This document provides a guide to using analytics to control healthcare costs. It explains that analytics can help replace intuitive decision making with data-driven insights. Healthcare organizations have large amounts of data and a need to reduce costs, making them well-suited for analytics. The guide prescribes steps for launching an analytics initiative and introduces nFORM Health Benefits Analytics, a full-support analytics solution that helps users implement analytics through training and ongoing consultation.
Healthcare Analytics: Right-Brain Advice in a Left-Brain WorldHealth Catalyst
U.S. healthcare is badly missing the soft, human side of healthcare analytics, especially as it impacts clinicians. How do we fix that? This webinar explores those ideas.
You won’t hear Dale talk about SQL, inner joins, outer joins, R, Python, logistic regression, random forest, or convolutional neural networks but instead, in this webinar he talks about the principles and philosophy of analytics.
For the most part, we’ve figured out the technology of analytics. That is all left-brain thinking—analytical, logical and methodical in nature—and it is literally getting easier every day with new data technology. But, in healthcare, we’re missing the right-brain thinking—creative and artistic in nature—that has almost nothing to do with technology but has everything to do with the human side of pursuing “data driven healthcare.”
Right-brain thinking is required for the oddities and shortcomings of healthcare data, and how to manage those shortcomings in the context of delivering data to the humans who we hope will consume it. The right-brain relates to the personality characteristics of the people who are leading your analytics strategy. It relates to the leadership culture of the organization and where that culture resides on a scale of transparency, internally and externally. The right-brain relates to behavioral economics, evolutionary psychology, human decision making theories, and the fundamental factors that motivate or demotivate human behavior. The right-brain relates to concepts like experimental design and PICO—patients, interventions, comparisons, and outcomes—that, if followed, can make your analytics more truthful and believable. It has to do with the way we negotiate and structure performance-based contracts that are loaded with quality metrics that either measure things that can’t be measured accurately or may measure the wrong thing, altogether.
You see, right-brained thinking in this left-brain world of analytics relates to a bunch of things, but mostly it relates to the Golden Rule of Data. Do unto others with data as you would have them do unto you.
The Future of Personalized Health Care: Predictive Analytics by @Rock_HealthRock Health
View the archived webinar here: https://www.youtube.com/watch?v=UJak41hIDWc
How can we use new and existing sources of data to deliver better, personalized care? Predictive analytics underlies what has always been conducted by doctors through their training, experience, and decision-making. Dozens of new digital products have hit the market and $1.9B has flowed into the space since 2011—but what does it take for an algorithm to accurately and reliably impact care?
Purchase the report here: https://gumroad.com/l/gzbzV
Clinical Decision Support: Driving the Last MileHealth Catalyst
Self-driving cars have become the most visible form of computer-aided decision support in society. What can we learn from these innovations—both good and bad, technically and culturally—about computer-aided decision support for clinicians? The adoption of EHRs provided a foundation; what and how do we build on that foundation to help clinicians, and patients, benefit from meaningful, precise decision support?
Scott Weingarten, MD, MPH, and Dale Sanders explore clinical decision support in a joint webinar. Dr. Weingarten is recognized throughout the U.S. and international healthcare space as a physician and for his contributions to decision support, including his role in founding Zynx and Stanson Health. Dale brings a technologist’s viewpoint to the conversation, informed by his background in computer-aided decision support in the healthcare, military, and national intelligence sectors.
During this webinar, learn more about the following topics:
-How clinical decision support can improve the quality, safety, and value of care.
-How developments in the field of artificial intelligence will impact clinical decision support.
-The conceptual framework for digitizing an industry.Tradeoffs in artificial intelligence models between data volume and algorithm complexity.
-The approach to digitization in the automobile and aerospace industries.
-Shortcomings in current healthcare data.Future aspirations and plans for further digitization of healthcare.
Six Steps to Managing an Infection Control BreachHealth Catalyst
Despite widespread efforts to improve patient safety, infection control breaches still happen at an alarming rate. In order to improve patient safety and prevent infections, healthcare organizations need to have infection control procedures in place and regularly assess protocols and adherence to these policies. In the case of an infection control breach, organizations need to be prepared to act quickly and follow a six-step evaluation procedure outlined by the CDC:
1. Identify the infection control breach.
2. Gather additional data.
3. Notify and involve key stakeholders.
4. Perform a qualitative assessment.
5. Make decisions about patient notification and testing.
6. Handle communications and logistical issues.
Opportunity analysis uses data to identify potential improvement initiatives and quantifies the value of these initiatives—both in terms of patient care benefits and financial impact. This process is an effective way to find unwarranted and costly clinical variation and, in turn, develop strategies to reduce it, improving outcomes and saving costs along the way. Standardizing the opportunity analysis process makes it repeatable and prioritizes actionable opportunities.
Quarterly opportunity analysis should follow four steps:
Kicking off the analysis by getting analysts together to do preliminary analysis and brainstorm.
Engaging with clinicians to identify opportunities and, in the process, get clinician buy in.
Digging deeper into the suggested opportunities to prioritize those that offer the greatest benefits.
Presenting findings to the decision makers.
Survey Shows the Role of Technology in the Progress of Patient SafetyHealth Catalyst
A lack of effective technology is impeding the progress of patient safety, according to a 2018 survey of healthcare professionals. Even though most healthcare organizations claim safety as a priority, serious challenges remain to making a significant impact on patient safety outcomes.
Survey respondents said ineffective information technology and the related lack of real-time warnings for possible harm events were the top barriers to improving patient safety. They cited a number of key obstacles:
Lack of resources.
Organization structure.
Lack of reimbursement for safety measures.
Changes in patient population.
This survey of more than 400 healthcare professionals tackles a big question many hospital leaders are asking: Why aren’t we seeing improvements in patient safety despite our efforts?
For a complete podcast interview on this topic with Jim Kean, visit: http://rebootedbody.com/006/
Check out wellnessFX: http://rebootedbody.com/wellness/
And find more information on sustainable health, nutrition, fitness, and psychology at http://rebootedbody.com
Healthcare Analytics: Right-Brain Advice in a Left-Brain WorldHealth Catalyst
U.S. healthcare is badly missing the soft, human side of healthcare analytics, especially as it impacts clinicians. How do we fix that? This webinar explores those ideas.
You won’t hear Dale talk about SQL, inner joins, outer joins, R, Python, logistic regression, random forest, or convolutional neural networks but instead, in this webinar he talks about the principles and philosophy of analytics.
