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Data and Analytics Platforms 2021 Data and Analytics Platforms 2021
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Data and Analytics Platforms 2021
An Early Look at Deep Adopters

author - Ryan Pretnik
Author
Ryan Pretnik
author - Lois Krotz
Author
Lois Krotz
 
September 21, 2021 | Read Time: 9  minutes

The need in healthcare for broader, deeper analytics has increased dramatically, and provider organizations are now looking for consolidated, end-to-end analytics platforms that offer a wide variety of capabilities. To validate what is possible with these solutions, KLAS gave vendors with broad analytics offerings the opportunity to identify their deepest platform adopters. We then interviewed three such organizations for each vendor and validated their adoption across the five pillars of a data and analytics platform (see framework below). To provide additional context as to how vendors perform, this report also includes customer experience data collected from the broader base of platform users.

Data and Analytics Platform Framework

(n=27 deep adopters)

The framework below outlines the five pillars of a data and analytics platform as well as the basic and advanced capabilities included within each pillar. See the full report for a detailed definition of each capability as well as a vendor-specific look at validated adoption.

data and analytics platforms framework

Capability Validation from Deep Adopters

For each measured platform, three deep adopter organizations were asked to validate their use of the various data and analytics capabilities in the platform framework. These organizations were identified by their vendors as some of their most progressive and comprehensive platform users, and their early insights are intended to help peers understand what is possible at the cutting edge of this technology. Readers should note that these customers likely experience deeper adoption and partnership than a vendor’s broader customer base.

Cerner, Epic & Health Catalyst See Deepest Adoption among Established Analytics Solutions

Cerner’s deep adopters validate adoption of 100% of the basic platform capabilities and 86% of advanced capabilities (not validated are supervised machine learning, NLP, and system ROI calculation). Customers highlight Cerner’s data-ingestion capabilities and services and describe them as a standout strength for the vendor. Deep adopters report deeper advanced analytics adoption than some other customer bases, with most leveraging predictive, prescriptive, and geospatial analytics.

100% of the basic capabilities have been adopted by at least one of Epic’s deep adopters; among the advanced capabilities, only NLP and system ROI calculation have not been validated. Though all deep adopters use Epic for predictive analytics, not all leverage Epic’s machine learning, partially due to difficulty integrating non-Epic data and to a lack of APIs to connect to other databases.

All three of Health Catalyst’s deep adopters leverage the vendor to aggregate clinical, financial, and operational data, and they report broad adoption of the advanced platform capabilities. Data management areas—including data stewardship workflows, data lineage, and data life cycle management—see lower adoption compared to other vendors. Two deep adopters say the solution’s prebuilt healthcare applications add great value.

Deep adopters of Dimensional Insight report particularly strong adoption of data aggregation, data management, and analytics capabilities. Adoption of advanced analytics is low compared to the other established solutions—no deep adopters validate using supervised ML, unsupervised ML, or prescriptive analytics. Areas for improvement include more visualization and, for larger clients, the ability to handle bigger data sets.

Depth of adoption for Information Builders (who was recently acquired by TIBCO) is lower compared to that of other long-term players. Adoption of data management capabilities is deep, but adoption in the remaining pillars is below average, particularly in advanced analytics—no clients validate use of ML or NLP, and only one client reports use of predictive analytics. Outside of the three deep adopters, no additional customers responded, meaning Information Builders does not meet the data threshold required for inclusion in the “Performance Insights” section.

depth of adoption

Among Newcomers, Innovaccer Has Deepest Adoption

Compared to the more longstanding solutions above, four data platforms have more recently emerged as viable options. Innovaccer and Arcadia.io have expanded their data sources and capabilities beyond population health management (PHM) and value-based care (VBC) to create broader analytics offerings. Alteryx, a cross-industry analytics automation platform vendor, has increased their healthcare focus in recent years. Starting from a data archiving background, Clearsense is beefing up their capabilities to include analytics.

