Archive for the ‘Data Analytics’ Category

Guest Post: Lab Data is the Missing Link in Healthcare Risk Adjustment

June 19th, 2018 by Jason Bhan, MD

Data informing risk adjustment programs is critical under value-based healthcare reimbursement models.

For health plans, value-based care means a continuous need to innovate and improve their risk adjustment, clinical quality, and care management programs. Unless payers identify and receive the correct amount of reimbursement, it is difficult for them to invest appropriately into member care programs for better outcomes while remaining financially successful.

The data informing risk adjustment programs are critical, as they build the foundation for accurate member risk stratification. In that respect, those data sources are directly related to the correct amount of reimbursement payers receive and can invest in proactive care management. In other words, high-quality clinical data delivered quickly enough for a plan to get a member into a care management program early enough is important to the health of the member and the business. The approach leads to improved clinical outcomes and reduced costs in emergency room visits, hospitalizations and chronic condition management.

Lab Data: An Untapped Resource

To achieve such clinical granularity, at scale, plans can turn to diagnostics—or lab—data. Lab data drives approximately 70 percent of medical decisions and, unlike claims data, is available in near real-time. It also provides an unrivaled level of specificity for clinical conditions. When lab data is integrated into plans’ claims- and chart-based programs, it enables earlier, more comprehensive and accurate clinical insights to benefit care management of both existing and new members. Utilizing the same information that clinicians use to make decisions, within the same timeframe, provides a powerful and unique opportunity to intervene and impact a patient’s health.

What Can Lab Data Do for You?

Expanding and improving their clinical data supply with diagnostics data can help health plans to:

  • Provide historical insights on members where claims are unavailable to improve risk adjustment. For new enrollees, this enables the health plan to get new members into the appropriate care/disease management programs from day one.
  • Serve as an early detection system for care management of all enrollees. Plans can identify patients in need of additional or alternative therapy from lab data earlier than from any other data source. For existing members, the detailed results uncover needs that may have been overlooked based on a claims analysis alone.
  • Identify high-risk members for case management and provider interventions from lab data. Optimized risk adjustment aligns reimbursements to health status, enabling the plan to more heavily invest in member care programs.

Applying AI Solutions

When it comes to gaining actionable insights from diagnostics data, plans can benefit from partnering with healthcare artificial intelligence (AI) specialists in the field. Healthcare AI organizations use techniques such as machine learning and natural language processing—coupled with massive computational power—on big data sets, to make sense out of non-standard, complex, and heterogeneous data.

Healthcare AI, when applied to diagnostics clinical lab data, improves risk stratification by identifying diagnoses earlier in the year versus waiting for the claim or searching charts. Rich in clinical details, it presents a more complete picture of the member’s health. Better risk stratification leads to better care management programs; and successful programs have been shown to reduce costs by targeting those most likely to benefit and keeping intervention costs low.

Dr. Jason Bhan

About the Author: Jason Bhan, MD, is co-founder and Chief Medical Officer at Prognos, an innovator in applying AI to clinical lab diagnostics. More than half of the Prognos team is made of engineers, data scientists, and clinicians. Prognos aims to increase the usefulness of disparate healthcare data to better inform clinical decisions and ultimately improve patient outcomes.

Guest Post: As Mergers Continue, Healthcare Industry Faces New Data Consolidation Realities

June 12th, 2018 by Christian Puff

As if the healthcare system wasn’t confusing enough, construction signs are now popping for consolidations.

As if navigating the twists and turns of the U.S. healthcare system highway wasn’t confusing enough, construction signs are now popping up all over the place in the form of consolidations. Why is this happening? What does this mean for consumers? And, how will this change the way consumers receive care?

The United State’s annual medical spend has risen to over $3.4 trillion and is only projected to grow. This spend accounts for roughly 18 percent of the U.S. GDP. Some want a piece of the incredibly large pie, while others are focused on reducing its size. Then, there are those who have accepted the need for a smaller pie but want the biggest piece possible. It’s in this third group where we’re seeing many of the industry consolidations. From Aetna and CVS to Cigna and Express Scripts and, most recently, Walmart and Humana, these big-name players are intent on controlling the largest portion of the multi-trillion dollar industry they can.

If these consolidations are successful, the way insurers and healthcare providers interact will change because of one word: data. Data is king, and many believe it is the key to reducing healthcare costs in this country.

