Abstract
Background
We sought to determine the impact of the presence of a pharmacist on medication and patient related outcomes during the emergency management of critically ill patients requiring resuscitation or medical emergency response team care in a hospital setting .
Methods
We conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A literature search of databases from January 1995 to April 2023 was conducted to identify studies of contemporary pharmacist practice. Results were extracted and analysed for included studies, those evaluating the impact of the presence of a pharmacist on medication and patient related outcomes during the emergency management of critically ill hospitalised patients requiring resuscitation or medical emergency response team care. To determine risk of bias, the Newcastle-Ottowa Quality Assessment scale was used for non-randomised studies and the Revised Cochrane risk-of-bias tool for randomised trials.
Results
Of 1345 studies identified, 54 were selected for full text review, and 30 were included in the final analysis. There were 29 cohort studies and one randomised controlled trial. The studies reported the impact of a pharmacist for a variety of patient presentations. The study team assigned each study to one of eight patient cohorts: acute stroke, cardiac arrest, rapid response calls, S-T segment elevation myocardial infarction, acute haemorrhage, major trauma resuscitation, sepsis and status epilepticus. The most frequently reported outcome, associated with a statistically significant benefit in 23 studies, was time to medication administration. Few studies reported a significant difference in patient outcome measures such as mortality. Only 8 of the 30 studies were assessed to have a low risk of bias.
Conclusions
The results of this systematic review provide support for a beneficial impact of a pharmacist presence and intervention during resuscitation or medical emergency response team care, with significant improvements in outcomes such as time to initiation of time-critical medications, medication appropriateness and guideline compliance. However, studies were predominantly small and retrospective and were not powered to detect differences in patient related measures such as length of stay and mortality. Future research should investigate the clinical impacts of the pharmacist in ED resuscitation settings in controlled, prospective studies with robust sampling methods.
1
Introduction
Medication safety in the acute care setting represents a significant challenge [ ]. It has been estimated that medication errors occur in 5% of all drug administrations [ ] and preventable adverse drug events occur in 1.6% of hospitalised patients [ ]. Medication errors are common in emergency departments (ED). A study of 192 patients in a United States (US) ED found that 59.4% of ED patients had one or more medication error and 37% had one or more medication errors that were not intercepted before administration [ ].
The reasons for medication errors are multifactorial. Emergency clinicians work in overcrowded, time-pressured environments in which the risk of medication error is high [ ]. Overcrowding in EDs has been recognised as a widespread problem in many countries [ ] and has been shown to increase the risk of medication errors and delays in the administration of time critical medications [ , ]. In the ED, the use of verbal medication orders is common and multitasking is needed to manage workload. These strategies have been associated with an increased risk of prescribing and administration errors and can lead to patient harm [ ]. Within this hazardous environment, emergency physicians and nurses often need to quickly prescribe and administer high-risk or time-critical medications to critically ill patients, with errors involving high-risk medications are more likely to result in significant patient harm [ , ].
In-hospital, medical emergencies and resuscitation events also occur outside of the ED. High-risk medications are used by medical emergency teams to manage patients and the potential for medication error in this setting is extremely high [ , ]. Similar to the ED resuscitation setting, in-hospital medical emergencies, are fast-paced, requiring quick decision making, use of verbal orders and rapid administration of medications [ ]. A prospective, observational evaluation of 50 medical emergency responses found that one out of two doses of medications given during these events were administered with an error [ ]. The results of studies of pharmacists participating in medical emergency or rapid response teams are relevant to an investigation of pharmacists’ impact on medication and patient related outcomes when working as part of ED resuscitation teams because the patient acuity managed, medications used and clinician time pressures are similar. We included studies in inpatient resuscitation and medical emergency response settings as part of this investigation to ascertain if there are studies with demonstrable pharmacist-led impacts on outcomes which may provide learning for EM pharmacy practice in the ED resuscitation setting.
Involvement in resuscitation has been identified as an emerging area of practice for EM pharmacists and is currently considered standard of care by pharmacy practice standards in the US [ ]. A 2016 US survey revealed that 98% of EM pharmacists participated in resuscitation responses, commonly performing “emergency response” activities which were defined as responding to medical emergencies such as cardiopulmonary arrest, trauma resuscitation, myocardial infarction and stroke [ ]. In Canada surveys reveal that between 61 and 77% of pharmacist respondents perform trauma or resuscitation care [ , ]. In Australia in 2016, 9 out of 35 hospitals (27%) had EM pharmacists directly involved in the care of patients requiring resuscitation [ ]. The role of the pharmacist during in-hospital resuscitation or medical emergency response teams has also been described [ ]. A large population study found that hospitals with clinical pharmacist participation on the cardiopulmonary resuscitation team had associated reduced overall mortality rates [ ]. However, the effectiveness and benefits of pharmacists on medication and patient related outcomes while practicing within a medical emergency or ED resuscitation team have not been fully identified or described.
The objective of this systematic review was to identify and critically appraise studies evaluating the impact of the presence of a pharmacist on medication and patient related outcomes during the emergency management of critically ill patients requiring resuscitation or medical emergency response team care in a hospital setting.
2
Methods
2.1
Study design and search strategy
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was used. A protocol was registered with the International Prospective Register of Systematic Reviews prior to study initiation (PROSPERO2021 CRD42021285683 https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021285683 ).
A search of the following databases was conducted from 1 January 1995 to 8 September 2022 and updated on 15 April 2023; PubMed, Embase, International Pharmaceutical Abstracts, The Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, and Cochrane Database of Systematic Reviews. We hand searched references of included studies and relevant review articles. A grey literature search of Google Scholar was performed on 8 September 2022. The search strategy was designed by the principal investigator (EC) with input from an experienced librarian and members of the research team (NF and MB). It included terms related to pharmacists and the management of acute critical events. We limited the database search from 1995 onwards to reflect contemporary clinical pharmacy practice and standards of modern healthcare systems.
