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Data in Business Analytics Perspective for Indian Healthcare Market
1. Data in Business Analytics
Perspective for Indian Healthcare
Market
Debashis Basu
Partner and Leader Enterprise Intelligence and Analytics
EY India
September 7, 2013
2. Page 2
Challenges with Data Analytics in Healthcare
► Data available in healthcare can be segregated along the following
lines
► Structured Data : EMR systems, Claims systems, Revenue cycle
systems
► Unstructured Data : Doctor notes, Images
► Focus has been on the "volume" end of analytics, namely Data
Management and Governance
► Descriptive analytics, while Advanced Analytics and Predictive
Modelling usage is limited
► Most Hospitals are understaffed for the most basic reporting and
analytical needs
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
3. Page 3
Emerging markets/India Specific Challenges
► Lack of country wide hospital KPI data
► No adequate survey-based data
► No administrative reporting system that provide basic
hospital service statistics
► Healthcare organizations are wary of technology
integration due to cost burden caused by requirement of
IT infrastructure and technical expertise
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
4. Page 4
Silver lining for Data Analytics for Indian
Healthcare providers
► According to Gartner, India's healthcare providers plan to
spend US$ 1.05 billion on IT products and services in
2013
► As the health care industry moves to electronic health
records, the storage of data is increasingly going to be on
the cloud.
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
5. Page 5
The healthcare business intelligence /
EPM landscape
► Healthcare decision support is usually workflow-specific
► Provided within functional systems of enterprise HCIT
vendors
► And is not cross-application or cross-enterprise
► Enterprise-level BI solutions in healthcare are scarce
► Enterprise software vendors (McKesson, Siemens, Cerner,
GE, Eclipsys, Epic)
• Offer data warehouses and OLAP tools specific to their applications
• But are not an effective enterprise solution, particularly for revenue cycle
► Technology vendors (BEA, Cognos, Business Objects,
Hyperion, Qulikview Microsoft)
• Offer tools to create BI/EPM solutions but must be custom-developed
• Are costly to implement and maintain – most hospitals & physicians can’t
afford them
Functional
Systems
Data
Warehouse
Business
Intelligence
Performance
Management
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
6. Page 6
The healthcare business intelligence /
EPM landscape
► Pure healthcare BI companies (limited number - Avega,
Precision.BI, MedeAnalytics, Craneware, Advisory Board,
Premier, Thompson Reuters, Healthcare Management
Council, CareMedic)
• Provide subscription-based solutions
• But technology is not leading edge
• They are usually retrospective reporting and benchmarking services
• Rather than EPM
► The industry still lacks an affordable healthcare-specific
EPM solution that can be easily implemented
Functional
Systems
Data
Warehouse
Business
Intelligence
Performance
Management
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
7. Page 7
Key Problems – Inefficiency & lack of
visibility
Assignment &
Transfer Delays
Limited Capacity Intelligence
Unmonitored bed turnaround
Delayed visibility of empty beds
Unseen capacity
Delayed Discharges
Transport delays
Equipment/pharmacy req
Test results
―My housekeeping staff finds out
about discharged patients by checking
a handwritten log.‖
―My surgeries are being
canceled for want of an
inpatient bed‖
――We are having difficulty in tracking
quality of care. Our CMS scores are
low and we are not getting full
reimbursements‖
―Patients are being sent to other
hospitals—we can’t find room‖
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
8. Page 8
Integrating Information Across Silos in Real
time
Clinical &
Quality
Operational
& Financial
IT & Security
Health Metrics
HIS ADT Radiology
(PACS)
Order Entry Bed
Management
Pharmacy
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
9. Page 9
Hospital EPM Solutions Landscape
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
10. Page 10
Benefits - Increased Admissions & ROI Gain
for Hospitals
► Executive Objectives
► CXO’s are looking for ways to increase patient throughput
► Increasing throughput is increasing the number of admits at
a hospital
► Through making processes in the hospital more efficient
► Roadmap to improved bed utilization
► By optimizing latency between discharge & occupancy
► By creating visibility at the time of admissions
► By improving the discharge process
► Estimated Increased Admissions & Revenue
► An average 400 bed hospital can expect the following
benefits
Performance Level Conservative Moderate Aggressive
Bed Turns Gained per Year 3.12 5.32 10
Admissions Gained 905 1542 2899
Revenue Opportunity $4,070,658 $6,940,993 $13,046,980
Saving Just 2 Hours
between discharge to
admission can lead to an
extra capacity of 6
bed days (increase of 1
bed turn)
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
11. Page 11
Illustrative out come
► Bed Turnaround Time
► 20% reduction in Bed Assignment Time (request to assignment)
► 15-30% reduction in Bed Occupancy Time (request to
occupied)
► 30-40% reduction in Bed Occupancy Time for evening and night
► Bed Occupancy & Capacity Improvement
► 8-10% improvement in bed occupancy (inpatient conversions)
► 10-13% improvement in ED Admissions (improved bed
utilization)
► 8-10% improvement in ED utilization (better resource
management)
► Nursing & Clinical
► 25-40% reduction in outpatient conversions
► 30% reduction in outpatient conversions for interventional
radiology
► 20% reduction in overall outpatient conversions
► 3% improvement in early discharges (before 2:00 PM as) % of
total
ACTUAL
PERFORMANCE
25% Improvement in Bed
Requested vs. Bed
Assigned
ACTUAL
PERFORMANCE
10% Improvement in
Inpatient Conversions
4th International Conference on Transforming Healthcare with IT - 6th – 7th Sep. 2013
Hyderabad, India
Structured data (external): Public data (CMS), benchmark data, syndicated data Unstructured data (external): social media
types of out-patient visits and in-patient admission, bed utilization rates, bed days, occupancy rates, and average length of stay, etc.The availability of quality data on morbidity patterns and patient safety is also grossly inadequate. In all, this scenario, limits the ability to design innovative health insurance products and effective patient safety programs in the hospitals
types of out-patient visits and in-patient admission, bed utilization rates, bed days, occupancy rates, and average length of stay, etc.The availability of quality data on morbidity patterns and patient safety is also grossly inadequate. In all, this scenario, limits the ability to design innovative health insurance products and effective patient safety programs in the hospitals