Quality and Patient Safety in Emergency Medicine

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208 Quality and Patient Safety in Emergency Medicine

image      Key Points

The great variability in local and regional clinical practice patterns indicates that the U.S. population does not consistently receive high-quality health care. Problems with overuse, underuse, and misuse of health care resources have been documented.

Two watershed Institute of Medicine reports brought the quality problems in health care to center stage. These reports championed that health care should be safe, effective, patient-centered, timely, efficient, and equitable.

The greatest sources of quality problems in health care are not “bad apples” (i.e., incompetent providers), but rather “bad systems,” specifically systems that promote, or at least do not mitigate, predictable human errors.

Medical errors and adverse events are caused by both active and latent failures, as well as factors (e.g., error-producing conditions or reliance on heuristics) that lead to cognitive errors (e.g., slips, lapses, premature closure). Diagnostic errors are a leading cause of patient safety issues in emergency medicine. High-reliability organizations are preoccupied with failures and serve as models for health care.

Both public and private sectors have a strong movement away from purchasing health care services by volume and toward purchasing value (defined as health care value per dollar spent). Future reimbursement models will inevitably center on performance measurement and accountability, with a likely shift in level of financial risk borne from payer to provider.

History of Health Care Quality

Efforts to assess quality in health care extend back to Dr. Ernest A. Codman, an early twentieth-century surgeon at Massachusetts General Hospital in Boston. Codman was the first to advocate for the tracking and public reporting of “end results” of surgical procedures and initiated the first morbidity and mortality conferences.1 Such public information would allow patients to choose among surgeons and surgeons to learn from better performers. Codman was clearly ahead of his time. The medical establishment resisted having their “results” measured and publicized, and Codman was accordingly ostracized by his peers. In 1913, however, the American College of Surgeons adopted Codman’s proposal of an “end result system of hospital standardization” and went on to develop the Minimum Standard for Hospitals. These efforts led to the formation of the forerunner of today’s Joint Commission (JC) in the 1950s. The JC’s accreditation process, local hospital quality reviews, professional boards, and other systems that developed allowed the medical profession and hospitals to judge the quality of their work and be held accountable only to themselves for most of the twentieth century.

The academic science of quality management in health care is credited to Dr. Avedis Donabedian’s efforts in the 1980s. Donabedian advocated for evaluating health care quality through assessment of structure (e.g., physical plant, personnel, policies and procedures), process (how things are done), and outcome (final results).2 His ideas were first adopted in public health and later spread to administration and management. Shortly thereafter, Dr. Donald Berwick, a Harvard Medical School (Boston) pediatrician, building on a systems approach to quality management, introduced the theory of continuous quality improvement into the medical literature. In his landmark New England Journal of Medicine article,3 Berwick remarked the that the “Theory of Bad Apples” relies on inspection to improve quality (i.e., find and remove the bad apples from the lot). In health care, those who subscribe to this theory seek outliers (deficient health care workers who need to be punished) and advocate a blame and shame culture through reprimand in settings such as morbidity and mortality conferences. The “Theory of Continuous Improvement,” however, focuses on the average worker, not the outlier, and on systems problems, rather than an individual’s failure.

Examples of bad systems abound in medicine. One example provided by Berwick involves the reported deaths resulting from an inadvertent mix-up of racemic epinephrine and vitamin E.4 Newborns in a nursery received the epinephrine instead of the vitamin in their nasogastric tubes. If presented as the mix-up of a benign medication for a potentially toxic one, it is viewed as appalling, and blaming individual negligent behavior is easy. Yet when one notes that the two bottles were nearly identical, one can understand why the system “is perfectly designed to kill babies by ensuring a specific—low but inevitable—rate of mixups.” The Theory of Continuous Improvement suggests that quality can be improved by improving the knowledge, practices, and engagement of the average worker and by improving the systems environment in which they work. The “immense, irresistible quantitative power derived from shifting the entire curve of production upward even slightly, as compared with a focus on trimming the tails” is what makes a systems focus so attractive (Fig. 208.1).

Although Berwick and others were publishing new studies critiquing health care’s approach to quality and safety throughout the 1980s and 1990s, not until the publication of two reports by the Institute of Medicine (IOM) did quality and safety capture the public’s attention: To Err is Human: Building a Safer Health System,5 in 1999, and Crossing the Quality Chasm: A New Health System for the 21st Century,6 in 2001.

To Err is Human focused the attention of the U.S. public on patient safety and medical errors in health care. The report’s most famous sound bite, that medical errors result in the deaths of two jumbo jetliners full of patients in U.S. hospitals each day, gained traction with lawmakers, employers, and patient advocacy groups. This estimate, that 44,000 to 98,000 deaths occur per year in the United States as a result of medical error, would make hospital-based errors the eighth leading cause of death in the United States, ahead of breast cancer, acquired immunodeficiency syndrome, and motor vehicle crashes. These statistics were derived from two large retrospective studies. In the Harvard Medical Practice Study,7 nurses and physicians reviewed more than 30,000 hospital records and found that adverse events occurred in 3.7% of hospitalizations. Of these adverse events, 13.6% were fatal, and 27.6% were caused by negligence. The Colorado-Utah study8 reviewed 15,000 hospital records and found that adverse events occurred in 2.9% of hospitalizations. Negligent adverse events accounted for 27.4% of total adverse events in Utah and for 32.6% of those in Colorado. Of these negligent adverse events, 8.8% were fatal. Extrapolation of results from these two studies provided the upper and lower limits for deaths associated with medical errors for the IOM report. In both studies, compared with other areas of the hospital, the emergency department (ED) had the highest proportion of adverse events resulting from negligence.