2.2
Eligibility criteria
English language, peer reviewed, primary studies of patients requiring resuscitation or emergency management of an acute critical illness in a hospital setting were eligible. We excluded abstract-only studies, case reports, narrative or systematic reviews, and guidelines. We used a patients-intervention-comparison-outcomes format to determine the eligibility of studies for inclusion:
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Patient population: Studies of critically ill patients requiring resuscitation or medical emergency response team care in hospital
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Intervention: Pharmacist impact as part of a resuscitation or medical emergency response team, on patient or medication related outcomes
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Comparison: Concurrent or historical controls who received resuscitation or medical emergency response team care when a pharmacist was not present
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Outcomes: (1) Patient related: length of stay (LOS) in hospital, intensive care unit (ICU) or ED, hospital readmission, mortality, discharge disposition; (2) Process outcomes: adherence to evidence-based practice or guidelines; (3) Medication related outcomes: time from ED arrival to medication administration, appropriateness of medication, medication error, medication harm; (4) Reported cost savings due to reduced drug costs
Medication error was defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer” [ ].
2.3
Study selection
All identified studies were imported into Covidence® systematic review software [ ]. Two investigators (EC and NF) independently performed a title and abstract review to assess relevance and select studies for full text review. Any conflicts were resolved by a consensus discussion involving a third reviewer [ ].
2.4
Data collection and processing
Publications selected for full text review were independently assessed for inclusion by two members of the research team (EC and NF or MB). A checklist was developed with input from the research team to identify data items, key outcomes and to identify patient cohorts. All outcome results were collected. Data was extracted from the included studies by EC and confirmed by a second reviewer (NF or MB). Discrepancies were resolved by discussion within the team. Data from the reviewed studies were entered into a predesigned Microsoft Excel® spreadsheet created by EC. The following study characteristics were collected: country of origin, study setting, study design, patient population and level of evidence as per the Australian National Health and Medical Research Council classification system [ ]. Each study was assigned to one of 8 patient cohorts to cohesively describe the range of patient presentations, group similar studies, and summarise in a table.
2.5
Risk of bias and quality assessment
To determine risk of bias (RoB) the Newcastle-Ottowa Quality Assessment scale (NOS) [ ] was used for non-randomised studies and the Revised Cochrane risk-of-bias tool for randomised trials (RoB 2) [ ]. In addition, five Quality Assessment criteria that weren’t addressed by the NOS tool were used to describe the presence or absence of robust study methods, as performed in the systematic review by Roman et al. [ ] Specifically, the criteria assessed whether the study methodology included double data extraction, explicit record review, blinded assessmentand power calculation. Retrospective cohort studies were also assessed for the presence of a statistical adjustment approach to address potential confounding. The formal quality assessment of all included studies was conducted independently by two reviewers and any disagreement was resolved by consensus during research team discussions.
3
Results
3.1
Study selection
After removal of duplicates, 1500 studies were identified. Following abstract and title screening, 54 studies were identified for full text review. Of these, 30 studies met the inclusion criteria and were included in the review. Fig. 1 depicts the PRISMA flow diagram.
3.2
Study characteristics and patient populations
The characteristics of each study including study setting, duration and design, level of evidence, patient cohort, population and intervention and control group descriptions from the 30 included studies are summarised in Table 1 . Of these, 29 were retrospective cohort studies, [ , ] including eight before and after study designs [ , , , , , , ]. All but three studies, set in Japan and Australia [ , ], were conducted in the US. There were 25 studies set in the ED [ , , , , , , ] and five studies [ , , , , , ] which included inpatient settings. There was only one randomised controlled trial (RCT) [ ], with the other non-randomised studies using a variety of methods to determine intervention and comparator groups. In 14 studies [ , , , , , , , , , , , ] the intervention group was determined by the pharmacists’ usual working hours and a corresponding comparator group was selected outside of pharmacist working hours. The patient populations across studies varied widely. The impact of a pharmacist on acute stroke management was investigated in 8 studies [ , , , , , , , ] and on the management of haemorrhage requiring anticoagulant reversal in 5 studies [ , , , , ]. Other patient cohorts included cardiac arrest [ , , ] and rapid response teams [ ] in 4 studies and STEMI management in one [ ]. There were 8 studies [ , , , , , , , ] that investigated the involvement of EM pharmacists in major trauma and resuscitation response, 3 studies [ , , ] in the management of sepsis and 1 in status epilepticus [ ].
