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GE Healthcare Camden Group Insights Blog

Webinar Reminder: Building an Analytics-Based Value Model to Validate Transformation Investments

Posted by Matthew Smith on Nov 29, 2016 2:10:38 PM

Please join GE Healthcare Camden Group for a complimentary, 60-minute webinarBuilding an Analytics-Based Value Model to Validate Transformation Investments, on Thursday, December 8, 2016, at 12:00 P.M., ET.

Date:

Thursday, December 8th, 12:00 P.M., Eastern

Background:

Healthcare organizations are struggling to understand the impact of their investments in population health initiatives. To help measure performance risk and evaluate return on investment ("ROI"), organizations are building and implementing analytics-based value models as decision-making tools. Creating these value models allows healthcare organizations to quantify risks and evaluate viability. It also allows organizations to measure and track ROI in digital health technology and resources associated with various programs aimed at managing the health of the populations they serve.

GE Healthcare Camden Group's team of analysts, data scientists, and actuaries builds comprehensive analytics-based value models for organization leaders (CFO, CMO, CIO, Population Health Leaders) wanting to evaluate their ROI from investments in care management programs, look to better manage utilization, and predict outcomes.

Overview:

In this complimentary webinar, members of the GE Healthcare Camden Group team will deliver an overview of the analytics-based value model and how high-performing healthcare organizations are leveraging these to guide strategic decision making and prioritize investments in value-based care initiatives.  

Topics to be Addressed:

Held in a round-table format with GE Healthcare Camden Group senior leaders representing the roles of an organization's CFO, CMO, and CIO, the webinar will address the following questions facing today's leaders:
  • Where should organizations invest resources in order to drive the most value from their care management programs?
  • What is the impact on their programs to both acute and ambulatory utilization?
  • Which programs are driving the greatest value and how are these measured?
  • What “value levers” are important in order to drive the best outcomes?
  • What is the expected outcomes from managing certain medical conditions and/or population risk cohorts?
  • What is the typical ROI of their care management programs and population health initiatives?
  • How can this information be used to support risk-based contracting with payers and other providers?

GE Healthcare Camden Group Presenters:

Marino_Dan.jpgDaniel Marino, MBA, MHA, Executive Vice President Mr. 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.

chopra2-110511-edited-239718-edited.jpgShaillee J. Chopra, PMP, Senior Manager Ms. 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.

 

DiLoreto.pngDavid DiLoreto, M.D., MBA Dr. DiLoreto, senior vice president at GE Healthcare Camden Group, is a physician-executive who is highly experienced in executive management, strategy and operations of healthcare delivery systems, and managed care companies. He has deep management expertise in community-based and academic health systems, large group medical practices, hospitals, and managed care organizations. His areas of specialty include clinical transformation, population health, business process improvement, leadership development, medical informatics, and data management and analytics.

GreenB1.pngRobert Green, MBA, FACHE, CHFP Mr. Green is a senior vice president and the practice lead for the Financial Operations and Transactions practice. He has more than 26 years of healthcare experience with 13 years of healthcare consulting experience and 13 years of provider-based financial, operational, and strategic experience among health systems, hospitals, medical groups, management services organizations, and physician hospital organizations.

 

To Register:

To register, simply click the button below, complete a short registration form, and press the "Cick to Register!" button. You will receive a confirming email. A second email will be sent the week of December 5th with webinar login/call-in instructions.

Please note: This webinar is intended for providers, provider organizations, and industry partners. Because of the proprietarty nature of the information shared during this webinar, independent consultants and consulting agencies will not be provided access to programming. GE Healthcare Camden Group reserves to the right to limit attendance at this event. 

Value Model, Webinar, Digital Health Analytics

Questions?

Please contact Matthew Smith at msmith@ge.com

Topics: Webinar, Daniel J. Marino, Shaillee Chopra, Digital Health Services and Data Analytics, Value Model, David DiLoreto, Robert Green

New Webinar: Building an Analytics-Based Value Model to Validate Transformation Investments

Posted by Matthew Smith on Nov 16, 2016 1:16:09 PM

Please join GE Healthcare Camden Group for a complimentary, 60-minute webinarBuilding an Analytics-Based Value Model to Validate Transformation Investments, on Thursday, December 8, 2016, at 12:00 P.M., ET.

