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The authors are knowledgeable experts and well-known for their books. They accomplish the goal of providing an intermediary work that is comprehensive covering material beyond an introductory level but is not burdensome and can be easily read and interpreted by college and university students. Features: The book covers the U. It divides this subject into broad themes and separates the chapters accordingly.
The first section covers the basis of the current system.
The historical perspectives provided in this section are invaluable, but weak. The second section covers the necessary resources to support the healthcare system, then the process of healthcare, taking readers through the system.
Finally, a section covers the outcomes of healthcare. Main Takeaways from Essentials of The US Healthcare System Cost, access, quality — 3 components to measure effectiveness of a health care system These are often conflicting.
Increasing access to more patients will increase total costs. Forcibly decreasing cost may decrease quality or access. Cost is a function of price x quantity.
Price is easier because quantity risks backlash re: rationing Access is a lower class, liberal, social justice problem. Also, restricting access to high tech healthcare leads to claims of rationing. Quality is difficult to define and is in the eye of the beholder patient vs provider vs payer have different conceptions of quality.
Each side finds the other incomprehensible Determinants of individual health — lifestyle, environmental, heredity, medical access Brief history of US healthcare Healthcare began as unscientific and haphazard, practiced by barbers, clergy, and family members.
Hospitals became community-owned institutions supported by private charitable donations, starting the dominant trend today of private nonprofit hospitals.
As science improved and medicine gained legitimacy anesthesia, germ theory, sterilization , people began paying out of pocket, and hospitals realized they could make profits. Hospitals became centers of research affiliated with universities. However, ICDs are now part of the culture in electrophysiology. Even so, to some extent the data on benefits lag behind usage, particularly in subgroups such as elderly people and women Lin et al.
PCIs show similar trends. There is tremendous geographic variation in the use of PCI. We have done some work in collaboration with colleagues at Dartmouth looking at the use of PCI across the country and documenting its appropriate use. As one might expect, we found a great deal of geographic variation and data suggesting that much PCI use is actually inappropriate, or there was no documentation of ischemia prior to its use.
A key point of this paper, therefore, is that technology use often goes far beyond what the data show with respect to patient benefit. For example, it is estimated that more than one-third of all CT scans are unnecessary.
Therefore, it is easy to discern a great deal of inefficiency in the system. The implication is that there is room for improvement in our culture, our practice, and our delivery of health care. A major step would be to begin more systematic data collection and to develop more prospective registries, such as the National Cardiovascular Data Registry at the ACC.
Kaiser has large registries. More systematic data collection and analysis would lead to better-informed decisions.
More randomized controlled trials—which will require more funding—is in order, as is the development of more observational data. It is important that these data be gathered, analyzed, and incorporated into practice guidelines and reimbursement. Changing practice patterns is much more difficult after they have been established, even with the introduction of new evidence.
In addition, all these data must be more widely available. Currently, it can be very difficult to access large databases. More transparency is needed for these kinds of data. Finally, there must be more consistent review of the evidence for clinical benefit prior to the routine use of new technologies.
A change of culture is needed in this regard so that a technology does not see widespread adoption before the evidence review is complete. This is one crucial way to concentrate healthcare spending so that it yields the greatest possible benefit in actually improving health outcomes.
Once a technology has been widely adopted, curtailing its use is extremely difficult, and there are many examples of this point in our healthcare system. The healthcare system could benefit from a systems engineering approach whereby data collection and review are incorporated into the practice of medicine; the data collection is accessible, easily performed, and inexpensive; and with rapid turnaround, the data can be examined quickly. It is essential to align incentives and reward evidence-driven care.
Too few practices and hospitals use electronic medical records EMRs , and usability issues remain. Existing data standards are used inconsistently, as are interoperability standards. Thus the information needs of patients, physicians and care teams, organizations, and the healthcare system as a whole are not being met. Privacy and security concerns persist. More important, the culture of health care presents barriers to the effective use of the data and information. From a process perspective, the complexity of health care has dramatically increased.
More people have chronic disease, more have multiple chronic diseases, and the treatments and technologies available have increased. In response to this increased complexity, health care has not taken full advantage of engineering principles that can be used to deal with complex processes. The healthcare environment, with its structure and financing, adds considerably to the barriers. The above issues limit the effectiveness of clinical decision support.
To create a more effective learning healthcare system, the healthcare establishment will need to direct more attention to various areas, including the people and culture, the processes, the data and technology, and the healthcare environment.
Integrated delivery systems are well positioned to address these areas and can serve as a model for those that deliver care outside of such systems.
Much work remains, however, before a learning healthcare system can be fully realized throughout the United States. The study found a blood pressure control rate of 95 percent, significantly better than what is usually seen.
