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research-article2013
AJMXXX10.1177/1062860613514770American Journal of Medical QualityAhmed et al
Article
Outcome of Adverse Events and Medical Errors in the Intensive Care Unit: A Systematic Review and Meta-analysis
American Journal of Medical Quality 2015, Vol. 30(1) 23–30 © 2013 by the American College of Medical Quality Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1062860613514770 ajmq.sagepub.com
Adil H. Ahmed, MBBS,1 Jyothsna Giri, MD,1 Rahul Kashyap, MBBS,1 Balwinder Singh, MBBS,1 Yue Dong, MD,1 Oguz Kilickaya, MD,1 Patricia J. Erwin, MLS,1 M. Hassan Murad, MD,1 and Brian W. Pickering, MB, BCh, MSc1
Abstract Adverse events and medical errors (AEs/MEs) are more likely to occur in the intensive care unit (ICU). Information about the incidence and outcomes of such events is conflicting. A systematic review and meta-analysis were conducted to examine the effects of MEs/AEs on mortality and hospital and ICU lengths of stay among ICU patients. Potentially eligible studies were identified from 4 major databases. Of 902 studies screened, 12 met the inclusion criteria, 10 of which are included in the quantitative analysis. Patients with 1 or more MEs/AEs (vs no MEs/AEs) had a nonsignificant increase in mortality (odds ratio = 1.5; 95% confidence interval [CI] = 0.98-2.14) but significantly longer hospital and ICU stays; the mean difference (95% CI) was 8.9 (3.3-14.7) days for hospital stay and 6.8 (0.2-13.4) days for ICU. The ICU environment is associated with a substantial incidence of MEs/AEs, and patients with MEs/AEs have worse outcomes than those with no MEs/AEs. Keywords adverse events, intensive care unit, medical error, systematic review, outcomes The Institute of Medicine report, To Err Is Human,1 started a debate on patient safety and brought attention to the high prevalence of likely preventable medical errors (MEs) and adverse events (AEs). It was subsequently proposed that preventable harm can be caused by deviation from best practices and evidence-based clinical practice guidelines, which can lead to increased patient morbidity and mortality and increased resource utilization.2 The Institute of Medicine defined an ME as “the failure of a planned action to be completed as intended (ie, an error of execution) or the use of a wrong plan to achieve an aim (ie, an error of planning).”1 Other studies have defined an AE as “an injury caused by medical management.”3 An AE was designated as “preventable” if it was attributable to error and as “negligent” if the care provided did not meet the standard care of an average qualified physician.3 Previous studies of MEs/AEs define these terms similarly4 and the terms are often used interchangeably; this can make quantifying or categorizing patient safety events difficult in the acute care setting.5 Patients admitted to the intensive care unit (ICU) during their hospital stay are more likely to experience an AE than those in other hospital units.6 The incidence of MEs/
AEs has been reported to be as high as 31% of ICU admissions.7 Some of these events result in a requirement for additional life-sustaining interventions.8 Other studies, using provider self-reporting systems, noted that the ME/AE incidence approached 20% of ICU admissions.9 A recent systematic review of in-hospital AEs found a higher incidence in surgical populations.10 Although patient safety in emergency medical services has been studied, a systematic review of MEs/AEs in ICU populations—a complex group of patients who may be especially prone to such events—has not been performed. The true incidence of errors in the ICU remains unclear, as is whether the occurrence of MEs/AEs leads to increased mortality or extended hospital or ICU stay. In this study, the research team conducted a systematic review and meta-analysis to examine the effects of MEs/AEs on mortality and hospital and ICU length of stay (LOS) among ICU patients. 1
Mayo Clinic, Rochester, MN
Corresponding Author: Adil H. Ahmed, MBBS, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905. Email: [email protected]
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American Journal of Medical Quality 30(1)
Methods
Data Abstraction
This systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.11
The data abstraction sheet was modified from the Cochrane data extraction template. A pilot assessment of this template was performed by the simultaneous extraction of data from 3 studies by 2 reviewers, which allowed further modification of the data abstraction sheet. The following variables were abstracted: author, country, publication year, study settings, characteristics of the study case/exposed along with control/nonexposed, study type, description of study participants, location of study (academic hospital vs nonacademic), hospital mortality, and hospital and ICU LOS. In the event of missing data, the corresponding authors of the studies were contacted twice by e-mail.
Information Sources and Search Criteria The search strategy was conducted by an expert librarian (PJE) and included 4 main databases—MEDLINE, Embase, Web of Science, and Scopus—with search dates of January 1990 through May 2013. The search strategy used the following subject headings in Ovid MEDLINE: intensive care units, burn units, coronary care units, and respiratory care units as well as ICUs and CCUs. The search was limited to the adult population. Subject headings for ME (including Medication Errors) and iatrogenic disease were enhanced with text words such as “mistake,” “error,” “missed,” “unintended,” and “near-miss.” The search was further focused using a combination of subject headings; the final concept used a combination of subject headings related to decision support (such as “clinical risk management”) and text words such as “lists” and “checklists.” These concepts were added to broaden the results and to include more quality initiative types of studies. The final strategy was then translated to the subject headings available for Ovid Embase and text words for the ISI Web of Science and Scopus. All results were filtered to include trials and cohort studies. (The exact search strategy is available from the corresponding author on request.)
Study Selection Two reviewers independently screened the abstracts and titles identified in the search using the inclusion criteria “intensive care unit” or “decision support” for one of the following: checklist, error, incident, adverse event, nearmiss, error reporting, patient safety, and medical errors. Thereafter, reviewers went in parallel through the full text of the selected studies and excluded nonoriginal research (systematic reviews and meta-analyses), descriptive studies (eg, narrative reviews, case reports, expert opinion, letter to the editor), and duplicate publications if identified on the final full article review. The interrater agreement was assessed using Cohen’s κ statistic. Any disagreement was solved by mutual consensus in the presence of a third investigator. The primary outcome of this study was in-hospital mortality; the secondary outcomes were ICU and hospital LOS among critically ill patients, comparing those with and without MEs/AEs.