Date:

Thursday, December 8th, 12:00 P.M., Eastern

Background:

Healthcare organizations are struggling to understand the impact of their investments in population health initiatives. To help measure performance risk and evaluate return on investment ("ROI"), organizations are building and implementing analytics-based value models as decision-making tools. Creating these value models allows healthcare organizations to quantify risks and evaluate viability. It also allows organizations to measure and track ROI in digital health technology and resources associated with various programs aimed at managing the health of the populations they serve.

GE Healthcare Camden Group's team of analysts, data scientists, and actuaries builds comprehensive analytics-based value models for organization leaders (CFO, CMO, CIO, Population Health Leaders) wanting to evaluate their ROI from investments in care management programs, look to better manage utilization, and predict outcomes.

Overview:

In this complimentary webinar, members of the GE Healthcare Camden Group team will deliver an overview of the analytics-based value model and how high-performing healthcare organizations are leveraging these to guide strategic decision making and prioritize investments in value-based care initiatives.  

Topics to be Addressed:

Held in a round-table format with GE Healthcare Camden Group senior leaders representing the roles of an organization's CFO, CMO, and CIO, the webinar will address the following questions facing today's leaders:
  • Where should organizations invest resources in order to drive the most value from their care management programs?
  • What is the impact on their programs to both acute and ambulatory utilization?
  • Which programs are driving the greatest value and how are these measured?
  • What “value levers” are important in order to drive the best outcomes?
  • What is the expected outcomes from managing certain medical conditions and/or population risk cohorts?
  • What is the typical ROI of their care management programs and population health initiatives?
  • How can this information be used to support risk-based contracting with payers and other providers?

GE Healthcare Camden Group Presenters:

Marino_Dan.jpgDaniel Marino, MBA, MHA, Executive Vice President Mr. 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.

chopra2-110511-edited-239718-edited.jpgShaillee J. Chopra, PMP, Senior Manager Ms. 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.

 

DiLoreto.pngDavid DiLoreto, M.D., MBA Dr. DiLoreto, senior vice president at GE Healthcare Camden Group, is a physician-executive who is highly experienced in executive management, strategy and operations of healthcare delivery systems, and managed care companies. He has deep management expertise in community-based and academic health systems, large group medical practices, hospitals, and managed care organizations. His areas of specialty include clinical transformation, population health, business process improvement, leadership development, medical informatics, and data management and analytics.

GreenB1.pngRobert Green, MBA, FACHE, CHFP Mr. Green is a senior vice president and the practice lead for the Financial Operations and Transactions practice. He has more than 26 years of healthcare experience with 13 years of healthcare consulting experience and 13 years of provider-based financial, operational, and strategic experience among health systems, hospitals, medical groups, management services organizations, and physician hospital organizations.

 

To Register:

To register, simply click the button below, complete a short registration form, and press the "Cick to Register!" button. You will receive a confirming email. A second email will be sent the week of December 5th with webinar login/call-in instructions.

Please note: This webinar is intended for providers, provider organizations, and industry partners. Because of the proprietarty nature of the information shared during this webinar, independent consultants and consulting agencies will not be provided access to programming. GE Healthcare Camden Group reserves to the right to limit attendance at this event. 

Value Model, Webinar, Digital Health Analytics

Questions?

Please contact Matthew Smith at msmith@ge.com

Topics: Webinar, Daniel J. Marino, Shaillee Chopra, Digital Health Services and Data Analytics, Value Model, David DiLoreto, Robert Green

Top 10 Considerations for an Optimal Data Science Strategy

Posted by Matthew Smith on Nov 2, 2016 1:59:35 PM

By Tony Ursitti, MS, Manager, GE Healthcare Camden Group


Data science is the field of techniques, tools and frameworks used to study and make meaningful conclusions from data. Data is being collected at an accelerated rate and the techniques, tools, and frameworks available to data scientists have evolved significantly over the last several years. The growth of this field has created tremendous opportunity as well as challenges for leaders in the healthcare industry. As this field evolves, healthcare leaders will need to become more knowledgeable about what investments are required in order to make the best use of their data.

There are ten key points for healthcare executives to consider when forming a data science strategy:

1. Realize that data is an asset, but its value is directly proportional to how it is used

Data is an asset to organizations in a similar way that buildings and medical devices are assets. An increasing share of the present and future value of health systems will be derived from the type of data that is collected and how effectively it is used to meet clinical, financial, operational, and strategic goals.

