Advertisement
Am J Health-Syst Pharm
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

American Journal of Health-System Pharmacy, Vol. 63, Issue 19, 1876-1881
Copyright © 2006 by American Society of Health-System Pharmacists
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kane-Gill, S.
Right arrow Articles by Weber, R. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kane-Gill, S.
Right arrow Articles by Weber, R. J.

Practice Reports

Adverse-drug-event rates for high-cost and high-use drugs in the intensive care unit

Sandra Kane-Gill, Rhonda S. Rea, Margaret M. Verrico and Robert J. Weber

SANDRA KANE-GILL, PHARM.D., M.SC., is Assistant Professor, Department of Pharmacy and Therapeutics, Center for Pharmacoinformatics and Outcomes Research, School of Pharmacy, University of Pittsburgh (UP), Pittsburgh, PA. RHONDA S. REA, PHARM.D., is Assistant Professor, Department of Pharmacy and Therapeutics, School of Pharmacy, UP, and Critical Care Specialist, Medical Intensive Care Unit, University of Pittsburgh Medical Center (UPMC), Pittsburgh. MARGARET M. VERRICO, B.S., is Assistant Professor, Department of Pharmacy and Therapeutics, School of Pharmacy, UP, and Drug Information Pharmacist, UP Drug Information Center, UPMC. ROBERT J. WEBER, M.S., FASHP, is Associate Professor and Chairman, Department of Pharmacy and Therapeutics, School of Pharmacy, UP, and Chief Pharmacy Officer, UPMC.

Address correspondence to Dr. Kane-Gill at the Center for Pharmacoinformatics and Outcomes Research, University of Pittsburgh, 918 Salk Hall, 3501 Terrace Street, Pittsburgh, PA 15261 (kanesl{at}upmc.edu).


Purpose. The rates of adverse drug events (ADEs) associated with high-cost and high-use drugs in the intensive care unit (ICU) were studied.

Methods. This retrospective analysis was conducted from October 1997 through June 2001 in a 647-bed academic medical center with over 120 ICU beds. Adult patients with a documented ADE occurring in the ICU were included in the analysis. ADE information, including suspected medication, causality, preventability, and severity, was extracted from the institutional ADE database. Published definitions of ADEs and published scales for causality and severity assessments were used. High-cost medications were those in the top 50% of cumulative ICU medication costs, and high-use medications accounted for the upper 50% of all medications used in the ICU. Between-group comparisons of ADE rates, preventability, and severity associated with high-cost and high-use medications were conducted.

Results. Of the 17 medications that were considered high cost, 9 (53%) were associated with ADEs. Of the 15 medications that met the criteria for high-use drugs, 12 (80%) were associated with ADEs. The rates of ADEs associated with high-cost and high-use drugs did not significantly differ (43% versus 75%, respectively; p = 0.098). ADEs associated with high-cost and high-use medications were categorized as mild (15% versus 10%, respectively), moderate (52% versus 50%, respectively), and severe (33% versus 40%, respectively) (p > 0.05).

Conclusion. The frequency, severity, and preventability of ADEs in the ICU were not associated with a drug’s cost or frequency of use. Monitoring priorities of the critical care pharmacist should not be dictated by cost alone but should include frequency of use and the potential for causing an ADE.

Index terms: Costs; Drug use; Drugs, adverse reactions; Errors, medication; Hospitals; Pharmacists, hospital

 
Adverse drug events (ADEs) occur in approximately 30% of hospitalized patients, and patients in the intensive-care-unit (ICU) setting are at greater risk of having ADEs.1,2 The increased ADE risk for these critically-ill patients is related to the higher number of medications administered, acute changes in organ function (altering the pharmacokinetics of drugs), and increased length of hospital stay.3 For example, the incidence of ADEs in a medical ICU was 19 events per 1000 patient days, higher than the rate reported for general care units (10 events per 1000 patient days).4

In the past, ADE prevention efforts by institutions, professional organizations and the government have been limited2,4,5 because of the labor and expense involved with prospective ADE surveillance.6 The recent public interest in patient safety is now shifting the paradigm toward ADE prevention.7,8 The presence of pharmacists in the ICU and general medicine units has been shown to reduce the rate of preventable ADEs by 66%.9,10 Computer-based monitoring of drug interactions, therapeutic duplication, and dosage checks is another means of ADE prevention.11

