Injury, Int. J. Care Injured 46 (2015) 21–28
Contents lists available at ScienceDirect
Injury journal homepage: www.elsevier.com/locate/injury
Compliance with a massive transfusion protocol (MTP) impacts patient outcome§ Bawazeer M.*, Ahmed N.1, Izadi H.2, McFarlan A.3, Nathens A.4, Pavenski K.5 Trauma Program and Transfusion Medicine, Departments of Surgery and Laboratory Medicine, St. Michael’s Hospital, University of Toronto, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Accepted 25 September 2014
Background: About 5% of civilian trauma requires massive transfusion. Protocolized resuscitation with blood products to achieve high plasma:RBC ratio has been advocated to improve survival. Our objectives were to measure compliance to our institutional MTP, to identify quality assurance activities that could improve protocol compliance and to determine if protocol compliance was related to patient outcome. Methods: The investigators determined 13 compliance criteria based upon our institutional protocol. We measured compliance in 72 consecutive MTP activations between January 2010 and September 2011 at a Level I trauma centre. Data elements were retrospectively retrieved from blood bank, trauma registry and clinical records. Patients were stratified into three groups based on compliance level, and mortality differences were compared. Results: Average compliance for the cohort (n = 72) was 66%. The most common cause of noncompliance was failure to send a complete haemorrhage panel from the trauma bay (96%). Failure to monitoring blood work every 30 min occurred in 89% of cases. Delay in activation and deactivation occurred in 50% and 50% respectively. Non-compliance to protocol-based administration of blood products happened in 47%. The cohort was stratified into three groups based on compliance, A: 80% (low, moderate and high compliance groups). There was no statistical significance with regard to median age, median ISS, ED SBP, ED GCS and AIS of the head/spine, chest and abdomen. The mortality rates in each group were 62%, 50% and 10% in the low, moderate and high compliance groups respectively. Mortality differences were compared using adjusted logistic regression. The OR for mortality between Groups A and B = 1.1 [95% CI 0.258–4.687 (P = 0.899)] while the OR for mortality between Groups C and B = 0.02 [95% CI 3 in head/spine AIS, chest AIS and abdomen AIS respectively. Slightly greater than half (53%) of the cohort survived and was discharged from the hospital. Table 2 summarizes the compliance criteria and the level of compliance for each criterion. The most common cause of noncompliance was failure to send a complete haemorrhage panel from the trauma bay (96%) and the most commonly missing element was fibrinogen. A full panel was missed in 6% of cases. According to the protocol, laboratory investigations (ABG, electrolytes, CBC, INR and fibrinogen) should be done every 30 min. Only
Age Gender Female Males ISS (minimum–maximum) Mechanism Penetrating Blunt Head AIS 3 >3 Chest AIS 3 >3 Abdomen AIS 3 >3 Survival Alive Dead
N = 72 (%)
Median
16–88
47.5
16 (22%) 56 (78%) 4–75 19 (26%) 53 (74%) 45 (63%) 27 (37%) 32 (44%) 40 (56%) 56 (78%) 16 (22%) 38 (53%) 34 (47%)
34
Quartile range 59.5–30.5
50–25.0
M. Bawazeer et al. / Injury, Int. J. Care Injured 46 (2015) 21–28
24
Table 2 Compliance criteria and the level of compliance in each. Protocol criteria
% Compliance
Comments
1
Was MTP activation based on the pre-specified indications?
82
2 3 4
Timely communication with Blood Bank ( 15 min From trauma bay CBC, INR, FN; FN missing in 96% 6% missed the full panel 6:4:1; RBC:FP:Plat + early cryoprecipitate Active re-warming within 2 h of ICU arrival This was not accounted for in early deaths HCO3 infusion within 2 h of ICU arrival This was not accounted for in early deaths Given in 6% of cases (N = 4), one case (25%) was not given according to the protocol Q30 min This was not accounted for in early deaths Wastage occurred in 6% of cases Within 1 h of last blood product given Within 2 h of MTP activation This was not accounted for in early deaths Within 2 h of MTP activation This was not accounted for in early deaths
Average compliance
66
MTP = massive transfusion protocol, CBC = complete blood count, INR = international normalized ratio, FN = fibrinogen, RBC = red blood cells, FP = frozen plasma, Plat = platelets, rFVIIa = recombinant Factor VIIa, ABG = arterial blood gas, Lytes = serum electrolytes, K = potassium, Ca = calcium.
