Between the Meaningful Use program, the upcoming ICD-10 transition, productivity issues with EHRs and increasing pressure on finances, hospitals and providers everywhere have too much going on to worry about big data. Developing a comprehensive solution that can analyze disparate data sets to deliver new insights is a complex undertaking, requiring substantial investment.
As with any large-scale technical project, there are a number of obstacles to be removed before clinical analytics can deliver the promised results. The most critical aspect is data integrity. The most expensive and advanced digital software will be unable to deliver meaningful insight if it only has incomplete or garbled data. With paper records, physicians were used to taking down notes that needed to be legible to themselves and maybe other specialists. But with electronic systems, patient health data needs to be comprehensive and organized in a manner that makes it easy for software to sort and parse. In short, practices will have to clean up their documentation before even thinking about implementing analytical systems.
Another obstacle is the healthcare industry’s perspective when it comes to sharing data. Most hospitals consider clinical data to be their most valuable asset and hesitate to share such information with outsiders. Nevertheless, analytic software must be able to combine data from various sources such as financial, operational and clinical processes in order to produce results. This means that organizations have to foster an environment where medical data is freely shared between departments under appropriate guidelines.
Still that is just the first step. To derive the full benefits promised by big data, organizations will have to go beyond and share knowledge with partners and collaborators. Naturally such knowledge swapping will not extend to sensitive patient information but sharing experience, roadmaps and technical expertise can benefit all parties in the ecosystem. Some hospitals are well on their way to implementing advanced analytics while others have not yet started. Awareness of potential pitfalls and obstacles can be helpful to prevent other organizations from making the same mistakes.
Finally, big data projects need the support of the various departments just as much as EDR implementations. The team in charge of developing analytics should ensure buy-in from all stakeholders such as employees, management, as well as organizational leaders if the project is to be a success. Practices that are using Dovetail dental software can rest assured that their data is well organized and maintained. Our dental software satisfies all the required interoperability standards, which means that your data is accessible when and where you need it.