Amy J. Grizzle

Drug-Related Morbidity and Mortality: Updating the Cost-of-Illness Model

OBJECTIVE To update the 1995 estimate of

Pharmacist workload and pharmacy characteristics associated with the dispensing of potentially clinically important drug-drug interactions

76.6 billion for the annual cost of drug-related morbidity and mortality resulting from drug-related problems (DRPs) in the ambulatory setting in the United States to reflect current treatment patterns and costs. DESIGN For this study, we employed the decision-analytic model developed by Johnson and Bootman. We used the models original design and probability data, but used updated cost estimates derived from the current medical and pharmaceutical literature. Sensitivity analyses were performed on cost data and on probability estimates. SETTING Ambulatory care environment in the United States in the year 2000. PATIENTS AND OTHER PARTICIPANTS A hypothetical cohort of ambulatory patients. MAIN OUTCOME MEASURES Average cost of health care resources needed to manage DRPs. RESULTS As estimated using the decision-tree model, the mean cost for a treatment failure was

Recommendations to Improve the Usability of Drug-Drug Interaction Clinical Decision Support Alerts

977. For a new medical problem, the mean cost was

Consensus recommendations for systematic evaluation of drug-drug interaction evidence for clinical decision support.

1,105, and the cost of a combined treatment failure and resulting new medical problem was

Contemporary Pharmacologic Treatments for Spasticity of the Upper Limb After Stroke: A Systematic Review

1,488. Overall, the cost of drug-related morbidity and mortality exceeded

IMPACT - Integrative Medicine PrimAry Care Trial: protocol for a comparative effectiveness study of the clinical and cost outcomes of an integrative primary care clinic model

177.4 billion in 2000. Hospital admissions accounted for nearly 70% (

Recommendations for selecting drug–drug interactions for clinical decision support

121.5 billion) of total costs, followed by long-term-care admissions, which accounted for 18% (

Critical issues associated with drug–drug interactions: Highlights of a multistakeholder conference

32.8 billion). CONCLUSION Since 1995, the costs associated with DRPs have more than doubled. Given the economic and medical burdens associated with DRPs, strategies for preventing drug-related morbidity and mortality are urgently needed.

Development of computerized alerts with management strategies for 25 serious drug–drug interactions

Background:Drug-drug interactions (DDIs) are preventable medical errors, yet exposure to DDIs continues despite systems that are designed to prevent such exposures. The purpose of this study was to examine pharmacy characteristics that may be associated with dispensed potential DDIs. Methods:This study combined survey data from community pharmacies in 18 metropolitan statistical areas with pharmacy claims submitted to 4 pharmacy benefit managers (PBMs) over a 3-month period from January 1, 2003 to March 31, 2003. Pharmacy characteristics of interest included prescription volume, the number of full-time equivalent pharmacists and pharmacy staff, computer software programs, and the ability to modify those programs with respect to DDI alerts, the use of technologies to assist in receiving, filling and dispensing medication orders, and prescription volume. The dependent variable in this study was the rate of dispensed medications that may interact. Results:A total of 672 pharmacies were included in the analysis. On average (±SD), the respondents filled 1375 ± 691 prescriptions per week, submitted 17,948 ± 23,889 pharmacy claims to the participating PBMs, had 1.2 ± 0.3 full-time equivalent pharmacists per hour open, and 545 (81%) were affiliated with a chain drug store organization. Factors significantly related to an increased risk of dispensing a potential DDI included pharmacist workload (odds ratio [OR] 1.03; 95% confidence interval [CI] 1.028–1.048), pharmacy staffing (OR 1.10; 95% CI: 1.09–1.11), and various technologies (eg, sophisticated telephone systems, internet receipt of orders, and refill requests) that assist with order processing, and the ability to modify DDI alert-screening sensitivity and detailed pharmacological information about DDIs. Conclusions:This study found that there was an increase in the risk of dispensing a potential DDI with higher pharmacist and pharmacy workload, use of specific automation, and dispensing software programs providing alerts and clinical information.

A survey of how drug information experts search for evidence about potential drug-drug interactions (Preprint)

OBJECTIVE To establish preferred strategies for presenting drug-drug interaction (DDI) clinical decision support alerts. MATERIALS AND METHODS A DDI Clinical Decision Support Conference Series included a workgroup consisting of 24 clinical, usability, and informatics experts representing academia, health information technology (IT) vendors, healthcare organizations, and the Office of the National Coordinator for Health IT. Workgroup members met via web-based meetings 12 times from January 2013 to February 2014, and two in-person meetings to reach consensus on recommendations to improve decision support for DDIs. We addressed three key questions: (1) what, how, where, and when do we display DDI decision support? (2) should presentation of DDI decision support vary by clinicians? and (3) how should effectiveness of DDI decision support be measured? RESULTS Our recommendations include the consistent use of terminology, visual cues, minimal text, formatting, content, and reporting standards to facilitate usability. All clinicians involved in the medication use process should be able to view DDI alerts and actions by other clinicians. Override rates are common but may not be a good measure of effectiveness. DISCUSSION Seven core elements should be included with DDI decision support. DDI information should be presented to all clinicians. Finally, in their current form, override rates have limited capability to evaluate alert effectiveness. CONCLUSION DDI clinical decision support alerts need major improvements. We provide recommendations for healthcare organizations and IT vendors to improve the clinician interface of DDI alerts, with the aim of reducing alert fatigue and improving patient safety.