This document summarizes the background and work of Prof. Steven H. Shaha, who has published over 100 peer-reviewed publications and presentations on using analytics and clinical decision support systems to improve healthcare quality and outcomes. Some key points discussed include using analytics of electronic medical record data to reduce sepsis rates and length of ICU stays, developing alert systems to more quickly recognize and treat at-risk patients, and creating connected networks between healthcare providers to better monitor population health and improve outcomes for conditions like diabetes.

1. Analytics Leads to ImprovedQuality and Performance: Population Health & Measuring and Improving the Impacts of HIT on Clinical, Cost and Efficiency Outcomes
Prof Steven H. Shaha, PhD, DBA
November 2014

2. Prof. Steven H. Shaha, PhD, DBAProfessor, Center for Public Policy & AdministrationPrincipal Outcomes Consultant, AllscriptsFormer Director of Research, KLAS
100+ peer-reviewed publications, 200+ peer-reviewed presentations, 2 books
Advisory and consulting work for 11 governments on four continents
Professor or Lectured or at 14 universities and graduate schools
e.g. UCLA, Harvard, Cambridge (UK), King’s College, London University, South Manchester, Yale, Princeton, Columbia, Cornell, Zayed Univ(UAE)
Advisory and consulting to 50+ non-healthcare organisations, including
Disney, Ritz-Carlton, Coca-Cola, New Line Cinema, IBM, AT&T,
Time Warner, Johnson & Johnson, Marriott, 3 Depts. of Defense,
and Pharma: Sanofi, Aventis, Novartis
Education:
PhD, Research Methods & Applied Statistics
DBA, Business Administration (PhD)
MA, MEd, BS
Disclosures & Bio

4. Sample of Peer-reviewed Journals
•Advance for Health Information Executives
•Advances in Patient Safety
•Agency for Healthcare Res & Qual(AHRQJournal)
•American Journal of Ob & Gynecology
•American Journal of Sports Medicine
•Applied Clinical Informatics
•Archives of Otolaryngology, Head & Neck Surg
•Breast Cancer Research and Treatment
•British Medical Journal of Quality & Safety
•Epidemiology and Infection
•Health Management Technology
•Healthcare Financial Management
•Healthcare Technology Management
•Intl. Journal of Medical Informatics
•Intl. Journal of Pediatric Otorhinolaryngology
•Intl. Journal for Quality in Health Care
•Journal of Arthroscopic and Related Surgery
•Journal of Clinical Ultrasound
•Journal of Emergency Nursing
•Journal of Mat, Fetal & Neonatology Med
•Journal of Neurosurgery
•Journal of Obstetrics and Gynecology
•Journal of Orthopedic Trauma
•Journal of Pediatric Emergency Care
•Journal of Perinatal Medicine
•Journal of Perinatology
•Journal of Shoulder and Elbow Surgery
•Journal of the Am Acadof PedOphth& Strab
•Journal of Ultrasound in Medicine
•Journal of Ultrasound in Ob & Gynecology
•Laryngoscope
•Nurse Executive Watch
•Nurse Leader
•Nursing Economics
•Pediatric Critical Care Medicine
•Pediatric Emergency Care
•Pediatrics
•RN Magazine
•Spine
•Intl. Journal of Pediatric Otorhinolaryngology
•The Journal of Bone & Joint Surgery
•Ultrasound in Obstetrics & Gynecology

5. The Dynamics in HealthcarePressure on every aspect of performance
“Variable demand with fixed capacity & poor patient flow.”
“Safety, quality and
value-based delivery.”
“Do more with less.”

6. 3.90
4.00
4.10
4.20
4.30
4.40
4.50
0.0% 20.0% 40.0% 60.0% 80.0% 100.0%
Average LOS - mvg avg
Percent CPOE Adoption
SQL with Analytics: Study, Test, Monitor

7. Delicate Balance …
The Golden Rule

8. Heads up display

9. Levels of Information: Needs and Perspectives
Routine change –Enabling Success
Evolving figures –Process Improvement focus
Operational perspective –Managing Success
MISSION …
Fluid change / Real-time figures
Real results –NOW or catastrophic
Care and Continuum perspective
MISSION …
Slow change –Empowering Success
Stable figures –Attention to Needs
Strategic perspective –Org Excellence
MISSION …

