NICON Technology Enabling Change; Health Analytics Paul Pierotti Managing Director

Copyright © 2014 Accenture All rights reserved. 2 Health Outcomes: Complex relationship with spend, payer structure and provider structure

Copyright © 2014 Accenture All rights reserved. 3 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 Population Health 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)

Copyright © 2014 Accenture All rights reserved. 4 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 Population Health 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)

Copyright © 2014 Accenture All rights reserved. 5 Understanding the bottlenecks across the hospital contributing to Emergency Department performance 1 Bottleneck 1: Attendances No visibility of anticipated patient visits and presenting complaints 2 Bottleneck 2: Triage Patients wait for triage prior to treatment 3 Bottleneck 3: Waiting Times Unpredictable demand for medical consults generating waiting time pressures 4 5 Bottleneck 4: Clinical Support Services Patients waiting for diagnostics Bottleneck 5: Discharge Destination Unclear 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

Copyright © 2014 Accenture All rights reserved. 6 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 Population Health 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)

Copyright © 2014 Accenture All rights reserved. 7 5% of patients driving 60% of health spend Source: Basque Country Health Department 2009

Copyright © 2014 Accenture All rights reserved. 8 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 -2 Years -1 Year Intense Year +1 Year +2 Years +3 Years +4 Years +5 Years 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

Copyright © 2014 Accenture All rights reserved. 9 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 PHIELLFjordSFDCQcomSFDCQcomLiaison PHIELL Camp. Mgmt Predixion

Copyright © 2014 Accenture All rights reserved. 10 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 Coaching 13% 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 Implementation Remote monitoring asset deployment Aged & Chronic Disease Strategy Business case input key into Council of Australian Government (COAG) planning Patient Navigation Programme HbA1C: 8.89 improved to 7.75 Large BCBS Plan Reduced readmission rates by over 500 basis points via in- home visit programme Diabetes Programme Reduced patient costs by 40% Reduced ED visits by 50%

Copyright © 2014 Accenture All rights reserved. 11 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.

Copyright © 2014 Accenture All rights reserved. 12 Accenture has identified 6 attributes critical to successfully delivering an analytical programme Strategy Clearly defined and agreed direction and scope of an analytical capability to deliver actionable insight to enable the desired business outcomes Governance Clear understanding of the analytical organisational structure and accountabilities with strong business leadership and sponsorship from the management team. Robust and trusted data governance Data Internal 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. People Access to people with appropriate analytical background, skills set and expertise. Methods/ Evaluation Using proven methodology and processes for continuous testing, learning and improvement. Technology Availability of data warehousing, analytical systems, big data and social media platforms and ability to integrate with patient systems.

Copyright © 2014 Accenture All rights reserved. 13 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