Decision support at the point of prescribing to increase formulary adherence.

PURPOSE: Study results demonstrating the effectiveness of order-entry clinical decision support (CDS) alerts as a tool for enforcing therapeutic interchange are presented. METHODS: A retrospective observational study was conducted at an academic medical center to evaluate formulary nonadherence before and after implementation of a fully electronic medical record with computerized prescriber order-entry (CPOE) technology configured to display therapeutic interchange alerts immediately on entry of orders for nonformulary agents. Formulary nonadherence (defined as the proportion of pharmacist-verified nonformulary orders to total verified orders) within eight medication classes was assessed during a six-month baseline period and two consecutive six-month periods after implementation. RESULTS: In the 12 months after implementation of the therapeutic interchange alerts, the overall rate of formulary nonadherence decreased by 65%, from 3.5% at baseline to 1.2% during the second 6-month postintervention period (p < 0.001). The total number of verified nonformulary orders decreased from 300 at baseline to 102 during the second postintervention period. The largest decreases in formulary nonadherence were observed in the intranasal steroid drug class (the rate of nonadherent orders declined by a total of 12 percentage points) and the nonbarbiturate sedatives and hypnotics class (a 5-point decline), with significant 6- and 12-month declines also documented in four of the remaining six drug classes. CONCLUSION: The incorporation of hard-stop CDS alerts into the CPOE system improved the overall rate of prescriber adherence to institutional therapeutic interchange protocols.

Drug-drug interaction checking assisted by clinical decision support: a return on investment analysis.

BACKGROUND: Drug-drug interactions (DDIs) are very prevalent in hospitalized patients. OBJECTIVES: To determine the number of DDI alerts, time saved, and time invested after suppressing clinically irrelevant alerts and adding clinical-decision support to relevant alerts. MATERIALS AND METHODS: The most frequently occurring DDIs were evaluated for clinical relevance by a multidisciplinary expert panel. Pharmacist evaluation of relevant DDIs was facilitated using computerized decision support systems (CDSS). During Phase 1, only CDSS-assisted DDI checking was implemented. During Phase 2, CDSS-assisted DDI checking remained in place, and clinically irrelevant DDIs were suppressed. In each phase, the number of alerts and duration of pharmacist DDI checking were compared to conventional DDI checking. In addition, the time invested to implement and configure the CDSS was compared to the time saved using CDSS-assisted DDI checking. RESULTS: CDSS-assisted DDI checking resulted in a daily decrease of DDI checking alerts from 65 to 47 alerts in Phase 1 (P = .03) and from 73 to 33 alerts in Phase 2 (P = .003). DDI checking duration decreased from 15 to 11 minutes (P = .044) and from 15½ to 8½ minutes (P = .001) in Phases 1 and 2, respectively. Almost 298 of the 392 hours required for implementation were invested by pharmacists. An annual timesaving of 30 hours yielded a return on investment of 9.8 years. CONCLUSION: CDSS-assisted DDI checking resulted in a 55% reduction of the number of alerts and a 45% reduction in time spent on DDI checking, yielding a return on investment of almost 10 years. Our approach can be used to refine other drug safety checking modules, increasing the efficiency of checking for drug safety without the need to add more staff pharmacists.

Formulary compliance and pharmacy labor costs associated with systematic formulary management strategy.

PURPOSE: The impact of a comprehensive hospital formulary management system on formulary compliance and pharmacy labor costs was evaluated. METHODS: The formulary management system consisted of monitoring nonformulary medication use, reviewing formulary medication use annually, and providing periodic feedback. Workflow scenarios for nonformulary medication requests were identified. Pharmacy personnel were interviewed to obtain the probability of occurrence of each scenario and the time involved. Labor costs were determined by multiplying the average total minutes spent on each activity by the corresponding average salaries per minute. Formulary compliance was compared before the implementation of the formulary management system (January to June 2008) with six consecutive six-month periods after implementation. RESULTS: Nonformulary medication use decreased from 17.8 to 5.9 nonformulary medication initiations per 100 admissions over a three-year period (p < 0.001). Time and labor costs associated with managing nonformulary medication requests varied from 4 to 69 minutes and from $3.68 to $27.28, respectively, depending on the scenario used. Automatically converting to a formulary alternative was the least labor-intensive option ($4.40 per request), followed by changing to a formulary alternative after consulting the prescriber ($9.92). CONCLUSION: A comprehensive formulary management system resulted in increased compliance to a formulary that matched the needs of the institution and minimized the number of nonformulary medication requests. Expanding pharmacists' therapeutic interchange authorities was the least labor-intensive way of managing nonformulary medication requests, and adding the most frequently used nonformulary medications to the formulary was the second least costly option.

Effects of a direct refill program for automated dispensing cabinets on medication-refill errors.

PURPOSE: The effects of a direct refill program for automated dispensing cabinets (ADCs) on medication-refill errors were studied. METHODS: This study was conducted in designated acute care areas of a 386-bed academic medical center. A wholesaler-to-ADC direct refill program, consisting of prepackaged delivery of medications and bar-code-assisted ADC refilling, was implemented in the inpatient pharmacy of the medical center in September 2009. Medication-refill errors in 26 ADCs from the general medicine units, the infant special care unit, the surgical and burn intensive care units, and intermediate units were assessed before and after the implementation of this program. Medication-refill errors were defined as an ADC pocket containing the wrong drug, wrong strength, or wrong dosage form. RESULTS: ADC refill errors decreased by 77%, from 62 errors per 6829 refilled pockets (0.91%) to 8 errors per 3855 refilled pockets (0.21%) (p < 0.0001). The predominant error type detected before the intervention was the incorrect medication (wrong drug, wrong strength, or wrong dosage form) in the ADC pocket. Of the 54 incorrect medications found before the intervention, 38 (70%) were loaded in a multiple-drug drawer. After the implementation of the new refill process, 3 of the 5 incorrect medications were loaded in a multiple-drug drawer. There were 3 instances of expired medications before and only 1 expired medication after implementation of the program. CONCLUSION: A redesign of the ADC refill process using a wholesaler-to-ADC direct refill program that included delivery of prepackaged medication and bar-code-assisted refill significantly decreased the occurrence of ADC refill errors.

