Adherence to black box warnings for prescription medications in outpatients.

BACKGROUND: Few data are available regarding the prevalence of potentially dangerous drug-drug, drug-laboratory, and drug-disease interactions among outpatients. Our objectives were to determine how frequently clinicians prescribe drugs in violation of black box warnings for these issues and to determine how frequently such prescribing results in harm. METHODS: In an observational study of 51 outpatient practices using an electronic health record, we measured the frequency with which patients received prescriptions in violation of black box warnings for drug-drug, drug-laboratory, and/or drug-disease interactions. We performed medical record reviews in a sample of patients to detect adverse drug events. Multivariate analysis was conducted to assess the relationship of prescribing in violation of black box warnings to patient and clinician characteristics, adjusting for potential confounders and clustering. RESULTS: Of 324 548 outpatients who received a medication in 2002, 2354 (0.7%) received a prescription in violation of a black box warning. After adjustment, receipt of medication in violation of a black box warning was more likely when patients were 75 years or older or female. The number of medications taken, the number of medical problems, and the site of care were also associated with violations. Less than 1% of patients who received a drug in violation of a black box warning had an adverse drug event as a result. CONCLUSIONS: About 7 in 1000 outpatients received a prescription violating a black box warning. Few incidents resulted in detectable harm.

Resource utilization among patients with sepsis syndrome.

OBJECTIVE: To assess the resource utilization associated with sepsis syndrome in academic medical centers. DESIGN: Prospective cohort study. SETTING: Eight academic, tertiary-care centers. PATIENTS: Stratified random sample of 1,028 adult admissions with sepsis syndrome and all 248,761 other adult admissions between January 1993 and April 1994. The main outcome measures were length of stay (LOS) in total and after onset of sepsis syndrome (post-onset LOS) and total hospital charges. RESULTS: The mean LOS for patients with sepsis was 27.7 +/- 0.9 days (median, 20 days), with sepsis onset occurring after a mean of 8.1 +/- 0.4 days (median, 3 days). For all patients without sepsis, the LOS was 7.2 +/- 0.03 days (median, 4 days). In multiple linear regression models, the mean for patients with sepsis syndrome was 18.2 days, which was 11.0 days longer than the mean for all other patients (P < .0001), whereas the mean difference in total charges was $43,000 (both P < .0001). These differences were greater for patients with nosocomial as compared with community-acquired sepsis, although the groups were similar after adjusting for pre-onset LOS. Eight independent correlates of increased post-onset LOS and 12 correlates of total charges were identified. CONCLUSIONS: These data quantify the resource utilization associated with sepsis syndrome, and demonstrate that resource utilization is high in this group. Additional investigation is required to determine how much of the excess post-onset LOS and charges are attributable to sepsis syndrome rather than the underlying medical conditions.

Electronic health record feedback to improve antibiotic prescribing for acute respiratory infections.

OBJECTIVE: To examine whether the Acute Respiratory Infection (ARI) Quality Dashboard, an electronic health record (EHR)-based feedback system, changed antibiotic prescribing. STUDY DESIGN: Cluster randomized, controlled trial. METHODS: We randomly assigned 27 primary care practices to receive the ARI Quality Dashboard or usual care. The primary outcome was the intent-to-intervene antibiotic prescribing rate for ARI visits. We also compared antibiotic prescribing between ARI Quality Dashboard users and nonusers. RESULTS: During the 9-month intervention, there was no difference between intervention and control practices in antibiotic prescribing for all ARI visits (47% vs 47%; P = .87), antibiotic-appropriate ARI visits (65% vs 64%; P = .68), or non­antibiotic-appropriate ARI visits (38% vs 40%; P = .70). Among the 258 intervention clinicians, 72 (28%) used the ARI Quality Dashboard at least once. These clinicians had a lower overall ARI antibiotic prescribing rate (42% vs 50% for nonusers; P = .02). This difference was due to less antibiotic prescribing for non-antibiotic-appropriate ARIs (32% vs 43%; P = .004), including nonstreptococcal pharyngitis (31% vs 41%; P = .01) and nonspecific upper respiratory infections (19% vs 34%; P = .01). CONCLUSIONS: The ARI Quality Dashboard was not associated with an overall change in antibiotic prescribing for ARIs, although when used, it was associated with improved antibiotic prescribing. EHR-based quality reporting, as part of "meaningful use," may not improve care in the absence of other changes to primary care practice.

