Citations

Strategic projects in large healthcare organisations are often highly complex and dynamic, and they require a team of skilled business professionals to execute them. Examples of difficult, costly and extended project executions have been shared in the literature. Successful project execution involves many critical facets. One facet that continues to be of marked interest is effective resourcing of strategic projects. This paper focuses on describing a staffing approach used at Mayo Clinic (Rochester, Minnesota) to facilitate successful, agile and sustainable execution, with desired outcomes. In 2016, Management Engineering & Consulting (ME&C) began exploring a collaborative staffing model that partnered management engineers with project managers (PMs) to drive strategic, multisite projects. This ongoing collaboration model was evaluated from multiple perspectives, including project outcomes, timeliness, client and staff satisfaction and opportunities for innovation. Data and feedback on the model were collected with historical reports, surveys and focus groups with stakeholders, leaders, PMs and management engineers. The feedback and data indicated that the collaborative staffing strategy and model have further optimised service delivery, enabled professional staff to work at the highest level of their competency and dynamically blended knowledge, expertise and skills to achieve better and more sustainable overall project outcomes.

Implementation of Epic as an integrated electronic health record and revenue cycle management system was the largest software implementation in the history of Mayo Clinic. It converged thousands of workflows, eliminated hundreds of legacy systems and affected thousands of end users across Mayo Clinic campuses. Strong physician leadership, project management and deliberate change management were important components in this US$1.5bn project. Mayo’s leadership used a distinctive approach to prepare staff to make these important changes. At the beginning of the project, leaders developed a deliberate and robust change management strategy and formed a team focused on change management and communications. The change management team comprised Mayo Clinic health systems engineers, who know healthcare and Mayo’s culture and values and have expertise in systems engineering and quality improvement principles. The team developed an approach using various tools to support operational readiness and change readiness and to communicate important messages throughout the project cycle. In this paper, crucial components of the project for successfully managing the people side of change are described: development of an approach to change management that fits the organisation, creation of a dynamic team with the right skills mix and execution of appropriate timing of tactics.

The novel severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19), has presented healthcare delivery challenges the world has never encountered before. Healthcare and its practitioners, while finding themselves in difficult situations, must still care for patients with emergent needs and ensure the safety and well-being of all patients and staff. At Mayo Clinic, effective navigation of the dynamic and complex situation created by COVID-19 required unique multidisciplinary collaborations to design and implement solutions quickly. Frontline care providers and staff of ancillary services and other critical healthcare functions partnered with the Department of Management Engineering and Consulting (ME&C) team to organise and re-engineer operations to iteratively adapt to the dynamic ‘new normal’. Health systems engineers (HSEs) and project managers (PMs) accelerated the implementation of innovative interventions by leveraging advanced engineering and consulting frameworks, models and methods. Utilising a patient and staff-centric systems approach to align electronic systems, operational processes, staffing resources and organisational infrastructure has been invaluable for speed and effectiveness. Harnessing the promise of digital technology and advanced analytics was imperative and set the stage for a broader set of possibilities to transform healthcare. These possibilities include scaling of consumerfocused virtual services in multiple and unfamiliar settings, new assets that could be reused for future emergencies, accelerating the implementation of time-sensitive solutions, applied analytics and modelling to predict clinical, financial and community impacts and reimaging the healthcare supply chain. As more has been learned about the trajectory and management of COVID-19, the need to rapidly evolve and pivot interventions for short-, medium-, and long-term applications continues. This article addresses the unique contributions of ME&C during the COVID-19 crisis and the results-oriented collaborations with staff in critical business functions. We believe that the experiences, outcomes and lessons learned through this journey are broadly transferable to other healthcare and nonhealthcare organisations.