Crossing the Quality Chasm focused more broadly on redesign of the health care delivery system to improve the quality of care. The report begins by stating: “The American health care delivery system is in need of fundamental change. … Between the health care we have and the care we could have lies not just a gap, but a chasm.” The report goes on to detail that this chasm exists for preventive, acute, and chronic care and reflects overuse (provision of services when potential for harm exceeds potential for benefit), underuse (failure to provide services when potential for harm exceeds potential for benefit), and misuse (provision of appropriate services, complicated by a preventable error, such that the patient does not receive full benefit). The report first defined six domains for classifying quality improvement for the health care system (Table 208.1). Together, the IOM reports solidified a key concept—quality problems are generally not the result of bad apples but of bad systems. In fact, well-intentioned, hard-working people are routinely defeated by bad systems, regardless of training, competence, and vigilance.

Table 208.1 Institute of Medicine’s Six Aims for Quality Improvement

AIM DEFINITION
Health Care Should Be:  
Safe “Avoiding injuries to patients from care that is intended to help”
Effective “Providing services based on scientific knowledge (avoiding underuse and overuse)”
Patient centered “Providing care that is respectful of and responsive to individual patient preferences, needs, and values and ensuring that patient values guide all clinical decisions”
Timely “Reducing waits and sometimes harmful delays for both those who receive and those who give care”
Efficient “Avoiding waste, in particular waste of equipment, supplies, ideas, and energy”
Equitable “Providing care that does not vary in quality because of personal characteristics such as gender, ethnicity, geographic location, and socioeconomic status”

Adapted from Committee on Quality Health Care in America. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academies Press; 2001.

Costs in Health Care

In 2009, the United States spent $2.5 trillion, or $8000 per person, on health care.9 Although we spend well over twice as much per capita on health care than any other industrialized country, we repeatedly fare poorly when compared with other systems on quality and outcomes.10 Half of the U.S. population admits to being very worried about paying for health care or health care insurance.11 One in four persons in the United States reports that his or her family has had problems paying for medical care during the past year.12 Close to half of all bankruptcy filings are partly the result of medical expenses.13 U.S. businesses similarly feel shackled by health care costs, with reports of companies spending more on health care than on supplies for their main products. In Massachusetts, annual health care costs in school budgets outpaced state aid for schools and forced schools to make spending cuts in books and teacher training.14 The increased cost of U.S. health care threatens the ability of our society to pay for other needed and wanted services.

Variability in Health Care

Although the number of errors coupled with increasing health care costs paints a negative picture, the variability of care is both more concerning and a source for optimism. Dr. John (Jack) E. Wennberg’s work in regional variability has illustrated the differences in cost, quality, and outcomes of U.S. health care since the 1970s. In 1973, Wennberg and Gittelsohn15 first identified the extreme degree of variability that exists in clinical practice by documenting that 70% of women in one Maine county had hysterectomies by the age of 70 years, as compared with 20% in a nearby county with similar demographics. Not surprisingly, the rate of hysterectomy was directly proportional to the physical proximity of a gynecologist. Similarly, residents of New Haven, Connecticut are twice as likely to undergo coronary artery bypass grafting (CABG), whereas patients in Boston are twice as likely to undergo carotid endarterectomy, even though both cities are the home of top-rated academic medical centers.16

Dr. Wennberg’s work in regional variability led to the creation in the 1990s of the Dartmouth Atlas Project, which maps health care use and outcomes for every geographic region in the United States, and details care down to the referral region of each hospital. Atlas researchers, notably Dr. Elliott Fisher et al.,17,18 have looked at the pattern of health care delivery and have found no clear association between the volume, intensity, or cost of care and patient outcomes. According to the Dartmouth Atlas Project, patients in areas of higher spending receive 60% more care, but the quality of care in those regions is no better, and at times worse, when key quality measures are compared.17,18 More widely reported in the lay press was the finding that Medicare spends twice the national average per enrollee in McAllen, Texas than it does any other part of the country, including other cities in Texas, without better-quality outcomes.19 The increased expense comes from more testing, more hospitalizations, more surgical procedures, and more home care. Variability in practice pattern, however, is not limited to overuse, but also includes underuse. McGlynn et al.20 found that, in aggregate, the U.S. population receives only 55% of recommended treatments, regardless of whether preventive, acute, or chronic care is examined.

The findings of the Dartmouth Atlas Project have frequently been cited as a rationale for health care reform law. The Project’s underlying methodology, however, has been scrutinized. Some investigators have questioned whether it appropriately adjusts for the costs of medical practice in different regions. Others have pointed out the limitations of focusing analysis on health care costs incurred by patients over the 2 years before their deaths and attributing these costs to the hospital most frequently visited.21 A study by Romley et al.22 reported an inverse relationship between hospital spending and inpatient mortality. Although great variability clearly exists in clinical practice, what is not clear is how to translate maps of geographic variation into health care policies that improve quality and contain costs.

