Quality initiatives: Key performance indicators for measuring and improving radiology department performance.

Key performance indicators (KPIs) are financial and nonfinancial measures that are used to define and evaluate the success of an organization. KPIs differ, depending on the nature of the organization and the organizational strategy; they are devised to help evaluate the progress of an organization toward achieving its long-term goals and fulfilling its vision. In healthcare organizations, performance assessment is especially critical for the development of best practices that can lead to improved outcomes in patient care, and KPIs have been incorporated into many healthcare management systems. In the future, radiology-specific KPIs such as those in use at the authors' institution may help provide a framework for measuring performance in radiology practice.

The outpatient availability score: an alternative approach to measuring demand.

Radiology business managers are challenged daily to maximize access, improve utilization, and enhance the efficiency of very costly resources. They rely on a variety of reports, metrics, and indicators to make operational decisions. Among the many metrics managers track today, one of the more inexact is the determination of outpatient appointment availability. The outpatient availability score (OAS) was developed to improve how access to resources is predicted in the department of radiology at Massachusetts General Hospital by accounting for patient preference. The OAS uses a range of predictors (thresholds) to determine the low, medium, and high likelihood that patients will find appointments suitable for them. The OAS can be customized to fit individual operations by adjusting these thresholds as fluctuations in demand dictate. The OAS is more useful than other current methodologies for measuring availability, such as next appointment availability or third next appointment availability, for the following reasons: (1) the OAS forecasts availability for an extended period of time, (2) the OAS forecasts the quantity of available appointments, and (3) the OAS is a better indication of the department's ability to satisfy patients' appointment needs. The OAS used in conjunction with other measures (such as the third next available appointment) of availability affords managers a clearer picture of access and the ability to deal proactively with demand to run more efficient operations.

Application of recently developed computer algorithm for automatic classification of unstructured radiology reports: validation study.

PURPOSE: To validate the accuracy of Lexicon Mediated Entropy Reduction (LEXIMER), a new information theory-based computer algorithm developed by the authors for independent analysis and classification of unstructured radiology reports based on the presence of clinically important findings (F(T), where (T) represents "true") and recommendations for subsequent action (R(T)). MATERIALS AND METHODS: The study was approved by the Human Research Committee of the institutional review board. Consecutive de-identified radiology reports (n = 1059) comprising results of barium studies (n = 99), computed tomography (n = 107), mammography (n = 90), magnetic resonance imaging (n = 108), nuclear medicine (n = 99), positron emission tomography (n = 106), radiography (n = 212), ultrasonography (n = 131), and vascular procedures (n = 107) were independently analyzed by two radiologists and then with LEXIMER to categorize the reports into F(T) and F(T)0 (containing or not containing clinically important findings) categories and R(T) and R(T)0 (containing or not containing recommendations for subsequent action) categories. Accuracy, sensitivity, specificity, and positive and negative predictive values of LEXIMER for placing reports into F(T) and F(T)0 and R(T) and R(T)0 categories were assessed by using appropriate statistical tests. RESULTS: There was strong interobserver concordance between the two radiologists for placing radiology reports into F(T) and R(T) categories (kappa = 0.9, P < .01). For the LEXIMER program, accuracy, sensitivity, specificity, and positive and negative predictive values, respectively, were 97.5% (95% confidence interval [CI]: 96.6%, 98.5%), 98.9% (95% CI: 97.9%, 99.6%), 94.9% (95% CI: 93.1%, 96.0%), 97.5% (95% CI: 96.6%, 98.0%), and 97.7% (95% CI: 95.8%, 98.8%) for placing radiology reports into F(T) and F(T)0 categories and 99.6% (95% CI: 99.2%, 99.9%), 98.2% (95% CI: 95.0%, 99.6%), 99.9% (95% CI: 99.4%, 99.99%), 99.4% (95% CI: 96.3%, 99.9%), and 99.7% (95% CI: 98.9%, 99.9%) for placing reports into R(T) and R(T)0 categories. CONCLUSION: LEXIMER is an accurate automated engine for evaluating the percentage positivity of clinically important findings and rates of recommendation for subsequent action in unstructured radiology reports.

Comparative effects of tobacco smoking and nasal nicotine.

OBJECTIVE: Compare the electroencephalographic (EEG) and cardiovascular effects of tobacco smoking and nasal nicotine in the same subjects. METHODS: Eleven volunteer smokers were studied after >10 h of overnight tobacco deprivation. Quantitative EEG was used to measure brain electrical changes produced by four different treatments. Each subject smoked a low (0.08 mg) and average nicotine (1 mg) yield cigarette on one test day and received placebo and nicotine nasal spray (0.5 mg/spray) on a second day in a counterbalanced design. EEG activity was measured from 16 scalp electrodes and analyzed as delta, theta, alpha (1), alpha (2), beta (1), and beta (2) frequency bands. Heart rate (HR), blood pressure (BP), and plasma venous nicotine concentrations (VNC) were monitored during both sessions. EEG data from all 16 channels at each of six frequencies were compared over 10 min using repeated measures ANOVA analysis. Changes in HR, BP, and VNC from baseline were compared using ANOVA followed by post hoc Scheffe's test. RESULTS: Smoking an average nicotine delivery cigarette resulted in highly significant decreases in alpha (1) activity, significant increases in alpha (2) activity, and significant increases in both HR and VNC compared to all other conditions. CONCLUSION: When smokers are allowed to pace themselves, cigarette smoking is far more effective than nasal nicotine in activating the EEG and increasing HR and VNC. This lack of equivalent physiological effects may explain the low success rate when nicotine nasal spray is used by those trying to quit smoking.