2. Understand the types of available data assets and prioritize the ones to acquire

As the pressure to cut costs and demonstrate high quality care continues to mount, understanding the types of data assets available and also the ones necessary to acquire is increasingly important. Consider how data assets are positioning the organization for future success…or future difficulty. For example, if a data element needed for calculating a quality metric that will be publicly reported in two years is not yet being captured, determine how quickly it can be captured. Two years from now, when that data becomes publicly reported, there will be no ability to go back and create a historical data record to use, and the organization could be understating the quality of care they provide simply because they don’t have the historical data to prove how well they actually performed.

3. Position your organization to compete on analytics

In the coming years, some organizations will thrive and others will struggle. Organizations that make smart use of data and analytics will have a strong competitive advantage over those that do not. Increasing pressure to cut costs and improve quality means increasing pressure to understand as quickly as possible the factors or organizational behavior that are contributing to positive as well as negative results.

4. Understand the importance of data science in getting the most from data assets

When planning to acquire the appropriate data assets, anticipate how the organization will make the best use of these assets once they have been acquired. Data science helps organizations start to understand some of the important relationships between practice patterns or other organizational behavior and undesired or desired outcomes. For example, it is important for organizations to know that their average length of stay at a particular hospital is increasing, but it is at least equally important to know why this increase is occurring and what, if anything, can be done about it. Data science helps uncover the why and enables organizations to make more informed strategic decisions.
 
One general principle for executives to keep in mind when thinking about data science is that good decisions require good knowledge, that good knowledge requires asking good questions of data, and that it is impossible to know what the “good questions” are unless you understand the scope of questions that are answerable. In other words, 30 years ago it would have been fruitless for executives to be asking questions like “what variables contribute to readmission risk and to what extent” because methods for answering that question did not exist in the way that they do today. Today, because of advances made in data science, that type of question is not only appropriate to ask but increasingly important to answer. Because data science has advanced so rapidly, the risk is no longer asking questions that cannot be adequately answered, but not understanding the breadth of questions that can be answered and, consequently, leaving them unasked.

5. Keep a focus on the critical problems

While starting or continuing on the journey of using the increasingly advanced techniques, tools, and frameworks that data science makes available, it is important to keep a focus on the problems that are most important for the organization. Data science is something like a Pandora’s box; insights beget insights and those insights beget more. Without the proper focus from leadership, data scientists will find endless interesting insights that have little or no strategic value for the organization. Good data scientists should be able to uncover insights buried in data that would otherwise be left undiscovered, but for this discovery to be relevant requires an appropriate level of understanding between leadership and data scientists about the most important strategic pain points the organization must address over the coming years.

6. There is not a “one size fits all” approach to data science

Each organization is at a different stage in the journey to deliver lower cost and high quality care while competing in local markets with different dynamics. Data insights that are of significant strategic value for one organization may be of little or no strategic value for another. For example, large multispecialty organizations can benefit from a robust site of service strategy that not only moves volume out of inpatient settings where appropriate, but also moves elective procedures from high cost inpatient facilities to lower cost inpatient facilities. For physician groups, the data and analysis requirements to build a site of service strategy would need to be more granular to be of any value.

7. Get the technical expertise required to succeed

Organizations will need access to technical expertise to help sort out the signal from the noise. Concepts like model accuracy, overfitting, and statistical significance will be important to understand in order to make sure that the inferences being drawn from modeling efforts are well founded.

8. Data science is not a “check the box” exercise

There are increasingly advanced techniques for making sense of data, and the organizational decision-making process must continue to evolve in order to keep up with and derive full benefit from these techniques. This means that the way organizations solved problems and developed strategies 5 to 10 years ago is no longer the best way to solve problems and develop strategy. As data science continues to advance, organizations must continue to evolve and make smart use of it.

9. Data literacy will be increasingly important at all levels of management

There is an increased need for data literacy within members of executive teams and across many operational areas within health systems. Good data scientists will be able to translate most of their technical knowledge into actionable insights for non-technical leaders. However, executives and other stakeholders will need to know enough to ask relevant questions about the data science with which they are presented to ensure nothing important is lost in translation. Iterative conversation between leadership and data scientists is incredibly powerful.

10. Competition for data scientists will increase

There is and will continue to be a shortage of data scientists in the market. In 2014, Accenture found that more than 90 percent of its clients planned to hire employees with data science expertise, but more than 40 percent cited a lack of talent as their number one problem. This problem is even greater in healthcare, an industry that is uniquely complex in which knowledge is highly specialized and takes years to develop. This means it is critical to start focusing now on building internal or external teams to support your organizational decision-making through data science.

