Abstract Background Overuse of antibiotics for upper respiratory tract infections (URIs) and acute bronchitis is a persistent and vexing problem. In the U.S., more than half of all patients with upper respiratory tract infections and acute bronchitis are treated with antibiotics annually, despite the fact that most cases are viral in etiology and are not responsive to antibiotics. Interventions aiming to reduce unnecessary antibiotic prescribing have had mixed results, and successes have been modest. The objective of this evaluation is to use mixed methods to understand why a multi-level intervention to reduce antibiotic prescribing for acute bronchitis among primary care providers resulted in measurable improvement in only one third of participating clinicians. Methods Clinician perspectives on print-based and electronic intervention strategies, and antibiotic prescribing more generally, were elicited through structured telephone surveys at high and low performing sites after the first year of intervention at the Geisinger Health System in Pennsylvania (n = 29). Results Compared with a survey on antibiotic use conducted 10 years earlier, clinicians demonstrated greater awareness of antibiotic resistance and how it is impacted by individual prescribing decisions—including their own. However, persistent perceived barriers to reducing prescribing included patient expectations, time pressure, and diagnostic uncertainty, and these factors were reported as differentially undermining specific intervention components’ effectiveness. An exam room poster depicting a diagnostic algorithm was the most popular strategy. Conclusions Future efforts to reduce antibiotic prescribing should address multi-level barriers identified by clinicians and tailor strategies to differences at individual clinician and group practice levels, focusing in particular on changing how patients and providers make decisions together about antibiotic use.

Converting the health care delivery system into a learning organization is a key strategy for improving health outcomes. Although the collaborative learning organization approach has been successful in neonatal intensive care units and disease-specific collaboratives, there are few examples in general medicine and none in adult medicine that have leveraged the role of hospitalists nationally across multiple institutions to implement improvements. The authors describe the rationale for and early work of the Hospital Medicine Reengineering Network (HOMERuN), a collaborative of hospitals, hospitalists, and multidisciplinary care teams founded in 2011 that seeks to measure, benchmark, and improve the efficiency, quality, and outcomes of care in the hospital and afterwards. Robust and timely evaluation, with learning and refinement of approaches across institutions, should accelerate improvement efforts. The authors review HOMERuN's collaborative model, which focuses on a community-based participatory approach modified to include hospital-based staff as well as the larger community. HOMERuN's initial project is described, focusing on care transition measurement using perspectives from the patient, caregiver, and providers. Next steps and sustainability of the organization are discussed, including benchmarking, collaboration, and effective dissemination of best practices to stakeholders.

Background

National quality indicators show little change in the overuse of antibiotics for uncomplicated acute bronchitis. We compared the effect of 2 decision support strategies on antibiotic treatment of uncomplicated acute bronchitis.

Methods

We conducted a 3-arm cluster randomized trial among 33 primary care practices belonging to an integrated health care system in central Pennsylvania. The printed decision support intervention sites (11 practices) received decision support for acute cough illness through a print-based strategy, the computer-assisted decision support intervention sites (11 practices) received decision support through an electronic medical record-based strategy, and the control sites (11 practices) served as a control arm. Both intervention sites also received clinician education and feedback on prescribing practices, as well as patient education brochures at check-in. Antibiotic prescription rates for uncomplicated acute bronchitis in the winter period (October 1, 2009, through March 31, 2010) following introduction of the intervention were compared with the previous 3 winter periods in an intent-to-treat analysis.

Results

Compared with the baseline period, the percentage of adolescents and adults prescribed antibiotics during the intervention period decreased at the printed decision support intervention sites (from 80.0% to 68.3%) and at the computer-assisted decision support intervention sites (from 74.0% to 60.7%) but increased slightly at the control sites (from 72.5% to 74.3%). After controlling for patient and clinician characteristics, as well as clustering of observations by clinician and practice site, the differences for the intervention sites were statistically significant from the control sites (P = .003 for control sites vs printed decision support intervention sites and P = .01 for control sites vs computer-assisted decision support intervention sites) but not between themselves (P = .67 for printed decision support intervention sites vs computer-assisted decision support intervention sites). Changes in total visits, 30-day return visit rates, and proportion diagnosed as having uncomplicated acute bronchitis were similar among the study sites.

Conclusions

Implementation of a decision support strategy for acute bronchitis can help reduce the overuse of antibiotics in primary care settings. The effect of printed vs computer-assisted decision support strategies for providing decision support was equivalent.

Trial registration

clinicaltrials.gov Identifier: NCT00981994.

Background

The HIV care continuum (diagnosis, linkage to care, retention in care, receipt of antiretroviral therapy (ART), viral suppression) has been used to identify opportunities for improving the delivery of HIV care. Continuum steps are typically calculated in a conditional manner, with the number of persons completing the prior step serving as the base population for the next step. This approach may underestimate the prevalence of viral suppression by excluding patients who are suppressed but do not meet standard definitions of retention in care. Understanding how retention in care and viral suppression interact and change over time may improve our ability to intervene on these steps in the continuum.