Validity Assessment Two reviewers independently performed the quality assessment of study methodology using the NewcastleOttawa Scale.12 The research team used a “star system” in which a study was judged on 3 broad perspectives: selection of the study groups, comparability of the groups, and ascertainment of the exposure and outcome of interest for case-control or cohort studies. The interrater agreement was assessed, and any disagreement was solved by mutual consensus in the presence of a third investigator.
Statistical Analysis Statistical analysis was performed using Comprehensive Meta-Analysis Version 2 (Biostat, Englewood, NJ). Relative risks and differences in means with 95% confidence intervals (CIs) were estimated for the primary outcome of mortality and secondary outcomes of hospital LOS and ICU LOS. Results from each study were pooled using the DerSimonian-Laird random-effects model. Heterogeneity was assessed using the I2 statistic.13
Subgroup and Sensitivity Analysis A priori hypotheses to explain potential heterogeneity in the direction and magnitude of effect among studies included the type of study setting (academic vs nonacademic) and the preventability of errors as estimated by whether the individual study quantified the preventable AEs to be more than half of the total events in the study (>50% preventable). Moreover, a post hoc subgroup analysis was added for study location (US vs non-US setting) and if the study reported AE versus ME. The statistical significance across subgroups was examined using an interaction test.14
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Ahmed et al
Figure 1. Study flow diagram.
Abbreviations: ME/AE, medical error/adverse event; ICU, intensive care unit.
2 studies19,21 had insufficient data for meta-analysis, and their findings are summarized qualitatively. One study19 examined the association of a tele-ICU intervention with hospital mortality, LOS, and complications that are preventable by adherence to best practices. Implementation of this intervention “was associated with reduced adjusted odds of mortality and reduced hospital LOS, as well as with changes in best practice adherence and lower rates of preventable complications.”19(p.2181) The other study21 estimated the incidence and characteristics of AEs and no-harm events in critically ill patients and found that the individual risk of at least 1 incident was 62%, the risk of at least 1 no-harm event was 45%, and the risk of at least 1 AE was 29%.
Hospital Mortality Outcomes Results The search identified a total of 902 studies, 12 of which were included in the final analysis (Figure 1). The overall mean age of the patient population in the included studies was 64 years; 40% were women. Of the 12 studies, 7 were conducted in academic hospitals, 4 in a nonacademic hospital, and 1 in both settings. Two of the ICUs were exclusively medical, 8 were mixed ICUs, and 1 was a cardiac ICU; 1 other study was conducted in both medical and cardiac ICUs. Other main study characteristics are summarized in Table 1. Three authors were contacted for more information regarding nonreported outcomes, but only 1 author responded with the requested data.15
Methodological Quality The overall quality of the included studies varied from very low to high (Table 2). The research team used a score of 7 on the Newcastle-Ottawa scale as a cutoff to identify studies with adequate methodological quality. A few studies did not provide explicit descriptions of methods to protect against bias, whereas in other studies it was clear that such techniques were used. Only 1 study adequately reported complete quality criteria.16 In all, 8 studies2,7,8,15-19 were considered good quality (score ≥7), and 420-23 were deemed low quality (score 65 years
Medical
Yes
Medical error
Mortality
314 (31.6)
58 (16)
Mixed
No
Critical incident, human errors
Mortality
All consecutive pts admitted to ICU, predominantly with cardiovascular and pulmonary disorders Adult pts admitted to ICU during the study period. Those with AEs were cases and those without were controls Adult pts admitted to CCU during the study period. Those with AE were cases and those without were controls Adult ICU pts in 3 ICUs at an academic hospital in 2003 and 2004. Pts with ICU stays that extended 2 weeks or more beyond study period were excluded Adult ICU pts in 2 ICUs at a nonacademic hospital in 2003 and 2004. Pts with ICU stays that extended 2 weeks or more beyond study period were excluded Retrospective study of charts of consecutive adult pts admitted to CCU
65 (30%)
63 (14)
Medical
Yes
Mortality, ICU LOS, hospital LOS
Cases: 22 (39.3); controls: 103 (53.6) Cases: 17 (32.7); controls: 89 (48.6) Cases: 65 (46.8); controls: 59 (42.5)
Cases: 60.3; controls: 63.6
Medical
Yes
Medical and nonmedical errors Adverse event
Cases: 66.3; controls: 66.2
Cardiac
Yes
Adverse event
Mortality, ICU LOS, hospital LOS
Mixed
Yes
Adverse event
Mortality, hospital LOS
Mixed
No
Adverse event
Mortality, hospital LOS
56 (29)
Cases: 64.7 (17.7); controls: 65.1 (16.4) Cases: 64.7 (17.7); controls: 65.1 (16.4) 65 (35)
Cardiac
Yes
Adverse event
Mortality, ICU LOS, hospital LOS
75 (36)
66 (54-75)
Mixed
No
Adverse event
Mortality
2705 (43)
64 (16.8)
Mixed
Yes
Preventable complications
Mortality, ICU LOS, hospital LOS
210 (35)
62 (17)
Mixed
Yes
Adverse events and no-harm events
Mortality
With AE = 9(36); without AE = 46(45); total = 55(42)
With AE, 67; without AE, 72
Mixed
No
Medical and Medication AE
ICU LOS
Cases: (47); controls: (45)
Cases: 59; controls: 60
Mixed
Yes
ICU LOS, hospital LOS, mortality
With AE, 61(40); without AE, 150(38.5)
With AE, 53; without AE, 52
Mixed
Yes
Medication Adverse events Medical Adverse Event
All adult pts admitted to ICU at the Ottawa Hospitals. Studied from ICU admission until hospital discharge or death Consecutive hospital discharge cases from an administrative database for cases managed in each of 7 adult ICUs All pts in ICU at any time during the observation period, including those admitted and discharged during this period as well as those who died Pts >18 years old who had received care on the ICU during the years 2007 or 2008 and died on the ICU or within 96 hours after discharge from the ICU but still received care at the same hospital were included Adults admitted to the ICU from July 1998 to January 2006 and had a documented ADE in database. Adults admitted to the study institution between May 31, 2009, and January 12, 2011, who were on mechanical ventilation for >48 hours
Cases: 93 (47.9); controls: 82 (42.3)
Mortality, ICU LOS, hospital LOS
Duration of mechanical ventilation, ICU LOS, hospital LOS, mortality
Abbreviations: ICU, intensive care unit; pts, patients; LOS, length of stay; AE, adverse events; CCU, cardiac care unit; ADE, adverse drug event; SD, standard deviation. a Age is given as mean, mean (SD), or median (interquartile range), unless otherwise noted.
