The Democratisation of Information

The Democratisation of
Information
Dr. Gareth Goodier
Chief Executive
Melbourne Health
21 October 2015

• Serving more than 1 million
Victorians
• Victoria’s first public
hospital
• Provides local and tertiary/
quaternary academic health
services
• Largest mental health
service in Melbourne
• Services over 1.2 million
Melburnians
• Opened in 2013
• Joint venture with the
University of Melbourne
• World-class institute in
infection and immunity
Royal Park
Campus
City Campus

“The goal is to turn data into information, and information
into insight.” – Carly Fiorina
(Former CEO and Chair Hewlett, Packard)
Analytics
Tools
External:
Information
for strategic
development and
external
advocacy
Internal:
Insights to
inform operational and
clinical
decisions
• Embed analytics within
decision making processes
• Drive behavioural change
• Improved outcomes for
patients
• Improved resource
utilisation
• Faster response to
challenges and opportunities
• Track Strategic Plan and
Business Plan
• Benchmark with peer
organisations
• Improved strength in
negotiation with funding
bodies
Data
Data
DATA
DATA
data
Data
Data

Information is power
How do clinicians want information?
 Electronic
 Accessible
 Intuitive
 Graphical
 Real-time
 Reliable
 Comprehensive
“The most valuable
commodity I know of is
information”
– Gordon Gecko (Wall Street)

The Business Intelligence Maturity Model
Several sources
of truth
Centralised
information
Advanced
Analytics
Information:
• We have consistent
and accessible
information across
RMH
• Ongoing work with
Consultant
Attribution data
accuracy
Insight:
• We are developing
and acting on
insights including:
− Emergency
− Length of Stay
− Patient Incidents
− DNA rates
We
are
here