Critical care pharmacists have many patient care responsibilities, resulting in a limited amount of time to perform each function.12 Budgeting within most hospitals encourages departments to focus on cost reduction instead of cost avoidance when changing processes or improving quality.13,14 Since ICU drug costs contribute to at least 38.4% of a hospital’s total drug costs and have increased at a rate twice that in non-ICUs,15 many cost-containment efforts encourage pharmacists to monitor the appropriate use of costly ICU medications. However, this strategy may not be the most effective approach, since direct costs are not the only costs associated with drug use.16 The use of treatment algorithms and guidelines may aid pharmacists in cost-containment efforts but does not address the prevention of ADEs.17,18 Further, patients who have an ADE incur an additional cost of $3000–$7000, clearly justifying efforts to increase the prevention and detection of ADEs.3,6,19 Identification of the drugs most commonly associated with ADEs may improve patient safety and contain costs.

The objective of this study was to determine whether ADEs in the ICU occur more often with high-cost or high-use drugs in an attempt to direct pharmacists’ attention toward those medications that most compromise patient safety. Specifically, this study sought to compare the rates, preventability, and severity of ADEs associated with (1) high- and low-cost drugs used in the ICU, (2) high- and low-use drugs in the ICU, and (3) high-cost versus high-use drugs in the ICU.


   Methods
Top
 Methods
Results
 Discussion
 Conclusion
 References
 
This study was approved by the University of Pittsburgh’s institutional review board as an exempt protocol. This retrospective study was conducted from October 1997 through June 2001 at a 647-bed academic medical center that contains over 120 ICU beds for adult solid organ transplant, cardiac surgery, general surgery, medicine, neurotrauma, neurovascular, trauma, and coronary care patients. Patients older than 18 years of age who had a documented ADE while in the ICU were included in the study. Patients’ age and sex; suspected medication for the ADE; ADE reaction type; ADE assessment, which included causality, preventability, and severity; and patient outcome (i.e., recovered with treatment or prolonged admission) were extracted from the ADE program database (ADE database). The institution’s electronic data repository with clinical, administrative, pharmacy, and financial databases (MARS, Medical Archival System, Inc., Pittsburgh, PA) was used to validate patient demographics and to obtain data for drug cost and frequency of use.

Description of the ADE surveillance system.   ADEs were identified using the ADE database, retrospective screening of International Classification of Diseases, 9th Revision, codes, and reviewing antidote use and potentially drug-related electrolyte disturbances. Reported ADEs were reviewed and classified by a drug information pharmacist with over 10 years of experience in ADE evaluation and validated by the hospital’s ADE subcommittee. The institution’s interdisciplinary ADE subcommittee consisted of physicians, pharmacists, nurses, and risk management representatives who reviewed all reported ADEs to determine preventability and validate causality and severity.

An ADE was defined as an injury resulting from drug treatment.4 Preventable ADEs were defined as medication errors in which a patient received a drug resulting in harm.3,9 All others were classified as nonpreventable ADEs. Severity was defined using a modified version of the National Cancer Institute Toxicity Criteria20 and designated as severity level I (minor interventions required [e.g., discontinuation of suspected medication, additional patient monitoring]), level II (moderate intervention [e.g., initiation of antidote]), or level III (immediate life-sustaining treatment required or transfer to an acute care unit [e.g., use of vasopressors, cardiac monitoring, respiratory support]). Causality assessment was defined as highly probable, probable, possible, or remote.21

Drug cost.   High-cost medications were defined as those accounting for the top 50% of cumulative ICU medication costs for the study period. The remaining medications were considered low cost. Cost was determined by multiplying units of medication charged to a patient by the pharmacy acquisition cost. ADEs were categorized by high- and low-cost medications and were compared by the percentage of medications causing ADEs. Severity and preventability of each ADE were also described.

Frequency of drug use.   Because of the large number of medications in the pharmacy database and the small number of units associated with many of the drugs, the usage was narrowed to those medications most frequently used in an ICU before frequency of use could be quantified.

Initial selection of these drugs was aided by a review of the literature on ICU drug use.22–24 Next, critical care pharmacists practicing in 37 different institutions’ ICUs were asked to list the top 10 most frequently used medications in the ICU. The hospital’s use of the 74 medications listed by these pharmacists was quantified by the charge data in MARS, as was our use of 64 additional medications that appeared in ADE reports or were listed as high-cost drugs. High-use medications were defined as the upper 50% of all medications used during the study period. Use was defined as the total units of medication that contain an ICU billing charge. One unit was equivalent to one vial or tablet. ADEs were categorized by high- and low-use medications and quantified and described by severity and preventability.