For the most part, we’ve figured out the technology of analytics. That is all left-brain thinking—analytical, logical and methodical in nature—and it is literally getting easier every day with new data technology. But, in healthcare, we’re missing the right-brain thinking—creative and artistic in nature—that has almost nothing to do with technology but has everything to do with the human side of pursuing “data driven healthcare.”
Right-brain thinking is required for the oddities and shortcomings of healthcare data, and how to manage those shortcomings in the context of delivering data to the humans who we hope will consume it. The right-brain relates to the personality characteristics of the people who are leading your analytics strategy. It relates to the leadership culture of the organization and where that culture resides on a scale of transparency, internally and externally. The right-brain relates to behavioral economics, evolutionary psychology, human decision making theories, and the fundamental factors that motivate or demotivate human behavior. The right-brain relates to concepts like experimental design and PICO—patients, interventions, comparisons, and outcomes—that, if followed, can make your analytics more truthful and believable. It has to do with the way we negotiate and structure performance-based contracts that are loaded with quality metrics that either measure things that can’t be measured accurately or may measure the wrong thing, altogether.
You see, right-brained thinking in this left-brain world of analytics relates to a bunch of things, but mostly it relates to the Golden Rule of Data. Do unto others with data as you would have them do unto you.
The Future of Personalized Health Care: Predictive Analytics by @Rock_HealthRock Health
View the archived webinar here: https://www.youtube.com/watch?v=UJak41hIDWc
How can we use new and existing sources of data to deliver better, personalized care? Predictive analytics underlies what has always been conducted by doctors through their training, experience, and decision-making. Dozens of new digital products have hit the market and $1.9B has flowed into the space since 2011—but what does it take for an algorithm to accurately and reliably impact care?
Purchase the report here: https://gumroad.com/l/gzbzV
Clinical Decision Support: Driving the Last MileHealth Catalyst
Self-driving cars have become the most visible form of computer-aided decision support in society. What can we learn from these innovations—both good and bad, technically and culturally—about computer-aided decision support for clinicians? The adoption of EHRs provided a foundation; what and how do we build on that foundation to help clinicians, and patients, benefit from meaningful, precise decision support?
Scott Weingarten, MD, MPH, and Dale Sanders explore clinical decision support in a joint webinar. Dr. Weingarten is recognized throughout the U.S. and international healthcare space as a physician and for his contributions to decision support, including his role in founding Zynx and Stanson Health. Dale brings a technologist’s viewpoint to the conversation, informed by his background in computer-aided decision support in the healthcare, military, and national intelligence sectors.
During this webinar, learn more about the following topics:
-How clinical decision support can improve the quality, safety, and value of care.
-How developments in the field of artificial intelligence will impact clinical decision support.
-The conceptual framework for digitizing an industry.Tradeoffs in artificial intelligence models between data volume and algorithm complexity.
-The approach to digitization in the automobile and aerospace industries.
-Shortcomings in current healthcare data.Future aspirations and plans for further digitization of healthcare.
Six Steps to Managing an Infection Control BreachHealth Catalyst
Despite widespread efforts to improve patient safety, infection control breaches still happen at an alarming rate. In order to improve patient safety and prevent infections, healthcare organizations need to have infection control procedures in place and regularly assess protocols and adherence to these policies. In the case of an infection control breach, organizations need to be prepared to act quickly and follow a six-step evaluation procedure outlined by the CDC:
1. Identify the infection control breach.
2. Gather additional data.
3. Notify and involve key stakeholders.
4. Perform a qualitative assessment.
5. Make decisions about patient notification and testing.
6. Handle communications and logistical issues.
Opportunity analysis uses data to identify potential improvement initiatives and quantifies the value of these initiatives—both in terms of patient care benefits and financial impact. This process is an effective way to find unwarranted and costly clinical variation and, in turn, develop strategies to reduce it, improving outcomes and saving costs along the way. Standardizing the opportunity analysis process makes it repeatable and prioritizes actionable opportunities.
Quarterly opportunity analysis should follow four steps:
Kicking off the analysis by getting analysts together to do preliminary analysis and brainstorm.
Engaging with clinicians to identify opportunities and, in the process, get clinician buy in.
Digging deeper into the suggested opportunities to prioritize those that offer the greatest benefits.
Presenting findings to the decision makers.
Survey Shows the Role of Technology in the Progress of Patient SafetyHealth Catalyst
A lack of effective technology is impeding the progress of patient safety, according to a 2018 survey of healthcare professionals. Even though most healthcare organizations claim safety as a priority, serious challenges remain to making a significant impact on patient safety outcomes.
Survey respondents said ineffective information technology and the related lack of real-time warnings for possible harm events were the top barriers to improving patient safety. They cited a number of key obstacles:
Lack of resources.
Organization structure.
Lack of reimbursement for safety measures.
Changes in patient population.
This survey of more than 400 healthcare professionals tackles a big question many hospital leaders are asking: Why aren’t we seeing improvements in patient safety despite our efforts?
For a complete podcast interview on this topic with Jim Kean, visit: http://rebootedbody.com/006/
Check out wellnessFX: http://rebootedbody.com/wellness/
And find more information on sustainable health, nutrition, fitness, and psychology at http://rebootedbody.com
Three Cost-Saving Strategies to Reduce Healthcare SpendingHealth Catalyst
Health systems continue to face fiscal challenges and burdens due to changing reimbursement rates, COVID-19, and managing the aftermath of care disruptions from the pandemic. Operating on thin margins with limited resources means health systems need to adopt alternative cost-saving measures to maximize limited resources.
Comprehensive, reliable data increases visibility into expenses across the care continuum so that leaders can leverage new methods to save money, generate income, and accelerate cashflow to keep patients healthy and hospital doors open. With access to recent data, health systems can focus on three cost-saving strategies:
Increase physician engagement.
Predict propensity to pay.
Implement evidence-based standards of care.
The Digitization of Healthcare: Why the Right Approach Matters and Five Steps...Health Catalyst
While many industries are leveraging digital transformation to accelerate their productivity and quality, healthcare ranks among the least digitized sectors. Healthcare data is largely incomplete when it comes to fully representing a patient’s health and doesn’t adequately support diagnoses and treatment, risk prediction, and long-term health care plans. But even with the obvious urgency for increased healthcare digitization, the industry must raise this trajectory with sensitivity to the impacts on clinicians and patients. The right digital strategy will not only aim for more comprehensive information on patient health, but also leverage data to empower and engage the people involved.
Health systems can follow five guidelines to digitize in a sustainable, impactful way:
Achieve and maintain clinician and patient engagement.