Plerixafor as first- and second-line strategies for autologous stem cell mobilization in patients with non-Hodgkin's lymphoma or multiple myeloma.

STUDY OBJECTIVE: To describe the institutional experience of plerixafor plus filgrastim as the initial peripheral blood stem cell (PBSC) mobilization (first-line strategy) and as rescue therapy after failure with filgrastim plus cyclophosphamide (second-line strategy). DESIGN: Retrospective medical record review. SETTING: Academic medical center. PATIENTS: Thirty-three patients (median age 62 yrs) who received plerixafor between January 2008 and December 2009. MEASUREMENTS AND MAIN RESULTS: We collected data on total CD34(+) cell yield and number of apheresis sessions in both first-line and second-line plerixafor recipients. Mobilization with plerixafor plus filgrastim resulted in a median yield of 8.95 × 10(6) and 2.45 × 10(6) CD34(+) cells/kg in patients with multiple myeloma or non-Hodgkin's lymphoma, respectively. As rescue mobilization, plerixafor plus filgrastim successfully mobilized CD34(+) cells in 16 (84%) of 19 patients. When comparing first-line plerixafor plus filgrastim therapy with second-line therapy, we found an increase in CD34(+) yield and 1 less apheresis day in patients with multiple myeloma, but no difference in patients with non-Hodgkin's lymphoma. CONCLUSION: A regimen of plerixafor plus filgrastim successfully mobilized CD34(+) cells in a median of 1 apheresis day for patients with multiple myeloma and 2 apheresis days for patients with non-Hodgkin's lymphoma, including patients who failed initial filgrastim plus cyclophosphamide mobilization. Plerixafor plus filgrastim could be a viable first-line option in patients with multiple myeloma, as it improved CD34(+) cell yield and decreased number of apheresis days compared with second-line plerixafor plus filgrastim therapy, whereas it was comparable to second-line therapy in patients with non-Hodgkin's lymphoma.

High rates of venous thromboembolism prophylaxis did not increase the incidence of heparin-induced thrombocytopenia.

BACKGROUND: Venous thromboembolism (VTE) prophlaxis is recommended for most hospitalized patients. At a 505-bed urban academic medical center, the rate of VTE prophylaxis recently increased from 50%-55% to > 95% of eligible patients. Heparin-induced thrombocytopenia (HIT) is a potentially devastating, but rare, reaction to medications commonly used for VTE prophylaxis. METHODS: Patients were identified who were tested for HIT, treated with direct thrombin inhibitors (DTIs), or received International Classification of Diseases, 9th Revision codes consistent with HIT ("suspected HIT") from January 2005 through April 2008. Two physicians classified each patient as having confirmed, possible, or excluded HIT on the basis of laboratory testing, final diagnosis, and clinical course. The rate of suspected and confirmed HIT during the latter two years was compared to rates during the first (reference) year of the project. RESULTS: Some 430 unique patients had received HIT testing or DTI therapy for possible HIT. Thirteen cases of confirmed HIT were identified, of which 7 were due to treatment at the institution and 2 occurred while on VTE prophylaxis. HIT was confirmed in 0.02% of hospital admissions and only 3% of patients initially tested or treated for HIT. Rates of suspected and confirmed HIT did not change during the study period (Risk Ratios [95% confidence intervals] 0.976 [0.77-1.23] and 1.09 [0.39-2.99]). CONCLUSIONS: Optimizing the VTE prophylaxis rate to > 95% of eligible patients at a single academic institution did not cause an increase in the rate of HIT. Concerns about HIT should not limit implementation ofVTE prophylaxis protocols. HIT surveillance in patients on VTE prophylaxis may have a very low yield.

Effect of bar-code-assisted medication administration on medication administration errors and accuracy in multiple patient care areas.

PURPOSE: The effect of a commercially available bar-code-assisted medication administration (BCMA) technology on six indicators of medication administration accuracy and nine types of medication administration errors in distinct patient care areas were studied. METHODS: This prospective, before-and-after, observational study was conducted in two medical-surgical units, one medical intensive care unit (ICU), and one surgical ICU of a 386-bed academic teaching hospital. Nursing staff were observed administering medications one month before and three months after implementation of BCMA technology. Observations were conducted by two pharmacists and four pharmacy students on weekdays and weekends. Medication administration accuracy was measured using the accuracy indicator of the California Nursing Outcomes Coalition. RESULTS: The majority of medication administrations occurred during the 9 a.m. medication round. After BCMA implementation in the medical-surgical units, improved adherence to patient identification policies was observed, but more distractions of the nursing staff occurred and the medications administered were less frequently explained to the patient. Although an increase in wrong-time errors was observed in the medical-surgical units, the total number of medication errors did not change. When wrong-time errors were excluded, the rate of medication errors decreased by 58%. In the ICUs, the charting of medication administration improved after BCMA implementation, but total medication errors and wrong-time errors did not change. CONCLUSION: Implementing BCMA technology decreased medication administration errors in medical-surgical units but not in ICUs when time errors were excluded. BCMA technology affected different types of medication administration errors in different patient care areas.