Table 2:
Author/Year | Study | Study Objective | CDS Intervention Implementation | Study Design (population, setting, comparison) | Reported Outcome and Impact | |
---|---|---|---|---|---|---|
Clinical and Process Measures | User Experience | |||||
Bernstein et al, 200521 | An Electronic Chart Prompt to Decrease Proprietary Antibiotic Prescription to Self-Pay Patients | “To develop a clinical decision support system to display patient insurance status before prescription writing for outpatient conditions” |
CDS: Synchronous decision support system with an on-screen prompt “to alert
physicians to patients’ insurance status before prescribing antibiotics for patients to be discharged from the
ED” Decision: Medications guideline adherence Implementation: Brief ED-based in-service, 30-minute didactic lecture, brief email reminder |
Design: Pre-post intervention comparison in 13 weeks leading up to and immediately
after implementation Setting: Urban ED with 78,000 visits/year serving a medically underserved population Clinicians: 61 prescribes during control and intervention periods: all attending emergency physicians, PAs, EM residents, medical and PA students, residents rotating from other services in the ED Patients: All ED patients aged 18 years or older discharged from the ED receiving antibiotic prescriptions during the 26-week study period: 543 during control and 514 during intervention |
Proprietary antibiotics prescribed decreased: 26.6% to 20.7% (22% reduction;
p=0.03) Preplanned subgroup analysis of self-pay patients with respiratory and urinary infections: proprietary antibiotics prescribed decreased 44.4% to 31.3% (30%reduction; p=0.005) |
No data reported; but authors discussed the ‘apparent resistance to change’ from prescribers |
Kirk et al, 200556 | Computer Calculated Dose in Pediatric Prescribing | “To assess the rate of medication errors in predominantly ambulatory pediatric patient and the effect of computer calculated does in medication error rates of two commonly prescribed drugs” |
CDS: Computer calculated dosing for acetaminophen or
promethazine Decision: Medication appropriateness for pediatric patients Implementation: Department staff training session, reinforced via email. |
Design: Prospective cohort between March 2003 (date of implementation) and August
2003 Setting: Outpatient clinic, pediatric ED, at National University Hospital, Singapore Clinicians: All prescribing physicians (84% pediatricians) Patients: 3,347 patients with 4,274 prescriptions analyzed |
Medication error rate: 12.6% (299/2381) in the computer calculated dose system, 28.2% in the
traditional method (534/1893) Overall error rate was 19.5% with most errors being a result of an underdose (64%) OR for error with CDS vs traditional method 0.436 in LR model controlling for drug, prescriber and patient characteristics |
No assessment reported |
Buising et al, 200837 | Improving antibiotic prescribing for adults with community acquired pneumonia: Does a computerized decision support system achieve more than academic detailing alone? - a time series analysis | “To describe the impact of … both academic detailing (AD) and a computerized decision support system (CDSS) on the management of patients with CAP” |
CDS: Web based design, integrated with hospital database to provide PSI to
recommend inpatient vs. outpatient care and CURB score to recommend ICU need, as well as provided antibiotics
recommendations. Decision: Treatment of CAP Implementation: Intervention implemented after an 8-month period of academic detailing where physicians received 1 on 1 training |
Design: Two stage pre-post intervention cohort and time series analysis over 3 time
periods: Baseline, April 2003 – March 2004. Academic Detailing, February 2005 - October 2005. CDS, April 2006 -
September 2006 Setting: A single urban tertiary care ED with 50,000 visits/year Clinicians: 30 different emergency physicians, both senior and junior medical staff Patients: All ED patients aged 18 years or older with a diagnosis of pneumonia, chest infection, lower respiratory tract infection, pleuritic chest pain, cough, shortness of breath, and/or aspiration who met a pneumonia definition by case review. Baseline N = 392, Academic Detailing N = 215, CDS N = 133 |
The adjusted odds ratio for concordant therapy in the academic detailing period, compared with
the baseline period was 2.79 [1.88,4.14], p < 0.01, and for the CDS period compared to the academic detailing
period was 1.99 [1.07, 3.69], p = 0.02 With CDS an improvement in the appropriateness of antibiotic prescribing was demonstrated, which was greater than that expected to have occurred with time and academic detailing alone, based on predictions from a binary logistic model |
No assessment reported |
Sard et al, 200854 | Retrospective evaluation of a computerized physician order entry adaptation to prevent prescribing errors in a pediatric emergency department | “To determine the impact on medication prescribing errors by adding a pediatric medication list (drug dosing support tool) into the CPOE” |
CDS: Pediatric medication quick-list (drug dosing support tool) added into
CPOE Decision: Medication appropriateness for pediatric patients Implementation: 2-hour training required to access the new system |
