An Internal Quality Improvement Collaborative Significantly Reduces Hospital-Wide Medication Error Related Adverse Drug Events Richard E. McClead, Jr., MD, MHA1,2, Charline Catt, RN1, J. Terrance Davis, MD1, Shelly Morvay, PharmD1, Jenna Merandi, PharmD1, Dorcas Lewe, RN1, Barbara Stewart, RN1, and Richard J. Brilli, MD1,3, on behalf of the Adverse Drug Event Quality Collaborative* Objective To reduce the rate of harmful adverse drug events (ADEs) of severity level D-I from a baseline peak of 0.24 ADE/1000 doses to 0.08 ADE/1000 doses. Study design A hospital-wide, quasi-experimental time series quality improvement (QI) initiative to reduce ADEs was implemented. High-reliability concepts, microsystem-based multidisciplinary teams, and QI science methods were used. ADEs were detected through a combination of voluntary reporting, trigger tool analysis, reversal agent review, and pharmacy interventions. A multidisciplinary ADE Quality Collaborative focused on medication use processes, not on specific classes of medications. Effective interventions included huddles and an ADE prevention bundle. Results The rate of harmful ADEs initially increased by >65% because of increased error reporting, temporally associated with the implementation of a program focused on high reliability and an improved safety culture. The quarterly rate was 0.17 ADE/1000 dispensed doses in Q1 2010. By the end of Q2 2013, the rate had decreased by 76.5%, to 0.04 ADE/1000 dispensed doses (P < .001). Conclusion Using an internal collaborative model and QI methodologies focused on medication use processes, harmful ADEs were reduced hospital-wide by 76.5%. The concurrent implementation of a high-reliability, safetyfocused program was important as well. (J Pediatr 2014;165:1222-29).
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edication errors are common and significant causes of preventable harm, particularly for hospitalized children, in whom medication errors are 3 times more common than in adults.1 Children are more prone to medication errors and resulting harm for several reasons. First, pediatric weight-based dosing requires use of nonstandard medication preparations that are subject to miscalculations in prescribing, dispensing, and administration processes. Second, immature metabolic systems are less tolerant of medication errors. Finally, children may be unable to communicate regarding the symptoms of an adverse drug event (ADE).2 Estimates of the frequency of harmful medication errors or ADEs range from 13.4 to 49.8 per 1000 patient-days.3,4 In the fall of 2008, Nationwide Children’s Hospital (NCH) set a goal of eliminating preventable patient harm. A key metric in monitoring the success of the safety program was the Preventable Harm Index.5 At that time, medication errors accounted for nearly two-thirds of preventable patient harm, with more than 50% of those errors related to medication administration and smaller percentages related to prescribing and dispensing processes. The most common administration errors involved failure to perform the “5 rights of medication administration.”6 One-half of the preventable medication errors occurred in the critical care units; thus, the initial ADE reduction effort focused on medication administration errors in the critical care units. Eventually the other medication management processes were addressed, and the improvement effort spread throughout the hospital system.
Methods Medications errors are mistakes in the prescribing, dispensing, administration, or monitoring of medications. ADEs, as defined here, are preventable medication errors that reach the patient and cause some deADE ADEQC BCMA CPOE EMR IV NCCMERP NCH QI
Adverse drug event Adverse Drug Event Quality Collaborative Bar-coded medication administration Computerized practitioner order entry Electronic medical record Intravenous National Coordinating Council for Medication Error Reporting and Prevention Nationwide Children’s Hospital Quality improvement
From the 1Nationwide Children’s Hospital; and Department of Pediatrics, 2Division of Neonatology; 3 Division of Critical Care Medicine, The Ohio State University, Columbus, OH *A list of members of the Adverse Drug Event Quality Collaborative is available in the Appendix (available at www.jpeds.com). Funded by Cardinal Health Foundation (PI: R.M.). The authors declare no conflicts of interest. 0022-3476/$ - see front matter. Copyright ª 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2014.08.063
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Vol. 165, No. 6 December 2014 gree of harm. Potential ADEs are medication errors in which prevention strategies (eg, pharmacist interventions with prescribers) prevent the error from reaching the patient. This quality improvement (QI) effort involved implementation of evidence-based interventions or best practices designed to meet an established goal of zero patient harm from ADEs. No interventions involved a comparison of devices or therapies, and patients were not subjected to randomization. Medical records were accessed by QI team members as part of their normal responsibilities. No personal health information was shared. Therefore, the need for Institutional Review Board approval was waived (personal communication, Alex Rawkowsky, MD, Chairman, NCH Institutional Review Board). NCH is an academic, nonprofit, 450-bed freestanding children’s hospital located in Columbus, Ohio. Annually, the hospital provides care to more than 1 million outpatients, performs 26 000 surgeries, and has 25 000 inpatient discharges. The NCH pharmacy dispenses more than 1.5 million medication doses per year. The current electronic medical record (EMR) and computerized practitioner order entry (CPOE) systems (Epic Systems, Verona, Wisconsin) are fully integrated with clinical decision making support. ADE and medication error detection methodology includes a voluntary electronic event reporting system, monthly 20-chart trigger tool analysis,7,8 100% review of all dispensed reversal agents (eg, naloxone), and pharmacist interventions with prescribing practitioners. The severity of ADEs is measured using a variation of the National Coordi-
nating Council for Medication Error Reporting and Prevention (NCCMERP) Scale.9 (A detailed description of the NCCMERP Scale is available at http://www.nccmerp.org/ pdf/indexColor2001-06-12.pdf.) We classified ADEs with a NCCMERP severity level of D-I as harmful. Relatively minor level D medication errors were more frequent and involved the same failure modes as more serious ADEs, and thus were included to ensure a sufficient number of ADEs to allow identification of opportunities for improvement. The primary outcome metric was the rate of ADEs per 1000 dispensed doses over time. The numerator was the number of ADEs identified by the detection strategies, and the denominator was total medications dispensed. Secondary metrics included total detected ADEs regardless of severity per 1000 dispensed doses and total nonharmful potential ADEs (severity level A-C) per 1000 dispensed doses. Statistical process control charts10 were used to show outcome metric progress and assess the impact of interventions over time. Collaborative Model and Improvement Methodology In July 2009 (phase 1), an internal QI collaborative comprising multidisciplinary representatives from all critical care units and 2 additional units that were experiencing frequent ADEs was convened. This ADE Quality Collaborative (ADEQC) mirrored the Institute for Healthcare Improvement Breakthrough Series11 and used the Model for Improvement.12 Figure 1 illustrates the initial specific aim and key driver diagram developed by the ADEQC. The
Figure 1. Specific aim and key driver diagram for the ADEQC. The baseline was not officially determined until February 2010, when reporting of ADEs peaked as the full impact of the safety program was felt. The key drivers are barriers that must be overcome to impact the specific aim. Typically, key drivers are expressed as elements that must be addressed to achieve the specific aim; however, the key driver diagram as presented here is what we used to drive change. CTICU, cardiothoracic intensive care unit; PDSA, plan-do-study-act. 1223