Mayo Clinic Health System — Southwest Minnesota Region, one of four practice regions in the Midwest, provides primary and speciality care in ambulatory, procedural and hospital settings. Clinic appointment fill rates, no-show rates and late cancellation rates are closely monitored operational metrics, but at the time this study began, less was known about the refill rates of late appointment cancellations. This metric is of importance because these unfilled appointment times contribute to increased expenses for healthcare organisations, unnecessary delays in care and decreases in revenue. The main objectives of this study were to understand the current state and potential opportunities for refilling late cancellations. Qualitative and quantitative methods were used, including variance analysis, the Tukey post hoc test, Pareto analysis, the completion of interviews with important stakeholders and data extraction from the institution’s electronic health record. Findings showed that late cancellation rates remained steady in 2021 and that late cancellations were not being refilled consistently across departments and regions. Appointment refill rates were higher in departments with few or no requirements for preparatory evaluation, whereas in specialties that did require preparatory evaluations, refill rates were lower across the four regions of the Mayo Clinic Health System. Even in departments with high demand, the refill rates were lower, resulting in missed opportunities for patient visits. Mapping the workflow for late cancellations indicated inconsistent methods for refilling late cancellation openings and the lack of a defined process for refilling them that was understood by the entire care team. The logistics of optimising refill rates for late cancellations were affected by provider preference, selfscheduling functionality and appointment requirements. This study identified opportunities for optimising workflows to use the waiting list proactively to refill late cancellations.

The COVID-19 pandemic disrupted the workforce, resulting in a shift to a largely remote working population. As a result of this shift, Employee Occupational Health Services (EOHS) was required to develop a solution to evaluate new employees and provide occupational medical clearance without the physical presence of the candidate. An online candidate portal was created where individuals could complete evaluation paperwork and screenings asynchronously. The evaluation forms and screenings were then reviewed by occupational health nursing staff, and testing was conducted in the candidate’s home location. The virtual evaluation solution expedited the assessment process, added convenience for candidates and reduced the amount of time needed from EOHS staff. It is imperative that EOHS departments adjust to the changing workforce by offering virtual evaluation solutions that provide candidates with a seamless and efficient solution to complete required paperwork, testing and immunisations.

With current and projected staffing shortages, healthcare settings must find innovative ways to address workload problems. One possible solution in the outpatient setting is the use of patient self-check-in kiosks. This paper aimed to understand the effectiveness of the use of self-check-in kiosks in a rural community-based clinic setting. Data was gathered retrospectively on patients seen in our clinic during 2022. Two-sample z-tests were used to compare the use of kiosks before and after the implementation of intentional interventions to help motivate patients to check in using kiosks. Binomial logistic regression was used to determine factors that influence use of kiosks. We then analysed patient satisfaction surveys to determine whether the interventions affected patient satisfaction. A total of 143,208 patients were included in the study. Significantly more patients used the self-check-in kiosks during the post-intervention period (24.9 per cent) than during the pre-intervention period (6.5 per cent) ( z = −102.79, P < 0.001). The outcome of the binomial logistic regression in the form of a model was significant ( χ2(9) = 2,274, P < 0.001) and showed that gender, age, financial (insurance) class and time of check-in significantly affect the likelihood of patients using the self-check-in kiosks. Patient satisfaction was not affected by the interventions. The study findings suggest that it is possible to increase the use of self-check-in kiosks with intentional interventions in a community-based clinic setting without negatively affecting patient satisfaction. Expecting that patients will use technology just because it is there may not be feasible, as evidenced by this case. Non-use of the technology by patients could lead to negative consequences, such as longer wait times and effects on overall patient flow.

In 2018, Mayo Clinic completed the largest transformational project in its 150-year history. Mayo Clinic was prepared to take on the implementation of new software systems (Epic Systems Corp) as an integrated electronic health record (EHR) and revenue cycle management (RCM) system across all sites of the enterprise. Three foundational teams were launched for this project: leadership, project management and change management. In a project such as this, a common pitfall is to focus completely on the system and lose sight of the end users. For Mayo Clinic, the people side of change was at the forefront of the project. A robust change management team was budgeted, staffed and engaged with an experienced outside consulting partner. A goal for the change management team centred on the best way to measure the change management impact and the degree to which it was making a positive contribution in driving successful adoption of the new EHR and RCM system. With literature lacking in this area, the team moved forward with courage and quickly learned that the easy part was the development of a survey with questions mapped to the six components of the change management strategy and the phases of the awareness, desire, knowledge, ability, reinforcement (ADKAR) Model (Prosci Inc). The hard part was building the infrastructure to visually display millions of rows of data that needed to be positioned, filtered and analysed for all affected locations. The authors share the methods to measure change and explain the importance of developing a comprehensive and robust means of gathering and displaying large volumes of change management data at the project onset. This paper prepares the reader to confidently develop an organisational framework to measure and report the effectiveness of a change management strategy.