Deep adopters of Innovaccer report high adoption across all key pillars except advanced analytics. Compared to other customer bases, Innovaccer clients report deeper adoption of underlying components—all interviewed deep adopters are using FHIR, APIs, analytics process automation, operationalization of analytics, and security features. Deep adopters report adoption of 100% of the basic capabilities. They note that in addition to InData—the platform’s foundation—there are various PHM applications that help bring meaningful insights to the point of care, regardless of EMR.

Arcadia.io’s interviewed deep adopters—two large clinics and one ACO—report adoption of 100% of the basic capabilities. Across the pillars, use of advanced capabilities isn’t as deep, especially for machine learning. Customers highlight the ability to ingest data from all sources, especially clinical and claims sources.

Alteryx customers highlight several unique features, including the solution’s ability to automate workflows, perform many SQL functions, and enable the use of multiple programming languages in the same platform. Only one of the three interviewed deep adopters reports leveraging the reporting and visualization capabilities; the other two feel the tools are not sufficiently mature.

Validated depth of adoption is lower among Clearsense’s deep adopters. The system’s ability to ingest, curate, and harmonize data from various sources is seen as a top feature. The reporting/dashboards and advanced analytics are still in development, though clients are optimistic about leveraging the ML technology more for prediction.

Performance Insights from Platform Users

To provide helpful context to the validation data shared above, the sections below provide customer experience insights collected from organizations within each vendor’s broader base of platform users (including deep adopters).

Partnering, Value Consistently Generate High Satisfaction with Dimensional Insight; Cerner Has Great Potential but Overpromises

overall performance vs depth of adoption

Cerner | Despite continued functionality development (e.g., Snowflake and enhanced security features) and high energy among deep adopters, struggles to deliver consistently, and 40% of respondents report overall dissatisfaction. While some frustration stems from product quality, functionality, or support issues, the more common complaint is overpromising on timelines and features, leading 47% to say Cerner does not keep promises. There is some optimism that Cerner is starting to listen to customer concerns and make needed changes. Early users of Snowflake (a cloud database platform) are complimentary of the added speed and process power.

Dimensional Insight | Customer base composed mostly of midsize to small organizations; a handful of larger customers have been validated. Generates high loyalty and excitement with customer-centric approach; all respondents are satisfied or highly satisfied. Seen as a partner who keeps promises and seeks to understand customer needs. Integration is a strength. Solution is seen as a great value, especially for smaller organizations. Many customers would like better, more specific training to mitigate what can be a steep learning curve.

Epic | Customers consistently report positive experience and note that while functionality may be limited, Epic doesn’t oversell what the system can do. Not surprisingly, highlighted benefits include integrated analytics tools and system consolidation. Viewed as a partner, with support personnel described as smart, quick learners. Customers report receiving more features and models and are hopeful Epic will better integrate external data. Due to some immature tools, solution is not seen as up to par with some other offerings. A handful of customers note that Epic takes longer than expected to incorporate development requests.

Health Catalyst | Has large number of customers. Highlighted for strong focus on understanding customer needs to better achieve desired outcomes. The solution and Health Catalyst’s consultants drive results by integrating disparate data to produce actionable insights. A highly engaged partner that fosters a strong support culture and is seen as having a vested interest in customer success. Several interviewed customers are struggling overall—common concerns include cost, unmet timelines, and complex, disorganized implementations.

Among Newcomers, Alteryx Leads in High-Focus Areas of Functionality and Outcomes

Not surprisingly, in emerging markets like data and analytics platforms, provider organizations are eager for solutions that can keep up with their evolving functionality needs and drive tangible outcomes. Alteryx does well in both areas, with customers specifically highlighting that the software allows the use of multiple programs and languages and can be used enterprise-wide. Several customers report achieving high value with Alteryx because the solution is scalable, eliminates the need for some third-party tools, and helps drive tangible outcomes by improving staff efficiency. Alteryx’s AI capabilities receive mixed reviews, and the reporting and dashboards don’t meet all needs.

