Skip to main content
Mobile
  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations
HS Talks HS Talks
Subjects  
Search
  • Notifications
    Notifications

    No current notifications.

  • User
    Welcome Guest
    You have Limited Access The Business & Management Collection
    Login
    Get Assistance
    Login
    Forgot your password?
    Login via your organisation
    Login via Organisation
    Get Assistance
Finance, Accounting & Economics
Global Business Management
Management, Leadership & Organisation
Marketing & Sales
Strategy
Technology & Operations
Case study

Staffing models for integration of virtual visits into clinical operations

Amrika Ramjewan, Aaron Stelpflug, Michelle Leung, Sandra Elsen, Pawan Bhandari and Jordan Coffey
Management in Healthcare: A Peer-Reviewed Journal, 6 (2), 121-133 (2021)
https://doi.org/10.69554/ACEW5933

Abstract

The demand for telehealth services in the United States saw an unprecedented increase following the 2020 COVID-19 pandemic. Prior to the pandemic, intake and virtual rooming functions for scheduled, synchronous video appointments at Mayo Clinic were supported by a small centralised team of virtual agents within its Center for Connected Care (Connected Care). In response to the pandemic-generated demand, Connected Care leveraged its existing model and the support of temporary staff to rapidly scale support for the increased video visit demand across the enterprise. Once demand stabilised in the summer of 2020, Mayo Clinic’s destination medical centres in Minnesota, Florida and Arizona, and Mayo Clinic Health System’s sites in the Midwest, launched pilots to evaluate alternative telehealth delivery models. The goal of these pilots was to test the flexibility of alternative intake models for supporting long-term scalability and growth. Through these pilots, each site developed unique workflows and staffing plans with the overall intake function remaining standardised across all locations. The workflows delineated responsibilities between clinical departments and virtual agents, leveraged current infrastructure and maximised best practices from the original model. This paper outlines the models implemented, and presents lessons learned and best practices garnered from each implementation.

Keywords: telehealth delivery; telemedicine; staffing models

The full article is available to subscribers to the journal.

Already a subscriber? Login or review other options.

Author's Biography

Amrika Ramjewan is a Principal Strategist with the Mayo Clinic Innovation Exchange, where she partners with health care entrepreneurs, start-ups, and industry experts to bring breakthrough innovations to market. She has nine years of experience leading transformation projects in healthcare, with expertise in advanced analytics, digital transformation, innovation, process and systems engineering. She joined Mayo Clinic in 2017, having previously worked as a public sector transformation specialist in Trinidad and Tobago. She holds a postgraduate diploma in machine learning and artificial intelligence from Columbia Engineering Executive Education, New York; MSc in analytics: operations research and risk analysis from the University of Manchester, United Kingdom; and BSc in industrial engineering from the University of the West Indies, St. Augustine. She is a member of the Institute of Industrial & Systems Engineers (IISE) and is an Instructor of Health Care Systems Engineering with the Mayo Clinic College of Medicine and Science.

Aaron Stelpflug is a Senior Health Systems Engineer with Mayo Clinic’s Strategy Department. He holds an MA in management from Saint Mary’s University Minnesota, a BS in biology and chemistry from the University of Wisconsin La Crosse and a clinical laboratory science — chemistry/urinalysis certificate from the University of North Dakota. Aaron is an Instructor in Health Care Systems Engineering at the Mayo Clinic College of Medicine and Science with six years of experience in the Strategy Department (formerly Management Engineering & Consulting). He also has over ten years of laboratory experience within Mayo’s Department of Laboratory Medicine and Pathology. Aaron is in the Clinical Systems unit, where he supported an electronic health record transition and optimization, leads process improvement efforts between the laboratory and clinical practice groups and has supported projects related to COVID-19, telehealth and population health, among others.

Michelle Leung is a Health Systems Engineer with Mayo Clinic’s Strategy Department based out of Rochester, MN. She joined the Mayo Clinic in 2019 as an Associate-Fellow with the Strategy Department (formerly Management Engineering & Consulting). At the Mayo Clinic, she supported Enterprise Telehealth initiatives by providing expertise in business consulting, process design and improvement, strategic planning, and implementation, and change management. She holds an MPH from Emory University-Rollins School of Public Health, a LSSGB from Emory University and, a BS in public health from the University at Albany. Michelle has experience in the public and private sectors of public health and healthcare.