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peak ADE baseline rate of 0.24 per 1000 dispensed doses was not established until February 2010, when reporting of ADEs was at its peak. The interim goal of 0.08 ADE per 1000 dispensed doses by December 2011 was chosen empirically. The key drivers were those processes related to the medication use phase and collaborative communication. The ADEQC met monthly, reviewed unit-specific data, discussed recent ADEs, and developed interventions. Successful intervention strategies were disseminated to other units within the collaborative. After multiple successful interventions, the ADEQC was expanded in the spring of 2011 (phase 2) to include the remaining inpatient units, emergency department, outpatient clinics, and urgent care centers. Interventions Before the ADEQC, all of the prevention strategies described by Miller et al13 and the Joint Commission2 had been implemented except for an automated ADE detection system and bar-coded medication administration (BCMA). ADEQC interventions included CPOE, automated dispensing cabinets, clinical pharmacist rounding in the intensive care units, unit dose drug dispensing, weight-based dosing, and a pediatric drug formulary. Additional interventions intended to impact the key drivers of ADEs and medication errors are outlined in Figure 1. Key interventions aimed at administration errors included: (1) revision of the hospital’s independent double-check process for high-risk medications, to clarify performance expectations (as originally written, the policy was subject to varying interpretations by front-line nurses); (2) implementation of a wireless communication system (Vocera, San Jose, California) to allow nurses to identify readily available colleagues to assist with the independent double-check process; (3) addition of smart syringe and large-volume infusion pumps with drug libraries (Alaris System; Carefusion, San Diego, California), to alert the nursing staff to possible pump programming and/ or dosing errors; (4) rigorous unit-based audits of the 5 rights of medication administration; and (5) implementation of a BCMA system in April 2011. For the unit-based audits, each month a medication safety nurse observed 10 medication administration events on each inpatient unit. Each staff nurse was asked to describe the steps in the medication administration process as she or he performed it, and the medication safety nurse then completed a detailed checklist of the correctly performed steps and reported unit performance to the ADEQC and unit leadership. Prescribing error prevention interventions included review of the medication reconciliation process and modifications to the electronic medication reconciliation template. Inaccurate weight was addressed by creating an “aberrant weight alert” in the EMR if the recorded weight was 10% higher or lower than the expected weight based on established growth curves. In addition, the alert required documentation of the method for obtaining the admission weight (ie, scale, parent report, or estimate). 1224
Vol. 165, No. 6 Dispensing errors were related primarily to delivery of stat drugs to the patient care units. This problem area was addressed by reconfiguring the process for urgent drug preparation and redesigning the process for storing pneumatic tubes, to increase the number available in the pharmacy for urgent delivery purposes. Two interventions were particularly effective: development and auditing of an ADE “prevention bundle” and a post–medication error apparent cause “huddle” process. ADE Prevention Bundle An ADE bundle was developed that included those practices which if done correctly and completely would minimize the risk of medication errors. The initial bundle elements included documented review of home medications, application of the 5 rights of medication administration with independent double-checks, use of smart pump libraries, accurate weight documentation, and BCMA when available. Random monthly chart audits reviewing documentation for each ADE bundle element were conducted by unit-based nursing “medication safety champions” and reported to the ADEQC. In February 2012, additional ADE bundle elements were added, including management of appropriate intravenous (IV) tubing setups and compliance with proper administration of secondary IV infusions. ADE Huddles The huddle process14 examined harmful ADEs to learn from frontline staff why the event occurred and what might be done to prevent similar future events. Following an ADE, be it related to prescribing, dispensing, administering, or monitoring, an ADEQC team met with unit nursing leadership and the involved medical and hospital staff members. The ADE was reviewed using a standardized set of questions intended to identify improvement opportunities.15 Example questions included “What happened?,” “Was an accurate handoff performed?,” and “Was the patient care assignment typical?” The equipment involved in the ADE (eg, infusion pumps) and the patient’s actual EMR were reviewed to simulate the error with the staff member and to identify any contributing factors. Potential interventions to mitigate future ADEs identified during the huddle process were entered into a Web-based platform. Accountability for completion of each intervention was assigned by the huddle team. Completion of recommended interventions was monitored by QI analysts.16 The results of unit-based intervention trials were presented at the monthly ADEQC meetings and, when appropriate, disseminated throughout the hospital. Additional details of the ADE huddle process are provided elsewhere.15 Safety Culture Activities Beginning in 2008-2009 and coinciding with the work of the ADEQC, NCH embarked on a journey toward high reliability practices and just culture accountability (known as Zero Hero). A goal of eliminating preventable harm was established. The details of the Zero Hero program are described McClead Jr. et al
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December 2014 elsewhere.17,18 Following implementation of this safety culture program, reporting of nonharmful medication errors (NCCMERP severity level A-C) increased by 65.4%, with the increase sustained through Q3 2013. This new reporting culture greatly facilitated the effort to identify and eliminate harmful ADEs.
Results Reduction in Medication Errors Causing Harmful ADEs Figure 2 depicts ADEs per 1000 dispensed doses, annotated with various improvement interventions. The initial ADE rate increase coincided with increased error reporting and detection. ADEs peaked in 2010. By March 2011, the ADE rate had decreased by 52%, from a mean of 0.17 to 0.08 per 1000 doses dispensed (P < .001). By December 2012, the rate had further declined to 0.04 per 1000 doses dispensed, a 76.5% decrease from peak value (P < .001). This occurred even as the units reporting ADEs to the collaborative expanded to include all inpatient units, perioperative and emergency services, and outpatient clinics (ADEQC phase 2). During the collaborative time period, a total of 7511 medication events were reported, of which 462 were category D events (6.2%) and 273 were category E events (3.97%). However, only 28 ADEs (0.4%) caused serious harm (category F or higher). No ADE-related deaths occurred while the ADEQC was active. During 2012, the medications most often associated with harmful ADEs were vaccines (29%), analgesics and narcotics (16%), insulin (9%), IV fluids (9%), and parenteral nutrition (6%). Figure 3 shows the total number of nonharmful medication errors (NCCMERP severity level A-C) and
ADEs (severity level D-I) by quarter. There was a progressive increase in reported nonharmful medication errors reporting per quarter, but a decrease in reported ADEs (by definition harmful). Figure 4 shows the proportional changes in the distribution of error types between 2010 and 2012. In 2010, administration errors accounted for 55% of all ADEs, and prescribing errors for 32%. As the number of ADEs decreased through 2012, the proportions were reversed, with administration errors decreasing to 38% of the total and prescribing errors increasing to 52% of a smaller number of total harmful ADEs. The proportional change in administration and prescribing errors in 2010 compared with 2012 was statistically significant (P < .001). The changes in the other categories (dispensing, monitoring, and other) were small and statistically unchanged. Residents and attending physicians account equally for 90% of prescribing errors, with advanced practice nurses accounting for the remaining 10%. ADE Bundle Audits Overall compliance with initial ADE bundle elements improved over time, peaking at 98% in October 2010 (Figure 5). Subsequent audit compliance remained above 94% through October 2011. After revision of the ADE bundle in February 2012, compliance fell below 90% until October 2012. Since March 2013, overall ADE bundle compliance has ranged from 93% to 96%. Compliance with individual bundle elements was as follows: 5 rights and double-checks, 99%-100%; syringe and infusion pump medication library audits, 100%; accurate admission weights, 91%-95%; EMR documentation of medication reconciliation review, 84%-91%; bar code scanning of
Figure 2. Monthly rate of harmful ADEs per 1000 dispensed doses. *P < .001. PIC, pediatric intensive care unit; RMH MAR, Riverside Methodist Hospital medication administration record; Amb MAR, Ambulatory medication administration record. An Internal Quality Improvement Collaborative Significantly Reduces Hospital-Wide Medication Error Related Adverse Drug Events
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Figure 3. Harmful ADEs (NCCMERP severity level D-I) and nonharmful ADEs (NCCMERP severity level A-C) by quarter. The number of harmful ADEs per quarter decreased by 74.1%.
patients, >97%; bar code scanning of medications, >93%. Compliance with management of appropriate IV tubing setups and with proper administration of secondary IV infusions was 98% and 95%, respectively.
roughly 92% have been implemented.16 Huddles also have led to the formation of task forces to address complex issues, such as the inpatient management of home insulin infusion pumps, EMR alert fatigue, and therapeutic drug monitoring.