Discussion The research team conducted a systematic review and meta-analysis to examine the effects of MEs/AEs on mortality and hospital and ICU LOS among ICU patients. This meta-analysis showed that patients with MEs/AEs have significantly longer ICU and hospital stays. They also may have higher mortality, but the results were associated with significant heterogeneity and the analysis became nonsignificant using a random-effects model. In addition, the confidence in the provided estimates is low
(ie, low-quality evidence at risk of bias) because of the observational nature of the studies, the unexplained heterogeneity, the inability to evaluate publication bias, and the lack of robustness of analysis (results differ based on the choice of model). The research team used the random effects model because it includes within-study and between-study heterogeneity in the width of the CI; hence, it is more conservative. However, the team also presented an alternate model to demonstrate the effect of the analysis method used. Overall, considering both models, patients with errors may have worse outcomes, but
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Ahmed et al Table 2. Methodological Quality of Included Studies. Newcastle-Ottawa Scorea Studies b,8
Giraud et al (1993) Bracco et al (2001)b,7 Graf et al (2005)b,23 Kaushal et al (2007)c,2 Forster et al (2008)b,22 Nuckols et al (2008)c,16 Rahim et al (2009)b,15 Lilly et al (2011)b,19 Merino et al (2012)b,21 Nilsson et al (2012)b,20 Kane-Gill et al (2012)c,18 Hayashi et al (2012)b,17
Selection
Comparability
Exposure
Total Number of Stars
*** *** *** **** ** **** **** **** **** *** *** ****
** * * ** ** ** * *
** ***
7/9 7/9 4/9 8/9 5/9 9/9 8/9 7/9 5/9 6/9 7/9 8/9
** * *** *** ** * *** *** ***
* *
a
The studies were scored on a “star” system (denoted here by asterisks), in which a maximum of 1 star is given for each item within the “Selection” and “Exposure/Outcome” categories and a maximum of 2 stars for “Comparability.” b Cohort study. c Case-control study.
Figure 2. Mortality outcome of adverse events (AEs) and medical errors (MEs) across the included studies. Abbreviation: CI, confidence interval.
the magnitude of the effect may not be reliable as derived from the current data. This meta-analysis is aligned with results from previous individual studies.25 Differences in patient populations and the lack of standardized definitions of MEs/AEs may result in difficulty comparing rates of MEs/AEs across ICU populations.26 Moreover, assessing the effects of MEs/AEs is difficult because of differences in case mix, confounding factors for mortality, and multiple MEs/AEs in the same patient.27 Although MEs/AEs are undesirable, there is a certain inevitability to their occurrence in the ICU.26 The available evidence failed to establish an expected strong
relationship between errors and mortality.22 The research team postulates that fatal or substantial harmful errors or AEs that could result in death may have been underreported in the presented studies.28 Intensivists recognize the necessity of disclosing the occurrence of harmful events to their patients, yet less than half of them actually report it.29 Although some reports suggest that US physicians are more likely to disclose errors than their European counterparts,30 the discrepancy between the rate of ME/ AE occurrence and the rate of disclosure is substantial.31 Iedema et al32 listed lack of physician awareness of what and how to disclose along with the moral challenges to
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American Journal of Medical Quality 30(1)
Figure 3. Hospital and ICU length of stay outcome for adverse events (AEs) and medical errors (MEs) across included studies. Abbreviations: CI, confidence interval; MICU, medical intensive care unit; CCU, cardiac care unit; ICU, intensive care unit.
report other colleagues as some of the barriers to disclosure and handling MEs/AEs; they also place emphasis on making suitable organizational reforms to have a disclosure policy in place. As suggested by Studdert et al,33 the fear of litigation poses a substantial obstacle to transparency. However, others discussed the importance of communication and disclosure as being most crucial to liability reduction and strengthening the physician-patient relationship.34 Human factors were identified frequently in the literature7; some studies suggested that higher workload is a major contributor of MEs/AEs8 but other studies fail to prove that.23 Errors of omission related to application of evidence-based practice are rarely reported and become targets for quality improvement projects through the application of checklists and electronic alerts.35 System or organizational factors characterize the second component of ME/AE roots. Although health care organizations recognized the significance of maintaining a safe and error-free environment, several challenges such as rising health care costs and the failure to sustain a robust reporting practice hindered the leadership in adopting such initiatives.36 Various methods to detect MEs/AEs have been described, typically yielding different results.37 The method of detection of MEs/AEs also varied among the studies included in this report; prospective direct field observation was used in 2 studies,8,22 retrospective or prospective chart review in 5 studies,2,15,16,19,21 and an incident report form and standardized data sheet in the remaining 2.7,23 Because the numbers of MEs/AEs depend on the method of detection, it is important to recognize
the differences between the 3 methods used. Voluntary or self-reporting is common and used in many studies9; however, fear of litigation is a major drawback, which potentially results in failure to self-report serious and harmful events and a tendency to overlook minor events that appear to be of no consequence from the reporter’s perspective.38 The second method, retrospective chart review, relies heavily on the quality of documentation and reviewer interpretation.39 Direct field observation demonstrated superiority over self-reporting, especially for detection of errors of omission,40 and there has been a steady increase in the use of this method in the past decade, with cost and workload being the main limitations.