10. Levels of Information: Needs and Perspectives
When we build with “pilots” in mind …

11. Notify
Improved
Outcomes
Individually and collectively
For Clinicians
For Responders
To Systems
From Devices
From Systems
For Clinicians
For Responders
To Systems
The Evolution of Health Care Information
Retrospective
Automated
Reporting
Concurrent
Synchronous
Care
Prospective
Predictive
Care
Retrospective
Manual
Reporting
Real-Time Outcomes OptimizationBest care and best quality scores optimized while the patient is still in the bed
The Power to Change Outcomes
The best in advanced Clinical Decision Support
Continuous Clinical Decision Support Engine
Clinical Intelligence and Automated Assessments Extracted from multi-disciplinary documentation
“Our” Recommended Treatments
e.g. Order sets, pathways, algorithms, evidence-based medicine, inter- disciplinary documentation templates
Providing the best care andachieving
optimal quality and performance
From Clinicians
To Patients

12. “Clinical Decision Support” –Many Meanings
Where HIT Lives
Beginning CDS
Advanced CDS:
Intelligent

13. Statistics:
•The leading cause of death in hospitals globally –1.7 Million cases a year
•Prolonged LOS in ICU w/ CCs, complex therapies, high costs –est.£18BnannuallySolution –Understand and Conquer:
•SQL query 12-month retrospective chart review
•MEWS: Perpetual, house-wide, imbedded monitoring and surveillance
13
3
2
1
0
1
2
3
SystolicBP (mmHg)
< 70
71-80
81-100
101-199
>= 200
Heart rate (bpm)
< 40
41-50
51-100
101-110
110-129
>= 130
Respiratory rate (bpm)
< 9
9-14
15-20
21-29
>= 30
Temperature (°C)
< 35
35-38.4
>= 38.5
Age (y)
65-74
75-84
>= 85
BMI (kg/m²)
< 18.5
25.1- 34.9
> 35
Sepsis: An example of infections and “avoidables”
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.

14. Document
•Vitals
•Device integration
•Key CCs
Query
•Key Indicators (Age, BMI)
Calculate
•Score via Matrix
Alert
•Does score exceed threshold? Send Alert
The Process: Identification and Remediation
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.

15. Our first alert, May 6, 15:38
Abx LevaQuinOrdered, May 7, 10:33
Disaster Averted
Vigilance only
Abx VancOrdered, May 8, 8:10
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.

16. Summary Impacts:
Measure
Pre
Post
Timeliness of Recognition1
571.2minutes
93.7minutes
Cardiopulmonary Arrest Rate Outside ICU2
5.54%
3.86%
ICU Length of Stay3
3.8days
3.3 days
Down to 51.8 min (9-11-13)
Down to 28.2 min (11-Dec-13)
p<0.001
p<0.001
p<0.01
The Process: Identification and Remediation
Document
•Vitals
•Device integration
•Key CCs
Query
•Key Indicators (Age, BMI)
Calculate
•Score via Matrix
Alert
•Does score exceed threshold? Send Alert
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.
1.T Test procedure, statistically significant (p <.0001)
2.Chi square procedure, statistically significant (p 0.046)
3.Not statistically significant (t=1.74/p=.08) buclinically significant?

17. Quarterly Surveillance and Refinement
17
Daily Rounding at the Bedside
Quarterly Summary and Refining
Sepsis Outside of the ICU
0
5
10
15
20
25
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
August
September
October
November
December
January
February
March
April
May
June
July
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2011
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2013
2013
2013
2013
2013
2013
2013
40.2% reduction(p<.01)
37.5% addl. reduction (p<.01)
62.5% cumulative (p<.001)
36 Month Avg.
£ 8.9 Million est. Cash Release
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.

18. Community Analytics: Patient-specific Normalisation
LOW Acuity Patient
HIGH Acuity Patient
Shaha SH( 2014) The EMR as an Effective Tool for Boosting Medication Adherence. Invited Presentation: 2ndAnnual World Congress Summit to Improve Adherence and Patient Engagement, March 10-11, 2014, Philadelphia.
Shaha SH, Hutchinson M (2014). EPR Impacts: The Real ROI. HC 2014: The National Health IT Conf& Exh, Manchester, England, March 20, 2014.
Shaha SH, et.al. (2014). CPOE’sPredictive Impact on LOS: Three Case Studies Illustrate the Impact of High Capability EMRs. HIC 2014 Health Informatics Society of Australia, Melbourne.
OPEN solution
vs.
Restrictive connectivity?