One attempt at decreasing practice variability has been the rapid proliferation of clinical practice guidelines. Guidelines have been developed by physician specialty societies, hospitals, employers’ consortia, and government agencies (e.g., the Agency for Healthcare Research and Quality). The physician community, however, has been slow to adopt guidelines for several reasons. Some physicians disparage guidelines as “cookbook medicine,” whereas others point to the limited evidence on which these guidelines are built. Fear that deviation from guidelines may lead to more malpractice claims has also dampened enthusiasm for their use. Although clinical practice guidelines, order sets, and electronic decision support may not individually be the magic bullet for decreasing unwarranted clinical practice variability, all health care efforts should aim to be safe, effective, patient centered, timely, efficient, and equitable.

Institute of Medicine Aim: Patient Safety

Echoing the ancient axiom of medicine, Primum non nocere, or “First, do no harm,” patients expect not to be harmed by the very care that is intended to help them. As such, patient safety is the most fundamental of the IOM’s six domains. Tables 208.2 and 208.3 provide the IOM’s Patient Safety and Adverse Event Nomenclature.

Table 208.2 Institute of Medicine’s Patient Safety and Adverse Event Nomenclature

TERM DEFINITION
Safety Freedom from accidental injury
Patient safety Freedom from accidental injury; involves the establishment of operational systems and processes that minimize the possibility of error and maximize the probability of intercepting errors when they occur
Accident An event that damages a system and disrupts the ongoing or future output of the system
Error The failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim
Adverse event An injury caused by medical management rather than by the underlying disease or condition of the patient
Preventable adverse event Adverse event attributable to error
Negligent adverse event A subset of adverse event meeting the legal criteria for negligence
Adverse medication event Adverse event resulting from a medication or pharmacotherapy
Active error Error that occurs at the front line and whose effects are felt immediately
Latent error Error in design, organization, training, or maintenance that is often caused by management or senior-level decisions; when expressed, these errors result in operator errors but may have been hidden, dormant in the system for lengthy periods before their appearance

Adapted from Kohn LT, Corrigan J, Donaldson MS, McKenzie D. To err is human: building a safer health system. Washington, DC: National Academies Press; 2000.

Table 208.3 Active and Latent Failure Types

FAILURE TYPE CHARACTERISTICS
Active

 

  Latent

From Aghababian R, editor. Essentials of emergency care. 2nd ed. Sudbury, Mass: Jones and Bartlett; 2006.

Active and Latent Failure Types

Failures in the ED fall into two main failure types: active and latent. Active failures are unsafe acts or omissions at the level of the front-line operator, such as the emergency physician (EP), nurse, or care provider, and the effects are felt almost immediately. This is sometimes called the sharp end of care. Latent failures are failures of the system that can lie dormant, or latent, for years. Despite, or perhaps because of, their obscurity, latent failures can cause multiple types of operator, or active, failures, yet go unnoticed to the casual observer; thus, they pose the greatest threat to safety in the complex ED system. Masked as the cause of incidents, these failures are powerful in joining with other factors to breach the system’s defences and coalesce in errors. In large part, latent failures are the result of decisions affecting daily ED operations, decisions often made by persons not directly involved in care delivery; for example, managers, designers, procedure writers, and drug manufacturers.

Active and latent failures are plentiful in the ED. An active failure occurs when a triage nurse accidentally measures a pediatric patient’s weight in pounds but writes down the weight in a chart box labeled kilograms instead. A similar error occurs when an EP orders antibiotics for a pediatric patient based on milligrams per kilograms (mg/kg) but uses weight in pounds instead. A latent failure exists when a patient with a pending pregnancy test undergoes computed tomography imaging before the positive result returns, or a patient with a pending creatinine test is given intravenous contrast before the abnormal results are acknowledged by the ordering provider.

Reason’s “Swiss Cheese” Model

Described by James Reason in 1990,23 the “Swiss cheese” model of human error has four levels of human failure useful to evaluating a medical error (Fig. 208.2). The first level depicts active failures, which are the unsafe acts of the operator that ultimately led to the error. The next three levels depict latent failures (preconditions for unsafe acts, unsafe supervision, and organizational influence), which are underlying holes (or hazards) that allow errors to pass through to the sharp end. As with slices of Swiss cheese, when the levels of error are not aligned, an active failure can be caught before it causes harm—a near miss. With the right alignment, however, patients can be harmed by predictable human errors when systems are not appropriately designed to protect them.

image

Fig. 208.2 Reason’s “Swiss cheese” model.

(Adapted from Reason J. Human error. Cambridge: Cambridge University Press; 1990.)

Cognitive Errors

Cognitive errors fall into three distinct types: skill based, rule based, and knowledge based. Consider the act of driving a car or putting on your shoes. At some point, most of us acquired the requisite skills to accomplish these tasks quickly and efficiently without having to think about them. Skill-based cognitive performance refers to such acts. In the clinical setting, experienced clinicians approach the tasks of preparing a wound, tying a suture, or starting a central line in like fashion. Such clinical actions require little cognitive decision making. Skill-based errors are known as slips and lapses. Slips arise when actions fail to proceed as planned; for example, when a physician chooses an appropriate medication and writes 10 mg when the intention was to write 1 mg. Slips are errors in execution resulting from a failure of attention or perception often caused by interruptions or altered routines. In lay terms, slips are often equated with minor incidents. In the ED, patients can die as a result of slips. Lapses also result in failure to execute a plan, but whereas slips are observable, memory-based lapses are not. Pressing the wrong button on a defibrillator because you are interrupted and lose your train of activity is a slip; not being able to recall the correct energy to defibrillate ventricular stimulation is a lapse.

