Original Article
Further characterization of the influence of crowding on medication errors Hannah Watts, Muhammad Umer Nasim, Rolla Sweis, Rishi Sikka, Erik Kulstad Department of Emergency Medicine, Advocate Christ Medical Center, Oak Lawn, Illinois, USA
ABSTRACT Study Objectives: Our prior analysis suggested that error frequency increases disproportionately with Emergency department (ED) crowding. To further characterize, we measured this association while controlling for the number of charts reviewed and the presence of ambulance diversion status. We hypothesized that errors would occur significantly more frequently as crowding increased, even after controlling for higher patient volumes. Materials and Methods: We performed a prospective, observational study in a large, community hospital ED from May to October of 2009. Our ED has full-time pharmacists who review orders of patients to help identify errors prior to their causing harm. Research volunteers shadowed our ED pharmacists over discrete 4- hour time periods during their reviews of orders on patients in the ED. The total numbers of charts reviewed and errors identified were documented along with details for each error type, severity, and category. We then measured the correlation between error rate (number of errors divided by total number of charts reviewed) and ED occupancy rate while controlling for diversion status during the observational period. We estimated a sample size requirement of at least 45 errors identified to allow detection of an effect size of 0.6 based on our historical data. Results: During 324 hours of surveillance, 1171 charts were reviewed and 87 errors were identified. Median error rate per 4-hour block was 5.8% of charts reviewed (IQR 0-13). No significant change was seen with ED occupancy rate (Spearman’s rho = –.08, P = .49). Median error rate during times on ambulance diversion was almost twice as large (11%, IQR 0-17), but this rate did not reach statistical significance in univariate or multivariate analysis. Conclusions: Error frequency appears to remain relatively constant across the range of crowding in our ED when controlling for patient volume via the quantity of orders reviewed. Error quantity therefore increases with crowding, but not at a rate greater than the expected baseline error rate that occurs in uncrowded conditions. These findings suggest that crowding will increase error quantity in a linear fashion. Key Words: Crowding, errors, pharmacists
INTRODUCTION Background
Among the many challenges that emergency departments (EDs) are facing, crowding appears to be a major influence. ED crowding represents an international crisis that may affect the quality of and access to healthcare.[1] Causes of Address for correspondence: Dr. Muhammad Umer Nasim, E-mail: [email protected] Access this article online Quick Response Code: Website: www.onlinejets.org
DOI: 10.4103/0974-2700.120370
264
crowding have been categorized as; input factors (i.e., nonurgent visits, so-called frequent-flyer patients, the influenza season, etc.); throughput factors (i.e., lower staffing and mandated medical screening for all patients who present to an ED); outflow factors (i.e., inpatient boarding[2] with 22% of all ED patients boarding at one time in some cases); and hospital bed shortages.[1] Regardless of the aggravating factors, crowding appears to result in increased risk of death and disability,[3-7] poor quality of care in patients with severe pain, and medication errors. Medication errors (including dosing protocols or routes that are incorrectly administered[8]) contribute to significant morbidity, mortality, and costs to the health system.[9] One study of a national medication error database found that nearly 11,000 medication errors were reported over a 5-year period by EDs in 484 unique facilities.[10] Despite many reports on the impact of crowding on medication errors[11] few studies of this problem have been published.[12-14] Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Watts, et al.: Crowding and Medication errors
Study objective
Our prior analysis suggested that medication error frequency increases disproportionately with crowding.[15] And another prior study suggested that Emergency Department Work Index (EDWIN) scores may provide some measure to quantify crowding and perhaps discriminate between conditions that may be associated with higher error frequencies. [16] In order to better determine the relation between crowding and medication error occurrence, and control for variables not measured in our earlier study; we measured the association between medication errors and crowding in the ED over discrete time intervals while controlling for the number of charts reviewed and the presence of ambulance diversion status. Hypothesis
We hypothesized that escalation in medication errors is correlated positively with crowding in the ED regardless of controlling for higher patient volumes. MATERIALS AND METHODS Study participants, data source, institutional setting, and patient census. We performed this prospective, observational study in a large, community hospital ED from May to October of 2009. ED full time pharmacists, who worked weekday morning and evening shifts, reviewed orders of patients to help identify errors prior to their causing harm. Our ED has 50 licensed beds with annual patient visits at the time of the study of approximately 85,000. Our ED supports a 3-year emergency medicine residency program with 33 residents in postgraduate year (PGY) 1-3 format, and at the time of the study employed two full-time ED pharmacists working different 8-h shifts, 5 days a week. Intervention
