Health Catalyst is excited to announce the Patient Safety Monitor™ Suite: Surveillance Module, the industry’s first comprehensive patient safety application to use predictive and text analytics combined with concurrent clinician review of data to help monitor, detect, predict and prevent threats to patients before harm can occur. The Patient Safety Monitor Suite leverages AI and machine learning to quickly identify patterns of harm, learn from those patterns, and suggest strategies to eliminate patient safety risks and hazards. This potent combination of AI, machine learning, text analytics and near real-time data from multiple IT systems enables the Patient Safety Monitor Suite to predict harm events and guide clinical interventions while the patient is still in the hospital. In this webinar you will learn how the Surveillance Module can provide: * Greater clarity to the types, numbers, and causes of adverse events, enabling leaders to quickly prioritize improvement efforts. * Improved patient outcomes such as reduced morbidity, mortality, and length-of-stay, and increased quality-of-life and satisfaction. * Bottom-line cost savings and improved brand recognition related to unnecessary or preventable high-cost care and reduced/eliminated penalties. * The ability for clinicians and infection preventionists to focus on patient care instead of burdensome manual data extraction, aggregation, and reporting.

1. Introducing the
Patient Safety Monitor™ Suite:
Surveillance Module
Stanley Pestotnik, MS, RPh
Vice President, Patient Safety
Catalyst

2. Agenda
Why Patient Safety Matters
Problems & Pain Points
Product Overview
Professional Services
Key Takeaways

3. Agenda
Why Patient Safety Matters

4. © 2018
Health
Catalyst
Patient Safety
4
“…there are some patients
we cannot help, there are
none we cannot harm.”
Arthur L. Bloomfield, MD (1888-1962; Professor of Medicine;
Executive Director Dept of Medicine; Stanford Medical School, 1926-1954

5. © 2018
Health
Catalyst
• Told she had active hepatitis B and advanced cirrhosis at an Air Force
Medical Facility with no additional treatment options available. She
was referred for a liver transplant.
• After consultation at LDS Hospital in Utah she was placed on the liver
transplant waiting list. Past Air Force medical records were
incomplete and illegible in many sections.
• LDSH’s automated trigger-based surveillance system2 prompted a
review of her medication history by Stanley Pestotnik.
• Recurrent/multi-year high-dose use of Macrodantin (nitrofurantoin)
was identified and her attending physicians were notified (chronic
nausea, vomiting, nose bleeds, weight loss and hepatitis).
• Macrodantin use was discontinued and she recovered without the
need for a liver transplant.
Betty Redocto Story1
1Finkelstein, K. E. (1998, September 14 & 28). The Computer Cure. The New Republic.
2DC Classen, SL Pestotnik, et al., Computerized Surveillance of Adverse Drug Events in Hospital Patients, JAMA 1991;266:2847-51
5

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Health
Catalyst
6
Kimberly Hiatt, RN
http://www.nbcnews.com/id/43529641/ns/health-health_care/t/nurses-suicide-highlights-twin-tragedies-medical-errors/

7. © 2018
Health
Catalyst
We are all affected
7
What do all of these stories
have in common?
They are not just
consequences of
medical care. They
are people with a
face and name.
They are someone’s
child, wife, or loved one.
Whether you are the provider, the patient,
or the loved one, patient harm affects you.

8. © 2018
Health
Catalyst
• Preventable medical injuries are
on the rise
• There has been 10x more
preventable harm since 1999
IOM report
• 400,000 lives per year
• >$100B annually
• Patient harm is the 3rd leading
cause of death
• <5% of hospitals are measuring
and tracking all-cause harm1
Why Patient Safety?
8
Causes of Death, U.S.
(CDC 2013 Final Data)2
Heart disease
611k
Cancer
585k
Medical
error 251k
COPD
149k
All causes
2,597 k
Suicide
41k
Firearms
34k
Motor
vehicles 34k
Based on our
estimates, medical
error is the 3rd most
common cause of
death in the U.S.
However,
medical error is
not recorded on
U.S. death
certificates.
1Conway PH, Mostashari F, Clancy C. Future of Quality Measurement for Improvement and Accountability. JAMA 2013;309:2215-16.
OIG, Hospital Incident Reporting Systems Do Not Capture Most Patient Harm, HHS, 2012.
2Xu, M.D., J., M.D., Murphy, S. L., B.S., Kochanek, K. D., M.A., & Bastian, B. A., B.S. (2016, February 16).
Deaths: Final Data for 2013 (Rep. No. Volume 64, Number 2). Retrieved https://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_02.pdf

