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CHILMARKR E S E A R C H
MARKET TRENDS REPORT
2019 PROVIDER ANALYTICS
CURRENT SOLUTIONS AND TOOLSFOR HEALTHCARE DELIVERY
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ABOUT CHILMARK RESEARCH
Chilmark Research is a global research and advisory firm whose sole focus is the market for healthcare IT solutions.
This focus allows us to provide our clients with the most in-depth and accurate research on the critical technology and
adoption trends occurring throughout the healthcare sector. Areas of current research focus include among others:
Clinician Network Management, Cloud-computing Models for Healthcare, IT-enabled Accountable Care Organiza-
tions, Care Coordination, Adoption of Mobile Technology and Consumer-facing Health & Wellness Appli¬cations and
Services.
Using a pragmatic, evidence-based research methodology with a strong emphasis on primary research, Chilmark Re-
search structures its research reports to serve the needs of technology adopters, consultants, investors and technol-
ogy vendors. In addition to reports for the general market, Chilmark Research performs research for clients based on
their specific needs. Such research has included competitive analyses, market opportunity assessments, strategic as-
sessment of market and vendors for partnership and/or acquisition.
In 2012, Chilmark Research launched the Chilmark Advisory Service (CAS) in direct response to clients’ request for a
continuous feed of research on the most pertinent trends in the adoption and use of healthcare IT. This is an annual
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crosoft, and Thomson Reuters to name a few. It is our hope that at some future date we will have the pleasure to serve
you as well.
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The information in this report is proprietary to and copyrighted by Chilmark Research. No part of this report may be reproduced or distributed without prior permission of Chilmark Research. The information contained within the report is not intended as a solicitation of an offer to buy or sell any investment or other specific product. All information and opinions expressed in this report were obtained from sources believed to be reliable and in good faith. No representations or warranty expressed or implied is made as to its accuracy or completeness. Trademarked and service marked names appear throughout this report. Rather than use a trademark or service mark symbol with every occurrence, names are used in an editorial fashion, with no intention of infringement of the respective owner’s trademark or service mark.
TABLE Of CONTENTS
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TABLE OF CONTENTS
CHAPTER 1: EXECUTIVE SUMMARY 9
Key Takeaways ....................................................................................................................11
CHAPTER 2: PROVIDER ANALYTICS TECHNOLOGIES AND MARKETS 12
Analytics Across the Provider Enterprise .....................................................................12
Putting Reports into Practice ...................................................................................12
Healthcare Analytics Technology Review .....................................................................12
Mainstream Analytics ................................................................................................12
Electronic Health Records and Claims Data .............................................................................. 13Other Data Sources for Analytics ................................................................................................ 13
Moving Applications from Descriptive to Prescriptive .........................................14
Advanced Analytics....................................................................................................15
AI and ML ........................................................................................................................................... 15Data Science ...................................................................................................................................... 15Big Data .............................................................................................................................................. 16Challenges for Advanced Analytics.............................................................................................. 16
Healthcare Provider Use Cases .......................................................................................17
Hospital Use Cases ...................................................................................................17
Non-hospital Use Cases ............................................................................................18
Vendor Types .......................................................................................................................20
EHR Vendors ..............................................................................................................20
Independent Vendors ................................................................................................21
Claims Analytics Vendors ..........................................................................................21
Analytics Maturity ..............................................................................................................22
CHAPTER 3: VENDOR EVALUATIONS AND PROFILES 24
Chilmark Bearing – Provider Analytics ..........................................................................24
Vendor Letter Grades ........................................................................................................25
Detailed Vendor Ratings ...................................................................................................25
Product Capabilities Ratings.....................................................................................25
Vendor Product Capabilities .....................................................................................28
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Market Execution Ratings .........................................................................................29
Vendor Market Execution Ratings ...........................................................................30
Vendor Profiles ....................................................................................................................31
Inclusion Criteria ........................................................................................................31
VENDOR PROFILES 32
Allscripts ........................................................................................................................................................ 32