The morning shift pharmacist reviewed and processed medication orders placed from early morning to late afternoon and the evening shift pharmacist reviewed and processed orders from later that afternoon until 11:00 pm. These orders comprised of medications ordered for newly arrived patients, patients in the critical care area of our ED, and boarded patients. There was no pharmacist coverage during overnight hours and weekends. In addition to satisfying responsibilities pertaining to every patient’s medication order, our pharmacists reviewed orders to help identify errors prior to producing harmful results. We organized a group of research volunteers who shadowed our ED pharmacists over a variety of discrete 4-h time periods during their reviews of orders on patients in the ED. We documented total numbers of charts reviewed by pharmacists during their shifts along with the errors identified in those charts. We categorized these errors according to the National Coordinating Council for Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Medication Error Reporting and Prevention (NCC MERP) Index for Categorizing Medication Errors Guidelines: Category A: Circumstances or events that have the capacity to cause error, category B: An error occurred but the error did not reach the patient (An “error of omission” does reach the patient), category C: An error occurred that reached the patient but did not cause patient harm, category D: An error occurred that reached the patient and required monitoring to confirm that it resulted in no harm to the patient and/ or required intervention to preclude harm, category E: An error occurred that may have contributed to or resulted in temporary harm to the patient and required intervention, category F: An error occurred that may have contributed to or resulted in temporary harm to the patient and required initial or prolonged hospitalization, category G: An error occurred that may have contributed to or resulted in permanent patient harm, category H: An error occurred that required intervention necessary to sustain life, category I: An error occurred that may have contributed to or resulted in the patient’s death [Table 1: NCC MERP error categories and Table 2: Error categories]. (Source: http://www.nccmerp.org/medErrorCatIndex.html) We then measured the correlation between error rate (number of errors divided by the total number of charts reviewed) and ED occupancy rate while controlling for diversion status during the 6-month observation period from May 2009 to October 2009. We estimated a sample size requirement of at least 45 errors identified to allow detection of an effect size of 0.6 based on our historical data. RESULTS Pharmacists and research volunteers reviewed a total of 1,171 charts. Total documented error surveillance was comprised of 81 discrete observation periods, each 4 h in duration (324 h total). We identified a total of 87 errors in these 81 observation periods. For each 4-h observation period, average numbers of charts reviewed were 14.4 [Figure 1, Table 3: Percentage of errors per charts reviewed]. Median error rate per 4-h block was 5.8% of charts reviewed (interquartile range (IQR) 0-13) Table 1: National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) error categories NCC MERP Error Categories
Errors Identified
A
5
B
35
C
21
D
20
E
4
F
2
G
0
H
0
I
0
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Watts, et al.: Crowding and Medication errors
Table 2: Error category Med error index
Error category
A
Error details
Med error index
Error category
Error details
Unapproved abreviation 10U written
C
Incorrect drug
Prednisone IV ordered instead of solumedrol
A
Unapproved abreviation U i/o units
C
Incorrect dose
Protonix 60 mg instead of 80 mg
A
Incomplete order
Missing type of insulin
C
Incorrect dose
Magnesium oxide ordered iv, only available po
A
Incorrect dose
Calcium accetate 670, should have been 667
C
Incorrect dose
Rocephin im ordered instead of iv
A
Non-formulary medication
Levofloxacin
C
Incorrect dose
Hctz 10 mg written for, 50 mg correct
B
Incorrect dose
Route missing
C
Incorrect formulation
Macrobid written, wrong dosage form for gtube
B
Allergy
Pcn, zosyn
C
Duplicate order
Prednisone given twice
B
Duplicate order
C
Incorrect frequency
Cipro q 8 i/o q12
B
Incorrect dose
Missing frequency
C
Delay in therapy
Dose due at t6:30 am, not given until 10 am
B
Incorrect dose
Propofol, wrong drip rate
C
Incorrect dose
500 mg of daptomycin ordred, should have been 600 mg
B
Incorrect dose
Td, missing route
C
Delay in therapy
Missed dose of solumedrol
B
Incorrect dose
Fentanyl, wrong drip rate
C
Incorrect dose
Rocephin
B
Incorrect dose
Unasyn, wrong dose
C
Incorrect dose
Total daily dose of tegretol not divided
B
Incorrect dose
Phenytoin, dosing error
C
Incorrect dose
Total daily dose of gapabpentin not divitided
B
Incorrect dose
Etomidate, missing route
C
Incorrect dose
500 mg po dilantin
B
Incorrect dose
Missing dose/directions on rx for peritoneal dialysis
C
Incorrect dose
Iron sulfate 500mg, not 325 mg
B
Incorrect dose
D
Missing order
Zosyn given, not ordered for uti
B
Incorrect dose
No ivf rate
D
Incorrect medication
Metoprolol ordered, metporolol xl given
B
Allergy
Zosyn, pcn allergy
D
Incorrect dose
Metoprolol 12.5 mg ordered, 25 mg administered
B
Incorrect dose
Correct med given, abx
D
Rx not written
Untreated Blood Sugar
B
Allergy
Pcn all, not given
D
Rx not written
Did not replace mag
B
Incorrect drug
Omnicell misfilled
D
Delay in therapy
2 hours late
B
Incorrect dose
Mucomyst writtent oral, not iv
D
Delay in therapy
Pneumonia
B
Incorrect dose
L-carnitine incorrect dose, should be 7000 mg, not 700 mg
D
Incorrect dose
Dilaudid
B
Incorrect dose
L-carnitine, 7 g intended, max is 6 gm
D
Delay in therapy
B
Incorrect dose
Incorrect frequency
D
Delay in therapy
Med not redosed
B
Incorrect dose
Missing route
D
Delay in therapy
Pt did not get keppra, home med
B
Incorrect dose
Wrong units, ml instead of gm
D
Incorrect dose
No renal dosing
B
Incorrect dose
Wrong route
D
Delay in therapy
Delay in therpay for cefepime, orders not written
B
Incorrect dose
Incorrect frequency
D
Incorrect dose
Genatmycin, dose too high
B
Incorrect dose
Wrong frequency
D
Incorrect dose
Amlodipine 10/20 mg ordered
B
Incorrect dose
Wrong units, ml instead of mg
D
Incorrect route
Insulin subq written, should have been IV for hyper kalemia
B
Incomplete order
Medication name ommitted
D
Incorrect dose
Lovenox with renal dysfunction, supratherapeutic dose writtent
B
Incorrect dose
Mucomyst incorrect dose written
D
Duplicate order
Heparin given and lovenox given in close proximity