Sandra Elsen is a Senior Health Systems Engineer with Mayo Clinic’s Strategy Department based out of La Crosse, WI. She holds an MBA from University of Wisconsin – La Crosse, a BS in clinical laboratory science from the University of North Dakota, and a BS in genetics, cell biology, and development from University of Minnesota, Twin Cities. With more than a decade at Mayo Clinic and over 8 years in the quality field, her background includes clinical genetics, quality management systems, and process engineering. She recently supported COVID-19 process improvements and management efforts at Mayo Clinic on the topics of telehealth, COVID testing facilities, strategic practice ramp up and surge planning.

Pawan Bhandari is a Principal Health Systems Engineer with Mayo Clinic’s Strategy Department in the Southwest Minnesota Region, where he provides business consultative and management engineering services from discovery to execution at various levels of the Mayo Clinic organization. He holds a BS and MS in manufacturing engineering technology from Minnesota State University and is also an Instructor in Health Care Systems Engineering with the Mayo Clinic College of Medicine and Science. He is a member of the American Society for Quality (ASQ), Association of Technology, Management and Applied Engineering (ATMAE), and Industrial Engineering & Operations Management Society (IEOM). He is an ASQ Certified Six Sigma Black Belt and ASQ Certified Quality Improvement Associate. His research interests are quality and process improvement, technology management, quality systems, performance improvement in healthcare, and business analytics.

Jordan Coffey is the Director of Digital Practice Research within the Mayo Clinic Center for Digital Health (the contemporary to the Mayo Clinic Center for Connected Care), where he provides leadership and day-to-day management for a novel unit dedicated to evaluating and understanding the impact of digital health solutions in practice. Prior to this current role, he helped to lead Mayo Clinic’s remote patient monitoring program and telehealth frontline operations. Jordan has over a decade of experience in research, operations, strategic management, and program development for both nonprofit and for-profit organizations. He joined Mayo Clinic in 2011, having previously worked in the healthcare consulting and aerospace industries. He holds a bachelor’s degree in chemistry from the University of Wisconsin La Crosse, masters’ degrees in business administration and leadership from Augsburg University, and a master’s degree in healthcare administration from the University of Minnesota.

Citation

Ramjewan, Amrika, Stelpflug, Aaron, Leung, Michelle, Elsen, Sandra, Bhandari, Pawan and Coffey, Jordan (2021, December 1). Staffing models for integration of virtual visits into clinical operations. In the Management in Healthcare: A Peer-Reviewed Journal, Volume 6, Issue 2. https://doi.org/10.69554/ACEW5933.

Options

  • Download PDF
  • Share this page
    Share This Article
    Messaging
    • Outlook
    • Gmail
    • Yahoo!
    • WhatsApp
    Social
    • Facebook
    • X
    • LinkedIn
    • VKontakte
    Permalink
cover image, Management in Healthcare: A Peer-Reviewed Journal
Management in Healthcare: A Peer-Reviewed Journal
Volume 6 / Issue 2
© Henry Stewart
Publications LLP

The Business & Management Collection

  • ISSN: 2059-7177
  • Contact Us
  • Request Free Trial
  • Recommend to Your Librarian
  • Subscription Information
  • Match Content
  • Share This Collection
  • Embed Options
  • View Quick Start Guide
  • Accessibility

Categories

  • Finance, Accounting & Economics
  • Global Business Management
  • Management, Leadership & Organisation
  • Marketing & Sales
  • Strategy
  • Technology & Operations

Librarian Information

  • General Information
  • MARC Records
  • Discovery Services
  • Onsite & Offsite Access
  • Federated (Shibboleth) Access
  • Usage Statistics
  • Promotional Materials
  • Testimonials

About Us

  • About HSTalks
  • Editors
  • Contact Information
  • About the Journals

HSTalks Home

Follow Us On:

HS Talks
  • Site Requirements
  • Copyright & Permissions
  • Terms
  • Privacy
  • Sitemap
© Copyright Henry Stewart Talks Ltd

Personal Account Required

To use this function, you need to be signed in with a personal account.

If you already have a personal account, please login here.

Otherwise you may sign up now for a personal account.

HS Talks

Cookies and Privacy

We use cookies, and similar tools, to improve the way this site functions, to track browsing patterns and enable marketing. For more information read our cookie policy and privacy policy.

Cookie Settings

How Cookies Are Used

Cookies are of the following types:

  • Essential to make the site function.
  • Used to analyse and improve visitor experience.

For more information see our Cookie Policy.

Some types of cookies can be disabled by you but doing so may adversely affect functionality. Please see below:

(always on)

If you block these cookies or set alerts in your browser parts of the website will not work.

Cookies that provide enhanced functionality and personalisation. If not allowed functionality may be impaired.

Cookies that count and track visits and on website activity enabling us to organise the website to optimise the experience of users. They may be blocked without immediate adverse effect.