Our journey to date
2015
Engaged a new vendor in
Draper & Dash
2012/13
Commencement of our
Qlikview journey
2012
In-house reporting system
and excel spreadsheets
Admission Care TypeAdmission MethodAdmission Account GroupAdmission DateAdmission TimeDischarge MethodExpected DischargeMedical DischargeDischarge DateDischarge TimeDRG Same DayGender Age BandWIES WIES Estimation
##### 18,012.36
Acute Planned AdmissionPublic 14-01-2015 13:49 Home/Private residence/accommodation17/01/2015 : - 15-01-2015 14:13 Q61B-RED BLOOD CELL DISDERS -CSCCOvernightMale 90-94 0.38 0.63
Acute Admission from ED (VEMD only)Private 27-12-2014 20:39 Transfer to other hospital- - 07-01-2015 14:36 B70B-STROKE & OTH CEREB DIS +SCCOvernightFemale 90-94 1.36 4.29
Designated Rehabilitation UnitPlanned AdmissionPublic 20-03-2015 15:55 Home/Private residence/accommodation- - 31-03-2015 08:42 Z60Z-REHABILITATIONOvernightFemale 85-89 0.00 0.00
Acute Admission from ED (VEMD only)Private 03-01-2015 18:26 Home/Private residence/accommodation- - 08-01-2015 15:52 E62A-RESPIRATRY INFECTN/INFLAMM+CCCOvernightMale 80-84 1.64 1.71
Acute Admission from ED (VEMD only)Public 31-01-2015 18:59 Home/Private residence/accommodation- - 01-02-2015 08:30 F66B-CORONARY ATHEROSCLEROSIS -CSCCOvernightMale 85-89 0.46 0.52
Acute Admission from ED (VEMD only)Public 25-02-2015 15:11 Transfer to other hospital- - 27-02-2015 12:52 L67B-OTH KIDNY & URNRY TRCT DX-CSCCOvernightMale 90-94 0.62 0.62
Acute Admission from ED (VEMD only)Public 18-02-2015 23:36 Statistical Separation- - 27-02-2015 16:01 F12B-IMPLANT/REPLCE PM,TOT SYS -CCCOvernightFemale 85-89 2.88 2.21
Geriatric Evaluation & ManagementStatistical AdmissionPublic 27-02-2015 16:02 Home/Private residence/accommodation- - 17-03-2015 10:26 F76B-ARRHY, CARD & COND DISDR -CSCCOvernightFemale 85-89 0.00 0.00
Acute Admission from ED (VEMD only)Public 12-02-2015 20:01 Home/Private residence/accommodation16/02/2015 : 15/02/2015 : 15-02-2015 12:29 L63A-KDNY & UNRY TRCT INF +CSCCOvernightMale 75-79 1.22 0.74
Acute Admission from ED (VEMD only)Public 09-02-2015 13:50 Home/Private residence/accommodation- - 10-02-2015 16:50 E74C-INTERSTITIAL LUNG DIS -CCOvernightMale 90-94 0.77 0.54
Acute Planned AdmissionPublic 19-02-2015 06:27 Home/Private residence/accommodation- 19/02/2015 : 19-02-2015 14:00 B05Z-CARPAL TUNNEL RELEASESame DayFemale 70-74 0.39 0.46
Acute Admission from ED (VEMD only)Public 01-01-2015 18:36 Home/Private residence/accommodation- - 06-01-2015 15:36 E65B-CHRNIC OBSTRCT AIRWAY DIS -CCCOvernightFemale 70-74 1.07 0.83
Acute Admission from ED (VEMD only)Public 08-02-2015 20:20 Home/Private residence/accommodation- - 12-02-2015 15:16 L63A-KDNY & UNRY TRCT INF +CSCCOvernightFemale 75-79 1.22 0.95
Acute Admission from ED (VEMD only)Public 28-02-2015 17:58 Home/Private residence/accommodation01/03/2015 : - 01-03-2015 13:40 T63B-VIRAL ILLNESS -CCOvernightFemale 75-79 0.55 0.54
Acute Planned AdmissionPublic 19-01-2015 13:41 Home/Private residence/accommodation- - 21-01-2015 09:13 F65B-PERIPHERAL VASCULAR DSRD -CSCCOvernightMale 75-79 0.77 1.23
Acute Planned AdmissionPublic 25-02-2015 07:00 Home/Private residence/accommodation- - 27-02-2015 11:46 E42B-BRONCHOSCOPY -CCCOvernightMale 80-84 1.68 1.21
Acute Admission from ED (VEMD only)Public 15-01-2015 20:25 Aged care residential facility19/01/2015 : - 16-01-2015 15:24 F76A-ARRHY, CARD & COND DISDR +CSCCOvernightFemale 90-94 1.26 0.54
Acute Planned AdmissionPublic 03-01-2015 06:00 Home/Private residence/accommodation- - 03-01-2015 11:00 L61Z-HAEMODIALYSISSame DayMale 70-74 0.11 0.11
Acute Planned AdmissionPublic 28-01-2015 06:00 Aged care residential facility- - 28-01-2015 11:00 L61Z-HAEMODIALYSISSame DayMale 70-74 0.11 0.11
Acute Planned AdmissionPublic 30-01-2015 06:00 Aged care residential facility- - 30-01-2015 11:00 L61Z-HAEMODIALYSISSame DayMale 70-74 0.11 0.11
• Multiple data sources
• Multiple sources of truth
• Static inflexible reporting
• Delayed period reporting
• Analytics was the domain of
a few with the time and skill
• Engaged the BI Unit of a
generalist management
consulting firm
• Improved data flexibility but
very clunky, not intuitive and
time consuming
• Poor user adoption - users
continued with former
familiar system
• Specialist in Healthcare BI
and Qlikview
• Includes several pre-built
and proven applications
• Best practice principles in
dashboard design
• Single source of truth
• Live data in meetings
• Increasing end user adoption

The Democratisation of Information
“It is not just about
providing better
information. It is the
democratisation of
information, leading to
culture and behaviour
change”

A new approach to reporting
“You can have data
without information, but
you cannot have
information without
data”
- Daniel Keys Moran
“Few people will
appreciate the music if
I just show them the
notes. Most of us need
to hear it”
- Hans Rosling

Performance at a glance
Emergency Department Visibility
Emergency Department

Targeted audience requirements
Outpatients

Improved design principles
Reflecting the operating theatre workflow
Theatres

Drill-down functionality
Mortality over time & primary diagnosis
Mortality and Outcomes