B
Incorrect dose
Zosyn 3.375 mg instead of gms
D
Incorrect dose
Renal dosing
B
Allergy
Zosyn to pcn allergic pt
D
Incorrect dose
Ancef, flagyl, renal
B
Incorrect dose
Incorrect dose
E
Incorrect dose
Propofol drip, started at 60 mg/kgmin
B
Incorrect patient
Insulin, dextrose
E
Drug not administered
Lasix not given with blood
B
Allergy
Zosyn, pcn allergy
E
Delay in therapy
Pt on dka protocol, no bs checked for 4 hours
B
Incorrect dose
Zosyn
E
Drug not administered
Pt on dka protocol, k not added to fluids
C
Incorrect medication
Prilosec ordered, protonix given
F
Incorrect dose
Insulin drip started at 8 instead of 15 units/h
C
Incorrect dose
Incorrect frequency, zofran
F
Medication not titrated
Nitro not titrated
C
Incorrect medication
Exforge ordered, valsartan given only, no amplodipine
G
No error
No error
C
Incorrect medication
Rocephin instead of zosyn ordered
H
No error
No error
C
Incorrect dose
Toradol 60 mg iv written
I
No error
No error
Rx: Treatment
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Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Watts, et al.: Crowding and Medication errors
Table 3: Percentage of errors per charts reviewed Date
No. of errors found
No. of charts reviewed
Percentage errors
Date
No. of errors found
No. of charts reviewed
Percentage errors
5/12/2009
5
23
0.22
8/20/2009
0
6
0.00
5/12/2009
5
21
0.24
8/24/2009
1
12
0.08
5/20/2009
8
18
0.44
8/26/2009
0
10
0.00
5/22/2009
0
24
0.00
8/26/2009
1
8
0.13
5/26/2009
2
13
0.15
8/26/2009
0
17
0.00
5/27/2009
1
7
0.14
8/28/2009
0
13
0.00
5/29/2009
0
11
0.00
8/28/2009
0
16
0.00
6/1/2009
1
16
0.06
9/2/2009
0
17
0.00
6/2/2009
0
7
0.00
9/2/2009
2
10
0.20
6/2/2009
0
11
0.00
9/2/2009
1
16
0.06
6/8/2009
3
14
0.21
9/3/2009
0
15
0.00
6/9/2009
2
17
0.12
9/3/2009
0
10
0.00
6/11/2009
2
8
0.25
9/4/2009
0
12
0.00
6/12/2009
1
14
0.07
9/8/2009
0
15
0.00
6/15/2009
3
19
0.16
9/8/2009
1
14
0.07
6/16/2009
3
18
0.17
9/9/2009
1
13
0.08
6/19/2009
0
12
0.00
9/9/2009
0
14
0.00
6/23/2009
1
23
0.04
9/9/2009
0
18
0.00
6/30/2009
2
20
0.10
9/11/2009
1
15
0.07
7/1/2009
1
18
0.06
9/14/2009
2
15
0.13
7/7/2009
0
14
0.00
9/14/2009
0
12
0.00
7/8/2009
0
21
0.00
9/15/2009
0
9
0.00
7/10/2009
3
15
0.20
9/16/2009
1
15
0.07
7/14/2009
0
10
0.00
9/16/2009
0
18
0.00
7/15/2009
1
22
0.05
9/18/2009
0
13
0.00
7/21/2009
2
21
0.10
9/23/2009
1
10
0.10
7/22/2009
0
17
0.00
9/30/2009
0
18
0.00
7/24/2009
1
18
0.06
10/2/2009
0
11
0.00
7/27/2009
0
15
0.00
10/5/2009
0
5
0.00
7/29/2009
1
17
0.06
10/5/2009
0
12
0.00
7/31/2009
2
8
0.25
10/6/2009
3
12
0.25
8/12/2009
0
14
0.00
10/6/2009
2
15
0.13
8/12/2009
1
14
0.07
10/7/2009
0
13
0.00
8/13/2009
2
13
0.15
10/7/2009
0
6
0.00
8/14/2009
1
14
0.07
10/7/2009
1
15
0.07
8/17/2009
1
16
0.06
10/8/2009
1
7
0.14
8/18/2009
0
12
0.00
10/8/2009
0
20
0.00
8/18/2009
0
15
0.00
10/9/2009
0
9
0.00
8/19/2009
2
11
0.18
10/16/2009
3
20
0.15
8/19/2009
1
6
0.17
10/21/2009
1
13
0.08
8/19/2009
2
18
0.11
10/21/2009
3
17
0.18
8/20/2009
1
10
0.10
Total errors
87
1171
[Figure 2]. Errors occurred throughout the spectrum of care. Errors included; (a) incorrect dosage, (b) incorrect administration routes (e.g., intravenous (IV) medications ordered for intramuscular (IM)), (c) medication duplications, and (d) delays in therapy. No significant change was seen with the ED occupancy rate (Spearman’s rho (r) = – 0.08, P = 0.49) [Figure 3], whereas previously error frequency showed a positive correlation with daily average EDWIN score (Spearman’s ρ = 0.33; P = 0.001).[15] The Median error rate during times on ambulance diversion was almost twice as large (11%, IQR 0-17) [Figure 4], but this rate did not reach statistical significance in univariate or multivariate analysis. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Limitations
Since we collected data from only one ED, our results may not be generalizable to all EDs. Our pharmacists are experienced and have specific skills and knowledge to perform their function in a busy ED environment. Changes in daily census may impact findings, with an increased inflow of patients possibly resulting in a higher number of medication and therapy orders, which may hinder pharmacists’ availability to review charts for errors and accurately document the results. Our ED has employed pharmacists for two full-time shifts, morning (7:00 am-3:00 pm) and evening (3:00 pm11:00 pm), but the ED at the time of this study was devoid of pharmacists’ coverage from 11:00 pm to 7:00 am. This lack 267
Watts, et al.: Crowding and Medication errors
Figure 1: Histogram showing the occurrence of errors during each observation period. Most observations periods yielded no errors, whereas the largest number found in one observation period was eight
Figure 3: Showing no significant change was seen with the emergency department (ED) occupancy rate (Spearman’s rho = −0.08, P = 0.49)
of coverage limits extrapolation of our data beyond hours when pharmacists were present. DISCUSSION Previously we determined a positive correlation between medication error frequency and ED occupancy as we used the EDWIN score as a point of reference for ED occupancy and medication error frequency measurement. We grouped EDWIN score into low, medium, and high crowding days; and determined that the error frequency was significantly increased in the high crowding group.[15] To further characterize this crowding influence on medication error, we reviewed patients’ charts for medication orders. After reviewing 1,171 charts and 324 h of error surveillance; we found that there was not a disproportionate increase in medication errors as ED occupancy increased [Figure 3], rather there is a linear 268
Figure 2: Showing median error rate per 4-h block was 5.8% of charts reviewed (IQR: 0-13)
Figure 4: Showing median error rate during times on ambulance diversion was almost twice as large (11%, IQR: 0-17)