Arcadia.io ....................................................................................................................................................... 34
athenahealth ................................................................................................................................................ 36
CareEvolution ............................................................................................................................................ 38
Cerner Corporation ................................................................................................................................. 40
Change Healthcare ................................................................................................................................... 42
eClinicalWorks ............................................................................................................................................ 44
Epic Systems Corporation ..................................................................................................................... 46
forward Health Group ........................................................................................................................... 48
Health Catalyst ........................................................................................................................................... 50
HealthEC ....................................................................................................................................................... 52
IBM Watson Health .................................................................................................................................. 54
Innovaccer .................................................................................................................................................... 56
Lightbeam Health Solutions .................................................................................................................. 58
MedeAnalytics ............................................................................................................................................ 60
Medecision ................................................................................................................................................... 62
Medical Information Technology, Inc. ............................................................................................... 64
NextGen Healthcare ................................................................................................................................ 66
Optum ............................................................................................................................................................ 68
Philips Wellcentive .................................................................................................................................... 70
SCIO Health Analytics ............................................................................................................................ 72
SpectraMedix ...............................................................................................................................................74
SPH Analytics .............................................................................................................................................. 76
ABOUT THE AUTHORS 78
Brian Murphy .......................................................................................................................78
Matthew Guldin ..................................................................................................................78
APPENDIX A: SCOPE AND METHODOLOGY 79
APPENDIX B: ACRONYMS USED 80
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TABLES AND FIGURES
CHAPTER 1: EXECUTIVE SUMMARY 9
figure 1.1: Provider Analytics Vendors and Vendor Types ..................................11
CHAPTER 2: PROVIDER ANALYTICS TECHNOLOGIES AND MARKETS 12
Table 2.1: Other Data Sources for Analytics ..........................................................13
figure 2.1: Example Use Cases of Mainstream and Advanced Analytics ...........14
Table 2.3: Healthcare Provider Analytics Venue Characteristics ........................17
figure 2.2: Hospital Analytics Use Cases Heat Map .............................................18
figure 2.3: Non-hospital Analytics Use Cases Heat Map ....................................19
figure 2.4: Vendor Types and Vendors Profiled ....................................................20
Table 2.4: EHR Vendors Profiled ..............................................................................21
Table 2.5: Independent Vendors Profiled................................................................21
Table 2.6: Claims Analytics Vendors Profiled .........................................................22
figure 2.5: Relative Maturity of Vendor functionality by Venue .........................23
CHAPTER 3: VENDOR EVALUATIONS AND PROFILES 24
figure 3.1: Chilmark Bearing – Provider Analytics ................................................24
Table 3.1: Vendor Letter Grades ..............................................................................25
Table 3.2: Product Capabilities Harvey Ball Key ....................................................27
Table 3.3: Product Capabilities Rating ....................................................................28
Table 3.4: Market Execution Harvey Ball Key ........................................................29
Table 3.5: Market Execution Ratings .......................................................................30
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Chapter 1: Executive SummaryThe scope of this report is the healthcare provider enterprise and any application of analytics within it. In recent years, analytics technology has been widely deployed to support the transition from fee-for-service (FFS) to val-ue based care (VBC). The variety of pay-for-performance (P4P), pay-for reporting (P4R), and risk- and reve-nue-sharing programs with payers is leading provider organizations to invest in applications that help measure and monitor costs, quality, and utilization, as well as understand the risks of the populations they serve. But the applications for analytics are broader than just VBC. Providers recognize that taking a more systematic approach to analytics and reporting can help yield higher value from their data for both existing and new applications.
Providers have many legacy point and departmental reporting solutions in addition to VBC and population health management (PHM) analytics. These applications use data from the providers’ diverse and siloed applications to assist with revenue optimization, operational efficiency, and improving patient care.
