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How Your Medical Practice Can Get the Most Out of Big Data

January 10, 2019

Many medical practitioners may not think their practice is large enough to benefit from big data, a term which means a collection of data from traditional and digital sources inside and outside your practice that represents a source for ongoing discovery and analysis. However, done correctly, leveraging big data could help your medical practice – regardless of its size – deliver more effective and efficient care to your patients.

Recognizing this, the American Medical Association last year launched an initiative to develop a standardized framework for the medical industry, with an early focus on hypertension and diabetes. This will help practitioners know what data to use to improve health outcomes.  It will also address practitioners’ concerns about poorly organized or incomplete information stored in current medical records.  In the meantime, there are several steps you can take to prepare your medical practice to harness big data.

Find a Big Data Software Solution and Expert

Even if you already have a good amount of data on your practice’s computers and other electronic devices, combing through all that information can be a daunting task.

Make sure you conduct a thorough review of your practice’s data inventory, so you know what’s stored where and how different devices might be able to interface with each other. With that mapped out, there are different software tools, such as SAS and SQL, available to help you scan that information and present it in a usable fashion.

You should consider using a third-party contractor to assist with the data analysis. Electronic health records often are not organized in a way that’s easily searchable. Provided that the right confidentiality agreements and patient protections are in place, data scientists can access your servers and data to get the best use out of your medical information.

Big data provides useful insights into improving patient care. An outside expert can make sure your practice doesn’t waste time and resources analyzing large datasets inefficiently or incorrectly.

Utilize Medical Registries and Other Sources

Along with traditional records, your practice may use other resources to analyze and collect useful data.

Many practitioners participate in medical registries related to their specialty, where they can upload and review anonymized patient data – provided with permission – on various illnesses. This can help practitioners more easily identify patterns and earlier identify what type of treatment certain patients need, particularly with the right big data tools in place.

Individuals are increasingly using a variety of mobile devices and services that track everything from blood pressure to physical activity levels. Accessing patient data from such devices helps improve that patient’s treatment and documents information that may prove useful for treating others.

Protecting Confidentiality

Although medical data collection is becoming more common, privacy protection standards haven’t changed. Keep patients aware of the data you collect and how you protect it, especially if they provide medical data from personal mobile devices. Train employees on cybersecurity and data privacy and carefully review the privacy policies of any third-party vendors.

Big data can greatly improve the service your medical care provides to your patients. But with the vast amount of data out there, work with your business advisors to make sure you have the right systems and expertise available to use it properly and effectively.

 Need help building your digital roadmap? Call your MarksNelson Smart Technology professional at 816-743-7700 to discuss how our Digital Solutions Assessment will help you find the right tools to meet – and exceed -- your goals.

About THE AUTHOR
At MarksNelson, we pride ourselves on our commitment to innovation and technology. This fuels our professionals' drive to work with you, not for you - bringing comprehensive and innovative solutions to the conversation and helping remove uncertainty from the outcome. >>> READ MORE
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