11% of cases were compliant with this criterion. Timely activation of the MTP (within 15 min of patient arrival) occurred in 50% and timely deactivation of the MTP (within 1 h from the last blood product issued) occurred in 50%. Delay in activation and deactivation occurred in 50% and 50% respectively. 53% of patients had per-protocol administration of blood products, while 47% did not (based on high INR, low platelets and low fibrinogen which were not corrected). Recombinant factor VIIa is recommended for refractory bleeding following attempt of surgical haemostasis as well as correction of coagulopathy and thrombocytopaenia. Recombinant factor VIIs was administered in four cases (6%), and in three cases it was administered according to protocol. This protocol was an older version of our institutional MTP, which is revised every 2 years. Of the four cases who received rFVIIa, two were in the moderate compliance group with compliance rate of 77% and 62% respectively. The other two patients were in the high compliance group with a compliance rate of 85% in both patients. In one patient only in the high compliance group, it was administered before correction of coagulopathy, that is FFP and platelets were administered after rFVIIa. Potassium and calcium monitoring and correction occurred in 71% and 58% respectively. Active measures to correct hypothermia and acidosis occurred in 68% and 83% respectively. In 82% of cases, MTP was activated according to the pre-specified indications, while in 18% MTP was neither required nor indicated. In 93% of cases, compatibility testing (blood group and screen and cross match) was sent upon MTP activation from the trauma bay. Wastage of blood products was prevented in 94%. The overall compliance in this cohort was 66%. The cohort was then stratified into three groups based on compliance, 80% (low, moderate and high compliance groups). The summary of the characteristics of the groups is in Table 3. There were no statistical differences between the three groups’ demographics. Group A had higher ISS than Groups B and C but P value was not significant. With regard to blood products administration, Group C received slightly higher rates of RBC, FFP and platelets, but without statistical significance. Group C had also longer ICU and Hospital LOS but not statistically significant. The average mortality rates in each group were 62%,
50% and 10% (low, moderate and high compliance groups respectively). We also compared survivors to non-survivors. Table 4 summarizes demographics of the two groups. Non-survivors had a higher ISS, more patients with ED GCS 3 with P values of 0.005, 0.004 and 0.005 respectively. Median age, ED SBP and AIS of the chest and abdomen were not different between survivors and non-survivors. Compliance criteria were also compared between survivors and nonsurvivors. The summary of the comparison is provided in Table 5. We found that amongst survivors there was higher compliance with sending blood group and cross match and correction of hypothermia with P values 0.04 and 0.05 respectively. The rest of the compliance measures were not statistically significant between survivors and non-survivors. Average compliance amongst survivors was 70% while in non-survivors was 62% [P = 0.002]. In an effort to decrease the risk of bias, we used first an unadjusted logistic regression model to compare between Groups A, B and C. Group B was used as the reference group because it represented the average compliance rate of the whole cohort. The OR for mortality between Groups A and B = 1.67, [95% CI 0.520– 5.346 (P = 0.390)] while the OR for mortality between Groups C and B = 0.11 [95% CI 0.013–0.949 (P = 0.045)]. In another effort to further decrease the risk of bias, an adjusted logistic regression model was created to compare between mortality differences. Because of the small sample size, it was not possible to fit a model with many predictors. We selected only factors that were most associated with mortality based on Table 5, namely age, ISS, ED GCS and AIS head/spine. Table 6 describes the model. The OR for mortality between Groups A and B = 1.1 [95% CI 0.258–4.687 (P = 0.899)] while the OR for mortality between Groups C and B = 0.02 [95% CI 90 4 3 Chest AIS 3 >3 Abdomen AIS 3 >3 RBC administered (min–max units)
42 (17–82) (n = 13) 81% (n = 3) 19%
51 (16–88) (n = 35) 76% (n = 11) 24%
39 (16–62) (n = 10) 100% (n = 0) 0%
0.334a 0.282b
(n = 5) 31% (n = 11) 69% 4–66 42
(n = 11) 24% (n = 35) 76% 9–75 38
(n = 0) 0% (n = 10) 100% 9–66 26
0.166b
(n = 14) 88% (n = 2) 12%
(n = 34) 74% (n = 12) 26%
(n = 5) 50% (n = 5) 50%
0.124b
(n = 9) 56% (n = 7) 44%
(n = 18) 39% (n = 28) 61%