9. © 2018
Health
Catalyst
Patient Safety Events Driving the
Biggest Burden of Disease and Costs
9
• Medication Safety
• Pressure Ulcers
• Diagnostic Safety
• DVT/PE
• Unnecessary
Readmissions
• Falls
• Patient Handoffs
• WPWSWI1
• CLABSI
• CAUTI
• C. diff
• SSI
• Antibiotic Resistance
• HAP/VAP
• Sepsis
• ABX Stewardship
• CPOE Order Sets
• Cut and Paste
• Incomplete Data
• Latent Data
• Inadequate Monitoring
• Loss of Narrative
• Implementation &
Training
Patient Care Infections HIT Workforce
• Psychological Safety
• Burnout
• Resilience
• 2nd Victim
• Turnover
• Human Factors
– Physical Ergonomics
– Cognitive Ergonomics
Direct Costs
Of Care
Litigation and
Penalty Costs
Accreditation
Costs
Human Capital
Costs
Brand and
Marketing Costs
1Wrong patient, wrong site, wrong indication
2Patient Safety in Healthcare, Forecast to 2022 (Rep.). (2018). Frost & Sullivan.
Ltd, R. A. (n.d.). Global Patient Safety And Risk Management Software Market Analysis & Trends - Industry Forecast to 2025.
Retrieved June 4, 2018, from https://www.researchandmarkets.com/research/sv9pdf/global_patient
Overall Impact
$146B
total U.S. cost
burden in 20162
30-70%
are avoidable
Decreased
Bottom-line

10. Agenda
Problems & Pain Points

11. © 2018
Health
Catalyst
Please select your most significant gap(s) in patient safety reporting.
1. Inpatient clinical (e.g. LOS, mortality, readmissions) – 41%
2. Outpatient/ambulatory clinical – 64%
3. Operations (e.g. service line cost/charge metrics, ED wait times, medication
reconciliation rates, instructions given at time of discharge) – 45%
4. Regulatory/reporting (e.g. HACs) – 36%
5. Severity of illness (e.g. Case Mix Index, RAF, other coding) – 43%
Poll Question
11

12. © 2018
Health
Catalyst
Health Catalyst Survey Results
12
7%
33%
50%
55%
46%
67%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Other
Severity of illness
Regulatory/reporting
Operations
Outpatient/ambulatory clinical
Inpatient clinical
462
Total Participants

13. © 2018
Health
Catalyst
What prevents you from achieving your patient safety goals today?
Select all that apply.
1. Lack of resources (e.g. staffing, budget) – 43%
2. Organization structure, culture, or priorities – 45%
3. Ineffective information technology (e.g. data quality, patient matching, reporting) –
47%
4. Lack of real-time warnings for possible harmful events – 65%
5. Lack of reimbursement for safety initiatives – 29%
Poll Question
13

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Health
Catalyst
Health Catalyst Survey Results
14
6%
9%
10%
14%
16%
19%
27%
0% 5% 10% 15% 20% 25% 30%
Other
Changes in patient population and practice settings
Lack of reimbursement for safety initiatives
Lack of real-time warnings for possible harmful events
Ineffective information technology
Organization structure, culture, or priorities
Lack of resources

15. © 2018
Health
Catalyst
What are your sources for patient safety data? Select all that apply.
1. Retrospective coding
2. Trigger tool
3. Manual audits
4. Hospital acquired infection surveillance
5. Voluntary incident reporting system
Poll Question
15

16. © 2018
Health
Catalyst
Health Catalyst Survey Results
16
10%
82%
67%
58%
28%
29%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%
Other
Voluntary incident reporting system
Hospital acquired infection surveillance
Manual audits
Trigger tool
Retrospective coding