Adopt a modern commercial digital platform.
Digitize the assets (the patients) and the processes.
Understand the importance of data to drive AI insights.
Prioritize data volume.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Why Clinical Quality Should Be Your Core Business StrategyHealth Catalyst
Over 100 years ago, healing professionals and healthcare itself went through a massive transformation that led us to the models of care delivery that we use today. Dr. Brent James argues that we are now, again, at a once-in-a-century inflection point to change the course of healthcare. Change takes real effort, but provides massive opportunity.
Those changes include a move away from the highly-profitable fee-for-service payment to fee-for-value. An IOM report, published in 2010, substantiated that more than a third of healthcare spending is waste. Pay-for-value aligns financial returns for those who invest in waste elimination. It also requires that clinicians move away from the craft of medicine to the science of medicine, using data and evidence to drive better clinical care.
As the vice president and chief quality officer at Intermountain Healthcare, Dr. James led much of the change that produced Intermountain’s recognized operational and clinical excellence. In this webinar Dr. James educates and inspires all of us to do great work by sharing practical stories of how data has become the critical tool to help healthcare shift from revenue enhancement to clinical quality, which produces the most affordable care.
Learn how to:
- Use data to find variations in both cost and quality of care.
- Standardize care without demotivating underperforming outliers.
- Build a culture of data-driven care providers.
- Develop an improvement strategy that you can start today.
Sought the world over, Dr. James is a recognized expert in this outcomes improvements area. He has championed the standardization of clinical care through data collection and analysis on a wide variety of treatment protocols and complex care processes for more than 20 years.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Healthcare organizations have worked hard to improve patient safety over the past several decades, however harm is still occurring at an unacceptable rate. Though the healthcare industry has made efforts (largely regulatory) to reduce patient harm, these measures are often not integrated with health system quality improvement efforts and may not result in fewer adverse events. This is largely because they fail to integrate regulatory data with improvement initiatives and, thus, to turn patient harm information into actionable insight.
Fully integrated clinical, cost, and operational data coupled with predictive analytics and machine learning are crucial to patient safety improvement. Tools that leverage this methodology will identify risk and suggest interventions across the continuum of care.
Exceptions to Information Blocking Defined in Proposed Rule: Here’s What You ...Health Catalyst
Information blocking practices inhibit care coordination, interoperability, and healthcare’s forward progress. The ONC’s proposed rule ushers in the next phase of the Cures Act by defining information blocking practices and allowed exceptions. To make the final rule as strong as possible, exceptions should be narrowly defined. In proposed form these include the following:
Preventing Harm.
Promoting the Privacy of EHI.
Promoting the Security of EHI.
Recovering Costs Reasonably Incurred.
Responding to Request that are Infeasible.
Licensing of Interoperability Elements on Reasonable and Non-discriminatory Terms.
Maintaining and Improving Health IT Performance.
This article covers each of these exceptions and discusses what to watch for in the final version of the rule.
Reduce Bad Debt: Four Tactics to Limit Exposure During COVID-19Health Catalyst
Health systems have always faced bad debt—from charity care to insurance claim denials—and COVID-19 has exacerbated its impact on revenue. While hospitals and clinics are responsible for providing care to populations, they can still generate revenue from care delivery without compromising care accessibility or quality. An effective bad debt management approach provides the patient with every financial resource possible and allows the health systems to focus less on payment and more on delivering the best care.
With four tactics, health system leadership can identify bad debt and implement effective processes to minimize it without undue burden on patients:
Identify bad debt exposure early.
Educate patients about alternative payment options.
Leverage technology within the workflow.
Understand the true cost of care.
How Healthcare Cost-Per-Case Improvements Deliver Big Bottom-Line SavingsHealth Catalyst
As health systems face more pressure than ever to deliver cost savings, they’re turning their attention to cost-per-case improvement projects. These strategies can produce quick wins for improvement teams looking to gain momentum and buy-in. This article addresses the following topics:
How to identify areas of opportunity.
The importance of costing accuracy.
Four strategies for implementing cost-per-case improvement projects.
Example projects for new teams.
How to sustain results.
Why Data-Driven Healthcare Is the Best Defense Against COVID-19Health Catalyst
COVID-19 has given data-driven healthcare the opportunity to prove its value on the national and global stages. Health systems, researchers, and policymakers have leveraged data to drive critical decisions from short-term emergency response to long-term recovery planning.
Five areas of pandemic response and recovery stand out for their robust use of data and measurable impact on the course of the outbreak and the individuals and frontline providers at its center:
Scaling the hospital command center to pandemic proportions.
Meeting patient surge demands on hospital capacity.
Controlling disease spread.
Fueling global research.
Responding to financial strain.
Good surfers are the consummate analysts. They dynamically process streams of seemingly unrelated information bypassing lesser opportunities, then strategically selecting the perfect wave.
The ability to tease out genuine opportunities amidst a tumult of noise is a hallmark of great analysts. By viewing these slides you will learn:
- The human elements of a great analyst.
- How to re-frame the role of technology in analysis.
- Healthcare knowledge required to maximize the value of a healthcare analyst.
John Wadsworth's (Senior Vice President of Client Engagement, Health Catalyst) engaging presentation style leverages simple and fun analogies to galvanize key concepts for technical, clinical, and executive audiences alike. Join us as he brings principles from the world of surfing and applies them to healthcare analytics.
MYnd Analytics, (NASDAQ: MYND) with its wholly owned subsidiary Arcadian Telepsychiatry Services LLC, is a technology-enabled telepsychiatry and teletherapy company that provides enhanced access to behavioral health services, improves patient outcomes and helps lower the costs associated with behavioral health issues. The MYnd Psychiatric EEG Evaluation Registry (PEER) is a predictive analytics decision support tool that helps physicians reduce trial and error treatment for behavioral health conditions. PEER provides the physician a personalized care plan with recommended treatment options based on a patient’s unique brain markers, reducing treatment time and treatment costs. Arcadian Telepsychiatry Services LLC provides a suite of complementary telemedicine services that can be combined with PEER, including telepsychiatry, teletherapy, digital patient screening, curbside consultation, on-demand services, and scheduled encounters for all age groups. MYnd’s customers include major health plans, health systems, and community-based organizations. To read more about the benefits of this patented technology for patients, physicians and payers, please visit: http://www.myndanalyticsinfo.com
Hospital Capacity Management: How to Prepare for COVID-19 Patient SurgesHealth Catalyst
Health system resource strain became an urgent concern early in the COVID-19 pandemic. Hard-hit areas exhausted their hospital beds, ventilators, personal protective equipment, staffing, and other life-saving essentials, while other regions scrambled to prepare for inevitable surges. These resource concerns heightened the need for accurate, localized hospital capacity planning. With additional waves of infection in the summer months following the initial spring 2020 crisis, health systems must continue to forecast resource demands for the foreseeable future. An accurate capacity planning tool uses population demographics, governmental policies, local culture, and the physical environment to predict healthcare resource needs and help health systems prepare for surges in patient demand.