The editorial suggested that the system described in the paper provided a hint as to how electronic data systems may hold the key to achieving better blood pressure control in the future. It read: For a moment, imagine you live in a world in which an integrated EMR system was the standard in most community practices … the blood pressure trajectories of hypertensive patients could be easily tracked … feedback reports could then quickly update busy caregivers regarding which of their patients fell short of treatment goals and needed closer follow-up.
And as an intervention, such data could be used to provide various incentives for meeting blood pressure control goals. Peterson, The purpose of this paper is to identify some of the barriers to fully realizing such a vision of a learning healthcare system and to discuss how they might be overcome. The barriers to synthesizing and using information to support enhanced care delivery can be viewed in terms of four broad categories: people and culture, process, data and technology, and the healthcare environment.
Challenges from the people standpoint include the prevailing culture of health care with its hierarchical, often physician-centric, and slow-to-evolve team-based approach to care. The clinical leadership needed to address the larger issues in health care is often lacking and not adequately fostered and valued.
The skills and training required to use technology and information systems, as well as team skills, need further development. With respect to the process of care, health care has grown in complexity, thanks in part to its complex workflows. One of the major purposes of this workshop is to highlight the underuse of tools that could be adopted from engineering, particularly as they apply to complex systems, such as tools for system design, analysis, and control. Because of the culture and structure of health care, an end-to-end, patient-centered view of the process is often lacking.
Care is viewed at the departmental level or from a disciplines frame of reference, as opposed to a continuous view of the care process. As a result, problems with transitions of care between departments or venues of care are magnified. The healthcare industry lags behind other industries in how information technology is used.
Clinical information systems often are not integrated. Data are locked away in various applications, often still on paper, and in various databases. This lack of integration occurs even within organizations; it is far worse across organizations. Data standards and interoperability standards are used inconsistently. Usability issues remain, and there is continued concern about privacy and security issues.
Finally, the healthcare system in the United States presents significant barriers. Most primary care is delivered by relatively small practices, and most specialty care is delivered by individual departments with, as noted above, a lack integration among the various care venues. Healthcare financing and reimbursement reinforce this fragmented care.
In considering what is required to provide clinical decision support that will enhance the care delivered to patients, one needs to take into account both an individual patient-centered view and a population view. Accomplishing this requires getting the right information to the right team member at the right time in the workflow or the decision-making process so as to trigger the right event for the care of an individual patient as well as for a population of patients.
This observation suggests that we are dealing with a very complex system, one that is not sufficiently understood. Engineering expertise can be applied to better understand the process of care and the application of technology so as to improve the provision of effective clinical decision support. The paper pointed to potential errors in the process of entering and retrieving information, such as human—computer interface issues and cognitive overload, and it addressed the overemphasis on structured and complete information entry or retrieval.
The paper also warned about errors in the communication and coordination process, including the potential for misrepresenting collective, interactive work as a linear, clear-cut, and predictable workflow; the possibility of misrepresenting communication as information transfer; decision support overload; and the loss of prior mechanisms for catching errors.
The paper highlights the fact that we do not completely understand healthcare processes and do not fully recognize the disruption that occurs when technology is introduced—underscoring the need for engineering expertise in the process of designing a better learning healthcare system.
What are some general themes regarding effective clinical decision support? Clinical decision support should be carried out in the context of a planned care model—a model that is much more patient-centric, that takes into account process redesign and a team approach, and that is enhanced by information technology. This model differs significantly from the old one-doctor, one-patient, one-exam-room, paper-record model.
In approaching clinical decision support, one needs to think broadly across the care team members, including the patient; across the continuum of care; and across the tools and systems available. Some decision support opportunities include reference information and guidance—clinical evidence sources and guidelines, direct-to-patient clinical decision support—availability of information, relevant data presentation—attention to the human-computer interface, documentation forms and templates—integration into the workflow, order entry facilitator—integration of decision support at order entry, protocol and pathway support—a way to facilitate the care process, reactive alert and reminders—used judiciously, and use of clinical data—clinical registries to support the planned care model.
Use of clinical data, including clinical registries in the context of team process redesign, is one particular area in which one can often see significant improvement of care at both the individual and population levels. What might this effective use of clinical decision support look like? Imagine a patient time line that extends for a year.
On that time line is a point that represents an encounter. If one enlarges that point, one can see what some of the decision support opportunities are, many of which are currently available at Kaiser Permanente. The systems underlying decision support includes the EMR, online tools that give patients access to their medical records, and clinical registries.
The patient time line starts with the appointment process and may include an appointment. A patient questionnaire can be delivered, such as a health risk appraisal or a questionnaire specific to the patient's condition or disease. A preventive alert system is available that, at check-in, alerts the patient to needed interventions, thereby activating the patient as well as the care team as the patient moves through the healthcare system.
