Zacks Industry Outlook Highlights: Johnson & Johnson, Medtronic, Zimmer Biomet and Roche
Торговый представитель России в США Александр Стадник рассказал об усилиях главы Татарстана Рустама Минниханова в налаживании бизнес-связей между странами в ходе годового собрания американо-российского делового совета.
Medtronic plc (MDT) recently announced the receipt of reimbursement approval from MHLW for its transcatheter CoreValve Evolut R System.
On Nov 30, 2016, we issued an updated research report on medical device major, Medtronic plc (MDT).
Medtronic plc (MDT) recently announced the signing of its Integrated Health Solutions agreement with University Hospitals (UH) in the U.S.
Ask yourself this: What will be most important to you when the time comes to die? We know, it’s a tough question, and one that patients, their families and loved ones, and their clinicians may avoid discussing. The result of putting off this conversation is that people often experience their final moments in a hospital room hooked up to machines, which isn’t what they would actually want. It needn’t go this way. A program we’re involved with at Ariadne Labs, a joint center of innovation between the Brigham and Women’s Hospital (BWH) and the Harvard T.H. Chan School of Public Health, has made good progress changing the way patients and their doctors talk about death so that, in the end, patients’ wishes, and their experience, are aligned. When people do have this conversation, most describe the importance in the final moments of being comfortable, in familiar surroundings with loved ones nearby. However, if you ask physicians, nurses, and social workers who care for the seriously ill, most quickly recall seeing patients, and their loved ones, suffering in the hospital at the end of life because the experience is so technology-driven and medicalized. This happens in part because of the powerful interventions we now have that can forestall death. But, more important, it happens because patients, their families, and clinicians have not discussed end-of-life wishes or, when they have, because the conversation isn’t well-documented and readily available when caretakers need it. Insight Center Innovating for Value in Health Care Sponsored by Medtronic Exploring cutting edge ways to lower costs and improve quality. To address this communication gap, the Ariadne Labs team asked “Why don’t these conversations happen?” and “What can we do to assure that they do?” The team identified a complex set of system failures that get in the way, from difficulty identifying patients who are likely to die soon to lack of training to overloaded physician schedules, and created a systematic, multistep intervention called the Serious Illness Care Program. The program includes intensive communication training for clinicians, centered on skills practice with trained actors standing in as patients. The primary tool is a structured and intensively tested conversation guide built around a set of questions clinicians should ask. These are very different from the sorts of questions doctors typically ask patients at the end of life which tend to revolve around treatment options. Instead, the guide suggests questions such as “What abilities are so critical to your life that you can’t imagine living without them?” and “How much are you willing to go through for the chance of gaining more time?” The program also includes guidance in identifying patients early, before crises occur, and documenting conversations, as well materials to help patients and families communicate about this difficult subject. We launched the program in primary care settings, where we guessed that doctors’ long-term and trusting relationships with their patients would ease these conversations. We targeted the sickest and most complex patient in six BWH primary care practices and trained the doctors, nurses and social workers caring for them to conduct comprehensive, “upstream” conversations about patients’ values, priorities and goals and carefully document them. Almost three quarters of more than 200 patients identified had detailed conversations that were clearly captured in the electronic medical record. Analysis of this work in ongoing, but as we’ll see, efforts beyond primary care have already revealed the program’s positive impacts on a host of measures. While initiating the program in primary care settings made sense, we discovered early on that confining it to primary care overlooked many patients who could benefit; a review of more than 350 deaths among BWH patients found that half of the most complex of these hadn’t been closely engaged with primary care, in large part because