ADE Huddles Between March 2010 and June 2013, more than 900 huddles were conducted. The apparent causes of ADEs identified during the huddle process are described elsewhere.15 Some key themes emerged, including failure of the 5 rights of medication administration, inaccurate medication reconciliation, and improper independent double-check of high-risk medications. Of the more than 3000 huddle recommendations,
Discussion The 76.5% reduction in the rate of harmful ADEs during the study period occurred despite the expansion of the ADEQC to include the entire inpatient and outpatient hospital system. We believe that the key factors contributing to the collaborative’s success were the internal quality collaborative model, focus on medication management failure modes,
Figure 4. Distribution of error types, 2010 vs 2012, and total number of ADEs of severity level D-I. *P < .001. Note the prevalence of administration errors in 2010 that changed to predominantly prescribing errors in 2012.
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Figure 5. Compliance with use of the ADE bundle was excellent a few months after initiation in May 2010. However, performance degraded in February 2012 following a revision of the bundle and the opening of a new 12-story patient tower in August 2012. Compliance subsequently improved and has remained at or near the goal (94%) since April 2013.
reliable use of an ADE prevention bundle, ADE huddles, and the evolution of a safety culture that led to increased medication error reporting. The quality collaborative model can “accelerate the translation of evidence into practice and improve care and outcomes for children.”19 We adapted this approach to a single hospital system that included a diverse group of inpatient and outpatient units. A unique aspect of this work was the strategy to focus initially on the processes of medication management (ie, administration, prescribing, dispensing, monitoring) and to apply this to all classes of medications. This approach is different from that reported by others. Most previous studies focused on specific medications or groups of medications and often involved only a few patient care units over a relatively short time period.20-24 Others focused on ADE rate determination,1,3,4,25-27 epidemiologic characteristics of medication errors,13,28-30 or single ADE prevention strategies.31,32 A few studies involved multicenter collaborative networks that implemented a variety of prevention strategies, but the major outcome was reduction of ADEs for a single class of medications, such as opioids.33,34 Our work encompasses most of the foregoing strategies applied across all medication groups. By achieving high compliance with the prevention bundle strategies, we showed robust improvement for the entire organization. A factor that we believe contributed to the significant increase in voluntarily ADE reporting was the enhanced safety culture, reflected by a statistically significant improvement in NCH safety survey data from 2009 to 2011.16,18 Others have reported the association between an improved safety culture
and prevention of patient harm, including ADEs.35,36 Although the majority of our identified failures were system failures, individual failures were identified as well. Managers used an accountability tool adapted from Reason’s Decision Tree for Determining Culpability for Unsafe Acts to develop an intervention action plan designed to improve performance for those individuals.37 A residual challenge has been prescribing errors. As a result of the success achieved in decreasing administration errors, prescribing errors now predominate. The current emphasis is on reducing prescribing errors in 5 persistently problematic areas: medication reconciliation, insulin therapy, therapeutic drug monitoring, neonatal total parenteral nutrition orders, and EMR alert fatigue (ie, frequent electronic alerts resulting in recurrent overrides). Others have focused on reducing prescribing errors. An Australian group38 reported a 4-year study at an urban children’s hospital using interventions targeting prescribing errors. Intensive care units were excluded. Their program achieved a >50% reduction in total ADEs over the study period (P < .05). These results are comparable with ours in the present study, which focused on all medication management failure modes for an entire hospital system and achieved a 76.5% ADE reduction from peak (Figure 2; P < .001). The present study has several limitations. First, it was conducted at a single freestanding children’s hospital system. Although not all hospitals have access to advanced medication safety technology (ie, smart pumps, BCMA, and CPOE), we believe that the resources needed to implement
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an effective ADE prevention bundle, as described here, are readily available. Second, much of the ADE reporting resulted from voluntary event reports. All ADE detection methods have strengths and weaknesses.39,40 As noted by Takata et al,3 there is no gold standard for identifying ADEs. They referred to the robustness of the monthly 20-chart trigger tool methodology; however, our data suggest that a voluntary reporting system within a culture of safety can be equally valuable. We believe that combining a robust voluntary reporting system with an effective pharmacy reporting trigger tool system may provide the best ADE detection approach. With the exception of opioid-induced constipation resulting from omission of laxatives during therapy, we did not find any harmful ADEs using the trigger tool methodology that had not been previously identified by the voluntary event reporting system. Although underreporting of harmful ADEs is possible, the overall sustained increase in ADE reporting that followed implementation of the safety culture program supports our belief that underreporting is minimal. We believe that nonharmful ADEs, especially those from pharmacist intervention of practitioner orders, are underreported, however. A 1-month audit of pharmacist phone calls to practitioners identified approximately 50 interventions per day. Many of these interventions resulted in changes to the medication orders and the prevention of potentially harmful ADEs. Few of these interventions were reported because of pharmacist and practitioner time constraints. Overall, we agree with Miller et al that “an ideal error identification system may involve multiple data sources.”13 That idea is the basis of our medication error reporting and identification system. We believe that the success of this system derives from the use of QI collaborative methodologies, an evolving high-reliability and safety-focused culture, and reliable implementation of an ADE prevention bundle of care practices. n We acknowledge T. Arthur Wheeler MS, MSES, MBA, for assistance with statistical analysis of the data presented in this study, as well as the support of Michael Fetzer, BSISE, Emily Mackal, RHIA, MBA, Jeffrey Hoffman, MD, Laura Rust, MD, Stacy Kuehn, RN, and James Gallup, MBA, for their assistance with ADEQC leadership and data analysis and preparation. Submitted for publication Dec 22, 2013; last revision received Jul 14, 2014; accepted Aug 27, 2014. Reprint requests: Richard E. McClead, Jr., MD, MHA, Department of Pediatrics, Nationwide Children’s Hospital, Room ED 333, 700 Children’s Dr, Columbus, OH 43205. E-mail: [email protected]
References 1. Kaushal R, Bates DW, Landrigan C, McKenna KJ, Clapp MD, Federico F, et al. Medication errors and adverse drug events in pediatric inpatients. JAMA 2001;285:2114-20. 2. Joint Commission. Preventing pediatric medication errors. Sentinel Event Alert 2008;39:1-5. 3. Takata GS, Mason W, Taketomo C, Logsdon T, Sharek PJ. Development, testing, and findings of a pediatric-focused trigger tool to identify medication-related harm in US children’s hospitals. Pediatrics 2008; 121:e927-35. 1228
