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Reducing Readmissions in Community-Acquired Pneumonia

Reducing Readmissions in Community-Acquired Pneumonia

In the United States, community-acquired pneumonia (CAP) is the leading cause of morbidity and mortality due to infection and most often strikes the elderly and individuals with comorbidities. The 30-day mortality rate for Medicare patients admitted to the hospital for CAP is about 12% and has not changed significantly in decades (Table 1). CAP has been shown to increase long-term mortality to as high as 40% within 1 year of admission. The infection is one of seven conditions that account for nearly 30% of potentially preventable readmissions in the 15-day window after initial hospital discharge. Estimates show that the cost of treating CAP exceeds $17 billion per year. Hospitalizing Patients With Community-Acquired Pneumonia “The decision on whether or not hospitalization is necessary for CAP is critical because there are multiple consequences,” says Thomas M. File, Jr., MD, MSc. “Hospitalizations can influence the cost of care, the intensity of diagnostic testing, and the selection of antimicrobial agents.” There are several advantages to outpatient treatment of CAP—when used appropriately—including cost, patient preference, faster convalescence, and fewer nosocomial complications. Hospitalization decisions should be based on several factors, including (among others): age over 50; significant underlying coexisting conditions; elevated blood urea nitrogen levels; and the presence of altered mental status or significant abnormalities in vital signs. “Readmission for CAP patients recently discharged after hospitalization represents an important, expensive, and often preventable adverse outcome,” Dr. File says. “The risk of readmission can be modified by the quality and type of care that is provided. Improving CAP readmission rates is the joint responsibility of hospitals and clinicians.” He adds that measuring readmission rates can help...
Data Standards for ACS & CAD

Data Standards for ACS & CAD

With the emergence of electronic health records (EHRs) and administrative and professional databases, it’s critical to facilitate clear communication and assure the accurate interchange of data and information. Clinical data standards are important for managing patients, assessing outcomes, and conducting research. Having a broad agreement on a common vocabulary and a standardized list of data elements helps lay the groundwork for future clinical registries and quality- improvement initiatives. It also can be used in the development of performance measures. An Important Update In 2013, the American College of Cardiology (ACC) and American Heart Association (AHA), in conjunction with 11 other organizations, developed a list of key data elements with standardized definitions for patients with acute coronary syndromes (ACS) and coronary artery disease (CAD). The document was published jointly in the Journal of the American College of Cardiology and Circulation. It updates information on elements specific to ACS that were released in 2001. CAD was added because of the overlap between the two conditions. The ACC/AHA publication listed key data elements and provided detailed definitions in seven categories, including demographics and admissions; history and risk factors; clinical presentation; diagnostic procedure; invasive therapeutic intervention; medications; and outcomes. The document is organized in tabular form to be a helpful tool for everyday use. Special attention is also given to important predictors of outcomes, including laboratory results and clinical presentation. This information should be mandatory reading for clinical investigators, quality assurance personnel, and research nurses. For cardiologists, the latest terminology and methods may seem obvious at first glance. However, even the most sophisticated practitioners can discover better ways to communicate and describe ambiguous...

Measuring the Quality of Diabetes Care

In 1995, the National Committee for Quality Assurance began the process of developing quality performance measures for diabetes care, which have become more sophisticated with time. Diabetes was one of the first conditions for which quality measures were developed because many disease-related factors can be quantified. Impact of Diabetes Quality Measures In the July 2011 issue of Diabetes Care, my colleagues and I published a consensus statement sponsored by the American Diabetes Association on the importance of diabetes quality measures. In our analysis, we found that diabetes care has improved dramatically since 1995. For example, the median national A1C goal was 8.6% in 1995, but it is now around 7.0%. Median systolic blood pressure and LDL cholesterol measurements have also dropped substantially. Physicians, most notably primary care physicians but also diabetes educators and endocrinologists, should be largely credited for these improvements because they have changed their approaches to managing the disease. It’s clear that quality measures for diabetes are here to stay and have contributed to at least some of the momentum toward improved care in recent years. Quality measures for diabetes are here to stay and have contributed to at least some of the momentum toward improved care in recent years. The potential unintended consequences of diabetes quality measures are a cause of concern. Standards of care proposed by the American Diabetes Association indicate that an A1C of less than 7.0% is appropriate for some patients while 8.0% is appropriate for others. The simplest solution would be to set the A1C target at less than 8.0% for quality measures, giving providers flexibility to tailor A1C goals based on...
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