At the rooming stage, the medical assistant can be reminded to address important risk factors, such as assessing smoking status and informing the patient about smoking cessation programs.
An array of tools are available to clinicians during this encounter, including reminders for prevention issues, alerts for chronic care issues, and a variety of charting tools supporting the care process and facilitating data entry. Computerized physician order entry is a particularly powerful tool to facilitate clinical decision making. There are also alerts and reminders for those instances in which, for example, a physician may prescribe a medication to which the patient is allergic, that interacts negatively with another medication, or that is contraindicated for the patient's specific condition.
As this process unfolds, one can see that it would be very easy to overload one part of the system, such as the encounter in the exam room between physician and patient.
That is why one needs to think across the continuum of care and across the care team members who are available to avoid creating a bottleneck in one part of the process. At discharge, printing of patient instructions and other visit information can be available for reinforcement and later review by the patient or family members.
Decision support can also be embedded in the pharmacy information system, thereby using the pharmacist as another team member in the care delivery process. Finally, the enhanced system uses clinical registries, which apply data from the EMR as well as other clinical systems. This is one way to enable new models of care, including outreach to patients with needed interventions that can be done outside of the usual face-to-face visit. This availability of information allows all of the care team members, including patients and their families, to participate in the care being delivered.
Now let us look at a specific example of enhanced care enabled by information technology. It is a service whereby nurses and clinical pharmacists coordinate the provision of cardiac risk reduction activities in patients with cardiovascular disease by supporting and working collaboratively with patients, primary care physicians, and cardiologists.
The focus is on activities that have been shown to improve patient outcomes. The service assists patients in managing and monitoring antiplatelet therapy, antilipid therapy, beta-blocker medication, angiotensin-converting enzyme inhibitor medication, blood pressure control, and diabetes management, if applicable.
It also provides counsel and support on lifestyle changes. The service follows more than 12, patients with cardiovascular disease. More important is that the cardiac mortality of this population has been reduced by 73 percent.
Also of interest is that the organization has seen a financial return because fewer patients with cardiovascular disease require rehospitalization or further cardiac interventions.
The development of the KPCO Cardiac Rehabilitation and Clinical Pharmacy Cardiac Risk Service addressed and overcame many of the barriers in the areas of people and culture, process, data and technology, and the healthcare environment that were reviewed earlier, resulting in superior clinical outcomes. The service has many of the characteristics that could be considered components of a model learning healthcare system.
With regard to the people issue, KPCO has developed a culture of physicians, nurses, and clinical pharmacists working together and focused on the patient. That collaboration has extended to those who work in information technology. There has been effective clinical leadership on the part of clinical pharmacists, nurses, physicians, and information technologists in the establishment of these services.
Clinical staff have focused roles and clear accountability and are trained in their roles, including use of the technology. In terms of process, clear, evidence-based guidelines and clinical pathways are agreed upon by all involved and modified as needed according to new research findings or internal learning.
Alternative approaches to care and communication with patients have been more fully exploited with the use of phone contacts, mail, secured messaging, group visits, and direct patient Internet access to medical records, including laboratory results, medications, and patient instructions. There are clear hand-offs and communication with other team members, including primary care clinicians and cardiologists. An information infrastructure is required with the capability to aggregate data that facilitate the identification and stratification of populations of patients into the clinical registry.
This registry provides the real-time information needed by the team members to properly manage both individual patients and the population. It alerts the team members when needed interventions are due or when they have not been completed, thus ensuring long-term adherence to agreed-upon goals. The registry facilitates the tracking of the performance of the service, providing necessary feedback on its processes.
A clearly defined clinical model from an engineering perspective informs the technology approach. Collaboration with information technology enables system adjustments as the clinical model transitions. KPCO is an integrated healthcare delivery system that allows a system-level view.
The program design was not significantly constrained by the financing and reimbursement system that currently prevails in the United States. Is information the answer? Yes, but it is only part of the answer. One cannot think about data and technology without also taking into account people and their culture, focusing on the process of care from the patient's perspective, and addressing the healthcare environment.
In sum, the challenge and opportunity for all who want to see an improved learning healthcare system is to address all of these interrelated components. Deutschendorf, M. The proliferation of new medical information and technologies, increased regulatory oversight, an aging population, and heightened consumer awareness and expectations are all affecting the ability to provide coherent care for patients.
The dismantling of traditional care delivery models as a result of cost constraints in the early s has also contributed to the disorganization, fragmentation, and discontinuity of patient care. With as many as 20 healthcare providers per patient, the need for effective communication and collaboration has become more important than ever to achieve quality and safety outcomes.
The National Quality Forum has identified care coordination as one of its top national priorities National Priorities Partnership, This paper focuses on those structure and process factors that contribute to the current state of discontinuity and fragmentation in patient care. The critical factors in effective care delivery models are discussed, as well as the need for communication models and systems that can provide the accurate and timely transfer of patient information throughout the healthcare continuum.