Any task departure from skills-based processing requires either a rules-based or a knowledge-based approach. Rules-based processing occurs when the clinician applies a known rule to make a decision. Rules, typically applied in the form “if X, then Y,” come from past experience, explicit instructions, or clinical guidelines. Traditional medical education is full of experienced-based rules, often termed clinical pearls. For example, the advice not to discharge a patient with abnormal vital signs is based on clinicians’ cumulative experience of reviewing adverse events after ED discharges. In contrast, the use of formalized clinical decision rules or guidelines (e.g., the Ottawa ankle rules to determine need for radiographs in ankle injuries) is another form of rule-based processing. Knowledge-based processing is when medical knowledge is applied and analytic processes are used to execute a plan of care. Errors of rule-based and knowledge-based cognition are known as mistakes. In rules-based errors, the wrong rule is selected, applied, or linked to the situation. Knowledge-based errors result when incomplete or incorrect knowledge is applied or flawed analytic processes are used, resulting in a poor plan of care. A mistake in medicine may involve selecting the wrong drug or treatment because of an incorrect diagnosis.

As clinicians gain experience, they engage to greater extent in skill-based and rule-based processing and to a lesser degree in knowledge-based processing. This shift in cognitive processing creates an interesting paradox with respect to the types of errors clinicians are most likely to commit. Although the rate of their knowledge-based errors is substantially reduced, highly trained individuals are more likely to experience skill-based errors, which are errors that arise from processes requiring the least amount of cognitive function.

EP are at particular risk for cognitive errors related to the core tasks of the specialty of emergency medicine—the rapid evaluation of patients with undifferentiated complaints and the high-risk decisions that must be made with incomplete information.

Heuristics

Medical decision making in the ED is also characterized by a reliance on heuristics. Heuristics are shortcuts, rules of thumb, or any kind of abbreviated thinking that accomplishes quick and efficient decision making. Although they often serve EPs well, heuristics sometimes fail, thus leading to poor outcomes.

The four most commonly applied heuristics in emergency medicine are representativeness, availability, anchoring, and premature closure. The representativeness heuristic is applied when a clinician makes a subjective judgment of the similarity of a particular patient’s presentation to that of most patients who present with a particular condition. The more unrepresentative the patient’s presentation is, the greater is the chance that the diagnosis will be delayed or missed. Representativeness errors appear most often in settings of high diagnostic uncertainty, such as that typifying the ED, and they are more likely to be committed by clinicians with lower levels of experience. An example is the evaluation of a patient for thoracic aortic dissection, a relatively rare diagnosis. Although the classic symptom of a sudden onset of tearing thoracic chest pain that radiates to the back is not present in most cases, most physicians are less likely to consider this diagnosis without a representative presentation.

Another heuristic that can lead to errors in decision making is availability. Certain encounters are more prevalent in our memories, perhaps because they have occurred more recently, but more often because they are emotionally salient. When making diagnoses, human nature leads to an overreliance on encounters that are vivid and to place less importance on those least salient. For example, if a physician has a particularly vivid experience of missing an acute myocardial infarction (AMI) in a young person, the physician may become overcautious in managing similar patients with chest pain. Availability may similarly be increased by indirect experience: a recent discussion with a colleague, a case presentation at rounds, or an article reviewing a particular case. In contrast, availability is decreased by long intervals since encountering a particular disease, or never having previously seen it.

Anchoring results when physicians commit early to a diagnosis and give it undue weight when considering the available data. One way of avoiding anchoring is to ask “What else could this be?” and always to be disciplined in thinking about the differential diagnosis. The tendency to look for evidence that bolsters an original hypothesis is referred to as confirmation bias. Instead of ignoring conflicting data, EPs must look for disconfirming evidence that rejects the initial contention. If anchoring occurs early in a presentation and EPs operate under a strong confirmation bias, they are sure to miss diagnoses. For example, an older patient who presents with epigastric pain and a bulge in the abdomen could have either an incarcerated hernia or an AMI. A clinician who anchors on the diagnosis of incarcerated hernia can easily explain away tachycardia as the result of pain, and subtle electrocardiographic changes as nonspecific, rather than identifying them as the pattern of an early AMI.

Finally, premature closure occurs when a physician makes a quick diagnosis (often based on pattern recognition and not confirmed by appropriate testing), then stops collecting data, and fails to consider other possible diagnoses. Premature closure can occur in any case, but it is especially common when EPs take care of patients who seem to have an exacerbation of a known disorder. For example, a patient with a history of migraine is assumed to have another migraine, rather than an acute presentation of subarachnoid hemorrhage. Another example is a patient with chest pain and ST-segment elevation on the electrocardiogram who is assumed to be suffering from an acute coronary syndrome, rather than thoracic aortic dissection leading to coronary artery dissection.

Awareness of such cognitive biases is crucial, and simply knowing what they look like can help in overcoming them. Avoiding reflexive thinking and taking the time to think about how we think can help to minimize or avoid errors. Decision support tools, such as templated charts with potential diagnoses, or more sophisticated electronic tools that are queued by patient complaints and history, can help physicians overcome some of these biases.

