NICON Technology Enabling Change; Health Analytics Paul Pierotti Managing Director.

NICON Technology Enabling Change;Health Analytics

Paul PierottiManaging Director

Copyright © 2014 Accenture All rights reserved. 2

Health Outcomes: Complex relationship with spend, payer structure and provider structure


Health Analytics: Providing insights to deliver a more effective and efficient Health System

Care Management

Provider Cost Containment

Fraud & Non-Compliance Reduction

Clinical Delivery Transformation

PopulationHealth Planning

Understand your future health demand, define the health system to meet and deliver the associated reform and capacity requirements

Stratify patients based on their risk of acute episodes and / or chronic conditions and intervene to reduce future demand by 20%

Address significant variations in hospital and primary care supplier performance to reduce costs by up to 10%

Better tackle the 3% to 15% of health spend lost to fraud and non-compliance through more targeted compliance activities

Embed insights in clinical services to improve outcomes and efficiency (e.g. medicine management, hospital readmissions, etc)



Care Management











Understanding the bottlenecks across the hospital contributing to Emergency Department performance

1

Bottleneck 1: AttendancesNo visibility of anticipated patient visits and presenting complaints

2

Bottleneck 2: TriagePatients wait for triage prior to treatment

3

Bottleneck 3: Waiting TimesUnpredictable demand for medical consults generating waiting time pressures

4

5Bottleneck 4: Clinical Support Services Patients waiting for diagnostics

Bottleneck 5: Discharge DestinationUnclear demand for discharge packages

How the ED planning tool can help overcome current operational challenges

• Show existing hospital capacity

• Predict ED and other volumes

• Understand implications on hospital capacity and service performance

• Complete what if analysis

• Understand effective mitigating actions to address potential failures

http://www.google.co.uk/url?sa=i&rct=j&q=&esrc=s&frm=1&source=images&cd=&cad=rja&uact=8&ved=0CAcQjRw&url=http://www.crabbscrosssurgery.nhs.uk/ppg.aspx&ei=JJb4VODsI4GqUM_TgrAE&bvm=bv.87519884,d.d24&psig=AFQjCNEUN6l1nAZh9r4xvP8CzaqZ8on7sA&ust=1425663849269351



Care Management











5% of patients driving 60% of health spend

Source: Basque Country Health Department 2009


An integrated care solution reduces cost by treating people before their symptoms deteriorate

Number of Hospital Days(*)

(*) Source: Roger Halliday, UK Department of Health; For illustrative purposes only

-4 Years

-3 Years

-2Years

-1Year

IntenseYear

+1 Year

+2 Years

+3 Years

+4 Years

+5 Years

0

10

20

30

40

50 Before Integrated Care

After Integrated Care

Patient hospital days

Target Population

Predictive analytics allow population segmentation and identification of those that will reach “peak utilisation” within a year


Accenture’s Predictive Health Intelligence (PHI) Platform is helping Life Sciences clients focus on patient outcomes

PATIENT EXPERIENCE MANAGEMENT

INTERACTION ENABLEMENT

SERVICE EXCHANGE

Cloud-based patient data & patient insight driven by interaction channels as well as health outcomes data (devices, EHR, etc) large data-sets to measure impact of patient services, further knowledge on

therapies and provide opportunities for improve outcomes

PATIENT DATA MANAGEMENT & INSIGHT

Identifying and adapting the services which are provided

based on understanding of the patient needs and ability to coordinate the experience

Connected, multi-channel interaction (apps, portals,

contact centers) with patients, physicians, nurses and SP’s to

patient care services

Multi-source (EHR’s, SP’s, vendors, devices), information

exchange providing inter-operability for data intake,

matching, distribution, security

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Predixion


Care Management / PHI Case Studies

Predictive Analytics/Population Health Management Pilot• 80% reduction in inpatient stays• 40% cost savings per target pop.

Chronic Population Management • Improved clinical HbA1C• Improved patient compliance• Decrease in average cost of

hospital stays

Chronic Health Coaching13% cost savings per patient

Integrated Disease Management• 50% decrease in ED visits • 65% reduction in inpatient

admission rates • Improvements in medication

compliance with ACE Inhibitors or ARBs

Multichannel Health Services Center ImplementationRemote monitoring asset deployment

Aged & Chronic Disease StrategyBusiness case input key into Council of Australian Government (COAG) planning

Patient Navigation ProgrammeHbA1C: 8.89 improved to 7.75

Large BCBS PlanReduced readmission rates by over 500 basis points via in-home visit programme

Diabetes Programme• Reduced patient

costs by 40%• Reduced ED

visits by 50%

http://www.health.nsw.gov.au/index.html


• Population of 210,000• 10% of the population has chronic

condition• Care center locations

• University Hospital La Fe • 6 Primary care centers

Context

Solution Summary

• Developed predictive analytic model to identify high risk patients (nearly 2x more accurately than CARS)

• Established innovative operating model with new organization, technology, population management and care center for patient follow-up

• Implemented low cost interventions to prevent acute high cost episodes

• Reduced high-risk patient costs by 65%

• Equates to 9% total healthcare cost reduction (applied against full population)

• Reduced hospital stays by 80% for this high risk group

• Increased inpatient bed capacity by 16%

• Reduced unplanned hospital visits by 38%

Benefits Achieved

Case Study: Chronic Disease Management through Predictive Analytics

Valencia Spain – Regional health authority was concerned about the rising costs of chronic disease. Accenture partnered with the region to provide analytic support and outsourced service to enable proactive care.


Accenture has identified 6 attributes critical to successfully delivering an analytical programme

StrategyClearly defined and agreed direction and scope of an analytical

capability to deliver actionable insight to enable the desired business outcomes

GovernanceClear understanding of the analytical organisational structure and

accountabilities with strong business leadership and sponsorship from the management team. Robust and trusted data governance

DataInternal sources of data are complete in content, valid, consistent, fit for purpose and timely. Ability to use unstructured and external data. Data completeness can enrich internal data to deliver further analysis.

PeopleAccess to people with appropriate analytical background, skills set

and expertise.

Methods/Evaluation

Using proven methodology and processes for continuous testing, learning and improvement.

TechnologyAvailability of data warehousing, analytical systems, big data and

social media platforms and ability to integrate with patient systems.


Summary of key lessons learned for health analytics programmes

Focus on the patient and outcome not the technology

Plan big, start small, scale fast

Your data is probably good enough – use it and show the value

Your clinical champion is critical

Start where there is a clear business case

Always be looking to industrialise

NICON Technology Enabling Change; Health Analytics Paul Pierotti Managing Director.

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