Question

Looking ahead to 2020, pick one area of the current National Patient Safety Goals program and make a prediction of what might change in that area based on technological or other advancements. Consider patient identification standards, communication processes, and infection control protocols, among others.

You are required to use and cite a minimum of two references to support your response.

Answer 1

Patient safety was defined by the IOM as “the prevention of harm to patients.” 1. Emphasis is placed on the system of care delivery that (1) prevents errors; (2) learns from the errors that do occur; and (3) is built on a culture of safety that involves health care professionals, organizations, and patients.

The Joint Commission established its National Patient Safety Goals (NPSGs) program in 2002; the first set of NPSGs was effective January 1, 2003. The NPSGs were established to help accredited organizations address specific areas of concern in regard to patient safety.

Development of the Goals
A panel of widely recognized patient safety experts advise The Joint Commission on the development and updating of NPSGs. This panel, called the Patient Safety Advisory Group, is composed of nurses, physicians, pharmacists, risk managers, clinical engineers and other professionals who have hands-on experience in addressing patient safety issues in a wide variety of health care settings. The Patient Safety Advisory Group works with Joint Commission staff to identify emerging patient safety issues, and advises The Joint Commission on how to address those issues in NPSGs, Sentinel Event Alerts, standards and survey processes, performance measures, educational materials, and Center for Transforming Healthcare projects. Following a solicitation of input from practitioners, provider organizations, purchasers, consumer groups and other stakeholders, The Joint Commission determines the highest priority patient safety issues and how best to address them. The Joint Commission also determines whether a goal is applicable to a specific accreditation program and, if so, tailors the goal to be program-specific.

National Patient Safety Goals are a series of specific actions that accredited organizations are required to take in order to prevent medical errors such as miscommunication among caregivers, unsafe use of infusion pumps, and medication mix-ups.

The purpose of the National Patient Safety Goals is to improve patient safety. The goals focus on problems in health care safety and how to solve them. This is an easy-to-read document. It has been created for the public.

Historically, knowledge acquisition has been considered the essential ingredient for ensuring highly qualified clinicians and safe, high quality medical care. However, over time it has become abundantly clear that knowing the right thing to do and doing the right thing (i.e., performance) do not necessarily go hand-in-hand. The old adage of “see one, do one, teach one” tended to minimize the indispensable role of skilled performance and practice. While patients certainly want highly knowledgeable clinicians, they also expect their health systems to perform on par with the Nation’s better run organizations. Hence, there is an increasing focus on performance and the skilled use of tools in support of the optimal delivery of care.

As medicine has moved from the independent solo practitioner, low tech model involving long hospital stays to a high tech, complex, systems-based model reflecting increased use of specialists, shorter hospital stays, limited work hours, multiple hand-offs, and growing use of non-hospital settings, it has become ever more apparent that health care delivery in today’s environment requires excellent teamwork and communication skills. The performance-based component of clinical competency is further illustrated in the set of papers that focus on simulation. Given advances in medical simulation technology, a lowering of associated costs, and a national spotlight on patient safety, the recent growth of simulation centers in schools of medicine and nursing, and its increasing migration as a training tool to other clinical settings, is indeed impressive. Just as other hazardous environments—e.g., aviation, military operations, disaster preparedness—have reduced the risk of achieving high levels of individual, team, and system performance using simulation, so too are health care practitioners finding a diverse range of application involving simulation. The authors in this section describe their efforts in using various forms of simulation to improve proficiency, reinforce behaviors, and identify both individual and systems issues in a range of environments and settings. The use of in situ techniques—i.e., bringing the simulation on site to the place of patient care—is quite evident.

Physicians, nurses, pharmacists, technicians, and other health care professionals must coordinate their activities to make patient care safe and efficient. Health care workers perform interdependent tasks while functioning in specific roles and sharing the common goals of quality and safety in care. However, even though the delivery of care requires teamwork, members of these teams are rarely trained together; they often come from separate disciplines and diverse educational programs. Given the interdisciplinary nature of the work and the necessity for cooperation amongst those who perform it, teamwork is critical to ensure patient safety. Teams make fewer mistakes than individuals, especially when each team member knows his or her responsibilities, as well as the responsibilities of other team members.

Key motivators for change
“With the steady move toward value-based care, there continues to be convergence among health care sectors and further development of a continuum of care within health care companies. Parties that have historically been separate, such as managed care and providers — or subsectors within the provider universe — are coming together in different ways.” While there are many strategies and motivations, a few themes emerge that point toward strategic reasons behind M&A activity. Bolstered by cheap financing and spurred by the opportunities that big data might offer, these include:

1. The evolution toward value-based reimbursement from volume-based payments — forcing a focus on the full spectrum of care. Organizations seek to better manage risk if they are paid based on patient outcomes, yet provide only part of the continuum of care. Further, these reimbursement models require more results tracking, and health organizations need to effectively adopt and employ digital technology and analytics.

2. The move toward consumer-directed health care — adding an incentive for technology and wearables. To ride the rising tide of consumerism, organizations must incentivize customers to use new technologies and services and share the resulting data.