(n = 3) 30% (n = 7) 70%
0.392b
(n = 12) 75% (n = 4) 25%
(n = 38) 83% (n = 8) 17%
(n = 8) 80% (n = 2) 20%
0.757b
(n = 8) 50% (n = 8) 50%
(n = 29) 63% (n = 17) 37%
(n = 8) 80% (n = 2) 20%
0.304c
(n = 7) 44% (n = 9) 56%
(n = 22) 48% (n = 24) 52%
(n = 3) 30% (n = 7) 70%
0.588c
(n = 10) 63% (n = 6) 37% 0–30 Total 156 12 units 0–15 Total 58 4 units 0–6 Total 15 1 pool 1–73 1 day 0–53 1 day
(n = 37) 80% (n = 9) 20% 2–40 Total 648 12 units 0–21 Total 228 4 units 0–4 Total 49 1 pool 1–75 8 days 0–51 3 days
(n = 9) 90% (n = 1) 10% 0–74 Total 228 14 units 0–34 Total 119 8 units 0–17 Total 38 2 pools 1–70 17 days 0–40 7 days
0.240b
(n = 10) 62% (n = 6) 38%
(n = 23) 50% (n = 23) 50%
(n = 1) 10% (n = 9) 90%
Median FFP administered (min–max, units) Median Platelets administered (min–max, pool of platelets) Median Length of stay (LOS) (min–max) Median ICU days (min–max) Median Outcome Dead Alive
0.182a
0.902a
0.564a
0.542a
0.279a 0.623a
0.024c
ISS = injury severity score, ED SBP = Emergency Department systolic blood pressure, ED GCS = Emergency Department Glasgow coma score, AIS = abbreviated injury score, 1 pool of platelets = 5 units of platelet-rich plasma. a Kruskal–Wallis test. b Fisher’s exact test. c Chi-square test.
them was in Group A (compliance rate 50%) and the other one was in Group B (compliance rate 75%). There was only one patient in Group A required resuscitative thoracotomy and died in the trauma bay (compliance rate was 50%). There were three patients required resuscitative thoracotomy and survived to the operating room but died there. Two of them were in Group B with compliance rates of 62% and 75%. The last one was in Group C with a compliance rate of 87%. Those activations missed some system factors like delay in activation and deactivation, missing cross match and haemorrhage panel upon admission and blood products administration was inappropriate. Discussion The principles of trauma quality improvement include identification; intervention and measurement of pre-defined standards of care [12]. Retrospective reviews are only one way to identify factors that may compromise patient care and ‘‘to see how we are doing’’. After identification of factors, which are provider-, systemor patient-related, appropriate quality assurance measures can be applied to improve standards of care [1]. The goals of the current study were to assess compliance with our institutional MTP 3 years
after its implementation and to identify quality indicators that can be regularly tracked. We also wanted to see if compliance with MTP impacted patient outcomes. We found that the mean compliance rate was 66%. In his study, Cotton et al. reported initial 27% full compliance (all 7 criteria were met), 73% had one violation and 46% had more than one violation. This was subsequently improved to more than 80% following appropriate interventions, except in one measure (early activation of the MTP) [1]. The lowest level of compliance in our study was 25% in one patient who made palliative and died early. The causes of non-compliance were failure to send a complete haemorrhage panel, delay in activation and deactivation, blood product administration was inappropriate and there was some product wastage. Of interest, the highest level of compliance was 87% (7 criteria met out of 8) in one patient. This patient had an ED thoracotomy and survived to the operating room but died there. The only criterion which was not met was failure to send a complete haemorrhage panel. In no patients had full compliance with all 13 criteria were seen. In our study, the most common non-compliance criterion was failure to send a complete haemorrhage panel from the ED in 96%, and fibrinogen was the most commonly missing element. In 6%
M. Bawazeer et al. / Injury, Int. J. Care Injured 46 (2015) 21–28
26 Table 4 Comparison of demographics by mortality. Demographics
Non-survivors N = 34 (%)
Survivors N = 38 (%)
P value
Median age (minimum–maximum) Gender Female Male Median ISS (minimum–maximum) Mechanism of injury Blunt Penetrating ED SBP >90 3 AIS abdomen 3 >3
51 (16–88)
45 (16–83)
0.142a
8 (24%) 26 (76%) 44 (9–75)
8 (21%) 30 (79%) 29 (4–66)
1.00b
28 (82%) 6 (18%)
25 (66%) 13 (34%)
0.186b
12 (35%) 22 (65%)
18 (47%) 20 (53%)
0.425b
22 (65%) 12 (35%)
36 (95%) 2 (5%)
0.004b
15 (44%) 19 (56%)
30 (79%) 8 (21%)
0.005b
12 (35%) 22 (65%)
20 (53%) 18 (47%)
0.215b
26 (76%) 8 (24%)
30 (79%) 8 (21%)
1.00b
0.005a
ISS = injury severity score, ED SBP = Emergency Department systolic blood pressure, ED GCS = Emergency Department Glasgow coma score, AIS = abbreviated injury score. Bold values indicate significant p values a Wilcoxon two-sample test. b Continuity-adjusted chi square test.