Further, ADEs categorized into high-cost and high-use groups were compared by the percentage of medications causing ADEs and the severity and preventability of each ADE.

Statistical analysis.   Student’s t test, chi-square analysis, and Fisher’s exact test were used for between-group comparisons of ADE rate, preventability, and severity. An alpha of 0.05 was considered statistically significant. Statistical analysis was conducted using SPSS version 13.0 (SPSS, Inc., Chicago, IL).


   Results
Top
 Methods
 Results
Discussion
 Conclusion
 References
 
A total of 280 ADEs caused by 97 unique medications were identified in 181 ICU patients. The overall mean ± S.D. age of these patients was 59 ± 17 years, with 52% of ADEs occurring in men. There were 21,436 ICU admissions and 116,656 patient days during the study period, with an ADE incidence of 1.3 per 100 admissions or 2.4 ADEs per 1000 patient days.

Antimicrobials, analgesics, and anticoagulants were the three most common drug classes to cause ADEs. Individual drugs associated with more than five ADEs are listed in Table 1Go. The most common ADEs were pruritis (10.3%), thrombocytopenia (8.5%), somnolence (6.4%), hypotension (5%), and increases in serum creatinine levels (4.3%). Thirty-two percent of ADE reports were defined as serious or severe, with the majority classified as moderate in severity (59%). Almost all ADEs (99.3%) were possibly caused by the medication based on the Jones algorithm.21 Interventions (e.g., blood transfusions, vasopressors) were required for 7.8% of the ADEs. No ADEs caused a disability. Life-threatening reactions and prolonged hospital stays occurred with less than 3% of ADEs. Only 24 (8.6%) of 280 ADEs were determined to be preventable, with antihypertensives accounting for 29% (n = 7) of the preventable ADEs.


View this table:
[in this window]
[in a new window]
  		Table 1. Medications Associated with More Than Five ADEsa
 
Drug costs.   Of the 1005 drugs analyzed, 17 met criteria for a high-cost medication (Table 2Go). Of these 17 medications, 9 were documented as causing ADEs. Of the 988 low-cost medications, 88 (8.9%) were reported as causing ADEs. The low-cost medications associated with the most ADE reports were heparin, morphine, and fentanyl. There was a statistically significant difference in the percentage of medications causing ADEs between the high- and low-cost groups (53% versus 8.9%, respectively) (p < 0.001, Fisher’s exact test). A comparison of the severity and preventability of these ADEs appears in Table 3Go.


View this table:
[in this window]
[in a new window]
  		Table 2. High-Cost Medications and Number of Associated ADEsa
 

View this table:
[in this window]
[in a new window]
  		Table 3. Severity and Preventability of ADEs Stratified by Medication Cost and Frequency of Usea
 
Frequency of use.   Of the 138 medications evaluated for use, 15 met the criteria for high-use medications, representing 13.7% of the 1005 total medications charged (Table 4Go). Of these 15 medications, 12 (80%) were associated with ADEs. Of the 123 low-use medications, 85 (69%) were associated with ADEs (n = 206). The most common low-use medications associated with ADEs were morphine, piperacillin, and phenytoin. The percentage of high- and low-use medications associated with ADEs did not significantly differ (p = 0.552, Fisher’s exact test) (Table 3Go).


View this table:
[in this window]
[in a new window]
  		Table 4. High-Use Medications and Associated ADEsa
 
High-cost versus high-use drugs.   Lorazepam, mycophenolate, and propofol were included in both the high-cost and high-use groups; however, these medications were removed from the statistical analysis to avoid overlap. As a result, a total of 12 ADEs were removed from each group. There was no statistically significant difference in the number of medications associated with ADEs between the high-cost (6 of 14, 43%) and high-use (9 of 12, 75%) groups ({chi}2 = 2.735; p = 0.098). The ADEs associated with high-cost and high-use medications were categorized as mild (level I) (4 of 27 and 6 of 62, respectively), moderate (level II) (14 of 27 and 31 of 62, respectively), and severe (level III) (9 of 27 and 25 of 62, respectively). There was no significant difference in the number of ADEs rated mild and moderate, mild and severe, or moderate and severe. Two of the 27 ADEs in the high-cost group were considered preventable, compared with 6 of the 62 ADEs in the high-use group (p = 1.00, Fisher’s exact test).