17. © 2018
Health
Catalyst
• Patient safety management crosses all care settings, care models and
specialty boundaries – very few have special training, knowledge or analytics
in patient safety
• Involves a multitude of causes and risks, including genetic
• Culture plays a pivotal role & tends to be undervalued
• Providers usually don’t have appreciation or insight into the topography
(topography of harm = number, types, root causes) of harms occurring in their
patients or populations
• Organizations rely on voluntary, historical reporting rather than automated,
proactive analytics
• The depth, breadth and timeliness of required data is suboptimal
Summary of Key Pain Points
Advanced analytics and clinical decision support are essential
17
Safety is the
Priority
Quality is the
Standard

18. Agenda
Product Overview

19. © 2018
Health
Catalyst
All-Cause Harm
Surveillance
• PSO Services
• Patient Safety Monitor NPI
Safety
Consultant
• Advanced Clinical
Decision Support
Patient Safety Roadmap
19
Risk
Surveillance
• Data Models and
User Interface
Whole Patient
Measure of Safety
(Clinical, Culture,
Financial, Regulatory &
Improvement –
integration of DOS
clinical apps)
Voluntary
Reporting

20. © 2018
Health
Catalyst
Health Catalyst Patient Safety Solutions
• Monitor all data sources, including text, to
detect and measure all-cause harm events
with precision and fidelity, in a timely manner
• Vendor agnostic but data hungry
• Leverages Data Operating System (DOS™)
• Categorize harm through standardized
clinical assessment1
• Benchmarking advantage
• Communicate harm intelligently to multiple
stakeholders
• Protect harm data from legal discovery
• PSO protection (in process)
20
A sound epidemiologic methodology and robust technology for all-cause harm surveillance
1http://www.ihi.org/resources/Pages/Tools/GlobalTriggerToolImplementationToolkit.aspx

21. © 2018
Health
Catalyst
Health Catalyst Patient Safety Solutions
• Predict harm, using machine
learning and other techniques
including genomics
• Learn from harm to protect future
patients and build a culture of
safety
• Manage and prevent patient
harm by applying advanced
clinical decision support to at-risk
populations within the clinical
workflow
21
A sound epidemiologic methodology and robust technology for all-cause harm management

22. © 2018
Health
Catalyst
Patient Safety Monitor™ Suite:
Primary, Secondary and Future Users
22
Quality / Safety / Risk
Clinical Team (MD, RN, PharmD etc.)
Service Line & Care Managers
Primary Clinical Users - Interventionists
C-Suite / Board
Secondary Users - Analytics
Patient / Home
Front-line Caregivers across the
continuum (MD, RN, PharmD, etc.)
Future Users

23. © 2018
Health
Catalyst
Key Differentiators
All-cause harm literature-based trigger libraries
23
Patient Care
e.g. Return to
surgery, post-
op MI
Surgical
e.g. Patient
fall, intubation,
ICU readmit
e.g. Positive
blood/urine
culture, MRSA
Hospital Acquired
Infection
e.g. Morphine
milligram
equivalents
Pain Management
e.g. Digoxin or
Naloxone
administration
Medication
Reversal
e.g. Possible
acute kidney
injury
Renal Injury
e.g. Decrease in
hemoglobin, PTT
Coagulation
e.g. Glucose levels,
administration of
glucagon
Glycemic
Management
e.g. Total bilirubin,
elevated drug levels,
infiltrations
Pediatric
e.g. Pre-term birth,
delivery method
Perinatal
e.g. Unplanned
readmission, ER
after hospital stay
Readmission