(4 cases) a complete haemorrhage panel was missing. All of those four cases were haemodynamically unstable and none of those patients survived. In these critically ill patients, laboratory-based approach may not be appropriate and management should be based on empiric protocol including ratio-based resuscitation. It is not very clear whether this particular criterion can affect patient outcome, but knowledge of the patient’s coagulations system would be very useful to guide ongoing therapy, i.e. delay in measuring fibrinogen might delay administration of cryoprecipitate. Point-of-care coagulation testing (e.g. TEG or ROTEM) may also play a role by allowing to specifically tailor haemotherapy and is likely to eventually replace the need for conventional coagulation testing [13]. A study of 1974 patients, TEG was shown to be
clinically superior to conventional coagulation studies with similar costs [13]. The second most common non-compliance criterion was failure to regularly order laboratory investigations. This occurred in 89% of cases. Possible factors contributing to this high rate of noncompliance were on-going patient instability; in the operating room or the ICU; and possibly lack of knowledge and/or appreciation of the importance of ongoing monitoring. As an academic teaching centre, and with frequently changing housestaff of fellows and residents, this aspect will require aggressive provider education and academic detailing. As well consideration may be given to displaying the MTP flowchart in poster format in the ED or ICU, or development of MTP pocket cards or apps to be used as reminders. Development of pre-printed ICU orders with check boxes to facilitate rapid ordering of the required blood tests may also be helpful. The third and fourth most common non-compliance criteria were delay in activation (50%) and delay in deactivation (50%) of MTP. Cotton et al. [1] reported that failure to activate MTP in ED was the second most common cause of non-compliance in their study (44%). In his study, this criterion failed to improve throughout the study period even after aggressive educational efforts. They also reported that the presence of a clinical instructor was more likely to be associated with appropriate termination of the MTP than a senior faculty. In our study, factors that might have contributed to delay in activation and deactivation were likely related to provider-related education and awareness of the MTPs. Patient-related factors could include rapidly changing clinical status of a patient such as those who come initially stable and become precipitously unstable. Provider-related factors can be improved by re-education and implementation of a scoring system that can be integrated into the current MTP. An easy scoring system was recommended by Cotton et al. This system uses dichotomous variables that require only a ‘‘Yes’’ or ‘‘No’’ answer: a penetrating mechanism, systolic BP 120 BPM and a positive FAST. A score 2 was 75% sensitive and 85% specific in predicting the need for massive transfusion [14]. MTP-based administration of blood products had a noncompliance rate of 47%. Since there is no consensus even among our own staff about the best way to administer blood products (e.g. ratio-based vs lab-based), this was left to the discretion of the attending physician. We assumed non-compliance if the patient had an elevated INR >1.5 and FFP was not given, platelets less than
Table 5 Comparison of compliance by mortality. Protocol criteria
Non-survivors N = 34 (% compliance)
Survivors N = 38 (% compliance)
P value
Was MTP activation based on the pre-specified indications? Timely communication with blood bank (3
B 0.094 3.789 0.024 0.047 3.673 0.771
SE
OR
95% CI
P value
0.740 1.853 0.016 0.024 1.201 0.776
1.099 0.023 1.024 1.049 0.025 2.161
0.258–4.687
Contents lists available at ScienceDirect
Injury journal homepage: www.elsevier.com/locate/injury
Compliance with a massive transfusion protocol (MTP) impacts patient outcome§ Bawazeer M.*, Ahmed N.1, Izadi H.2, McFarlan A.3, Nathens A.4, Pavenski K.5 Trauma Program and Transfusion Medicine, Departments of Surgery and Laboratory Medicine, St. Michael’s Hospital, University of Toronto, Canada