association between crowding and medication error. This may be due to at least two factors: First, our department may be getting better at reducing the number of errors made when crowding conditions increase, which in turn would result in a reduction in the number of errors available to be identified by the pharmacists. Second, increases in errors seen with increased crowding may be occurring in a nonlinear fashion that is not detected by our sample size. Nevertheless, the fact that errors demonstrably increase as crowding increases raises significant concerns, and suggests that greater vigilance is warranted as crowding conditions occur. The differences in the findings of the current study from our previous work are likely a result of the more granular measurement process employed, combined with the fact that in this study, we controlled for error number by factoring in the number of charts analyzed; whereas in earlier work, we did not. Performance improvement at our institution may additionally be a factor; however temporal changes in these processes are more difficult to quantify. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Watts, et al.: Crowding and Medication errors
In 2007, there were about 117 million ED visits in the United States, about one-fifth of ED visits by children younger than 15 years of age were to pediatric EDs, there were 121 ED visits for asthma per 10,000 children under 5 years of age.[17] From 1997 and 2007, total annual visits to US EDs increased from an estimated 94.9 million to an estimated 116.8 million, an increase of 23.1%, with this increase being almost double what would be expected from population growth during this period.[18] Regardless of the causes of crowding; the negative results include delays in treatment,[19] decreased quality of care for patients,[20] and medication errors[21] among others.[22-26] Medication error includes components of administrative mistakes, physician focus disr uption, and perhaps miscommunication; but it does not necessarily mean direct harm to patients and their care. MEDMARX (the anonymous national database for reporting medication errors) shows 105,603 medication errors documented, with 2,063 (2%) of total errors occurring in the ED. Although most of these were corrected before causing harm to the patient, 147 (7%) resulted in patient harm. Of those cases; 123 resulted in temporary harm to the patient and required intervention, 21 resulted in admission to hospital, one may have contributed to or resulted in permanent harm, another required lifesaving intervention, and one resulted in a patient’s death.[27] In our institution, most of these errors are identified with the help of pharmacists as they review orders before dispensing. A study to determine the frequency of medication errors in one facility’s ED before and after an ED pharmacist was assigned to check medication orders found that the rate of errors decreased significantly (66.6%) when pharmacists prospectively reviewed the orders.[28] Pharmacists have assisted ED staff with drug selection, drug administration, and patient monitoring; as well as with emergency and trauma-related codes.[29,30] Nurses and physician assistance staff can also provide another filter before uneventful effects of medication errors. With the help of computer technology and medication databases, that may eliminate most obvious errors with the indications of harmful medication effects.[31] CONCLUSIONS The error frequency in our ED appears to remain relatively constant across the range of crowding when controlling for patient volume via the quantity of orders reviewed. Error quantity therefore increases with crowding, but not at a rate greater than the expected baseline error rate that occurs in uncrowded conditions. These findings nevertheless suggest that crowding may result in an increase in the error quantity in a linear fashion. ACKNOWLEDGEMENTS We would like to thank Jim Jensen, Pharm D; Kathy Hesse, RN; and our research volunteers Saada Zegar, Raheel Moody, and Brian Sweis for helping with data collection. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
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21. Patanwala AE, Warholak TL, Sanders AB, Erstad BL. A prospective observational study of medication errors in a tertiary care emergency department. Ann Emerg Med 2010;55:522-6. 22. Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, et al. Society for Academic Emergency Medicine, Emergency Department Crowding Task Force. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med 2009;16:1-10. 23. Cowan RM, Trzeciak S. Clinical review: Emergency department overcrowding and the potential impact on the critically ill. Crit Care 2005;9:291-5. 24. Hwang U, Richardson LD, Sonuyi TO, Morrison RS. The effect of emergency department crowding on the management of pain in older adults with hip fracture. J Am Geriatr Soc 2006;54:270-5. 25. American Academy of Pediatrics Committee on Pediatric Emergency Medicine. Overcrowding crisis in our nation’s emergency departments: Is our safety net unraveling? Pediatrics 2004;114:878-88. 26. Shayne P, Lin M, Ufberg JW, Ankel F, Barringer K, Morgan-Edwards S, et al. The effect of emergency department crowding on education: Blessing or curse? Acad Emerg Med 2009;16:76-82.
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27. Dobson R. US body reviews errors in emergency departments. BMJ 2003;326:620. 28. Brown JN, Barnes CL, Beasley B, Cisneros R, Pound M, Herring C. Effect of pharmacists on medication errors in an emergency department. Am J Health Syst Pharm 2008;65:330-3. 29. Wymore ES, Casanova TJ, Broekemeier RL, Martin JK Jr. Clinical pharmacist’s daily role in the emergency department of a community hospital. Am J Health Syst Pharm 2008;65:395-6, 398-9. 30. Case LL, Paparella S. Safety benefits of a clinical pharmacist in the emergency department. J Emerg Nurs 2007;33:564-6. 31. Hunter K. Implementation of an electronic medication administration record and bedside verification system. Online J Nurs Inform 2011;15. Available from: http://ojni.org/issues/?p=672 [Last accessed date on 3 Oct 2013]. How to cite this article: Watts H, Nasim MU, Sweis R, Sikka R, Kulstad E. Further characterization of the influence of crowding on medication errors. J Emerg Trauma Shock 2013;6:264-70. Received: 07.03.13. Accepted: 28.08.13. Source of Support: Nil. Conflict of Interest: None declared.
Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
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Further characterization of the influence of crowding on medication errors Hannah Watts, Muhammad Umer Nasim, Rolla Sweis, Rishi Sikka, Erik Kulstad Department of Emergency Medicine, Advocate Christ Medical Center, Oak Lawn, Illinois, USA
ABSTRACT Study Objectives: Our prior analysis suggested that error frequency increases disproportionately with Emergency department (ED) crowding. To further characterize, we measured this association while controlling for the number of charts reviewed and the presence of ambulance diversion status. We hypothesized that errors would occur significantly more frequently as crowding increased, even after controlling for higher patient volumes. Materials and Methods: We performed a prospective, observational study in a large, community hospital ED from May to October of 2009. Our ED has full-time pharmacists who review orders of patients to help identify errors prior to their causing harm. Research volunteers shadowed our ED pharmacists over discrete 4- hour time periods during their reviews of orders on patients in the ED. The total numbers of charts reviewed and errors identified were documented along with details for each error type, severity, and category. We then measured the correlation between error rate (number of errors divided by total number of charts reviewed) and ED occupancy rate while controlling for diversion status during the observational period. We estimated a sample size requirement of at least 45 errors identified to allow detection of an effect size of 0.6 based on our historical data. Results: During 324 hours of surveillance, 1171 charts were reviewed and 87 errors were identified. Median error rate per 4-hour block was 5.8% of charts reviewed (IQR 0-13). No significant change was seen with ED occupancy rate (Spearman’s rho = –.08, P = .49). Median error rate during times on ambulance diversion was almost twice as large (11%, IQR 0-17), but this rate did not reach statistical significance in univariate or multivariate analysis. Conclusions: Error frequency appears to remain relatively constant across the range of crowding in our ED when controlling for patient volume via the quantity of orders reviewed. Error quantity therefore increases with crowding, but not at a rate greater than the expected baseline error rate that occurs in uncrowded conditions. These findings suggest that crowding will increase error quantity in a linear fashion. Key Words: Crowding, errors, pharmacists
INTRODUCTION Background
Among the many challenges that emergency departments (EDs) are facing, crowding appears to be a major influence. ED crowding represents an international crisis that may affect the quality of and access to healthcare.[1] Causes of Address for correspondence: Dr. Muhammad Umer Nasim, E-mail: [email protected] Access this article online Quick Response Code: Website: www.onlinejets.org
DOI: 10.4103/0974-2700.120370
264
crowding have been categorized as; input factors (i.e., nonurgent visits, so-called frequent-flyer patients, the influenza season, etc.); throughput factors (i.e., lower staffing and mandated medical screening for all patients who present to an ED); outflow factors (i.e., inpatient boarding[2] with 22% of all ED patients boarding at one time in some cases); and hospital bed shortages.[1] Regardless of the aggravating factors, crowding appears to result in increased risk of death and disability,[3-7] poor quality of care in patients with severe pain, and medication errors. Medication errors (including dosing protocols or routes that are incorrectly administered[8]) contribute to significant morbidity, mortality, and costs to the health system.[9] One study of a national medication error database found that nearly 11,000 medication errors were reported over a 5-year period by EDs in 484 unique facilities.[10] Despite many reports on the impact of crowding on medication errors[11] few studies of this problem have been published.[12-14] Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Watts, et al.: Crowding and Medication errors
Study objective
Our prior analysis suggested that medication error frequency increases disproportionately with crowding.[15] And another prior study suggested that Emergency Department Work Index (EDWIN) scores may provide some measure to quantify crowding and perhaps discriminate between conditions that may be associated with higher error frequencies. [16] In order to better determine the relation between crowding and medication error occurrence, and control for variables not measured in our earlier study; we measured the association between medication errors and crowding in the ED over discrete time intervals while controlling for the number of charts reviewed and the presence of ambulance diversion status. Hypothesis
We hypothesized that escalation in medication errors is correlated positively with crowding in the ED regardless of controlling for higher patient volumes. MATERIALS AND METHODS Study participants, data source, institutional setting, and patient census. We performed this prospective, observational study in a large, community hospital ED from May to October of 2009. ED full time pharmacists, who worked weekday morning and evening shifts, reviewed orders of patients to help identify errors prior to their causing harm. Our ED has 50 licensed beds with annual patient visits at the time of the study of approximately 85,000. Our ED supports a 3-year emergency medicine residency program with 33 residents in postgraduate year (PGY) 1-3 format, and at the time of the study employed two full-time ED pharmacists working different 8-h shifts, 5 days a week. Intervention