24. © 2018
Health
Catalyst
Key Differentiators
24
Systems & Holistic
Approach to Patient
Safety
• All-cause harm analytics
strategy
o Patient, location and
population – across the
continuum of care
• Tactical flexibility to
address specific harms
• Enhanced accuracy of
predictions about harm
events
• DOS™ platform
• Sick Data, Health Data,
Activity Data (includes
narrative, numeric, signal,
picture etc.)
• AI, NLP, etc.
Clinical Data & Clinical
Logic/Algorithms
• DOS™ normalized and
optimized for surveillance
and decision support
• Time and point-of-care
orientation
o Support time-driven and
event-driven processing
o Pull and push notification
• Root-cause,
epidemiologic based
methodology
• Configurable to multiple
stakeholders and
situations
o Rules triggered by events,
views are triggered by
situations, intelligent
options throughout
Automated Guidance4,5
• Outputs are actionable,
concise, patient-, disease-
or task-specific
• Intelligent filtering of
knowledge and patient
data (smart views)
• Knowledge is human-
readable and machine
computable
o Infrastructure makes
computable knowledge
findable, accessible,
interoperable and reusable
(FAIR6 criteria)
• What to do
• Why to do it
1Patient Safety: achieving a new standard of care; National Academy Press, 2004
2https://www.healthit.gov/topic/safety/safer-guides
37-step Framework for Outcomes Improvement, Health Catalyst
4Improving Outcomes with Clinical Decision Support – An Implementer’s Guide, 2nd ed.
5SL Pestotnik, Pharmacotherapy, 2005, Vol. 25(8):1116-25
6https://www.force11.org/fairprinciples
Socio-technical
Development
Framework1
• Workflows and
thoughtflow UI (SAFER
Guides2)
• QI-focused professional
services; 10-yr track
record3
• Create highly reliable
organizations by
identifying safety risks,
predicting individual
outcomes, suggesting
process improvement and
promoting a culture of
safety

25. © 2018
Health
Catalyst
The Data Operating System
Data Ingest
Real-time
Streaming
Source
Connectors
Catalyst Analytics Platform Fabric Data Services
Real-time
Processing
Health Catalyst Applications
Data
Quality
Data
Governance
Pattern
Recognition
Hadoop/
Spark
Data Export
Population &
Registry
Builder
Leading
Wisely
Care
Management
Atlas
Client-built
Applications
NLP
Touchstone
Benchmarks
CORUS
Cost
Accounting
Patient
Safety
Measures
Manager
ACO
Financials
Patient
Engagement
HL7
Data Pipelines Metadata
Data Lake
Reusable
Content
AI Models
Third-party
Apps
Artificial
Intelligence
Pipelines
Marketplace
SAMD
& SMD
Fabric Application Services
Terminology
& Groupers
EMR
Integration
Security, Identity
& Compliance
Patient & Provider
Matching
Value Sets
& Measures
Standard,
Extensible
Data Models
RegistriesFHIR
HL7
Analytic
Accelerators

