Doctors are pretty smart people, and it’s not a lack of want that historically denied them better insights to their patient data. But things are changing. New ways of exploring vast lakes of healthcare data is now becoming a reality thanks to advanced analytics platforms that are capable of handling extremely complex and varied data sets that typically characterize the healthcare industry.
And the timing couldn’t have been better with pressures to reduce costs while improving services on the rise and the Affordable Healthcare Act (ACA) placing new stipulations on providers to better manage and leverage data to improve services and comply with regulations.
Traditionally, getting a healthcare analytics solution off the ground was often fraught with obstacles, ranging from complex data governance concerns, to mountains of data, to buy-in from clinical staff. These and other factors are contributors to the reality that the industry has been one of the slowest to adopt big data technology over the years. Fortunately, while the challenges are many, shifts in the healthcare sector are creating a more fertile environment within which big data solutions can yield big payoffs.
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Overcoming historic obstacles for a more BI friendly industry
Few industries have as many silos as the healthcare sector. Information lives in virtual puddles all over the place, with lab records, patient diagnoses, radiology files, emergency room data and case management documents all living in separate storage locations – some digitized, some not. Overcoming information management challenges has been a historic burden for most healthcare organizations, making the adoption of viable analytics solutions difficult at best.
Fortunately, a shift in recent years is seeing a concerted effort from both federal government and healthcare industries to invest in information digitisation and new, more innovative data management solutions and practices. The drive toward electronic health records (EHR), for example, is making patient data more available across organizations.
And the argument for a more digitized approach to the issue of patient care is clear, especially in an industry that has historically been bogged down by bureaucracy, paper-heavy processes and excessive red-tape.
Making analytics available across the organization is key
Doctors and other clinical professionals stand to gain an unprecedented leg up with the help of analytics platforms that promote a culture self-service. In the current scenario, the data is there in abundance, but healthcare professionals simply don’t have the time, nor resources to contend with complex BI platforms that require data scientists to operate them. The nature of the industry simply doesn’t cater for slow turnarounds when the well-being of patients are at stake.
But where traditional BI falls short, next generation search-driven analytics platforms are stepping in to bridge the divide between healthcare professionals and their data. By allowing clinical staff to make their own correlations between vast expanses of medical data, such as admission frequency, prescription data, treatment histories, staff observation records and emergency room data, patient care stands to get a much-needed shot in the arm.
Search-driven analytics platforms typically do not rely on pre-canned reports, which makes it easy for hospital staff to visualise organizational, financial and patient data to highlight issues within the organization or predict future health issues for patients – or even segments of populations. Through the lens of predictive data models, search analytics can help organizations better understand the causes of diseases, predict the likelihood of patients’ future healthcare requirements based on historic, family and other data.
In the near future we can most likely expect more advanced smart devices and apps that will become treasure troves of people’s personal medical data. When infusing data sources like these to a healthcare organization’s or general practitioner’s patient data, the possibilities of healthcare through the lens of search become endless.
From treatment to early intervention
Search-driven analytics, especially in healthcare, can be a powerful prevention tool and as healthcare organizations continue to collect larger quantities of data, the more important it becomes to make that data available across the entire organization.
Search analytics’ ability to do exactly that is one of the reasons it’s getting attention in the industry of late. According to iCrunchData, search-driven analytics addresses historic BI issues by, “…. using a relational search-engine database that provides users with easy reporting access to their entire silo’d corporate data, whilst bridging the gap between a non-technical user and the more advanced data analyst.”
The patterns in historic patient records make prescriptive analytics relatively simple, but it’s when medical staff can explore this data through intuitive search-based technology that the potential in healthcare analytics truly becomes realized. For example, healthcare professionals can better manage re-admission rates by making correlations between patients’ historic data, which may include past admissions, treatment prescriptions, emergency room data and doctor’s records and recommendations. This translates into fewer misdiagnoses or treatments that put hospitals at risk while simultaneously managing resources smartly.
At Tellius Business Intelligence, we’re at the forefront of bringing next-generation data analytics solutions to the healthcare sector. Through lens of search-driven analytics, we’re helping healthcare organizations improve patient care while elevating performance across operational, financial and supply chain spheres. To learn more, contact us.