Design: Pre-post intervention comparison Setting: Academic, urban, pediatric ED, volume ~30,000 visits/year Clinicians: Attending physicians, pediatric EM fellows, pediatric residents Patients: 840 randomly selected visits (420 pre-implementation, 420 post-implementation) |
Medication errors/100 visit significantly decreased (24 pre to 13
post) Medication errors/100 orders significantly decreased (31 pre to 14 post) |
No assessment reported |
Terrell et al, 200922 | Computerized decision support to reduce potentially inappropriate prescribing to older emergency department patients: A randomized, controlled trial |
“To evaluate the effectiveness of computer-assisted decision support in reducing potentially inappropriate prescribing to older adults” |
CDS: Alert issued when one of 9 preselected high-risk medications was provided as a
discharge prescription Decision: Medication appropriateness for older adult patients Implementation: Physicians were randomized, with half receiving the alerts when applicable during the study period |
Design: Randomized, controlled trial Setting: An academic [urban] emergency department (ED) in Indianapolis, Indiana, with 100,000 visits/year Clinicians: 63 emergency physicians [faculty and PG-2 & 3 residents] were randomized to the intervention (32 physicians) or control (31 physicians) group Patients: 5,162 analyzed visits by patients aged 65 or over, 210 of whom had attempts to provide a potentially inappropriate recommendation |
Intervention physicians prescribed one or more inappropriate medications during 2.6% of ED visits by seniors, compared with 3.9% of visits managed by control physicians (P=.02; odds ratio=0.55,95% Cl 0.34–0.89) | No assessment reported |
Melnick et al, 201029 | Knowledge translation of the American College of Emergency Physicians’ clinical policy on syncope using computerized clinical decision support | “To identify the presence of a change in physician ordering of cranial imaging and admission practices due to implementation of a HPI-based CDSS in patients with a final diagnosis of syncope” |
CDS: 3 item module added to the syncope documentation template including
recommendations on imaging and admission and forcing documentation Decision: CT brain in syncope Implementation: Module announced via email |
Design: Pre-post intervention comparison of consecutive patients presenting with
syncope during June 2017 – February 2008 (pre) to February 2008 – June 2008
(post) Setting: Mount Sanai Medical Center (New York, NY), a 1,171-bed tertiary care academic medical center Clinicians: 34 emergency physicians supervising both EM and rotating residents Patients: 410 pre-implementation visits and 301 post-implementation |
No significant difference in the head CT imaging rate (39.8% pre-intervention, 43.2%
post-intervention, p=0.358) Significant decrease in admission rate (68.1% pre-intervention, 60.5% post-intervention, p=0.036) |
No assessment reported |
Terrell et al, 201038 | Computerized decision support for medication dosing in renal insufficiency: A randomized, controlled trial | “To examine whether decision support in a computerized physician order entry system would reduce the rate of excessive medication dosing for patients with renal impairment” |
CDS: CPOE alert providing dosing recommendations for targeted medications when the
patient’s estimated creatinine clearance level was below the threshold for dosage
adjustment Decision: Medication dosing Implementation: Physicians were randomized, with half receiving the alerts when applicable during the study period |
Design: Randomized, controlled trial Setting: An academic [urban] emergency department (ED) in Indianapolis, Indiana, with 100,000 annual visits Clinicians: The sample included 42 physicians who were randomized to the intervention (21 physicians) or control (21 physicians) group; including emergency medicine faculty and year 2 & 3 residents Patients: 2,783 patients with sufficient data to estimate creatinine clearance, of whom 119 were written prescriptions for meds requiring potential adjustment |
Decision support was provided 73 times to physicians in the intervention group, who excessively dosed 31 (43%) prescriptions. In comparison, control physicians excessively dosed a significantly larger proportion of medications: 34 of 46,74% (effect size = 31%; 95% confidence interval 14% to 49%; P= .001) | No assessment reported |
Venkat et al, 201052 | Feasibility of integrating a clinical decision support tool into an existing computerized physician order entry system to increase seasonal influenza vaccination in the emergency department | “We hypothesized that integration of clinical decision support into an existing ED CPOE system would allow large-scale patient screening and provision of seasonal influenza vaccination in the ED setting without added staffing resources” |
CDS: Protocolized order for influenza vaccination screen which automatically fired
at registration for patients who had no record of prior vaccination Decision: Screening for influenza vaccination Implementation: 15 minutes of training at staff meetings prior to initiation of the order set |
Design: Pre-post intervention comparison of October 2009 (immediately post
intervention) to October 2008 (pre-intervention) Setting: Urban, tertiary care center with an annual census of 48,000 visits/year, approximately 10% pediatric Clinicians: 59 nurses Patients: 3,900 pre-implementation visits and 3,091 post-implementation |