Aetna is one of the largest health insurers. Its plan to merge with CVS, the largest national retail pharmacy chain that also happens to own the largest pharmacy benefit manager, Caremark, will give the consolidated healthcare giant access to an incredible amount of member, patient and provider data. The same is true for Cigna and Express Scripts, although to a slightly lesser extent. While this consolidated entity would not, at this time, have brick-and-mortar pharmacies, together, they will reap the benefits of combining member, patient and provider data. However, the proposed Walmart and Humana merger could prove the most impressive in terms of data consolidation, followed by Aetna and CVS. Not only will the newly combined company know whether their members and patients fill their prescriptions, they’ll know what those same members and patients purchased while waiting for their prescriptions. Did the depressed, hypertensive diabetic buy ice cream, red meat and cigarettes? They will now have those answers.

So why is this important? According to the Centers for Disease Control and Prevention (CDC), over 86 percent of the healthcare spend is due to those suffering from chronic disease. More importantly, however, is over 50 percent of these costs are attributable to patient behavior. As a result, having access to both medical and behavioral data allows the depressed, hypertensive diabetic purchasing ice cream, red meat and cigarettes to become an opportunity for outreach and case management.

These companies will attempt to capitalize on the data available to them to help manage the cost of care. Perhaps it will be in the form of a letter or phone call to the member. Perhaps it will come in the form of a highly personalized clinical program where the member receives access to nicotine replacement therapy, a gym membership and nutritionist services.

These organizations alone cannot and will not be able to force patients and members into participating in programs designed to improve health and reduce the cost of care.

Okay, so now what? Let’s assume for an instant all of this data conglomeration works to drive down the cost of care to a more reasonable $2.5 trillion. Will consumers benefit from the savings? This is yet to be determined. In reviewing the proposed consolidations, the federal antitrust enforcers will attempt to discern the impact on the consumers. Undoubtedly, these entities will argue the proposed mergers will reduce costs by increasing efficiencies and allowing them to positively affect the medical spend trend. Critics, however, predict individual consumers will never see the savings projected by these organizations. Who’s right? That’s a question that can only be answered with time.

This article is educational in nature and is not intended as legal advice. Always consult your legal counsel with specific legal matters.

Christian Puff

Christian Puff

About the Author:

Christian Puff is an attorney with Hall, Render, Killian, Heath & Lyman, P.C., the largest healthcare-focused law firm in the country. Please visit the Hall Render Blog at http://blogs.hallrender.com/ for more information on topics related to healthcare law.

HIN Disclaimer: The opinions, representations and statements made within this guest article are those of the author and not of the Healthcare Intelligence Network as a whole. Any copyright remains with the author and any liability with regard to infringement of intellectual property rights remains with them. The company accepts no liability for any errors, omissions or representations.

Infographic: Unlock Your Data To Optimize Your EMR

June 6th, 2018 by Melanie Matthews

As healthcare shifts from volume to value, imaging clinicians need intelligent solutions that help them leverage the data available in the EMR at the point of care for faster, more accurate diagnoses, according to a new infographic by Change Healthcare.

The infographic examines how to mine clinical information and leverage it in a way that provides more efficient care.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Infographic: Big Data Healthcare Trends Will Improve Outcomes

May 14th, 2018 by Melanie Matthews

Improved technology will play a pivotal role in the collection and analysis of big data for healthcare facilities. Healthcare providers will have access to large data sets to help improve their patients’ overall well-being, according to a new infographic by Compliant Healthcare Technologies.

The infographic examines how big data analytics will drive healthcare forward.

Predictive Healthcare Analytics: Four Pillars for SuccessWith an increasing percentage of at-risk healthcare payments, the Allina Health System’s Minneapolis Heart Institute began to drill down on the reasons for clinical variations among its cardiovascular patients. The Heart Institute’s Center for Healthcare Delivery Innovation, charged with analyzing and reducing unnecessary clinical variation, has saved over $155 million by reducing this unnecessary clinical variation through its predictive analytics programs.

During Predictive Healthcare Analytics: Four Pillars for Success, a 45-minute webinar on March 29th now available for replay, Pam Rush, cardiovascular clinical service line program director at Allina Health, and Dr. Steven Bradley, cardiologist, Minneapolis Heart Institute (MHI) and associate director, MHI Healthcare Delivery Innovation Center, shared their organization’s four pillars of predictive analytics success…addressing population health issues, reducing clinical variation, testing new processes and leveraging an enterprise data warehouse. Click here for more information.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Infographic: Enabling a 360-degree View of Patient Data

May 2nd, 2018 by Melanie Matthews

As healthcare organizations move toward more integrated and personalized service delivery, they need the ability to securely access and analyze all data along the patient journey, according to a new infographic by BridgeHead.