3. The traditional consolidation drivers of increasing market presence and reducing costs — to reduce the cost of care and increase efficiency. Cost pressures are intense, and organizations must continually improve operational efficiency and effectiveness while also reducing overall and per capita costs.

4. The shift from inpatient to outpatient care — to reduce the cost of care and increase efficiency. Hospitals are challenged to carry on the traditional mode of inpatient care. As reimbursements drop for inpatient services, many are spurred to focus on other avenues for growth, particularly outpatient services. Outpatient care is often delivered at lower cost sites, and outpatient volumes have accelerated at a faster pace than inpatient admissions over the past five years. This scenario is advantageous to larger health services providers with more developed outpatient networks, especially when compared with single facilities or smaller hospitals. The cost factor is driving established hospital operators to seek M&A opportunities outside of the scope of the traditional acute care hospital, such as buying smaller community hospitals to develop regional networks or setting up acute care outpatient surgical sites.

5. Scale up or consolidate — to better spread the cost of overhead and to offer a wider range of services along the care spectrum. Driven in part by health reform, cost pressures on health providers encourage an increase in scale, and the reporting requirements demand a more complex and robust technology infrastructure. Here, larger players will have an advantage, with more overhead dollars to fund IT and clinical systems, improve purchasing contracts, negotiate better deals with large commercial insurers and enhance organizational capabilities. Effects we see in the market include:
• Larger hospital and managed care operators acquiring smaller hospitals, taking advantage of the scale and scope to further reduce their cost per patient. The same is true for managed care operators (MCOs), which continue to pursue strategic acquisitions as actively as regulatory approval allows. Last year produced the proposed megamergers of Aetna-Humana and Anthem-Cigna (pending government approval), and large regional MCOs, such as Kaiser Permanente and other MCOs, are bulking up through acquisitions.
• Regional consolidation of hospital operators, to achieve scale and scope to drive down the cost per patient. One example is Detroit-based Henry Ford Health System’s acquisition of Allegiance Health, a dominant provider in Jackson, Michigan.
• “Super physician” practice groups, combining to form behemoth practices to achieve scale and market concentration. An example is the recent merger of equals between Envision Healthcare and Amsurg, creating a large physician group.

6. A focus on technology, tools and digital devices — to track required outcomes and leverage analytics to increase operational and patient effectiveness. Health care-related information technology continues to grow, in part buoyed by government policies and requirements. Although lagging other industries, health organizations are increasingly adopting IT solutions to help simplify and streamline their operations, and technology is often a big factor in M&A activity and decisionmaking. Hospitals, health organizations, individuals or small practices unable (or unwilling) to provide the required capital outlay for electronic health record (EHR) systems are seeking to bridge the gap, either through partnerships, mergers or acquiring technology companies outright. Those with robust EHRs are looking to boost their scale as a way to maximize value from those investments. And all are focused on technology as a tool to help find efficiencies in operational processes, enhance clinical decision support systems for providers and bolster patient engagement (by encouraging patients to access and use portals, for example). Hospitals are also starting to link their EHR data directly to administrative and billings functions, not only to streamline and automate the revenue cycle but also to gather data for analysis of operational and care flows and ready their organizations for value-based reimbursement.

7. Move toward investment in less risky segments of health — to count on better, more stable reimbursement. Health organizations, especially those privately owned or funded by private equity investors, are diversifying their services and acquiring providers in niche segments in an effort to smooth or manage overall risk. Niche organizations sought for acquisition or alliances are attractive because of the lower reimbursement risk and include:
• Physiotherapy – Physicians with orthopedic practices and others are looking to purchase or partner with these organizations to improve the outcomes of orthopedic and other procedures and/or reduce the incidence of surgeries.
• Behavioral care – This large, often overlooked market is facing growing support, as both the regulatory and legislative sides seek to provide better mental health coverage for adult Medicaid beneficiaries. These moves bode favorably for behavioral care providers.
• Home health and hospice – Demographics, patient preference and meaningful cost advantages suggest more growth in the home health and hospice arena, as the percentage of Americans 65+ is expected to grow from 13% to 20% of the population by 2030.2.5 Industry analysts also point out that those focusing on quality are likely to benefit as the Centers for Medicare & Medicaid Services continues to move toward outcome-based reimbursement.
• Ancillary health care services – This includes revenue cycle management businesses, independent specialty providers (such as neonatal, anesthesia, teleradiology, maternal-fetal and pediatric physician services) and independent medical examiners.
• Niche segments – These include dental care, dermatology and veterinary services, all of which are off the radar for most traditional health organizations.