26. 200+ Data Sources and growing
26
1. 2010 US Census Detail for State of Colorado
2. 835 – Denials
3. Adirondack ACO Clinical Data from HIXNY (HIE)
4. Adirondack ACO Medicare
5. ADT HIE Patient Programs - Patient Tracking
6. Aetna - Claims
7. Affiliate Provider Database
8. Affinity - ADT/Registration
9. Affinity - Costing
10. Affinity - Hospital Billing
11. AHRQ Clinical Classification Software (CCS)
12. All Payer All Claims (certain States) ---In process UT, CO, MA
13. Alliance Decision Support
14. Allscripts - Ambulatory EMR Clinicals
15. Allscripts - Ambulatory Practice Management
16. Allscripts - Case Management
17. Allscripts - Patient Flow
18. Allscripts (EPSi) - Budget
19. Allscripts (EPSi) - Costing
20. Allscripts (TSI) - Costing
21. Allscripts EHRQIS - Quality
22. Allscripts Enterprise/Touchworks - Ambulatory EMR
23. Allscripts Sunrise - Acute EMR Clinicals
24. Anthem - Claims
25. Aon Hewitt - Claims
26. API Healthcare - Time and Attendance
27. Apollo - Lumed X Surgical System
28. Aprima EMR
29. Aspire - Cardiovascular Registry
30. Avaya
31. Axis (MDX)
32. BCBS Illinois
33. BCBS Vermont
34. Bed Ready - Other
35. BOXI - GL
36. Carestream - Other
37. Cerner - Acute EMR Clinicals
38. Cerner - Laboratory
39. Cerner - PowerWorks Ambulatory EMR
40. Cerner HomeWorks - Other
41. Cerner Signature
42. Charlson Deyo and Elixhauser Comorbidity
43. Children's Community Health Plan (CCHP) - Payer
44. CHMB 360+ RCM - Hospital Billing
45. Cigna - Claims
46. CIT Custom - Claims
47. Clinical Improvement Grouper (Care Process Hierarchy)
48. CMS Hierarchical Condition Category
49. CMS Place Of Service
50. CMS Standard Analytical Files
51. Cone Health Employee Plan (United Medicare) - Claims
52. Cost Flex - Costing
53. CPSI - Acute EMR Clinicals
54. CPSI - Hospital Billing
55. Daptiv
56. Digimax Materials Management - Inventory Management
57. Discharge Abstract Data (DAD)
58. Echo Credentialing - Provider Management
59. eClinicalWorks - Ambulatory EMR Clinicals
60. eClinicalWorks - Mountain Kidney Data Extracts
61. Epic - Acute EMR Clinicals
62. Epic - Ambulatory EMR Clinicals
63. Epic - Hospital Billing
64. ePIMS
65. Fazzi - Patient Satisfaction
66. First Click-Wellness
67. FlightLink
68. GE (IDX) Centricity - Ambulatory EMR Clinicals
69. GE (IDX) Centricity - Hospital Billing
70. GE (IDX) Centricity - Practice Management
71. GE (IDX) Centricity - Professional Billing
72. GE (IDX) Centricity Muse - Cardiology
73. Hawaii Medical Service Association (HMSA) - Claims
74. HCUP (NRD, NIS, NED Sample sets)
75. Health Trac
76. HealtheIntent
77. HealthNet - Claims
78. HealthQuest - Patient Accounting
79. Healthscope
80. HealthStream - Patient Satisfaction
81. HST Pathways - Other
82. Humana (PPO) - Claims
83. Humana MA - Claims
84. Hyperion
85. iCIMS
86. ImageTrend
87. ImmTrac
88. InitiateEMPI
89. Innotas
90. IOS ENVI - Costing
91. IVR Outreach Detail
92. Kaufman Hall Budget Advisor - Other
93. Keane - Hospital Billing
94. Kentucky Hospital Association (KHA) - Claims
95. Kronos - HR
96. Kronos - Time and Attendance
97. Lancet Trauma Registry
98. Lawson - Accounts Payable
99. Lawson - Accounts Receivable
100. Lawson - GL
101. Lawson - HR
102. Lawson - Payroll
103. Lawson - Supply Chain
104. Lawson - Time and Attendance
105. Loinc
106. MacLab (CathLab)
107. Maestro
108. McKesson - Accounts Payable
109. McKesson Enterprise Materials Management
110. McKesson Horizon - Acute EMR Clinicals
111. McKesson Horizon Enterprise Visibility
112. McKesson HPM - Costing
113. McKesson HPM - GL
114. McKesson PFM - Accounts Payable
115. McKesson PFM - GL
116. McKesson Series - Accounts Receivable
117. McKesson Series - Patient Billing
118. McKesson STAR - Hospital Billing
119. MD Associates - Professional Billing
120. MD People
121. Medicaid - Claims
122. Medicaid - Claims - CCO
123. Meditech - GL
124. Meditech 5.66 EHR w/DR
125. Merit Cigna - Claims
126. Merit SelectHealth - Claims
127. Microsoft Great Plains - GL
128. MIDAS - Credentialing Module
129. MIDAS - Infection Surveillance
130. MIDAS - Other
131. MIDAS - Risk Management
132. Morrisey Medical Staff Office for Web (MSOW)
133. MSSP (CMS) - Claims
134. National Ambulatory Care Reporting System (NACRS)
135. National Drug Codes (NDC)
136. Navitus - Pharmacy
137. Nextgate EMPI
138. NextGen - Ambulatory Practice Management
139. NextGen (CMS) - Claims
140. NHSN
141. Now Solutions Empath - HR
142. NPI Registry
143. NRC Picker - Patient Satisfaction
144. NSQIPFlatFile
145. OBIX - Perinatal
146. Ohio Hospital Association (OHA) - Claims
147. Onbase
148. OnCore CTMS
149. Oracle (Hyperion) - Costing
150. Oracle (PeopleSoft) - GL
151. Oracle (PeopleSoft) - HR
152. Oracle (PeopleSoft) - Supply Chain
153. Orchard Software Harvest - Pathology
154. PACSHealth - Radiology
155. PARExpress
156. PeopleStrategy/Genesys - HR
157. PeopleStrategy/Genesys - Payroll
158. Pharmacy Benefits Manager
159. PHC Legacy EDW
160. PICIS (OPTUM) Perioperative Suite
161. PPM - Costing
162. PRC - Patient Satisfaction
163. Press Ganey - Patient Satisfaction
164. ProHealth - Claims
165. Provation
166. Provider Taxonomy
167. PWHP Custom - Claims
168. Quadramed Patient Acuity Classification System - Other
169. Quality Systems (Next Gen) - Ambulatory EMR Clinicals
170. QXNT - Claims
171. QXNT/Cactus - Provider
172. QXNT/Vital - Member
173. RLSolutions
174. Rx Norm
175. SafeTrace
176. Siemens RIS - Radiology
177. Siemens Sorian Clinicals - Inpatient EMR
178. Siemens Sorian Financials - Inpatient Registration and Billing
179. SIS Surgical Services
180. Smartstream - GL
181. SMS Legacy - Other
182. StatusScope - Clinical Decisions
183. StrataJazz - Costing
184. Sullivan Luallin - Patient Satisfaction
185. Sunquest - Laboratory
186. Sunrise Clinical Manager
187. Surgical Information System
188. TheraDoc
189. TransChart - Other
190. Truven Quality
191. Ultimate Software Ultipro - HR
192. UMR Claims Source
193. University HealthSystem Consortium - Clinical and Operational
Resource Database
194. University HealthSystem Consortium - Regulatory
195. Value Set Authority Center
196. Varian Aria - Oncology
197. Vermont HIE
198. Vigilanz - Infection Control
199. Wisconsin Health Information Organization (WHIO) - Claims
200. WorkDay
Generally Available
As of May - 2017