The infographic examines how an Application Independent Clinical Archive (AICA) provides this type of patient-data view.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Infographic: Healthcare Colocation Myths

April 27th, 2018 by Melanie Matthews


The average healthcare organization stores well over one petabyte of data (1,000,000 gigabytes) leading many organizations to store data off premise, according to a new infographic by CoreSite.

The infographic explores some of the myths surrounding off premise data hosting.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Mounting Pressure from Value-Based Reimbursement Models Drives Clinical Improvement Strategy at Allina Health System

April 17th, 2018 by Melanie Matthews

Value-Based Reimbursement Models Drive Clinical Improvement Strategy

As a greater percentage of hospital payments are through value-based contracts, hospitals that reduce costs while maintaining quality will survive, predicts Pam Rush, cardiovascular clinical service line program director at Allina Health.

“How do we improve outcomes and decrease costs?” Rush asked participants in the March 2018 webinar, Predictive Healthcare Analytics: Four Pillars for Success. “We need to start to look at the world differently.”

How can we be more creative and do things differently? How can we use different members of the healthcare teams in new ways, such as nurse practitioners or advanced practice providers, she added. In addition, “we need to invest in data analytics and data resources and have data analysts who can pull the information for us so we can find the variation. We need to invest in physician and caregiver time to look at the data, to make changes in how they improve care, to monitor and see what is working and what doesn’t work.”

These four pillars…population health management, reducing clinical variation, testing new care processes and new models of payment, and leveraging cutting edge technologies…have been critical to the work at Allina Health System’s Minneapolis Heart Institute Center for Healthcare Delivery Innovation, said Rush.

In population health management, we’re looking at how can we focus on adherence to guidelines, identify where there are gaps in care and partner with people across the system, primary care and specialists, to improve consistency and adherence to guidelines, she explained.

Allina is reducing clinical variation by looking at unnecessary variations in care where there is inconsistent care without an influence on outcomes.

“We’re also looking at new ways of doing things. How can we use our nurse practitioners, how do we care for patients once they’re discharged from the hospital and bring them back in for clinic visits? It’s really looking at the care model and how we can do things differently to reduce total cost of care,” she said.

In cardiology, there are so many new devices, procedures and techniques to monitor, said Rush, but we need to figure out who are the right providers to do that monitoring, who are the right patients to do these expensive procedures on and who achieves the best outcomes, because we can’t afford to do all of this new technology to every single person.

Allina looks at these four pillars across the continuum. Starting in primary care to partner on prevention strategies, moving to who gets referred to cardiology, and when they’re referred to cardiology, what are the set of tests or treatments and guidelines to adhere to along the continuum to subspecialties, emergency services and all the way up through advanced therapies, such as transplant.

During the webinar, Rush along with Dr. Steven Bradley, cardiologist, MHI and associate director, MHI Healthcare Delivery Innovation Center, shared these four pillars of predictive analytics success along with details on creating a culture of quality and innovation, building performance improvement dashboards, as well as several case examples of quality improvement initiatives contributing to these savings and much more.

Listen to Ms. Rush describe how MHI leveraged an enterprise data warehouse to identify care gaps and clinical quality improvement opportunities.

Guest Post: Outcomes Drive the Evidence-Based Practice Journey

March 29th, 2018 by Michele Farrington and Cindy Dawson

The Institute of Medicine set a goal that 90 percent of all healthcare decisions will be evidence-based by 2020. Executives and nursing leaders, at all levels within organizations, have clear responsibility for making this goal a reality and ensuring consistent, standardized use of evidence-based practice (EBP) in care delivery that will meet patient, family, clinician, and organizational outcomes.

Promoting use of evidence, valuing questioning of clinical and administrative practice, and building organizational capacity, culture, and commitment are pivotal to building a supportive organizational culture related to EBP.

Organizations must meet regulatory requirements, from the Centers for Medicare and Medicaid Services and The Joint Commission, that incorporate EBPs and the need for increasing public accountability and transparency (e.g., use of national benchmarks) for quality and safety. Financial incentives associated with pay-for-performance are also directly linked to EBP. Despite these outside forces in today’s healthcare environment, clinicians and executives cannot forget about the need to provide individualized patient care, which includes patient engagement strategies aimed at improving the overall patient experience.

EBP is a continuous journey for individual clinicians and organizations alike and starts with building organizational capacity.

