Kamath, Janine R.

Community organisations, alternative schools and business institutions worldwide prepare youth for the workforce. Since the COVID-19 pandemic, changes in work—life decisions and business needs have led to a shortage of talent. To equip students with the skills and mindset needed to be future ready, the power of diversity, equity and inclusion (DEI) must be harnessed through a network of meaningful connections and partnerships. A small group at Mayo Clinic, sharing a common interest in DEI and the local community, explored ways to encourage diverse, young talent to embark on careers in science, technology, education and mathematics. Input from community organisations and professionals indicated that collaborating with educational institutions is vital, which led to the initiation of a pilot programme involving one high school. The group collaborated with the school’s Work Experience Coordinator and students to develop and implement a pilot Career Preparation Programme (CPP) as part of a Work Experience Seminar (WES) course to deepen students’ knowledge of healthcare careers and provide one-on-one and group mentorship. Through discussions about career possibilities, levers of success and a higher purpose, the team sought to help students appreciate available and attainable career opportunities. Student evaluations were conducted after each of the two semesters. A total of 93 students participated in the pilot programme, of whom 85 (91 per cent) reported that the combined offering was engaging and worthwhile. The primary takeaways were ‘the importance of soft skills’, ‘following dreams and passions’ and ‘being a lifelong learner’. Inspired by this experience, the students established a club focused on career mentoring and tutoring. Throughout the process, trust, credibility and role modelling were emphasised. In addition, flexibility, patience and openness to bidirectional learning and creative ideas were identified as the main elements of programme’s success. The team plans to expand the pilot programme to include a non-healthcare focus and implement the programme at additional high schools. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/ business/.

The application of artificial intelligence (AI), large language models and generative AI (GenAI) is accelerating rapidly across many industries worldwide. Innovative models and tools are being piloted to understand their business and societal value. Models such as ChatGPT (OpenAI), Gemini (Google) and Copilot (Microsoft) have become increasingly sophisticated and widely adopted. Understanding the advantages and drawbacks of GenAI models is crucial for organisations seeking to leverage GenAI to maximise their efficiency and expand their capabilities. This paper describes the strategic approach, implementation and findings of using GenAI in a health care business context. A GenAI model was used to analyse and summarise strategic and operational information submitted by external organisations seeking to collaborate with Mayo Clinic. The goal was to reduce process cycle time and manual resource intensity. In parallel, a comparative human review was conducted by functional experts. Both the AI-generated and human-reviewed results were evaluated using sentiment analysis (SA) and then categorised as positive, neutral or negative. Attention was paid to possible inaccuracies and biases associated with the use of the GenAI model. GenAI reduced the manual workload by approximately 20−25 per cent and presented information in a well-structured format. However, the SA showed the GenAI results as positively biased and the human-generated results as neutral. These results were most likely influenced by a positive bias in the input documents, the lack of contextual comparators/ standards in the GenAI model and an inherent bias within the model’s algorithm(s). Additionally, limitations in input size and language translation hindered the GenAI model’s effectiveness. The possibility of AI hallucinations/inaccuracies emphasised the importance of validation by a human expert. Furthermore, carefully formatting the input data enhanced the value and relevance of the GenAI model’s outputs. GenAI has the potential to increase efficiency and alleviate manual burden, but it must be thoughtfully implemented to address inaccuracies, biases and privacy concerns. This article is also included in The Business & Management Collection which can be accessed at https:// hstalks.com/business/.