   Discussion
Top
 Methods
 Results
 Discussion
Conclusion
 References
 
Patient safety is a component of all pharmacists’ jobs.12,25–28 This study was designed to aid in prioritizing the pharmacist’s efforts with high-cost and high-use medications based on the frequency of ADEs in these groups and the importance of patient safety. There was a 32% difference in the number of medications associated with ADEs between the high-cost and high-use groups. Although this difference was not statistically significant, it illustrates that monitoring high-cost and high-use drugs is equally important in the ICU setting. Only three drugs (lorazepam, mycophenolate, and propofol) were considered both high cost and high use, demonstrating that there is minimal overlap between these categories based on reports generated from an intensive ADE program. Heparin, the medication associated with the most ADEs, was categorized as high use but low cost. If medication monitoring had a strictly monetary focus, then heparin would be missed. Interestingly, morphine was associated with the second highest number of ADEs but was not ranked as a high-use or high-cost drug. The large number of ADEs occurring in low-cost and low-use groups and the severity of these ADEs demonstrate that the mechanism to prioritize medication monitoring in the ICU extends beyond cost and use. Monitoring priorities of critical care pharmacists should include the frequency of ADEs and the potential for incurring injury from a medication.29

Although the severity and preventability of ADEs did not vary significantly between high-cost and high-use groups, the high frequency of ADEs indicates opportunity for improvement in ADE prevention. The most preventable ADEs involved antihypertensives. Anticoagulants were commonly associated with life-threatening events and a prolonged length of stay, further justifying pharmacist monitoring of the use of this class of medications.

Of the 17 high-cost medications, 53% were associated with ADEs. The low-cost group had significantly fewer medications associated with ADEs (8.9%). However, it should not be overlooked that 88 low-cost medications were associated with 241 ADEs. Of note, similar percentages of the ADEs were severe and preventable in the high-cost and low-cost groups, although a larger sample size is needed to verify these results.

It seems logical that high-use medications would be associated with more ADEs because of the frequent exposure, but this did not hold true in our study. A similar percentage of medications in the high-use and low-use groups were associated with ADEs (80% versus 69%, respectively). Approximately 35% of these were severe and 9% were preventable in both groups; however, the study was not powered to detect these differences. High-use medications were not associated with more ADEs than were low-use medications; however, this may reflect reduced reliance on ADE reporting or the clinicians’ familiarity in handling high-use medications.

To select a sample that was representative of high-use medications, the initial selection process included a review of the literature, though these data were typically unit specific and evaluated for only short periods of time.21–24 To minimize this limitation, ICU pharmacists in other institutions were surveyed to capture high-use medications. Also, medications evaluated for use included those causing ADEs and those in the high-use group that were not part of the literature and survey data. While the capture of use data on all medications would have been ideal, it was not practical due to the size of the entire database.

The intensive ADE surveillance program at our institution is consistent with published definitions for ADE, causality, preventability, and severity. The incidence of ADEs in our study was 1.3 per 100 admissions, or 2.4 events per 1000 patient days. This rate is lower than that cited in the literature for ICUs3 because our institution’s system captures ADEs in several different ICUs and uses certain triggers for detection, unlike the chart review completed in the published studies. Also, the ADE rate reported in the literature includes potential and preventable ADEs. Our ADE surveillance system did not include potential ADEs. It is known that different detection methods yield different quantities and types of ADEs.30–33 The ideal detection method would be a combination of voluntary reporting, chart review, and computer-based monitoring; however, most institutions do not have this type of resource-intensive system.

Causality of ADEs was not completed, since the Jones algorithm predicted that 99.3% of medications in this study were a possible cause of an ADE. The inability to confirm causality beyond "possible" status may be due to the lack of rechallenging with the suspect medication to confirm the reaction in this acutely ill population. A more definitive algorithm may be necessary for ADE evaluation in the critically ill.34

Another limitation to this study is its potential lack of generalizability to other institutions. Acetaminophen–oxycodone is the most widely used ICU medication at our institution, accounting for 10.7% of drug use in the ICU; however, the influence of formularies, protocols, and differences in ICU patient population need to be considered when comparing our list of ADEs to those of other institutions. For example, our institution has a large population of transplant recipients; consequently, the list of high-use medications includes tacrolimus, prednisone, and mycophenolate, which may not be frequently used in other institutions.