| Author, Year Published | Country/Setting Study duration | Study design (level of evidence) a | Patient population ( n ) | Intervention group ( n ) | Control group ( n ) |
|---|---|---|---|---|---|
| Barbour 2022 [ ] | US / ED August 2016–May 2020 | Cohort study III-2 | Adults presenting to the ED who received IV alteplase for AIS ( n = 164) | Pharmacist present at the bedside during acute stroke management ( n = 31) | Pharmacist not present (outside stroke alert hours) ( n = 133) |
| Gilbert 2019 [ ] | US / ED Nov 2017–May 2018, May–Oct 2017 | Historical Control study III-3 | Adults who received rTPA for AIS in the ED ( n = 65) | Pharmacist present during acute stroke management ( n = 33) | Pharmacist not present (historical control) ( n = 32) |
| Gosser 2016 [ ] | US / ED Jan 2008–Oct 2012 | Cohort study III-2 | Adults who received IV rTPA for AIS in the ED ( n = 105) | Pharmacist present during acute stroke management ( n = 67) | Pharmacist not present during stroke alert ( n = 38) |
| Jacoby 2018 [ ] | US / ED Aug 2012–Aug 201 | Cohort study III-2 | Adults who received rTPA for AIS in the ED ( n = 100) | Pharmacist present during acute stroke management ( n = 49) | Pharmacist not present during response ( n = 51) |
| McSwain 2022 [ ] | US / ED Jan 2014–Dec 2018 | Cohort study III-2 | Adults who received IV alteplase for AIS ( n = 159) | Pharmacist present during acute stroke management ( n = 40) | Pharmacist not present during stroke team activation ( n = 119) |
| Montgomery 2016 [ ] | US / ED Jan 2012–Sept 2014 | Cohort study III-2 | Adults presenting to ED who received thrombolytics ( n = 97) | Pharmacist present during acute stroke management ( n = 38) | Pharmacist absent during stroke alert response ( n = 59) |
| Rech 2017 [ ] | US / ED and inpatients Jan 2012–Dec 2015 | Cohort study III-2 | Adults with acute ischemic stroke in ED or as an inpatient who received alteplase ( n = 125) | Stroke competent pharmacist present during acute stroke management ( n = 45) | Pharmacist not present ( n = 80) |
| Roman 2021 [ ] | Aus / ED Dec 2011 to Jun 2014, Jul 2014–Dec 2019 | Historical control study III-3 | Adults with AIS who received thrombolysis in ED within pharmacist working hours ( n = 186) | Post implementation of addition of a pharmacist to the acute stroke team ( n = 122) | Pre-implementation of addition of pharmacist to the acute stroke team ( n = 64) |
| Draper 2008 [ ] | US / inpatients Jan 2003–Jun 2004 | Cohort study III-2 | Adults with cardiopulmonary arrest while an inpatient ( n = 74) | Presence of pharmacist on the CPR team ( n = 27) | Pharmacist not present during CPR ( n = 47) |
| Heavner 2017 [ ] | US / inpatients Jan 2012–Dec 2013 | Historical control study III-3 | All cardiac arrest events ( n = 80) | Integrated pharmacist on the cardiac arrest team ( n = 54) | Pre-implementation of pharmacist on cardiac arrest team ( n = 26) |
| McAllister 2017 [ ] | US / ED Aug 2012–Jan 2013 | Cohort study III-2 | Adults who had a cardiac arrest in the ED ( n = 65) | Pharmacist present during resuscitation attempt ( n = 20) | Pharmacist not present for resuscitation ( n = 45) |
| Acquisto 2012 [ ] | US / ED Aug 2005–Aug 2006 | Cohort study III-2 | STEMI presenting to ED, requiring urgent cardiac catheterisation ( n = 120) | Pharmacist present during STEMI management (working hours) ( n = 68) | Pharmacist not present (outside working hours) ( n = 52) |
| Feih 2017 [ ] | US / inpatients Aug–Oct 2012 Mar–May 2013 | Historical control study III-3 | Adult inpatients who experienced an RRT event ( n = 391) | Pharmacist involvement on the RRT ( n = 157) | Pre-implementation of pharmacist role ( n = 234) |
| Alarfaj 2018 [ ] | US / ED March 2014–Oct 2015 | Cohort study III-2 | Adults in ED with bleeding. Subgroup of patients who received PCC ( n = 60) | Pharmacist present during working hours ( n = NR) | Pharmacist not present (outside working hours) ( n = NR) |
| Corio 2018 [ ] | US / ED Sept 2015–Feb 2017 | Historical control study III-3 | Adults with confirmed ICH, documented warfarin use and INR>/= 2 ( n = 48) | Pharmacist driven warfarin reversal protocol ( n = 24) | Pre-implementation of pharmacist driven protocol ( n = 24) |
| Imanaka 2020 [ ] | Japan / ED ICU Dec 2017–May 2019 | Cohort study III-2 | Adults who received 4F-PCC due to major bleeding or urgent surgical/invasive procedures ( n = 10) | Emergency ICU pharmacist intervention on weekdays ( n = 5) | Emergency ICU pharmacist absent (on weekends) ( n = 5) |
