Faculty Bibliography

BACKGROUND: Previous studies have suggested that weekend hospital care is inferior to weekday care and that this difference may be related to diminished care intensity. The purpose of this study was to determine whether a metric for measuring intensity of hospital care based on utilization of the electronic health record (EHR) was associated with patient-level outcomes. METHODS: We performed a cohort study of hospitalizations at an academic medical center. Intensity of care was defined as the hourly number of provider accessions of the electronic health record, termed "EHR interactions." Hospitalizations were categorized based on the mean difference in EHR interactions between the first Friday and Saturday of hospitalization. We used regression models to determine the association of these categories with patient outcomes after adjusting for covariates. RESULTS: EHR interactions decreased from Friday to Saturday in 77% of the 9,051 hospitalizations included in the study. As compared to hospitalizations with no change in Friday to Saturday EHR interactions, the relative lengths of stay for hospitalizations with a small, moderate, and large decrease in EHR interactions were 1.05 (95% CI 1.00-1.10), 1.11 (95% CI 1.05-1.17), and 1.25 (95% CI 1.15-1.35), respectively. Although a large decrease in EHR interactions was associated with in-hospital mortality, these findings were not significant after risk adjustment (odds ratio 1.74, 95% CI 0.93-3.25). CONCLUSIONS: Intensity of inpatient care, measured by EHR interactions, significantly diminished from Friday to Saturday, and this decrease was associated with length of stay. Hospitals should consider monitoring and correcting temporal fluctuations in care intensity.

OBJECTIVES: The study sought to assess the quality of care for heart failure patients who are hospitalized for all causes. BACKGROUND: Performance measures for heart failure target patients with a principal diagnosis of heart failure. However, patients with heart failure are commonly hospitalized for other causes and may benefit from treatments such as angiotensin-converting enzyme (ACE) inhibitors for left ventricular (LV) systolic dysfunction. METHODS: We assessed rates of compliance with care measures for patients hospitalized with acute or chronic heart failure in the ARIC (Atherosclerosis Risk In Communities) study surveillance catchment area from 2005 to 2009. Rates of compliance were compared between patients with a principal discharge diagnosis of heart failure and those with another principal discharge diagnosis. RESULTS: Of 4,345 hospitalizations of heart failure patients, 39.6% carried a principal diagnosis of heart failure. Patients with a principal heart failure diagnosis had higher rates of LV function assessment (89.1% vs. 82.5%; adjusted prevalence ratio [aPR]: 1.07; 95% confidence interval [CI]: 1.04 to 1.10) and discharge ACE inhibitor/angiotensin receptor blocker (ARB) in LV dysfunction (64.1% vs. 56.3%; aPR: 1.11; 95% CI: 1.03 to 1.20) as compared to patients hospitalized for another cause. LV assessment and ACE inhibitor/ARB use were associated with reductions in 1-year post-discharge mortality (adjusted odds ratio: 0.66, 95% CI: 0.51 to 0.85; adjusted odds ratio: 0.72, 95% CI: 0.54 to 0.96, respectively) that did not differ for patients with versus without a principal heart failure diagnosis. CONCLUSIONS: Compared with individuals hospitalized with a principal diagnosis of heart failure, heart failure patients hospitalized for other causes were less likely to receive guideline recommended care. Quality initiatives may improve care by targeting hospitalizations with either principal or secondary heart failure diagnoses.

BACKGROUND: Exercise testing with echocardiography or myocardial perfusion imaging is widely used to risk-stratify patients with suspected coronary artery disease. However, reports of diagnostic performance rarely adjust for referral bias, and this practice may adversely influence patient care. Therefore, we evaluated the potential impact of referral bias on diagnostic effectiveness and clinical decision-making. METHODS AND RESULTS: Searching PubMed and EMBASE (1990-2012), 2 investigators independently evaluated eligibility and abstracted data on study characteristics and referral patterns. Diagnostic performance reported in 4 previously published meta-analyses of exercise echocardiography and myocardial perfusion imaging was adjusted using pooled referral rates and Bayesian methods. Twenty-one studies reported referral patterns in 49 006 patients (mean age 60.7 years, 39.6% women, and 0.8% prior history of myocardial infarction). Catheterization referral rates after normal and abnormal exercise tests were 4.0% (95% CI, 2.9% to 5.0%) and 42.5% (36.2% to 48.9%), respectively, with odds ratio for referral after an abnormal test of 14.6 (10.7 to 19.9). After adjustment for referral, exercise echocardiography sensitivity fell from 84% (80% to 89%) to 34% (27% to 41%), and specificity rose from 77% (69% to 86%) to 99% (99% to 100%). Similarly, exercise myocardial perfusion imaging sensitivity fell from 85% (81% to 88%) to 38% (31% to 44%), and specificity rose from 69% (61% to 78%) to 99% (99% to 100%). Summary receiver operating curve analysis demonstrated only modest changes in overall discriminatory power but adjusting for referral increased positive-predictive value and reduced negative-predictive value. CONCLUSIONS: Exercise echocardiography and myocardial perfusion imaging are considerably less sensitive and more specific for coronary artery disease after adjustment for referral. Given these findings, future work should assess the comparative ability of these and other tests to rule-in versus rule-out coronary artery disease.

