GE Healthcare Camden Group Insights Blog

5 Key Questions to Ask when Building an Analytics Framework for your Healthcare Organization

Posted by Matthew Smith on Jul 28, 2016 11:30:09 AM

By Shaillee Chopra, PMP, Senior Manager, GE Healthcare Camden Group

As the healthcare industry continues to make the shift towards value-based care models, organizations are faced with an increasing need to invest in technology platforms that offer analytics-based decision making. Faced with rapidly evolving strategic needs and surrounded by abundance of technology choices, healthcare executives struggle to conceptualize an effective approach to creating an analytics framework for their organization. Rather than adding one more product to the portfolio, organizations want to create an information framework that drives decisions and is action oriented.

Following are key strategic questions to ask when building an analytics platform for your organization. This approach ensures that you are able to successfully outline a data and analytics strategy that leverages adequate and accurate data across the network to create an action-oriented knowledge framework that is closely aligned with the value proposition.

1. What are the key problems you wish to solve?

Key to establishing an analytics framework that drives decision making and actions within the organization is to ensure that you start with the end in mind. What are some of the key objectives that your organization wants to achieve? Is facilitating transitions of care within the integrated network an immediate need? Is your organization aiming to capture market share by offering competitive services and offerings? Is referral management and reducing patient outmigration (often referred to as ‘patient leakage’) an area of concern? Is entering into value-based contracts one of the long-term goals for your organization? Succinctly outlining end goals guides what problems need to be solved for and helps conceptualize knowledge framework that will assist with the decision making.

2. What type of data is required to build this information framework and at what frequency?

Value-based goals and metrics often require harmonized data across the continuum. Atypical data types include, but are not limited to, billing data, inpatient EMR data, outpatient EMR data, ambulatory data from employed and affiliate provider practices, claims data from payors, HIE data, external pharmacies data, bedside monitoring, and at-home monitoring data.

Outline which data types are required to be updated in real time to support predictive analytics needs (clinical data elements such as diagnosis, problems, medications, etc.) and which ones can be brought in a retrospective format (claims, utilization etc.). This will assist you in establishing an integration architecture with various source systems across the network. Developing integration architecture also offers an opportunity to estimate realistic answers to how much the infrastructure will cost and how long will it take.

Consider building a data integration roadmap that outlines the sequence in which various data domains would be aggregated into the analytics platform. 

3. What is the data worth?

The relative importance of data from varied locations across a continuum of an integrated care network can influence your data acquisition strategy.  Key considerations include:

  • Data relevance. How relevant is the data type in your decision making process and what problems does it help solve for?
  • Data accuracy. Are all expected attributes of data accessible and transmittable? Is there minimal uncertainty due to workflow at the front lines?
  • Data frequency. Is the data available in a required format (discrete and structured vs. static image)? Is the data transmittable at a desired pace (updates to lab data might be required in real time to facilitate transitions of care; while claims data can be loaded in retrospectively to produce trends in cost-of-care)?
  • Data depth. Is there needed depth of historical data that is aligned with analytic needs (certain specialties such as oncology clinical historical data needs go farther back than primary care)?
  • Data consistency. Are the standardized vocabularies integrated into data domain offering consistent definition and interpretation of each data element?

4. What organizational capabilities need to be developed to support the future state?

It is important to identify key consumers of analytics within your organization early on. Understanding key information needs of the users, level of data literacy (ability to understand and interpret data) and the ability to exploit information offered via an analytics platform determines the pace at which your organization can adopt a knowledge-based decision making system.

Consider setting up a multidisciplinary data governance council that aims to provide:

  • Guidelines for management of the quality of data being leveraged across the continuum
  • Data literacy within consumers of analytics across the continuum
  • An operational framework that allows for maximizing data exploitation for the organization’s benefit

5. What are some key requirements for technology solutions that will aggregate and harmonize this data?

Product selection driven by clearly outlined end goals that the organization wants to achieve and key functional capabilities it wants to enable (care coordination, consumer engagement, increase market share, stop leakage) ensures that technology is successfully positioned as an enabler of operational workflows.

Key considerations when outlining requirements for an aggregation platform include:

  • Capabilities enablement. How does the technology platform operationalize key functional areas for the organization?
  • Product functionality. What are some of the key functionality needs to support operational objectives for the organization?
  • Data consumption abilities. What is the data footprint that the product can consume (clinical, financial, socio-demographic etc.)? What is the integration footprint with key healthcare technology vendors?
  • Product roadmap. What is the product roadmap, and how does it align with your organization’s strategic goals?
  • Speed to implementation. What is the product implementation methodology? What are the key resource needs from your organization, and what are key external dependencies that impact speed to market?

Transitioning to outcomes-based decision-making frameworks enables your healthcare organization to harness the power actionable analytics. You can leverage these best practice recommendations to avoid commonly observed pitfalls and implement a sustainable and scalable solution.