Strengths and Limitations This review and meta-analysis used a comprehensive literature search and rigorous inclusion criteria to identify studies relevant to the research team’s objectives, applied bias protection measures in the selection of the studies, and evaluated study methodological quality. However, the team limited the outcome measures to mortality and LOS exclusively among ICU patients. Although the search was comprehensive, it is possible that some citations were missed, and as with all systematic reviews, selective availability of studies with positive results might have resulted in hard-to-detect publication bias. Moreover, excluding children risks excluding studies that include both adults and children. It is plausible that many quality improvement projects evaluated ICU errors in local settings but remained internal documents and were
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Ahmed et al not published. Therefore, inferences are limited by the low quality of the evidence, considering the imprecision, heterogeneity, and methodological limitations of the included studies. The lack of standardized definitions, different patient populations, and various methods to detect and prevent MEs/AEs also hindered analysis aimed at detecting the true nature and outcomes of MEs/ AEs.
Conclusion To the research team’s knowledge, this is the first systematic review and meta-analysis to provide some evidence that AEs/MEs are very common in the adult ICU population. Patients with MEs/AEs have significantly longer hospital and ICU stay and nonsignificant higher mortality. Studies examining the outcome of MEs/AEs have diverse methods, unstandardized terminology, and greater heterogeneity. Significant knowledge gaps exist, and future research is needed to study the nature and implications of errors. Acknowledgment Editing was provided by the Section of Scientific Publications, Mayo Clinic.
Authors’ Note Dr Kilickaya is a visiting scientist at the Division of Pulmonary and Critical Care Medicine and at Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC).
Declaration of Conflicting Interests The authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received the following financial support for the research, authorship, and/or publication of this article: This study was partially funded through the Critical Care Research Committee and the Center for the Science of Health Care Delivery, Mayo Clinic Rochester.
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4. Rothschild JM, Landrigan CP, Cronin JW, et al. The Critical Care Safety Study: the incidence and nature of adverse events and serious medical errors in intensive care. Crit Care Med. 2005;33:1694-1700. 5. Chang A, Schyve PM, Croteau RJ, O’Leary DS, Loeb JM. The JCAHO patient safety event taxonomy: a standardized terminology and classification schema for near misses and adverse events. Int J Qual Health Care. 2005;17:95-105. 6. Andrews LB, Stocking C, Krizek T, et al. An alternative strategy for studying adverse events in medical care. Lancet. 1997;349:309-313. 7. Bracco D, Favre JB, Bissonnette B, et al. Human errors in a multidisciplinary intensive care unit: a 1-year prospective study. Intensive Care Med. 2001;27:137-145. 8. Giraud T, Dhainaut JF, Vaxelaire JF, et al. Iatrogenic complications in adult intensive care units: a prospective twocenter study. Crit Care Med. 1993;21:40-51. 9. Osmon S, Harris CB, Dunagan WC, Prentice D, Fraser VJ, Kollef MH. Reporting of medical errors: an intensive care unit experience. Crit Care Med. 2004;32:727-733. 10. de Vries EN, Ramrattan MA, Smorenburg SM, Gouma DJ, Boermeester MA. The incidence and nature of in-hospital adverse events: a systematic review. Qual Saf Health Care. 2008;17:216-223. 11. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62:10061012. 12. Wells GA, Shea B, O’Connell D, et al. The NewcastleOttawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. http://www.ohri.ca/ programs/clinical_epidemiology/oxford.asp. Accessed June 27, 2013. 13. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557-560. 14. Altman DG BJ. Interaction revisited: the difference between two estimates. BMJ. 2003;326(7382):219. 15. Rahim SA, Mody A, Pickering J, Devereaux PJ, Yusuf S. Iatrogenic adverse events in the coronary care unit. Circ Cardiovasc Qual Outcomes. 2009;2:437-442. 16. Nuckols TK, Paddock SM, Bower AG, et al. Costs of intravenous adverse drug events in academic and nonacademic intensive care units. Med Care. 2008;46:17-24. 17. Hayashi Y, Morisawa K, Klompas M, et al. Toward improved surveillance: the impact of ventilator-associated complications on length of stay and antibiotic use in patients in intensive care units. Clin Infect Dis. 2013;56:471-477. 18. Kane-Gill SL, Kirisci L, Verrico MM, Rothschild JM. Analysis of risk factors for adverse drug events in critically ill patients. Crit Care Med. 2012;40:823-828. 19. Lilly CM, Cody S, Zhao H, et al. Hospital mortality, length of stay, and preventable complications among critically ill patients before and after tele-ICU reengineering of critical care processes. JAMA. 2011;305:2175-2183. 20. Nilsson L, Pihl A, Tågsjõ M, Ericsson E. Adverse events are common on the intensive care unit: results from a structured record review. Acta Anaesthesiol Scand. 2012;56:959-965.