Organizational Capacity

EBP capacity is built using a strategic, systematic approach to create a solid foundation and infrastructure to support the work. Before EBP work can be successful at the unit or clinic level, EBP must be integrated at the organizational level and a culture for change must exist.

The organization’s mission, vision, and strategic plan must include EBP language to ensure evidence-based healthcare is clearly portrayed as the organizational norm. Creating a culture valuing inquiry and innovation must start during orientation for new hires and continue during competency review for current employees and through ongoing training and professional development opportunities for both clinicians and executive leaders.

An infrastructure that directly integrates EBP work into the organizational governance structure is needed to support the mission, vision, and strategic plan. A crucial organizational decision is determining what group will hold primary accountability or functional responsibility for EBP to ensure it is integrated into practice processes, policies, and documentation.

Recruiting and hiring clinicians and executives with experience and/or interest in EBP will help build the desired culture and capacity. EBP mentors are developed from successful projects and are used to nurture the next generation.

A well-defined path for EBP includes adoption of an EBP-process model to guide implementation and sustained organizational change across disciplines. There are a number of EBP process models: The Iowa Model Revised: Evidence-Based Practice to Promote Excellence in Health Care; Johns Hopkins Nursing Evidence-Based Practice Model; Stetler Model of Evidence-Based Practice; and Advancing Research and Clinical Practice Through Close Collaboration (ARCC) Model. Each model follows a step-by-step problem-solving process suitable for concurrent use with the organization’s quality improvement processes.

Culture

The governance structure must clearly outline the process and channels for communicating EBP work and obtaining necessary approvals from applicable committees. EBP discussions should be a regular agenda item for all shared governance committees.

Project results should be reported internally through the organization’s shared governance and quality improvement structures to promote practice change adoption, share learning, garner continued support (e.g., time, resources), and as a platform to recognize success for the institution’s EBP program.

Successful EBP work takes time and effort, so successes should be celebrated and rewarded throughout the process. Celebrations are an opportunity to spotlight clinicians for doing this work and helps build a pervasive culture that supports and expects use of evidence in practice. These strategies promote organizational buy-in and commitment for the EBP process and set higher standards as a foundation for future efforts.

Expected behaviors from clinicians across all job classifications at every level must clearly demonstrate the value of EBP. Behavioral expectations regarding EBP are easily set if they are built into every job description and can be quickly reviewed annually during the performance appraisal process. Utilizing documents and mechanisms that already occur is an easy and efficient way to promote positive reinforcement and priority setting in busy work environments with many ongoing and competing demands for clinicians’ and leaders’ time and attention.

Benefits

EBP is value-added with a strong return on investment and responds to current priorities. A single project may improve patient and clinician safety, improve clinical outcomes, improve patient/family satisfaction, promote innovate care, and/or reduce costs.

Clinicians, nurses, and leaders all influence an organization’s capacity for EBP. Leaders who demonstrate and expect EBP will promote its use in clinical and operational decision-making at the unit or clinic and organizational levels. Building on the organization’s mission, vision, capacity, and value for delivery of reliable, safe, high quality care provides a foundation for success.

About the Authors:

Michele Farrington, BSN, RN, CPHON, is a clinical healthcare research associate at the University of Iowa Hospitals and Clinics. She is certified in pediatric hematology/oncology nursing and received her BSN from the University of Iowa. She has been leading, co-leading, or mentoring EBP initiatives since 2003, and her work has been awarded extramural funding, validating the strength of the projects and impact on nursing care. She is widely published and has given multiple local, regional, national, and international presentations.

Cindy Dawson, MSN, RN, CORLN, is the chief nurse executive and associate director of the University of Iowa Hospitals and Clinics. She received her BSN from the University of Iowa, MSN from the University of Phoenix, and is a Certified Otorhinolaryngology Nurse. Over the course of her career, she has published extensively on EBP, nurse triage, nursing management/leadership, and clinical practice guidelines and has given numerous local, regional, national, and international presentations on these topics.

HIN Disclaimer: The opinions, representations and statements made within this guest article are those of the author and not of the Healthcare Intelligence Network as a whole. Any copyright remains with the author and any liability with regard to infringement of intellectual property rights remains with them. The company accepts no liability for any errors, omissions or representations.