Vol. 165, No. 6 4. Kirkendall ES, Kloppenborg E, Papp J, White D, Frese C, Hacker D, et al. Measuring adverse events and levels of harm in pediatric inpatients with the Global Trigger Tool. Pediatrics 2012;130:e1206-14. 5. Brilli RJ, McClead RE Jr, Davis T, Stoverock L, Rayburn A, Berry JC. The Preventable Harm Index: an effective motivator to facilitate the drive to zero. J Pediatr 2010;157:681-3. 6. Hughes R. Patient safety and quality: An evidence based handbook for nurses. Publication 08-0043. Rockville (MD): Agency for Healthcare Research and Quality; 2008. 7. Rozich JD, Haraden CR, Resar RK. Adverse drug event trigger tool: a practical methodology for measuring medication-related harm. Qual Saf Health Care 2003;2:194-200. 8. Children’s Hospital Association. [homepage on the Internet, CHCA Link] Shawnee Mission, KS: c 2009. PICU Trigger instruction manual: measuring adverse events in the PICU using a PICU trigger tool. [19 screens] Available from: http://www.chca.com/triggers/docs/PICU_ triggertoolkit_for%20CHCAwebsite.pdf. Accessed October 2, 2014. 9. Hartwig SC, Denger SD, Schneider PJ. Severity-indexed, incident reportbased medication error-reporting program. Am J Hosp Pharm 1991;48: 2611-6. 10. Provost LP, Murray S. The health care data guide: Learning from data for improvement. San Francisco (CA): Jossey-Bass; 2011. 11. Kilo CM. A framework for collaborative improvement: lessons from the Institute for Healthcare Improvement’s Breakthrough Series. Qual Manag Health Care 1998;6:1-14. 12. Langley GJ, Moen R, Nolan KM, Nolan TW, Norman CL, Provost LP. The Improvement Guide: A practical approach to enhancing organizational performance. San Francisco (CA): Jossey-Bass; 2009. 13. Miller MR, Robinson KA, Lubomski LH, Rinke ML, Pronovost PJ. Medication errors in paediatric care: a systematic review of epidemiology and an evaluation of evidence supporting reduction strategy recommendations. Qual Saf Health Care 2007;16:116-26. 14. Wilbur K, Scarborough K. Medication safety huddles: teaming up to improve patient safety. Can J Hosp Pharm 2005;58:151-5. 15. Morvay S, Stewart B, Catt C, McClead RE, Brilli R. How to conduct medication event huddles: a tool for reducing adverse drug events. Jt Comm J Qual Patient Saf 2013;40:39-45. 16. Merandi J, Morvay F, Lewe D, Stewart B, Catt C, Chanthasene P, et al. Improvement of medication event interventions through use of an electronic database. Am J Health Syst Pharm 2013;70:1708-14. 17. Crandall WV, Davis JT, McClead R, Brilli RJ. Is preventable harm the right patient safety metric? Pediatr Clin North Am 2012;59: 1279-92. 18. Brilli RJ, McLead RE Jr, Crandall WV, Stoverock L, Berry JC, Wheeler TA, et al. A comprehensive patient safety program can reduce significantly preventable harm, associated costs, and hospital mortality. J Pediatr 2013;163:1638-45. 19. Lannon CM, Miles PV. Pediatric collaborative improvement networks: bridging quality gaps to improve health outcomes. Pediatrics 2013; 131:S187-8. 20. Leonard MS, Cimino M, Shaha S, McDougal S, Pilliod J, Brodsky L. Risk reduction for adverse drug events through sequential implementation of patient safety initiatives in a children’s hospital. Pediatrics 2006;118: e1124-9. 21. Porter SC, Kaushal R, Forbes PW, Goldmann D, Kalish LA. Impact of a patient-centered technology on medication errors during pediatric emergency care. Ambul Pediatr 2008;8:329-35. 22. Burmester MK, Dionne R, Thiagarajan RR, Laussen PC. Interventions to reduce medication prescribing errors in a paediatric cardiac intensive care unit. Intensive Care Med 2008;34:1083-90. 23. Holdsworth MT, Fichtl RE, Raisch DW, Hewryk A, Behta M, MendezRico E, et al. Impact of computerized prescriber order entry on the incidence of adverse drug events in pediatric inpatients. Pediatrics 2007;120: 1058-66. 24. Wang JK, Herzog NS, Kaushal R, Park C, Mochizuki C, Weingarten SR. Prevention of pediatric medication errors by hospital pharmacists and the potential benefit of computerized physician order entry. Pediatrics 2007;119:e77-85.
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December 2014 25. Kaushal R, Goldmann DA, Keohane CA, Christino M, Honour M, Hale AS, et al. Adverse drug events in pediatric outpatients. Ambul Pediatr 2007;7:383-9. 26. Kaushal R, Bates DW, Abramson EL, Soukup JR, Goldmann DA. Unitbased clinical pharmacists’ prevention of serious medication errors in pediatric inpatients. Am J Health Syst Pharm 2008;65:1254-60. 27. Agarwal S, Classen D, Larsen G, Tofil NM, Hayes LW, Sullivan JE, et al. Prevalence of adverse events in pediatric intensive care units in the United States. Pediatr Crit Care Med 2010;11:568-78. 28. Latif A, Rawat N, Pustavoitau A, Pronovost PJ, Pham JC. National study on the distribution, causes, and consequences of voluntarily reported medication errors between the ICU and non-ICU settings. Crit Care Med 2013;41:389-98. 29. Bourgeois FT, Mandl KD, Valim C, Shannon MW. Pediatric adverse drug events in the outpatient setting: an 11-year national analysis. Pediatrics 2009;124:e744-50. 30. van Rosse F, Maat B, Rademaker CM, van Vught AJ, Egberts AC, Bollen CW. The effect of computerized physician order entry on medication prescription errors and clinical outcome in pediatric and intensive care: a systematic review. Pediatrics 2009;123:1184-90. 31. Fortescue EB, Kaushal R, Landrigan CP, McKenna KJ, Clapp MD, Federico F, et al. Prioritizing strategies for preventing medication errors and adverse drug events in pediatric inpatients. Pediatrics 2003;111: 722-9.
ORIGINAL ARTICLES 32. Ferranti J, Horvath MM, Cozart H, Whitehurst J, Eckstrand J. Reevaluating the safety profile of pediatrics: a comparison of computerized adverse drug event surveillance and voluntary reporting in the pediatric environment. Pediatrics 2008;121:e1201-7. 33. Sharek PJ, McClead RE, Taketomo C, Luria JW, Takata GS, Walti B, et al. An intervention to decrease narcotic-related adverse drug events in children’s hospitals. Pediatrics 2008;122:e861-6. 34. Tham E, Calmes HM, Poppy A, Eliades AB, Schlafly SM, Namtu KC, et al. Sustaining and spreading the reduction of adverse drug events in a multicenter collaborative. Pediatrics 2011;128:e438-45. 35. Neuspiel DR, Stubbs EH, Liggin L. Improving reporting of outpatient pediatric medical errors. Pediatrics 2011;128:e1608-13. 36. Smetzer J, Navarra M. Measuring change: a key component of building a culture of safety. Nurs Econ 2007;25:49. 37. Reason JT. Managing the risks of organizational accidents. Burlington (VT): Ashgate Publishing; 1997. 38. Gazarian M, Graudins LV. Long-term reduction in adverse drug events: an evidence-based improvement model. Pediatrics 2012;129:e1334-42. 39. Meyer-Massetti C, Cheng CM, Schwappach DL, Paulsen L, Ide B, Meier CR, et al. Systematic review of medication safety assessment methods. Am J Health Syst Pharm 2011;68:227-40. 40. Flynn EA, Barker KN, Pepper GA, Bates DW, Mikeal RL. Comparison of methods for detecting medication errors in 36 hospitals and skillednursing facilities. Am J Health Syst Pharm 2002;59:436-46.
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Appendix Members of the ADEQC (NCH, Columbus, Ohio) include: Craig Anderson, MD; Carl Backes, Sr., MD; Vicky Armstrong, RN; Jane Balint, MD; Daniel Barr; Thomas Bartman, MD; Amy Biddle, RN; Mindy Bibart, RN; Angela Blankenship; Richard Brilli, MD; Janice Cannon, RN; Lisa Carney, RN; Steve Cassidy, MD; Charline Catt, RN; Tamara Clark, APN; Kimberly Conkol, RN; William Cotton, MD; Wallace Crandall, MD; Pam Creech, RN; Mike Cummings; James Dail; Kim Davis; Carlo Dilorenzo, MD; Richard Fernandez, MD; Michael Fetzer; Randy Frost; James Gallup; Renee Gardikes, RN; Justin Golias; Cindy Hafer; Melissa Hamms, RN; Judy Hanlon, RN; Sheilah Harrison; Hannah Hays, MD; Wendy Heiligmann, RN; Debbie Hockett RN; Jeffrey Hoffman, MD; Timothy Hoffman, MD; Scott Holliday, MD; Rhonda Humphrey, RN; Karla Johnson, RN; Heath Jolliff, DO; Karl Kappeler; Erin Keels, RN; Jeff Lewis; Emily Mackall; Jamie Manley, RN; Gina Marcum, RN; Richard McClead, MD; Karen McCoy, MD; Jenna Merandi, PharmD; Martha Meyers; Leslie Mihalov, MD; Michelle Miller, MD; Kathy Moellman, RN; Shelly Morvay, PharmD; Randy Olshefski, MD; Winifred Payne; Karen Principe, RN; Sandhya Ramachandran; Octavio Ramilo, MD; Anamarie Rayburn; David Repaske, MD; Stacie Rhoades, RN; David Ries, MD; Steve Roach, MD; Laura Rust, MD; Matthew Sapko, PharmD; Steven Teich, MD; Ed Shepherd, MD; Jodi Smathers, RN; Randy Smith, RN; Janet Simsic; Barb Stewart, RN; Linda Stoverock, DPN; Thomas Taghon, MD; Olivia Thomas; Jill Tice, RN; Maria Vegh, RN; Pat Wall, MD; Jonathan Wispe, MD; Renee Wolfe, RN; Chad Zerangue, RN; Brian Kenney, MD; Nadeem Khan, MD; Duane Kusler, VP; Anthony Lee; Dorcas Lewe, RN; and Richard Lisciandro, RN.