they had been cycling between the hospital, nursing homes and other care facilities. As these patients had been visiting the hospital at an alarmingly high rate, we reasoned that it would be valuable to engage with patients like these at the hospital, rather than just in primary care settings. The challenge was that, traditionally, end-of-life conversations within the hospital focus on medical procedures; more nuanced discussions about the patients’ goals and wishes tend to be deferred to the outpatient clinicians who know the patient best. Thus, we needed to design a program specifically for inpatient clinicians – the hospitalists who manage patients once they do arrive at the hospital. We adapted our primary-care approach to develop the SAGE (Speaking about Goals and Expectations) program to engage hospitalists, who may be meeting patients for the first time, and whose needs and time constraints are quite different from primary care providers’. This required updating the program’s Serious Illness Conversation Guide and training to fit the new hospital context, including adding training cases and language to change the way that clinicians introduce the end-of-life conversation to patients and deliver the prognosis. We found that hospitalists needed help not only in identifying patients with whom they should have these challenging conversations, but in the specifics of the conversations itself. They also needed support to ensure rapid follow up with patients, families and primary care teams after the patient left the hospital. Managing this post-discharge transition, we found, was best done by a social worker who could assure both that information from the hospital discussions was transmitted to the external facilities and providers who might need it, and that patients and their families had a steady contact after discharge when returning to the hospital. During the first year of this hospital pilot program, we identified 151 complex, seriously ill hospitalized patients and randomly assigned 80 to the SAGE program, with the remaining 71 patients receiving usual care. Of the 80 SAGE program patients, 100% had detailed and clearly documented conversations about goals and priorities compared with just 40% of patients in the usual care group. In addition to the primary care and hospitalist programs, the Serious Illness Care Program has been implemented in oncology, nephrology, and numerous other settings at sites across the country. These sites share their challenges and successes through an online community called the Serious Illness Care Community of Practice. Analysis of this work across primary care and specialties is ongoing, but the impact of the program has been analyzed in a randomized trial at the Dana-Farber Cancer Institute. In that trial, half of the clinician participants were trained in the program, while the remaining served as controls. Over 90% of patients in the trained practices had conversations, as compared to 70% of patients in control practices, and the trained clinicians’ conversations occurred on average three months earlier in the course of patients’ illness. What’s more, the discussions were more than twice as likely to be focused on the patient’s experience and wishes (95% vs. 45%), and retrievable from the electronic record (68% vs. 28%). Finally, having the conversation lowered patients’ anxiety, and patients reported that their hopefulness remained steady, while their sense of control over medical decisions increased. The impact of these conversations and the close connections facilitated by the social worker is evident in the story of a patient we’ll call Evelyn: An elegant 81-year-old woman with advanced dementia, Evelyn was hospitalized four times in eight months with confusion and recurrent infections related to her progressive Alzheimer’s disease. Before Evelyn started with the SAGE program, her devoted daughter had advocated for any treatment that might keep her mother alive longer. After careful discussions between Evelyn’s clinicians and the family that focused on Evelyn’s personality, sources of enjoyment, and known life priorities, as well as the trajectory of her illness, the family shifted the goals of her care from quantity of life to quality. Evelyn was content and comfortable in her final months, spending time with family, listening to music, and eating foods she enjoyed, rather than returning to the unfamiliar and restrictive environment of the hospital. Her daughter later reflected on the pivotal role of these discussions in helping to plan better for what lay ahead – in order to honor the things that were most important to Evelyn in her final months.