| Kozlow 2021 [ ] | US / ED May 2014–June 2015. Nov 2018–Dec 2019 | Historical control study III-3 | Adults who received 4F-PCC in the ED for acute rapid reversal of oral anticoagulation due to bleeding ( n = 100) | Pharmacist presence at the bedside to assist with anticoagulant reversal ( n = 67) | Pharmacist not present (prior to 24 h EM pharmacist service) ( n = 33) |
| Masic 2019 [ ] | US / ED 2014–2018 | Cohort study III-2 | Adults who received 4F-PCC for life-threatening bleeding or urgent procedure in the ED ( n = 116) | Pharmacist presence at the bedside to assist with anticoagulant reversal ( n = 50) | Pharmacist not present ( n = 66) |
| Amini 2013 [ ] | US / ED July 2009–June 2011 | Cohort study III-2 | Adult trauma intubated using RSI and rocuronium in the ED ( n = 100) | Pharmacist present during intubation within working hours ( n = 30) | Pharmacist not present (outside working hours) ( n = 70) |
| Ernst 2012 [ ] | US /ED Jan–Apr 2009 | Historical control study III-3 | Adults presenting to the resuscitation and trauma areas ( n = 694) | Presence of a pharmacist during 10 h working day ( n = 242) | Pharmacist not present ( n = 452) |
| Harvey 2018 [ ] | US / ED May 2014–June 2016 | Cohort study III-2 | Adult trauma alert with fractures who presented to ED ( n = 146) | Pharmacist present during trauma response (when available within working hours) ( n = 67) | Pharmacist not present (after hours or not available) |
| Johnson 2015 [ ] | US / ED Oct 2009–Dec 2012 | Cohort study III-2 | Adults intubated in the ED who received rocuronium or succinylcholine ( n = 106) | Pharmacist present during intubation ( n = 72) | Pharmacist not present during intubation ( n = 34) |
| Lamkin 2019 [ ] | US / ED July 2014–December 2014 | Cohort study III-2 | Adults who presented to the critical care area of ED with trauma on weekdays ( n = 1082) | Pharmacist present during trauma response within working hours ( n = 782) | Pharmacist not present (outside working hours) ( n = 300) |
| Montgomery 2015 [ ] | US / ED Jan 2009–May 2013 | Cohort study III-2 | Adult trauma alert activations who received IV hydromorphone, fentanyl or morphine ( n = 340) | Pharmacist present during trauma team response ( n = 170) | Pharmacist not present during trauma team response ( n = 170) |
| Riley 2013 [ ] | US / ED Dec 2009–Nov 2010 | Cohort study III-2 | All priority 1 or 2 trauma alert patients in ED ( n = 538) | Pharmacist present during trauma response ( n = 167) | Pharmacist not present during trauma response ( n = 371) |
| Robey-Gavin 2016 [ ] | US / ED Jan-June 2010, Jan-June 2011 | Historical control study III-3 | Adults who had undergone RSI in the ED ( n = 82) | Post implementation pharmacist service and presence ( n = 41) | Pre-implementation of pharmacist service and presence ( n = 41) |
| Chanas 2019 [ ] | US / ICU Sept 2016–Mar 2017 | Cohort study III-2 | Septic shock in a surgical ICU ( n = 97) | Pharmacist response to alert and bedside attendance ( n = 58) | Pharmacist did not respond ( n = 39) |
| Roman [ ] 2023 | Aus / ED Pre: Jan 2015 to Feb 2016 Post: 8 Feb 2016 to Feb 2018 | Cohort study III-3 | Adults with sepsis or septic shock requiring transfer to ICU within pharmacist working hours ( n = 184) | Post implementation of pharmacist led sepsis alert response system ( n = 104) | Pre- implementation of sepsis alert response ( n = 80) |
| Tarabichi 2021 [ ] | US / ED Aug–Dec 2019 | Randomised controlled trial II | Adults for whom a sepsis flag triggered during their ED encounter ( n = 598) | Sepsis score triggered: 1) icon on ED patient tracking tool 2) message to EMR monitored by pharmacist ( n = 285) | Standard sepsis care ( n = 313) |
| Gawedzki 2022 [ ] | US / ED Jan 2018–July 2020 | Cohort study III-2 | Adults with status epilepticus in ED ( n = 20) | Pharmacist present during status epilepticus management ( n = 13) | Pharmacist not present ( n = 7) |
a As graded by the authors of this review according to the Australian National Health and Medical Research Council Designation of Levels of Evidence hierarchy, in which evidence is graded on 4 levels; AIS, acute ischemic stroke; Aus = Australia; CPR, cardiopulmonary resuscitation; ED, emergency department; EMR = electronic medical record; ICH, intracranial haemorrhage; ICU, intensive care unit; INR, international normalised ratio; IV, intravenous; NR, not reported; RSI, rapid sequence intubation; r-TPA = recombinant tissue plasminogen activator; RRT, rapid response team; STEMI, ST-segment elevation myocardial infarction; US, United States; 4F-PCC, four-factor prothrombin complex concentrate.
3.3
Outcomes