27. © 2018
Health
Catalyst
Health Catalyst Patient Safety Monitor™ Suite Features
• Built on the DOS™ platform
• Automated identification of potential safety events
• All-cause harm review of more than 80 triggers
• Bridges gap in inadequate voluntary reporting
• Clinically validated data
• Patient safety organization protection
• Customizable trigger logic
• Customizable review and documentation workflow
• Multi-disciplinary user workflow
• Harm review from system to patient view
• Harm trend and pattern identification
• Timeline view of identified triggers
• Supporting clinical data displayed for rapid clinical review
Adverse event trend displayed in multiple breakdown types to
support multi-level user perspectives, including:
• Adverse events by unit
• Adverse events by category
• Adverse events by severity
• Adverse events by service line
• Adverse events by frequency
• Adverse events by rate
• Estimated costs of harm
• Safety Huddle Dashboard
• Ad hoc export
Risk Surveillance (Future State): Predictive models and user
interface
• Utilizes documented harm from Patient Safety Monitor
• Identifies modifiable risk factors
• Identifies impactability
• Clinical decision support application per patient
27

28. Agenda
Professional Services

29. © 2018
Health
Catalyst
Professional Services
29
Initial
Offerings
Future
Offerings
Application
deployment
Training, adoption,
governance, &
readiness
assessment1
Custom trigger
development
Outcomes
improvement
services, including
client collaboratives1,2
Patient Safety Organization
membership and services
(pending anticipated PSO
listing)
Enhanced Culture of Safety
consulting & governance
Expand existing patient safety
improvement collaboratives
17-step Framework for Outcomes Improvement, Health Catalyst
2https://www.healthcatalyst.com/knowledge-center/success-stories/?fwp_topics=patient-safety-2

30. © 2018
Health
Catalyst
Health Quest focused on identifying ways to improve these
outcomes. Despite instituting several evidence-based
recommendations, the organization had not succeeded in
reducing sepsis mortality to its desired rate. Health Quest
established a multidisciplinary sepsis committee to lead
improvement efforts, including the use of analytics to combat
sepsis mortality rates and improve patient outcomes, resulting in
a:
54 percent relative reduction in sepsis mortality, saving 92 lives in 10
months.
57.1 percent relative reduction in catheter-associated urinary tract
infection (CAUTI) standardized infection ratio (SIR).
30.7 percent relative reduction in C. difficile SIR.
Collaborative, Data-driven Approach Reduces
Sepsis Mortality by 54 Percent
Sepsis can result from an infection
anywhere in the body, such as
respiratory, integumentary, or
urinary tract.
In the U.S., sepsis impacts more
than 1.5 million people annually,
of which about 250,000 will die.
Sepsis accounts for one-third to
one-half of all deaths for
hospitalized patients.