Precision Medicine: Four Trends Make It PossibleHealth Catalyst
When realized, the promise of precision medicine (to specifically tailor treatment to each individual) stands to transform healthcare for the better by delivering more effective, appropriate care. To date, to achieve precision medicine, health systems have faced financial, data management, and interoperability barriers. Current trends in healthcare, however, will give researchers and clinicians the quality and breadth of health data, biological information, and technical sophistication to overcome the challenges to achieving precision medicine.
Four notable trends in healthcare will bolster to growth of precision medicine in the coming years:
Decision support methods harness the power of the human genome.
Healthcare leverages big data analytics and machine learning.
Reimbursement methods incentivize health systems to keep patients well.
Emerging tools enable more data, more interoperability.
Data-Driven Precision Medicine: A Must-Have for the Next-Generation of Person...Health Catalyst
Under a precision medicine approach, clinicians, academics, and pharma and biotech researchers and regulators aim to deliver the right drug for the right patient at the right time. Data, however, can present a challenge to precision medicine goals due to gaps in clinical care, research, and drug development when organizations don’t have the ability to capture and report on relevant real-world data. With the right systems to collect and share clinical and molecular data, the healthcare industry can realize the full benefits of precision medicine.
Extended Real-World Data: The Life Science Industry’s Number One AssetHealth Catalyst
The life science industry has historically relied on sanitized clinical trials and commoditized data sources (largely claims) to inform its drug development process—an under-substantiated approach that didn’t reflect how a new drug would affect broader patient populations. In an effort to gain more accurate insight into the patient experience and bring drugs to market more efficiently and safely, the industry is now expanding into extended real-world data (RWD).
To access the needed breadth and depth of patient-centric data, life science companies must partner with a healthcare transformation company that has three key qualities:
A broad and deep data asset.
Extensive provider partnerships.
An outcomes-improvement engine to support the next generation of drug development.
Agnostic Analytics Solutions vs. EHRs: Six Reasons EHRs Can’t Deliver True He...Health Catalyst
As enterprisewide analytics demands grow across healthcare, health systems that rely on EHRs from major vendors are hitting limitations in their analytics capabilities. EHR vendors have responded with custom and point-solution tools, but these tend to generate more complications (e.g., multiple data stores and disjointed solutions) than analytics interoperability.
To get value out of existing EHRs while also evolving towards more mature analytics, health systems must partner with an analytics vendor that provides an enterprise data management and analytics platform as well as deep improvement implementation experience. Vendor tools and expertise will help organizations leverage their EHRs to meet population health management and value-based payment goals, as well as pursue some of today’s top healthcare strategic goals:
Growth.
Innovation.
Digitization.
Five Solutions to Controlling Healthcare's Cost ProblemHealth Catalyst
When expenses exceed revenue, business has a financial problem. In healthcare, the focus has been on revenue for so long, we’ve lost sight of runaway costs brought about by high labor and technology expenses, inefficient use of resources, and supply waste. Recognizing the cost problem is a big first step toward solving it.
Five expense-controlling strategies can play a significant role in returning healthcare systems to a stronger financial position:
Refocus on labor management.
Manage employed physicians.
Change the patient encounter environment.
Augment standard approaches with technology.
Manage patient access and flow through the healthcare system.
With new, value-based payment structures, shrinking margins, and decreasing reimbursements, this insight offers some new ways to think about expense inefficiency and how to get costs under control.
Healthcare IT Services Insights - January 2016Duff & Phelps
This issue of Healthcare IT Insights details the increased use of predictive analytics in the healthcare industry to reduce costs and improve outcomes for patients and populations. Predictive analytics can address three categories that unnecessarily cost the healthcare delivery system in the U.S. approximately $350 billion annually: overtreatment, care delivery failure and lack of care coordination.
Three Cost-Saving Strategies to Reduce Healthcare SpendingHealth Catalyst
Health systems continue to face fiscal challenges and burdens due to changing reimbursement rates, COVID-19, and managing the aftermath of care disruptions from the pandemic. Operating on thin margins with limited resources means health systems need to adopt alternative cost-saving measures to maximize limited resources.
Comprehensive, reliable data increases visibility into expenses across the care continuum so that leaders can leverage new methods to save money, generate income, and accelerate cashflow to keep patients healthy and hospital doors open. With access to recent data, health systems can focus on three cost-saving strategies:
Increase physician engagement.
Predict propensity to pay.
Implement evidence-based standards of care.
The Digitization of Healthcare: Why the Right Approach Matters and Five Steps...Health Catalyst
While many industries are leveraging digital transformation to accelerate their productivity and quality, healthcare ranks among the least digitized sectors. Healthcare data is largely incomplete when it comes to fully representing a patient’s health and doesn’t adequately support diagnoses and treatment, risk prediction, and long-term health care plans. But even with the obvious urgency for increased healthcare digitization, the industry must raise this trajectory with sensitivity to the impacts on clinicians and patients. The right digital strategy will not only aim for more comprehensive information on patient health, but also leverage data to empower and engage the people involved.
Health systems can follow five guidelines to digitize in a sustainable, impactful way:
Achieve and maintain clinician and patient engagement.
Adopt a modern commercial digital platform.
Digitize the assets (the patients) and the processes.
Understand the importance of data to drive AI insights.
Prioritize data volume.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Why Clinical Quality Should Be Your Core Business StrategyHealth Catalyst
Over 100 years ago, healing professionals and healthcare itself went through a massive transformation that led us to the models of care delivery that we use today. Dr. Brent James argues that we are now, again, at a once-in-a-century inflection point to change the course of healthcare. Change takes real effort, but provides massive opportunity.
Those changes include a move away from the highly-profitable fee-for-service payment to fee-for-value. An IOM report, published in 2010, substantiated that more than a third of healthcare spending is waste. Pay-for-value aligns financial returns for those who invest in waste elimination. It also requires that clinicians move away from the craft of medicine to the science of medicine, using data and evidence to drive better clinical care.
