Enhancements in healthcare information technology systems: customizing vendor-supplied clinical decision support for a high-risk patient population

Healthcare organizations continue to adopt information technologies with clinical decision support (CDS) to prevent potential medication-related adverse drug events. End-users who are unfamiliar with certain high-risk patient populations are at an increased risk of unknowingly causing medication errors. The following case describes a heart transplant recipient exposed to supra-therapeutic concentrations of tacrolimus during co-administration of ritonavir as a result of vendor supplied CDS tools that omitted an interaction alert. After review of 4692 potential tacrolimus-based DDIs between 329 different drug pairs supplied by vendor CDS, the severity of 20 DDIs were downgraded and the severity of 62 were upgraded. The need for institution-specific customization of vendor-provided CDS is paramount to ensure avoidance of medication errors. Individualized care will become more important as patient populations and institutions become more specialized. In the future, vendors providing integrated CDS tools must be proactive in developing institution-specific and easily customizable CDS tools.

[1]  Jared J Cash Alert fatigue. , 2009, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[2]  N. Laird,et al.  Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention , 1995 .

[3]  Randolph A. Miller,et al.  The anatomy of decision support during inpatient care provider order entry (CPOE): Empirical observations from a decade of CPOE experience at Vanderbilt , 2005, J. Biomed. Informatics.

[4]  N. Laird,et al.  Incidence of adverse drug events and potential adverse drug events , 1995 .

[5]  Steven R. Simon,et al.  Impact of Vendor Computerized Physician Order Entry in Community Hospitals , 2012, Journal of General Internal Medicine.

[6]  J. Bradley,et al.  Immunosuppressive agents in solid organ transplantation: Mechanisms of action and therapeutic efficacy. , 2005, Critical reviews in oncology/hematology.

[7]  Marc Berg,et al.  Overriding of drug safety alerts in computerized physician order entry. , 2006, Journal of the American Medical Informatics Association : JAMIA.

[8]  Philip F Halloran,et al.  Immunosuppressive drugs for kidney transplantation. , 2004, The New England journal of medicine.

[9]  Thomas H. Payne,et al.  Review Paper: Medication-related Clinical Decision Support in Computerized Provider Order Entry Systems: A Review , 2007, J. Am. Medical Informatics Assoc..

[10]  J. McCulloch,et al.  CHAPTER 7 – Implications for Prevention , 1972 .

[11]  D. Classen,et al.  Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. , 1997, JAMA.

[12]  S D Small,et al.  Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. , 1995, JAMA.

[13]  T E Starzl,et al.  Transplantation in HIV+ patients. , 1990, Transplantation.

[14]  A. Egberts,et al.  Adverse drug events in hospitalized patients A comparison of doctors, nurses and patients as sources of reports , 1999, European Journal of Clinical Pharmacology.

[15]  Peter Elkin,et al.  The Human Factors Engineering Approach to Biomedical Informatics Projects: State of the Art, Results, Benefits and Challenges , 2007, Yearbook of Medical Informatics.

[16]  David W. Bates,et al.  Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation. , 2011, Health affairs.

[17]  P. Stock,et al.  Solid organ transplantation is a reality for patients with HIV infection , 2006, Current HIV/AIDS reports.

[18]  David W. Bates,et al.  Reducing the frequency of errors in medicine using information technology. , 2001, Journal of the American Medical Informatics Association : JAMIA.

[19]  Christopher R. Zimmerman,et al.  Developing and implementing clinical decision support for use in a computerized prescriber-order-entry system. , 2010, American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists.

[20]  Marc Berg,et al.  Research Paper: Turning Off Frequently Overridden Drug Alerts: Limited Opportunities for Doing It Safely , 2008, J. Am. Medical Informatics Assoc..

[21]  Joan S. Ash,et al.  Some Unintended Consequences of Clinical Decision Support Systems , 2007, AMIA.