The morning shift pharmacist reviewed and processed medication orders placed from early morning to late afternoon and the evening shift pharmacist reviewed and processed orders from later that afternoon until 11:00 pm. These orders comprised of medications ordered for newly arrived patients, patients in the critical care area of our ED, and boarded patients. There was no pharmacist coverage during overnight hours and weekends. In addition to satisfying responsibilities pertaining to every patient’s medication order, our pharmacists reviewed orders to help identify errors prior to producing harmful results. We organized a group of research volunteers who shadowed our ED pharmacists over a variety of discrete 4-h time periods during their reviews of orders on patients in the ED. We documented total numbers of charts reviewed by pharmacists during their shifts along with the errors identified in those charts. We categorized these errors according to the National Coordinating Council for Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Medication Error Reporting and Prevention (NCC MERP) Index for Categorizing Medication Errors Guidelines: Category A: Circumstances or events that have the capacity to cause error, category B: An error occurred but the error did not reach the patient (An “error of omission” does reach the patient), category C: An error occurred that reached the patient but did not cause patient harm, category D: An error occurred that reached the patient and required monitoring to confirm that it resulted in no harm to the patient and/ or required intervention to preclude harm, category E: An error occurred that may have contributed to or resulted in temporary harm to the patient and required intervention, category F: An error occurred that may have contributed to or resulted in temporary harm to the patient and required initial or prolonged hospitalization, category G: An error occurred that may have contributed to or resulted in permanent patient harm, category H: An error occurred that required intervention necessary to sustain life, category I: An error occurred that may have contributed to or resulted in the patient’s death [Table 1: NCC MERP error categories and Table 2: Error categories]. (Source: http://www.nccmerp.org/medErrorCatIndex.html) We then measured the correlation between error rate (number of errors divided by the total number of charts reviewed) and ED occupancy rate while controlling for diversion status during the 6-month observation period from May 2009 to October 2009. We estimated a sample size requirement of at least 45 errors identified to allow detection of an effect size of 0.6 based on our historical data. RESULTS Pharmacists and research volunteers reviewed a total of 1,171 charts. Total documented error surveillance was comprised of 81 discrete observation periods, each 4 h in duration (324 h total). We identified a total of 87 errors in these 81 observation periods. For each 4-h observation period, average numbers of charts reviewed were 14.4 [Figure 1, Table 3: Percentage of errors per charts reviewed]. Median error rate per 4-h block was 5.8% of charts reviewed (interquartile range (IQR) 0-13) Table 1: National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) error categories NCC MERP Error Categories
Errors Identified
A
5
B
35
C
21
D
20
E
4
F
2
G
0
H
0
I
0
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Watts, et al.: Crowding and Medication errors
Table 2: Error category Med error index
Error category
A
Error details
Med error index
Error category
Error details
Unapproved abreviation 10U written
C
Incorrect drug
Prednisone IV ordered instead of solumedrol
A
Unapproved abreviation U i/o units
C
Incorrect dose
Protonix 60 mg instead of 80 mg
A
Incomplete order
Missing type of insulin
C
Incorrect dose
Magnesium oxide ordered iv, only available po
A
Incorrect dose
Calcium accetate 670, should have been 667
C
Incorrect dose
Rocephin im ordered instead of iv
A
Non-formulary medication
Levofloxacin
C
Incorrect dose
Hctz 10 mg written for, 50 mg correct
B
Incorrect dose
Route missing
C
Incorrect formulation
Macrobid written, wrong dosage form for gtube
B
Allergy
Pcn, zosyn
C
Duplicate order
Prednisone given twice
B
Duplicate order
C
Incorrect frequency
Cipro q 8 i/o q12
B
Incorrect dose
Missing frequency
C
Delay in therapy
Dose due at t6:30 am, not given until 10 am
B
Incorrect dose
Propofol, wrong drip rate
C
Incorrect dose
500 mg of daptomycin ordred, should have been 600 mg
B
Incorrect dose
Td, missing route
C
Delay in therapy
Missed dose of solumedrol
B
Incorrect dose
Fentanyl, wrong drip rate
C
Incorrect dose
Rocephin
B
Incorrect dose
Unasyn, wrong dose
C
Incorrect dose
Total daily dose of tegretol not divided
B
Incorrect dose
Phenytoin, dosing error
C
Incorrect dose
Total daily dose of gapabpentin not divitided
B
Incorrect dose
Etomidate, missing route
C
Incorrect dose
500 mg po dilantin
B
Incorrect dose
Missing dose/directions on rx for peritoneal dialysis
C
Incorrect dose
Iron sulfate 500mg, not 325 mg
B
Incorrect dose
D
Missing order
Zosyn given, not ordered for uti
B
Incorrect dose
No ivf rate
D
Incorrect medication
Metoprolol ordered, metporolol xl given
B
Allergy
Zosyn, pcn allergy
D
Incorrect dose
Metoprolol 12.5 mg ordered, 25 mg administered
B
Incorrect dose
Correct med given, abx
D
Rx not written
Untreated Blood Sugar
B
Allergy
Pcn all, not given
D
Rx not written
Did not replace mag
B
Incorrect drug
Omnicell misfilled
D
Delay in therapy
2 hours late
B
Incorrect dose
Mucomyst writtent oral, not iv
D
Delay in therapy
Pneumonia
B
Incorrect dose
L-carnitine incorrect dose, should be 7000 mg, not 700 mg
D
Incorrect dose
Dilaudid
B
Incorrect dose
L-carnitine, 7 g intended, max is 6 gm
D
Delay in therapy
B
Incorrect dose
Incorrect frequency
D
Delay in therapy
Med not redosed
B
Incorrect dose
Missing route
D
Delay in therapy
Pt did not get keppra, home med
B
Incorrect dose
Wrong units, ml instead of gm
D
Incorrect dose
No renal dosing
B
Incorrect dose
Wrong route
D
Delay in therapy
Delay in therpay for cefepime, orders not written
B
Incorrect dose
Incorrect frequency
D
Incorrect dose
Genatmycin, dose too high
B
Incorrect dose
Wrong frequency
D
Incorrect dose
Amlodipine 10/20 mg ordered
B
Incorrect dose
Wrong units, ml instead of mg
D
Incorrect route
Insulin subq written, should have been IV for hyper kalemia
B
Incomplete order
Medication name ommitted
D
Incorrect dose
Lovenox with renal dysfunction, supratherapeutic dose writtent
B
Incorrect dose
Mucomyst incorrect dose written
D
Duplicate order
Heparin given and lovenox given in close proximity
B
Incorrect dose
Zosyn 3.375 mg instead of gms
D
Incorrect dose
Renal dosing
B
Allergy
Zosyn to pcn allergic pt
D
Incorrect dose
Ancef, flagyl, renal
B
Incorrect dose
Incorrect dose
E
Incorrect dose
Propofol drip, started at 60 mg/kgmin
B
Incorrect patient
Insulin, dextrose
E
Drug not administered
Lasix not given with blood
B
Allergy
Zosyn, pcn allergy
E
Delay in therapy
Pt on dka protocol, no bs checked for 4 hours
B
Incorrect dose
Zosyn
E
Drug not administered
Pt on dka protocol, k not added to fluids
C
Incorrect medication
Prilosec ordered, protonix given
F
Incorrect dose
Insulin drip started at 8 instead of 15 units/h
C
Incorrect dose
Incorrect frequency, zofran
F
Medication not titrated
Nitro not titrated
C
Incorrect medication
Exforge ordered, valsartan given only, no amplodipine
G
No error
No error
C
Incorrect medication
Rocephin instead of zosyn ordered
H
No error
No error
C
Incorrect dose
Toradol 60 mg iv written
I
No error
No error
Rx: Treatment
266
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Watts, et al.: Crowding and Medication errors
Table 3: Percentage of errors per charts reviewed Date
No. of errors found
No. of charts reviewed
Percentage errors
Date
No. of errors found
No. of charts reviewed
Percentage errors
5/12/2009
5
23
0.22
8/20/2009
0
6
0.00
5/12/2009
5
21
0.24
8/24/2009
1
12
0.08
5/20/2009
8
18
0.44
8/26/2009
0
10
0.00
5/22/2009
0
24
0.00
8/26/2009
1
8
0.13
5/26/2009
2
13
0.15
8/26/2009
0
17
0.00
5/27/2009
1
7
0.14
8/28/2009
0
13
0.00
5/29/2009
0
11
0.00
8/28/2009
0
16
0.00
6/1/2009
1
16
0.06
9/2/2009
0
17
0.00
6/2/2009
0
7
0.00
9/2/2009
2
10
0.20
6/2/2009
0
11
0.00
9/2/2009
1
16
0.06
6/8/2009
3
14
0.21
9/3/2009
0
15
0.00
6/9/2009
2
17
0.12
9/3/2009
0
10
0.00
6/11/2009
2
8
0.25
9/4/2009
0
12
0.00
6/12/2009
1
14
0.07
9/8/2009
0
15
0.00
6/15/2009
3
19
0.16
9/8/2009
1
14
0.07
6/16/2009
3
18
0.17
9/9/2009
1
13
0.08
6/19/2009
0
12
0.00
9/9/2009
0
14
0.00
6/23/2009
1
23
0.04
9/9/2009
0
18
0.00
6/30/2009
2
20
0.10
9/11/2009
1
15
0.07
7/1/2009
1
18
0.06
9/14/2009
2
15
0.13
7/7/2009
0
14
0.00
9/14/2009
0
12
0.00
7/8/2009
0
21
0.00
9/15/2009
0
9
0.00
7/10/2009
3
15
0.20
9/16/2009
1
15
0.07
7/14/2009
0
10
0.00
9/16/2009
0
18
0.00
7/15/2009
1
22
0.05
9/18/2009
0
13
0.00
7/21/2009
2
21
0.10
9/23/2009
1
10
0.10
7/22/2009
0
17
0.00
9/30/2009
0
18
0.00
7/24/2009
1
18
0.06
10/2/2009
0
11
0.00
7/27/2009
0
15
0.00
10/5/2009
0
5
0.00
7/29/2009
1
17
0.06
10/5/2009
0
12
0.00
7/31/2009
2
8
0.25
10/6/2009
3
12
0.25
8/12/2009
0
14
0.00
10/6/2009
2
15
0.13
8/12/2009
1
14
0.07
10/7/2009
0
13
0.00
8/13/2009
2
13
0.15
10/7/2009
0
6
0.00
8/14/2009
1
14
0.07
10/7/2009
1
15
0.07
8/17/2009
1
16
0.06
10/8/2009
1
7
0.14
8/18/2009
0
12
0.00
10/8/2009
0
20
0.00
8/18/2009
0
15
0.00
10/9/2009
0
9
0.00
8/19/2009
2
11
0.18
10/16/2009
3
20
0.15
8/19/2009
1
6
0.17
10/21/2009
1
13
0.08
8/19/2009
2
18
0.11
10/21/2009
3
17
0.18
8/20/2009
1
10
0.10
Total errors
87
1171
[Figure 2]. Errors occurred throughout the spectrum of care. Errors included; (a) incorrect dosage, (b) incorrect administration routes (e.g., intravenous (IV) medications ordered for intramuscular (IM)), (c) medication duplications, and (d) delays in therapy. No significant change was seen with the ED occupancy rate (Spearman’s rho (r) = – 0.08, P = 0.49) [Figure 3], whereas previously error frequency showed a positive correlation with daily average EDWIN score (Spearman’s ρ = 0.33; P = 0.001).[15] The Median error rate during times on ambulance diversion was almost twice as large (11%, IQR 0-17) [Figure 4], but this rate did not reach statistical significance in univariate or multivariate analysis. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Limitations
Since we collected data from only one ED, our results may not be generalizable to all EDs. Our pharmacists are experienced and have specific skills and knowledge to perform their function in a busy ED environment. Changes in daily census may impact findings, with an increased inflow of patients possibly resulting in a higher number of medication and therapy orders, which may hinder pharmacists’ availability to review charts for errors and accurately document the results. Our ED has employed pharmacists for two full-time shifts, morning (7:00 am-3:00 pm) and evening (3:00 pm11:00 pm), but the ED at the time of this study was devoid of pharmacists’ coverage from 11:00 pm to 7:00 am. This lack 267
Watts, et al.: Crowding and Medication errors
Figure 1: Histogram showing the occurrence of errors during each observation period. Most observations periods yielded no errors, whereas the largest number found in one observation period was eight
Figure 3: Showing no significant change was seen with the emergency department (ED) occupancy rate (Spearman’s rho = −0.08, P = 0.49)
of coverage limits extrapolation of our data beyond hours when pharmacists were present. DISCUSSION Previously we determined a positive correlation between medication error frequency and ED occupancy as we used the EDWIN score as a point of reference for ED occupancy and medication error frequency measurement. We grouped EDWIN score into low, medium, and high crowding days; and determined that the error frequency was significantly increased in the high crowding group.[15] To further characterize this crowding influence on medication error, we reviewed patients’ charts for medication orders. After reviewing 1,171 charts and 324 h of error surveillance; we found that there was not a disproportionate increase in medication errors as ED occupancy increased [Figure 3], rather there is a linear 268