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edication errors are common and significant causes of preventable harm, particularly for hospitalized children, in whom medication errors are 3 times more common than in adults.1 Children are more prone to medication errors and resulting harm for several reasons. First, pediatric weight-based dosing requires use of nonstandard medication preparations that are subject to miscalculations in prescribing, dispensing, and administration processes. Second, immature metabolic systems are less tolerant of medication errors. Finally, children may be unable to communicate regarding the symptoms of an adverse drug event (ADE).2 Estimates of the frequency of harmful medication errors or ADEs range from 13.4 to 49.8 per 1000 patient-days.3,4 In the fall of 2008, Nationwide Children’s Hospital (NCH) set a goal of eliminating preventable patient harm. A key metric in monitoring the success of the safety program was the Preventable Harm Index.5 At that time, medication errors accounted for nearly two-thirds of preventable patient harm, with more than 50% of those errors related to medication administration and smaller percentages related to prescribing and dispensing processes. The most common administration errors involved failure to perform the “5 rights of medication administration.”6 One-half of the preventable medication errors occurred in the critical care units; thus, the initial ADE reduction effort focused on medication administration errors in the critical care units. Eventually the other medication management processes were addressed, and the improvement effort spread throughout the hospital system.
Methods Medications errors are mistakes in the prescribing, dispensing, administration, or monitoring of medications. ADEs, as defined here, are preventable medication errors that reach the patient and cause some deADE ADEQC BCMA CPOE EMR IV NCCMERP NCH QI
Adverse drug event Adverse Drug Event Quality Collaborative Bar-coded medication administration Computerized practitioner order entry Electronic medical record Intravenous National Coordinating Council for Medication Error Reporting and Prevention Nationwide Children’s Hospital Quality improvement
From the 1Nationwide Children’s Hospital; and Department of Pediatrics, 2Division of Neonatology; 3 Division of Critical Care Medicine, The Ohio State University, Columbus, OH *A list of members of the Adverse Drug Event Quality Collaborative is available in the Appendix (available at www.jpeds.com). Funded by Cardinal Health Foundation (PI: R.M.). The authors declare no conflicts of interest. 0022-3476/$ - see front matter. Copyright ª 2014 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2014.08.063
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Vol. 165, No. 6 December 2014 gree of harm. Potential ADEs are medication errors in which prevention strategies (eg, pharmacist interventions with prescribers) prevent the error from reaching the patient. This quality improvement (QI) effort involved implementation of evidence-based interventions or best practices designed to meet an established goal of zero patient harm from ADEs. No interventions involved a comparison of devices or therapies, and patients were not subjected to randomization. Medical records were accessed by QI team members as part of their normal responsibilities. No personal health information was shared. Therefore, the need for Institutional Review Board approval was waived (personal communication, Alex Rawkowsky, MD, Chairman, NCH Institutional Review Board). NCH is an academic, nonprofit, 450-bed freestanding children’s hospital located in Columbus, Ohio. Annually, the hospital provides care to more than 1 million outpatients, performs 26 000 surgeries, and has 25 000 inpatient discharges. The NCH pharmacy dispenses more than 1.5 million medication doses per year. The current electronic medical record (EMR) and computerized practitioner order entry (CPOE) systems (Epic Systems, Verona, Wisconsin) are fully integrated with clinical decision making support. ADE and medication error detection methodology includes a voluntary electronic event reporting system, monthly 20-chart trigger tool analysis,7,8 100% review of all dispensed reversal agents (eg, naloxone), and pharmacist interventions with prescribing practitioners. The severity of ADEs is measured using a variation of the National Coordi-
nating Council for Medication Error Reporting and Prevention (NCCMERP) Scale.9 (A detailed description of the NCCMERP Scale is available at http://www.nccmerp.org/ pdf/indexColor2001-06-12.pdf.) We classified ADEs with a NCCMERP severity level of D-I as harmful. Relatively minor level D medication errors were more frequent and involved the same failure modes as more serious ADEs, and thus were included to ensure a sufficient number of ADEs to allow identification of opportunities for improvement. The primary outcome metric was the rate of ADEs per 1000 dispensed doses over time. The numerator was the number of ADEs identified by the detection strategies, and the denominator was total medications dispensed. Secondary metrics included total detected ADEs regardless of severity per 1000 dispensed doses and total nonharmful potential ADEs (severity level A-C) per 1000 dispensed doses. Statistical process control charts10 were used to show outcome metric progress and assess the impact of interventions over time. Collaborative Model and Improvement Methodology In July 2009 (phase 1), an internal QI collaborative comprising multidisciplinary representatives from all critical care units and 2 additional units that were experiencing frequent ADEs was convened. This ADE Quality Collaborative (ADEQC) mirrored the Institute for Healthcare Improvement Breakthrough Series11 and used the Model for Improvement.12 Figure 1 illustrates the initial specific aim and key driver diagram developed by the ADEQC. The
Figure 1. Specific aim and key driver diagram for the ADEQC. The baseline was not officially determined until February 2010, when reporting of ADEs peaked as the full impact of the safety program was felt. The key drivers are barriers that must be overcome to impact the specific aim. Typically, key drivers are expressed as elements that must be addressed to achieve the specific aim; however, the key driver diagram as presented here is what we used to drive change. CTICU, cardiothoracic intensive care unit; PDSA, plan-do-study-act. 1223
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peak ADE baseline rate of 0.24 per 1000 dispensed doses was not established until February 2010, when reporting of ADEs was at its peak. The interim goal of 0.08 ADE per 1000 dispensed doses by December 2011 was chosen empirically. The key drivers were those processes related to the medication use phase and collaborative communication. The ADEQC met monthly, reviewed unit-specific data, discussed recent ADEs, and developed interventions. Successful intervention strategies were disseminated to other units within the collaborative. After multiple successful interventions, the ADEQC was expanded in the spring of 2011 (phase 2) to include the remaining inpatient units, emergency department, outpatient clinics, and urgent care centers. Interventions Before the ADEQC, all of the prevention strategies described by Miller et al13 and the Joint Commission2 had been implemented except for an automated ADE detection system and bar-coded medication administration (BCMA). ADEQC interventions included CPOE, automated dispensing cabinets, clinical pharmacist rounding in the intensive care units, unit dose drug dispensing, weight-based dosing, and a pediatric drug formulary. Additional interventions intended to impact the key drivers of ADEs and medication errors are outlined in Figure 1. Key interventions aimed at administration errors included: (1) revision of the hospital’s independent double-check process for high-risk medications, to clarify performance expectations (as originally written, the policy was subject to varying interpretations by front-line nurses); (2) implementation of a wireless communication system (Vocera, San Jose, California) to allow nurses to identify readily available colleagues to assist with the independent double-check process; (3) addition of smart syringe and large-volume infusion pumps with drug libraries (Alaris System; Carefusion, San Diego, California), to alert the nursing staff to possible pump programming and/ or dosing errors; (4) rigorous unit-based audits of the 5 rights of medication administration; and (5) implementation of a BCMA system in April 2011. For the unit-based audits, each month a medication safety nurse observed 10 medication administration events on each inpatient unit. Each staff nurse was asked to describe the steps in the medication administration process as she or he performed it, and the medication safety nurse then completed a detailed checklist of the correctly performed steps and reported unit performance to the ADEQC and unit leadership. Prescribing error prevention interventions included review of the medication reconciliation process and modifications to the electronic medication reconciliation template. Inaccurate weight was addressed by creating an “aberrant weight alert” in the EMR if the recorded weight was 10% higher or lower than the expected weight based on established growth curves. In addition, the alert required documentation of the method for obtaining the admission weight (ie, scale, parent report, or estimate). 1224