Focussed on key challenges
Understanding readmissions
Readmissions

Driving user adoption
• Measuring and
monitoring usage since
re-launch in April 2015
• Uptake continues to be
supported by:
− Launch and
promotional
activities
− Education
− Scorecard reporting
− Cultural change

The data is
wrong
DENIAL
It does not
apply to me
ANGER
I will get the
correct data
But we are
special
BARGAINING
There is
nothing I can
do about it
DEPRESSION
Acceptance
and action
RESOLUTION
Adapted from Elisabeth Kübler-Ross 5 stage model
The 5 stages of data grief

Relentless focus on variation
• “In the last 30 years, research has demonstrated that:
1) quality can be measured,
2) that quality varies enormously,
3) that where you go for care affects its quality far more than who you are, and
4) that improving quality of care, while possible, is difficult and painful”.
– Brook, McGlynn & Shekelle (2000)
• Evidence suggests that there is, at best, a TWO to THREE fold variance in clinical
behaviour/treatment practice across medicine
• Where there is poor clinical evidence (e.g. ADHD) the variation can increase to more
than a TWENTY fold difference
“If all variation were bad, solutions would be easy. The difficulty is in reducing the bad
variation, which reflects the limits of professional knowledge and failures in its
application, while preserving the good variation that makes care patient centered”
- AJ Mulley (BMJ, 2010)

“The most expensive
item in the hospital is
the Doctor’s pen”
Variation – at what cost?

International variation
Foreign
body left in
during
procedure in
adults, 2011
Average length of stay for acute myocardial
infarction (AMI), 2011
Different
rates of
mortality
from
cancer in
people
<75yrs
Source: OECD Health
Statistics 2013

Case Examples
“However beautiful the strategy, one
should occasionally look at the results”
- Winston Churchill

Case Example 1: Improving patient safety - Falls
Identifying contributing factors
11am
3pm
9pm
Understanding
falls incidents by:
• Ward
• Outcome
• Time
• Patient level
details
• Age
• Location
• Time
• Activity

Case Example 1: Improving patient safety - Falls
Implementing and monitoring change
Strategies, such
as focussed
rounding at key
times, have
facilitated a
significant
reduction in falls
RMH is now applying the same methodology to
target pressure injuries

Case example 2 – Understanding mortality
Granular Drill-down Functionality

Drill down to Specialty and Consultant
Consultant outlier
Majority of
cases of
mortality
were
Palliative
Care

Audit of 60 cases of mortality from aspiration pneumonia
More than half (32/60) were admitted from 23 different nursing homes with
aspiration pneumonia
Speech Pathologist and Physician worked with nursing homes to improve
management of patients with dysphagia:
– dysphagia management guidelines
– e-learning package
– expert advice
– advance care planning for patients with chronic dysphagia
Using data for improvement

• RMH has had significant success with short stay surgical models of care that both reduce
length of stay and reduce complications
• Our emergency general surgery model has delivered reduced LOS, reduced complications,
a reduction in conversion to surgery and a statistically significant reduction in mortality
(Shakerian et al, WJS, 2015; Shakerian et al, BJS accepted for publication August 2015)
• Are there opportunities to make similar improvement to LOS and outcomes in the elective
patient cohort?
Benchmarking
surgical LOS
with British
Association of
Day Surgery
(BADS)
Case Example 3: Improving resource utilisation
In-depth analysis and benchmarking