Ursitti_Tony.pngMr. Ursitti is a manager with GE Healthcare Camden Group in the Digital Health and Advanced Analytics practice. He has more than seven years of analytics and leadership experience in both the consulting and provider settings. He focuses on helping health executives make data-driven strategic decisions through value model development using statistics, predictive modeling, advanced data mining, and machine learning techniques. He may be reached at tony.ursitti@ge.com.

 

Topics: Data Analytics, Data Governance, Digital Health Services and Data Analytics, Data Science, Tony Ursitti

Utilizing Analytics to Measure Risk and Evaluate ROI in Your Organization's Value-Based Care Initiatives

Posted by Matthew Smith on Oct 4, 2016 2:06:19 PM

By Shaillee Chopra, PMP, Senior Manager, and Daniel J. Marino, MBA, MHA, Executive Vice President, GE Healthcare Camden Group

Data AnalyticsHealthcare organizations transitioning from fee-for-service to value-based models are making substantial investments in building technology and operational infrastructure to drive new services and workflows. Developing an effective and an efficient care delivery system from which to identify and drive profitability under risk arrangements remains of utmost importance. However, developing an analytics framework to support population health management, evaluate potential and expected returns from investment continues to be a struggle for many healthcare organizations.

Creating an analytics-based evaluation model enables healthcare organizations to quantify risks and evaluate viability and value-add of outcomes associated with various decisions. It also allows them to measure and track return on their investments in technology and resources associated with various programs aimed at managing health of populations they serve.

An Analytics-Based Value Model for Population Health

The framework for this model is grounded in measurement of utilization by place of service. It provides near real-time insight into “what works and what does not” in an operational environment. It also serves as a mechanism to ensure an organization’s positive position during re-contracting discussions with payers since it is supported with demonstrable value of delivering the right care to the right patient at optimal cost in the most appropriate setting. It serves as an information-based decision making model that enables the organization to make the transition to pay-for-value while preserving margins and without upsetting the apple cart of existing payer -provider relationships.

The Need for a Value Model Within an Organization’s Population Health Framework

A value model allows your organization to develop a deeper understanding around which variables drive outcomes that impact decisions about investments and resource allocation. For example, high-performing and value-based organizations are committed to improving quality and reducing avoidable utilization and costs. Cost reductions are a byproduct of the reduction in avoidable ER and acute inpatient utilization for individuals with chronic conditions. These costs are offset by an increase in “good utilization” such as increased PCP visits, wellness screenings, and pharmacy costs associated with medication adherence.  An analytics-based value model allows your organization to meaningfully sift through large amounts of data to identify and isolate important variables for future strategic success.

It allows for assessment of returns on investments made in various disease management intervention programs for at-risk, rising-risk and chronically ill population cohorts. It identifies assets and value levers that can be leveraged to prioritize and tweak the operational models for optimal returns.

Finally, it allows your organization to use analytics as a cornerstone for an innovative and data-driven approach to population health management.

Key Questions to Ask Within Your Healthcare Organization

Top performing healthcare organizations that are invested in developing their analytic capabilities begin with the end in mind and work from an analytics roadmap. Below are some of the key questions to consider to ensure you are achieving outcomes you desire without “boiling the ocean” and wasting valuable resources on programs that have minimally aligned outcomes:

  • What are the key questions you want to answer? Do you have 3-5 clearly defined use cases?
  • Accuracy, validity and credibility of your data: Do you know what data is needed? Do you have the right data? Is the data useable, i.e., accurate and credible? What data do you not have? Do you have a data acquisition strategy?
  • Analytics roadmap: Have you established a needs based analytics framework within your organization? Do you have right skillset and adequate tools to conduct analytics? After you perform analytics do you know how to interpret the results and make them actionable?
  • Driving actions: Do you have an actionable strategy for executing on the results? What are the actionable opportunities to execute against? How are you evaluating competing analytic priorities for resources and investment?
  • Monitoring impact and evaluate results: Have you implemented processes to track performance as part of your activation plan? Are you tracking both outcomes and the steps required to achieve the outcomes? Are you leveraging predictive modelling to consider varied “What if” scenarios to continually optimize the focus areas of your operational work plan?

Utilizing an analytics-based value model allows your healthcare organization to optimally invest resources and dollars towards operational programs that generate outcomes and value most alignment with strategic goals.

Value Model, Health Analytics


chopra2-110511-edited-239718-edited.jpgMs. 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 shaillee.chopra@ge.com.

 

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 daniel.marino@ge.com.