Vol. 165, No. 6 Dispensing errors were related primarily to delivery of stat drugs to the patient care units. This problem area was addressed by reconfiguring the process for urgent drug preparation and redesigning the process for storing pneumatic tubes, to increase the number available in the pharmacy for urgent delivery purposes. Two interventions were particularly effective: development and auditing of an ADE “prevention bundle” and a post–medication error apparent cause “huddle” process. ADE Prevention Bundle An ADE bundle was developed that included those practices which if done correctly and completely would minimize the risk of medication errors. The initial bundle elements included documented review of home medications, application of the 5 rights of medication administration with independent double-checks, use of smart pump libraries, accurate weight documentation, and BCMA when available. Random monthly chart audits reviewing documentation for each ADE bundle element were conducted by unit-based nursing “medication safety champions” and reported to the ADEQC. In February 2012, additional ADE bundle elements were added, including management of appropriate intravenous (IV) tubing setups and compliance with proper administration of secondary IV infusions. ADE Huddles The huddle process14 examined harmful ADEs to learn from frontline staff why the event occurred and what might be done to prevent similar future events. Following an ADE, be it related to prescribing, dispensing, administering, or monitoring, an ADEQC team met with unit nursing leadership and the involved medical and hospital staff members. The ADE was reviewed using a standardized set of questions intended to identify improvement opportunities.15 Example questions included “What happened?,” “Was an accurate handoff performed?,” and “Was the patient care assignment typical?” The equipment involved in the ADE (eg, infusion pumps) and the patient’s actual EMR were reviewed to simulate the error with the staff member and to identify any contributing factors. Potential interventions to mitigate future ADEs identified during the huddle process were entered into a Web-based platform. Accountability for completion of each intervention was assigned by the huddle team. Completion of recommended interventions was monitored by QI analysts.16 The results of unit-based intervention trials were presented at the monthly ADEQC meetings and, when appropriate, disseminated throughout the hospital. Additional details of the ADE huddle process are provided elsewhere.15 Safety Culture Activities Beginning in 2008-2009 and coinciding with the work of the ADEQC, NCH embarked on a journey toward high reliability practices and just culture accountability (known as Zero Hero). A goal of eliminating preventable harm was established. The details of the Zero Hero program are described McClead Jr. et al
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December 2014 elsewhere.17,18 Following implementation of this safety culture program, reporting of nonharmful medication errors (NCCMERP severity level A-C) increased by 65.4%, with the increase sustained through Q3 2013. This new reporting culture greatly facilitated the effort to identify and eliminate harmful ADEs.
Results Reduction in Medication Errors Causing Harmful ADEs Figure 2 depicts ADEs per 1000 dispensed doses, annotated with various improvement interventions. The initial ADE rate increase coincided with increased error reporting and detection. ADEs peaked in 2010. By March 2011, the ADE rate had decreased by 52%, from a mean of 0.17 to 0.08 per 1000 doses dispensed (P < .001). By December 2012, the rate had further declined to 0.04 per 1000 doses dispensed, a 76.5% decrease from peak value (P < .001). This occurred even as the units reporting ADEs to the collaborative expanded to include all inpatient units, perioperative and emergency services, and outpatient clinics (ADEQC phase 2). During the collaborative time period, a total of 7511 medication events were reported, of which 462 were category D events (6.2%) and 273 were category E events (3.97%). However, only 28 ADEs (0.4%) caused serious harm (category F or higher). No ADE-related deaths occurred while the ADEQC was active. During 2012, the medications most often associated with harmful ADEs were vaccines (29%), analgesics and narcotics (16%), insulin (9%), IV fluids (9%), and parenteral nutrition (6%). Figure 3 shows the total number of nonharmful medication errors (NCCMERP severity level A-C) and
ADEs (severity level D-I) by quarter. There was a progressive increase in reported nonharmful medication errors reporting per quarter, but a decrease in reported ADEs (by definition harmful). Figure 4 shows the proportional changes in the distribution of error types between 2010 and 2012. In 2010, administration errors accounted for 55% of all ADEs, and prescribing errors for 32%. As the number of ADEs decreased through 2012, the proportions were reversed, with administration errors decreasing to 38% of the total and prescribing errors increasing to 52% of a smaller number of total harmful ADEs. The proportional change in administration and prescribing errors in 2010 compared with 2012 was statistically significant (P < .001). The changes in the other categories (dispensing, monitoring, and other) were small and statistically unchanged. Residents and attending physicians account equally for 90% of prescribing errors, with advanced practice nurses accounting for the remaining 10%. ADE Bundle Audits Overall compliance with initial ADE bundle elements improved over time, peaking at 98% in October 2010 (Figure 5). Subsequent audit compliance remained above 94% through October 2011. After revision of the ADE bundle in February 2012, compliance fell below 90% until October 2012. Since March 2013, overall ADE bundle compliance has ranged from 93% to 96%. Compliance with individual bundle elements was as follows: 5 rights and double-checks, 99%-100%; syringe and infusion pump medication library audits, 100%; accurate admission weights, 91%-95%; EMR documentation of medication reconciliation review, 84%-91%; bar code scanning of
Figure 2. Monthly rate of harmful ADEs per 1000 dispensed doses. *P < .001. PIC, pediatric intensive care unit; RMH MAR, Riverside Methodist Hospital medication administration record; Amb MAR, Ambulatory medication administration record. An Internal Quality Improvement Collaborative Significantly Reduces Hospital-Wide Medication Error Related Adverse Drug Events
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Figure 3. Harmful ADEs (NCCMERP severity level D-I) and nonharmful ADEs (NCCMERP severity level A-C) by quarter. The number of harmful ADEs per quarter decreased by 74.1%.
patients, >97%; bar code scanning of medications, >93%. Compliance with management of appropriate IV tubing setups and with proper administration of secondary IV infusions was 98% and 95%, respectively.
roughly 92% have been implemented.16 Huddles also have led to the formation of task forces to address complex issues, such as the inpatient management of home insulin infusion pumps, EMR alert fatigue, and therapeutic drug monitoring.
ADE Huddles Between March 2010 and June 2013, more than 900 huddles were conducted. The apparent causes of ADEs identified during the huddle process are described elsewhere.15 Some key themes emerged, including failure of the 5 rights of medication administration, inaccurate medication reconciliation, and improper independent double-check of high-risk medications. Of the more than 3000 huddle recommendations,
Discussion The 76.5% reduction in the rate of harmful ADEs during the study period occurred despite the expansion of the ADEQC to include the entire inpatient and outpatient hospital system. We believe that the key factors contributing to the collaborative’s success were the internal quality collaborative model, focus on medication management failure modes,
Figure 4. Distribution of error types, 2010 vs 2012, and total number of ADEs of severity level D-I. *P < .001. Note the prevalence of administration errors in 2010 that changed to predominantly prescribing errors in 2012.