The results reported across the 30 studies are detailed in Table 2 . Twenty-five studies compared the difference in time to administration of time critical medications between the control and intervention groups, but there were a variety of other outcomes assessed, such as medication error and appropriateness and length of stay (LOS). As shown in Table 3 , the populations studied were grouped into 8 patient cohorts and the outcomes reported were divided into 8 categories. The table provides an overview of the key outcomes measured and whether the results were statistically significant for each category. Time to medication administration was commonly reported ( n = 25). The remaining study outcomes measured were: appropriate medication use or medication error ( n = 10); mortality ( n = 11), including in-hospital mortality, 90 day mortality and survival to admission or discharge; hospital or ICU LOS ( n = 9); guideline compliance ( n = 8); efficacy measures ( n = 6), which included 24 h or discharge National Institute of Health Stroke Scale (NIHSS) scores and change in pain score; adverse events ( n = 7); and other patient outcomes ( n = 7), which included admission to ICU, time on ventilator, discharge disposition to home, days alive and out of hospital, 90 day modified rankin scale (mRS) or NIHSS scores.
| Author, Year Published, Patient Cohort, Number (n) | Outcomes | Results (Intervention vs Control) | Method of statistical analysis | p -value, 95% CI (if presented) |
|---|---|---|---|---|
| Barbour 2022 [ ] Acute stroke n = 164 | P: Median alteplase DTN time, min (IQR) | 35 (29–44) vs 42 (34–55) | MWU test | p = 0.025 |
| S: Patients with DTN time ≤ 60 min, % | 93.6 vs 81.9, OR 3.19 | χ 2 test | p = 0.111, 0.71–14.3 | |
| S: Patients with DTN time ≤ 45 min, % | 80.7 vs 57.1, OR 3.13 | χ 2 test | p = 0.015, 1.20–8.12 | |
| S: Patients with DTN time ≤ 30 min, % | 35.5 vs 16.5, OR 2.78 | χ 2 test | p = 0.018, 1.17–6.60 | |
| S: Median NIHSS at 24 h, score (IQR) | 3 (1–9) vs 6 (2−11) | FE test | p = 0.087 | |
| S: Median NIHSS at discharge, score (IQR) | 2 (0–5) vs 4 (0.25–8.75) | FE test | p = 0.049 | |
| S: Median hospital LOS, days (IQR) | 3 (2–5) vs 4 (3–4) | MWU test | p = 0.063 | |
| Gilbert 2019 [ ] Acute stroke n = 65 | P: Patients with DTN time ≤ 60 min, n (%) | 26 (78.8) vs 17 (53.1), OR 3.3 | χ 2 test | p = 0.04, 1.1–9.6 |
| S: Median DTN time, min (range) | 47 (22–74) vs 60 (36–109) | WRS test | p = 0.001 | |
| S: Mean DTN time, min (range) | 49 (22–74) vs 63 (36–109) | WRS test | p = 0.003 | |
| Gosser 2016 [ ] Acute stroke n = 105 | P: Median DTN time, min (IQR) | 69.5 (59–87.5) vs 89.5 (70–104) | MWU test | p = 0.0027 |
| S: Patients with a DTN time ≤ 60 min, n (%) | 20 (29.9) vs 6 (15.8) | χ 2 test | p = 0.1087 | |
| S: Appropriate thrombolysis dose, % | 96.6 vs 95.6 | Student’s t- test | p = 0.8953 | |
| Jacoby 2018 [ ] Acute stroke n = 100 | P: Median DTN time, min (IQR) | 46 (34.5–67) vs 58 (45–79) | MWU test | p = 0.019 |
| S: Patients with a DTN time ≤ 45 min, n (%) | 24 (49) vs 13 (25), OR 2.81 | χ 2 test | p = 0.015, 1.21–6.52 | |
| S: Patients with a DTN time ≤ 60 min, n (%) | 35 (71) vs 31 (61), OR 1.61 | χ 2 test | p = 0.261, 0.70–3.72 | |
| S: Median NIHSS at 24 h, score (IQR) | 1 (0–4) vs 2 (1–9.25) | MWU test | p = 0.047 | |
| S: Median NIHSS at discharge, score (IQR) | 0 (0–4) vs 2 (0–6) | MWU test | p = 0.077 | |
| S: Median NIHSS at follow up, score (IQR) | 0 (0–2) vs 1 (0–5.5) | MWU test | p = 0.198 | |
| S: Symptomatic ICH, number of events | 3 vs 2 | FE test | p = 0.068 | |
| S: Hospital LOS, days (IQR) | 2.6 (1.8–3.9) vs 2.9 (2.0–4.0) | MWU test | p = 0.500 | |
| S: Patients discharged to home, n (%) | 30 (65) vs 26 (54) | FE test | p = 0.384 | |
| McSwain 2022 [ ] Acute stroke n = 159 | P: Mean DTN time, min (SD) | 66 (27) vs 78 (38) | Welch’s t-test | p = 0.038 |
| S: Patients with DTN time < 60 min, n (%) | 24 (60) vs 41 (34), OR 2.85 | FE test | p = 0.05, 1.37–5.96 | |
| S: Patients with DTN time < 45 min, n (%) | 7 (18) vs 24 (20), OR 0.83 | FE test | p = 0.71, 0.33–2.13 | |
| Montgomery 2016 [ ] Acute stroke n = 97 | P: Patients with DTN time < 60 min, n (%) | 27 (71) vs 23 (39) | χ 2 test | p = 0.002, 0.10–0.50 |
| S: Patients with DTN time < 45 min, n (%) | 16 (42) vs 11 (19) | χ 2 test | p = 0.012, 0.05–0.41 | |
| S: Mean DTN time, min (range) | 54 (21–160) vs 74 (28–187) | Student’s t- test | p = 0.004, 6.6–33.4 | |
| Rech 2017 [ ] Acute stroke n = 125 | P: Median DTN time, min (IQR) | 48 (36–65) vs 73 (58–97.5) | MWU test | p < 0.01 |
| S: Patients with DTN time ≤ 60 min, n (%) | 32 (71.1) vs 23 (28.8) | χ 2 test | p < 0.01 | |
| S: Patients with DTN time ≤ 45 min, n (%) | 20 (44.4) vs 7 (8.8) | χ 2 test | p < 0.01 | |