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21. Merino P, Alvarez J, Martin MC, Alonso A, Gutierrez I; Syrec Study Investigators. Adverse events in Spanish intensive care units: the SYREC study. Int J Qual Health Care. 2012;24:105-113. 22. Forster AJ, Kyeremanteng K, Hooper J, Shojania KG, van Walraven C. The impact of adverse events in the intensive care unit on hospital mortality and length of stay. BMC Health Serv Res. 2008;8:259. 23. Graf J, von den Driesch A, Koch KC, Janssens U. Identification and characterization of errors and incidents in a medical intensive care unit. Acta Anaesthesiol Scand. 2005;49:930-939. 24. Kaushal R, Bates DW, Abramson EL, Soukup JR, Goldmann DA. Unit-based clinical pharmacists’ prevention of serious medication errors in pediatric inpatients. Am J Health Syst Pharm. 2008;65:1254-1260. 25. Landrigan CP, Rothschild JM, Cronin JW, et al. Effect of reducing interns’ work hours on serious medical errors in intensive care units. N Engl J Med. 2004;351:1838-1848. 26. Garrouste-Orgeas M, Timsit JF, Vesin A, et al. Selected medical errors in the intensive care unit: results of the IATROREF study: parts I and II. Am J Respir Crit Care Med. 2010;181:134-142. 27. Orgeas MG, Timsit JF, Soufir L, et al. Impact of adverse events on outcomes in intensive care unit patients. Crit Care Med. 2008;36:2041-2047. 28. Dubois RW, Brook RH. Preventable deaths: who, how often, and why? Ann Intern Med. 1988;109:582-589. 29. Vincent JL. European attitudes towards ethical problems in intensive care medicine: results of an ethical questionnaire. Intensive Care Med. 1990;16:256-264. 30. Mazor KM, Simon SR, Gurwitz JH. Communicating with patients about medical errors: a review of the literature. Arch Intern Med. 2004;164:1690-1697.
31. Lamb RM, Studdert DM, Bohmer RM, Berwick DM, Brennan TA. Hospital disclosure practices: results of a national survey. Health Aff (Millwood). 2003;22:73-83. 32. Iedema R, Allen S, Sorensen R, Gallagher TH. What prevents incident disclosure, and what can be done to promote it? Jt Comm J Qual Patient Saf. 2011;37:409-417. 33. Studdert DM, Brennan TA. No-fault compensation for medical injuries: the prospect for error prevention. JAMA. 2001;286:217-223. 34. Saxton JW, Finkelstein MM. Adverse event management: your evidence to decrease professional liability risk. J Med Pract Manage. 2008;24:5-8. 35. Byrnes MC, Schuerer DJE, Schallom ME, et al. Implementation of a mandatory checklist of protocols and objectives improves compliance with a wide range of evidence-based intensive care unit practices. Crit Care Med. 2009;37:2775-2781. 36. Ruchlin HS, Dubbs NL, Callahan MA. The role of leadership in instilling a culture of safety: lessons from the literature. J Healthc Manag. 2004;49:47-58; discussion 58-49. 37. Beckmann U, Bohringer C, Carless R, et al. Evaluation of two methods for quality improvement in intensive care: facilitated incident monitoring and retrospective medical chart review. Crit Care Med. 2003;31:1006-1011. 38. Brennan TA, Gawande A, Thomas E, Studdert D. Accidental deaths, saved lives, and improved quality. N Engl J Med. 2005;353:1405-1409. 39. Valentin A, Bion J. How safe is my intensive care unit? An overview of error causation and prevention. Curr Opin Crit Care. 2007;13:697-702. 40. Capuzzo M, Nawfal I, Campi M, Valpondi V, Verri M, Alvisi R. Reporting of unintended events in an intensive care unit: comparison between staff and observer. BMC Emerg Med. 2005;5:3.
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research-article2013
AJMXXX10.1177/1062860613514770American Journal of Medical QualityAhmed et al
Article
Outcome of Adverse Events and Medical Errors in the Intensive Care Unit: A Systematic Review and Meta-analysis
American Journal of Medical Quality 2015, Vol. 30(1) 23–30 © 2013 by the American College of Medical Quality Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/1062860613514770 ajmq.sagepub.com
Adil H. Ahmed, MBBS,1 Jyothsna Giri, MD,1 Rahul Kashyap, MBBS,1 Balwinder Singh, MBBS,1 Yue Dong, MD,1 Oguz Kilickaya, MD,1 Patricia J. Erwin, MLS,1 M. Hassan Murad, MD,1 and Brian W. Pickering, MB, BCh, MSc1
Abstract Adverse events and medical errors (AEs/MEs) are more likely to occur in the intensive care unit (ICU). Information about the incidence and outcomes of such events is conflicting. A systematic review and meta-analysis were conducted to examine the effects of MEs/AEs on mortality and hospital and ICU lengths of stay among ICU patients. Potentially eligible studies were identified from 4 major databases. Of 902 studies screened, 12 met the inclusion criteria, 10 of which are included in the quantitative analysis. Patients with 1 or more MEs/AEs (vs no MEs/AEs) had a nonsignificant increase in mortality (odds ratio = 1.5; 95% confidence interval [CI] = 0.98-2.14) but significantly longer hospital and ICU stays; the mean difference (95% CI) was 8.9 (3.3-14.7) days for hospital stay and 6.8 (0.2-13.4) days for ICU. The ICU environment is associated with a substantial incidence of MEs/AEs, and patients with MEs/AEs have worse outcomes than those with no MEs/AEs. Keywords adverse events, intensive care unit, medical error, systematic review, outcomes The Institute of Medicine report, To Err Is Human,1 started a debate on patient safety and brought attention to the high prevalence of likely preventable medical errors (MEs) and adverse events (AEs). It was subsequently proposed that preventable harm can be caused by deviation from best practices and evidence-based clinical practice guidelines, which can lead to increased patient morbidity and mortality and increased resource utilization.2 The Institute of Medicine defined an ME as “the failure of a planned action to be completed as intended (ie, an error of execution) or the use of a wrong plan to achieve an aim (ie, an error of planning).”1 Other studies have defined an AE as “an injury caused by medical management.”3 An AE was designated as “preventable” if it was attributable to error and as “negligent” if the care provided did not meet the standard care of an average qualified physician.3 Previous studies of MEs/AEs define these terms similarly4 and the terms are often used interchangeably; this can make quantifying or categorizing patient safety events difficult in the acute care setting.5 Patients admitted to the intensive care unit (ICU) during their hospital stay are more likely to experience an AE than those in other hospital units.6 The incidence of MEs/