Calls for teamwork in health care are as persistent as they are hard to heed. Over the past decade, a growing number of observers, ourselves included, have called attention to the need for providers to coordinate better across specialties, shifts, departments, and even organizations (for example between primary care and urgent care facilities) to produce safe, affordable, high-quality care. Cross-boundary teamwork is particularly important when caring for patients with multiple chronic illnesses that require clinicians to coordinate across specialties. This type of teamwork is also critical in making the customized, time-sensitive care decisions required in busy emergency departments staffed around the clock by over-stretched clinicians. Prior research in healthcare and other industries makes clear the importance of team stability for team performance in general, yet stable teams are not always possible with chaotic 24/7 operations and heterogeneous work schedules. Told to form and act as teams, most clinicians will agree with the spirit of the request but will struggle to make it happen given well-documented challenges of communicating across shifts, expertise areas, or hierarchical levels. For years, the basic model for managing coordination in health care delivery has relied on what organizational scholars called role-based coordination. The premise is that professional training imbues “role occupants” (say, an emergency physician, or a scrub nurse) with the expertise needed to execute a part of a larger production or service operation. The model assumes that role responsibilities and boundaries are clear, and that crucial interdependencies between roles are sufficiently scripted to unfold appropriately. Insight Center Innovating for Value in Health Care Sponsored by Medtronic Exploring cutting edge ways to lower costs and improve quality. Unfortunately, role-based coordination theory faces important limitations in practice. First, although roles specify who is responsible for which tasks, role occupants often focus narrowly on their own responsibilities, neglecting the larger shared goal; this risk increases when their interdependent partners are difficult to identify or when accountability around the larger goal is ambiguous. Second, people in different roles are trained to think and communicate about, and value, different dimensions of performance, which further complicates coordination. Thus, even though roles are meant to clarify who is supposed to do what, they rarely guarantee the kind of teamwork across role boundaries in which people actively communicate about progress, exchange ideas, and help each other. We have studied these challenges for years – separately (here and here) and together – and we suggest that healthcare providers focus on implementing effective teaming, rather than traditional bounded teams, to improve care coordination. What is needed is fast-paced communication and coordination on the fly, among constantly shifting partners in care who don’t have the luxury of forming stable, well-bounded teams. There are structural and managerial ways to support this kind of teaming. In a study of teaming in a busy urban hospital’s emergency department, we found that implementing minimal role-based structures – which we call team scaffolds – helped people in different clinical roles collaborate effectively despite working together only temporarily. In that ED, coordination was given a boost – and made more like real team behavior – with the help of scaffolds that clarified fluid boundaries, provided an explicit shared goal, and ensured the availability of roles (skills) to accomplish that goal. Prior to the redesign, the hospital used ad-hoc groupings in the emergency department; any available nurse would triage a patient, then return the patient’s chart for any available resident, who would then leave the chart for any available attending. The nurses did not know which doctor was working on which patient, and vice versa, which led to inefficiencies and a lack of perceived accountability to one another. Schisms between professional groups also hampered communication. The redesign divided the ED into four pods, each of which had the necessary equipment to treat any type of patient. One attending physician, one or two residents, and three nurses were assigned randomly to a pod at the start of each of their shifts. Patients were doled out consecutively to the four pods, with the staff of each pod having ultimate responsibility for a queue of patients. Because of the staggered and differing shifts, the entire team composition could change over in as little as five hours. Although the scaffolds lacked stable membership, they triggered significant changes in teaming networks and behaviors and improved operational performance. The doctors and nurses were co-located, making it easy to know who was on the team. They were collectively responsible for getting the patients through the ED. And their teaming improved: They held each other accountable, actively updated and helped each other, and explicitly prioritized their shared efforts. Despite this noteworthy success, we’ve found that team scaffolds can underperform if they’re poorly managed. Thoughtful leadership is needed to implement them well – explaining the goals, engaging people in helping work out the details, and framing the entire endeavor as a learning journey. If scaffolds are simply imposed on people to make them “work as a team” without engaging them as equal partners in improving how work is done, the new structures are unlikely to enhance performance. For team scaffolds to work, leaders from different role groups – say medical and nursing directors – must collaborate with each other and with the staff to design, pilot, and manage the new structures. To get started, leaders should elicit and use feedback from the staff about the new design. They must invest in training people in the new system, for example operating a pilot scaffold in parallel with the existing processes for a few weeks, allowing people to practice working as a team in the new structure. Using this iterative approach, by listening and learning together, real teamwork can take hold.
Medtronic plc (MDT) recently announced the receipt of CE mark for its HVAD System left ventricular assist device (LVAD) for patients with advanced heart failure.