ED influenza vaccination rose by 17.5% (95%CI16–19%, p<0.001) | No assessment reported |
Carman et al, 201125 | Use of a Clinical Decision Support Tool to Improve Guideline Adherence for the Treatment of Methicillin-Resistant Staphylococcus Aureus Skin and Soft Tissue Infections | “To examine whether development of a CDS tool based on current guidelines for the outpatient management of CAMRSA-related abscesses and interfaced with the documentation and order-entry process would improve prescriptive practice in an ED setting” |
CDS: H&P template, abscess order-entry form, and prebuilt discharge pathway to
guide prescriptions, follow-up, and discharge instructions specific to the care of MRSA
abscesses Decision: Diagnosis and treatment of skin and soft tissue infections Implementation: Email and verbal presentation at department meeting |
Design: Pre-post intervention comparison of a pre-implementation baseline to 6 and
12 weeks after intervention Setting: One level-one trauma center with separate adult and pediatric EDs, a smaller community hospital ED, and two freestanding EDs with 200,000 visits/year total Clinicians: Private group practice, with 71 board-certified emergency physicians and 30 mid-level providers Patients: All patients presenting to the ED with a chief complaint of abscess during the time periods. N= 863. Exclusions: animal bites and oral/dental infections |
Adherence to recommended antibiotics therapy: 86.8% at baseline, 90.6% at week 6 and 96.7% at
week 12 (p <0.001) Wound cultures: 34.6% at baseline, 7.0% at week 6 and 22.0% at week 12 (p=0.002) Chlorhexidine decontamination 0.0% at baseline, 5.0% at week 6 and 7.3% at week 12 (p =0.001) |
Usability survey was generated at 6 and 12 weeks post intervention: low response rate (20% at week 6 and 6% at week 12). Median responses were positive for all usability questions |
Drescher et al, 201153 | Effectiveness and acceptability of a computerized decision support system using modified Wells’ criteria for evaluation of suspected pulmonary embolism | “To determine whether a validated prediction algorithm embedded in a computerized decision support system improves the positive yield rate of CT angiography for pulmonary embolism and is acceptable to emergency physicians” |
CDS: Required physicians to enter information into a calculator for the
dichotomized version of the Wells’ score, embedded in the CPOE and fired every time a physician ordered a D-dimer
or CT-angiography Decision: CT for PE Implementation: Physicians briefed on intervention 1 month prior to implementation |
Design: A prospective interventional study with a retrospective pre-interventional
comparison group Setting: Academic community hospital ED Clinicians: 19 board-certified attending physicians without residents Patients: 205 pre-implementation visits, 229 post-implementation |
Overall increase in the positivity rate of from 8.3% (95% confidence interval [Cl] 4.9% to 12.9%) pre-intervention to 12.7% (95% Cl 8.6% to 17.7%) post-intervention (higher yield) | Clinicians did not complete the algorithm or adhere to its recommendation for 105 cases (26.7%) Reasons given included time requirement and lack of belief that the CDS was helpful for guiding patient evaluations |
Nelson et al, 201130 | Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis | “An automated, real-time electronic medical record query and caregiver notification system was developed and examined for its utility in improving sepsis care” |
CDS: EMR surveillance algorithm ran for patients > 18 having ≥ 2 SIRS
criteria and ≥ 2 BP measurements ≤ 90 mm Hg during their ED stay. Algorithm prompted notification by paging
and text entry in EHR for fluid resuscitation, blood culture, and antibiotic
administration Decision: Diagnosis and treatment of sepsis Implementation: Algorithm was run in background leading up to implementation |
Design: Pre-post prospective study, comparing patients identified by the algorithm
“dry firing” to a period of full implementation with physician
notification Setting: One academic hospital ED with 68,000 visits/year Clinicians: No information Patients: 33,860 total patients screened of whom 398 (1.2%) met criteria |
Two interventions had increased frequency after system activation: chest radiograph before
admission (OR 3.2; 95% Cl 1.1 to 9.5) and collection of blood cultures (OR 2.9; 95% Cl 1.1 to
7.7) Non-significant increased frequency in lactate ordering or antibiotic administration Only blood cultures exhibited decrease in median time to performance: (pre-intervention 86 min, IQR 31, 296 min; post intervention 81 min, IQR37,245min;P=.032) |
No assessment reported |
Griffey et al, 201249 | Guided medication dosing for elderly emergency patients using real-time, computerized decision support | “To evaluate the impact of a real-time computerized decision support tool in the emergency department that guides medication dosing for the elderly on physician ordering behavior and on adverse drug events (ADEs)” |
CDS: Alert providing age-adjusted recommendations, e.g., medication, dosage or
frequency. Fires in CPOE for patients older than 65 for pre-specified medication
orders Decision: Medication appropriateness for older adult patients Implementation: Not discussed |
Design: Prospective controlled trial over 4 consecutive periods consisting of