Effects of documentation-based decision support on chronic disease management.

OBJECTIVE: To evaluate whether a new documentation-based clinical decision support system (CDSS) is effective in addressing deficiencies in the care of patients with coronary artery disease (CAD) and diabetes mellitus (DM). STUDY DESIGN: Controlled trial randomized by physician. METHODS: We assigned primary care physicians (PCPs) in 10 ambulatory practices to usual care or the CAD/DM Smart Form for 9 months. The primary outcome was the proportion of deficiencies in care that were addressed within 30 days after a patient visit. RESULTS: The Smart Form was used for 5.6% of eligible patients. In the intention-to-treat analysis, patients of intervention PCPs had a greater proportion of deficiencies addressed within 30 days of a visit compared with controls (11.4% vs 10.1%, adjusted and clustered odds ratio =1.14; 95% confidence interval, 1.02-1.28; P = .02). Differences were more pronounced in the "on-treatment" analysis: 17.0% of deficiencies were addressed after visits in which the Smart Form was used compared with 10.6% of deficiencies after visits in which it was not used (P <.001). Measures that improved included documentation of smoking status and prescription of antiplatelet agents when appropriate. CONCLUSIONS: Overall use of the CAD/DM Smart Form was low, and improvements in management were modest. When used, documentation-based decision support shows promise, and future studies should focus on refining such tools, integrating them into current electronic health record platforms, and promoting their use, perhaps through organizational changes to primary care practices.

Frequency of potential azole drug-drug interactions and consequences of potential fluconazole drug interactions.

PURPOSE: To assess the frequency of potential azole-drug interactions and consequences of interactions between fluconazole and other drugs in routine inpatient care. METHODS: We performed a retrospective cohort study of hospitalized patients treated for systemic fungal infections with an oral or intravenous azole medication between July 1997 and June 2001 in a tertiary care hospital. We recorded the concomitant use of medications known to interact with azole antifungals and measured the frequency of potential azole drug interactions, which we considered to be present when both drugs were given together. We then performed a chart review on a random sample of admissions in which patients were exposed to a potential moderate or major drug interaction with fluconazole. The list of azole-interacting medications and the severity of interaction were derived from the DRUGDEX System and Drug Interaction Facts. RESULTS: Among the 4,185 admissions in which azole agents (fluconazole, itraconazole or ketoconazole) were given, 2,941 (70.3%) admissions experienced potential azole-drug interactions, which included 2,716 (92.3%) admissions experiencing potential fluconazole interactions. The most frequent interactions with potential moderate to major severity were co-administration of fluconazole with prednisone (25.3%), midazolam (17.5%), warfarin (14.7%), methylprednisolone (14.1%), cyclosporine (10.7%) and nifedipine (10.1%). Charts were reviewed for 199 admissions in which patients were exposed to potential fluconazole drug interactions. While four adverse drug events (ADEs) caused by fluconazole were found, none was felt to be caused by a drug-drug interaction (DDI), although in one instance fluconazole may have contributed. CONCLUSIONS: Potential fluconazole drug interactions were very frequent among hospitalized patients on systemic azole antifungal therapy, but they had few apparent clinical consequences.

Clinical impact of drug-drug interactions with systemic azole antifungals.

