Developing a Healthcare Analytics Strategy Across the Continuum of Care

Transcription

1 Developing a Healthcare Analytics Strategy July 2015

2 Healthcare Provider Analytics Investments Are Steadily Increasing Healthcare providers are still focusing their investment plans on more traditional BI (i.e., reporting on facts) rather than on analytics that interrogates the data and provides insight to improve decision making. 75% of providers say they d invest $1 million in big data and analytics 1 of providers indicated the hiring of new analysts to support new contract models 2 30% of providers indicated the acquisition of analytics technology to support new contract models 2 Larger organizations are looking for more dynamic real time analysis of health data for Government planning Insights and management purposes Healthcare providers still focusing their investment plan on more traditional BI (i.e., reporting on facts) rather than on analytics that interrogates the data and provides insight to improve decision making 1. Business Strategy: Big Data and Analytics in Healthcare is an Emerging Market (IDC Health Insights HI# ). 2. Business Strategy: Providers Continue to Lag Behind Payers in Investments in Accountable Care (IDC HI#253591). pg 2

3 Drivers of Analytics Globally Protecting patient privacy and cybersecurity, which are key compliance mandates that come with incentives and penalties Ubiquitous availability of mobile devices and proliferation of Internetconnected devices Healthcare reform emphasizing cost and clinical outcomes, resulting in IT innovation 3rd Platform technology (mobile, social, cloud and big data and analytics) adoption and increased computing power Compliance to care delivery standards, quality, and best practices Increasing access to healthcare and social care through technology Unsustainable healthcare costs pg 3

4 Common Use Cases for Analytics 45% 70% of providers indicated their top reason for investing in analytics is to analyze patient behaviors and conditions to determine the most effective pathway of providers indicated illness/ disease progression was the reason to invest in analytics 50% of providers indicated organization resource utilization and turnover was a top reason for investment 4 Determine drivers of re-admissions for patients and avoid un-necessary re-admissions 4 Understand treatment variations and establish best practices 4 Leverage genomic data globally to personalize treatments for complex cancer patients to improve life expectancy, quality of life, and costs 4 Identify psychological and social drivers of patient compliance to chronic care paths to improve overall health and avoid disease progression globally Source: 3 IDC European Healthcare Provider Survey 2014/2015 pg 4

5 Adoption Maturity Model for Big Data Analytics 0% 16.7% 57.8% 25.5% 0% Ad Hoc Opportunistic Repeatable Managed Optimized Maturity Stage Definitions Ad hoc pilot projects Opportunistic un-budgeted projects Repeatable processes and data analytics that Financial can be Insights replicated Managed budget, enterprise recognition Optimized maintenance and improvement of established strategy There are 5 stages of maturity for big data analytics that must be traversed ad hoc, opportunistic, repeatable, managed, and optimized across five organizational dimensions (intent, data, processes, people, and technology). Distribution of maturity for hospitals across the five stages is consistent with other industries with the largest number of hospitals (58%) in the repeatable stage. Unlike other industries, hospitals are not represented in the ad hoc or the optimized stages of maturity. High and low achievers have reached the managed stage for the dimension of intent 41% of high achievers and 38% of low achievers. The greatest variation between high and low achievers is in the data dimension. Over 50% of high achievers were in the repeatable stage and 54% of low achievers were in the opportunistic stage. Source: Business Strategy: IDC MaturityScape Benchmark - Big Data and Analytics in U.S. Acute Care Hospitals (IDC, HI# ). N= 100 acute care hospitals. Source: IDC. pg 5

6 Best Practices: Intent Healthcare organizations attempting to improve quality and manage costs must make analytics an organizational priority invest in people, processes, and technology. 4 47% of high achievers and 31% of low achievers manage their big data analytics at the enterprise level 4 Create a strategic and operational plan for data and analytics. Only 26% of providers have a business intelligence strategy Don t overlook the importance of data governance and data management. 4 Assign a Chief Data Officer and data stewards who are responsible for the development and compliance of data related policy and procedure and the quality of data sources 4 80% of data and analytic investment will fail due to a lack of data management and governance 4 There s a 42% variation in data governance between high and low achievers 4 Align BDA efforts evenly over the 5 dimensions in organizations where there is tight alignment of dimensions, 93% were high achievers and 7% were low achievers Analytics for population health management must be administrative-led but physician-driven. Government Chief Operating Insights Officer of a multi-hospital complex Source: Business Strategy: IDC MaturityScape Benchmark - Big Data and Analytics in U.S. Acute Care Hospitals (IDC, HI# ) pg 6