The emergence of big data, as well as advancements in data science approaches and technology, is providing pharmaceutical companies with an opportunity to gain novel insights that can enhance and accelerate drug development. It will increasingly help government health agencies, payers, and providers to make decisions about such issues as drug discovery, patient access, and marketing. From our unique vantage points at Genentech, a leading biotechnology company with a major data science practice, and The Data Incubator, a data-science education company that places and trains data scientists, we have seen how the pharmaceuticals industry has leveraged big data for some potentially revolutionary advances and the challenges it has faced along the way. For the industry, the biggest challenge by far has been talent: upgrading skill sets from those sufficient to analyze relatively small amounts of clinical trial data to those required to gain insights from the vast amount of real-world data, including unstructured data such as physicians’ notes, scans and images, and pathology reports. The pharmaceuticals industry has seen an explosion in the amount of available data beyond that collected from traditional, tightly controlled clinical trial environments. To be sure, anonymized insurance-claims data and electronic health record (EHR) data has been accessed and analyzed for many years. But in the past, EHR data was often limited to a single research institution or provider network, and obtaining the data needed to help answer a specific research question usually involved a tedious and inefficient process. While much still needs to be done to create standardized methods for sharing and making sense of anonymized EHR and genomic data across providers, it is now possible to link different data sources, which allows complex research questions to be addressed. Insight Center Innovating for Value in Health Care Sponsored by Medtronic Exploring cutting edge ways to lower costs and improve quality. For example, the analysis of comprehensive EHR patient data collected in real time during doctor or hospital visits provides an opportunity to better understand diseases, treatment patterns, and clinical outcomes in an uncontrolled, real-world setting. These valuable insights complement those gained from clinical trials and can provide an opportunity to assess a wider spectrum of patients that are traditionally excluded from clinical trials (e.g., elderly, frail, or immobile patients, as well as people with rare indications and diseases not yet studied in clinical trials). It also allows companies to assess real-world challenges that cannot be observed in a clinical trial, such as drug compliance and the utilization of health care resources. While these advances are generating great opportunities, they also pose resourcing and capability development challenges. One of the biggest is how to make the transition from legacy technology and analytical competence to more-powerful and sophisticated analytical tools and analysis methodologies. Historically, the pharmaceutical industry has recruited SAS programmers who have executed well-defined analyses of clinical trials in a standardized, efficient manner. This worked well, given that clinical trials have been designed to answer questions about efficacy and safety with clean data sets in an industry-standard structure with few missing values. But real-world data comes in a variety of different formats, is often highly unstructured (containing textual and other nonnumeric data), and is rife with missing values. It is messy data, filled with inconsistencies, potential biases, and noise. These attributes force data scientists to find creative ways to answer critical research questions to support drug research and development and ultimately to provide patients with access to the right therapies. Consequently, there is an emerging need for analysts and data scientists who can take full advantage of tools and techniques developed in Silicon Valley that are capable of handling noisy data and presenting results to stakeholders in a simple, easy-to-interpret way. These analysts must be able to deal with ambiguity and be collaborative, entrepreneurial, and adaptive in their approaches. They must be able to apply “options thinking” to figure out what questions to ask, what data to examine, and what methodologies and technologies to use to address the aim. They must also have a deep knowledge of the health care system, including its standard practices, in order to understand how the data was originally collected, what biases may exist, and how it can be repurposed to answer clinical research questions. Genentech, which is owned by F. Hoffmann-La Roche, has been building such capability for two years. In addition to investing in data partnerships and analytics tools, it has built a big-data infrastructure — a platform that can analyze billions of patient records in seconds. It has been aggressively recruiting and developing people with the requisite skills, partnering with universities and firms such as The Data Incubator to recruit and train data scientists, and it now has an entrepreneurial global team of more than 80. A recent example of the kind of work it conducts is the creation of a database on a historical cohort of real-world patients previously diagnosed with cancer. The team analyzed their data to understand the outcomes of different patient subtypes and treatment regimens. This helped Genentech learn how different biomarker alterations and different treatment patterns affect clinical outcomes in the real world. This information will ultimately support critical drug development decisions. Genentech is also utilizing real-world data in other therapeutic areas, such as neuroscience, where drug development is notoriously challenging, in order to better understand the variability of disease patterns, progression rates, and treatment responses, and to quantify cost dynamics as diseases advance. It will not be easy to learn how to tap the full potential of real-world data. But it can be done. The potential to use that data to improve drug discovery and get the right treatments to the right patients at the right time is enormous.