The number of drug-drug interactions is remarkably high among hospitalized patients receiving systemic azole antifungal agents. Recent estimates suggest that as many as 95% of hospitalized patients treated with azole antifungals may receive medications capable of producing a major or moderate pharmacokinetic interaction. The antifungal properties of the azoles stem from their propensity to inhibit fungal cytochrome P-450 enzymes. In humans, however, azole antifungals also interfere with several hepatic and intestinal cytochrome P-450 isoenzymes responsible for the metabolism of numerous drugs. As a result, the azole antifungals have drug-drug interactions with a plethora of drug classes, including H(1)-antihistamines, antineoplastics, steroids, antimicrobials, antiretrovirals, opioids, long acting barbiturates, cardiovascular agents, psychotropics and oral contraceptives. These interactions are so numerous that it is extremely difficult to remember them all and would be even harder to prospectively predict their consequences in an individual patient. In fact, any drug that shares the same cytochrome P-450 isoenzymes for metabolism may potentially to give rise to drug-drug interactions in vivo. Patients with specific polymorphisms are probably at especially high risk. Certain drug combinations with azoles should be absolutely avoided, while other combinations may be prescribed provided monitoring of drug levels is undertaken, dosage reduction of one or more of the drugs is made (as appropriate) and/or careful monitoring of clinical parameters is performed.

Relationship of pulmonary artery catheter use to mortality and resource utilization in patients with severe sepsis.

OBJECTIVE: To examine the relationship of pulmonary artery catheter (PAC) use to patient outcomes, including mortality rate and resource utilization, in patients with severe sepsis in eight academic medical centers. DESIGN: Case-control, nested within a prospective cohort study. SETTING: Eight academic tertiary care centers. PATIENTS: Stratified random sample of 1,010 adult admissions with severe sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The main outcome measures were in-hospital mortality, total hospital charge, and length of stay (LOS) for patients with and without PAC use. The case-matched subset of patients included 141 pairs managed with and without the use of a PAC. The mortality rate was slightly but not statistically significantly lower among the PAC use group compared with those not using a PAC (41.1% vs. 46.8%, p =.34). Even this trend disappeared after we adjusted for the Charlson comorbidity score and sepsis-specific Acute Physiology and Chronic Health Evaluation (APACHE) III (adjusted odds ratio, 1.02; 95% confidence interval, 0.61-1.72). In linear regression models adjusted for the Charlson comorbidity score, sepsis-specific APACHE III, surgical status, receipt of a steroid before sepsis onset, presence of a Hickman catheter, and preonset LOS, no significant differences were found for total hospital charges (139,207 US dollars vs. 148,190, adjusted mean comparing PAC and non-PAC group, p =.57), postonset LOS (23.4 vs. 26.9 days, adjusted mean, p =.32), or total LOS in intensive care unit (18.2 vs. 18.8 days, adjusted mean, p =.82). CONCLUSIONS: Among patients with severe sepsis, PAC placement was not associated with a change in mortality rate or resource utilization, although small nonsignificant trends toward lower resource utilization were present in the PAC group.

Severe sepsis: variation in resource and therapeutic modality use among academic centers.

BACKGROUND: Treatment of severe sepsis is expensive, often encompassing a number of discretionary modalities. The objective of the present study was to assess intercenter variation in resource and therapeutic modality use in patients with severe sepsis. METHODS: We conducted a prospective cohort study of 1028 adult admissions with severe sepsis from a stratified random sample of patients admitted to eight academic tertiary care centers. The main outcome measures were length of stay (LOS; total LOS and LOS after onset of severe sepsis) and total hospital charges. RESULTS: The adjusted mean total hospital charges varied from 69 429 dollars to US237 898 dollars across centers, whereas the adjusted LOS after onset varied from 15.9 days to 24.2 days per admission. Treatments used frequently after the first onset of sepsis among patients with severe sepsis were pulmonary artery catheters (19.4%), ventilator support (21.8%), pressor support (45.8%) and albumin infusion (14.4%). Pulmonary artery catheter use, ventilator support and albumin infusion had moderate variation profiles, varying 3.2-fold to 4.9-fold, whereas the rate of pressor support varied only 1.92-fold across centers. Even after adjusting for age, sex, Charlson comorbidity score, discharge diagnosis-relative group weight, organ dysfunction and service at onset, the odds for using these therapeutic modalities still varied significantly across centers. Failure to start antibiotics within 24 hours was strongly correlated with a higher probability of 28-day mortality (r2 = 0.72). CONCLUSION: These data demonstrate moderate but significant variation in resource use and use of technologies in treatment of severe sepsis among academic centers. Delay in antibiotic therapy was associated with worse outcome at the center level.