A R T I C L E I N F O
A B S T R A C T
Article history: Accepted 25 September 2014
Background: About 5% of civilian trauma requires massive transfusion. Protocolized resuscitation with blood products to achieve high plasma:RBC ratio has been advocated to improve survival. Our objectives were to measure compliance to our institutional MTP, to identify quality assurance activities that could improve protocol compliance and to determine if protocol compliance was related to patient outcome. Methods: The investigators determined 13 compliance criteria based upon our institutional protocol. We measured compliance in 72 consecutive MTP activations between January 2010 and September 2011 at a Level I trauma centre. Data elements were retrospectively retrieved from blood bank, trauma registry and clinical records. Patients were stratified into three groups based on compliance level, and mortality differences were compared. Results: Average compliance for the cohort (n = 72) was 66%. The most common cause of noncompliance was failure to send a complete haemorrhage panel from the trauma bay (96%). Failure to monitoring blood work every 30 min occurred in 89% of cases. Delay in activation and deactivation occurred in 50% and 50% respectively. Non-compliance to protocol-based administration of blood products happened in 47%. The cohort was stratified into three groups based on compliance, A: 80% (low, moderate and high compliance groups). There was no statistical significance with regard to median age, median ISS, ED SBP, ED GCS and AIS of the head/spine, chest and abdomen. The mortality rates in each group were 62%, 50% and 10% in the low, moderate and high compliance groups respectively. Mortality differences were compared using adjusted logistic regression. The OR for mortality between Groups A and B = 1.1 [95% CI 0.258–4.687 (P = 0.899)] while the OR for mortality between Groups C and B = 0.02 [95% CI 3 in head/spine AIS, chest AIS and abdomen AIS respectively. Slightly greater than half (53%) of the cohort survived and was discharged from the hospital. Table 2 summarizes the compliance criteria and the level of compliance for each criterion. The most common cause of noncompliance was failure to send a complete haemorrhage panel from the trauma bay (96%) and the most commonly missing element was fibrinogen. A full panel was missed in 6% of cases. According to the protocol, laboratory investigations (ABG, electrolytes, CBC, INR and fibrinogen) should be done every 30 min. Only
Age Gender Female Males ISS (minimum–maximum) Mechanism Penetrating Blunt Head AIS 3 >3 Chest AIS 3 >3 Abdomen AIS 3 >3 Survival Alive Dead
N = 72 (%)
Median
16–88
47.5
16 (22%) 56 (78%) 4–75 19 (26%) 53 (74%) 45 (63%) 27 (37%) 32 (44%) 40 (56%) 56 (78%) 16 (22%) 38 (53%) 34 (47%)
34
Quartile range 59.5–30.5
50–25.0
M. Bawazeer et al. / Injury, Int. J. Care Injured 46 (2015) 21–28
24
Table 2 Compliance criteria and the level of compliance in each. Protocol criteria
% Compliance
Comments
1
Was MTP activation based on the pre-specified indications?
82
2 3 4
Timely communication with Blood Bank ( 15 min From trauma bay CBC, INR, FN; FN missing in 96% 6% missed the full panel 6:4:1; RBC:FP:Plat + early cryoprecipitate Active re-warming within 2 h of ICU arrival This was not accounted for in early deaths HCO3 infusion within 2 h of ICU arrival This was not accounted for in early deaths Given in 6% of cases (N = 4), one case (25%) was not given according to the protocol Q30 min This was not accounted for in early deaths Wastage occurred in 6% of cases Within 1 h of last blood product given Within 2 h of MTP activation This was not accounted for in early deaths Within 2 h of MTP activation This was not accounted for in early deaths
Average compliance
66
MTP = massive transfusion protocol, CBC = complete blood count, INR = international normalized ratio, FN = fibrinogen, RBC = red blood cells, FP = frozen plasma, Plat = platelets, rFVIIa = recombinant Factor VIIa, ABG = arterial blood gas, Lytes = serum electrolytes, K = potassium, Ca = calcium.