Infographic: Statewide Health Information Network for New York

March 23rd, 2018 by Melanie Matthews

The Statewide Health Information Network for New York (SHIN-NY) is a statewide network that facilitates secure and confidential sharing of patient data across the healthcare system to improve outcomes. The SHIN-NY is comprised of eight Qualified Entities (QEs) that are regional health information exchanges, according to a new infographic by the New York eHealth Collaborative, which leads the advancement of SHIN-NY.

The infographic examines how SHIN-NY works, the information that can be shared and the benefits to patients and providers.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results Between Medicare’s aggressive migration to value-based payment models and MACRA’s 2017 Quality Payment Program rollout, healthcare providers must accept the inevitability of participation in fee-for-quality reimbursement design—as well as cultivating a grounding in health data analytics to enhance success.

As an early adopter of the Medicare Shared Savings Program (MSSP) and the largest sponsor of MSSP accountable care organizations (ACOs), Collaborative Health Systems (CHS) is uniquely positioned to advise providers on the benefits of data analytics and technology, which CHS views as a major driver in its achievements in the MSSP arena. In performance year 2014, nine of CHS’s 24 MSSP ACOs generated savings and received payments of almost $27 million.

Health Analytics in Accountable Care: Leveraging Data to Transform ACO Performance and Results examines program goals, platforms, components, development strategies, target populations and health conditions, patient engagement metrics, results and challenges reported by more than 100 healthcare organizations responding to the February 2016 Digital Health survey by the Healthcare Intelligence Network.

Get the latest healthcare infographics delivered to your e-inbox with Eye on Infographics, a bi-weekly, e-newsletter digest of visual healthcare data. Click here to sign up today.

Have an infographic you’d like featured on our site? Click here for submission guidelines.

Essentia Health Virtual Telemedicine Services Support Rural Hospitals and Clinics

March 13th, 2018 by Patricia Donovan

Essentia Health conducts 5,000 virtual visits annually.

There may be some challenges associated with Essentia Health’s comprehensive telemedicine program, but provider engagement isn’t one of them.

“In the seven years I have been with Essentia Health, I have not gone to any provider to ask them to do telehealth,” notes Maureen Ideker, RN, BSN, MBA, the organization’s senior advisor for telehealth. Instead, physicians seek out Ms. Ideker, asking to be connected to any of Essentia Health’s six hospital-based and more than 20 clinic-based telehealth services.

Such robust telemedicine adoption among Essentia Health’s more than 800 physicians may be one reason why the organization averages 5,000 virtual visits annually, and why it has another 10 to 20 new telehealth offerings in development, according to Ms. Ideker’s presentation during Telemedicine Across the Care Continuum: Boosting Health Clinic Revenue and Closing Care Gaps.

The largely rural footprint of Essentia Health, which touches the three states of Minnesota, Wisconsin and North Dakota, is ideally suited to telehealth implementation. During this March 2018 webinar, which is now available for rebroadcast, Ms. Ideker outlined her organization’s telehealth program models, history of program development, and equipment and staffing requirements. She also shared key program outcomes, such as the impact of remote patient monitoring on hospital readmissions and clinic ROI from telehealth.

For example, the 30-day readmission rate for Essentia Health patients with heart failure remotely monitored at home is 2 percent, versus its non-monitored heart failure patients (9 percent) and the national 30-day readmissions average of 24 percent.

Essentia Health’s hospital-based telemedicine began with an emergency room platform, which includes pediatric ER and pharmacy and toxicology and a soon-to-be-added behavioral health component. Today, hospitalist and stroke care are the largest of Essentia Health’s hospital-based telemedicine programs, explained Ms. Ideker. These virtual services support Essentia Health’s rural hospitals in five key ways, including the avoidance of unnecessary patient transfers.

On the outpatient side, the 20-something tele-clinic based services developed by Essentia Health over the last seven years run the gamut from allergy and infant audiology to urology and vascular conditions, she explained. Her organization’s telemedicine approach to opioid tapering is catching on across Minnesota, she added.

And while it is appreciative of its providers’ enthusiasm, Essentia Health approaches telehealth development with precision, consulting data analytics such as metrics on annual health screenings to create target groups for new services. The launching of a new telemedicine service can take up to twelve weeks, using a 75-item checklist and an implementation retreat and walk-through, Ms. Ideker explained.

In closing, Ms. Ideker shared several innovation stories from its portfolio of telehealth offerings, including Code Weather, employed during hazardous weather for patient safety reasons and to reduce cancellations of appointments, and a gastroenterology initiative designed to reduce no-show rates.

Listen to Maureen Ideker explain how Essentia Health pairs remote patients with hospital- and clinic-based telehealth services.