuel an Effective Healthcare Data Management Strategy

Updated on January 13, 2023
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COVID-19 impacted businesses across nearly every sector, but perhaps the most drastically affected industry was healthcare. During the height of the pandemic, healthcare organizations were grappling with increased medical emergencies, longer wait times and at-capacity care facilities – but behind-the-scenes, these obstacles also created data overload, creating yet another ominous challenge for the sector.

Now, as the industry has learned to better manage COVID-19 surges, and with the pandemic factored into most business plans, healthcare leaders have an immense opportunity to benefit from the data in their possession, and use actionable data insights to better inform the business on what’s working, what’s not and what needs immediate attention. To do so, healthcare decision-makers must prioritize an effective data management strategy, one that accounts for every area of the business and puts patients at the center of every outcome. Based on my discussions with healthcare leaders, here are a few top tips to achieve just that:

Breaking down silos to improve internal processes

Within a healthcare organization, it’s common to have multiple locations or branches of the business. For example, a hospital can have several locations, which each then have dozens of departments, while also working closely with third-party partners that provide services like radiology, blood testing and more. Within that business structure, there are many organizational silos – finance handles billing, HR manages the employee experience, etc. – all analyzing different, dispersed data without working in unison. It’s not beneficial for anyone, especially when trying to deliver the best possible patient care.

The first step in an effective healthcare data management strategy is to ensure that all department leaders have access to the same actionable data insights to better inform their business decisions. When building this collaborative structure, a good place to start is by working closely with the organization’s Chief Data Officer (CDO). CDOs will help others better understand the data currently in possession, how it’s analyzed and what it means for patient care. Upon collaboration, there will be instant areas of improvement to better streamline internal processes – like information-sharing across those various branches and partner services – without creating a bottleneck or working in a vacuum. Seize those immediate opportunities as the organization works towards longer-term, data-informed goals. The most effective data management strategies take into account infrastructure, processes and tools that are fit for future challenges, with the ability to grow and adapt as the company evolves over time.

Acting on insights to deliver better patient care

Of course, the number one priority fueling a data management strategy is how it will improve patient care. Patients are at the center of every healthcare experience. For starters, patient feedback – whether through surveys, call center interactions or in-person medical appointments – should be treated as critical data. In fact, this type of information can be extremely valuable to identify common areas that need improvement, and fast. For instance, are patients complaining about long wait times? Poor bedside manner? Ineffective imaging? If there’s several instances in the data set of a poor patient experience, it should be elevated immediately to see what the disconnect is, and fix it – fast. 

Speed is also critical to produce actionable data insights, which can then yield faster turnaround times for patients. This can include shorter wait times for a medical appointment, less time on the phone with representatives, and faster test results. Speed matters – fast, yet actionable, data insights should be prioritized in a data management strategy for a better, nearly instantaneous patient experience.

As data is collected and analyzed to enhance the patient experience, healthcare organizations must also stay ahead of evolving healthcare regulations. For instance, as HIPAA Covered Entities, healthcare providers must implement the proper administrative, physical and technical safeguards to protect electronically protected health information (ePHI). These safeguards are often extensive, but with an effective data analytics database, compliance can often be achieved without it becoming a taxing burden for data analyst teams.

To solve today’s pressing business challenges, especially in a post-pandemic emergency environment, healthcare organizations must leverage the large amounts of data in their possession. In order to do so, an effective, efficient data management strategy must be established – one that factors in how to best streamline internal processes, while putting patients at the heart of everything data can enhance. 

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John Knieriemen
Regional Business Lead North America at Exasol

John Knieriemen is the Regional Business Lead for North America at Exasol, the market-leading high-performance analytics database. Prior to joining Exasol, he served as Vice President and General Manager at Teradata during an 11-year tenure with the company.
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