AEs has been reported to be as high as 31% of ICU admissions.7 Some of these events result in a requirement for additional life-sustaining interventions.8 Other studies, using provider self-reporting systems, noted that the ME/AE incidence approached 20% of ICU admissions.9 A recent systematic review of in-hospital AEs found a higher incidence in surgical populations.10 Although patient safety in emergency medical services has been studied, a systematic review of MEs/AEs in ICU populations—a complex group of patients who may be especially prone to such events—has not been performed. The true incidence of errors in the ICU remains unclear, as is whether the occurrence of MEs/AEs leads to increased mortality or extended hospital or ICU stay. In this study, the research team conducted a systematic review and meta-analysis to examine the effects of MEs/AEs on mortality and hospital and ICU length of stay (LOS) among ICU patients. 1
Mayo Clinic, Rochester, MN
Corresponding Author: Adil H. Ahmed, MBBS, Division of Pulmonary and Critical Care Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905. Email: [email protected]
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Methods
Data Abstraction
This systematic review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.11
The data abstraction sheet was modified from the Cochrane data extraction template. A pilot assessment of this template was performed by the simultaneous extraction of data from 3 studies by 2 reviewers, which allowed further modification of the data abstraction sheet. The following variables were abstracted: author, country, publication year, study settings, characteristics of the study case/exposed along with control/nonexposed, study type, description of study participants, location of study (academic hospital vs nonacademic), hospital mortality, and hospital and ICU LOS. In the event of missing data, the corresponding authors of the studies were contacted twice by e-mail.
Information Sources and Search Criteria The search strategy was conducted by an expert librarian (PJE) and included 4 main databases—MEDLINE, Embase, Web of Science, and Scopus—with search dates of January 1990 through May 2013. The search strategy used the following subject headings in Ovid MEDLINE: intensive care units, burn units, coronary care units, and respiratory care units as well as ICUs and CCUs. The search was limited to the adult population. Subject headings for ME (including Medication Errors) and iatrogenic disease were enhanced with text words such as “mistake,” “error,” “missed,” “unintended,” and “near-miss.” The search was further focused using a combination of subject headings; the final concept used a combination of subject headings related to decision support (such as “clinical risk management”) and text words such as “lists” and “checklists.” These concepts were added to broaden the results and to include more quality initiative types of studies. The final strategy was then translated to the subject headings available for Ovid Embase and text words for the ISI Web of Science and Scopus. All results were filtered to include trials and cohort studies. (The exact search strategy is available from the corresponding author on request.)
Study Selection Two reviewers independently screened the abstracts and titles identified in the search using the inclusion criteria “intensive care unit” or “decision support” for one of the following: checklist, error, incident, adverse event, nearmiss, error reporting, patient safety, and medical errors. Thereafter, reviewers went in parallel through the full text of the selected studies and excluded nonoriginal research (systematic reviews and meta-analyses), descriptive studies (eg, narrative reviews, case reports, expert opinion, letter to the editor), and duplicate publications if identified on the final full article review. The interrater agreement was assessed using Cohen’s κ statistic. Any disagreement was solved by mutual consensus in the presence of a third investigator. The primary outcome of this study was in-hospital mortality; the secondary outcomes were ICU and hospital LOS among critically ill patients, comparing those with and without MEs/AEs.
Validity Assessment Two reviewers independently performed the quality assessment of study methodology using the NewcastleOttawa Scale.12 The research team used a “star system” in which a study was judged on 3 broad perspectives: selection of the study groups, comparability of the groups, and ascertainment of the exposure and outcome of interest for case-control or cohort studies. The interrater agreement was assessed, and any disagreement was solved by mutual consensus in the presence of a third investigator.
Statistical Analysis Statistical analysis was performed using Comprehensive Meta-Analysis Version 2 (Biostat, Englewood, NJ). Relative risks and differences in means with 95% confidence intervals (CIs) were estimated for the primary outcome of mortality and secondary outcomes of hospital LOS and ICU LOS. Results from each study were pooled using the DerSimonian-Laird random-effects model. Heterogeneity was assessed using the I2 statistic.13
Subgroup and Sensitivity Analysis A priori hypotheses to explain potential heterogeneity in the direction and magnitude of effect among studies included the type of study setting (academic vs nonacademic) and the preventability of errors as estimated by whether the individual study quantified the preventable AEs to be more than half of the total events in the study (>50% preventable). Moreover, a post hoc subgroup analysis was added for study location (US vs non-US setting) and if the study reported AE versus ME. The statistical significance across subgroups was examined using an interaction test.14
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Ahmed et al
Figure 1. Study flow diagram.
Abbreviations: ME/AE, medical error/adverse event; ICU, intensive care unit.
2 studies19,21 had insufficient data for meta-analysis, and their findings are summarized qualitatively. One study19 examined the association of a tele-ICU intervention with hospital mortality, LOS, and complications that are preventable by adherence to best practices. Implementation of this intervention “was associated with reduced adjusted odds of mortality and reduced hospital LOS, as well as with changes in best practice adherence and lower rates of preventable complications.”19(p.2181) The other study21 estimated the incidence and characteristics of AEs and no-harm events in critically ill patients and found that the individual risk of at least 1 incident was 62%, the risk of at least 1 no-harm event was 45%, and the risk of at least 1 AE was 29%.
