Implementation of Real-time ADE Surveillance and Decision Support (VA ADE)

The purpose of this study is to determine if an electronic alerting technology improves time to intervention for possible ADEs, identify what factors affect adoption of ADE alerts, and whether there is a cost benefit associated with the alerting technology.

Inpatient adverse drug events (ADEs) continue to be a major source of morbidity and mortality despite advances in computerized drug safety measures. Reports on the ability of computerized ADE alerts to prevent and mitigate ADEs are lacking. The aims of this project are to 1) Assess organizational, social, and cognitive factors that affect adoption of real-time ADE alerting technology; 2) Analyze the effect of the ADE alerting technology on management and rate of ADEs; and 3) Estimate the cost-benefit of the ADE alerting technology. This study will use a patient randomized design of computerized real-time ADE alerts intended for primary and secondary prevention of ADEs. The ADE alerts promise to reduce mortality, morbidity, and costs due to ADEs. This study will quantify the effect of the alerts in the hands of first-year medical residents and pharmacists. The study will explore the associations of organizational and soci-cognitive barriers and facilitators with the adoption of the ADE alert technology. At the cognitive level, it will explore whether ADE Alerts change user bias in diagnosing ADEs or whether the alerts heighten sensitivity to drug problems.

Arm 1 is a random intervention group in which half of the patients admitted to the VASLCHCS during study time period will be randomly selected. Providers will see ADE alerts for all patient in the randomly selected experimental group

A note in CPRS alerting providers that patients are at risk for an adverse event based on prescription and lab value histories.

From the time an ADE alert fires in CPRS until the time action has been taken, i.e. an order placed, up to 24 hours.

Inclusion Criteria: - All patients admitted to the SLCVAMC at time of study. Exclusion Criteria: - There are no exclusions.

LaFleur J, McAdam-Marx C, Alder SS, Sheng X, Asche CV, Nebeker J, Brixner DI, Silverman SL. Clinical risk factors for fracture among postmenopausal patients at risk for fracture: a historical cohort study using electronic medical record data. J Bone Miner Metab. 2011 Mar;29(2):193-200. doi: 10.1007/s00774-010-0207-y. Epub 2010 Aug 6.

Rupper RW, Bair BD, Sauer BC, Nebeker JR, Shinogle J, Samore M. Out-of-pocket pharmacy expenditures for veterans under medicare part D. Med Care. 2007 Oct;45(10 Supl 2):S77-80. doi: 10.1097/MLR.0b013e3180413871.

Weir CR, Nebeker JR. Critical issues in an electronic documentation system. AMIA Annu Symp Proc. 2007 Oct 11;2007:786-90.

Nebeker JR, Yarnold PR, Soltysik RC, Sauer BC, Sims SA, Samore MH, Rupper RW, Swanson KM, Savitz LA, Shinogle J, Xu W. Developing indicators of inpatient adverse drug events through nonlinear analysis using administrative data. Med Care. 2007 Oct;45(10 Supl 2):S81-8. doi: 10.1097/MLR.0b013e3180616c2c.

Boockvar KS, Livote EE, Goldstein N, Nebeker JR, Siu A, Fried T. Electronic health records and adverse drug events after patient transfer. Qual Saf Health Care. 2010 Oct;19(5):e16. doi: 10.1136/qshc.2009.033050. Epub 2010 Aug 19.

Kaafarani HM, Rosen AK, Nebeker JR, Shimada S, Mull HJ, Rivard PE, Savitz L, Helwig A, Shin MH, Itani KM. Development of trigger tools for surveillance of adverse events in ambulatory surgery. Qual Saf Health Care. 2010 Oct;19(5):425-9. doi: 10.1136/qshc.2008.031591. Epub 2010 May 31.

Olola CH, Rowan B, Narus S, Smith M, Hastings T, Poynton M, Nebeker J, Hales J, Evans RS. Implementation of an emergency medical card and a continuity of care report using continuity of care standard. Methods Inf Med. 2009;48(6):519-30. doi: 10.3414/ME09-01-0003. Epub 2009 Nov 5.