Error-Producing Conditions in the Emergency Department

The ED ranks among the top three hospital locations with the highest risk of error, along with the intensive care units and operating rooms. This finding is not surprising when one considers the combinations of error-producing conditions that exist in the typical ED. Many different providers (e.g., physicians, nurses, technicians) work closely together to care simultaneously for multiple patients of varying medical acuity who present with any imaginable chief complaint, from the most life-threatening to the most poorly defined, with whom these providers typically have no prior relationship. Providers are bombarded with multiple interruptions, and they struggle at times with understaffing and overcrowding while working through disruptive sleep cycles. As such, error-producing conditions in the ED include diagnostic uncertainty, low signal-to-noise ratio (i.e., the incidence of a serious condition or diagnosis [e.g., cauda equine syndrome] is low compared with more common and more benign diagnoses [e.g., musculoskeletal back pain]), high cognitive load, and poor feedback. Lack of continuity of care and unreliable and untimely feedback of patient diagnoses and outcomes make it difficult for EPs to refine their clinical skills continuously. A national survey of U.S. EDs documented commonly reported problems in four major areas: physical environment, staffing, inpatient coordination, and information coordination and consultation. The surveys suggest that the U.S. EDs have substantial room to reduce the latent conditions for errors.

High-Reliability Organizations

In the ED, we can learn from other industries (e.g., aviation, nuclear power) that have developed and incorporated systems allowing for early error corrections or prevention and leading them to function as high-reliability organizations.24 Such industries tightly couple the process of doing work with the process of learning to do it better. Operations are expressly designed to reveal problems as they occur. When problems arise, no matter how trivial, they are addressed quickly. High-reliability organizations share the following six traits:

Understanding the importance of a culture of safety in the strive for high quality, Johns Hopkins Hospital (Baltimore) researchers implemented a comprehensive, unit-based safety program (CUSPS) at almost 150 individual units in the hospital.25 This program ultimately led to the establishment of an organization-wide culture of safety at the hospital. Although in the past, organizations focused many resources on building a culture of safety, patient safety leaders have shifted to advocating for a just culture, one that balances safety with accountability.26 Whereas a culture of safety allows evaluation of suboptimal medical outcomes without fear of punitive action toward individuals, a culture of accountability also encourages providers to do the right thing, especially when doing the right thing is easy. A notable example is facilitating hand hygiene through provision of soap dispensers in key locations while holding providers accountable for their individual behavior through direct observation and feedback.

Institute of Medicine Aim: Timeliness

Timeliness is a core mission of the specialty of emergency medicine. In a little more than one decade, ED visits have grown by nearly 25%, whereas at least 10% of EDs have closed nationally. This situation has caused many EDs to experience increased waiting room times, length of stay, and boarding of inpatients in the ED.27 In fact, up to 25% of patients are not seen by an EP within acuity-based recommended times,28 and patients with AMI have experienced a 150% increase in wait times over this period.29 Deaths in the waiting room reported in the lay press serve as a stark reminder of the consequences of systems failures on individual patients.30

Although one goal of health care reform is to decrease ED visits, to date, large-scale health systems reforms have not been able to do this. In fact, given aging demographics (older patients have a higher ED use rate) and patient preferences (for rapid acute care at the time of their choosing), current crowding trends are likely to continue. Furthermore, if efforts at health care reform lead to an increased number of insured patients, Massachusetts’ experience of requiring individual to obtain health insurance (the individual mandate) suggests that more, rather than fewer, ED visits can be expected in the near term.31

A growing body of evidence links prolonged ED length of stay, ED crowding, and boarding of inpatients in the ED to lower quality care and worse patient outcomes. ED crowding has been associated with worse-quality care for patients with AMI, acute coronary syndromes, and hip fractures.3234 For example, cardiac patients boarded in the ED for longer than 8 hours are less likely to receive guideline-recommended therapies and are more likely to have recurrent MIs. Given prolonged wait times to evaluation in the ED, one study evaluated the safety of managing potential cardiac patients in the ED waiting room.35 Although approaches such as this, to improve safety in the crowded ED, are reasonable short-term solutions, they do not address the primary latent failure of ED crowding, which is the inability to evaluate and treat patients in the appropriate location in a timely fashion.

Given the challenge of addressing quality and safety issues in a crowded ED, many departments are redesigning their operations and patient flow models to improve the timelines of care. Most notably, newer models of care have been developed to replace the traditional model of ED care that was serial (e.g., patient triage, then nursing evaluation, then physician evaluation, then laboratory or diagnostic testing, then decision on final disposition) and uniform (regardless of patient’s clinical needs). Newer models of care have several common features: optimizing front-end operations, developing multiple pathways through the ED that attempt to match a patient’s acuity and resource needs, eliminating duplicate evaluations, maximizing the use of limited ED beds, and facilitating rapid discharge of patients.36 One example is vertical patient flow, a model in which a cohort of patients, rapidly identified on arrival to the ED, is evaluated, managed, and either admitted or discharged in advance (or in lieu) of occupying a traditional ED bed.37 These patients (often a subset of Emergency Severity Index [ESI] 3 patients) require greater medical decision making and more resources than do fast-track patients, but they do not require a room and a stretcher for evaluation. Because these patients do not need to be disrobed in a private room for most of their ED visit, they can sit in recliners in an internal waiting room for most of their ED visit.