Hospital Mortality Outcomes Results The search identified a total of 902 studies, 12 of which were included in the final analysis (Figure 1). The overall mean age of the patient population in the included studies was 64 years; 40% were women. Of the 12 studies, 7 were conducted in academic hospitals, 4 in a nonacademic hospital, and 1 in both settings. Two of the ICUs were exclusively medical, 8 were mixed ICUs, and 1 was a cardiac ICU; 1 other study was conducted in both medical and cardiac ICUs. Other main study characteristics are summarized in Table 1. Three authors were contacted for more information regarding nonreported outcomes, but only 1 author responded with the requested data.15
Methodological Quality The overall quality of the included studies varied from very low to high (Table 2). The research team used a score of 7 on the Newcastle-Ottawa scale as a cutoff to identify studies with adequate methodological quality. A few studies did not provide explicit descriptions of methods to protect against bias, whereas in other studies it was clear that such techniques were used. Only 1 study adequately reported complete quality criteria.16 In all, 8 studies2,7,8,15-19 were considered good quality (score ≥7), and 420-23 were deemed low quality (score 65 years
Medical
Yes
Medical error
Mortality
314 (31.6)
58 (16)
Mixed
No
Critical incident, human errors
Mortality
All consecutive pts admitted to ICU, predominantly with cardiovascular and pulmonary disorders Adult pts admitted to ICU during the study period. Those with AEs were cases and those without were controls Adult pts admitted to CCU during the study period. Those with AE were cases and those without were controls Adult ICU pts in 3 ICUs at an academic hospital in 2003 and 2004. Pts with ICU stays that extended 2 weeks or more beyond study period were excluded Adult ICU pts in 2 ICUs at a nonacademic hospital in 2003 and 2004. Pts with ICU stays that extended 2 weeks or more beyond study period were excluded Retrospective study of charts of consecutive adult pts admitted to CCU
65 (30%)
63 (14)
Medical
Yes
Mortality, ICU LOS, hospital LOS
Cases: 22 (39.3); controls: 103 (53.6) Cases: 17 (32.7); controls: 89 (48.6) Cases: 65 (46.8); controls: 59 (42.5)
Cases: 60.3; controls: 63.6
Medical
Yes
Medical and nonmedical errors Adverse event
Cases: 66.3; controls: 66.2
Cardiac
Yes
Adverse event
Mortality, ICU LOS, hospital LOS
Mixed
Yes
Adverse event
Mortality, hospital LOS
Mixed
No
Adverse event
Mortality, hospital LOS
56 (29)
Cases: 64.7 (17.7); controls: 65.1 (16.4) Cases: 64.7 (17.7); controls: 65.1 (16.4) 65 (35)
Cardiac
Yes
Adverse event
Mortality, ICU LOS, hospital LOS
75 (36)
66 (54-75)
Mixed
No
Adverse event
Mortality
2705 (43)
64 (16.8)
Mixed
Yes
Preventable complications
Mortality, ICU LOS, hospital LOS
210 (35)
62 (17)
Mixed
Yes
Adverse events and no-harm events
Mortality
With AE = 9(36); without AE = 46(45); total = 55(42)
With AE, 67; without AE, 72
Mixed
No
Medical and Medication AE
ICU LOS
Cases: (47); controls: (45)
Cases: 59; controls: 60
Mixed
Yes
ICU LOS, hospital LOS, mortality
With AE, 61(40); without AE, 150(38.5)
With AE, 53; without AE, 52
Mixed
Yes
Medication Adverse events Medical Adverse Event
All adult pts admitted to ICU at the Ottawa Hospitals. Studied from ICU admission until hospital discharge or death Consecutive hospital discharge cases from an administrative database for cases managed in each of 7 adult ICUs All pts in ICU at any time during the observation period, including those admitted and discharged during this period as well as those who died Pts >18 years old who had received care on the ICU during the years 2007 or 2008 and died on the ICU or within 96 hours after discharge from the ICU but still received care at the same hospital were included Adults admitted to the ICU from July 1998 to January 2006 and had a documented ADE in database. Adults admitted to the study institution between May 31, 2009, and January 12, 2011, who were on mechanical ventilation for >48 hours
Cases: 93 (47.9); controls: 82 (42.3)
Mortality, ICU LOS, hospital LOS
Duration of mechanical ventilation, ICU LOS, hospital LOS, mortality
Abbreviations: ICU, intensive care unit; pts, patients; LOS, length of stay; AE, adverse events; CCU, cardiac care unit; ADE, adverse drug event; SD, standard deviation. a Age is given as mean, mean (SD), or median (interquartile range), unless otherwise noted.
Discussion The research team conducted a systematic review and meta-analysis to examine the effects of MEs/AEs on mortality and hospital and ICU LOS among ICU patients. This meta-analysis showed that patients with MEs/AEs have significantly longer ICU and hospital stays. They also may have higher mortality, but the results were associated with significant heterogeneity and the analysis became nonsignificant using a random-effects model. In addition, the confidence in the provided estimates is low
(ie, low-quality evidence at risk of bias) because of the observational nature of the studies, the unexplained heterogeneity, the inability to evaluate publication bias, and the lack of robustness of analysis (results differ based on the choice of model). The research team used the random effects model because it includes within-study and between-study heterogeneity in the width of the CI; hence, it is more conservative. However, the team also presented an alternate model to demonstrate the effect of the analysis method used. Overall, considering both models, patients with errors may have worse outcomes, but
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Ahmed et al Table 2. Methodological Quality of Included Studies. Newcastle-Ottawa Scorea Studies b,8
Giraud et al (1993) Bracco et al (2001)b,7 Graf et al (2005)b,23 Kaushal et al (2007)c,2 Forster et al (2008)b,22 Nuckols et al (2008)c,16 Rahim et al (2009)b,15 Lilly et al (2011)b,19 Merino et al (2012)b,21 Nilsson et al (2012)b,20 Kane-Gill et al (2012)c,18 Hayashi et al (2012)b,17
Selection
Comparability
Exposure
Total Number of Stars
*** *** *** **** ** **** **** **** **** *** *** ****
** * * ** ** ** * *
** ***
7/9 7/9 4/9 8/9 5/9 9/9 8/9 7/9 5/9 6/9 7/9 8/9
** * *** *** ** * *** *** ***
* *
a
The studies were scored on a “star” system (denoted here by asterisks), in which a maximum of 1 star is given for each item within the “Selection” and “Exposure/Outcome” categories and a maximum of 2 stars for “Comparability.” b Cohort study. c Case-control study.