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Figure 5. Compliance with use of the ADE bundle was excellent a few months after initiation in May 2010. However, performance degraded in February 2012 following a revision of the bundle and the opening of a new 12-story patient tower in August 2012. Compliance subsequently improved and has remained at or near the goal (94%) since April 2013.
reliable use of an ADE prevention bundle, ADE huddles, and the evolution of a safety culture that led to increased medication error reporting. The quality collaborative model can “accelerate the translation of evidence into practice and improve care and outcomes for children.”19 We adapted this approach to a single hospital system that included a diverse group of inpatient and outpatient units. A unique aspect of this work was the strategy to focus initially on the processes of medication management (ie, administration, prescribing, dispensing, monitoring) and to apply this to all classes of medications. This approach is different from that reported by others. Most previous studies focused on specific medications or groups of medications and often involved only a few patient care units over a relatively short time period.20-24 Others focused on ADE rate determination,1,3,4,25-27 epidemiologic characteristics of medication errors,13,28-30 or single ADE prevention strategies.31,32 A few studies involved multicenter collaborative networks that implemented a variety of prevention strategies, but the major outcome was reduction of ADEs for a single class of medications, such as opioids.33,34 Our work encompasses most of the foregoing strategies applied across all medication groups. By achieving high compliance with the prevention bundle strategies, we showed robust improvement for the entire organization. A factor that we believe contributed to the significant increase in voluntarily ADE reporting was the enhanced safety culture, reflected by a statistically significant improvement in NCH safety survey data from 2009 to 2011.16,18 Others have reported the association between an improved safety culture
and prevention of patient harm, including ADEs.35,36 Although the majority of our identified failures were system failures, individual failures were identified as well. Managers used an accountability tool adapted from Reason’s Decision Tree for Determining Culpability for Unsafe Acts to develop an intervention action plan designed to improve performance for those individuals.37 A residual challenge has been prescribing errors. As a result of the success achieved in decreasing administration errors, prescribing errors now predominate. The current emphasis is on reducing prescribing errors in 5 persistently problematic areas: medication reconciliation, insulin therapy, therapeutic drug monitoring, neonatal total parenteral nutrition orders, and EMR alert fatigue (ie, frequent electronic alerts resulting in recurrent overrides). Others have focused on reducing prescribing errors. An Australian group38 reported a 4-year study at an urban children’s hospital using interventions targeting prescribing errors. Intensive care units were excluded. Their program achieved a >50% reduction in total ADEs over the study period (P < .05). These results are comparable with ours in the present study, which focused on all medication management failure modes for an entire hospital system and achieved a 76.5% ADE reduction from peak (Figure 2; P < .001). The present study has several limitations. First, it was conducted at a single freestanding children’s hospital system. Although not all hospitals have access to advanced medication safety technology (ie, smart pumps, BCMA, and CPOE), we believe that the resources needed to implement
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an effective ADE prevention bundle, as described here, are readily available. Second, much of the ADE reporting resulted from voluntary event reports. All ADE detection methods have strengths and weaknesses.39,40 As noted by Takata et al,3 there is no gold standard for identifying ADEs. They referred to the robustness of the monthly 20-chart trigger tool methodology; however, our data suggest that a voluntary reporting system within a culture of safety can be equally valuable. We believe that combining a robust voluntary reporting system with an effective pharmacy reporting trigger tool system may provide the best ADE detection approach. With the exception of opioid-induced constipation resulting from omission of laxatives during therapy, we did not find any harmful ADEs using the trigger tool methodology that had not been previously identified by the voluntary event reporting system. Although underreporting of harmful ADEs is possible, the overall sustained increase in ADE reporting that followed implementation of the safety culture program supports our belief that underreporting is minimal. We believe that nonharmful ADEs, especially those from pharmacist intervention of practitioner orders, are underreported, however. A 1-month audit of pharmacist phone calls to practitioners identified approximately 50 interventions per day. Many of these interventions resulted in changes to the medication orders and the prevention of potentially harmful ADEs. Few of these interventions were reported because of pharmacist and practitioner time constraints. Overall, we agree with Miller et al that “an ideal error identification system may involve multiple data sources.”13 That idea is the basis of our medication error reporting and identification system. We believe that the success of this system derives from the use of QI collaborative methodologies, an evolving high-reliability and safety-focused culture, and reliable implementation of an ADE prevention bundle of care practices. n We acknowledge T. Arthur Wheeler MS, MSES, MBA, for assistance with statistical analysis of the data presented in this study, as well as the support of Michael Fetzer, BSISE, Emily Mackal, RHIA, MBA, Jeffrey Hoffman, MD, Laura Rust, MD, Stacy Kuehn, RN, and James Gallup, MBA, for their assistance with ADEQC leadership and data analysis and preparation. Submitted for publication Dec 22, 2013; last revision received Jul 14, 2014; accepted Aug 27, 2014. Reprint requests: Richard E. McClead, Jr., MD, MHA, Department of Pediatrics, Nationwide Children’s Hospital, Room ED 333, 700 Children’s Dr, Columbus, OH 43205. E-mail: [email protected]
References 1. Kaushal R, Bates DW, Landrigan C, McKenna KJ, Clapp MD, Federico F, et al. Medication errors and adverse drug events in pediatric inpatients. JAMA 2001;285:2114-20. 2. Joint Commission. Preventing pediatric medication errors. Sentinel Event Alert 2008;39:1-5. 3. Takata GS, Mason W, Taketomo C, Logsdon T, Sharek PJ. Development, testing, and findings of a pediatric-focused trigger tool to identify medication-related harm in US children’s hospitals. Pediatrics 2008; 121:e927-35. 1228
Vol. 165, No. 6 4. Kirkendall ES, Kloppenborg E, Papp J, White D, Frese C, Hacker D, et al. Measuring adverse events and levels of harm in pediatric inpatients with the Global Trigger Tool. Pediatrics 2012;130:e1206-14. 5. Brilli RJ, McClead RE Jr, Davis T, Stoverock L, Rayburn A, Berry JC. The Preventable Harm Index: an effective motivator to facilitate the drive to zero. J Pediatr 2010;157:681-3. 6. Hughes R. Patient safety and quality: An evidence based handbook for nurses. Publication 08-0043. Rockville (MD): Agency for Healthcare Research and Quality; 2008. 7. Rozich JD, Haraden CR, Resar RK. Adverse drug event trigger tool: a practical methodology for measuring medication-related harm. Qual Saf Health Care 2003;2:194-200. 8. Children’s Hospital Association. [homepage on the Internet, CHCA Link] Shawnee Mission, KS: c 2009. PICU Trigger instruction manual: measuring adverse events in the PICU using a PICU trigger tool. [19 screens] Available from: http://www.chca.com/triggers/docs/PICU_ triggertoolkit_for%20CHCAwebsite.pdf. Accessed October 2, 2014. 9. Hartwig SC, Denger SD, Schneider PJ. Severity-indexed, incident reportbased medication error-reporting program. Am J Hosp Pharm 1991;48: 2611-6. 10. Provost LP, Murray S. The health care data guide: Learning from data for improvement. San Francisco (CA): Jossey-Bass; 2011. 11. Kilo CM. A framework for collaborative improvement: lessons from the Institute for Healthcare Improvement’s Breakthrough Series. Qual Manag Health Care 1998;6:1-14. 12. Langley GJ, Moen R, Nolan KM, Nolan TW, Norman CL, Provost LP. The Improvement Guide: A practical approach to enhancing organizational performance. San Francisco (CA): Jossey-Bass; 2009. 13. Miller MR, Robinson KA, Lubomski LH, Rinke ML, Pronovost PJ. Medication errors in paediatric care: a systematic review of epidemiology and an evaluation of evidence supporting reduction strategy recommendations. Qual Saf Health Care 2007;16:116-26. 14. Wilbur K, Scarborough K. Medication safety huddles: teaming up to improve patient safety. Can J Hosp Pharm 2005;58:151-5. 15. Morvay S, Stewart B, Catt C, McClead RE, Brilli R. How to conduct medication event huddles: a tool for reducing adverse drug events. Jt Comm J Qual Patient Saf 2013;40:39-45. 16. Merandi J, Morvay F, Lewe D, Stewart B, Catt C, Chanthasene P, et al. Improvement of medication event interventions through use of an electronic database. Am J Health Syst Pharm 2013;70:1708-14. 17. Crandall WV, Davis JT, McClead R, Brilli RJ. Is preventable harm the right patient safety metric? Pediatr Clin North Am 2012;59: 1279-92. 18. Brilli RJ, McLead RE Jr, Crandall WV, Stoverock L, Berry JC, Wheeler TA, et al. A comprehensive patient safety program can reduce significantly preventable harm, associated costs, and hospital mortality. J Pediatr 2013;163:1638-45. 19. Lannon CM, Miles PV. Pediatric collaborative improvement networks: bridging quality gaps to improve health outcomes. Pediatrics 2013; 131:S187-8. 20. Leonard MS, Cimino M, Shaha S, McDougal S, Pilliod J, Brodsky L. Risk reduction for adverse drug events through sequential implementation of patient safety initiatives in a children’s hospital. Pediatrics 2006;118: e1124-9. 21. Porter SC, Kaushal R, Forbes PW, Goldmann D, Kalish LA. Impact of a patient-centered technology on medication errors during pediatric emergency care. Ambul Pediatr 2008;8:329-35. 22. Burmester MK, Dionne R, Thiagarajan RR, Laussen PC. Interventions to reduce medication prescribing errors in a paediatric cardiac intensive care unit. Intensive Care Med 2008;34:1083-90. 23. Holdsworth MT, Fichtl RE, Raisch DW, Hewryk A, Behta M, MendezRico E, et al. Impact of computerized prescriber order entry on the incidence of adverse drug events in pediatric inpatients. Pediatrics 2007;120: 1058-66. 24. Wang JK, Herzog NS, Kaushal R, Park C, Mochizuki C, Weingarten SR. Prevention of pediatric medication errors by hospital pharmacists and the potential benefit of computerized physician order entry. Pediatrics 2007;119:e77-85.