Institute of Medicine Aim: Patient-Centered Care

The IOM report identified patient-centered care as a core element of quality. Although many physicians equate patient-centeredness with patient satisfaction, satisfaction is only one component of patient-centeredness. Patient-centered care respects individual patients by addressing the values, ethnicity, social situation, and information needs of each patient.38 Although patient satisfaction surveys have been used for a long time in emergency medicine, only more recently have EPs begun to implement changes that strive to make emergency care more inclusive and responsive to patients’ values, needs, and wishes. Two notable examples are the move to include families in resuscitations39 and the use of structured decision aids to guide joint medical decision making.4041 Historically, family members were kept out of ED resuscitation rooms when their loved one was undergoing advanced resuscitation (e.g., cardiopulmonary resuscitation). Studies show that family members benefit from their involvement at the end of the patient’s life because the resuscitation, instead of being traumatic, often helps bring closure to a tragic event. A second example is using structured decision aids to engage patients in complex diagnostic decisions, such as whether to conduct cardiac risk stratification in the ED, in the hospital, or in the outpatient environment. When presented with well-designed decision aids, patients are both less likely to request more resource-intensive testing and more likely to be satisfied with their care.

Institute of Medicine Aims: Effective, Efficient, and Equitable Care

According to the IOM, effective care should be based on best evidence, thus avoiding inappropriate underuse or overuse. The literature supports the care of some common patient presentations (e.g., syncope, sepsis). Much room for improvement remains, however, because much of emergency practice is without a strong basis in the literature. In this relatively new specialty that deals with a diverse patient population under challenging clinical conditions, conducting methodologically rigorous clinical research has been difficult. Much of the evidence that has been cited to justify emergency practice is from other populations, clinical venues, and focus on nonemergency outcomes. This situation is illustrated by the paucity of level I recommendations in the American College of Emergency Physicians Clinical Policies. As in other areas in which clinical practice has been studied, tremendous provider-to-provider variability exists in emergency medicine. The hope is that minimizing this variability by developing evidence-based guidelines will allow EPs to provide effective care more reliably.

According to the IOM, efficient care avoids waste. Although most ED administrators may define efficiency by the rapidity with which patients are processed through the ED, most health policy analysts view efficiency as a measure of the quality of care delivered for the amount of resources consumed. Efficiency is akin to value and can be improved by reducing waste or improving quality, while holding all else constant.

Unfortunately, ED care is widely viewed by the medical community as inefficient. This view is often based on comparisons of charges and costs for ED visits and primary care physician visits for simple presentations, such as sore throat or ear infections. The true marginal cost of such patient visits in the ED is open to debate, however, given the high fixed expenses associated with operating a clinical environment 24 hours a day, 365 days a year. More problematic is the view that all emergency visits are avoidable and examples of failures of the health care delivery system. Clearly appropriate ED visits for patients range from heart attacks and strokes to stab wounds and motor vehicle accidents.

EPs can respond to the push for increased efficiency in the health care system by looking for ways to deliver their care with less waste. For example, efficiency measures focused on appropriateness of imaging studies are likely to be defined. By reducing inappropriate and unnecessary testing, EPs can improve the efficiency of emergency care without reducing quality or access.

The IOM defined equitable care as care that does not vary in quality based on personal characteristics (e.g., race, gender, geographic location, socioeconomic status). Although most EPs pride themselves on providing equal care to all, regardless of ability to pay and personal background, studies have documented racial disparities in emergency care.4245 Significant room exists for future research on equality of emergency care because it has received little research attention.

Special Focus: Care Coordination

Appropriate care coordination around transitions of care is a topic that cuts across multiple domains of quality. The totality of care cannot be timely, efficient, and patient centered if it is poorly coordinated during the many hand-offs that occur in health care. For example, almost 20% of Medicare beneficiaries are rehospitalized within 30 days of hospital discharge, and half of these patients did not have an intervening primary care visit.46

Care coordination is especially important for “hot spotters,” patients who are extreme outliers in health care use and cost.47 Although 10% of patients account for two thirds of all U.S. health care costs (Fig. 208.3), these extreme outliers (top 1%) can account for a significant fraction of costs by themselves. Intensive outpatient care for complex high-needs patients can significantly reduce health care costs. So far, these efforts have viewed ED visits as systems failures and have not engaged emergency caregivers, but such programs will likely be more successful if they integrate coordination of care plans between the outpatient providers and the local ED providers.

image

Fig. 208.3 The high concentration of U.S. health care expenditures.

(Modified from Conwell LJ, Cohen JW. Characteristics of people with high medical expenses in the U.S. civilian noninstitutionalized population, 2002. Statistical brief no. 73. Rockville, Md: Agency for Healthcare Research and Quality; 2005. [http://www.meps.ahrq.gov/mepsweb/data_files/publications/st73/stat73.pdf].)

