Delivering quality patient care is a complicated human and technology interrelated process that depends on many factors. Timely access to data such as medical records, real-time medical device data, pharmacy, and other supply chain related information can be the key difference between life and death outcomes. In other industries, a lack of Data Availability may cause customer inconvenience or a myriad of other business function disruptions. In these businesses, data confidentiality is given the highest priority, with data integrity and then data access to follow.

However, in healthcare, those priorities are reversed since a lack of Data Availability can greatly impact patient outcomes and could lead to the loss of human life. While clearly, Data Availability is a paramount concern for every organization, this contrast amoungst industries demonstrates just how important Data Availability is in healthcare. There are numerous big data challenges healthcare organizations face, but in my 15 years of experience healthcare IT field I can say with confidence that the most notable have been centered on dealing with data from disparate / legacy medical applications, devices, and other data stores. Data availability is an enormous challenge for long-term phased migrations to new EMR systems (EPIC) and during mergers or acquisitions of other healthcare institutions.

Technical solutions have been cumbersome and costly because they utilize heavily customized ETL processes and other proprietary technologies. These solutions create their own challenges since data extracts take too long, require many resources, create opportunities for inappropriate data access and over-allocate already taxed high-level engineering resources. These efforts are further challenged by the need to import or export data to systems and applications that are sensitive to the cadence of data access or are otherwise directly incompatible.

In my experience, current legacy approaches to Data Availability are limited at best. Existing platforms and processes are quickly proving to be untenable as the scale, complexity, diversity, and dispersion of data grow exponentially. What organizations need is a solution that effectively meets the needs of the business to query and analyze all data, unifying it with a modern approach to data virtualization that does not move data. Look for a vendor that addresses these needs with a single virtual data layer to deliver unified data access, integrate data from disparate sources, locations, and formats, without the need for data replication. This yields significantly faster access to all data, greatly improving patient outcomes and mitigating costs.