Methods

We followed 17,140 patients at 11 U.S. HIV clinics between 2010-2012. For each calendar year, patients were classified into one of five categories: (1) retained/suppressed, (2) retained/not-suppressed, (3) not-retained/suppressed, (4) not-retained/not-suppressed, and (5) lost to follow-up (for calendar years 2011 and 2012 only). Retained individuals were those completing ≥ 2 HIV medical visits separated by ≥ 90 days in the year. Persons not retained completed ≥ 1 HIV medical visit during the year, but did not meet the retention definition. Persons lost to follow-up had no HIV medical visits in the year. HIV viral suppression was defined as HIV-1 RNA ≤ 200 copies/mL at the last measure in the year. Multinomial logistic regression was used to determine the probability of patients' transitioning between retention/suppression categories from 2010 to 2011 and 2010 to 2012, adjusting for age, sex, race/ethnicity, HIV risk factor, insurance status, CD4 count, and use of ART.

Results

Overall, 65.8% of patients were retained/suppressed, 17.4% retained/not-suppressed, 10.0% not-retained/suppressed, and 6.8% not-retained/not-suppressed in 2010. 59.5% of patients maintained the same status in 2011 (kappa=0.458) and 53.3% maintained the same status in 2012 (kappa=0.437).

Conclusions

Not counting patients not-retained/suppressed as virally suppressed, as is commonly done in the HIV care continuum, underestimated the proportion suppressed by 13%. Applying the care continuum in a longitudinal manner will enhance its utility.

Background

Streptococcus pneumoniae continues to cause a variety of common clinical syndromes, despite vaccination programs for both adults and children. The total U.S. burden of pneumococcal disease is unknown.

Methods

We constructed a decision tree-based model to estimate U.S. healthcare utilization and costs of pneumococcal disease in 2004. Data were obtained from the 2004-2005 National (Hospital) Ambulatory Medical Care Surveys (outpatient visits, antibiotics) and the National Hospital Discharge Survey (hospitalization rates), and CDC surveillance data. Other assumptions regarding the incidence of each syndrome due to pneumococcus, expected health outcomes, and healthcare utilization were derived from literature and expert opinion. Healthcare and time costs used 2007 dollars.

Results

We estimate that, in 2004, pneumococcal disease caused 4.0 million illness episodes, 22,000 deaths, 445,000 hospitalizations, 774,000 emergency department visits, 5.0 million outpatient visits, and 4.1 million outpatient antibiotic prescriptions. Direct medical costs totaled $3.5 billion. Pneumonia (866,000 cases) accounted for 22% of all cases and 72% of pneumococcal costs. In contrast, acute otitis media and sinusitis (1.5 million cases each) comprised 75% of cases but only 16% of direct medical costs. Patients ≥ 65 years old, accounted for most serious cases and the majority of direct medical costs ($1.8 billion in healthcare costs annually). In this age group, pneumonia caused 242,000 hospitalizations, 1.4 million hospital days, 194,000 emergency department visits, 374,000 outpatient visits, and 16,000 deaths. However, if work loss and productivity are considered, the cost of pneumococcal disease among younger working adults (18-<50) nearly equaled those ≥ 65.

Conclusions

Pneumococcal disease remains a substantial cause of morbidity and mortality even in the era of routine pediatric and adult vaccination. Continued efforts are warranted to reduce serious pneumococcal disease, especially adult pneumonia.

Background:Many experts believe that hospitals with more frequent readmissions provide lower-quality care, but little is known about how the preventability of readmissions might change over the postdischarge time frame. Objective:To determine whether readmissions within 7 days of discharge differ from those between 8 and 30 days after discharge with respect to preventability. Design:Prospective cohort study. Setting:10 academic medical centers in the United States. Patients:822 adults readmitted to a general medicine service. Measurements:For each readmission, 2 site-specific physician adjudicators used a structured survey instrument to determine whether it was preventable and measured other characteristics. Results:Overall, 36.2% of early readmissions versus 23.0% of late readmissions were preventable (median risk difference, 13.0 percentage points [interquartile range, 5.5 to 26.4 percentage points]). Hospitals were identified as better locations for preventing early readmissions (47.2% vs. 25.5%; median risk difference, 22.8 percentage points [interquartile range, 17.9 to 31.8 percentage points]), whereas outpatient clinics (15.2% vs. 6.6%; median risk difference, 10.0 percentage points [interquartile range, 4.6 to 12.2 percentage points]) and home (19.4% vs. 14.0%; median risk difference, 5.6 percentage points [interquartile range, -6.1 to 17.1 percentage points]) were better for preventing late readmissions. Limitation:Physician adjudicators were not blinded to readmission timing, community hospitals were not included in the study, and readmissions to nonstudy hospitals were not included in the results. Conclusion:Early readmissions were more likely to be preventable and amenable to hospital-based interventions. Late readmissions were less likely to be preventable and were more amenable to ambulatory and home-based interventions. Primary Funding Source:Association of American Medical Colleges.