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Healthcare Business Intelligence 2018
Who’s Advancing Data Analytics & Infrastructure?
Organizations’ business intelligence and analytics infrastructure is often composed of multiple solutions working in conjunction and on top of one another. As standard capabilities like data acquisition, storage, and management become commonplace, providers are experimenting with solutions that leverage more advanced capabilities to reduce costs and improve outcomes. This report validates those advanced capabilities, explores the healthcare outcomes being achieved by vendors’ clients with the most advanced usage of their solutions, and attempts to provide some helpful categorization in a market with a lot of options and historically little transparency.
Industry Insight & Context
HEALTHCARE BUSINESS INTELLIGENCE
Organizations’ business intelligence and analytics infrastructure is often composed of multiple solutions working in conjunction and on top of one another. As standard capabilities like data acquisition, storage, and management become commonplace, providers are experimenting with solutions that leverage more advanced capabilities to reduce costs and improve outcomes. This report validates those advanced capabilities, explores the healthcare outcomes being achieved by vendors’ clients with the most advanced usage of their solutions, and attempts to provide some helpful categorization in a market with a lot of options and historically little transparency.
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Healthcare Business Intelligence 2018
The Vendor with Deepest Adoption Is . . . Epic?
Epic has, by a significant margin, the deepest adoption of advanced functionalities among their customers with most advanced solution usage. While Epic has not historically been an analytics leader, they do have a track record of high adoption among their customers in new areas of focus. Epic clients are consistently leveraging the vendor’s predictive algorithms for best-practice alerts, readmissions, and decision support.
Advanced Analytics Newcomers Making a Splash
Many healthcare organizations are looking to smaller, focused analytics vendors to supplement their core business intelligence capabilities. Used most often to predict and help prevent patient readmissions, Jvion’s embedded solution is strengthened by vendor-employed clinicians who help customers identify at-risk patients, the factors contributing to their risk scores, and intervention recommendations. Clients using HBI Solutions' risk-stratification methodology report being able to replace otherwise complex and expensive analytics environments for use cases such as prevention of readmissions and ER visits and risk tracking for sepsis, opioid abuse, and other chronic diseases.
Traditional visualization vendors Qlik and Tableau are investing heavily in advanced analytics technologies. Qlik is demonstrating progress as current clients adopt new functionality. KLAS’ Decision Insights data, which draws on customer reports of purchasing decisions, shows Qlik was selected in 4 of the 5 decisions where they were considered. Tableau's customers are also making progress as the vendor accelerates investment with major acquisitions in AI and natural language processing. SAS is historically recognized for their predictive modeling capabilities, and Information Builders is the only vendor with clients that have been validated using native technology for all the core capabilities and advanced analytics functionalities KLAS measured.
Microsoft Waking Up in Healthcare? Premier New Entrant, Again
Microsoft clients are increasingly excited about the future of Power BI. Customers, who are seeing improved outcomes, functionality, and proactivity from Microsoft, describe the solution as fast, flexible, and easy to deploy. They expect the inclusion of R and Python to further improve the product’s performance. The solution is still highly cost effective via flat-fee enterprise agreements, and 100% of surveyed Microsoft customers report that they would buy the solution again and that Microsoft is part of their long-term plans. Premier, an up-and-comer in healthcare analytics back in 2014 due in large part to a partnership with IBM’s Watson, is back with new enterprise and service-line analytics technology. KLAS was able to validate two customers using the solution for waste identification, length-of-stay performance measures and supply-cost usage, and benchmarking in sepsis, COPD, and heart failure.
Highest Performers Improve Patient Care and Reduce Costs; Cerner Still Immature
Dimensional Insight continues to drive outcomes and deliver value, though the solution is still developing when it comes to advanced analytics. KLAS validated customers using Dimensional Insight to improve decision support and pharmacy utilization and to develop innovative strategies for enterprise cost reduction. Also making headway into predictive algorithms, Health Catalyst is shown in Decision Insights data as the likely winner of 3 of the 4 business intelligence decisions where they were considered, though their unique blend of consulting and software works best for organizations that are looking for guidance on achieving specific outcomes. Clients have successfully reduced readmissions, curbed opioid abuse, and significantly reduced length of stay and sepsis mortality, saving millions of dollars in the process.
Epic customers are using the solution’s real-time predictive modeling to develop risk scoring for sepsis and blood clots and to recognize patterns in caregiver behavior and medication administration. Clients say the solution has improved in the last 12 months, especially in regard to its ability to incorporate non-Epic data. Epic's BI solutions can be clunky and at times struggle with accuracy, but many customers are optimistic that the solutions will continue to evolve. Conversely, even Cerner's most advanced clients are just getting started with advanced analytics. With the exception of a demonstrated ability to drive outcomes related to sepsis mortality, Cerner customers (some of whom use other EMRs) report the solution is still immature. They say it lacks a testing environment, that incorporating external data is challenging, that support staff is not fully trained on available functionality, and that Cerner does not yet offer predictive analytics tools.
Promises of IBM Cognos’ Transformative Power Evaporate; Open-Source Technology Threatens Cross-Industry Behemoths
Healthcare organizations surveyed by KLAS, including some using IBM’s newest version 11, are generally dissatisfied with Cognos outside of basic query, extraction, and reporting tools. A lack of functionality and support from IBM means clients must invest significant amounts of their own time and effort to keep the product working. Frequent crashes, poor usability, substandard visualizations and security, and a lack of investment in client relationships have left customers feeling that IBM is abandoning the solution in order to focus on glossier products. KLAS did not target Watson customers for the purpose of this study, but a handful of respondents (some of whom are IBM customers) brought up the promises of Watson’s computing power. They mention difficultly in forming partnerships with IBM and have the perception that IBM isn’t yet contributing to tangible outcomes. Oracle’s promises of more user-friendly functionality aren’t coming to fruition, and clients express frustration that new product lines are simply rebranded upgrades of older solutions for which they’ve already paid. Due to the cost, complexity, and limited functionality of advanced analytics capabilities from traditional, broadly-focused BI vendors (and the upgrades that are often required), organizations are beginning to consider open-source options like Hadoop, Python, or R or cheaper alternatives from Microsoft or organizations' EMR vendors.
This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2024 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.