control periods alternating with intervention periods (6 to 7-week blocks) Setting: One urban, academic ED Clinicians: ED residents, off-service Residents, and rotating residents Patients: 2,398 orders among 1,407 patients: 668 control and 739 intervention |
Greater % of orders consistent with recommendations during ON periods (31%) as compared to OFF
periods (23%) (p<0.001) Physicians declined the recommendation in 93% of suggestions during ON periods No differences in admission rate, reversal drug administration, number of 10-fold orders, or ED LOS 39 ADEs during ON periods and 31 during OFF periods (p=0.02) |
No assessment reported |
Raja et al, 201227 | Effect of Computerized Clinical Decision Support on the Use and Yield of CT Pulmonary Angiography in the Emergency Department | “To determine the effect of evidence-based CDS on the use and yield of CT pulmonary angiography for acute pulmonary embolism (PE) in the emergency department ED” |
CDS: Addition to CPOE system for ordering CT angiography of chest. Required
physicians to enter D dimer (Not done, normal or elevated) and clinical suspicion of PE (low, intermediate or high), then
provided nonbinding advice regarding need for CT imaging Decision: CT for PE Implementation: Rollout accompanied by significant educational efforts |
Design: Pre-post intervention evaluation in a single ED from 2003–2009,
intervention in 2007 Setting: 793-bed quaternary care center with 60,000 ED visits/year Clinicians: All prescribing clinicians Patients: 338,230 patients seen during study period, of whom 6,838 received pulmonary CTA |
20.1% decrease in quarterly use of CTA per 1000 patients 69% increase in yield of CTA studies |
No assessment reported |
Dexheimer et al, 201339 | Modifications and Integration of the Electronic Tracking Board in a Pediatric Emergency Department | “To describe the modifications and decisions made in the implementation of a computerized tracking board in a pediatric ED” |
CDS: Tracking board timer that alerts nurses 30 minutes after medication
administration to reassess pain levels Decision: Pain reassessment Implementation: Not discussed |
Design: Pre-post prospective study Setting: Freestanding children hospital with 577 beds and more than 120,000 ED visits/year Clinicians: Physicians, nurses and patient care attendants Patients: No information |
After the inception of a screen icon and alert for pain reassessment, pain reassessments increased from 50–65% of patients to more than 85% | No assessment reported |
Prevedello et al, 201357 | Does Clinical Decision Support Reduce Unwarranted Variation in Yield of CT Pulmonary Angiogram? | “To determine whether previously documented effects of clinical decision support on computed tomography for pulmonary embolism in the emergency department (i.e., decrease use and increase yield) are due to a decrease in unwarranted variation” |
CDS: Addition to CPOE system for ordering CT angiography of chest. Required
physicians to enter D dimer (Not done, normal or elevated) and clinical suspicion of PE (low, intermediate or high), then
provided nonbinding advice regarding need for CT imaging Decision: CT for PE Implementation: Rollout accompanied by significant educational efforts |
Design: Retrospective pre-post evaluation conducted from January 2006 –
March 2009, in the emergency department of a 793-bed, quaternary care-academic hospital (adult-only emergency department,
Level 1 Trauma and Burn Center, and Stroke and Cerebrovascular Disease Center) Setting: 793-bed quaternary care center with 60,000 ED visits/year Clinicians: All prescribing clinicians Patients: 113,703 ED visits with 2,891 (2.5%) rate of CTA for PE |
PE-CT decreased from 26.5 (pre) to 24.3 (post) CT scans/1000 patients Overall yield of CT scans increased from 9.2% to 12.6%, a 3.4% increase post-CDS Inter-physician variability in yield ranged 2.6%–20.5% (pre) and 0%–38.1% (post) Intra-physician variability in yield ranged from a 9.1% decrease to a 21.0% increase in yield of PE—CT; was significant in 3 out of 25 physicians (the intra-physician variability was related to improved yield) |
No assessment reported |
Demonchy et al, 201458 | Impact of a computerized decision support system on compliance with guidelines on antibiotics prescribed for urinary tract infections in emergency departments | “To assess the impact of a CDSS on compliance with guidelines on empirical antibiotic prescriptions for UTIs in EDs” |
CDS: Triggered when a UTI diagnosis was validated and launched a tool to collect
limited additional data from popup screens. It provided recommendations regarding the investigations, the indications for
hospitalization, the antibiotic treatment and the follow-up, tailored to the individual patient
data Decision: Diagnosis and treatment of UTI Implementation: Intervention was preceded by passive recommendations at a single site |
Design: Pre-post prospective study in 3 French EDs from March 2012 – October
2012. Intervention was rolled out over 3 periods in 3 centers, with one center implementing a passive recommendation
screen between baseline and CDS Setting: 3 academic, French EDs Clinicians: Junior and senior physicians as well as rotating residents Patients: All patients aged 15 years or older and diagnosed with community-acquired UTI (N= 912); exclusions from the study if data were missing regarding the diagnosis and/or the antibiotic prescription |