11% of cases were compliant with this criterion. Timely activation of the MTP (within 15 min of patient arrival) occurred in 50% and timely deactivation of the MTP (within 1 h from the last blood product issued) occurred in 50%. Delay in activation and deactivation occurred in 50% and 50% respectively. 53% of patients had per-protocol administration of blood products, while 47% did not (based on high INR, low platelets and low fibrinogen which were not corrected). Recombinant factor VIIa is recommended for refractory bleeding following attempt of surgical haemostasis as well as correction of coagulopathy and thrombocytopaenia. Recombinant factor VIIs was administered in four cases (6%), and in three cases it was administered according to protocol. This protocol was an older version of our institutional MTP, which is revised every 2 years. Of the four cases who received rFVIIa, two were in the moderate compliance group with compliance rate of 77% and 62% respectively. The other two patients were in the high compliance group with a compliance rate of 85% in both patients. In one patient only in the high compliance group, it was administered before correction of coagulopathy, that is FFP and platelets were administered after rFVIIa. Potassium and calcium monitoring and correction occurred in 71% and 58% respectively. Active measures to correct hypothermia and acidosis occurred in 68% and 83% respectively. In 82% of cases, MTP was activated according to the pre-specified indications, while in 18% MTP was neither required nor indicated. In 93% of cases, compatibility testing (blood group and screen and cross match) was sent upon MTP activation from the trauma bay. Wastage of blood products was prevented in 94%. The overall compliance in this cohort was 66%. The cohort was then stratified into three groups based on compliance, 80% (low, moderate and high compliance groups). The summary of the characteristics of the groups is in Table 3. There were no statistical differences between the three groups’ demographics. Group A had higher ISS than Groups B and C but P value was not significant. With regard to blood products administration, Group C received slightly higher rates of RBC, FFP and platelets, but without statistical significance. Group C had also longer ICU and Hospital LOS but not statistically significant. The average mortality rates in each group were 62%,
50% and 10% (low, moderate and high compliance groups respectively). We also compared survivors to non-survivors. Table 4 summarizes demographics of the two groups. Non-survivors had a higher ISS, more patients with ED GCS 3 with P values of 0.005, 0.004 and 0.005 respectively. Median age, ED SBP and AIS of the chest and abdomen were not different between survivors and non-survivors. Compliance criteria were also compared between survivors and nonsurvivors. The summary of the comparison is provided in Table 5. We found that amongst survivors there was higher compliance with sending blood group and cross match and correction of hypothermia with P values 0.04 and 0.05 respectively. The rest of the compliance measures were not statistically significant between survivors and non-survivors. Average compliance amongst survivors was 70% while in non-survivors was 62% [P = 0.002]. In an effort to decrease the risk of bias, we used first an unadjusted logistic regression model to compare between Groups A, B and C. Group B was used as the reference group because it represented the average compliance rate of the whole cohort. The OR for mortality between Groups A and B = 1.67, [95% CI 0.520– 5.346 (P = 0.390)] while the OR for mortality between Groups C and B = 0.11 [95% CI 0.013–0.949 (P = 0.045)]. In another effort to further decrease the risk of bias, an adjusted logistic regression model was created to compare between mortality differences. Because of the small sample size, it was not possible to fit a model with many predictors. We selected only factors that were most associated with mortality based on Table 5, namely age, ISS, ED GCS and AIS head/spine. Table 6 describes the model. The OR for mortality between Groups A and B = 1.1 [95% CI 0.258–4.687 (P = 0.899)] while the OR for mortality between Groups C and B = 0.02 [95% CI 90 4 3 Chest AIS 3 >3 Abdomen AIS 3 >3 RBC administered (min–max units)
42 (17–82) (n = 13) 81% (n = 3) 19%
51 (16–88) (n = 35) 76% (n = 11) 24%
39 (16–62) (n = 10) 100% (n = 0) 0%
0.334a 0.282b
(n = 5) 31% (n = 11) 69% 4–66 42
(n = 11) 24% (n = 35) 76% 9–75 38
(n = 0) 0% (n = 10) 100% 9–66 26
0.166b
(n = 14) 88% (n = 2) 12%
(n = 34) 74% (n = 12) 26%
(n = 5) 50% (n = 5) 50%
0.124b
(n = 9) 56% (n = 7) 44%
(n = 18) 39% (n = 28) 61%