Whether centralised or decentralised, healthcare access models provide varying degrees of benefit to customers and to the organisations they serve. Mayo Clinic Health System in Southwest Minnesota, United States, is a community-based practice of 23 clinics and 6 hospitals that has undergone an evolution of its access model. In 2010, a centralised access model was adopted, including the physical location of schedulers, which was expected to offer greater efficiency, flexibility and staff savings. However, in 2016, the region noted concerning trends of low patient and provider satisfaction with scheduling, decreasing patient access and less-than-optimal patient throughput, all subsequently contributing to declining financial performance. Early concerning trends led to further investigation of practice areas and geographical sites that had notable appointment capacity yet low patient access and throughput. Provider productivity rates, calendar management and patient access varied substantially. Performance in scheduling operations was below par because of limited connection with the practice. The combination of practice variation and a centralised access model was causing an increase in scheduling errors, consistent rework/rescheduling, less-than-optimal patient access, low provider calendar fill rates and high levels of dissatisfaction for patients and providers. Our group was tasked with analysing the problems and developing a new scheduling model. This paper describes the resulting model: a hybrid of centralised and decentralised models, which promised the benefits of both and involved transformation in clinical practice operations and access management. Standardisation for provider scheduling and template management was enhanced. Pods of scheduling personnel were embedded in practice areas. The proximity of the pods to physician, nursing and other clinical staff allowed for increased collaboration and communication. The hybrid model improved access metrics for average speed to answer, abandoned call rates, patient access and throughput, financial performance, and patient and provider satisfaction.

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.

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 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.

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.

Agility has been adopted in the software development industry for decades and has been used in the business world for the past 10 years. In healthcare, however, agility has not been widely adopted or studied but is emerging as imperative for competitive advantage in a rapidly changing environment. Human-centred agility and change in the wake of the COVID-19 pandemic has become especially important. Change agility is composed of two aspects. While the first aspect is a mindset that embraces change, resiliency, flexibility and responsiveness to consumer needs, the second is an approach using collaborative efforts through self-organising teams. Healthcare organisations must adopt both aspects to leverage the collective value of change agility. To help staff embrace and develop a change agility mindset, healthcare organisations need to offer relevant educational courses and coaching; teach change agility principles and values by using case studies and real-life applications; and promote the right culture by building flexible systems, providing a safe learning environment and encouraging risk-taking. To grow and sustain change agility, healthcare organisations can benefit by using a continuous seven-step quest: examining the current state, defining the future state, assessing the gaps, developing strategies, executing the strategies, measuring progress and maintaining success. This paper addresses the strategy and iterative interventions developed by the Department of Management Engineering and Consulting (renamed the Strategy Department) at Mayo Clinic to prepare its professional staff to drive a business-focused, change agility mindset through benchmarking, education and experiential learning. The early experiences and lessons learned at Mayo Clinic in change agility are likely broadly transferable to other healthcare organisations.

The value of a shared service organisation (SSO) is recognised in transactional functions across manufacturing, technology and finance. Successful application of an SSO in healthcare is limited, particularly in professional, non-transactional functions. This article explores the application, effectiveness and challenges of creating an SSO in a fast-paced, dynamic environment. The Department of Management Engineering & Internal Consulting (ME&IC), a team of engineering and consulting staff at Mayo Clinic, completed its SSO journey by leveraging lessons from Mayo Clinic and various industries. Methods to implement a successful SSO included a literature review, customer and leadership interviews, and cross-industry benchmarking. ME&IC converged and streamlined its services, expenses, infrastructure and service delivery; realised economies of scale; translated best practices; and optimised staff talent. The SSO enabled customer responsiveness and performance excellence by integrating talent, processes and technologies. An effective SSO supports policy standardisation, agile decision-making, strong change management, consolidation of shadow groups, resource alignment with strategic priorities and more accurate measurement and benefits realisation. To achieve success, SSO models must be adapted to organisation culture, leadership commitment and service delivery expectations. The systematic transition to an SSO and lessons learned by ME&IC are broadly transferable to professional groups across industries.

Over the last two decades there has been considerable deliberation, experience, and research in the arena of Health Information Technology (HIT), Electronic Medical Records (EMR), Electronic Health Records (EHR), and more recently, Electronic Personal Health Records (PHR). Despite the challenges involved in adopting these systems and technologies, there is consensus that they bring significant value to the delivery of trusted and affordable healthcare. The investment involved and the impact on customers, clinical and non-clinical staff, and processes are significant and far reaching. This chapter attempts to synthesize the vast amount of information, experience, and implementation perspectives related to Electronic Health Records with the intent of assisting healthcare institutions and key stakeholders make informed choices as they embark on designing, developing, and implementing an EHR. EHR considerations, challenges, opportunities, and future directions are also addressed. The chapter highlights the power of management engineering to facilitate planning, implementation, and sustainability of the EHR, a critical asset for a healthcare organization and the overall healthcare industry.