Digital Health, Advanced Analytics

Chopra.pngMs. Chopra is a senior manager with GE Healthcare Camden Group and specializes in developing and managing innovative technology portfolios for value-based and clinically integrated healthcare networks. She is highly experienced in leading information technology and consumer experience strategy development, as well as transformations to enable clinical integration, accountable care, and population health management strategies for organizations invested in innovation and transformation of care delivery models. She may be reached at



Topics: Analytics, Data Analytics, Digital Health Strategy, Information Framework, Shaillee Chopra

New Download: Digital Health Services and Advanced Analytics

Posted by Matthew Smith on Jun 15, 2016 12:51:33 PM

Are you unsure of how to start the process of building a data strategy and an information roadmap? Are you worried that you're not aggregating the right data? Are you stuck in neutral and not making any headway with your population health analytics vendor? 

If so, GE Healthcare Camden Group can start you on the right path.

Start here...with our PDF outlining ourDigital Health Services and Advanced Analytics practice.

The PDF includes pages on:

  • Our Philosophy and Approach
  • Reasons Why Healthcare Analytics Vendor Implementations Fail
  • Initial Questions from Leadership and Teams
  • Data Analytics Strategy Components
  • Information Services and Advanced Analytics

Simply click the button below to get started!

Digital Health, Advanced Analytics

Topics: EHR, EMR, Value-Based Care, Data Analytics, Digital Health Strategy, Digital Health Services and Data Analytics

Meet the Practice: Digital Health Services and Advanced Analytics

Posted by Matthew Smith on Jun 14, 2016 1:45:24 PM

This Meet the Practice overview, examining the new Digital Health Services and Advanced Analytics practice, is part of an ongoing series in which GE Healthcare Camden Group's senior leaders share insights into our six practice areas.

Practice Lead: Daniel J. Marino, Executive Vice President

Explain the needs and problems you solve for clients through this practice.

The U.S. healthcare system is experiencing significant shifts in the way healthcare is accessed and delivered, fueling a strong desire for operational efficiencies, value-driven outcomes, and action-oriented information. In order to ensure that intelligible, actionable information is created, organizations are creating digital health strategies that focus on producing value-driven analytics while supporting their operational capabilities and needs.

As a result, there is a need to assist healthcare provider organizations in:

  • Building an operationally-focused information services and analytic strategy
  • Provide direction in creating comprehensive and powerful advanced analytics
  • Incorporating enterprise-wide data governance integrating clinical, financial and technical master data management
  • Focusing on analytic deliverables and capabilities and less on application functionality
  • Improving integration of applications and technology with provider workflows and care model delivery
  • Maximizing the optimal use of existing applications
  • Providing objective, vendor agnostic professional advisory services to provider organizations

Ultimately, we enable clinically integrated organizations to maximize value through an operationally driven digital health strategy.


What is the value or ROI that is provided by solving these challenges?

Organizations with a comprehensive digital health and analytics roadmap will be able to realize benefits in strategic development, operational optimization, and performance effectiveness.

From a strategic development point-of-view, organizations will be able to expand their provider networks through enhanced connectivity, integrated care management, analytics, and value-based programs. Operationally, they will benefit from real-time performance data which supports operational output for clinical, financial, and contracting objectives. They will also see improved performance effectiveness via cost-of-care modeling to support value-based contracting, and improved outcome tracking and clinical program effectiveness measures.

What types of organizations need your services?

We engage provider organizations at various stages of digital preparedness. Many organizations are simply looking for a starting point in working with their population health analytics vendor and want to ensure that they have a results-oriented digital health development blueprint and are aggregating the right data that leads to meaningful information. Other organizations are looking to create a complex data strategy and roadmap amidst a sea of ever-changing priorities and information requirements.

What synergies differentiate this practice area (and GE Healthcare Camden Group)?

Within GE Healthcare Camden Group, our Digital Health Services and Advanced Analytics practice provides a 360 degree operational perspective to the information services and analytic challenges existing within healthcare organizations.

Because we are vendor agnostic, our objective experts understand the clinical and operational impact of the ever-changing technology landscape and are equipped to advise on IT/IS strategies, system selection, activation support, and advanced analytics.

As a firm, GE Healthcare Camden Group provides professional advisory services across the care continuum incorporating our expertise in information services and analytics. We have built a reputation as a trusted partner to clinical, operational, and financial healthcare leaders by helping them close the gap between their challenges and the optimal solutions for success.

To learn more about GE Healthcare Camden Group's Digital Health Services and Advanced Analytics practice, please click the button below for a PDF download.

Digital Health, Advanced Analytics

Marino_Dan.jpgMr. Marino is an executive vice president with GE Healthcare Camden Group with more than 25 years of experience in the healthcare field. Mr. Marino specializes in shaping strategic initiatives for healthcare organizations and senior healthcare leaders in key areas such as population health management, clinical integration, physician alignment, and health information technology. With a comprehensive background in all aspects of practice management and hospital/physician alignment, Mr. Marino is a nationally acknowledged innovator in the development of Accountable Care Organizations and clinical integration programs. He may be reached at

Digital Health Services and Advanced Analytics

Topics: Value-Based Care, Daniel J. Marino, Data Analytics, Digial Health, Digital Health Strategy, Digital Health Services and Data Analytics

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