The costs considered in this study were exclusively drug acquisition costs, because this is typically the source of budgetary concerns. Another way to identify high-cost medications is by evaluating the cost of treatment and the effects on total cost of care. The high-cost medications identified in our study are subject to change based on the introduction of new medications and the availability of generic medications. Also, the list of high-use medications was determined by 37 pharmacists and by the medications associated with ADEs because of the resourceintensive mechanism for obtaining these data.

Monitoring the frequency, preventability, and severity of events using surveillance data is useful for guiding institutional patient safety directives. For those institutions that do not have an intensive ADE surveillance program, the 13 medications presented in Table 1Go can be used as a guide for focusing clinicians’ monitoring priorities. The results from this study can be used to develop patient safety prevention initiatives for anticoagulants, antibiotics, and sedatives, which could include the implementation of heparin nomograms and sedation protocols.


   Conclusion
Top
 Methods
 Results
 Discussion
 Conclusion
References
 
The frequency, severity, and preventability of ADEs in the ICU were not associated with a drug’s cost or frequency of use. Monitoring priorities of the critical care pharmacist should not be dictated by cost alone but should include frequency of use and the potential for causing an ADE.


   Footnotes
 
Vince Oriolo, Anthony Lacava, and Melissa Saul are acknowledged for obtaining the data necessary for this project. Teresa McKaveney is acknowledged for her critical review of the manuscript.

Funded in part by the American Society of Health-System Pharmacists Research and Education Foundation, Bethesda, MD.