Topics: Value-Based Care, Healthcare Analytics, Daniel J. Marino, Data Analytics, Shaillee Chopra, Digital Health Services and Data Analytics, Value Model

Determining ROI From Your Analytic Technology Investment

Posted by Matthew Smith on Sep 8, 2016 8:49:14 AM

By Mmekom Ekon, PMP, Consultant, GE Healthcare Camden Group

As the healthcare industry continues to make an accelerated move toward value-based care models, organizations are investing substantial amounts in analytic platforms to deliver insights that will drive  improved quality and reduced costs. Stakeholders also believe that these analytic solutions, with their predictive forecasting and trending capabilities, are key to successful value-based programs where they can help transform clinical and financial initiatives and address various regulatory and financial challenges that lie ahead.

The healthcare analytics market is stimated to reach $18.7 billion by 2020 (from $5.8 billion in 2015) at a combined annual growth rate of 26.5% during this forecast period. This places analytics among the top areas of spending growth for hospitals and health systems during this decade. 1 Given the projected increase in the overall analytics spend paired with low hospital operating margins, executives are faced with tough questions around return on investments on these technologies. Are these suite of business intelligence tools delivering as promised? How do you determine if these analytic platforms are providing value to your organization or if there’s any return on your technology investment?

Here are 3 key categories to consider when determining ROI on your analytics investment:

1. Organizational Penetration

What is the “analytics market share” within your organization? Who’s using it, and what is the percentage of your organization that uses or is aware of the capabilities of the analytic tool? Is there opportunity to “increase analytics market share” within your organization to get the tool to the right folks and get them to use the information from the tool?

The biggest challenges to the penetration of an analytic technology culture is fragmented ownership and limited access to skilled resources (super users) . A quick assessment of the departments and staff that use your current analytics platform will indicate how well your analytics platform is embedded in an organization, department, or individual workflows.

2. Utilization

What types of data and information are frequently produced from these reports? Without access to action-oriented reports with pertinent information, the ability to derive value from your investment is constrained. The true value of an analytic tool is to produce efficient and consistent reports. These reports are used at the executive or board level to make key decisions around hospital operations and allow key patient care staff (such as physicians, nurses, allied health professionals, and ancillary staff) to access key performance indicators and interactive dashboards. Such access allows them to deliver optimum quality of care while adhering to clinical best practices and minimizing costs for their patients.

3. Organizational Goal Alignment

What were your original goals for this investment? Can you tie any recent operational change to your analytic tool? The ability of your technology investment to contribute toward financial, clinical, and operational improvement projects is paramount to achieving value out of your technology.

Analytics has no value unless it is acted upon. Strong linkages to information produced from your analytic platform to cost and quality improvement is the chief value of any technology investment.

The successful use of any analytic tool requires establishing a framework that identifies the value-add of a product and its alignment to your organization’s strategic goals and objectives early on. Monitoring and measuring usability against this framework while adjusting utilization workflows and addressing organizational needs for data literacy and alignment with operational objectives are key factors that quantify ROI against your investment.

  1. http://www.marketsandmarkets.com/PressReleases/healthcare-data-analytics.asp

ekon.jpgMs. Ekon is a consultant with GE Healthcare Camden Group, specializing in the digital health and analytics. Prior to joining GE Healthcare Camden Group, Ms. Ekon served as a technology consultant with Crimson performance software. In this role, she managed several hospitals and health systems through Crimson software implementation to analyze and improve operational, clinical, and financial performance. She has also helped members to identify opportunities to improve operational, clinical, and financial performance as well as implement solutions to improve bottom line. She may be reached at mmekom.ekon@ge.com.

 

Topics: Value-Based Care, Healthcare Analytics, Digital Health Services and Data Analytics, ROI, Mmekom Ekon

Top 10 Recommendations When Selecting an Analytics Platform For Your Healthcare Organization

Posted by Matthew Smith on Sep 1, 2016 9:03:38 AM

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

The transition to value-based care for our healthcare industry is paired with the navigation of challenges related to shrinking margins and changing payment models. Analytics is often touted as the solution that will uncover new insights, drive cost reductions, improve quality, and enable competitive differentiation. Though investment in healthcare analytics technologies has skyrocketed in the past few years (estimated at close to $20 billion), organizations still struggle to realize a tangible return on their investment.

Instead of a singular technology product, analytics should be treated as an integrated approach to create an information architecture that provides meaningful insights that drive actions. Rather than building around fancy dashboards and functionality the product offers, organizations should shift the focus to creating operational capabilities that vendors have to build against. The following are 10 key recommendations to keep in mind when selecting an analytics platform for your healthcare organization.