(n = 3) 30% (n = 7) 70%
0.392b
(n = 12) 75% (n = 4) 25%
(n = 38) 83% (n = 8) 17%
(n = 8) 80% (n = 2) 20%
0.757b
(n = 8) 50% (n = 8) 50%
(n = 29) 63% (n = 17) 37%
(n = 8) 80% (n = 2) 20%
0.304c
(n = 7) 44% (n = 9) 56%
(n = 22) 48% (n = 24) 52%
(n = 3) 30% (n = 7) 70%
0.588c
(n = 10) 63% (n = 6) 37% 0–30 Total 156 12 units 0–15 Total 58 4 units 0–6 Total 15 1 pool 1–73 1 day 0–53 1 day
(n = 37) 80% (n = 9) 20% 2–40 Total 648 12 units 0–21 Total 228 4 units 0–4 Total 49 1 pool 1–75 8 days 0–51 3 days
(n = 9) 90% (n = 1) 10% 0–74 Total 228 14 units 0–34 Total 119 8 units 0–17 Total 38 2 pools 1–70 17 days 0–40 7 days
0.240b
(n = 10) 62% (n = 6) 38%
(n = 23) 50% (n = 23) 50%
(n = 1) 10% (n = 9) 90%
Median FFP administered (min–max, units) Median Platelets administered (min–max, pool of platelets) Median Length of stay (LOS) (min–max) Median ICU days (min–max) Median Outcome Dead Alive
0.182a
0.902a
0.564a
0.542a
0.279a 0.623a
0.024c
ISS = injury severity score, ED SBP = Emergency Department systolic blood pressure, ED GCS = Emergency Department Glasgow coma score, AIS = abbreviated injury score, 1 pool of platelets = 5 units of platelet-rich plasma. a Kruskal–Wallis test. b Fisher’s exact test. c Chi-square test.
them was in Group A (compliance rate 50%) and the other one was in Group B (compliance rate 75%). There was only one patient in Group A required resuscitative thoracotomy and died in the trauma bay (compliance rate was 50%). There were three patients required resuscitative thoracotomy and survived to the operating room but died there. Two of them were in Group B with compliance rates of 62% and 75%. The last one was in Group C with a compliance rate of 87%. Those activations missed some system factors like delay in activation and deactivation, missing cross match and haemorrhage panel upon admission and blood products administration was inappropriate. Discussion The principles of trauma quality improvement include identification; intervention and measurement of pre-defined standards of care [12]. Retrospective reviews are only one way to identify factors that may compromise patient care and ‘‘to see how we are doing’’. After identification of factors, which are provider-, systemor patient-related, appropriate quality assurance measures can be applied to improve standards of care [1]. The goals of the current study were to assess compliance with our institutional MTP 3 years
after its implementation and to identify quality indicators that can be regularly tracked. We also wanted to see if compliance with MTP impacted patient outcomes. We found that the mean compliance rate was 66%. In his study, Cotton et al. reported initial 27% full compliance (all 7 criteria were met), 73% had one violation and 46% had more than one violation. This was subsequently improved to more than 80% following appropriate interventions, except in one measure (early activation of the MTP) [1]. The lowest level of compliance in our study was 25% in one patient who made palliative and died early. The causes of non-compliance were failure to send a complete haemorrhage panel, delay in activation and deactivation, blood product administration was inappropriate and there was some product wastage. Of interest, the highest level of compliance was 87% (7 criteria met out of 8) in one patient. This patient had an ED thoracotomy and survived to the operating room but died there. The only criterion which was not met was failure to send a complete haemorrhage panel. In no patients had full compliance with all 13 criteria were seen. In our study, the most common non-compliance criterion was failure to send a complete haemorrhage panel from the ED in 96%, and fibrinogen was the most commonly missing element. In 6%
M. Bawazeer et al. / Injury, Int. J. Care Injured 46 (2015) 21–28
26 Table 4 Comparison of demographics by mortality. Demographics
Non-survivors N = 34 (%)
Survivors N = 38 (%)
P value
Median age (minimum–maximum) Gender Female Male Median ISS (minimum–maximum) Mechanism of injury Blunt Penetrating ED SBP >90 3 AIS abdomen 3 >3
51 (16–88)
45 (16–83)
0.142a
8 (24%) 26 (76%) 44 (9–75)
8 (21%) 30 (79%) 29 (4–66)
1.00b
28 (82%) 6 (18%)
25 (66%) 13 (34%)
0.186b
12 (35%) 22 (65%)
18 (47%) 20 (53%)
0.425b
22 (65%) 12 (35%)
36 (95%) 2 (5%)
0.004b
15 (44%) 19 (56%)
30 (79%) 8 (21%)
0.005b
12 (35%) 22 (65%)
20 (53%) 18 (47%)
0.215b
26 (76%) 8 (24%)
30 (79%) 8 (21%)
1.00b
0.005a
ISS = injury severity score, ED SBP = Emergency Department systolic blood pressure, ED GCS = Emergency Department Glasgow coma score, AIS = abbreviated injury score. Bold values indicate significant p values a Wilcoxon two-sample test. b Continuity-adjusted chi square test.
