2021 Best In KLAS Healthcare Artificial Intelligence

When making a core HIT purchasing decision, healthcare organizations must take into account how prospective partners deliver across a variety of key technology areas. This Epic “complete look” provides a high-level analysis of the key products that make up Epic’s enterprise suite. (Other reports in the series do the same for Altera Digital Health [Allscripts] , Evident , MEDITECH , and Oracle Health [Cerner] .)

The potential for artificial intelligence (AI) to transform healthcare has been both championed and challenged. In 2019, KLAS published our first research on healthcare AI data science solutions, exploring healthcare organizations’ clinical, financial, and operational use cases and the early outcomes they were achieving. An update to that research, this report examines how outcomes and customer satisfaction have evolved in the years since. Though progress has been somewhat hamstrung by the financial and operational constraints of COVID-19, many of the organizations interviewed for this research have found results by focusing on the right problems.

The Best in KLAS report recognizes software and services companies who excel in helping healthcare professionals improve patient care. All rankings are a direct result of the feedback of thousands of providers over the last year. A Best in KLAS award signifies to the healthcare IT industry the commitment and partnership that the top vendors should provide. Read the report to see the top-rated medical software and services for 2021. Watch sessions from our first-ever virtual Best In KLAS Award Show to hear from the winning vendors in each segment. View Awards Show Recordings

Decision Insights

Healthcare AI 2020

27 October 20 | Lois Krotz and Ryan Pretnik

The benefits of integrating artificial intelligence (AI) into the healthcare ecosystem are undeniable, † and investment from healthcare organizations is increasing at a fast pace. Yet few organizations have settled on any one AI vendor as their go-forward choice—most use a hodgepodge of solutions to meet their needs. In this report, KLAS examines the recent AI purchase decisions of 47 organizations to determine which vendors are being considered and chosen, which are being replaced, and why provider and payer organizations choose the AI solutions they do (technology? service? healthcare expertise?). Additionally, we share customer satisfaction data from current users of ClosedLoop.ai, DataRobot, Epic, Health Catalyst, Jvion, and KenSci and examine healthcare’s perceptions of the cross-industry AI giants—Amazon, Google, IBM, and Microsoft. † For details about how KLAS defines AI in healthcare, see " Healthcare AI 2019: Actualizing the Potential of Artificial Intelligence ."

Company/solution	Overall score	Total evaluations	Trend (2020-2021)	Culture	Loyalty	Operations	Product	Relationship	Value

Epic Cognitive Computing ( Only)	84.6	n=26	N/A	B	A-	B-	B	B+	B

Jvion Machine	78	n=22	0%	C+	C	C+	C+	A-	B-
	50.0	100.0		*Limited Data

Company/solution	Trend (2020-2021)	Culture	Loyalty	Operations	Product	Relationship	Value

Epic Cognitive Computing ( Only) 84.6 n=26 COMMENTS	N/A	B	A-	B-	B	B+	B
Jvion Machine 78 n=22 COMMENTS	0%	C+	C	C+	C+	A-	B-

Company/solution	Overall performance score	Total evaluations	Culture	Loyalty	Operations	Product	Relationship	Value

ClosedLoop ClosedLoop.ai Healthcare’s Data Science Platform * L	91.7	n=9	A	A	B	B+	A+	A+

Health Catalyst healthcare.ai * L	75	n=7	C	B	C-	D+	C+	B-

Company/solution	Overall performance score	Total evaluations

ClosedLoop ClosedLoop.ai Healthcare’s Data Science Platform * L culture A loyalty A operations B product B+ relationship A+ value A+	91.7	n=9

Health Catalyst healthcare.ai * L culture C loyalty B operations C- product D+ relationship C+ value B-	75	n=7

Healthcare Artificial Intelligence - Data Science Solutions

Past Healthcare Artificial Intelligence - Data Science Solutions Awards

Healthcare Artificial Intelligence - Data Science Solutions

Past Healthcare Artificial Intelligence - Data Science Solutions Awards

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