The healthcare industry, like many others, has become a data driven industry collecting data from patients, doctors, labs, and payers that are all crucial to patient healthcare diagnosis and outcome. When it comes to research, data can be useful in creating emerging healthcare technological innovations, pharmaceutical discoveries, as well as other advances in the market but it also is accompanied by strong regulatory compliance, like stringent HIPAA laws, that dictate that this data is kept private and secure.
In fact, in 2019 there were a reported 418 HIPAA violations, which amounts to 34.9 million Americans who have been victims of healthcare data breaches, which is roughly 10% of the US population. And in 2020, there were 17 hospitals, health systems, and health plans that have settled for HIPAA violations.
The highest penalty for a HIPAA breach is $1.5 million per year and a violation can cost anywhere from $100-$50,000 depending on each case. That is why, the Bureau of Labor and Statistics estimates that positions for compliance officers will grow by over 8% from 2016 through 2026 because the need to keep healthcare information secure is critical and growing, especially in today’s COVID-19 environment.
Just this week, several health IT players have announced support for the recent HR 7988 bill that would mandate the Department of Health and Human Services to encourage “covered entities” to adopt best practices for complying with HIPAA laws, specifically in relation to security. And while security is a major concern – it goes hand-in-hand with data management. Understanding that data is secure, how to access data and following the data lineage from start to finish will help all healthcare organizations be HIPAA compliant.
Healthcare organizations understand how crucial data is; however, they have yet to understand the value of a robust, unified approach to data management that provides an organization with a single of view of metadata across all business intelligence systems used in the healthcare organization so that accessibility is simple, errors can be detected immediately, and data lineage can be traced in seconds. What also yet to be recognized is that data management is key in keeping in regulatory compliance with HIPAA. Unfortunately, many healthcare organizations are still operating on a manual system and if they are using systems with automated capabilities, they are often not unified – creating an enormous task of aggregating metadata manually which, by nature, is error-prone. Manual data management will lead to a wealth of HIPAA issues.
“This is an area both payers and providers have underinvested in and have remained behind compared to other industries, while their consumers have grown accustomed to data-driven experiences from other industries,” stated Munzoor Shaikh, senior director of healthcare and life sciences at West Monroe Partners, to TechTarget.
In order to create a unified, automated approach to metadata management and business intelligence, one that will keep the organization HIPAA compliant, three critical capabilities must be put in place by the BI & analytics teams – automated data lineage, automated data discovery and an automated business glossary.
1. Automated data lineage and discovery will enable the business intelligence team to locate an error in a report immediately, track the source of the data automatically, and fix that error quickly, much to the delight of the healthcare. Automated data lineage also allows BI teams to quickly and easily conduct impact analysis ahead of making a change to any ETL process as well as find the root-cause of a reporting error by tracing data back to its origin.
2. Another important capability is automated data discovery, which enables BI teams to locate the data scattered throughout their BI environment in seconds. Accessing accurate data efficiently will be heavily relied upon to make the most crucial business decisions and automating the process allows healthcare executives to easily create accurate reports so that decisions can be made fast. This is especially important at a time where constant, rapid changes are happening continuously and unpredictably.
3. A business glossary is a cornerstone of data management for healthcare executives operating in different locations and in different departments because it creates company-specific business terms and definitions so that there is a universal language for data input across every department within a corporation. This is an important step to organizing data since it assigns terminology to specific data, minimizing the use of different terms throughout various departments for the same data assets.
Creating a unified system for data across a healthcare organization will ultimately lead to better patient treatment and outcome, the unlimited potential for innovation, and efficiency that will impact executives, payers, and patients alike. However, compromised or misplaced data can put the patient and hospital at high risk.
About Amnon Drori
Amnon Drori is the CEO of Octopai, a provider of metadata management automation for BI & Analytics. Before co-founding Octopai he led sales efforts at companies like Panaya (Acquired by Infosys), Zend Technologies (Acquired by Rogue Wave Software), ModusNovo and Alvarion, and also served as the Chief Revenue Officer at CoolaData, a big data behavioral analytics platform.