The CDSS led to a modification of the initial diagnosis in 23% (42/182) CDSS was not associated with significant increase in appropriate antibiotics or duration in multivariate analysis CDS used in 59% of cases |
Usability was rated as good by all clinicians, with the tool considered to be user-friendly and not time-consuming. Most clinicians found the CDSS to be useful in their daily practice |
Dexheimer et al, 201431 | Implementation and evaluation of an integrated computerized asthma management system in a pediatric ED: a RCT | “To determine whether patient eligibility identification by a probabilistic disease detection system (Bayesian net-work) combined with an asthma management system embedded in the workflow decreases time to disposition decision” |
CDS: Asthma management system with 2 components: (1) automatic disease detection
system (ADDS) and (2) management system Decision: Asthma management Implementation: 2 months of email and live announcements |
Design: Prospective, randomized controlled trial comparing CDS to a paper-based
protocol Setting: Urban tertiary care pediatric ED with 55,000 visits/year Clinicians: 68 ED attending physicians, 95 nurses, and 16 respiratory therapists Patients: Intervention group (n=398) was compared to control group (n=390) |
Primary outcome measure was the time from triage to disposition decision. Intervention and
control patients did not differ significantly in time to disposition Secondary outcome was adherence to guidelines for asthma care. There were no significant differences between intervention and control groups |
No assessment reported |
Fowler et al, 201459 | Electronic health record: integrating evidence-based information at the point of clinical decision making | “To(1) provide a straightforward mechanism for physicians to review alternative diagnoses prior to finalizing a treatment plan and (2) dramatically improve the ease of access to relevant evidence-based information resources without disrupting established workflows” |
CDS: Diagnostic decision support tool (DDST) and a web-based knowledge page (KP).
Based on age, gender, chief complaint, triage impression, positive findings and history of present illness, the DDST makes
suggestions for possible diagnosis. Clicking on a possible diagnosis provides the provider with information from different
sources (the KP) Decision: General diagnosis Implementation: Presentation about the tools were given to physicians before, during and after the study |
Design: Uncontrolled pilot, intervention available optionally in EHR for 6
months Setting: 250-bed pediatric teaching hospital. Focus groups and survey used to generate results Clinicians: 200 pediatric ED clinicians (attending physicians, fellows, residents) Patients: 34,000 potential visits, DDST used 167 times (0.03%) |
Only 2 physicians responded to survey, both stated DDST influenced their DDx. | Data collected during focus groups showed that physicians in the ED would prefer access to KP without the DDST |
Gupta et al, 201435 | Effect of clinical decision support on documented guideline adherence for head CT in emergency department patients with mild traumatic brain injury | “To determine the impact of an electronic CDS tool, based on validated evidence, designed to guide emergency clinician decision making for use of head CT for patients with MTBI” |
CDS: Electronic CDS triggered in CPOE when a head CT for trauma was ordered;
clinician prompted to enter justifying information and given recommendation on appropriateness of proceeding with
CT Decision: CT for head trauma Implementation: Not discussed |
Design: Pre-post prospective study; 27 months before and 27 months after CDS
implementation Setting: ED of a 793-bed, urban, academic level 1 trauma center Clinicians: No information Patients: Random sample of 200 head CTs on patients with MTBI from each of baseline and intervention periods |
Documented guideline adherence: from 49% to 76.5% (p<.001); absolute increase of 27.5% | No assessment reported |
Raja et al, 201436 | The use of decision support to measure documented adherence to a national imaging quality measure | “To determine feasibility of measuring adherence to national quality measure regarding CTPA for PE using CDS and whether this would affect use and yield of CTs” |
CDS: Wells’ score criteria based CDS within CPOE, required answering yes/no
to each Wells’ element and indicating result of D-Dimer (if ordered). CDS messages for non-adherent
orders Decision: CT for PE Implementation: Updated an existing CDS |
Design: Pre-post prospective study from September 2009 – November 2011,
intervention October 2010 Setting: 776 bed quaternary care center, ED volume ~60,000 visits/year Clinicians: Attending physicians and residents; all attendings EM boarded Patients: 1,209 patients with suspected PE in pre-intervention, 1212 in post-intervention |
Documented adherence to NQM improved (control 56.9% vs intervention 75.6%,
p<.008) No change in CT utilization or yield |
No assessment reported |
Carnevale et al, 201560 | Impact Of An Emergency Medicine Decision Support And Risk Education System On Computed Tomography And Magnetic Resonance Imaging Use | “To assess the impact of a multimodal emergency medicine decision support and risk education system (DS-RES) on the use of CT and MRI imaging” |
CDS: Point of care documentation templates selected by chief complaint which
collect data and drive recommendations and alerts on imaging, orders, and