As the vice president and chief quality officer at Intermountain Healthcare, Dr. James led much of the change that produced Intermountain’s recognized operational and clinical excellence. In this webinar Dr. James educates and inspires all of us to do great work by sharing practical stories of how data has become the critical tool to help healthcare shift from revenue enhancement to clinical quality, which produces the most affordable care.
Learn how to:
- Use data to find variations in both cost and quality of care.
- Standardize care without demotivating underperforming outliers.
- Build a culture of data-driven care providers.
- Develop an improvement strategy that you can start today.
Sought the world over, Dr. James is a recognized expert in this outcomes improvements area. He has championed the standardization of clinical care through data collection and analysis on a wide variety of treatment protocols and complex care processes for more than 20 years.
Analytics-Driven Healthcare: Improving Care, Compliance and CostCognizant
In the face of skyrocketing costs, the healthcare industry is addressing inefficiencies by improving data sharing and collaboration across the industry value chain and applying analytics to improve operations and patient outcomes.
Healthcare organizations have worked hard to improve patient safety over the past several decades, however harm is still occurring at an unacceptable rate. Though the healthcare industry has made efforts (largely regulatory) to reduce patient harm, these measures are often not integrated with health system quality improvement efforts and may not result in fewer adverse events. This is largely because they fail to integrate regulatory data with improvement initiatives and, thus, to turn patient harm information into actionable insight.
Fully integrated clinical, cost, and operational data coupled with predictive analytics and machine learning are crucial to patient safety improvement. Tools that leverage this methodology will identify risk and suggest interventions across the continuum of care.
Exceptions to Information Blocking Defined in Proposed Rule: Here’s What You ...Health Catalyst
Information blocking practices inhibit care coordination, interoperability, and healthcare’s forward progress. The ONC’s proposed rule ushers in the next phase of the Cures Act by defining information blocking practices and allowed exceptions. To make the final rule as strong as possible, exceptions should be narrowly defined. In proposed form these include the following:
Preventing Harm.
Promoting the Privacy of EHI.
Promoting the Security of EHI.
Recovering Costs Reasonably Incurred.
Responding to Request that are Infeasible.
Licensing of Interoperability Elements on Reasonable and Non-discriminatory Terms.
Maintaining and Improving Health IT Performance.
This article covers each of these exceptions and discusses what to watch for in the final version of the rule.
Reduce Bad Debt: Four Tactics to Limit Exposure During COVID-19Health Catalyst
Health systems have always faced bad debt—from charity care to insurance claim denials—and COVID-19 has exacerbated its impact on revenue. While hospitals and clinics are responsible for providing care to populations, they can still generate revenue from care delivery without compromising care accessibility or quality. An effective bad debt management approach provides the patient with every financial resource possible and allows the health systems to focus less on payment and more on delivering the best care.
With four tactics, health system leadership can identify bad debt and implement effective processes to minimize it without undue burden on patients:
Identify bad debt exposure early.
Educate patients about alternative payment options.
Leverage technology within the workflow.
Understand the true cost of care.
How Healthcare Cost-Per-Case Improvements Deliver Big Bottom-Line SavingsHealth Catalyst
As health systems face more pressure than ever to deliver cost savings, they’re turning their attention to cost-per-case improvement projects. These strategies can produce quick wins for improvement teams looking to gain momentum and buy-in. This article addresses the following topics:
How to identify areas of opportunity.
The importance of costing accuracy.
Four strategies for implementing cost-per-case improvement projects.
Example projects for new teams.
How to sustain results.
Why Data-Driven Healthcare Is the Best Defense Against COVID-19Health Catalyst
COVID-19 has given data-driven healthcare the opportunity to prove its value on the national and global stages. Health systems, researchers, and policymakers have leveraged data to drive critical decisions from short-term emergency response to long-term recovery planning.
Five areas of pandemic response and recovery stand out for their robust use of data and measurable impact on the course of the outbreak and the individuals and frontline providers at its center:
Scaling the hospital command center to pandemic proportions.
Meeting patient surge demands on hospital capacity.
Controlling disease spread.
Fueling global research.
Responding to financial strain.
Good surfers are the consummate analysts. They dynamically process streams of seemingly unrelated information bypassing lesser opportunities, then strategically selecting the perfect wave.
The ability to tease out genuine opportunities amidst a tumult of noise is a hallmark of great analysts. By viewing these slides you will learn:
- The human elements of a great analyst.
- How to re-frame the role of technology in analysis.
- Healthcare knowledge required to maximize the value of a healthcare analyst.
John Wadsworth's (Senior Vice President of Client Engagement, Health Catalyst) engaging presentation style leverages simple and fun analogies to galvanize key concepts for technical, clinical, and executive audiences alike. Join us as he brings principles from the world of surfing and applies them to healthcare analytics.
MYnd Analytics, (NASDAQ: MYND) with its wholly owned subsidiary Arcadian Telepsychiatry Services LLC, is a technology-enabled telepsychiatry and teletherapy company that provides enhanced access to behavioral health services, improves patient outcomes and helps lower the costs associated with behavioral health issues. The MYnd Psychiatric EEG Evaluation Registry (PEER) is a predictive analytics decision support tool that helps physicians reduce trial and error treatment for behavioral health conditions. PEER provides the physician a personalized care plan with recommended treatment options based on a patient’s unique brain markers, reducing treatment time and treatment costs. Arcadian Telepsychiatry Services LLC provides a suite of complementary telemedicine services that can be combined with PEER, including telepsychiatry, teletherapy, digital patient screening, curbside consultation, on-demand services, and scheduled encounters for all age groups. MYnd’s customers include major health plans, health systems, and community-based organizations. To read more about the benefits of this patented technology for patients, physicians and payers, please visit: http://www.myndanalyticsinfo.com
Hospital Capacity Management: How to Prepare for COVID-19 Patient SurgesHealth Catalyst
Health system resource strain became an urgent concern early in the COVID-19 pandemic. Hard-hit areas exhausted their hospital beds, ventilators, personal protective equipment, staffing, and other life-saving essentials, while other regions scrambled to prepare for inevitable surges. These resource concerns heightened the need for accurate, localized hospital capacity planning. With additional waves of infection in the summer months following the initial spring 2020 crisis, health systems must continue to forecast resource demands for the foreseeable future. An accurate capacity planning tool uses population demographics, governmental policies, local culture, and the physical environment to predict healthcare resource needs and help health systems prepare for surges in patient demand.