BADS
BADS Target
%Day Case
RMH
DC %
Cases
Below BADS
Target
Net
Financ ial
Outc ome
Modelling
Breast Surgery
Exc ision/biopsy of breast tissue Â± loc alisation 95% 53.10% 24 58,894$
Simple Mastec tomy (inc axillary node biopsy) 15% 0.00% 5 23,395-$
Breast Surgery Total 29 35,499$
Cardiology
Elec tiv e c ardiov ersion 95% 66.30% 25 89,391$
Implantation of c ardiac pac emaker 50% 0.00% 105 153,873$
Cardiology Total 130 243,264$
ENT/ Head and Neck
FESS Endosc opic unc inec tomy, anterior and posterior 50% 6.70% 5 8,933$
Intranasal antrostomy inc luding endosc opic 80% 0.00% 2 3,573$
Biopsy / Sampling of c erv ic al lymph nodes 40% 0.00% 1 5,229$
Enuc leation of c yst of jaw 95% 80.00% 1 2,141$
Exc ision of submandibular gland 30% 0.00% 1 7,103$
ENT/ Head and Neck Total 10 26,979$
General Surgery
Exc ision biopsy of lymph node for diagnosis (c erv ic al, 40% 0.00% 2 8,299$
Inc ision and drainage of perianal absc ess 90% 34.10% 9 3,318$
Laparosc opic repair of hiatus hernia with anti-reflux 40% 0.00% 1 2,101$
Pilonidal sinus surgery - laying open or suture/skin graft 45% 38.50% 20 5,514$
Primary repair of femoral hernia 90% 0.00% 1 1,611$
Primary repair of inguinal hernia 95% 29.40% 12 15,677$
Repair of other abdominal hernia 85% 0.00% 1 1,611$
General Surgery Total 46 38,131$
Ophthalmology
Dac ryoc ystorhinostomy inc insertion of tube 90% 40.00% 3 5,332$
Surgic al trabec ulec tomy or other penetraating 95% 0.00% 1 1,290$
Ophthalmology Total 4 6,622$
Oral
Surgic al remov al of impac ted / buried tooth / teeth 95% 9.00% 11 19,935$
T&O
Arthrosc opy of knee inc luding menisec tomy, menisc al 95% 0.00% 1 425$
Neurolysis and transposition of peripheral nerv e e.g 95% 0.00% 3 3,509-$
Repair of hand or wrist tendon 90% 29.10% 34 66,463$
T&O Total 38 63,380$
RMH TOTAL 268 433,810$
Royal Melbourne Hospital
Indicators
• Comparing RMH short
stay surgery episodes
with BADS benchmarks
• Identified cohorts with
longer LOS
• Financial outcome
modelling identified a
savings opportunity of
$433K if RMH aligned
areas of longer LOS with
with BADS targets
• Work progressing in
Cardiology and General
Surgery to review current
models and the
applicability of BADS
models of care for local
implementation at RMH

Lessons learned
Culture
 ‘Democratisation of Information’ leading to culture and behaviour
change
 Actively promote data transparency
 Staff engagement is important
““Opportunities multiply as they are
seized” - Sun Tzu

Lessons learned
Operational
 A Business Intelligence program requires both technical and clinical expertise
to develop and deliver
 Invest in Business Intelligence tool that is graphical and intuitive
 Take pragmatic approach to data accuracy – it tends to improve with
transparency and exposure
 Promote and measure end user adoption
 A change management approach is essential – the embedding of analytics
into organisational decision making is both a technical and a cultural journey
 Consultant attribution
 Patient level costing by sub-category (i.e. pharmacy and theatre mins)
 External benchmarking
““Opportunities multiply as they are
seized” - Sun Tzu

What can a data driven hospital achieve?
 High Quality
• RMH has a low standardised mortality rate (HSMR 80;
August 2015)
 Reduced Length of Stay
• RMH has an 86% Relative Stay Index compared with all
major Australian hospitals.
 Reduced cost
• RMH is $600 lower cost per funding unit (WIES) than
the closest peer hospital;
• The National Health Performance Authority (NHPA)
reported the RMH is the “LOWEST” cost tertiary
hospital in Australia.
“The price of light is less than the cost of darkness” - Arthur C. Nielsen

Our next steps…
 Mobile applications
• “Mobile is the future of everything” – Forbes
• Mobile applications for Senior Doctors early 2016
 Granular level benchmarking
• Combine benchmarking data with drill down
functionality
 Key in depth analytics projects
• Linking clinical costings with patient outcomes in
Orthopaedics
• Understanding and monitoring readmissions

“Hiding within those mounds of data is
knowledge that could change the life of a
patient, or change the world”
- Atul Butte

The Democratisation of Information

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