7 Best Practices: People While executive leadership is critical, be sure to have managers involved in the planning and execution of big data and analytics. 4 Collaboration among key stakeholders at the business, analytic, and IT levels is key to identifying the data types needed by business users 4 30% of high achievers and only 8% of low achievers reported significant collaboration 4 Recruit and retain IT staff with strategy and project management skills 4 There is a 25% difference between high and low achievers in their ability to be very successful in recruiting staff for data collection, integration, data preparation, and management 4 Understand and manage the cultural challenge of change with continuous reminders of the value of big data and analytics initiatives 4 Involve physicians early in the adoption of analytic initiatives they will be the greatest critics of the data and its quality We Financial gave Insights our physicians six months to work with their performance data before any penalties or bonus were adopted. This gave the physicians time to get comfortable with the performance data and make changes to their practices to achieve their goals. Analyst in a large group Source: Business Strategy: IDC MaturityScape Benchmark - Big Data and Analytics in U.S. Acute Care Hospitals (IDC, HI# ). ** High achievers are those organizations who reported that their Big Data and Analytics met or exceeded their company s expectation. pg 7

8 Best Practices: Technology Ensure technology meets performance expectations. 4 Be sure your vendor can incorporate multiple data sources from both internal and external sources, and can efficiently process increasing volumes of data 4 Analytics should support the enterprise requirements including financial, operational, and clinical 4 Technology platform must be able to grow with the client s organization and have the flexibility to meet ever-changing requirements 4 Analytic platforms must support end-user self-service Analytic tools are key to end-user adoption be sure your organization has the right tools 4 High achievers were 50% more satisfied with their analytic tools Technology vendors must be willing to enter into a partnership with their clients to reach analytics goals. CIO for a large integrated delivery system in the mid-west Source: Business Strategy: IDC MaturityScape Benchmark - Big Data and Analytics in U.S. Acute Care Hospitals (IDC, HI# ) pg 8

9 Best Practices: Data High quality and delivery of data to drive the next best action are key to data maturity. 4 Data from big data and analytics initiatives must be actionable and available at the point of care 4 Integrate structured data with other sources to gain greater insight 4 Recognize and plan for analytics as much if not more of a business challenge than as a technical challenge 4 By 2018, 80% of healthcare data will pass through the cloud as providers leverage cloud-based technologies and infrastructure for data collection, aggregation, analytics, and decision making 4 Providing patient data at the point of care dramatically improved our organization s ability to close gaps in care. Chief Operating Officer for a multi-hospital delivery system in the mid-atlantic 4. IDC FutureScape: Worldwide Healthcare Predictions 2015 (IDC HI# ) pg 9

10 Best Practices: Process 4 Establish continuous process improvement enabled by quantitative feedback and from innovative pilot programs 4 Establish service -level agreements and processes to deliver data and analysis 4 Establish processes for data quality review and root-cause analysis to correct quality issues in the source system 4 Create processes and procedures to collect end-user requirements The secret sauce for our organization s success ($8 million in savings) is driven by the data. Weekly our physicians review performance results and create action plans. Chief Medical Officer, for a family practice in the West pg 10

11 Essential Guidance 4 The transformation to value-based care is built on analytics 4 Establish analytics as a top priority 4 Perform a gap analysis 4 Develop a strategic and operational plan to improve analytic strength 4 Invest in analytics keeping in mind that it s more than technology it is about vision, people, processes, data, and technology 4 Remember that value-based care is a journey not a destination pg 11

12 Qlik Healthcare Solutions Qlik enables healthcare organizations to explore clinical, financial and operational data through visual analytics to discover insights, which lead to improvements in care, reduced costs and deliver higher value to patients. More than 1,500 healthcare providers rely on Qlik solutions to deliver information to the right people at the right time, supporting and enabling transformation across clinical processes, quality of care, finance and workforce optimization. For more information, visit All IDC research is 2015 by IDC. All rights reserved. All IDC materials are licensed with IDC s permission and in no way does the use or publication of IDC research indicate IDC s endorsement of Qlik products/or strategies. pg 12