Precision Medicine: Four Trends Make It PossibleHealth Catalyst
When realized, the promise of precision medicine (to specifically tailor treatment to each individual) stands to transform healthcare for the better by delivering more effective, appropriate care. To date, to achieve precision medicine, health systems have faced financial, data management, and interoperability barriers. Current trends in healthcare, however, will give researchers and clinicians the quality and breadth of health data, biological information, and technical sophistication to overcome the challenges to achieving precision medicine.
Four notable trends in healthcare will bolster to growth of precision medicine in the coming years:
Decision support methods harness the power of the human genome.
Healthcare leverages big data analytics and machine learning.
Reimbursement methods incentivize health systems to keep patients well.
Emerging tools enable more data, more interoperability.
Data-Driven Precision Medicine: A Must-Have for the Next-Generation of Person...Health Catalyst
Under a precision medicine approach, clinicians, academics, and pharma and biotech researchers and regulators aim to deliver the right drug for the right patient at the right time. Data, however, can present a challenge to precision medicine goals due to gaps in clinical care, research, and drug development when organizations don’t have the ability to capture and report on relevant real-world data. With the right systems to collect and share clinical and molecular data, the healthcare industry can realize the full benefits of precision medicine.
Extended Real-World Data: The Life Science Industry’s Number One AssetHealth Catalyst
The life science industry has historically relied on sanitized clinical trials and commoditized data sources (largely claims) to inform its drug development process—an under-substantiated approach that didn’t reflect how a new drug would affect broader patient populations. In an effort to gain more accurate insight into the patient experience and bring drugs to market more efficiently and safely, the industry is now expanding into extended real-world data (RWD).
To access the needed breadth and depth of patient-centric data, life science companies must partner with a healthcare transformation company that has three key qualities:
A broad and deep data asset.
Extensive provider partnerships.
An outcomes-improvement engine to support the next generation of drug development.
Agnostic Analytics Solutions vs. EHRs: Six Reasons EHRs Can’t Deliver True He...Health Catalyst
As enterprisewide analytics demands grow across healthcare, health systems that rely on EHRs from major vendors are hitting limitations in their analytics capabilities. EHR vendors have responded with custom and point-solution tools, but these tend to generate more complications (e.g., multiple data stores and disjointed solutions) than analytics interoperability.
To get value out of existing EHRs while also evolving towards more mature analytics, health systems must partner with an analytics vendor that provides an enterprise data management and analytics platform as well as deep improvement implementation experience. Vendor tools and expertise will help organizations leverage their EHRs to meet population health management and value-based payment goals, as well as pursue some of today’s top healthcare strategic goals:
Growth.
Innovation.
Digitization.
Five Solutions to Controlling Healthcare's Cost ProblemHealth Catalyst
When expenses exceed revenue, business has a financial problem. In healthcare, the focus has been on revenue for so long, we’ve lost sight of runaway costs brought about by high labor and technology expenses, inefficient use of resources, and supply waste. Recognizing the cost problem is a big first step toward solving it.
Five expense-controlling strategies can play a significant role in returning healthcare systems to a stronger financial position:
Refocus on labor management.
Manage employed physicians.
Change the patient encounter environment.
Augment standard approaches with technology.
Manage patient access and flow through the healthcare system.
With new, value-based payment structures, shrinking margins, and decreasing reimbursements, this insight offers some new ways to think about expense inefficiency and how to get costs under control.
Healthcare IT Services Insights - January 2016Duff & Phelps
This issue of Healthcare IT Insights details the increased use of predictive analytics in the healthcare industry to reduce costs and improve outcomes for patients and populations. Predictive analytics can address three categories that unnecessarily cost the healthcare delivery system in the U.S. approximately $350 billion annually: overtreatment, care delivery failure and lack of care coordination.
Gain insights from data analytics and take action! Learn why everyone is making a big deal about big data in healthcare and how data analytics creates action.
This white paper offers a detailed perspective on how big data is impacting the healthcare industry and its underlying implication on the industry as a whole. It outlines the role of big data in healthcare, its benefits, core components and challenges faced by the healthcare sector towards full-fledged adoption & implementation.
Using analytics to mine large datasets for insights, commonly known as Big Data, is already transforming industries ranging from consumer goods to transportation. Certainly, the healthcare sector has the raw information to join this group. For example, Kaiser Permanente, a California-based health network, has an estimated 27 to 44 million gigabytes of potentially useful patient information. Expectations are that the U.S. healthcare sector will soon have a zettabyte of these data.
To learn more about the research programme, visit http://hospitalresilience.eiu.com/.
Payers are being challenged as the industry shifts from volume-based care to a value-based reimbursement structure that would benefit the patient, the healthcare provider and the payer. New payment models including fee-for-service only and pay-for performance creates impetus for payers to acquire, aggregate, and analyze data.
Future of patient data global summary - 29 may 2018Future Agenda
We are witnessing a growing revolution around the provision of healthcare. Much is being driven by the proliferation of medical data and the technology that supports this. As the pressures on healthcare providers continue to escalate, the better collection, management and use of more patient-specific information provides a significant opportunity for innovation and change. The Future Agenda team made this, the Future of Patient Data, the focus of our major Open Foresight project for 2017/18 – 12 discussions across 11 countries, gathering views from over 300 experts.
This report shares the findings from the Future of Patient Data research project. It highlights several important emerging issues that are the source of major differences of opinion around the world. These include how to best accommodate rising data sovereignty concerns, the privatisation of health information and the growing value of health data. Some of the challenges and opportunities are technical in nature, but many are concerned with different ethical, philosophical and cultural approaches to health and how we treat the sick in society.
To access the full report please see https://www.futureofpatientdata.org
The convergence of separate health systems has led to
a great increase in data, which some organisations are
struggling to get to grips with. Harnessing analytic tools
and sharing knowledge is the best way forward
Accenture Transformative Power of Healthcare Technology M&A in Life Science 2015
White Paper
1. The Cost Control of
Health Benefits:
A Beginner’s Guide
to Analytics
by Ginger Campbell
This is the era of analytics. Decision-making based on a thorough
analysis of facts and figures is replacing intuitive “by-the-gut” prac-
tices. Healthcare payers, with their abundance of data and urgent
need to control costs, are in a perfect position to embrace analytical
initiatives.
This paper serves as a guide to analytics for third party administrators,
plan sponsors, hospitals, and other organizations seeking to contain
healthcare costs. It explains the rise of analytics and its acceptance
by the healthcare industry. With the rapidly changing healthcare
environment and emerging analytic trends, a plan for launching an
analytical initiative is prescribed.