documentation Decision: General imaging guidelines Implementation: Not discussed |
Design: Pre-post prospective study with intervention availably July 2009. Pre
period was July 2008 – June 2009, post was October 2009 – September 2010. Data were adjusted for age,
complaint, and “risk” status using a DxCG risk score Setting: “A Kaiser Permanente Northwest Medical Center” Clinicians: No information Patients: 18,105 pre-intervention visits, 20,892 post-intervention. Visits were included for 11 specific chief complaints, among only discharged patients |
Physicians used the tool in 81.6% of encounters. Overall rate of CT/MRI imaging increased from 26.0% to 28.3% (P<.0001) In low-risk group, CT/MRI use decreased by 6.2% (95% Cl 4.0%–8.5%). In medium risk, decreased 3.3% (95% Cl 1.6%–5.0). In high-risk group, imaging increased by 5.6% (95% Cl 4.3%–7.0%) Proportion of patients with a 3-day re-visit to either the ED or inpatient facility decreased by 1.4% (95% Cl 0.7%–2.2%) from 9.7% to 8.3%. 7-day revisits decreased by 0.7% (95% CI-0.2% to 1.5%), from 13.9% to 13.2% |
No assessment reported |
Dean et al, 201532 | Impact of an Electronic Clinical Decision Support Tool for Emergency Department Patients With Pneumonia | “To assess the effect of [CDS] tool deployment on 30-day all-cause mortality and patient disposition before and 6 months after tool deployment in 4 intervention hospital EDs compared with 3 usual care hospital EDs” |
CDS: Alert to identify ED patients with high risk of pneumonia and recommends
evidence-based management. Automatically calculated objective severity assessment and management recommendations,
including disposition, diagnostic testing, and antibiotic selection Decision: Diagnosis and treatment of PNA Implementation: No discussion |
Design: Pre-post prospective study from baseline December 2009 – November
2010 followed by post implementation December 2011 - November 2012 in 4 EDs, with comparison to 3 non-intervention EDs in
study Setting: 7 EDs, 19,500–86,400 visits/year Clinicians: No information Patients: 4,758 patients aged 18 or over who met criteria of ICD-9 diagnosis of PNA and had chest imaging performed consistent with PNA |
Concordance with admission recommendation increased significantly, from 79% to 84%
post-deployment in intervention group Time to antibiotics decreased significantly among CAP patients in intervention group No difference in mortality adjusted or unadjusted among all PNA patients CAP patients treated in intervention EDs had a lower 30-day Mortality post deployment OR 0.53 (0.28–0.99) |
CDS was used in 62.6% of patients in the intervention group |
Faine et al, 201561 |
Importance of Decision Support Implementation in Emergency Department Vancomycin Dosing |
“To assess the impact of an EMR intervention on vancomycin dosing accuracy in critically ill ED patients. Secondary objectives were to assess the impact of vancomycin dosing on mortality, hospital length of stay, acute kidney injury, and the impact of obesity on vancomycin dosing accuracy” |
CDS: Weight-based vancomycin dosing added to
(CPOE). Decision: Medication Dosage (Vancomycin) Implementation: Email notification and live presentation prior to rollout |
Design: Retrospective pre-post cohort study of all patients (n=278) treated with
vancomycin and admitted to an intensive care unit. Pre period March 2008 – May 2009, post November 2009 –
April 2011 Setting: 60,000 visits/year Midwestern academic ED (March 2008 and April 2011) and admitted to an intensive care unit Clinicians: ED Physicians Patients: Pre group (n=100) was compared with intervention group (n=178) |
The primary outcome was the proportion of vancomycin doses defined as
“appropriate” based on recorded actual body weight”. The EMR dose calculation tool was associated
with an increase in mean vancomycin dose ([14.1±5.0] vs. [16.5±5.7] mg/kg, p<0.001) and a 10.3%
absolute improvement in first-dose appropriateness (34.3% vs. 24.0%, p=0.07) Secondary outcomes included 28-day in-hospital mortality, hospital length of stay and acute kidney injury (safety outcome). None of the differences between pre- and post- measurements was statistically significant |
No assessment reported |
Ip et al, 201528 | Impact of clinical decision support on head computed tomography use in patients with mild traumatic brain injury in the ED | “To examine the impact of real-time computerized clinical decision support (CDS), based on published high-quality evidence, on the use of head CT in adult ED patients diagnosed with MTBI” |
CDS: CDS triggered in CPOE when a head CT for trauma was ordered; clinician
prompted to enter justifying information and given recommendation on appropriateness of proceeding with
CT Decision: CT brain for trauma Implementation: Not discussed |
Design: Pre-post prospective study, included all adult EDs for all ED patients with
a discharge diagnosis of MTBI between January 2009 and December 2010; direct comparison to a control cohort of ED patients
diagnosed with MTBI from the National Hospital Medical Care Survey (NHAMCS) during study
period Setting: 793-bed, level-one trauma center Clinicians: ED physicians Patients: 116,009 unique ED visits at study site and 53,477 visits in control cohort: MTBI represented 1.2% of all ED visits |
Study ED: MTBI ED visits associated with head CT for 58.1% in pre and 50.3% in post (p=0.005);