The current healthcare system evolved from the late s and early s with the broad penetration of managed care in an attempt to respond to economic pressures and manage rapidly escalating healthcare costs. Financial risk was transferred from the payer to the provider, with spending being more tightly controlled and facility service to the acutely ill being limited.
To contain costs, acute care facilities sought strategies to improve efficiencies in care delivery, which resulted in widespread restructuring, reengineering, and redesign efforts. These changes had a significant effect on hospital systems, clinical staff, and resources. Hospitals could no longer afford uncoordinated patient care that resulted in ad hoc patient care decisions.
Although some new patient care delivery models were proposed that centered care on patients and families, most were more closely related to industrial approaches geared to achieving efficiencies affecting the bottom line.
Untested models were implemented without evidence of improved clinical quality outcomes, effective care delivery systems were frequently dismantled, and unskilled workers were substituted for professional staff. There was an exodus of experienced care providers, resulting in shortages in most healthcare disciplines.
Ultimately, clinical quality and safety outcomes eroded as a result of a lack of understanding of the complexities of individual human responses to similar stimuli. In addition to such changes in care delivery systems, other factors played a major role in creating the complexity of the current healthcare environment.
New information and medical technology that must be translated into safe practice is proliferating at an extraordinarily rapid rate, making it nearly impossible to determine true priorities for implementation in evidence-based practice. As noted, each patient may have up to 20 healthcare providers, all generating assessments and treatment plans that must be coordinated and communicated.
Multiple levels of care must be considered when patients are being transitioned out of the acute care setting, all with different rules for admission and reimbursement. Although the average length of a patient's hospital stay has decreased by 23 percent over the past decade, the severity of illness has increased by 12 percent, necessitating improved assessment and monitoring strategies.
Twenty-five percent of a hospital's census may turn over in a hour period, adding to increased patient care unit activity and the need for accurate coordination of services and resources. As many as 62 percent of hospitals report operating over capacity. The increased collection and public reporting of quality and safety data, sanctioned by regulatory agencies as a means of demonstrating organizational performance, is contributing to health systems' administrative burden and threatens to distract caregivers from a focus on the bedside.
As the average length of stay decreased, it was estimated that half of American hospitals would close by the year , but this projection underestimated the effect of the aging population. Today, it is not unusual for an year-old with chronic health conditions to be living at home, still driving, with a spouse who also has chronic disease and has nowhere to go after a catastrophic illness. The health needs of the aging population were not fully anticipated when the Balanced Budget Act was passed in , reducing Medicare payments to skilled and long-term care providers.
Although these objectives are significantly different from those of just 20 years ago, patient care delivery processes have not changed dramatically, even as the increased severity of illness demands significant transformation. As noted, it is not uncommon for a quarter of a large academic hospital's patients to have a length of stay of 24 hours or less. The impact of this shortened length of stay combined with the increased severity of illness is that healthcare practitioners must accurately assess, evaluate, and treat patients during this time frame.
There is a disparity between the expectations of the acute care environment and those of the regulatory agencies. The acute care setting is frequently viewed by regulatory bodies as the point of access for all current and historical patient problems, when such attention to patient needs is more appropriately the purview of the ambulatory care environment.
The healthcare provider has a more limited exposure to the patient in the acute care setting than in any other setting.
Yet it is expected that all biopsychosocial, economic, and developmental problems the patient has ever experienced will be addressed and documented in this setting, at the same time that the healthcare providers are employing preventive strategies and facilitating healthy behaviors in the future.
More focus is required on how to improve access to ambulatory care departments, where the appropriate objectives are health promotion, illness prevention, and stabilization or improvement of function. The complexity of patient populations has changed radically, in part because of increased life spans, greater prevalence of chronic illness, and expanding consumer expectations.
Healthcare consumers are armed with Internet information and resources, arriving at appointments with their physicians well prepared with questions, background information, and specific suggestions about their preferred treatment.
Often, they present their findings in the form of demands, having decided in advance what the best therapy is. Healthcare providers have not fully anticipated the implications of an elderly, sicker consumer and have not implemented methods to manage unrealistic expectations. Education needs to be provided actively to patients and families so they know that although they are likely to live longer, they will do so with chronic disease. Preparing patients and families for realistic end-of-life decisions is more important than ever, given the increased healthcare costs associated with futile care.
The demand by payers, consumers, and downloadrs for demonstration of outcomes has led to a greater prevalence of regulatory standards and oversight focused on improving quality and safety outcomes. Reduced practice variation through evidence-based care and fiscal responsibility through cost-effective strategies are expected to be transparent to the consumer and payer through the provision of specific and quantifiable information.