Scientific efforts to find cures for cancer will be severely hampered if the scientific community does not change the ways in which patient data is collected, shared, and analyzed. The development of targeted therapies and immunotherapies — the two biggest hopes for cancer cures — depend on the existence of large data sets comprising patients’ genetic and clinical information. Today, that data is fragmented and guarded in silos. Indeed, the well-kept secret in the cancer space is that progress in finding cures is being impeded as much by the lack of sharing by the players in the precision medicine ecosystem as it is by the stubbornness of the underlying science. With about 20,000 genes and a total of 3 billion base pairs, finding the mutations responsible for a particular cancer is a daunting task. The larger the sets of data that contain the genomes of numerous patients, the higher the chances of finding deviations that are statistically significant. Only after this can the scientists begin their work of developing targeted therapies to overcome the effects of the mutated genes. This is where the cancer ecosystem comes into play. Today, the clinical and genetic information of cancer patients is held in a variety of places: academic medical centers, community hospitals, disease-specific foundations, pharmaceutical companies, and the government. There is very little sharing of data among these institutions. Insight Center Innovating for Value in Health Care Sponsored by Medtronic Exploring cutting edge ways to lower costs and improve quality. Let’s begin with the academic medical centers, which are the most likely to collect genetic information on their patients. (Many of them are sequencing the genomes of all of their cancer patients.) The reasons they don’t share data lies in the nature of academic medicine. Doctors in academic centers are promoted for their research. Having exclusive use of their own data is crucial for gaining credit for research and obtaining grant money. Add to this the fact that many academic centers often cover the expenses of sequencing the genomes of their cancer patients themselves and you can understand their reluctance to share data. The motivations of the pharmaceutical companies are similar: Why share data that may be critical to obtaining exclusive, patentable breakthroughs? The community hospitals, which treat over 70% of all cancer patients, have vast amounts of clinical data but historically have not sequenced many of their patients. Similarly, the disease-specific foundations, whose interests are most aligned with those of patients, typically do not collect genomic data of their constituents. The few who do incur significant costs. For example, the Multiple Myeloma Research Foundation spent over $40 million to collect genomic and clinical information on 1,200 multiple myeloma patients throughout their experience with the disease. The foundation has been exemplary in this regard, and its work over the past 20 years has been instrumental in leading to the development of 10 new drugs for treating multiple myeloma that have helped to triple the life expectancy of newly diagnosed patients. But there are roughly 100,000 multiple myeloma patients and only about 20% are involved with the foundation. The data of the other 80% resides in numerous silos. What is needed is to reshape the precision medicine ecosystem into one in which data is regularly shared and large data sets are stored in open-access portals available to researchers around the world. The opportunities for patentable discoveries will still exist and will actually be enhanced by the larger data sets, and most important, patients will be helped by the more rapid discovery of desperately needed therapies. Fortunately, some efforts to reform the ecosystem are underway. Some are being spearheaded by the U.S. government both in the Obama administration’s Precision Medicine Initiative, which aims to collect genetic information of 1 million individuals, as well as Vice President Joe Biden’s Cancer Moonshot initiative. But there are also important private initiatives: the Genomic Data Commons out of the University of Chicago, the Collaborative Cancer Cloud launched by Intel and Oregon Health & Science University, and the Oncology Research information Exchange (ORIEN) — all of which are collecting data from multiple sources, normalizing it, and beginning to make it available in an open-access manner. To give just one example, both the Multiple Myeloma Research Foundation and Flatiron Health have deposited their data on the Genomic Data Commons, thus doubling the size of the data available on multiple myeloma. While all these efforts are commendable, much more needs to be done. Indeed, one of the primary objectives of the recently launched Harvard Business School Kraft Precision Medicine Accelerator, which we cochair, is to make the broader health community aware of the existing efforts to increase the sharing of data and to get more institutions to join them. Toward that end, we encourage business leaders, many of whom serve on the boards of hospitals and medical foundations, to insist that these organizations start making their patient data available to the broader research community. The