| S: Median door to imaging, min (IQR) | 16 (10−21) vs 16 (8–25) | MWU test | p = 0.85 | |
| S: Median imaging to needle time, min (IQR) | 28 (22–42.5) vs 55.5 (42–70.5) | MWU test | p < 0.01 | |
| S: ICU LOS, days (IQR) | 3 (2–9) vs 2 (2–4) days | MWU test | p = 0.06 | |
| S: Hospital LOS, days (IQR) | 6 (3−13) vs 4 (3–8) | MWU test | p = 0.09 | |
| S: Hospital mortality, n (%) | 5 (11.1) vs 9 (11.3) | χ 2 test | p = 0.98 | |
| S: 90 day mortality, n (%) | 10 (22.2) vs 12 (15) | χ 2 test | p = 0.32 | |
| S: Median discharge mRS, score (IQR) | 3 (0–5) vs 3 (1–4) | FE test | p = 0.85 | |
| S: Median 90 day mRS, score (IQR) | 2 (0–4) vs 2 (1–4) | FE test | p = 0.84 | |
| S: Discharge NIHSS, score (IQR) | 3 (0−11) vs 4 (0−10) | FE test | p = 0.71 | |
| S: Median 90 day NIHSS (IQR) | 0 (0–0) vs 5 (0–5) | FE test | p = 0.05 | |
| S: Patients with symptomatic haemorrhage, n (%) | 5 (11.1) vs 6 (7.6) | χ 2 test | p = 0.51 | |
| Roman 2021 [ ] Acute stroke n = 186 | P: Median DTN time, min (IQR) | 61 (47–80) vs 73 (52–111) | WRS test | p = 0.012 |
| S: Patients with DTN time of <60 min, n (%) | 59 (48.4) vs 22 (34.4) | OLSR | p = 0.068 | |
| S: Median time from CTB to rtPA, min (IQR) | 39 (28–56) vs 50.5 (30.5–79) | WRS test | p = 0.013 | |
| S: Median hospital LOS, days (IQR) | 4.2 (2.9–7.3) vs 6.6 (4.1–10.8) | WRS test | p = 0.003 | |
| S: Hospital mortality, n (%) | 24 (19.7) vs 12 (18.8) | OLSR | p = 0.97 | |
| S: Extracranial haemorrhage, n (%) | 5 (4.1) vs 7 (10.9) | OLSR | p = 0.07 | |
| S: Patients with ICH, n (%) | 17 (13.9) vs 7 (10.9) | OLSR | p = 0.40 | |
| Draper 2008 [ ] Cardiac arrest n = 74 | Arrests compliant with ACLS guidelines, % | 59.3 vs 31.9 | χ 2 test | p = 0.03 |
| Arrests with non-compliant medication interventions, n (%) | 15 (32.6) vs 31 (67.4) | NR a | NR a | |
| Heavner 2017 [ ] Cardiac arrest n = 80 | Arrest events with all documentation complete, % | 28 vs 0 | χ 2 test | p = 0.002 |
| Events compliant with ACLS guidelines, % | 31 vs 8 | χ 2 test | p = 0.024 | |
| Patients who survived the acute event, % | 59 vs 58 | χ 2 test | Not significant | |
| McAllister 2017 [ ] Cardiac arrest n = 65 | P: Medication compliance with ACLS guidelines, n (%) | 93 (78) vs 154 (67) | χ 2 test | p = 0.0255 |
| S: Guideline compliance: defibrillation, n (%) | 23 (68) vs 8 (47) | χ 2 test | p = 0.1557 | |
| S: Guideline compliance: composite measure, n (%) | 116 (76) vs 162 (65) | χ 2 test | p = 0.0268 | |
| S: Resuscitation events compliant with ACLS guidelines, n (%) | 9 (43) vs 14 (27) | χ 2 test | p = 0.2000 | |
| S: Survival to hospital admission, n (%) | 8 (25) vs 5 (17.8) | FE test | p = 0.0155 | |
| S: Survival to hospital discharge, n (%) | 2 (15) vs 3 (4.4) | FE test | p = 0.6392 | |
| Acquisto 2012 [ ] STEMI n = 120 | Change in mean time from arrival/diagnosis to CCL, min | −13.1 | MV OLSR | p = 0.0324, 6.5–21.9 |
| Change in mean time from arrival/diagnosis to angioplasty, min | −11.5 | MV OLSR | p = 0.0487, 3.9–21.5 | |
| Arrival/ diagnosis to CCL of ≤30 min with pharmacist present | OR = 3.1 | MV OLSR | 1.3–7.8 | |
| Arrival/diagnosis to CCL time ≤ 45 min with pharmacist present | OR = 2.9 | MV OLSR | 1.0–8.5 | |
| Arrival/diagnosis to angioplasty ≤90 min when pharmacist present | OR = 1.9 | MV OLSR | 0.7–5.5 | |
| Feih 2017 [ ] Rapid response team n = 391 | P: Median time from order entry to administration, min | 32.0 vs 64.5 | WRS test | p = 0.004 |
| P: Patients administered medication within 30 min, % | 53.8 vs 22.2 | χ 2 test | p = 0.015 | |
| S: Patients admitted to ICU | NR a | χ 2 test | Not significant b | |
| S: ICU readmission <48 h of discharge | NR a | χ 2 test | Not significant b | |
| S: Hospital LOS | NR a | WRS test | Not significant b | |
| S: Survival to discharge | NR a | χ 2 test | Not significant b | |
| Alarfaj 2018 [ ] Haemorrhage n = 60 | Median time from order to PCC administration, min (IQR) | 24 (15–35) vs 42 (32–59) | WRS test | p < 0.001 |
| Corio 2018 [ ] Haemorrhage n = 48 | P: Median diagnosis to 4F-PCC administration time, min (IQR) | 35 (25–62) vs 70 (34–89) | MWU | p = 0.034 |
| S: Patients with appropriate dose of 4F-PCC, n (%) | 23 (95.8) vs 20 (83.3) | FE test | p = 0.174 | |
| S: Patients administered concomitant vitamin K, n (%) | 24 (100) vs 22 (91.7) | FE test | p = 0.244 | |
| S: In-hospital mortality, n (%) | 7 (29.2) vs 7 (29.2) | FE test | p = 1 | |
| Imanaka 2020 [ ] Haemorrhage n = 10 | Median ICU arrival to 4F-PCC administration time, min (range) | 103 (41–144) vs 111 (70–203) | MWU | p = 0.4 |
| Median 4F-PCC prescription to administration time, min (range) | 21 (5–39) vs 60 (33–157) | MWU | p = 0.02 | |