(4 cases) a complete haemorrhage panel was missing. All of those four cases were haemodynamically unstable and none of those patients survived. In these critically ill patients, laboratory-based approach may not be appropriate and management should be based on empiric protocol including ratio-based resuscitation. It is not very clear whether this particular criterion can affect patient outcome, but knowledge of the patient’s coagulations system would be very useful to guide ongoing therapy, i.e. delay in measuring fibrinogen might delay administration of cryoprecipitate. Point-of-care coagulation testing (e.g. TEG or ROTEM) may also play a role by allowing to specifically tailor haemotherapy and is likely to eventually replace the need for conventional coagulation testing [13]. A study of 1974 patients, TEG was shown to be
clinically superior to conventional coagulation studies with similar costs [13]. The second most common non-compliance criterion was failure to regularly order laboratory investigations. This occurred in 89% of cases. Possible factors contributing to this high rate of noncompliance were on-going patient instability; in the operating room or the ICU; and possibly lack of knowledge and/or appreciation of the importance of ongoing monitoring. As an academic teaching centre, and with frequently changing housestaff of fellows and residents, this aspect will require aggressive provider education and academic detailing. As well consideration may be given to displaying the MTP flowchart in poster format in the ED or ICU, or development of MTP pocket cards or apps to be used as reminders. Development of pre-printed ICU orders with check boxes to facilitate rapid ordering of the required blood tests may also be helpful. The third and fourth most common non-compliance criteria were delay in activation (50%) and delay in deactivation (50%) of MTP. Cotton et al. [1] reported that failure to activate MTP in ED was the second most common cause of non-compliance in their study (44%). In his study, this criterion failed to improve throughout the study period even after aggressive educational efforts. They also reported that the presence of a clinical instructor was more likely to be associated with appropriate termination of the MTP than a senior faculty. In our study, factors that might have contributed to delay in activation and deactivation were likely related to provider-related education and awareness of the MTPs. Patient-related factors could include rapidly changing clinical status of a patient such as those who come initially stable and become precipitously unstable. Provider-related factors can be improved by re-education and implementation of a scoring system that can be integrated into the current MTP. An easy scoring system was recommended by Cotton et al. This system uses dichotomous variables that require only a ‘‘Yes’’ or ‘‘No’’ answer: a penetrating mechanism, systolic BP 120 BPM and a positive FAST. A score 2 was 75% sensitive and 85% specific in predicting the need for massive transfusion [14]. MTP-based administration of blood products had a noncompliance rate of 47%. Since there is no consensus even among our own staff about the best way to administer blood products (e.g. ratio-based vs lab-based), this was left to the discretion of the attending physician. We assumed non-compliance if the patient had an elevated INR >1.5 and FFP was not given, platelets less than
Table 5 Comparison of compliance by mortality. Protocol criteria
Non-survivors N = 34 (% compliance)
Survivors N = 38 (% compliance)
P value
Was MTP activation based on the pre-specified indications? Timely communication with blood bank (3
B 0.094 3.789 0.024 0.047 3.673 0.771
SE
OR
95% CI
P value
0.740 1.853 0.016 0.024 1.201 0.776
1.099 0.023 1.024 1.049 0.025 2.161
0.258–4.687