More directly affecting ED care are the hand-offs between physicians at change of shift or on patient admission. Communication errors are the root cause of most safety events that occur in the ED. Many quality lapses occur when critical information is lost in such transitions. Many barriers to effective communication exist, including the need to balance conciseness with completeness, the lack of a standardized approach, and ambiguous time stamp for when transition of care occurs. Nonetheless, Cheung et al.48 provided with strategies to improve hand-offs, including reducing the number of unnecessary hand-offs, limiting interruptions and distractions, communicating outstanding tasks and anticipated changes along with a clear care plan, encouraging questioning of assessment, and signaling a clear moment in transition of care.

Special Focus: From “Never Events” to “Serious Reportable Events”

The most high-profile patient safety errors have been those that were serious and preventable. This is not surprising because explaining to a patient or patient’s family how a system allows such events to occur again and again is difficult. For example, at one hospital in Rhode Island, neurosurgeons operated on the wrong side of a patient’s brain three times over the course of 3 years, and an additional two other wrong-site surgical procedures occurred in this time.49,50 Such errors were initially labeled “never events”—events that should never occur. However, as the number of preventable events (e.g., hospital-acquired infections) grew, maintaining the paradigm of never events became difficult. Instead, the focus was changed from events that should never occur to ones that should not occur.

As such, in 2002, in an effort to develop a single standard list of serious medical errors requiring reporting, the National Quality Forum convened a multidisciplinary group that developed a consensus list of Serious Reportable Events in Healthcare (SREs). The goal of defining SREs was to guarantee that serious patient safety events would undergo systematic review to determine causes and contributing factors and that the findings would be used to improve care and avoid future events. Given public reporting requirements and potential nonpayment, SREs represent an important hospital patient safety priority.

Financial Strategies to Improve Health Care Quality and Value

Center for Medicare and Medicaid Services

As the country’s largest insurer and purchaser of health care services, the Centers for Medicare and Medicaid Services (CMS) is very interested in making sure its health care dollars are being well spent. Toward the aim of increased transparency and accountability, CMS launched a public reporting effort in 2004. Initially, participation in Hospital Compare (www.hospitalcompare.hhs.gov) was voluntary, and only quality measures related to pneumonia, AMI, and congestive heart failure were reported. Since then, the number of measures reported on this website has dramatically increased, and it includes risk-adjusted death and readmission rates, as well as patient satisfaction.

In 2007, the CMS rolled out a Physician Quality Reporting Initiative (PQRI), which has since been renamed the Physician Quality Reporting System (PQRS). Initially, physician groups received a 2% bonus for participating in the program. By 2014, that amount will decrease to 0.5%. Starting in 2016, physicians who do not participate in PQRS will see a 2% reduction in their Medicare payments. EPs have notably had one of the highest participation rates among all the specialties.

In January 2011, the CMS launched a Physician Compare website. Although it started with simple provider-specific information (e.g., whether a physician accepts Medicare and uses electronic prescribing), by 2015 it is expected to have public reports of physician-specific quality measures, including patient satisfaction. Developing physician profiles is replete with challenges.51 One of the most important unintended consequences of physician profiling is risk aversion (physician’s avoiding complex or high-risk patients), which inevitably leads to decreased health care access for minorities and economically disadvantaged populations.5254 Most problematic has been physician cost profiling because current methods misclassify physician ranking one fourth of the time.55 The reliability of these profiling schemes therefore is paramount.

The Affordable Care Act established an Innovation Center within the CMS to test innovative payment and health care delivery models, aimed at reducing health care expenditures and improving quality. For example, the Innovation Center will likely link payment to hospitals to their ability to reduce hospital-acquired infections and readmissions. The effectiveness of such financial incentive programs has been drawn into question. Looking at data from the United Kingdom’s Quality and Outcomes Framework, researchers did not find any improvement in outcome measures for patients treated before or after the introduction of the incentive program.56

Future Reimbursement Models

In both public and private sectors, a strong movement is leading away from purchasing health care services by volume and toward purchasing value (defined as health care value per dollar spent).57,58 Reimbursement models are evolving to motivate providers to be more cost and quality conscious. Since 2000, several schemes have emerged that have been called pay-for performance (P4P) programs. Many of these programs were simply fee-for-service models, with either a bonus or withhold based on achieving certain performance thresholds.

A newer, emerging reimbursement model is bundled payment, in which hospitals and providers share in the accountability for delivering value. Geisinger Health System’s ProvenCare program59 defined and implemented best practices for patients undergoing CABG and then offered risk-based pricing to insurers. Specifically, preoperative, inpatient, and postoperative care within 90 days was packaged into a fixed price and touted in the lay press as a “CABG warranty.” The success of this program in improving care and reducing costs brought the concept of bundled payments to the center stage of health care reform.

Global or capitated payment is also reemerging as a viable way to reimburse for care. Blue Cross/Blue Shield of Massachusetts reported that its global payment system improved patient care during its first year, including decreasing avoidable ED visits by 25% through one of its contracts.60 Under an alternative quality contract, physicians are provided a monthly per-patient budget, as well as bonuses for improving care. Future reimbursement models will inevitably center on performance measurement and accountability, with a likely shift in level of financial risk borne from payer to provider (Fig. 208.4).

