Using Clinical Decision Support Within the Electronic Health Record to Reduce Incorrect Prescribing for Acute Sinusitis

Purpose: Acute sinusitis has viral etiology in more than 90% of cases, but antibiotics are prescribed for more than 80% of adults in the United States. While applications of computer-assisted guidelines have been found effective in reducing inaccurate prescribing for acute respiratory infections, there is a paucity of research focused specifically on the utilization of electronic best practice alerts (BPA) in improving treatment for acute sinusitis. Methods: This observational cohort study examined prescribing behavior for sinusitis at a single Federally Qualified Health Center 1 year prior and during the first year of implementation of a BPA in the electronic health record (EHR) reminding providers of the recommended treatment of sinusitis. The advisory included a link to national guidelines and a note template was installed to assist providers in documentation. The BPA appeared on the providers’ screen when an ICD-9 code of acute or bacterial sinusitis was entered during the patient visit. Results: After adjusting for select patient and provider factors, the computer-assisted guidelines effectively reduced the overall antibiotic prescribing among these patients by 31% (relative risk: 0.69, 95% confidence interval: 0.51–0.95) and reduced incorrect prescribing from 88.5% to 78.7% (P = 0.02). Conclusions: Clinical reminders within the EHR can be an effective tool to reduce inappropriate antibiotic use and improve providers’ decisions regarding the correct antibiotic choices for patients with acute sinusitis

Using Clinical Decision Support Within the Electronic Health Record to Reduce Incorrect Prescribing for Acute Sinusitis

Purpose: Acute sinusitis has viral etiology in more than 90% of cases, but antibiotics are prescribed for more than 80% of adults in the United States. While applications of computer-assisted guidelines have been found effective in reducing inaccurate prescribing for acute respiratory infections, there is a paucity of research focused specifically on the utilization of electronic best practice alerts (BPA) in improving treatment for acute sinusitis. Methods: This observational cohort study examined prescribing behavior for sinusitis at a single Federally Qualified Health Center 1 year prior and during the first year of implementation of a BPA in the electronic health record (EHR) reminding providers of the recommended treatment of sinusitis. The advisory included a link to national guidelines and a note template was installed to assist providers in documentation. The BPA appeared on the providers’ screen when an ICD-9 code of acute or bacterial sinusitis was entered during the patient visit. Results: After adjusting for select patient and provider factors, the computer-assisted guidelines effectively reduced the overall antibiotic prescribing among these patients by 31% (relative risk: 0.69, 95% confidence interval: 0.51–0.95) and reduced incorrect prescribing from 88.5% to 78.7% (P = 0.02). Conclusions: Clinical reminders within the EHR can be an effective tool to reduce inappropriate antibiotic use and improve providers’ decisions regarding the correct antibiotic choices for patients with acute sinusitis

Computer-Administered Screening of Reproductive-Aged Women for Diabetes Risk in Primary Care Settings, Feasibility and Acceptability of Such Screening, and Validity of Risk Assessments Based on Self-reported Weight

Introduction Obesity, a major public health problem, is the key modifiable component of diabetes risk. Addressing obesity and diabetes risk during primary care visits is recommended but, because of time constraints, is often difficult for health care providers to do. The purpose of this study was to determine whether technology can streamline risk assessment and leave more time to educate patients. We also tested the validity of self-reported weight in assessing diabetes risk.Methods We recruited English-speaking women aged 18 to 44 years who came to a clinic for medical appointments from July through October 2003. Study participants completed a self-administered computer questionnaire that collected the following data: weight, height, family history of diabetes, level of exercise, amount of television time, and daily servings of fruits and vegetables. Self-reported and scale-measured weights were compared to determine the effect of self-reported weight on results of the American Diabetes Association’s Diabetes Risk Test (DRT). In determining the sensitivity and specificity of self-reported weight, we used scale measurements as the standard.Results Complete data were collected on 231 women, including 214 women without a history of a diabetes diagnosis. Compared with DRT results (determined by scale-measured weight), questionnaire results (determined by self-reported weight) had sensitivities of 93.9% (95% confidence interval [CI], 85.2%–97.6%) for high risk for diabetes and 90.4% (95% CI, 83.3%–94.7%) for moderate risk. The specificity of the self-administered DRT for any diabetes risk was 97.8% (95% CI, 88.4%–99.6%). About half the women reported discussing nutrition and exercise with their health care providers.Conclusion Health care professionals can provide personalized diabetes education and counseling on the basis of information collected by self-administered computerized questionnaires. In general, patients provided a self-reported weight that did not substantially bias estimates of diabetes risk