The remaining three vendors with limited data do fairly well overall, but each has at least one highly dissatisfied customer, indicating the need for these growing companies to deliver more consistently across organizations.

Satisfied Clearsense customers describe the vendor’s personnel as smart, innovative, and trustworthy, saying their flexibility in meeting customers’ specific needs has driven positive outcomes. Clearsense is newer to the market but has partnered with some very large organizations to test and develop their capabilities. Organizations feel the vendor’s tools and process are still maturing and lack certain capabilities, such as data science, reporting, and dashboarding.

Some Arcadia clients highlight the vendor’s data experts as a value-add that drives outcomes: these experts are able to help solve data structure issues and help customers understand how to use the data. Despite the platform’s data integration capabilities, a few customers report some functionality concerns, including data quality issues, the cost to connect different platforms, and the data connectors taking longer than promised to build. While Arcadia provides visualization and reporting through their services, customers would like more robust capabilities to create these things themselves.

Innovaccer customers say the prebuilt applications and templates with healthcare content are of great value in driving outcomes. Data ingestion and automation of integration workflows are key strengths. A commonly cited weak spot is the need for more predictive analytics. Innovaccer is the only vendor with an offshore support model, and customer feedback is mixed.

drives tangible outcomes and product has needed functionality

About This Report

The insights in this report are based on two types of customer insights: (1) capability validations from deep adopters, and (2) performance insights from platform users (including deep adopters).

Capability Validation from Deep Adopters

For each measured platform, three deep adopter organizations were asked to validate their adoption of the various data and analytics capabilities in the platform framework. These organizations were identified by their vendors as some of their most progressive and comprehensive platform users, and their early insights are intended to help peers understand what is possible at the cutting edge of this technology. Readers should note that these customers likely experience deeper adoption and partnership than a vendor’s broader customer base.

Performance Insights from Platform Users

This report also includes customer experience data collected from organizations within each vendor’s broader base of platform users (including the interviewed deep adopters). The feedback was collected over the last 12 months via KLAS’ standard quantitative evaluation for healthcare software and is intended to provide helpful context to the validation data from deep adopters.

KLAS’ standard quantitative evaluation for healthcare software is composed of 16 numeric ratings questions and 4 yes/no questions, all weighted equally. Combined, the ratings for these questions make up the overall performance score, which is measured on a 100-point scale. The questions are organized into six customer experience pillars—culture, loyalty, operations, product, relationship, and value.

customer experience pillars software

Sample Sizes

Sample sizes displayed throughout this report (e.g., n=16) represent the total number of unique customer organizations interviewed for a given vendor or solution. However, it should be noted that to allow for the representation of differing perspectives within any one customer organization, samples may include surveys from different individuals at the same organization. Ratings from these individuals are aggregated in order to prevent any one organization’s feedback from disproportionately impacting a solution’s score. The table below shows the total number of unique organizations interviewed for each vendor or solution as well as the total number of individual respondents.

Some respondents choose not to answer particular questions, meaning the sample size for any given vendor or solution can change from question to question. When the number of unique organization responses for a particular question is less than 15, the score for that question is marked with an asterisk (*) or otherwise designated as “limited data.” If the sample size is less than 6, no score is shown. Note that when a vendor has a low number of reporting sites, the possibility exists for KLAS scores to change significantly as new surveys are collected.

deep adopter interviews

Criteria for Measurement in Data and Analytics Platforms Segment

To be measured in this segment, vendors must meet the following criteria:

  • KLAS must have validated adoption of all basic capabilities in the data aggregation, data management, and analytics pillars. In addition, KLAS must have validated adoption of at least some capabilities in at least one of the remaining two pillars (advanced analytics and underlying components).
  • KLAS must have validated at least six live customers using the solution in a platform capacity (i.e., customer has adopted at least some capabilities within each of the five pillars).
customer base estimates
author - Elizabeth Pew
Writer
Elizabeth Pew
author - Natalie Jamison
Designer
Natalie Jamison
author - Natalie Jamison
Project Manager
Natalie Jamison
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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.

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