Mayo Clinic is committed to reskilling and upskilling its workforce and to creating a strong, diverse leadership pipeline to advance its ‘Bold. Forward.’ strategy. In alignment with this commitment, the Mayo Clinic Shared Services Organization (MCSSO) launched a pilot offering staff the opportunity to work in a hybrid role and build new skills and connections. Pilot participants split their time equally between job roles in which the professional skill sets required were approximately the same. The pilot involved six MCSSO departments and six candidates (three pairs) from the participating departments. Staff were recruited for three roles: senior project manager, senior business analyst and call centre representative. Each of the three pairs worked in a hybrid assignment for six months. Candidates were offered opportunities to network with each other, MCSSO senior leaders and other diverse colleagues. Pilot evaluations were conducted at 0, 3 and 6 months with candidates and their supervisors. Additionally, benchmarking with external organisations allowed learning from advanced talent mobility and leadership diversity programmes. The evaluations highlighted that 50 per cent of the candidates were promoted by the end of their hybrid assignment. Most of them engaged in new projects, cross-trained and gained valuable insights, skills and expertise. Candidates and supervisors valued the opportunity to network with senior leaders and cross-functional colleagues. The pilot and external benchmarks emphasised the importance of a formal ‘talent mobility programme’ to build and sustain a diverse leadership pipeline. It is crucial to be intentional and bold with hybrid and mobility opportunities for intersectional candidates, under-represented groups and staff committed to equity, inclusion and diversity. All candidates and supervisors wanted the pilot to be expanded and operationalised. We believe that these early experiences, results and lessons on preparing diverse talent for leadership levels in the organisation are broadly transferable to other healthcare and non-healthcare organisations.

As project leaders plan large, transformational initiatives, impacted departmental leaders are often forgotten. Operational leaders are in need of a practical, concise guide to prepare for project activities and allocate resources. The Plummer Project change management team of Mayo Clinic created a single source of timelines and tasks with links to more detailed information, termed a ‘playbook’ for operational leaders. The tool was dynamic and provided the operations-relevant project timeline, required preparedness activities and essential references. This paper analyses the format and content of this playbook to assist other organisations with the execution of complex projects. The playbook provided clarity, efficiency and cohesiveness with deep benefits to the project team and organisation.

The increased use of intelligent automation (IA) is challenging organisations to rethink their business models and focus on agility, consumer centricity, innovation and operations excellence. Recognising the global impact of COVID-19, rapid changes in technology, data-driven decision-making and competition for differentiated talent, the Department of Management Engineering and Consulting (ME&C) prioritised the next skilling of talent to proactively prepare for the increased use of IA. This paper discusses our strategic approach, best practice interventions and diversity of methods to prepare ME&C staff. In alignment with Mayo Clinic’s new strategy to the year 2030, which is a catalyst for staff to develop the skills needed to transform healthcare, ME&C leveraged the 70-20-10 model for learning and development. Various next skilling interventions were adopted to disseminate knowledge and accelerate skill building across the IA continuum of discovery, translation and application. Commercial digital offerings were used, and various Mayo Clinic offerings (eg a series of artificial intelligence [AI] seminars, a journal club and an IA community of practice) were introduced. A crowdsourcing website was created to promote learnings focused on industry insights on AI, robotics, cloud computing, digital transformation and platform scalability. ME&C staff engaged with multidisciplinary teams on the execution of IA strategic priorities. Through diverse interventions, ME&C validated the importance of experimenting, learning from experiences (inside and outside Mayo Clinic) and developing reusable assets such as frameworks and playbooks. While engaging in initiatives that covered a constellation of technologies, staff learnt about the applied value of emerging technologies, business implications and considerations for consumer and staff experiences. We believe that our project will inform other organisations in their quest to build IA capabilities to accelerate business transformation while developing talent.