BACKGROUND: Hospital care on weekends has been associated with reduced quality and poor clinical outcomes, suggesting that decreases in overall intensity of care may have important clinical effects. We describe a new measure of hospital intensity of care based on utilization of the electronic health record (EHR). METHODS: We measured global intensity of care at our academic medical center by monitoring the use of the EHR in 2011. Our primary measure, termed EHR interactions, was the number of accessions of a patient's electronic record by a clinician, adjusted for hospital census, per unit of time. Our secondary measure was percent of total available central processing unit (CPU) power used to access EHR servers at a given time. RESULTS: EHR interactions were lower on weekend days as compared to weekdays at every hour (P < 0.0001), and the daytime peak in intensity noted each weekday was blunted on weekends. The relative rate and 95% confidence interval (CI) of census-adjusted record accessions per patient on weekdays compared with weekends were: 1.76 (95% CI: 1.74-1.77), 1.52 (95% CI: 1.50-1.55), and 1.14 (95% CI: 1.12-1.17) for day, morning/evening, and night hours, respectively. Percent CPU usage correlated closely with EHR interactions (r = 0.90). CONCLUSIONS: EHR usage is a valid and easily reproducible measure of intensity of care in the hospital. Using this measure we identified large, hour-specific differences between weekend and weekday intensity. EHR interactions may serve as a useful measure for tracking and improving temporal variations in care that are common, and potentially deleterious, in hospital systems. Journal of Hospital Medicine 2013;8:513-518. (c) 2013 Society of Hospital Medicine.

OBJECTIVE To examine the association between diabetes, glycemic control, and risk of fracture-related hospitalization in the Atherosclerosis Risk in Communities (ARIC) Study. RESEARCH DESIGN AND METHODS Fracture-related hospitalization was defined using International Classification of Diseases, 9th revision, codes (733.1-733.19, 733.93-733.98, or 800-829). We calculated the incidence rate of fracture-related hospitalization by age and used Cox proportional hazards models to investigate the association of diabetes with risk of fracture after adjustment for demographic, lifestyle, and behavioral risk factors. RESULTS There were 1,078 incident fracture-related hospitalizations among 15,140 participants during a median of 20 years of follow-up. The overall incidence rate was 4.0 per 1,000 person-years (95% confidence interval [CI], 3.8-4.3). Diagnosed diabetes was significantly and independently associated with an increased risk of fracture (adjusted hazard ratio [HR], 1.74; 95% CI, 1.42-2.14). There also was a significantly increased risk of fracture among persons with diagnosed diabetes who were treated with insulin (HR, 1.87; 95% CI, 1.15-3.05) and among persons with diagnosed diabetes with hemoglobin A1c (HbA1c) >/=8% (1.63; 1.09-2.44) compared with those with HbA1c <8%. Undiagnosed diabetes was not significantly associated with risk of fracture (HR, 1.12; 95% CI, 0.82-1.53). CONCLUSIONS This study supports recommendations from the American Diabetes Association for assessment of fracture risk and implementation of prevention strategies in persons with type 2 diabetes, particularly those persons with poor glucose control.

The purpose of this study was to examine utilization and growth in echocardiography among the general population of Ontario between 2001 and 2009. The age- and sex-adjusted rates of echocardiography grew from 39.1 per 1,000 persons in 2001 to 59.9 per 1,000 persons in 2009, for an annual rate of increase of 5.5%. Repeat echocardiograms increased at a rate of 10.6% per year and accounted for 25.3% of all procedures in 2009 as compared to 18.5% in 2002. While significant increases in echocardiography utilization were observed, opportunities may exist to improve the clinical utility of the echocardiograms performed in Ontario.

OBJECTIVE: We sought to characterize temporal trends in hospitalizations with heart failure as a primary or secondary diagnosis. BACKGROUND: Heart failure patients are frequently admitted for both heart failure and other causes. METHODS: Using the Nationwide Inpatient Sample (NIS), we evaluated trends in heart failure hospitalizations between 2001 and 2009. Hospitalizations were categorized as either primary or secondary heart failure hospitalizations based the location of heart failure in the discharge diagnosis. National estimates were calculated using the sampling weights of the NIS. Age- and gender-standardized hospitalization rates were determined by dividing the number of hospitalizations by the United States population in a given year and using direct standardization. RESULTS: The number of primary heart failure hospitalizations in the United States decreased from 1,137,944 in 2001 to 1,086,685 in 2009, while secondary heart failure hospitalizations increased from 2,753,793 to 3,158,179 over the same period. Age- and gender-adjusted rates of primary heart failure hospitalizations decreased steadily over 2001-2009, from 566 to 468 per 100,000 people. Rates of secondary heart failure hospitalizations initially increased, from 1370 to 1476 per 100,000 from 2001-2006, then decreased to 1359 per 100,000 in 2009. Common primary diagnoses for secondary heart failure hospitalizations included pulmonary disease, renal failure, and infections. CONCLUSIONS: Although primary heart failure hospitalizations declined, rates of hospitalizations with a secondary diagnosis of heart failure were stable in the past decade. Strategies to reduce the high burden of hospitalizations of heart failure patients should include consideration of both cardiac disease and non-cardiac conditions.