31. Agenda
Key Takeaways

32. © 2018
Health
Catalyst
• Although finance, fear of penalty, and loss of accreditation is often
the motivator for patient safety, never forget the faces that should be
the real motivators.
• There is nothing more peaceful and comfortable than the truth, no
matter what the topic. Find the truth, tell the truth, face the truth.
• Surveilling for harm proactively rather than reactively will enhance
your culture of safety and provide greater protection for all of the
victims of patient harm.
• We welcome the opportunity to be your partner in delivering safe,
quality patient care.
If you take just these things away then . . .
32

33. © 2018
Health
Catalyst
Healthcare Analytics Summit 18
Sept. 11-13, Salt Lake, Grand America Hotel
TOBY COSGROVE, MD
former CEO and President of
Cleveland Clinic (2004-2017),
who as a cardiac surgeon
performed more than 22,000
operations and holds 30 patents
for medical innovations
KIM GOODSELL
the actualized ‘genomified,’ quantified,
digitalized “patient of the future," her debut at
the 2014 Future of Genomic Medicine
conference made headline news
announcing— “The patient from the future,
here today”
DANIEL KRAFT, MD
a Stanford and Harvard trained physician-
scientist, inventor, entrepreneur, and
innovator, Kraft is the Founder and Chair of
Exponential Medicine, a program that
explores convergent, rapidly developing
technologies and their potential in
biomedicine and healthcare
BRENT JAMES, MD
former Chief Quality Officer at
Intermountain Healthcare - known
internationally for his work in
clinical quality improvement,
patient safety, and the
infrastructure that underlies
successful improvement efforts
PENNY WHEELER, MD
President and Chief Executive
Officer of Allina Health,
returns a second time as one
of the most popular HAS
speakers ever
MARC RANDOLF
Co-founder of Netflix, Marc will
share the Netflixed story: how a
scrappy Silicon Valley startup
brought down Blockbuster and
the lessons that could be
applicable to healthcare
JILL HOGGARD GREEN
PhD, RN, Chief Operating Officer – Mission
Health and President – Mission Hospital,
and recently named to the 2017 Becker’s
Healthcare list of the country’s top Women
Hospital and Health System Leaders to
Know
ROBERT WACHTER, MD
global leader in healthcare safety,
quality, policy, IT; Chair of the
Department of Medicine, University of
California, San Francisco; best-selling
author, “The Digital Doctor: Hope, Hype
and Harm at the Dawn of Medicine’s
Computer Age”
More highlights
4 Digital Innovators (Keynotes)
AI Showcase (10 walkabout case studies)
Digitizing the Patient Showcase (10-12 stations)
28 Educational, Case Study, and Technical Breakouts
24 Analytics Walkabout Projects
More Networking (Introducing “Brain Date”)
CME Accreditation For Clinicians
5-Star Grand America Hotel Experience
96 Total Presentations
National keynotes
Employer
Innovation
Scott
Schreeve
MD, CEO, Crossover Health
Payer
Innovation
Kevin
Sears
Executive Director of Marketing
and Network Services, Cleveland
Clinic
Biosensor
Innovation
John
Rogers
PhD, Founding Director, Center
Bio-Integrated Electronics,
Northwestern University
Pricing
Innovation
Gene
Thompson
Project Director, Health City
Cayman Islands

34. Q&A

35. © 2018
Health
Catalyst
Around the globe, we are facing a trifecta of healthcare challenges: financial constraints, an aging population, and an
increased burden of chronic disease. We need to turn healthcare upside down, empowering our patients to take action
for their health and helping physicians, nurses, and healthcare professionals move from being sages to guides.
Thursday, July 26
1:00-2:00 PM EST
Join to learn:
• How increased patient engagement can help to improve healthcare outcomes while reducing costs
• Ways that technology can effectively improve data capture, patient accountability, and decision-making
• The impactful stories of four patients who became innovators in their own care
The Patient’s Power in Improving Health and Care
35
MAUREEN BISOGNANO
President Emerita and Senior Fellow, Institute for Healthcare Improvement
Maureen was the former IHI President and CEO for five years, after serving as
Executive Vice President and COO for 15 years. She is a prominent authority
on improving health care systems, whose expertise has been recognized by
her elected membership to the National Academy of Medicine, among other
distinctions.

36. Thank You!