Revenue Cycle Management Blog | GroupOne Health Source

Why Healthcare Organizations Can't Afford to Ignore Data Management

Written by Ricki Ransom | July 7, 2016

The data-driven healthcare organization is the one most likely to thrive today. Data analytics is now a top driver for IT spending, with more than one-third of hospitals overall saying analytics drives their IT spending. For medium sized hospitals, that figure is closer to 45%. Treating data as a strategic asset, and analyzing it appropriately can make decision-making more productive. This can lead to reduced costs and improved healthcare delivery. 

Why Healthcare Data Management Matters

Healthcare data management matters for several key reasons. For one, population health management is gaining prominence under government health initiatives. For another, value-based reimbursement is entering the mainstream, and that means understanding data at every step of the patient encounter.

How Healthcare Data is Unique

Dan LeSueur, VP of Technical Operations at HealthCatalyst, points out that while we tend to think of healthcare data in very structured, linear terms, healthcare data isn't that way. Healthcare data is "both diverse and complex making linear analysis useless" says LeSueur. 

There are also key characterists that make healthcare data very unique. HealthCatalyst mentions these characteristics in a recent post- 5 Reasons Healthcare Data is Unique and Difficult to Measure.

In this post, LeSueur states that healthcare data is unique in terms of where it exists, how it is structured, and how it is defined. All of these characteristic combined with a shifting payment model focused on value based care make healthcare data complex to say the least.

For all these reasons, healthcare organizations must prioritize accuracy, accessibility, usability, security, and governance of healthcare data.

How an Analytics Strategy Can Help Healthcare Providers

Enhanced data collection and analytics can yield measurable positive resultsA strong data management strategy can determine which patients consume the most healthcare resources and which are more prone to adverse outcomes, so providers can develop programs and treatment plans to improve these metrics.

It also gives healthcare consumers more power to manage their own health better. Data management helps clinicians learn which procedures don't deliver benefits that are worth the costs and risks, and helps them transition to more effective and efficient procedures.

Hospitals can use data to identify those at higher risk of adverse events or hospital readmission so they can adjust treatment plans and follow-up accordingly.

An efficient data management program is also going to help your clinic or organization attract better clinicians, who can continue to improve the organization's reputation with innovation, collaboration, and secure access to valuable data.

Why Data Management Strategies Can Fail

Providers may feel under pressure to deliver meaningful data insights right away, and this can cause them to rush the development of a data management program and make it less effective.

In fact, seventy to 80% of such initiatives fail to live up to expectations.

The good news is that business intelligence and analytics technology is advancing rapidly, so providers can more quickly capture and utilize data generated by EMRs, health insurance plans, and other sources.

Processes and personnel will also, however, have responsibility for things like establishing a common language (In a large hospital, for instance, what is an "admission?") so that data doesn't become siloed by department or location.

How to Initiate Better Data Management

Better data management starts with asking a few pointed questions:

• Who is responsible for the organization's data?
• Is data accurate and secure?
• Is data governance in place to ensure data is usable, secure, and relevant?

Moving toward a desired maturity level with respect to data analytics requires defining goals and plans that align desired patient outcomes with business objectives.

You could, for example, strive to get hospital readmissions under 7%, and then educate personnel on how data gathering can help movement toward this goal.

Executive buy-in is also essential, as is support from stakeholders in the clinical, technology, operations, and financial departments. Make data management a part of daily conversations, and discuss pain points as they arise.

Data management isn't entirely about technology, however. People and processes are just as important. User support, training, and data quality oversight are all essential. Technology alone can do very little without excellent processes and people to make use of it.

Allow for Evolving Technology

Your data management plan must allow for technology evolution, which continues at a rapid pace. Data management has to include both short and long term goals and plans, and there's no denying that it's hard work. However, data management leads to better insights and decisions, both of which are vital to healthcare providers thriving in a fast-paced, competitive business environment. 

 

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