Putting people at the center of health analytics
Today’s artificial intelligence (AI) technologies are, well, not that intelligent on their own. Although AI tools are progressing at an incredible rate, the real power emerges when the data analytics augment human decisionmaking rather than replace it. The analytics alone are just not smart enough to derive true insight. Identifying health trends means pairing AI and analytics with supervised, human learning. Imagine a future world where the analytics look at a patient’s specific gender, age, lifestyle, medical history, family background and geography and indicate a high risk of diabetes. To prevent the full onset of the disease, the patient uses a wearable app to regularly monitor blood glucose levels. When it rises, the device sends the physician a text, the physician makes a decision around the medication needed, and the patient is alerted to take a specific amount of oral medicine to reduce the amount of sugar made by the liver. Diabetes averted. With the capabilities of technology, wearable apps and data growing exponentially each year. But the key is the crucial interaction and “dialogue” between the data, technology and people. This reality requires an active level of human judgment and decision-making, informed by the analytics. Perhaps the best example of the gap that needs to be filled is represented by Google Flu Trends. When it first appeared, its ability to spot flu outbreaks weeks ahead of traditional methods, by analyzing search engine queries about symptoms, was hailed as a breakthrough. The algorithm didn’t distinguish between someone who had the symptoms and someone who was merely asking about the symptoms. With such a vast amount of data, the volume of false data became so great as to render the findings almost meaningless.

True data disruption requires human interpretation
We are facing an explosion of data, coming from every corner of the health industry across the globe, from a dizzying array of sources — audio, video, geospatial, telemetric and sensor data, electronic health records, payer claims data and real-time information generated by mobile health technologies. Computing power is now available at dramatically reduced costs, adding enormous new capabilities to the equation and making analytics more financially feasible. Google Flu Trends example, the sheer unprecedented volume and affordable accessibility of data are not in itself a disruptive force. What is disruptive — and even revolutionary — is the ability to put the data together, creating linkages among and between large data sets and data types to truly uncover patterns, trends and insights heretofore unseen. The right combination of smart algorithms and people could help reduce or even eliminate chronic diseases. It could help reduce cases of post-operative infection to a vanishing point. And it could point with confidence toward medicines and treatments that dramatically increase the efficacy among specific populations of people.
The key is strategy, leadership and people. “This disruption from advances in technology and advanced analytics offers a profound opportunity for the health industry,”. “If organizations truly put data and analytics at the center of their operations, the collective power of the data could utterly transform health care — and save lives. But getting there will not be easy. It is usually more difficult to transform a large, mature organization than it is to build something completely new.” The starting point Let’s start with where the health industry is now compared with other industries. The chart below shows health care close to the middle, with room to grow in terms of both analytics production and consumption. Combined with the almost incomprehensible projections for growth in health data to 2.3 zettabytes (2.3 trillion billion gigabytes) by 2020, working fast — and working now — to find the right combination of human decision-making with smart algorithms is both an opportunity and a mandate. The road ahead begins with your destination Before you begin any journey, it’s important to know where you’re going. The end purpose of data and analytics is to advance the health outcomes and experiences for patients and to provide organizations with new insights to make better operational decisions. Analytics requires having good data, but the value only comes with the behavioral alignment required to “consume” the results — moving from collection to insights to action. These insights could help with:
• Organizational decision-making to better understand the patients, outcomes, delivery mechanisms, services offered and operational structures, and service positioning and operations
• Individual decision-making, enabling and empowering employees at all levels and locations throughout the organization to improve the results for the organization and for patient outcomes and experiences
• Decisions on the collective, which in the health arena means profound insights into treating chronic disease and the potential for precision, customized medicine

Three steps toward powerful data insights
Insights are most valuable when they are the result of data that is accurate and carefully curated, generated by humansupervised algorithms and part of a clear process that defines how analyses are used to inform decisions. Many health organizations are struggling to transform into analytics-driven enterprises and derive value from their data analytics. How do organizations move from current to future state as quickly as possible? It requires a focus on three things:
1. A strategy: Without a strategic approach providing high-level guidance, analytics efforts are rudderless. “We see many organizations that have spun up initiatives and are spending a lot of money, yet don’t necessarily have a clear point of view on how value will be delivered,”.
2. A good structure: “In the earlier stages of analytics, organizations tend to have disparate, siloed efforts dotted all over the place, without much control, and with potential duplication and inefficiency,”, EY Global Business Modelling Leader. “One part of the organization may produce great insights, but they will not be leveraged elsewhere.”
3. People: “Data and analytics are as much an art as they are a science. A successful data and analytics environment doesn’t depend on technology alone to deliver
the right insights at the right time. “It requires a human capital strategy, with leadership coming from the top, and with employees at all levels buying into the effort.”

The people are the center Data and analytics could move health organizations in entirely new, innovative directions, change operational infrastructures, have a profound impact on chronic disease and patient outcomes, and change the way organizations think about health and patient care, opening new opportunities and providing new and powerful insights. However, these insights will only become a reality if people are at the center of the equation, curating the data, managing the algorithms and finding ways to translate the insights into practical use. organizations need to put more focus on understanding the current state of their return on analytics investment: what is working and what the barriers are to improving. “It’s the combination of people, process and technology that converge to create value,”. “And, often, the bottleneck is not data, technology or even advanced analytics skill sets. It’s a question of, once we have the insights from the analytics, what are we doing with those insights? That last mile is often the most difficult.” Realizing business value in data and analytics depends on getting the human element right. Strategy is only as good as its execution, and successful execution of insights from analytics happens individual by individual. Ultimately, data and analytics will drive most health care decision-making and augment — but not replace — human judgment. At the end of the day, most analytics uses still require a human being to do something different, such as change a business process or decision they would have otherwise made.