Implementation science

Implementation scientists in the Mayo Clinic Kern Center for the Science of Health Care Delivery aim to improve healthcare delivery processes and outcomes. They also aim to reduce the time it takes to translate evidence-based practices into routine use.

Healthcare practices that are developed and studied in controlled research environments often stall out or fail when they move to real-world settings such as patients' daily lives or busy clinic and hospital settings. Sometimes this occurs because patients, clinicians or caregivers were not involved in finding solutions or deciding how those solutions should be put into practice.

Implementation scientists engage with patients and care teams to design strategies to increase the adoption and use of evidence-based interventions in real-world contexts. In this context, an intervention is anything that a healthcare team does to care for a patient. Examples include providing counseling or education, running tests, prescribing medicine, or performing surgery.

Implementation scientists look at outcomes to figure out whether interventions are effective. They also look for better ways to put interventions into use in patient care. They examine how fast interventions change how healthcare teams provide care. And they identify ways to get more healthcare teams to use new inventions and make it easier for them to do so.

This approach can increase the likelihood that interventions will improve patient outcomes and reduce costs while being responsive to the needs of patients and care teams.

Focus areas

Center researchers engaged in implementation science provide timely consultation and scientific support in line with Mayo Clinic's practice priorities. This results in collaborations that:

  • Transform care delivery, improve patient experience and increase access to care. Researchers partner with clinical and operational teams to develop inclusive evaluation approaches. Their goal is to make sure that interventions and practice changes meet patients' and care teams' needs. This includes developing, implementing and evaluating remote and technology-enabled models of care in patients' homes or communities. Researchers blend quantitative and qualitative data for evidence-based transformations. They align these transformations with the concept of "the Quadruple Aim," which involves simultaneously improving patients' experiences, advancing large-scale population health, reducing costs and helping healthcare professionals avoid burnout.
  • Facilitate informed decision-making. The center's implementation experts work together to test and introduce unique new tools to support clinical decision-making. Many of these tools are digital and based on artificial intelligence (AI). Researchers also help develop and implement patient education and shared decision-making tools that support conversations between patients and their care teams.
  • Drive innovation and learning. Experts consult with clinicians and other research collaborators to ensure that they use implementation science principles as they develop and evaluate interventions. Implementation scientists work with multidisciplinary teams to refine interventions and conduct practice-embedded research. They help establish sustainable processes that are signs of a data-driven and improvement-focused learning health system.
  • Act to eliminate disparities and systemic issues. The Implementation Science Program team applies sociocultural perspectives from a range of stakeholders to promote a just and inclusive work environment. Researchers pinpoint racial disparities in care delivery. They examine how, in some cases, the introduction or use of clinical practices may make these inequities worse. They support creative solutions that take people's entire circumstances into account, including environmental and psychological factors. They address the needs of caregivers, family and other people who support patients day-to-day but are often overlooked. Furthermore, researchers study how information about race, ethnicity, sex and social risk factors can be used to ensure clinically meaningful and ethical data collection and application.
  • Design and evaluate AI integration. Implementation science experts consider the complex details of interactions between humans and computers. They consider societal factors that influence people's acceptance and adoption of AI and other technologies. Their work leads to effective, culturally sensitive and responsible use of AI interventions to improve healthcare quality and the experiences of staff members and patients.

Skills and capabilities

Center scientists who engage in implementation science bring diverse skills, including expertise in:

  • Behavioral science and health communication.
  • Human-computer interaction and human-centered approaches to AI implementation.
  • Implementation science and program evaluation models and methods.
  • Patient-reported outcome measurement.
  • Stakeholder engagement and formative evaluation.

The team provides leadership in the design, implementation and evaluation of projects. It collaborates with clinical partners to:

  • Apply appropriate implementation and evaluation theories, models and frameworks.
  • Assess implementation context and setting to identify barriers and facilitators to success.
  • Design new and unique pragmatic study proposals and protocols.
  • Engage care teams and patients to understand their needs, preferences and values.
  • Evaluate a range of outcomes using quantitative, qualitative and mixed methods approaches.

Implementation science principles are woven throughout the research that the Mayo Clinic Kern Center for the Science of Health Care Delivery supports. Faculty members with interests and expertise in implementation include:

Projects

Researchers focusing on implementation science collaborate on multiple practice-transforming projects. Several are briefly summarized here, along with links to related publications.

Risk communication during the COVID-19 pandemic

The Implementation Science Program team put into place and evaluated a community-engaged, two-way pandemic crisis and emergency risk communication framework during the COVID-19 pandemic. The team worked with African American churches and immigrant and refugee populations to create and test the framework.