Figure 2. Mortality outcome of adverse events (AEs) and medical errors (MEs) across the included studies. Abbreviation: CI, confidence interval.
the magnitude of the effect may not be reliable as derived from the current data. This meta-analysis is aligned with results from previous individual studies.25 Differences in patient populations and the lack of standardized definitions of MEs/AEs may result in difficulty comparing rates of MEs/AEs across ICU populations.26 Moreover, assessing the effects of MEs/AEs is difficult because of differences in case mix, confounding factors for mortality, and multiple MEs/AEs in the same patient.27 Although MEs/AEs are undesirable, there is a certain inevitability to their occurrence in the ICU.26 The available evidence failed to establish an expected strong
relationship between errors and mortality.22 The research team postulates that fatal or substantial harmful errors or AEs that could result in death may have been underreported in the presented studies.28 Intensivists recognize the necessity of disclosing the occurrence of harmful events to their patients, yet less than half of them actually report it.29 Although some reports suggest that US physicians are more likely to disclose errors than their European counterparts,30 the discrepancy between the rate of ME/ AE occurrence and the rate of disclosure is substantial.31 Iedema et al32 listed lack of physician awareness of what and how to disclose along with the moral challenges to
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American Journal of Medical Quality 30(1)
Figure 3. Hospital and ICU length of stay outcome for adverse events (AEs) and medical errors (MEs) across included studies. Abbreviations: CI, confidence interval; MICU, medical intensive care unit; CCU, cardiac care unit; ICU, intensive care unit.
report other colleagues as some of the barriers to disclosure and handling MEs/AEs; they also place emphasis on making suitable organizational reforms to have a disclosure policy in place. As suggested by Studdert et al,33 the fear of litigation poses a substantial obstacle to transparency. However, others discussed the importance of communication and disclosure as being most crucial to liability reduction and strengthening the physician-patient relationship.34 Human factors were identified frequently in the literature7; some studies suggested that higher workload is a major contributor of MEs/AEs8 but other studies fail to prove that.23 Errors of omission related to application of evidence-based practice are rarely reported and become targets for quality improvement projects through the application of checklists and electronic alerts.35 System or organizational factors characterize the second component of ME/AE roots. Although health care organizations recognized the significance of maintaining a safe and error-free environment, several challenges such as rising health care costs and the failure to sustain a robust reporting practice hindered the leadership in adopting such initiatives.36 Various methods to detect MEs/AEs have been described, typically yielding different results.37 The method of detection of MEs/AEs also varied among the studies included in this report; prospective direct field observation was used in 2 studies,8,22 retrospective or prospective chart review in 5 studies,2,15,16,19,21 and an incident report form and standardized data sheet in the remaining 2.7,23 Because the numbers of MEs/AEs depend on the method of detection, it is important to recognize
the differences between the 3 methods used. Voluntary or self-reporting is common and used in many studies9; however, fear of litigation is a major drawback, which potentially results in failure to self-report serious and harmful events and a tendency to overlook minor events that appear to be of no consequence from the reporter’s perspective.38 The second method, retrospective chart review, relies heavily on the quality of documentation and reviewer interpretation.39 Direct field observation demonstrated superiority over self-reporting, especially for detection of errors of omission,40 and there has been a steady increase in the use of this method in the past decade, with cost and workload being the main limitations.
Strengths and Limitations This review and meta-analysis used a comprehensive literature search and rigorous inclusion criteria to identify studies relevant to the research team’s objectives, applied bias protection measures in the selection of the studies, and evaluated study methodological quality. However, the team limited the outcome measures to mortality and LOS exclusively among ICU patients. Although the search was comprehensive, it is possible that some citations were missed, and as with all systematic reviews, selective availability of studies with positive results might have resulted in hard-to-detect publication bias. Moreover, excluding children risks excluding studies that include both adults and children. It is plausible that many quality improvement projects evaluated ICU errors in local settings but remained internal documents and were
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Ahmed et al not published. Therefore, inferences are limited by the low quality of the evidence, considering the imprecision, heterogeneity, and methodological limitations of the included studies. The lack of standardized definitions, different patient populations, and various methods to detect and prevent MEs/AEs also hindered analysis aimed at detecting the true nature and outcomes of MEs/ AEs.
Conclusion To the research team’s knowledge, this is the first systematic review and meta-analysis to provide some evidence that AEs/MEs are very common in the adult ICU population. Patients with MEs/AEs have significantly longer hospital and ICU stay and nonsignificant higher mortality. Studies examining the outcome of MEs/AEs have diverse methods, unstandardized terminology, and greater heterogeneity. Significant knowledge gaps exist, and future research is needed to study the nature and implications of errors. Acknowledgment Editing was provided by the Section of Scientific Publications, Mayo Clinic.
Authors’ Note Dr Kilickaya is a visiting scientist at the Division of Pulmonary and Critical Care Medicine and at Multidisciplinary Epidemiology and Translational Research in Intensive Care (METRIC).
Declaration of Conflicting Interests The authors declared no conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received the following financial support for the research, authorship, and/or publication of this article: This study was partially funded through the Critical Care Research Committee and the Center for the Science of Health Care Delivery, Mayo Clinic Rochester.
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