| Kozlow 2021 [ ] Haemorrhage n = 100 | P: Mean order entry to administration of 4F-PCC time, min (SD) | 35.2 (14.4) vs 71.2 (31.0) | MWU | p < 0.001, 27.0–45.0 |
| S: Median ED arrival to administration of 4F-PCC time, min (IQR) | 106 (66–142) vs 153 (89–205) | MWU | p = 0.033 | |
| S: Hospital LOS, days (IQR) | 4.1 (2.8–5.8) vs 6.9 (3.6–9.8) | MWU | p = 0.017 | |
| S: ICU admission, n (%) | 10 (30.3) vs 43 (64.2) | χ 2 test | p = 0.003 | |
| S: ICU LOS, days (IQR) | 1.6 (0.83–3.4) vs 2.2 (0.79–2.9) | MWU | p = 0.75 | |
| S: Admission mortality, n (%) | 4 (12.1) vs 10 (14.9) | χ 2 test | p = 1.0 | |
| Masic 2019 [ ] Haemorrhage n = 116 | P: Median ED arrival to 4F-PCC administration time, min (IQR) | 66.5 (37.5–95.5) vs 206.5 (88–325) | MWU | p < 0.01 |
| S: Achievement of haemostasis, n (%) | 29 (87.8) vs 38 (84.4) | χ 2 test | p = 0.67 | |
| S: Packed red blood cells within 24 h of 4F-PCC, mean (SD) | 0.11 (0.4) vs 0.06 (0.3) | χ 2 test | p = 0.53 | |
| S: Platelets <24 h of 4F-PCC, mean (SD) | 0.15 (0.5) vs 0.38 (0.7) | χ 2 test | p = 0.25 | |
| S: Fresh frozen plasma within 24 h of 4F-PCC, mean (SD) | 0.20 (0.6) vs 0.56 (1) | χ 2 test | p = 0.04 | |
| S: Patients given appropriate 4F-PCC dose, n (%) | 48 (96) vs 61 (92.4) | χ 2 test | p = 0.42 | |
| S: Safety outcomes | Multiple reported | χ 2 test | Not significant b | |
| S: Discharge disposition home, n (%) | 19 [38] vs 13 [19.7] | χ 2 test | p = 0.03 | |
| S: ICU LOS, days (IQR) | 2 (1–3) vs 5 (1–9) | MWU | p < 0.01 | |
| S: Hospital LOS, days (IQR) | 5.5 (2.5–8.5) vs 8 (2.5–13.5) | MWU | p = 0.02 | |
| S: 30-day mortality, n (%) | 11 [22] vs 14 [21.2] | χ 2 test | p = 0.55 | |
| Amini 2013 [ ] Major trauma resuscitation n = 100 | Mean time to postintubation sedation, min (SD) | 9 (± 12) vs 28 (± 29) | Student’s t- test | p < 0.007 |
| Mean time to postintubation analgesia, min (SD) | 21 (± 24) vs 44 (± 47) | Student’s t- test | p = 0.057 | |
| Ernst 2012 [ ] Major trauma resuscitation n = 694 | P: Total patients ( n = 694) with medication error, n (%) | 6 (2.5) vs 137 (30.3), OR 17.1 | χ 2 test | 7.4–39.4 |
| ICU admitted patients ( n = 157) with medication error, n (%) | 4 (7.7) vs 51 (48.6), OR 6.8 | χ 2 test | 3.7–12.7 | |
| Non-ICU admitted patient ( n = 200) with medication error, n (%) | 2 (5.1) vs 53 (32.5), OR 3.6 | χ 2 test | 1.9–6.5 | |
| Patients transferred to operating room with medication error, n (%) | 1 (0.4) 6 vs (37.5), OR 3.8 | χ 2 test | 1.3–11.2 | |
| Patients transferred to the ED observation area ( n = 40) with medication error, n (%) | 9 (22.5) vs 0 (0), OR 2.5 | χ 2 test | 1.0–6.3 | |
| Harvey 2018 [ ] Major trauma resuscitation n = 146 | P: Patients with initial AB prophylaxis guideline compliant, n (%) | 54 (81) vs 37 (47) | χ 2 test | p < 0.01 |
| S: Median ED arrival to AB administration time, min (IQR) | 14 (11−20) vs 20 (12–27) | Student’s t- test | p = 0.02 | |
| Johnson 2015 [ ] Major trauma resuscitation n = 106 | P: Mean time to sedation or analgesia after NMBA facilitated RSI, min (SD) | 20 (21) vs 49 (45) | Student’s t- test | p < 0.001 |
| P: Mean time to sedation or analgesia after rocuronium facilitated RSI, min (SD) | 23 (22) vs 55 (46) | Student’s t- test | p = 0.002 | |
| P: Mean time to sedation/analgesia after succinylcholine facilitated RSI, min (SD) | 13 (14) vs 28 (3) | Student’s t- test | p = 0.306 | |
| Lamkin 2019 [ ] Major trauma resuscitation n = 1082 | P: Median time to AB, min (IQR) | 20 (12–29) vs 18 (9–27) | WRS test | p = 0.39 |
| P: Median time to RSI, min (IQR) | 12.5 (6–18) vs 12 (10−22) | WRS test | p = 0.78 | |
| P: Median time from RSI to sedation, min (IQR) | 7.5 (5–16) vs 8 (0–10) | WRS test | p = 0.50 | |
| P: Median time to analgesia, min (IQR) | 11 (8–27) vs 13 (8.5–20) | WRS test | p = 0.047 | |
| P: Median time to anticoagulation reversal | Nil | |||
| S: Patients receiving appropriate AB, n (%) | 46 (80.7) vs 12 (52.2) | FE test | p = 0.01 | |
| S: Patients given tetanus vaccination, n (%) | 160 (20.5) vs 56 (18.7) | FE test | p = 0.55 | |
| Montgomery 2015 [ ] Major trauma resuscitation n = 340 | P: Mean time from arrival to analgesic administration, min | 17 vs 21 | Student’s t- test | p = 0.03 |
| S: Mean change in pain score from trauma bay arrival to ED transfer, pain score change | −2.4 vs −2.8 | MWU | p = 0.57 | |
| S: Mean time from prehospital to first ED analgesic, min | 29.9 vs 32 | Student’s t- test | p = 0.68 | |
| Riley 2013 [ ] Major trauma resuscitation n = 538 | Patients in whom an AB was given, n (%) | 80 (48) vs 105 (28.3) | χ 2 test | p = 0.0003 |