relative decrease of 13.4% Control cohort: use of head CT did not change: 73.3% in pre and 76.9% in post Decrease in head CT use persisted after accounting for baseline demographic differences No significant changes in rate of delayed imaging or rate of delayed diagnosis of radiologically significant findings |
No assessment reported |
Sethuraman et al, 201562 | Prescription errors before and after introduction of electronic medication alert system in a pediatric emergency department | “To compare prescription errors rates before and after introduction of CPOE with electronic medication alert system in a PED” |
CDS: CPOE with electronic medication alert system (EMAS) (Cerner), alerts provider
to drug allergies, dose range checked, drug-drug interactions, and drug frequency errors for outpatient
prescriptions Decision: Medication appropriateness Implementation: Not discussed |
Design: Pre-post prospective study, implementation in October 2010. Pre period
January 2010 – May 2010, post January 2011 – May 2011 Setting: Free standing PED/children’s hospital, inner city, level-one trauma center ~92,000 visits/year Clinicians: Children’s ED providers Patients: Randomized selection of 5,000 patients in both pre and post groups, generating a total of 7,268 prescriptions in pre-intervention, and 7292 in post-intervention |
Significant reduction in overall error (10.4/100 prescriptions pre vs 7.3/100 prescriptions
post) No reduction in rate of prescriptions with serious errors EMAS was 45.1% sensitivity and 57% specific for medication errors 32% of alerts were false positives |
No assessment reported |
Stevens et al, 201563 | Enhancing the quality of prescribing practices of older veterans discharged from the emergency department (EQUiPPED | “To decrease ordering of potentially inappropriate medications to <5% for veterans ≥ 65 years old” |
CDS: Geriatric outpatient pharmacy order sets grouped according to common discharge
diagnoses with medication options preferred for use in older adults. Dose adjustments for renal impairment,
point-of-prescribing education regarding medications to avoid, and links to synthesized geriatric content were embedded
within the order sets Decision: Medication Implementation: Concurrent education campaign with lectures, journal club, and reminder cards, academic detailing and individual provider feedback |
Design: Pre-post prospective study. 8 months pre-intervention April 2012 –
November 2012 compared with the following 17 months. Intervention was rolled out incrementally, with CDS intervention in
February 2013. Data analyzed using Poisson regression and piecewise nonlinear
regression Setting: One large, urban VAMC ED with 41,000 ED visits/year (40% veterans ≥ 65 years old) Clinicians: 13 physicians, 2 APPs & 1 clinical pharmacist (permanent staff) participated [study excluded > 40 “moonlighters”] Patients: 4,042 total patients aged 65 or older who were treated and discharged |
In the 8 months before the intervention, the average monthly proportion of PIMs prescribed was
9.4 +/− 1.5%. This declined to 4.6 +/− 1.0% after the interventions In the top 5 medications or categories, significant reductions were noted in 3 (muscle relaxants, promethazine, chronic NSAIDs) The observed change was sustained for the final year of the evaluation period |
Feedback from providers was important in developing order sets that facilitated workflow and were not perceived as burdensome |
Kharbanda et al, 201633 | Implementation of Electronic Clinical Decision Support for Pediatric Appendicitis | “To standardize care and reduce CT use while maintaining patient safety through implementation of a multicomponent electronic clinical decision support tool for pediatric patients with possible appendicitis” |
CDS: 3 component tool: a standardized abdominal pain order-set, a Web-based risk
stratification tool, and a “time of ordering alert” Decision: Radiology Implementation: CDS was introduced with “brief (20 minute) group and individual training sessions over a 4-week time period (October 2011)”. “During the implementation period, group quarterly e-mails were sent to ED providers describing the guidelines and risk stratification approach.” |
Design: Interrupted time series for analysis Quasi-experimental study of children
aged 3 to 18 years who presented with possible appendicitis to 2 urban, tertiary care pediatric EDs between January 2011
and December 2013. Pre-intervention period was 10-months prior to implementation Setting: 2 urban tertiary care pediatric EDs with collective census of 95,000 visits/year Clinicians: 47 PEM physicians, 8 NP’s, 9 PEM fellows Patients: 2,803 patients (767 pre-implementation; 2,085 post-implementation; excluded 49 subjects from week of CDS implementation) |
54% relative decrease in CT use from pre-implementation to the end of the study (38.8% to 17.7%;
p=,007) No significant change in US or total imaging trends No statistically significant differences in rates of missed appendicitis, ED revisits with 30 days, appendiceal perforation, and ED length of stay |
No assessment reported |
McGuire et al, 201651 | Using a configurable EMR and decision support tools to promote process integration for routine HIV screening in the emergency department | “To initiate routine, opt-out HIV screening in Maricopa Medical Center’s adult ED for patients aged 18–64 years who were having labs drawn via venipuncture as part of their care” |