19. Copyright © 2014 Allscripts Healthcare Solutions, Inc.
Regional
Hospital 9
Regional
Hospital 8
Regional
Hospital 7
Regional
Health
System 6
Regional
Clinic 2:
Senior Care
Regional
Clinic 1:
Pediatric Alliance
Regional
Hospital 4
Regional
Health
System 5
Regional
Hospital 2
Regional Hosp&
Health System 1
Regional
Hospital 3:
Children’s
Single
Data Home
and
Source of Truth
State Immunisations:
Lab System Interface
National Health Information Network
(NHIN)
State Govt. Info Network

20. | Copyright © 2010 Allscripts Healthcare Solutions, Inc.
A Connected Community of Health
Population Care Improvements
20
276.5% Improved (p<.0001)
3.77 Times Better
377.4% Improved (p<.0001)
4.8 Times Better
57.4% Improved (p<.0001)
1.6 Times Better
75.1% Improved (p<.0001)
1.8 Times Better

21. | Copyright © 2010 Allscripts Healthcare Solutions, Inc.
A Connected Community of Health
Diabetes Improvements
21
76.0% Improved (p<.0001)
1.8 Times Better
437.7% Improved (p<.0001)
5.4 Times Better
2,277.3% Improved (p<.0001)
23.8 Times Better

22. Without
With CDS-rich
Order Set
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Impact of Stroke Admission Order Set:
Comparative Quality with versus without
Improved Stroke Outcomes
Impact of Stroke Outcomes Toolkit:
Comparative Quality with versus without
CDS-rich Order Set
40.5% net
Greater Clinical
Excellence
80%+ Change
Stroke Care Best Practices
CPOE with Alerts Alone

23. Length of Stay
Discharge Patterns
CDS-rich Order Set Without Order Set
Discharge to Home Discharge to SNF Discharge to IP Rehab
Cost-per-Case Impact
CDS-rich Order Set Without Order Set
Average Direct Cost/Case Average Indirect Cost/Case
16.0% fewer
(p<.001)
11.4% lower Cost-per-Case
$ 628 avg (p<.05)
Readmissions in 31 Days
35.7 % fewer
(p<.001)
Improved Stroke Outcomes
9.4% more
(p<.001)
21.4% fewer
(p<.001)
12.7% lower Cost-per-Case
$249 avg (p<.05)
7.5% lower
0.35 fewer days avg. (p<.001)
CPOE with Alerts Alone
Est. Savings of $265k-$560k annualized
CDS-rich Order Set

24. Care Coord Network Pre
Readmissions in 31 Days Length of Stay
Significantly fewer (p<.001)
Better Outcomes after Discharge
Admissions to Nursing Homes and
Residential Age Care Facilities
Care Coord Network Pre
Significantly shorter (p<.001)
Additional Efficiencies
• Capacity for 130 additional admissions
with NO staffing increases
CPOE and Alerts alone
CDS-rich Order Set

25. Readmissions in 31 Days
Better Outcomes after Discharge
Discharges to Home
Significantly fewer (p<.001)
And …
•Fewer ED/A&Evisits (p<.01)
•Fewer clinic visits (p<.01)
•Fewer PCP interactions (p<.01)
CPOEand Alerts alone
CDS-rich Order Set

26. 26

27. Generalizable to All EPRs?
Not guaranteed!

28. SATISFACTION: IT VS. CLINICIANS
Average EMR Satisfaction
Average EMR Satisfaction
Shaha SH (2013). Comparative EPR Usability form the Clinician Perspective: What works and what doesn’t for impacting care. Digital Health Service Delivery – The Future Is Now. HIC 2013 Proceedings, Health
Information Society of Australia, Melbourne, pg. 122.
Shaha SH (2013). Benefits and Outcomes: Models for Getting the Most Out of Your EPR. EPR Awareness Forum: Sharing Best Practice from UK, Europe and the US, Manchester, UK, May 2013.
Shaha SH (2013). Clinical Systems Applications and Related technology: Today and into the Future. HC 2013: The National Health IT Conf & Exh, Birmingham, England, April 2013.
The Golden Rule

29. Remember WHY … Prove Outcomes
•Clinical
•Improved
•Avoided Worsening
•Cost-related
•Efficiency-focused
•Satisfaction for Key Stakeholders
29

30. Prioritisation
•High Frequency
•High Cost
•High Risk
•Problem-prone
•Strategically Important
30

31. Lessons Learnt: •The EMR is not “electronified paper”
• Computers that Compute
• Programmability
• Clinical Intelligence
•Adaptability and Interoperability
• Rigidity vs. Openness
•Local Innovation then Broader
Standardization
• “What work here with our needs and capabilities”
• Try, refine, prove … then standardize … then innovate
•Access to Clinical Data
•Community Connectivity
•Outcomes-driven
• Clinical
• Efficiency
• Cash Releasing and Cost Reducing
• Clinician Satisfaction