   References
Top
 Methods
 Results
 Discussion
 Conclusion
 References
 

  1. Leape LL, Brennan TA, Laird N et al. The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II. N Engl J Med. 1991; 324:377–84.[Abstract]
  2. Classen DC, Pestotnik SL, Evans RS et al. Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA. 1997; 277:301–6.[Abstract/Free Full Text]
  3. Cullen DJ, Sweitzer BJ, Bates DW et al. Preventable adverse drug events in hospitalized patients: a comparative study of intensive care and general care units. Crit Care Med. 1997; 25:1289–97.[CrossRef][Medline]
  4. Bates DW, Cullen DJ, Laird N et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. JAMA. 1995; 274:29–34.[Abstract/Free Full Text]
  5. Colley CA, Lucas LM. Polypharmacy: the cure becomes the disease. J Gen Intern Med. 1993; 8:278–83.[Medline]
  6. Bates DW, Spell N, Cullen DJ et al. The costs of adverse drug events in hospitalized patients. JAMA. 1997; 277:307–11.[Abstract/Free Full Text]
  7. Food and Drug Administration. FDA and Lincoln Technologies, Inc. to collaborate on developing tools for safety data mining. www.fda.gov/bbs/topics/NEWS/2003/NEW00899.html (accessed 2006 Jan 31).
  8. Kane-Gill SL, Dasta JF, Schneider PJ et al. Monitoring abnormal laboratory values as antecedents to drug-induced injury. J Trauma. 2005; 59:1457–62.[Medline]
  9. Leape LL, Cullen DJ, Clapp MD et al. Pharmacist participation on physician rounds and adverse drug events in the intensive care unit. JAMA. 1999; 282:267–70. [Erratum, JAMA. 2000; 283:1293.][Abstract/Free Full Text]
  10. Kucukarslan SN, Peters M, Mlynarek M et al. Pharmacists on rounding teams reduce preventable adverse drug events in hospital general medicine units. Arch Int Med. 2003; 163:2014–8.[Abstract/Free Full Text]
  11. Silverman JB, Stapinski CD, Huber C et al. Computer-based system for preventing adverse drug events. Am J Health-Syst Pharm. 2004; 61:1599–1603.[Free Full Text]
  12. Rudis MI, Brandl KM. Position paper on critical care pharmacy services. Society of Critical Care Medicine and American College of Clinical Pharmacy Task Force on Critical Care Pharmacy Services. Crit Care Med. 2000; 28:3746–50.[CrossRef][Medline]
  13. Racine E. Justifying high-cost anticoagulant therapy. Am J Health-Syst Pharm. 2002; 59(suppl 6):S18–20.[Abstract/Free Full Text]
  14. Halley HJ. Approaches to drug therapy, formulary, and pathway management in a large community hospital. Am J Health-Syst Pharm. 2000; 57(suppl 3):S17–21.[Abstract/Free Full Text]
  15. Weber RJ, Kane SL, Oriolo VA et al. Impact of intensive care unit (ICU) drug use on hospital costs: a descriptive analysis, with recommendations for optimizing ICU pharmacotherapy. Crit Care Med. 2003; 31(suppl 1):S17–24.[CrossRef][Medline]
  16. Dasta JF, Durtschi AJ, Kane-Gill SL. Pharmacoeconomics in critical care. In: Grenvik A, ed. Textbook of critical care. 5th ed. Philadelphia: Saunders, 2005:1732–9.
  17. Constantini O, Papp KK, Como J et al. Attitudes of faculty, housestaff and medical students toward clinical practice guidelines. Acad Med. 1999; 74:1138–43. [Erratum, Acad Med. 1999; 74:1322.][Medline]
  18. Fischer MA, Lilly CM, Churchill WW et al. An algorithmic computerised order entry approach to assist in the prescribing of new therapeutic agents: case study of activated protein C at an academic medical centre. Drug Saf. 2004; 27:1253–61.[CrossRef][Medline]
  19. Senst BL, Achusim LE, Genest RP et al. Practical approach to determining costs and frequency of adverse drug events in a health care network. Am J Health-Syst Pharm. 2001; 58:1126–32.[Abstract/Free Full Text]
  20. National Cancer Institute. National Cancer Institute common terminology criteria for adverse events v 3.0. http://ctep.cancer.gov/forms/CTCAEv3.pdf (accessed 2006 Jan 31).
  21. Jones JK. Definition of events associated with drugs: regulatory perspectives. J Rheumatol Suppl. 1988; 17:14–9.[Medline]
  22. Dasta JF. Drug use in a surgical intensive care unit. Drug Intell Clin Pharm. 1986; 20:752–6.[Abstract]
  23. Boucher BA, Kuhl DA, Coffey BC et al. Drug use in a trauma intensive-care unit. Am J Hosp Pharm. 1990; 47:805–10.[Abstract]
  24. Mann HJ, Wittbrodt ET. Identifying drug usage patterns in the intensive care unit. Pharmacoeconomics. 1993; 4:235–9.[Medline]
  25. Hassan Y, Aziz NA, Awang J et al. An analysis of clinical pharmacist interventions in an intensive care unit. J Clin Pharm Ther. 1992; 17:347–51.[Medline]
  26. Lata PF, Mainhardt M, Johnson CA. Impact of nurse case manager–pharmacist collaboration on adverse-drug-event reporting. Am J Health-Syst Pharm. 2004; 61:483–7.[Free Full Text]
  27. Van Grootheest AC, van Puijenbroek EP, de Jong-van den Berg LT. Contribution of pharmacists to the reporting of adverse drug reactions. Pharmacoepidemiol Drug Saf. 2002; 11:205–10.[CrossRef][Medline]
  28. Van Grootheest K, Olsson S, Couper M et al. Pharmacists’ role in reporting adverse drug reactions in an international perspective. Pharmacoepidemiol Drug Saf. 2004; 13:457–64.[CrossRef][Medline]
  29. Duwe B, Fuchs BD, Hansen-Flaschen J. Failure mode and effects analysis application to critical care medicine. Crit Care Clin. 2005; 21:21–30.[Medline]
  30. Jha AK, Kuperman GJ, Teich JM et al. Identifying adverse drug events: development of a computer-based monitor and comparison with chart review and stimulated voluntary report. J Am Med Inform Assoc. 1998; 5:305–14.[Abstract/Free Full Text]
  31. Dormann H, Muth-Selbach U, Krebs S et al. Incidence and costs of adverse drug reactions during hospitalization: computerised monitoring versus stimulated spontaneous reporting. Drug Saf. 2000; 22:161–8.[CrossRef][Medline]
  32. Thurmann PA. Methods and systems to detect adverse drug reactions in hospitals. Drug Saf. 2001; 24:961–8.[CrossRef][Medline]
  33. Kane-Gill SL, Devlin J. Adverse drug event reporting in intensive care units: a survey of current practices. Ann Pharmacother. DOI.1345/aph.1H088; 2006 Jul 18.
  34. Kane-Gill SL, Kirisci L, Pathak DS. Are the Naranjo criteria reliable and valid for determination of adverse drug reactions in the intensive care unit? Ann Pharmacother. 2005; 39:1823–7.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 The Annals of PharmacotherapyHome page
B. L Erstad
A Primer on Critical Care Pharmacy Services
Ann. Pharmacother., December 1, 2008; 42(12): 1871 - 1881.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kane-Gill, S.
Right arrow Articles by Weber, R. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kane-Gill, S.
Right arrow Articles by Weber, R. J.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS