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Int. 林泰祺Int. 林泰祺

Patterns of Errors Contributing to Trauma Mortality: Lessons Learned From 2594 Deaths

Russell L. Gruen, MD, PhD Gregory J. Jurkovich, MD Lisa K. McIntyre, MD Hugh M. Foy, MD Ronald V. Maier, MD

Ann Surg 244(3):371-380, 2006. © 2006 Lippincott Williams & Wilkins

Patterns of Errors Contributing to Trauma Mortality: Lessons Learned From 2594 Deaths

Russell L. Gruen, MD, PhD Gregory J. Jurkovich, MD Lisa K. McIntyre, MD Hugh M. Foy, MD Ronald V. Maier, MD

Ann Surg 244(3):371-380, 2006. © 2006 Lippincott Williams & Wilkins

IntroductionIntroduction

• Trauma care creates a perfect storm for medical errors: – unstable patients– incomplete histories– time-critical decisions– concurrent tasks– involvement of many disciplines– junior personnel working after-hours in

busy emergency departments

• Trauma care creates a perfect storm for medical errors: – unstable patients– incomplete histories– time-critical decisions– concurrent tasks– involvement of many disciplines– junior personnel working after-hours in

busy emergency departments

IntroductionIntroduction

• Trauma given– high baseline mortality rates– often complicated in-hospital care – relative paucity of widely applicable

management protocols, especially beyond the Golden Hour of initial resuscitation, to which Advanced Trauma Life Support (ATLS) protocols apply

• Trauma given– high baseline mortality rates– often complicated in-hospital care – relative paucity of widely applicable

management protocols, especially beyond the Golden Hour of initial resuscitation, to which Advanced Trauma Life Support (ATLS) protocols apply

IntroductionIntroduction

• In this study, we aimed to identify errors that had contributed to the death of trauma patients at a specific high-volume regional trauma center over a 9-year period and determine any apparent patterns of occurrence

• We also aimed to examine the effect of introduction of local institutional policies on reducing error

• In this study, we aimed to identify errors that had contributed to the death of trauma patients at a specific high-volume regional trauma center over a 9-year period and determine any apparent patterns of occurrence

• We also aimed to examine the effect of introduction of local institutional policies on reducing error

MethodMethod

• All trauma deaths that occurred after arrival in the emergency room and prior to discharge from Harborview Medical Center (HMC) in the 9 years from January 1, 1996 to December 31, 2004 were eligible for this study

• Those deaths identified at – M&M meetings as being possibly – Self-reporting of errors – Chart review

• All trauma deaths that occurred after arrival in the emergency room and prior to discharge from Harborview Medical Center (HMC) in the 9 years from January 1, 1996 to December 31, 2004 were eligible for this study

• Those deaths identified at – M&M meetings as being possibly – Self-reporting of errors – Chart review

MethodMethod• Appraised all deaths that had less than 50% pr

obability of death at the time of admission, as determined by the Trauma Injury Severity Score (TRISS) or the Harborview Adjusted Risk of Mortality (HARM) score

• Potential errors were identified by – examining the cause of death and its antecedent ev

ents– reviewing the process of care for apparent errors in

decision-making, timing, conduct of procedures, and nonprocedural mishaps

• Appraised all deaths that had less than 50% probability of death at the time of admission, as determined by the Trauma Injury Severity Score (TRISS) or the Harborview Adjusted Risk of Mortality (HARM) score

• Potential errors were identified by – examining the cause of death and its antecedent ev

ents– reviewing the process of care for apparent errors in

decision-making, timing, conduct of procedures, and nonprocedural mishaps

MethodMethod• Each case of suspected error was

subjected to peer review at one or more of the following forums: – weekly M&M meetings– monthly trauma council QA meetings– quarterly hospital quality assurance

forums – annual regional QA forums

• Each case of suspected error was subjected to peer review at one or more of the following forums: – weekly M&M meetings– monthly trauma council QA meetings– quarterly hospital quality assurance

forums – annual regional QA forums

Error Definition and ClassificationError Definition and Classification

• Error Impact, which in our study was death

• Error Type, as errors in diagnosis, treatment, prevention, or other (equipment failures; communication failures; and errors in transfer)

• Error Impact, which in our study was death

• Error Type, as errors in diagnosis, treatment, prevention, or other (equipment failures; communication failures; and errors in transfer)

Error Definition and ClassificationError Definition and Classification

• Error Domain, – initial assessment and resuscitation (inclu

ding prehospital); – secondary survey and tests (eg, CT); interh

ospital transfers– initial interventions (eg, OR, Angio); ICU; g

eneral ward; and rehabilitation

• Error Domain, – initial assessment and resuscitation (inclu

ding prehospital); – secondary survey and tests (eg, CT); interh

ospital transfers– initial interventions (eg, OR, Angio); ICU; g

eneral ward; and rehabilitation

Error Definition and ClassificationError Definition and Classification• Error Cause, which refers to the psychologic

cause, that is– Input error: the input data are incorrectly perceiv

ed; therefore, an incorrect intention is formed and the wrong action is performed

– Intention error: the input data are correctly perceived, but an incorrect intention is formed, and the wrong action is performed

– Execution error: the input data are correctly perceived and the correct intention is formed, but the wrong action is performed

• Error Cause, which refers to the psychologic cause, that is

– Input error: the input data are incorrectly perceived; therefore, an incorrect intention is formed and the wrong action is performed

– Intention error: the input data are correctly perceived, but an incorrect intention is formed, and the wrong action is performed

– Execution error: the input data are correctly perceived and the correct intention is formed, but the wrong action is performed

Pattern Recognition and Impact of Policies

Pattern Recognition and Impact of Policies

• The occurrence of errors relative to each policy's implementation was then plotted to give an indication of whether or not such policies had been effective in reducing error occurrence

• Observations were categorized into whether or not a new policy was implemented during the study period

• The occurrence of errors relative to each policy's implementation was then plotted to give an indication of whether or not such policies had been effective in reducing error occurrence

• Observations were categorized into whether or not a new policy was implemented during the study period

ResultsResults

• In 9 years between 1996 and 2004, inclusive, there were 44,401 trauma patient admissions that resulted in 2594 deaths (5.8% of admissions)

• Of the deaths: – 69% were male– median age was 46 years– 74% were due to blunt trauma– 17% due to penetrating trauma– 9% due to burns and other mechanisms

• In 9 years between 1996 and 2004, inclusive, there were 44,401 trauma patient admissions that resulted in 2594 deaths (5.8% of admissions)

• Of the deaths: – 69% were male– median age was 46 years– 74% were due to blunt trauma– 17% due to penetrating trauma– 9% due to burns and other mechanisms

ResultsResults• 53 deaths (2.0%) had quality of care

concerns discussed at M&M review that may have contributed to the death

• 601 deaths (1.4% admissions, 23.2% deaths) had less than 50% mortality risk at the time of admission, as defined by TRISS and HARM scores

• After this review, 64 patients (0.14% admissions, 2.5% deaths over the 9-year period) had recognized errors in care that were likely to have contributed to their death go

• 53 deaths (2.0%) had quality of care concerns discussed at M&M review that may have contributed to the death

• 601 deaths (1.4% admissions, 23.2% deaths) had less than 50% mortality risk at the time of admission, as defined by TRISS and HARM scores

• After this review, 64 patients (0.14% admissions, 2.5% deaths over the 9-year period) had recognized errors in care that were likely to have contributed to their death go

ResultsResults

• The major clinical groupings of errors included:– hemorrhage control (28%)– airway management (16%)– inappropriate management of unstable

patients (14%)– complications of procedures (12%)– inadequate prophylaxis (11%) – missed or delayed diagnoses (11%)– over-resuscitation with fluids (5%)– other poor management decisions (3%) go

• The major clinical groupings of errors included:– hemorrhage control (28%)– airway management (16%)– inappropriate management of unstable

patients (14%)– complications of procedures (12%)– inadequate prophylaxis (11%) – missed or delayed diagnoses (11%)– over-resuscitation with fluids (5%)– other poor management decisions (3%) go

ResultsResults• By phase of trauma management:

– 34% of errors occurred in the ED (20% during initial assessment and resuscitation, 14% during the secondary survey and initial diagnostic tests)

– 8% during stabilization and interhospital transport

– 11% during initial interventions (surgery and/or angiography)

– 37% during the intensive care unit stay– 9% during the general or rehabilitation war

d inpatient stay

• By phase of trauma management:– 34% of errors occurred in the ED (20% durin

g initial assessment and resuscitation, 14% during the secondary survey and initial diagnostic tests)

– 8% during stabilization and interhospital transport

– 11% during initial interventions (surgery and/or angiography)

– 37% during the intensive care unit stay– 9% during the general or rehabilitation war

d inpatient stay

ResultsResults• By type of error:

– 61% were errors of treatment– 20% were errors of prophylaxis– 13% were errors of diagnosis– 5% were errors associated with transfer– only 1 was a result of equipment failure

• By type of error:– 61% were errors of treatment– 20% were errors of prophylaxis– 13% were errors of diagnosis– 5% were errors associated with transfer– only 1 was a result of equipment failure

ResultsResults• By the internal processing

classification of cause:– 23% were input errors– 50% were intention errors– 27% were execution go

• By the internal processing classification of cause:– 23% were input errors– 50% were intention errors– 27% were execution go

DiscussionDiscussion• This study addressed the types and

nature of errors that contribute to trauma deaths and the integration of error detection into an institutional patient safety program

• Among 44,401 admissions and 2594 deaths over 9 years, 2.47% of deaths at our institution were contributed to by errors

• 2% to 3% error-related death rate may be an absolute baseline in complex trauma systems

• This study addressed the types and nature of errors that contribute to trauma deaths and the integration of error detection into an institutional patient safety program

• Among 44,401 admissions and 2594 deaths over 9 years, 2.47% of deaths at our institution were contributed to by errors

• 2% to 3% error-related death rate may be an absolute baseline in complex trauma systems

DiscussionDiscussion

• This study is likely to assist error reduction in 3 important ways:– Through identification of specific categorie

s of errors – Through considering the type and underlyi

ng psychologic cause– Demonstrating the likely effectiveness of su

ch evidence-based institutional protocols go

• This study is likely to assist error reduction in 3 important ways:– Through identification of specific categorie

s of errors – Through considering the type and underlyi

ng psychologic cause– Demonstrating the likely effectiveness of su

ch evidence-based institutional protocols go

DiscussionDiscussion

• This study combines contemporary understanding of error causation, classification, and remediation with an institution specific process

• The process uses existing systems and is goal-oriented in seeking out patterns of errors, which can then be targeted

• The process is likely to be relevant to other institutions and may be as applicable in other surgical disciplines as it is in trauma

• This study combines contemporary understanding of error causation, classification, and remediation with an institution specific process

• The process uses existing systems and is goal-oriented in seeking out patterns of errors, which can then be targeted

• The process is likely to be relevant to other institutions and may be as applicable in other surgical disciplines as it is in trauma

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