One area of increasing concern for provider organizations flows from uncertainty about the pace of transforma-tion from volume to value. Providers optimize their internal cost structures based on historical FFS revenue streams. Whether those cost structures will support a higher proportion of value-based payments is unclear. Providers are increasingly interested in planning tools to help them manage their costs and budgets for a rapidly changing payment system. Hospitals and health systems commonly use such tools while other venues have few to no options.
This report describes and evaluates the available analytics solutions from 23 vendors. They not only address VBC and PHM requirements but also enable performance improvement efforts across a provider’s enterprise. It reviews the current state of the market, maturity of solutions and describes in detail vendor’s solution capabili-ties for meeting the needs of their provider customers.
KEY TAKEAWAYSReporting is and will remain the “killer app” for analytics.
> Cost, quality, and utilization reports and dashboards are widely available and widely used, if not widely respected.
> Embedding analytic insights directly in applications workflow is growing but far from widespread.
Analytics for value-based care is the primary driver of adoption.
> Analytics for tracking performance in value-based contracts was the pioneer application for many healthcare users.
> Experience with value-based contracts has spawned demand for other enterprise performance im-provement purposes.
> Many vendors are consolidating point and departmental reporting solutions with value-based ana-lytics offerings onto a single analytics platform.
Advanced analytics is growing but the strongest interest is from larger organizations.
> Artificial intelligence (AI), machine learning (ML), and data science techniques and technologies are seeing more usage in vendor offerings.
> Big data technologies are widely used by analytics vendors.
> No vendor has a leading advanced analytics solution.
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> Large healthcare enterprises are adopting advanced analytics while smaller enterprises are skeptical about its promise.
> Advanced analytics adopters are pursuing predictive and prescriptive goals.
Taking action based on analytics is still a challenge.
> Translating insights into action is hard to do at the patient level and at the population level.
> While EHR vendors have long pushed analytics results into the clinician’s EHR, independent vendors increasingly support this capability.
> The problem of “actionability” is more complex than simply presenting data to a user.
Providers will find that claims analytics offerings enable different insights, if they would try them.
> Providers are still leery of payer-oriented ways of looking at data.
> Claims analytics offerings deliver precise insights into the drivers of cost, utilization, and clinical quality performance.
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figure 1.1: Provider Analytics Vendors and Vendor Types
Arc
adia
Care
Evol
ution
Chan
ge H
ealth
care
Forw
ard H
ealth
Group
Health Catalyst
IBM Watson
Health
Innovaccer
MedeAnalytics
Lightbeam
MedecisionPhilips
SCIO-EXLSpectraMedix
SPH Analytics
SCIO
-EXL
Opt
um
Med
ecisi
on
Med
eAna
lytic
s
IBM
Wats
on
Health
Change Healthcare
CareEvolution
Arcadia
EHR
Independent
Claims Analytics
NextGen
Meditech
Epic
eCW
Cerner
athenahealth
Allscripts
ExECUTIVE SUMMARy
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Chapter 2: Provider Analytics Technologies and MarketsANALYTICS ACROSS THE PROVIDER ENTERPRISE Healthcare’s historic transformation from volume to value is a primary driver of provider adoption of analytics solutions. Analytics support for pay for reporting (P4R), pay for performance (P4P), ACOs, bundled payments, and Medicaid plans have driven the sales of analytics offerings. Providers turned to analytics vendors and their products to help them reduce Medicare readmissions, meet the targets of the Medicare Shared Savings Program (MSSP), and the requirements of state-based managed care programs.
For many healthcare users, their first experience with analytics and reporting was in the context of a value-based contract. At an organizational level, value-based payments (VBP) triggered a new understanding by providers of the benefits of performance improvement generally. As a consequence, many providers are leveraging this in-vestment and using the technology for diverse performance improvement purposes beyond value-based care.