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December 2014 25. Kaushal R, Goldmann DA, Keohane CA, Christino M, Honour M, Hale AS, et al. Adverse drug events in pediatric outpatients. Ambul Pediatr 2007;7:383-9. 26. Kaushal R, Bates DW, Abramson EL, Soukup JR, Goldmann DA. Unitbased clinical pharmacists’ prevention of serious medication errors in pediatric inpatients. Am J Health Syst Pharm 2008;65:1254-60. 27. Agarwal S, Classen D, Larsen G, Tofil NM, Hayes LW, Sullivan JE, et al. Prevalence of adverse events in pediatric intensive care units in the United States. Pediatr Crit Care Med 2010;11:568-78. 28. Latif A, Rawat N, Pustavoitau A, Pronovost PJ, Pham JC. National study on the distribution, causes, and consequences of voluntarily reported medication errors between the ICU and non-ICU settings. Crit Care Med 2013;41:389-98. 29. Bourgeois FT, Mandl KD, Valim C, Shannon MW. Pediatric adverse drug events in the outpatient setting: an 11-year national analysis. Pediatrics 2009;124:e744-50. 30. van Rosse F, Maat B, Rademaker CM, van Vught AJ, Egberts AC, Bollen CW. The effect of computerized physician order entry on medication prescription errors and clinical outcome in pediatric and intensive care: a systematic review. Pediatrics 2009;123:1184-90. 31. Fortescue EB, Kaushal R, Landrigan CP, McKenna KJ, Clapp MD, Federico F, et al. Prioritizing strategies for preventing medication errors and adverse drug events in pediatric inpatients. Pediatrics 2003;111: 722-9.
ORIGINAL ARTICLES 32. Ferranti J, Horvath MM, Cozart H, Whitehurst J, Eckstrand J. Reevaluating the safety profile of pediatrics: a comparison of computerized adverse drug event surveillance and voluntary reporting in the pediatric environment. Pediatrics 2008;121:e1201-7. 33. Sharek PJ, McClead RE, Taketomo C, Luria JW, Takata GS, Walti B, et al. An intervention to decrease narcotic-related adverse drug events in children’s hospitals. Pediatrics 2008;122:e861-6. 34. Tham E, Calmes HM, Poppy A, Eliades AB, Schlafly SM, Namtu KC, et al. Sustaining and spreading the reduction of adverse drug events in a multicenter collaborative. Pediatrics 2011;128:e438-45. 35. Neuspiel DR, Stubbs EH, Liggin L. Improving reporting of outpatient pediatric medical errors. Pediatrics 2011;128:e1608-13. 36. Smetzer J, Navarra M. Measuring change: a key component of building a culture of safety. Nurs Econ 2007;25:49. 37. Reason JT. Managing the risks of organizational accidents. Burlington (VT): Ashgate Publishing; 1997. 38. Gazarian M, Graudins LV. Long-term reduction in adverse drug events: an evidence-based improvement model. Pediatrics 2012;129:e1334-42. 39. Meyer-Massetti C, Cheng CM, Schwappach DL, Paulsen L, Ide B, Meier CR, et al. Systematic review of medication safety assessment methods. Am J Health Syst Pharm 2011;68:227-40. 40. Flynn EA, Barker KN, Pepper GA, Bates DW, Mikeal RL. Comparison of methods for detecting medication errors in 36 hospitals and skillednursing facilities. Am J Health Syst Pharm 2002;59:436-46.
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Appendix Members of the ADEQC (NCH, Columbus, Ohio) include: Craig Anderson, MD; Carl Backes, Sr., MD; Vicky Armstrong, RN; Jane Balint, MD; Daniel Barr; Thomas Bartman, MD; Amy Biddle, RN; Mindy Bibart, RN; Angela Blankenship; Richard Brilli, MD; Janice Cannon, RN; Lisa Carney, RN; Steve Cassidy, MD; Charline Catt, RN; Tamara Clark, APN; Kimberly Conkol, RN; William Cotton, MD; Wallace Crandall, MD; Pam Creech, RN; Mike Cummings; James Dail; Kim Davis; Carlo Dilorenzo, MD; Richard Fernandez, MD; Michael Fetzer; Randy Frost; James Gallup; Renee Gardikes, RN; Justin Golias; Cindy Hafer; Melissa Hamms, RN; Judy Hanlon, RN; Sheilah Harrison; Hannah Hays, MD; Wendy Heiligmann, RN; Debbie Hockett RN; Jeffrey Hoffman, MD; Timothy Hoffman, MD; Scott Holliday, MD; Rhonda Humphrey, RN; Karla Johnson, RN; Heath Jolliff, DO; Karl Kappeler; Erin Keels, RN; Jeff Lewis; Emily Mackall; Jamie Manley, RN; Gina Marcum, RN; Richard McClead, MD; Karen McCoy, MD; Jenna Merandi, PharmD; Martha Meyers; Leslie Mihalov, MD; Michelle Miller, MD; Kathy Moellman, RN; Shelly Morvay, PharmD; Randy Olshefski, MD; Winifred Payne; Karen Principe, RN; Sandhya Ramachandran; Octavio Ramilo, MD; Anamarie Rayburn; David Repaske, MD; Stacie Rhoades, RN; David Ries, MD; Steve Roach, MD; Laura Rust, MD; Matthew Sapko, PharmD; Steven Teich, MD; Ed Shepherd, MD; Jodi Smathers, RN; Randy Smith, RN; Janet Simsic; Barb Stewart, RN; Linda Stoverock, DPN; Thomas Taghon, MD; Olivia Thomas; Jill Tice, RN; Maria Vegh, RN; Pat Wall, MD; Jonathan Wispe, MD; Renee Wolfe, RN; Chad Zerangue, RN; Brian Kenney, MD; Nadeem Khan, MD; Duane Kusler, VP; Anthony Lee; Dorcas Lewe, RN; and Richard Lisciandro, RN.
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