Related publications:

Home-based tampon sampling for endometrial cancer

For several years, Mayo Clinic researchers have led investigations on the use of tampons to detect endometrial cancer. As part of this research, the team conducted community focus groups to explore the acceptability and feasibility of a home-based tampon sampling approach for endometrial cancer.

Related publications:

ECG AI-Guided Screening for Low Ejection Fraction

This study is also called the EAGLE study. It is a randomized trial to validate a clinical decision-making tool. The tool uses an artificial intelligence (AI) algorithm that screens for low ejection fraction from an electrocardiogram (ECG). The tool then recommends actions that healthcare professionals can take to diagnose their patients. The project team partnered with the Mayo Clinic departments of Primary Care and Cardiovascular Medicine to understand users' preferences and experiences with the tool. The result was a set of human-centered implementation strategies to enable sustained use in clinical practice.

Related publications:

Home-based pulmonary rehabilitation with health coaching

Implementation science experts worked with physician-scientists to increase access to evidence-based care in patients' homes. The goal of this project was to develop a unique new pulmonary rehabilitation approach that makes technology and telephone-based health coaching available to patients with chronic obstructive pulmonary disease (COPD). Implementation science experts helped assess feasibility, including acceptability among patients.

Nurse-based care coordination to reduce hospital readmissions

This pragmatic trial compares the effectiveness of adult medical care coordination with the usual standard of care. The goal is to find out which approach reduces unplanned hospital readmissions among patients who are at high risk of being readmitted. The research team uses an integrated mixed methods assessment of patients' and clinicians' experiences with the care coordination program to gain a comprehensive understanding of how it is put into place and how knowledge about the program is shared.

Using the electronic heath record (EHR) to control cancer symptoms

This research aims to put in place and test an EHR-supported system. The system monitors and manages the symptoms of patients with cancer during and after active treatment. The project team is conducting a cluster randomized pragmatic clinical trial across 18 disease groups and clinical practice sites at Mayo Clinic's campus in Rochester, Minnesota, and Mayo Clinic Health System.

Related publications:

Shared decision-making for individualized cardiovascular event prevention

This project aims to integrate a tool to facilitate shared decision-making about cardiovascular health into preventive care settings. The research team is studying strategies that foster adoption and routine use of the tool. The team is conducting the trial at three diverse healthcare systems within the Mayo Clinic Care Network. The Mayo Clinic Care Network links more than 40 health systems around the globe with the research, education and clinical expertise of Mayo Clinic.

Video telemedicine for newborn resuscitation

In this study, members of the Implementation Science Program team studied the use of video telemedicine for newborn resuscitation. The goal was to better understand healthcare professionals' acceptance, use and integration of this technology in community hospital settings.

Educational interventions on mammographic breast density: The Latinas Learning About Density study

This study is also called the LLEAD study. It is a randomized trial of written and interpersonal education on breast density. It was conducted among Latinas in a federally qualified health center in Phoenix, Arizona. Implementation science experts conducted a process evaluation to understand if the study interventions were possible in that setting and if they were used consistently.

The 'Model' Unit: Facilitating continuous innovation and adaptation in family medicine

Family medicine addresses a wide range of medical, health and wellness concerns. These include well-child exams, behavioral healthcare, minor illnesses, chronic conditions such as diabetes and high blood pressure, and routine health exams. The field needs bold transformation to improve quality, cost and outcomes while caring for more people with increasingly complex health needs.

At Mayo Clinic, a model unit embedded in the Department of Family Medicine serves as a "living lab." In this lab, researchers and clinicians model new structures and processes, test them, and assess their usefulness and sustainability for patient care. This type of implementation science investigation allows rapid cycles of innovation and evaluation. Improvements in care delivery can be shared for immediate adoption across Mayo Clinic. Peer-reviewed publications and scientific presentations allow the team to spread new knowledge that can transform care for people everywhere.

Implementing remote patient monitoring tools in a variety of clinical contexts

The use of remote patient monitoring increased throughout the COVID-19 pandemic. Researchers are partnering with clinical staff to identify the best way to use remote monitoring tools. The research team also is developing plans for the sustainable use of these tools going forward. Another focus of this project is to integrate a set of remote patient monitoring devices into the patient care toolbox at Mayo Clinic in Arizona. These devices had previously proved to be successful when used at Mayo Clinic in Minnesota.

Reducing use of acute care for intermediate care with community paramedicine

The Care Anywhere With Community Paramedics trial is a pragmatic point-of-care trial. It is evaluating the effectiveness and implementation of a community paramedicine program for adults requiring an intermediate level of care. Participants were randomized to receive usual care — for example, hospitalization — or get care at home with visits from a community paramedic.

Contact

Contact the Mayo Clinic Kern Center for the Science of Health Care Delivery with inquiries about its implementation science research or collaboration opportunities.