To be fiscally viable within potential future reimbursement models, health care providers are being encouraged to organize themselves into accountable care organizations (ACOs).6163 ACOs are meant to encompass various provider arrangements (e.g., integrated delivery systems, multispecialty group practices, physician-hospital organizations, independent practice associations) that lead involved parties (e.g., physician group and hospital) to be jointly accountable for improving patient care and reducing spending. Unlike an HMO, this needs to be accomplished within the context of patients’ choice to visit providers internal or external to the ACO for which their care is attributed. Ideally, ACOs will be able to bend the cost curve of increasing health care expenditures. Many different prototypes have been reported in the lay and medical literature. Certification of ACOs for participation in the Affordable Care Act’s Shared Savings Program for Medicare still must occur. A fine balance will need to be reached because a liberal policy may lead to provider mergers and market dominance that have driven up costs in the past.

Measure Development

Future reimbursement models will depend on development of methodologically sound quality measures, and particularly on measures of outcomes of care. The most easily accessible outcome measures (e.g., mortality rate, readmission rates) are important but nonspecific measures of quality.

To date, numerous organizations have developed quality of care measures ranging from academic researchers, to individual hospitals and health systems, to federal agencies and their contractors. Although virtually anyone can develop a potential measure, several organizations have taken the lead in reviewing and endorsing measures of quality of care.

The American Medical Association’s Physician Consortium for Performance Improvement is composed of all the medical specialty societies and leads projects to develop measures for individual specialties and for conditions that cross specialties (e.g., stroke). Similarly, the National Center for Quality Assurance has taken the lead in developing measures of care for insurance plans and health care systems. The National Quality Forum (NQF) is a public-private venture whose mission is to improve health care by endorsing consensus-based national standards for measurement and public reporting of health care quality data. Payers and government agencies, such as CMS rely on the NQF to endorse valid performance measures.

Emergency medicine faces a unique challenge in developing and commenting on potential quality measures. Because EPs care for patients with all types of conditions, many specialties and condition-specific quality measure sets could measure and judge emergency care. As such, the American College of Emergency Physicians and the Society for Academic Emergency Medicine have lobbied to have EPs included in quality measure development panels that affect emergency medicine.

Without representation, poorly framed, yet nationally endorsed, quality measures may negatively affect emergency care. For example, the initial measure set for community-acquired pneumonia was developed using low-quality evidence from cross-sectional Medicare studies. EPs contended that these measures had many unintended consequences, including the administration of inappropriate antibiotics and excessive use of blood cultures.64 As more research was published showing that these measures were not linked to improved patient outcomes, the CMS revised the measures (Box 208.1).

Box 208.1 Blood Cultures for Community-Acquired Pneumonia

This measure serves as an example of a measure with a poor scientific basis and little regard for implementation feasibility. These guidelines were developed and approved without adequate input from the emergency medicine community. Despite feedback and modification, the current measures are not evidence based, they require laborious chart review, and performance is more easily improved by modifying documentation than by improving processes of care.

CAP, Community-acquired pneumonia; CMS, Centers for Medicare and Medicaid Services; ED, emergency department; ICU, intensive care unit.

Health Care Quality Lapses and Individual Providers

Despite an increased focus on transparency and systems improvement (Box 208.2), physicians and hospitals continue to underreport their errors and quality lapses. Too often, providers react to medical errors with shame, fear, and secrecy. To most physicians, the admission of wrongdoing has the dual effect of causing humiliation in front of patients and peers and introducing fear of lawsuits into everyday life. Ofri65 reported, “No doctor will easily confess to error when a core sense of self is at risk. … Unless we can defuse the shame and loss of self that accompany admitting medical errors, there will always be that taut inner core of resistance.”

Box 208.2 Quality Improvement Toolkit

In most emergency medicine residency programs, the morbidity and mortality conference is the most widely used error-based teaching conference. The culture of this conference helps shape physicians’ view of medical errors. One step in the right direction is for senior EPs to share their own mistakes with the next generation of physicians in an open and safe manner and to encourage reporting of errors, especially when appropriate peer-review protected systems are in place. Another cultural change is for EDs and hospitals to adopt policies encouraging rapid and open admissions of error to patients. Although individual physicians can adopt this strategy, it may be most effective if adopted by an institution and supported with changes in the way patients are compensated for medical errors. In 2001, the University of Michigan adopted a program of full disclosure of medical errors with offers of compensation. This approach both decreased the number of lawsuits and the time to resolution, without increasing the overall amount spent on medical malpractice.66

Remaining Challenges

Although more than a decade has passed since the IOM reports were published, studies still show that nearly 20% of patients continue to be harmed by their care.67 In addition, one in seven Medicare beneficiaries will experience adverse events while hospitalized, and SREs (e.g., wrong site surgery) continue to occur.68 Furthermore, physician involvement in quality improvement activities varies considerably and will become mandatory only as each specialty board incorporates quality improvement into its maintenance of certification programs.69 The American Board of Emergency Medicine requires a “patient care practice improvement activity” for those diplomates recertifying in 2013 and beyond.

No one can predict today what our health care system will look like in 3, 5, or 10 years. Current visions of bundled payment systems and ACOs are based more on theory than on experience. What one can be certain of is that pressure to address the rising costs of health care and the variable and often inadequate quality and safety of health care will continue. These pressures will lead to dramatic changes in the way physicians and hospitals are organized. The ED of 2020 may contain many more or many fewer patients, depending on how the system evolves. Yet EPs are uniquely qualified to understand quality and safety throughout health care systems and to mobilize multidisciplinary teams to address these challenges. EP engagement in improving care from the ED to the greater health care delivery system is needed now more than ever.

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