HBS Kraft Accelerator also hopes to enlist patients in the cause. They can play a lead role in bringing about these changes. Today, there is little patient awareness of how critical it is to have their cancer tissue genetically sequenced and to have their clinical and genomic data released for inclusion in larger databases. Doing so would not only aid new drug discovery but would also help patients know which treatment approaches are most likely to be effective and which clinical trials are targeted to their specific mutations. Of course, privacy safeguards need to be put in place. While it is generally unknown, all of us have the right under HIPAA regulations to request that our medical records be released in anonymized form for research purposes. Unfortunately, few providers make their patients aware of this right. There is a glaring need for patients to be made aware of this. This is one of the main goals of the HBS Kraft Accelerator. Efforts like these are likely to improve the ways the members of the precision medicine ecosystem cooperate. But for patients like the two of us — one a survivor of a curable cancer and the other living with a cancer for which there still is no cure — time is of the essence. Accelerating the pace of change is something all of us can help accomplish.
Organizational transformation is notoriously difficult. Twenty years ago, John Kotter pegged the failure rate at 70% and the needle hasn’t moved much since. Major change also takes a long time to implement — between five and seven years on average — and the performance improvements that are achieved rarely last. In healthcare, change is even harder than in most industries. Clinical and administrative staff often view their work as a vocation as much as a profession, and they are historically suspicious of senior administrators and resistant to strategic agendas. While a desperate need for change and organizational performance improvement may be obvious to the top team, staff can view that premise as fundamentally flawed. They’ve lived through tumultuous times before and the status quo has always returned. Insight Center Innovating for Value in Health Care Sponsored by Medtronic Exploring cutting edge ways to lower costs and improve quality. In 2011, when I came to Centura Health in Colorado as President of its largest operating group (Mountains and North Denver Operating Group or MNDOG) and CEO of its flagship health organization, Saint Anthony Hospital, I saw a clear mandate for change. The organization had a strong community tradition and over 4,500 talented employees. Yet, a variety of financial and operational problems impeded success and we lacked a clear strategic path toward building the kind of coordinated care delivery system healthcare desperately needs. I put my immediate energies toward building an exceptionally strong executive team. Together we developed an agenda for change and put it into action. Within a few years, we had dramatically turned around the organization’s finances, performance measures, and market share. Things were looking up on all fronts except one. Our employees weren’t along for the ride. This is the story of what we did to turn that around by involving our people in our organizational change process in a much deeper and more meaningful way. Doing so, we stumbled across a formula for accelerating organizational objectives while managing even higher levels of performance and engagement. Rounding and listening “I have hope that you are actually listening to associates now.” Out of more than 500 responses, that was the one that hit me hardest. We performed pulse surveys quarterly after every town hall meeting at Saint Anthony Hospital. The questions were developed by Press Ganey, the healthcare survey company, and were related to employee engagement. We also had open questions in our surveys to give people an opportunity to express their concerns related to leadership, operations, compensation, and staffing. The feedback could be tough at times. Though we’d achieved significant organizational change and performance improvement in a very complex and challenging industry and market, it was clear that our employees didn’t feel included on the journey or excited about our accomplishments. The disconnect between how they felt about our organization and how the organization was actually performing was perplexing. To dig into the details, I engaged in a hospital tradition and began rounding. I talked with clinical, administrative, and operational staff where they worked and asked them to tell me more. I learned that people didn’t feel connected to our vision or the changes we were working to make. Our goal was to become the destination healthcare provider in our market while achieving national standards for best practices, care quality and satisfaction, and becoming recognized as a health leader in the communities we serve. Most of our employees’ concerns were far more basic. They were worried about working conditions, managerial support, staffing levels, and so forth, and they believed that leadership was just talking out of its hat because we had failed to address their long-term concerns. Listening and taking notes, I knew I could solve almost everything and