| Patients given appropriate AB, n (%) | 70 (87.5) vs 83 (78) | χ 2 test | p = 0.132 | |
| Patients given appropriate AB dose, n (%) | 79 (99) vs 83 (79) | χ 2 test | p = 0.00006 | |
| Patients with AB omission, n (%) | 1 (1.23) vs 76 (20.5) | χ 2 test | p ≤ 0.00001 | |
| Mean time from arrival to AB administration, min (SD) | 17.7 (18.9) vs 36.6 (38.9) | Student’s t- test | p = 0.01 | |
| Robey-Gavin 2016 [ ] Major trauma resuscitation n = 82 | P: Patients given analgesia post RSI, % | 49 vs 20 | χ 2 test | p = 0.005 |
| S: Patients given sedation without analgesia, % | 51 vs 73 | χ 2 test | p = 0.04 | |
| S: Time to initiation of postintubation analgesia, min | 45 vs 98 | χ 2 test | Not stated | |
| S: Adverse drug events with discontinuation of analgesia, n | 1 vs 0 | χ 2 test | Not stated | |
| Chanas 2019 [ ] Sepsis | Time from advisory trigger to AB administration; h | 1.2 vs 4.2 | Kruskal-Wallis | p = 0.046 |
| Patients administered AB <1 h, n (%) | 9 (36) vs 8 (14) | χ 2 test | p = 0.021 | |
| Patients administered AB <3 h, n (%) | 15 (60) vs 20 (34) | χ 2 test | p = 0.031 | |
| Roman 2023 [ ] Sepsis n = 184 | P: Patients given AB <60 min arrival, n (%) S: Median time to antibiotics, min (IQR) S: Patients given fluids within 60 min, n (%) S: Serum lactate <60 min, n (%) S: Blood cultures taken <60 min, n (%) S: Blood cultures taken before ABs, n (%) S: All four indicators within 60 min, n (%) S: Median LOS in ED, h (IQR) S: Median LOS in ICU, h (IQR) S: Death at hospital discharge, n (%) S: Median LOS in hospital, h (IQR) | 85 (81.7) vs 21 (26.3) 38 (27–54) vs 91 (59.5–163.5) 75 (72.1) vs 38 (47.5) 81 (77.9) vs 40 (50.0) 89 (85.6) vs 42 (52.5) 71 (68.9) vs 60 (75.0) 52 (50.0) vs 8 (10.0) 6 (5–8.5) vs 6 (4–8) 82 (50.5–143.5) vs 82.5 (40–120) 15 (14.4) vs 9 (11.2) 269.5 (162.5–487.5) vs 234.5 (142–463) | NR c NR c NR c NR c NR c NR c NR c NR c NR c NR c NR c | p ≤0.001 p ≤0.001 p = 0.002 p ≤0.001 p ≤0.001 p = 0.37 p ≤0.001 p = 0.45 p = 0.24 p = 0.27 p = 0.36 |
| Tarabichi 2021 [ ] Sepsis n = 598 | P: Median ED arrival to AB administration time; h (IQR) | 2.3 (1.4–4.7) vs 3 (1.6–5.5) | WRS test | p = 0.039 |
| P: Median days alive and out of hospital at 28 days; days | 24.1 vs 22.5 | WRS test | p = 0.011 | |
| S: Median length of stay; days (IQR) | 3.2 (1.1–6.2) vs 4.0 (1.4–7.0) | WRS test | p = 0.124 | |
| S: Hospital mortality, n (%) | 13 (4.6) vs 25 (8.0) | χ 2 test | p = 0.086 | |
| S: 28-day mortality, n (%) | 17 (6.0) vs 31 (9.9) | χ 2 test | p = 0.077 | |
| S: AB utilisation; n (%) | 193 (67.7) vs 219 (70.0) | χ 2 test | p = 0.553 | |
| S: Fluid bolus administration; n (%) | 174 (61.1) vs 203 (64.9) | χ 2 test | p = 0.336 | |
| S: Median fluid volume by weight; mL/kg (IQR) | 39.1 (23.9–62.2) vs 41.0 (22.5–64.2) | WRS test | p = 0.831 | |
| S: Clostridiodes difficile diagnosis; n (%) | 2 (0.7) vs 5 (1.6) | χ 2 test | p = 0.309 | |
| S: Admitted to inpatient setting; n (%) | 217 (76.1) vs 254 (81.2) | χ 2 test | p = 0.135 | |
| S: Admission to ICU; n (%) | 101 (35.4) vs 128 (40.9) | χ 2 test | p = 0.170 | |
| S: Median ICU length of stay; days (IQR) | 3.6 (2.0–5.4) vs 3.4 (2.0–6.0) | WRS test | p = 0.937 | |
| S: 28-day ED/hospital representation, n (%) | 70 (24.6) vs 96 (30.7) | χ 2 test | p = 0.09 | |
| Gawedzki 2022 [ ] Status epilepticus n = 20 | P: Median time from ED arrival to antiepileptic administration, min (IQR) | 1st: 26 (17–177) vs 37 (21–206) 2nd: 51 (30−221) vs 171 (99–433) 3rd: 205 (96–416) vs 335 (0) | WRS test | p = 0.58 p = 0.07 p = 0.69 |
| S: Proportion of patients who received an appropriate antiepileptic for each antiepileptic selected, n (%) | 1st: 11 (85) vs 7 (100) 2nd: 11 (92) vs 4 (80) 3rd: 7 (88) vs 1 (100) | χ 2 test FE test | p = 0.52 p = 0.54 p = 1 | |
| S: Patients who received an appropriate dose for each antiepileptic, n (%) | 1st: 3 (23) vs 0 2nd: 3 (25) vs 1 (20) 3rd: 4 (50) vs 0 | χ 2 test | p = 0.52 p = 1.0 p = 1.0 | |
| S: Median lorazepam equivalent, mg (IQR) | 2.5 (2–4) vs 2 (0) | WRS test | p = 0.04 | |
| S: Received >/= 4 mg of lorazepam equivalents, n (%) | 5 (38) vs 0 | χ 2 test | p = 0.11 | |
| S: Intubated in ED, n (%) | 1 (8) vs 0 | χ 2 test | 1 | |
| S: Refractory status epilepticus, n (%) | 1 (8) vs 0 | χ 2 test | 1 | |
| S: 30-day mortality, n (%) | 1 (8) vs 0 | χ 2 test | 1 | |
| S: ICU admission, n (%) | 7 (54) vs 0 | χ 2 test | p = 0.04 | |
| S: Median ED LOS, min (IQR) | 431 (340–568) vs 679 (570–992) | WRS test | p = 0.006 | |
| S: Median Hospital LOS, days (IQR) | 3 (2–9) vs 3 (1–4) | WRS test | p = 0.18 |
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