New England Geriatrics (NEG) is a healthcare company that provides behavioral healthcare to elderly residents of nursing homes. Established in 1994 as a family-owned business, it now employs 200 staff members across Massachusetts. Many facilities for geriatric patients provide basic care to a high standard but lack the internal expertise to deal with mental health issues. This means that patients are transferred to the hospital which can be disruptive to their treatment and overall health - as well as costly. NEG works with nursing homes to provide excellent mental health care on site so that elderly patients don’t need to leave their residence to receive treatment.
CIO Eric Pavlak was overseeing the switch from paper to electronic record keeping and needed a smart way to store and analyze data to draw out actionable insights. After examining several solutions, he concluded that none could compete with Sisense’s ability to deliver self-service BI for business users, without requiring a data warehouse.
I am deeply satisfied with my selection of Sisense. In a fiercely competitive landscape, I did my due diligence and am thrilled by the results.
The Challenge: Data Latency and Performance Measurements
NEG’s data challenges were extensive: the switch to electronic health records meant a huge overhaul of its processes, workflows and data storage, before any kind of analysis could even begin. Until now, all diagnoses and treatments had been written on paper and mailed to the facility; once this documentation was recorded, data was input into a practice management system, services were billed to insurers and claims were paid. Doing things manually added a 30 day latency period from the time services are rendered until payment could be collected. This made it almost impossible to measure company performance.
The Practice Management System that NEG uses is a great product, but it was not built to analyze data. While it does come with a BI add-on, in reality, this simply a query that pulls out raw data, without allowing users to visualize and conceptualize the results. Eric needed a tool to present data in a compelling, interactive way.
The Search is on
Eric was already sold on the value of BI, and he understood that numbers are meaningless without the context to understand them. He knew that, to get real value out of any BI platform, he needed something that would allow him to easily report on performance and measure KPIs, with the option to drill down and draw out the context behind these numbers. He was also aware that his chosen platform would need to address the pain points of multiple audiences.
Firstly, the CEO would need the ability to view high-level data quickly, on the go, in order to make agile business decisions. Business users such as program directors would need to design their own dashboards and dip into the underlying details, to get the insights they needed to run their facilities better.
Eric began reviewing the options. He looked at four market-leading BI platforms – but only Sisense offered the flexibility he needed to cater to each internal audience at once. One competitor went so far as to offer the desktop version of the product for free, but even with this perk, the system was too complex, and lacked the versatility and self-service elements he was looking for. For Eric, it was essential that he would be able to figure out how to use the tools himself. He planned to become the primary user first, get to grips with the product, and then gradually roll it out to more and more business users until they were able to gather all their own BI insights unaided. This made it imperative that the platform was straightforward enough for a non-technical user to master – and that’s what ultimately led him to choose Sisense.
Merging Data Sources for Complete Insights
Going live was far easier than Eric expected. Over the years, he had tried to implement several different data solutions, but always struggled to persuade his team to adopt the tool. With Sisense, the BI solution was able to finally gain traction at the executive level.
NEG’s data is grouped into two categories: clinical and financial. Using Sisense, Eric could merge these two datasets for the first time, visualizing trend and patterns, and gaining a 360 degree view of the entire business. All of a sudden, management could clearly compare their figures to the previous year’s, and to see how their performance stacked up against the rest. Problem areas were immediately apparent, allowing them to take swift, effective actions to improve.
Through Sisense, users were able to perform data exploration and discovery on PMS records, in a visual environment. They could easily build executive dashboards, putting their data into context. Business users could then use this data to enhance their processes within the organization.
The legacy tools we had in place never seemed to inspire anyone to use it on a daily basis… Once I was able to pull in all the data sources, create the visualization, create context and then report that out on an automated basis, the light bulb went off and it naturally started gaining traction.
Eric was already impressed with Sisense, but it wasn’t until he came to deploy it at NEG that he hit on a huge, unexpected benefit.
The way Sisense works is that all data is fed into the Elasticube directly, meaning that Eric could pull in all data from all sources, including his Practice Management System, storing and manipulating this as if he had full stack data warehouse infrastructure in place. In other words, this means that NEG can work with multiple data sources without needing a data warehouse.
Eric was blown away. Coming from a strong database background, he had built many of his own custom databases in the past, which had now been relegated to orphan silos. Now, he could easily incorporate all of these data sources without having to invest in a warehousing solution, giving new depth to his analyses.
“There is an understanding and transparency in the business that we haven’t seen before,” he says. “When management can make agile decisions based on real numbers, we can see that the understanding and value are there.”
When management can make agile decisions based on real numbers, we can see that the understanding and value are there.