Figure 2: Showing median error rate per 4-h block was 5.8% of charts reviewed (IQR: 0-13)
Figure 4: Showing median error rate during times on ambulance diversion was almost twice as large (11%, IQR: 0-17)
association between crowding and medication error. This may be due to at least two factors: First, our department may be getting better at reducing the number of errors made when crowding conditions increase, which in turn would result in a reduction in the number of errors available to be identified by the pharmacists. Second, increases in errors seen with increased crowding may be occurring in a nonlinear fashion that is not detected by our sample size. Nevertheless, the fact that errors demonstrably increase as crowding increases raises significant concerns, and suggests that greater vigilance is warranted as crowding conditions occur. The differences in the findings of the current study from our previous work are likely a result of the more granular measurement process employed, combined with the fact that in this study, we controlled for error number by factoring in the number of charts analyzed; whereas in earlier work, we did not. Performance improvement at our institution may additionally be a factor; however temporal changes in these processes are more difficult to quantify. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
Watts, et al.: Crowding and Medication errors
In 2007, there were about 117 million ED visits in the United States, about one-fifth of ED visits by children younger than 15 years of age were to pediatric EDs, there were 121 ED visits for asthma per 10,000 children under 5 years of age.[17] From 1997 and 2007, total annual visits to US EDs increased from an estimated 94.9 million to an estimated 116.8 million, an increase of 23.1%, with this increase being almost double what would be expected from population growth during this period.[18] Regardless of the causes of crowding; the negative results include delays in treatment,[19] decreased quality of care for patients,[20] and medication errors[21] among others.[22-26] Medication error includes components of administrative mistakes, physician focus disr uption, and perhaps miscommunication; but it does not necessarily mean direct harm to patients and their care. MEDMARX (the anonymous national database for reporting medication errors) shows 105,603 medication errors documented, with 2,063 (2%) of total errors occurring in the ED. Although most of these were corrected before causing harm to the patient, 147 (7%) resulted in patient harm. Of those cases; 123 resulted in temporary harm to the patient and required intervention, 21 resulted in admission to hospital, one may have contributed to or resulted in permanent harm, another required lifesaving intervention, and one resulted in a patient’s death.[27] In our institution, most of these errors are identified with the help of pharmacists as they review orders before dispensing. A study to determine the frequency of medication errors in one facility’s ED before and after an ED pharmacist was assigned to check medication orders found that the rate of errors decreased significantly (66.6%) when pharmacists prospectively reviewed the orders.[28] Pharmacists have assisted ED staff with drug selection, drug administration, and patient monitoring; as well as with emergency and trauma-related codes.[29,30] Nurses and physician assistance staff can also provide another filter before uneventful effects of medication errors. With the help of computer technology and medication databases, that may eliminate most obvious errors with the indications of harmful medication effects.[31] CONCLUSIONS The error frequency in our ED appears to remain relatively constant across the range of crowding when controlling for patient volume via the quantity of orders reviewed. Error quantity therefore increases with crowding, but not at a rate greater than the expected baseline error rate that occurs in uncrowded conditions. These findings nevertheless suggest that crowding may result in an increase in the error quantity in a linear fashion. ACKNOWLEDGEMENTS We would like to thank Jim Jensen, Pharm D; Kathy Hesse, RN; and our research volunteers Saada Zegar, Raheel Moody, and Brian Sweis for helping with data collection. Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
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27. Dobson R. US body reviews errors in emergency departments. BMJ 2003;326:620. 28. Brown JN, Barnes CL, Beasley B, Cisneros R, Pound M, Herring C. Effect of pharmacists on medication errors in an emergency department. Am J Health Syst Pharm 2008;65:330-3. 29. Wymore ES, Casanova TJ, Broekemeier RL, Martin JK Jr. Clinical pharmacist’s daily role in the emergency department of a community hospital. Am J Health Syst Pharm 2008;65:395-6, 398-9. 30. Case LL, Paparella S. Safety benefits of a clinical pharmacist in the emergency department. J Emerg Nurs 2007;33:564-6. 31. Hunter K. Implementation of an electronic medication administration record and bedside verification system. Online J Nurs Inform 2011;15. Available from: http://ojni.org/issues/?p=672 [Last accessed date on 3 Oct 2013]. How to cite this article: Watts H, Nasim MU, Sweis R, Sikka R, Kulstad E. Further characterization of the influence of crowding on medication errors. J Emerg Trauma Shock 2013;6:264-70. Received: 07.03.13. Accepted: 28.08.13. Source of Support: Nil. Conflict of Interest: None declared.
Journal of Emergencies, Trauma, and Shock I 6:4 I Oct - Dec 2013
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