still not fix the bigger problem of connection and engagement. There was a lack of trust in us and alignment with our agenda. Years of experiences with administrators saying one thing and doing another had made people cynical. Hearts and minds would need to be changed in a fundamental way. So I did what CEOs often do when they confront a maze they might get lost in – I called for help and asked an executive advisor and organizational change expert for guidance. I’d worked with organizational change consultant Phil Harkins at a number of different health systems before, including Centura, and he understood our situation acutely. He proposed that we try something new. Unlocking the power of purpose through teams We’d already collaborated to develop the cohesion of my top executive team by clarifying each executive’s individual purpose and connecting that to the shared purpose of the group. For example, my chief strategist and one of our hospital CEOs were both passionate leaders who cared deeply about improving our system but they were always on opposite sides of key organizational and strategic issues. By getting them to dig deep and talk about their own personal motivations, it became obvious that they actually shared the same overall vision. This helped them to identify what they each wanted to do to contribute to our larger agenda and helped us define their distinct roles and responsibilities more clearly. That sort of work had a remarkable effect on bringing leadership together, helping us to communicate with each other more openly and candidly, and making it faster and easier for us to innovate and execute. We decided to expand that approach to the entire organization. But how do you make something like that happen at scale? Purpose is not a canned or artificial HR program. Discovering it is deeply personal and almost therapeutic. You can’t fake it or force it. Through Phil’s research and our experience, we knew that it was best engendered within the close environment of a cohesive team. When close peers face high stakes, real problems and interpersonal challenges, the work of discovering and sharing purpose seems to galvanize their sense of team almost magically. We decided to implement a similar process among other teams, and then cascade that throughout the organization. We started by identifying the “passionate champions” of the organization, meaning people who are particularly committed to healthcare, problem solving, and each other. Then we selected 50 of these people and divided them into four model teams. Next, we set these teams to work on defined areas of organizational need – Quality, Clinical Operations, Administrative Operations, and Associate Engagement. Each of these teams went through the same team development program as my senior leadership team. We helped team members identify their individual purpose and connect that to the organization’s overall purpose. For example, one front-line nurse was incredibly dedicated to patient satisfaction. Joining the Quality team gave her a way to bring her personal perspective on best approaches to patient care to that group and helped her to see how directly her individual efforts could contribute to our larger goal. Next, we gave these teams the freedom to identify organizational problems in their area of concern. The Clinical Operations team focused on “throughput” bottlenecks in order to improve how efficiently patients could be moved through the system from intake to discharge. This efficiency is a key driver of operational costs but also a leading indicator of patient satisfaction and quality since prompt discharge means clinical best practices are being applied and quality outcomes achieved. Our Clinical Operations team was composed of nine people who represented every area of the hospital that touched throughput, from the ER to the wards to pharmacy and administration. Whereas before they might have seen their roles as siloed from one another, now they worked collaboratively to solve bottleneck issues across the system. Sometimes this work surfaced tensions so it was important to facilitate and coach people through their conflicting points of view. Team members who were initially at odds were always able to reach a collaborative solution because they had spent time getting to know each other and they understood that everyone shared the same priorities around improving patient care. The vulnerability and openness the team-building process established made it easier to get aligned. Once each team had figured out a solution to whatever problem they identified, we recused some of the members and replaced them with other “passionate champions” closer to the field. This new group became the implementation team charged with executing on the strategy. The original team members who remained were responsible for bringing new team members through the team-building process. The team members who were recused were assigned to new teams where they also helped lead and develop team cohesion in those new groups. Many people were reluctant to leave the teams they’d helped build. Team members had grown close and wanted to stick together. But by dispersing them to other teams, we created a process of leaders teaching leaders