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How Big Data Improves Healthcare Analytics
Several major developments in data management will benefit healthcare, including data collection via electronic medical records, data sharing via health information exchanges, and improved data analysis via enterprise data warehouses and other new analytical tools.
Fremont, CA: Big data is proving to be a valuable asset in an industry under pressure to cut costs and improve member outcomes. Data, on the other hand, is insufficient to move the needle. It all comes down to how data is analyzed in order to make better decisions about intervention and treatment options.
Several major developments in data management will benefit healthcare, including data collection via electronic medical records, data sharing via health information exchanges, and improved data analysis via enterprise data warehouses and new analytical tools.
Let us look at how big data is improving healthcare analytics, such as the ability to track trends and patterns from multiple sources.
Providing the Right Intervention at the Right Time
One area where big data is improving analytics is in identifying people who are at risk. Another is ensuring that the most effective intervention is identified for each individual – and that it is delivered when it is required. Improvements in this area are being driven by technological advances combined with analytics. Large amounts of real-time information, for instance, are now available from wireless monitoring devices worn by postoperative patients and those with chronic diseases at home and in their daily lives.
As people start to understand their own risks, monitor their health, and share relevant information with their care providers, the ability to deliver the right intervention at the right time will improve. It also calls for a coordinated approach in which all caregivers, regardless of setting or provider, have access to the same information and work toward the same goal. Systems can identify high-risk members faster, recommend more timely interventions, as well as provide data-driven monitoring with better data accessibility and analysis.
Targeting the Right People
A health plan's beneficiaries consist of various groups of people who may be at any point along the health and wellness continuum. How does a plan determine who is at risk for coronary artery disease or diabetes, as well as who might benefit from additional screenings, weight management, or smoking cessation programs? Providing care to those in greatest need begins with an examination of multiple sources, ranging from claims data to member-provided information to health risk assessments.
Data from health risk assessments, for instance, can provide a snapshot of potential plan usage among new enrollees. Health plans would have to wait and see who needed care coordination if they didn't have the data. Furthermore, health plans can use healthcare analytics to learn what motivates people and how to change their behavior. Examining screening rates among different demographic groups can assist in identifying barriers to screening and determining the best way to encourage specific groups to complete recommended screenings. When dealing with large populations, it is even more important to understand who may benefit from the intervention in order to improve health and reduce poverty.