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5. Use evidence‐based decision making: Provide consistent quality of care based on best available scientific knowledge. 6. Equitable: Provide care consistent in quality irrespective of gender, ethnicity, geographical, and socioeconomic factors. 6. Develop safety as a systems property: Develop systems of safety that mitigate error, promote patient safety, and reduce risk of injury. 7. Be transparent: Make information available to patients and families about health plans, hospitals, clinical practice, and alternative treatment options, including performance related to their safety, evidence‐based practice, and patient satisfaction. 8. Anticipate needs: Anticipate patient needs rather than respond to events. 9. Continuously decrease waste: Use limited resources wisely. 10. Cooperate among clinicians: Collaborate and coordinate care between clinicians and institutions.

      Source: Compiled with information from the Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academy Press; and Berwick, D. M. (2002). A user's manual for the IOM's ‘Quality Chasm’ report. Health Affairs, 2 (3), 80–90.

      Health Care Variation

      Groundbreaking research beginning in the 1970s and continuing into the 1990s demonstrated that there was significant variation in utilization of specific health care services associated with geographical location, provider preferences and training, type of health insurance, and patient‐specific factors such as age and gender (Adams, Fraser, & Abrams, 1973; Greenfield et al., 1992; Leape, 1992; Safran, Rogers, Tarlov, McHorney, & Ware Jr., 1997; Wennberg & Gittelsohn, 1973). Associations between utilization rates of health care services have been found with availability of services and technologies, for example, MRIs, hospital beds, practitioners (Joines, Hertz‐Picciotto, Carey, Gesler, & Suchindran, 2003), prevalence and severity of morbidities (Dunn, Lyman, & Marx, 2005; AHRQ, 2008b), race or ethnicity (AHRQ, 2008b), patient adherence, health‐seeking behaviors of patients (Calvocoressi et al., 2004), and many other factors. Variation in the delivery and quality of health services is also associated with socio‐demographics, hospital types (e.g., urban and rural, teaching and nonteaching), and clinical areas (e.g., heart disease, diabetes, pneumonia, and clinical preventive services). Regions of the country and health care providers with more resources had higher rates of use and cost. Efforts to decrease the variation of health care practices through standardization of care with quality, evidence‐based guidelines are important to improve clinical decision making, care delivery, health outcomes, and cost efficiency.

      Achieving health care transparency or truth in reporting is the ability to discover information about health care costs, medical errors, or practice preferences, preferably before receiving the service. Transparency is being encouraged by the CMS, though transparency can be hampered by the fear of litigation or reprisal against the health care provider. The Patient Safety and Quality Improvement Act of 2005 addresses such concerns by encouraging health care providers to participate in developing and implementing evidence‐based improvement initiatives. The Act also highlights the importance of recognizing and responding to the underlying hazards and risks to patient safety. Establishing national health benchmarks, such as those in Healthy People 2020 (USDHHS, 2010), is another strategy by which to achieve and measure quality improvement.

      Highly Reliable Health Care: Improvements to Standardize Care

Using the example of the management of heart disease, recent research findings illustrate the need for significant improvements to standardize the process of health care delivery. Each year, heart disease contributes to thousands of deaths. When evidence‐based standards are used to guide the care of the patient with heart disease. and aspirin and beta‐blockers are given to patients who have had a myocardial infarction, it can lower health care dollars and save lives associated with heart disease (Schulte, 2011). This is true, even if it is because aspirin use is being measured to assess provider performance (Williams, Schmaltz, Morton, Koss, & Loeb, 2005). Standardization of patient care can change the list of the top ten health care conditions, both in cost and mortality, by making patient care delivery more reliable (Table 2.8).

Table 2.8 Top 10 Causes of Death—Cost and Death

Heart disease: 199 billion Cancer: 174 billion Accidents: 75 billion Chronic lower respiratory conditions: 36 billion Stroke: 34 billion Alzheimer's disease: 215 billion Diabetes: 237 billion Influenza and pneumonia: 8.7 billion Nephritis, nephrotic syndrome and nephrosis :124 billion Intentional self‐harm: 69 billion

      Source: CDC. (2019). FastStats—Deaths and Mortality. Retrieved from www.cdc.gov/nchs/fastats/deaths.htm.

      Performance and Quality Measurement

      Performance and quality measurement is an essential component of health care improvement efforts. Performance and quality are measured to determine resource allocation, organize care delivery, assess clinician competency, and improve health care delivery processes. Hospitals and practitioners have been given past and present financial incentives to score well on measures of quality from both public and private health care payers. When the quality of care is measured, it improves (Brook, Kamberg, & McGlynn, 1996; Chassin & Galvin, 1998). possibly largely due to the Hawthorne effect, which has illustrated that observed activity shows improvement. Ramirez (2019) reports that more people receive evidence‐based care (EBC) for heart attack when they arrive at a hospital, hospital‐acquired conditions decreased from 2014 to 2017, that medicare 30‐day hospital readmission rates have declined, and that mortality rates within 30 days after hospital admission for heart attack, stroke, and pneumonia have decreased.

      From 2003 to 2013, the mortality rate for deaths amenable to health care in the U.S. declined by about 17%. More recently, the rate has increased slightly.

Nursing leaders have also recognized the need to establish classifications that can be used to measure nursing care. Selected classifications are listed in Table 2.9.

Table 2.9 Selected Classification Systems (List compiled by R. Hughes).

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North American Nursing Diagnosis Association (NANDA): www.nanda.org

Home Health Care Classification (HHCC): www.sabacare.com

PeriOperative Nursing Data Set: www.aorn.org

National Quality Forum‐Endorsed Nursing‐Sensitive Consensus Standards: www.qualityforum.org

Omaha System: www.omahasystem.org

ABC Codes: www.alternativelink.com

Logical Observation Identifiers Names and Codes: www.loinc.org

Nursing Interventions Classification: www.nursing.uiowa.edu

Nursing Outcomes Classification: www.nursing.uiowa.edu

National Database of Nursing Quality Indicators (NDNQI): www.nursingworld.org. (Search for NDNQI.)

SNOMED CT: www.snomed.org