that cascaded throughout the organization, with increasing numbers of people aligned around a shared purpose and focused on solving meaningful challenges. Our focus on meaningful problems was critical. Many “team-building” exercises are theoretical and the stakes are low. Our approach engaged people on developing tangible solutions that would contribute to our vision. It reinforced alignment, helped build our capabilities and led to actual improvements in organizational performance. In the end, it felt as though we had 50 new leaders helping to run the organization. Picking up speed and measuring progress Not everyone was touched by the work right away, but the network effect was powerful. I was amazed by the level of commitment and passion that grew throughout the organization. We moved faster and made more significant progress because we combined the power of purpose with project work that was designed to improve organizational performance. We made sure to track and measure progress and status frequently. We measured each team’s performance and development at regular intervals through Phil’s Team Effectiveness Assessment (TEA) instrument, a 360 system that tracks, reinforces and bolsters team norms and best practices. We also measured operational metrics like quality, safety, satisfaction and financial scores to gauge our progress compared to national standards of excellence. And we continued to take the temperature of the organization by conducting surveys on employee engagement and culture. Measuring in three areas helped us to avoid letting personal experiences or perspectives cloud our judgement of how well we were doing as an organization. We also kept rounding and conducting listening forums and town halls to make sure we surfaced and were aware of every concern. The rich understanding that we developed enabled us to employ very crisp and targeted responses to problems and concerns that were tied to our strategic priorities. For example, we changed our leadership when it did not reinforce or align with our vision and new approach. We also altered our staffing approach and increased compensation in select areas to improve performance. Leading in a new way For the top executive group, the work of being a leader also transformed. The approach we put in place forced us to listen and learn how to support people rather than dictate or direct them. We became actively engaged in collaborating with our people as they worked to solve the problems of the organization. Sometimes we were coaches, sometimes mentors, sometimes facilitators. In this way, we modeled a new type of leadership, closer to the kind of servant leadership approach I’ve always admired. In breaking out of our own administrative silo, however, we were also very visible and open to scrutiny. We knew that cynicism in employee ranks was long-standing and any time we fell short we would be reinforcing old perspectives. So we articulated our promises clearly – even writing them down in memos – and we matched those to outcomes that people could observe and track, thereby linking what we said with what we did. Within our leadership group, we also defined new behaviors that would support our new approach to leadership and I took it on myself to continue to observe and coach our team to stay on track. Through this experience, I came to understand why traditional change agendas often fail to really move the needle. When change is imposed, active and passive resistance assures that it will never be a complete success because resentments never fully dissipate and engagement is lacking. There’s a better way. We shifted from a top down approach to a transformational one by involving as many people as possible as early as possible. We managed this by creating a cultural practice in which teams defined their purpose and objectives, and leaders taught others how to grow and lead. Some CEOs might worry that ceding a change agenda to multiple teams throughout an organization is a recipe for confusion, misalignment and a slower pace of change. But when people are aligned around shared purpose and engaged in real problem solving within a strong team environment, they achieve overall goals and change objectives much faster and more effectively. Not only does this bring leadership and engagement to a new level, but organizational culture is also stronger and more dynamic as a result. Sustaining change is a lot easier when those conditions are in place.
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Американские фондовые индексы вторую сессию подряд обновили исторические максимумы во вторник, при этом Dow Jones Industrial Average впервые в истории превысил отметку в 19 тыс. пунктов, а Standard & Poor's 500 взял отметку в 2,2 тыс. пунктов.
Medtronic plc's (MDT) second-quarter fiscal 2017 adjusted earnings per share (EPS) came in at $1.12.
Американские фондовые индексы поднимаются в начале торгов во вторник, обновляя исторические максимумы, при этом Dow Jones Industrial Average впервые в истории превысил отметку в 19 тыс. пунктов, а Standard & Poor's 500 взял отметку в 2200 пунктов.
Medtronic reported second quarter 2017 earnings with its adjusted EPS beating the Zacks Consensus Estimate, while revenues missing the same.