2. Table of Contents
The Era of Analytics: A Brief History 3
The Natural Expansion of Analytics to Healthcare 3
Controlling Costs for Healthcare Payers 4
A Full-Support Solution: nFORM Health Benefits Analytics 5
Conclusion 6
Works Cited 7
The Cost Control of Health Benefits • Page 2 May 2012 BancorpSouth Insurance Services, Inc.
3. The Era of Analytics: A Brief History COMPARISON OF
REPORTING AND ANALYTICS
Analytics refers to the practice of creating action-
Reporting Analytics
able information through the sophisticated analysis
of data. Analytics and reporting are different but Primary use To provide data To provide insight
analytics do involve an element of reporting. The
difference is that reporting provides retrospective, To convert To convert data
flat statistics while analytics are forward-looking and information into into knowledge
multi-dimensional. The extra dimensions provide
data [6] [6]
advantages such as drill-down capabilities, trend
tracking, enhanced data correlation, and budget
forecasting. Examples Standard Statistical
reports, graphs, analysis,
The rise in analytics began around 2003. During alerts extrapolation,
this time, technology-based organizations such predictive
as Google, Amazon, and Netflix were dominating
modeling
markets by using complex analytical systems. How-
ever, it soon became apparent that analytics had
applications in other industries. Sports teams such as Provides Past Future
the Boston Red Sox began recruiting top-line statis- quantifiable performance probabilities
ticians to develop a myriad of ways to judge player description of
performance. A prominent casino reaped millions
of dollars’ worth of customer retention by analyzing
Answers What happened Why is this
minute data points, such as the number of smiles its
employees gave in certain intervals of time [5]. The questions: on what date? happening?
list of creative uses for analytics is virtually limitless
and the outcomes are rather impressive. How many What if this
times did it keeps
In markets where new competitive ground is scarce, happen? happening?
analytic breakthroughs are acting as springboards
for forward-thinking organizations. Now, analytical
Where did it What will
practices are expanding to the healthcare industry.
Experts predicted that healthcare analytics would happen? happen next?
see a large increase in 2011 and 2012, and so far the Are any
prediction has proved to be true [3]. opportunities
present?
The Natural Expansion of Analytics to
Healthcare
prominent nonprofit research group, indicates that
The rise of analytics comes at a fortunate time for the the average annual premium for family coverage in-
health benefits industry. Healthcare costs are ex- creased 9 percent in 2011, to an average of $15,073.
ploding out of control and cost containment is criti- This is almost double the cost of family coverage in
cal. A recent study by the Kaiser Family Foundation, a 2001, when premiums averaged $7,061 [11].
The Cost Control of Health Benefits • Page 3 May 2012 BancorpSouth Insurance Services, Inc.
4. The complications causing this instability will likely improvements over existing medications. Pharma-
affect the market for some time. One sustaining ceuticals like Nexium and Clarinex are products of
cause of the rise in healthcare costs is the aging this kind[9]. Expensive “specialty drugs” make up
population. The “baby boom” generation (those born most of the new drugs on the market, and will likely
between 1946 and 1964) is arriving at old age. By account for roughly two-thirds of the projected in-
2020, the number of Americans older than 65 will crease in drug spending between 2010 and 2013[7].
rise by more than 19 million to a total of 54 million
[8]. Because older adults consume a disproportion- Many factors are affecting the market, but these are
ately high amount of medical services, the demand the most significant and prolonged among them.
for medical treatment is expected to increase over Unfortunately, experts are not forecasting the stabili-
subsequent years. zation of healthcare costs in the near future.
Another reason for the ongoing increase in health-
care costs is changing legislation. The Patient Protec- Controlling Costs for Healthcare Payers
tion and Affordable Care Act (PPACA) signed into law
by President Obama in 2010 will take full effect in In unfavorable market conditions, analytical report-
2014. However, important provisions became effec- ing tools open new doors for healthcare payers.
Traditional uses for analytics include budget fore-
tive in 2010 and others continue to roll out. The leg-
casting, rate setting, and identifying individuals for
islation affects large and small companies differently,
chronic-care management. However, because of the
but in general it places higher demands on employ-
capability and the opportunity analytic reporting
ers that provide health benefits to their employees.
provides, the number of applications continues to
grow.
Lastly, advances in medical technology are increas-
ing healthcare expenditures. Typically, technological New approaches to using analytics include financial
developments lead to lower prices, but for medical and clinical algorithms, which allow healthcare orga-
advances this is not always the case. For example, nizations to implement advanced methods to iden-
some new procedures allow for treatment of pre- tify, manage, and measure risk within a population.
viously untreatable conditions. Other scientific The analyses detect correlations between multiple
breakthroughs have created expensive but effec- related data sets. Once an outlier is located, it can
tive treatments for terminal diseases such as heart be drilled down upon and fully investigated. Con-
disease and HIV. Demand is extremely high for new trast this streamlined process with how employers
treatments, which inflates healthcare prices [10]. struggle to receive claims data from plan administra-
tors. Without access to this information, employers
The rapid development of new pharmaceuticals have little choice but to base decisions on what has
contributes to the rise in healthcare costs as well. happened as opposed to what is likely to happen as
The government awards pharmaceutical companies predicted by forward-looking analytics.
with patents that create monopolies on new drugs.
This helps the businesses offset the immense cost of With full exposure to claims data, many organiza-
drug development and generate profits[10]. How- tions use analytical auditing tools to shrink health-
ever, it also leads to consumers paying much more care and pharmacy costs. With auditing capabilities,
for a drug than what it costs to manufacture. On a companies get a better picture of their plan and can
macroeconomic scale, this is not cost-efficient past renegotiate with their carriers for better pricing. Also,
a certain point. Current regulation also incentivizes employers that internally monitor carriers can verify
companies to develop drugs that make only small that pharmacy discounts are truly being applied.
The Cost Control of Health Benefits • Page 4 May 2012 BancorpSouth Insurance Services, Inc.
5. Analytics play a large role in making plan partici- case, it is beneficial to ask a series of questions
pants accountable for their own health. Employers before committing to an analytics solution:
can hone in on which intervention programs are
needed and which members have care gaps, then Ten Questions to Consider When
?
adjust health coverage accordingly. Plan participants
who choose not to participate in these programs or Shopping for an Analytics Platform
refuse to comply with recommended treatment may 1. Is the platform suitable for someone with limited time?
find themselves paying more for their employer-
sponsored plan. 2. How will my organization learn to use this?
