Citations

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.

Background: Remote patient monitoring (RPM) is an emerging focus in health care, and specialized programs may reduce medical costs, supplement in-office visits, and improve patient satisfaction. In this study, we describe the development, feasibility, and early outcomes of an RPM program for patients with decompensated cirrhosis. Methods: Forty-six patients were offered enrollment at the time of hospital discharge in the cirrhosis RPM program (CiRPM), of which 41 completed at least 30 days of monitoring. Participants were mailed remote monitoring equipment and a tablet to be used for patient-reported outcomes. Alerts were continuously monitored by virtual nursing staff who could perform targeted interventions. A cohort of historical controls (n = 74) was created for comparison using inverse probability of treatment weighting. Results: Patients were enrolled in the program for a mean of 83.9 days, with 28 (68%) completing the full 90-day program. Participants uploaded vital signs and responded to symptom-based questionnaires on 93% of the monitored days. On end-of-program surveys, over 75% of patients expressed satisfaction with the program. Gender, age, and MELD-Na were similar between CiRPM and weighted control groups. The 90-day readmission rate was 34% in CiRPM and 47% in weighted controls. In the CiRPM group, 12% of subjects had 2 or more admissions, compared to 37% in the weighted control group. Conclusion: This study demonstrates the feasibility of a cirrhosis-specific RPM program. Overall, patient satisfaction and utilization of the CiRPM was high. Future studies are needed to confirm the impact of RPM on the reduction of hospital readmissions in decompensated cirrhosis.

Background and Aims: In a recent trial, patients with severe alcohol-associated hepatitis treated with anakinra plus zinc (A+Z) had lower survival and higher acute kidney injury (AKI) rates versus prednisone (PRED). We characterize the clinical factors and potential mechanisms associated with AKI development in that trial. Approach and Results: Data from 147 participants in a multicenter randomized clinical trial (74 A+Z, 73 PRED) were analyzed. AKI, AKI phenotypes, and kidney injury biomarkers were compared between participants who did/did not develop AKI in the 2 treatment arms. Multivariable competing risk analyses were performed to identify baseline risk factors for incident AKI, with death treated as a competing event. Risk factors considered were age, sex, mean arterial pressure, white blood cell count, albumin, MELD, ascites, HE, and treatment arm. At baseline, no participants had AKI; 33% (n=49) developed AKI during follow-up. AKI incidence was higher in A+Z than in PRED (45% [n=33] versus 22% [n=16], p=0.001). AKI phenotypes were similar between the 2 treatment arms (p=0.361), but peak AKI severity was greater in A+Z than PRED (stage 3 n=21 [63.6%] vs. n=8 [50.0%], p=0.035). At baseline, urine-neutrophil-gelatinase–associated lipocalin levels were similar between participants who developed AKI in both treatment arms (p=0.319). However, day 7 and 14 urine-neutrophil-gelatinase–associated lipocalin levels were significantly elevated in participants treated with A+Z who developed AKI versus participants treated with PRED who developed AKI (p=0.002 and 0.032, respectively). On multivariable competing risk analysis, only A+Z was independently associated with incident AKI (subdistribution hazard ratio 2.35, p=0.005). Conclusions: AKI occurred more frequently and was more severe in participants treated with A+Z. A+Z–treated participants with AKI had higher urine-neutrophil-gelatinase–associated lipocalin, suggesting that A+Z maybe nephrotoxic in patients with severe alcohol-associated hepatitis.

AbstractBackgroundTechnology has revolutionized not only direct patient care but also diagnostic care processes. This study evaluates the transition from glass‐slide microscopy to digital pathology (DP) at a multisite academic institution, using mixed methods to understand user perceptions of digitization and key productivity metrics of practice change.MethodsParticipants included dermatopathologists, pathology reporting specialists, and clinicians. Electronic surveys and individual or group interviews included questions related to technology comfort, trust in DP, and rationale for DP adoption. Case volumes and turnaround times were abstracted from the electronic health record from Qtr 4 2020 to Qtr 1 2023 (inclusive). Data were analyzed descriptively, while interviews were analyzed using methods of content analysis.ResultsThirty‐four staff completed surveys and 22 participated in an interview. Case volumes and diagnostic turnaround time did not differ across the institution during or after implementation timelines (p = 0.084; p = 0.133, respectively). 82.5% (28/34) of staff agreed that DP improved the sign‐out experience, with accessibility, ergonomics, and annotation features described as key factors. Clinicians reported positive perspectives of DP impact on patient safety and interdisciplinary collaboration.ConclusionsOur study demonstrates that DP has a high acceptance rate, does not adversely impact productivity, and may improve patient safety and care collaboration.