Putting Reports into PracticeThe more astute, or honest, vendors point out that analytics is great at identifying areas for improvement but that clinicians and administrators struggle to address them. HCOs, seeking to establish a more uniform set of clinical practices as they pursue performance improvement goals, want to use data to educate clinicians about better ways to organize and manage care. Many vendors refer to their reports and dashboards as the basis for a “conversation” with individual providers, usually about some form of performance improvement. A consistent observation of providers is that analytics and reporting are helpful tools but it is not always straightforward to get clinicians to act based on what reports or dashboards tell them.
HEALTHCARE ANALYTICS TECHNOLOGY REVIEWMost of the products in this report are vendor-hosted and offered on a Software-as-a-service (SaaS) basis. Over the last five years, cloud-hosted solutions became acceptable. A plurality of vendors profiled in this report use major cloud vendors such as Amazon Web Services (AWS) and Microsoft Azure to host their offerings.
Mainstream AnalyticsMainstream healthcare analytics relies on commercial databases, programming tools, and BI report writers. Most of the vendors in this report use this technology to deliver a subscription-based, hosted set of reports and dash-boards to their healthcare customers.
The vendors manage the ingestion, processing, and integration of the diverse data feeds that fuel the applica-tions. They clean, normalize, and standardize the data prior to loading it into a relational database for use by ap-plications. The vendors use standard extract, transform, and load (ETL) tools and approaches during this process. Most maintain an enterprise data warehouse (EDW) from which they build data marts for standard and custom-er-specific reporting and dashboard applications. In a diminishing minority of cases, all or part of the above runs in the customer’s data center.
This overall technology approach is more than equal to most of the demands of healthcare. It can readily incor-porate new data sources as they become available. It is a cost effective way to address the demand for reporting among every class of end-users. It allows vendors to deliver affordable solutions for even the smallest organiza-tions. ...
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See TOC for contents of full report.
ExECUTIVE SUMMARy
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About the AuthorsBRIAN MURPHY - Director of research
Brian Murphy joined Chilmark Research as an industry analyst in August 2012 and brings a wealth of experience to the table. He is an outspoken advocate for true interoperability being the key to unlocking the potential of health IT and has centered the majority of his research efforts with Chil-mark around this subject. He also currently heads research for the Analyt-ics domain.
Brian has worked in the IT business for over 25 years, beginning his career in the field-sales organization of IBM. He then joined Yankee Group as an analyst, where he managed an enterprise software service and led re-search on the dynamics of the database market. Leaving Yankee, Brian joined Eclipsys prior to its acquisition by Allscripts in 2010. At Eclipsys, Brian worked with product managers to refine and harmonize value prop-ositions in light of the organization’s broader goals.
Brian is a graduate of both Harvard College and Suffolk Law School. When not thinking about health IT, he’s a runner and armchair Boston historian.
MATTHEW GULDIN - senior analyst
Matt Guldin brings with him a diverse array of knowledge and experience about the healthcare industry having worked in a variety capacities includ-ing pharmaceutical consulting, medical education, and academic research. Prior to working with Chilmark Research in his current role, Matt worked as an IT analyst monitoring and analyzing emerging trends, technologies, and market behavior in the Healthcare IT industry (HIT) in North America. He worked with such major industry brands as Lumeris, Thomson Reuters and Siemens. It was with the recent Cerner acquisition of Siemens that brought Matt back to the Chilmark family.
Matt is interested in how the HIT industry is gradually evolving from one that accomplished basic administrative and clinical functions to one that begins to enable more dramatic transformational change across the health-care industry. Mr. Guldin has also held positions at the Managed Health Network (Health Net), Tufts Health Care Institute, the Boston University School of Public Health, and Metaworks, Inc. He holds a Master’s in Public Health with a concentration in Health Policy and Management from the Boston University School of Public Health and a B.A. in Biology from Bos-ton University.
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Appendix A: Scope and MethodologyTo compile this report, Chilmark Research combined extensive primary and secondary research techniques to create a composite profile for each vendor. Primary research was divided into two distinct steps, beginning with soliciting targeted vendors for their involvement in the research.