  1. Outline key operational capabilities that the vendor partner must enable for your organization. As you begin with the end in mind, consider outlining what are the key strategic goals your organization must accomplish within the next 12, 24, and 36 months. What are some of the key operational outcomes that must be achieved to realize these goals? What are key market conditions that would be influencers to the roadmap? A few examples are:  your organization aims to capture market share by offering competitive services and offerings; referral management and managing out of network utilization are areas of concern; or entering into value-based contracts is imminent or has already occurred.
  2. Define key operations focused use case scenarios. Clearly outline the key problems for which you want to solve and/or the new insights/trends you want to gather from the analytics platforms (e.g., trends in referral patterns) and ask the vendor to demonstrate their solutions that are specific to these needs. This allows you to shift away from general “sales demonstrations” to tailored, meaningful discussions on how the technology platform will address your needs and challenges. It also offers insight into what workflows and capabilities for which you have to plan within your organization to effectively realize the value from this investment.
  3. Utilize the information framework as a blueprint to drive the technology selection process. Consider building a data integration roadmap that outlines the data types that would be integrated into the analytics platform and in what sequence and frequency. The framework will identify how your organization can monitor and address variability when the quality of data is in doubt. This framework acts as a blueprint against which existing and new technology vendor partners in your portfolio have to deliver..
  4. Establish a multi-disciplinary selection council that conducts product assessment from varied perspectives (technical, clinical, financial, administrative etc.) Leverage the data governance framework to provide input and oversight for product selection so that there is a clear sense of how it will be operationalized.
  5. Develop a detailed product functionality assessment listing and a weighted scorecard that assist in objective assessment of product functionality. Create a detailed outline of product functionality that is critical to activation of operations use cases. This can include, but is not limited to, a detailed outline of reports, dashboards, work lists, business intelligence logic, need to integrate with other systems that will consume the data, etc. Consider developing a scorecard that will assist the selection team to objectively evaluate each feature.
  6. Collaborate with the vendor partner to develop a future state solution framework.
    Vendor SelectionSuccessful implementation of analytics tools and the ability to generate actionable information are highly dependent on effective integration with the current technology portfolio. Consider creating an architecture notebook outlining the current technology footprint of your organization, where relevant data pools exist, data needs, and limitations. Outline known data integrity concerns that the analytics vendor must respond to during demonstration sessions.
  7. Understand vendor data consumption capabilities and future roadmap. As your operational needs grow so will the need to consume new and varied types of data sources. Evaluate the varied data types (claims, payer, clinical) that the product can ingest today and the format and frequency of it. Does that align with your information architecture? Examine known limitations and mitigation plans. Consider the vendor’s plan for ingestion of additional data types such as patient provided data, device integration, pharmacy, retail etc.
  8. Review the vendor product and services roadmap to assess long term impact against your organization’s strategy. Being an emerging technology area that is constantly evolving, most vendors are still developing various functionalities. As a result, it is not uncommon that vendors end up over promising and under delivering. Carefully assess the vendor product and services roadmap and compare against your organization strategy. Does this offer an opportunity for a development partnership or at risk arrangements for shared commitment and success?
  9. Compare the vendor implementation approach against your operational needs. Most times analytics projects become too complicated too fast. Consider instead an incremental build approach that is problem focused. Evaluate if the products’ implementation approach allows for a phased build and is it focused on providing immediate value. Outline key external dependencies that impact speed to market. Evaluate if the proposed implementation roadmap allows you to position it as a value add service for your members and stakeholders within the first 60 to 90 days.
  10. Develop total cost of ownership ("TCO") model for the product to be implemented, integrated and operationalized within your organization. Additional cost factors can include data sources integration costs, infrastructure maintenance, organizational resource needs for implementation, governance and data integrity oversight etc. Be sure you have a complete picture of short and long-term costs to avoid troubling surprises when it’s too late.

As you approach technology selection with the mindset for creating organizational capabilities (e.g., services, outcomes, and experience) vs. building around functionality that the product offers you will be able to build an analytics framework that can objectively measure the value it provides and achieve progress towards the end goals you want to realize.

Analytics Platform


chopra2-110511-edited-239718-edited.jpgMs. 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 shaillee.chopra@ge.com.

 

Topics: Healthcare Data, Data Analytics, Shaillee Chopra, Digital Health Services and Data Analytics

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.


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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 daniel.marino@ge.com.

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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