3. Is this something that needs to be constantly monitored or does
Chief financial officers and other executives use it feature automated processes?
analytics to empower cost centers, especially human
resource departments, so that they affect revenues. 4. How committed is the platform’s provider in helping my
Where health plans are concerned, HR normally organization learn their product?
works between the company and the employee. For
5. Is it simple enough to be used by the less technically-minded
this reason, HR specialists tend to manage plans in a
way that is not equally beneficial to both the em- people, yet sophisticated enough to produce valuable information?
ployees and the company, making plans more costly 6. How long will it take my organization to learn to use this?
than they need to be. With analytical applications,
HR departments operate with bottom-line costs in 7. Will a basic understanding of office software help in learning this
mind and manage plans more equitably. platform?
8. What in-depth features are included?
Occasionally, an analytical initiative will innovate
and affect processes in such a way that it creates 9. Is the data easy to export out of the system?
great change within an organization. “Breakthrough 10. What upfront technology investment will be needed to use this
applications” are those analytic platforms that are
platform?
engineered to accomplish positive transformations.
This terminology originated in a 2011 white paper
by Bloor Research, a European healthcare IT and A Full-Support Solution: nFORM Health
consulting firm. The most effective breakthrough Benefits Analytics
applications 1) deliver personalized, accessible infor-
mation 2) have comprehensive access to data and Clearly, the application of analytics to health-bene-
3) and drive informed action [2]. Many new analytic fits management is a rapidly growing practice. How-
platforms provide these results.
ever, steep learning curves can be detrimental to
Analytics have created a new frontier of cost contain- the success of analytical initiatives. An ideal analytics
ment for healthcare payers. However, there are some solution will have a strong answer for this problem.
barriers to success in this process. Because analytic
platforms are powerful tools with breakthrough nFORM Health Benefits Analytics addresses the
capabilities, they take time to master. Unfortunately, learning curve by providing clients with training and
excessively high learning curves can cause organi-
ongoing consultation. nFORM personnel help clients
zations to let their investment fall by the wayside.
Analytics providers will address this issue if they are gather reporting information and install automated
dedicated to client success. To verify that this is the features, such as report generation and alert setting.
The Cost Control of Health Benefits • Page 5 May 2012 BancorpSouth Insurance Services, Inc.
6. After the platform is implemented, consultants work recognize the existence of a learning curve. Expert
with users to uncover the “gems” in the data that are consultation and ongoing guidance are effective at
instrumental in controlling costs. These consultants overcoming this obstacle. Platforms that offer abun-
remain committed to helping clients overcome dant personnel support should be strongly consid-
stumbling blocks and progress in their mission. ered when choosing an analytics solution.
For many analytic platforms, it is necessary that users
learn a whole new computer skillset. The difficulty is
comparable to using a program like Excel for the first
time. To avoid putting users through this, nFORM
functions similarly to common office software. Data
is arranged in cells and rows that can be easily ma-
nipulated and exported to spreadsheets or PDF. This
layout is familiar to most people and allows them to
transfer existing skills to new applications.
nFORM is a cloud-based solution that
Overall, a good goal to have when shopping for an includes ongoing consultation.
analytical solution is a manageable, capable platform
that provides lots of support. nFORM Health Benefits
Analytics is based on this idea and represents market
leadership in usability.
For a full list of nFORM features or to learn more
about the platform, visit www.nformanalytics.
com on the Web, or call (800) 486-8283 ext. 5304.
Live demos are available.
Conclusion
The inspiring companies and individuals responsible
for the rise of analytics have changed the business
landscape. Existing data records can now breathe
new life into business practices with transformative
results.
The advent of analytics could not come at a better
time for the data-rich health benefits industry. Likely,
healthcare costs will continue to rise due to persis-
tent, large-scale trends affecting the market. With
analytical tools, healthcare payers have the means
available to bring costs back down.
Organizations seeking an analytical solution should
The Cost Control of Health Benefits • Page 6 May 2012 BancorpSouth Insurance Services, Inc.
7. Works Cited
1. Abelson, Reed. “Health Insurance Costs Rising Sharply This Year, Study Shows.” The New York Times.
Sept 28, 2011. Page A1.
2. Bloor Research. “Building Breakthrough Applications.” Prepared by Philip Howard. London, Oct 2011.
White paper. Page 1.
3. Davenport, Thomas. “Analytical Integration in Healthcare.” Analytics-magazine.org. Web. Jan 2012.
4. Davenport, Thomas. “Are You Ready to Re-engineer Your Decision Making?” MIT Sloan Management
Review. Oct 1, 2010. Volume 52, Number 1, pages 1-6.
5. Davenport, Thomas H., and Jeanne G. Harris. 2007. “Competing on Analytics: The
New Science of Winning.” Boston: Harvard Business School Press.
6. Desa, Manish. “Reporting Vs Analytics”. My Business Analytics. Mar 29, 2011. Web. Accessed Feb 20, 2012.
7. Medco. “2011 Drug Trend Report.” Web. 2011. Volume 13.
8. National Center for Health Workforce Analysis, Bureau of Health Professions, Health Resources and
Services Administration. “The Impact of the Aging Population on the Health Workforce in the United
States: Summary of Key Findings.” Center for Health Workforce Studies, School of Public Health,
University at Albany. Web. Mar 2006.
9. Porter, Eduardo. “Do New Drugs Always Have to Cost So Much?” The New York Times. Web. Nov 2004.
10. The Henry J. Kaiser Family Foundation. “How Changes in Medical Technology Affect Health Care Costs.”
Snapshots: Healthcare Costs. Web. Mar 2007.
11. The Henry J. Kaiser Family Foundation. “U.S. Healthcare Costs.” Prepared by Adara Beamesderfer and
Usha Ranji. Web. Feb 2012.
For a full list of nFORM features or to learn more
about the platform, visit www.nformanalytics.com
or call (800) 486-8283 ext. 5304.
BancorpSouth Bank is a wholly owned subsidiary of BancorpSouth, Inc., a financial holding company headquartered in Tupelo, Mis-
sissippi, with $13 billion in assets. BancorpSouth Insurance Services, Inc., a division of BancorpSouth Bank, employs more than 500
insurance and risk management agents. The organization is annually ranked as one of the nation’s largest brokers by Business Insurance
magazine and serves clients across the globe through its Worldwide Broker Network.
The Cost Control of Health Benefits • Page 7 May 2012 BancorpSouth Insurance Services, Inc.