We asked participating vendors to complete a detailed questionnaire whose purpose was to collect qualitative and quantitative information about the company and the markets it serves. Questions included among others: 2018 revenue, number of employees, target market, number of healthcare entities currently using its solution, and more in-depth questions regarding solution features and functions.
Upon receiving the completed questionnaire, we conducted a follow-up interview with each vendor. These in-depth telephone interviews typically lasted 60-90 minutes and were for a demonstrations and to clarify respons-es to the questionnaire. This portion of the research effort also focused on topics that cannot easily be captured within the context of a written questionnaire including competitive positioning, product roadmap, partnership strategy, and which solution features are most attractive to prospective customers.
Chilmark Research performed a final analysis of the vendors via secondary research and telephone interviews with end users and consultants that have advised on, deployed, or used a vendor’s system. This information was compiled to provide the in-depth reviews and ratings of the profiled vendors. Prior to publication, all vendors were given an opportunity to review their profile narratives (not rankings) for fact checking. Their comments and feedback were considered and where relevant, incorporated into the final profile narratives.
In compiling this extensive report, Chilmark Research maintained absolute objectivity throughout the entire re-search process (sometimes to a vendor’s chagrin) and it is our sincere hope that this report brings greater clarity to this developing market.
ACRONyMS USED
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Term DefinitionACG Adjusted Clinical Groups
ACO Accountable Care Organization
AMC Academic medical center
API Application programming interface
BI Business intelligence
BPCI Bundled Payments Care Initiative
CHF Congestive heart failure
CIN Clinically integrated network
CM Case management
CMS Centers for Medicare and Medicaid Services
COPD Chronic obstructive pulmonary disease
CPT Current Procedural Terminology
CQM Clinical quality metric
CVD Cardiovascular disease
DRG Diagnosis-related group
DM Disease management
DSRIP Delivery System Reform Incentive Payment
EBM Evidence-based medicine
ED Emergency department
EDW Enterprise data warehouse
EHR Electronic health record
EMR Electronic medical record
ETL Extract, transform, and load
FFS fee-for-service
FHIR fast Healthcare Interoperability Resources
HCC Hierarchical Condition Category
HCO Healthcare organization
HEDIS Healthcare Effectiveness Data and Information Set
HHS Health and Human Services
HIE Health information exchange
HIT Healthcare information technology
HL7 Health Level 7
ICD International Classification of Disease
IDN Integrated Delivery Network
IPA Independent practice association
IQR Inpatient Quality Reporting
IRF Inpatient rehabilitation facility
IT Information technology
Term DefinitionLTPAC Long term and post-acute care
MA Medicare Advantage
MACRA Medicare Access and CHIP Reauthorization Act
MDS Long-Term Care Minimum Data Set
MIPS Merit-based Incentive Payment System
MSSP Medicare Shared Savings Program
MU Meaningful use
NCQA National Committee for Quality Assurance
NPR Net patient revenue
NQF National Quality forum
ONC Office of the National Coordinator
OON Out of network
P4P Pay for performance
P4R Pay for reporting
PAC Post-acute care
PBM Pharmacy benefits manager
PCMH Patient-centered Medical Home
PEPM Per employee per month
PM Practice management
PMPM Per member per month
PMPy Per member per year
PPPM Per provider per month
PPS Performing Provider System
PQRS Physician Quality Reporting System
RCM Revenue cycle management
RDBMS Relational Database Management System
REST Representational state transfer
SaaS Software-as-a-service
SDoH Social determinants of health
SNF Skilled nursing facility
SNOMED Systematized Nomenclature of Medicine
SQL Structured query language
TJC The Joint Commission
UM Utilization Management
VBC Value-based care
VBP Value-based Payment
VBR Value-based Reimbursement
Appendix B: Acronyms Used
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