CDS: Integrated elements specific to HIV screening into the triage/intake process,
used resulting data to drive new screening protocols Decision: HIV Screening Implementation: Not discussed |
Design: Pre-post prospective study over 3-year period, July 2011 – June 2014
with implementation at Q3 2012 Setting: Maricopa Medical Center, not further characterized Clinicians: ED triage nurses Patients: 130,761 total encounters, of whom 33,683 were tested for HIV |
Overall increase in tested patients (67% in the first year, 97% in the second year, 98% in the
third year) and decrease in missed opportunities (dwindled to fewer than 5% of eligible patients) HIV positivity finding rate of 0.27% (3 times the rate recommended by the CDC for implementing routine testing) |
No assessment reported |
Silveira et al, 201664 | Impact of a clinical decision support tool on adherence to the Ottawa Ankle Rules. | “To determine the impact of CDS tool on documented adherence to the Ottawa Ankle Rules and yield (significant fracture rate) of ankle/foot radiography” |
CDS: Ottawa Ankle Rule based CDS embedded into the
CPOE Decision: Radiographs for ankle injury Implementation: Not discussed |
Design: Pre-post prospective study, 6 months pre and 8 months post intervention in
February 2013 Setting: 793 bed quaternary care academic hospital Clinicians: ED clinicians Patients: Adults with ankle injury: 205 pre-intervention, 255 post-intervention |
Documented OAR adherence significantly increased from 55.9% to 95.7% Utilization and yield of X-rays did not change |
No assessment reported |
Austrian et al, 201750 | Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay. | “To determine whether an electronic health record-based sepsis alert system could improve quality of care and clinical outcomes for patients with sepsis” |
CDS: Sepsis alert triggered by abnormal vital signs or laboratory
results Decision: Laboratory evaluation for sepsis Implementation: ED physician and nurse sepsis champions provided in-service instruction for staff on the alert |
Design: Retrospective cohort study of pre and post intervention of CDS from January
2013 – April 2015. Intervention implemented February 2014 Setting: EDs and urgent care clinics of one urban, academic health system in the USA Clinicians: All physicians and nurses working in the above centers Patients: All adult patients who were subsequently hospitalized with discharge diagnosis of sepsis listed as present on admission |
Mean LOS for patients with sepsis decreased from 10.1 to 8.6 days (P<.001) following
alert introduction The sepsis alert system had no effect on mortality or other clinical or process measures |
No data reported, but discussion of alert fatigue |
Baird et al, 201724 | Impact of Developing Adult Ketamine Order Panels for the Emergency Department. | “To evaluate the impact of standardizing the ordering process with the intent of increasing appropriate dosing of ketamine in the ED” |
CDS: Standardized order set providing ketamine orders with dosage recommendations
based on weight and indication Decision: Medication dosage for ketamine Implementation: Provider education at a monthly meeting, and reference materials on EMR login screen |
Design: Pre-post intervention comparison; retrospective control collected November
2013 – October 2015 with prospective intervention group collected March 2016 – May
2016 Setting: Multi-institutional analysis of ED use in a large health system Clinicians: ED providers Patients: 240 patients pre-intervention, 33 post-intervention identified as receiving ketamine in the ED |
Pre-intervention: 63.8% appropriate dosing, post intervention 81.8%, p = 0.231 by
Mantel-Haenszel test 6 emergence reactions documented in pre-phase, 0 in post |
No assessment reported |
Bookman et al, 201765 | Embedded Clinical Decision Support in Electronic Health Record Decreases Use of High-cost Imaging in the Emergency Department: EmbED study | “To evaluate the impact of evidence-based clinical decision support tools integrated directly into provider workflow in the electronic health record on utilization of computed tomography (CT) brain, C-spine, and pulmonary embolism (PE)” |
CDS: Alert that fires for specific CT orders that brings a clinical decision tool
to the provider, with fields auto populated from the chart to determine appropriateness of
study Decision: CT imaging Implementation: Education about the intervention given to all providers by site leadership just prior to insertion of the scoring tools |
Design: 18-month longitudinal study comparing pre-implementation from July –
December 2014 to post-implementation of July – December 2015 Setting: 5 EDs across a large integrated healthcare system utilizing a common EHR. The healthcare system consists of 1 academic and 4 community sites Clinicians: 163 attending providers across all 5 sites Patients: All adult ED patients with CT Brain, CT Cervical Spine, or CT PE ordered |
Decrease of 6,106 CT scan ordering for the three studies compared pre and post implementation.
Across all sites, there was greater than 6% decrease in utilization of CT brain and CT C-spine. The use of CT PE also
decreased but was not significant For all CT types, high utilizers in the pre-intervention period decreased usage over 14% in the post-intervention period with CT brain, p < 0.001, CT C-spine p = 0.001, and CT PE p < 0.001 |
No assessment reported |
Dayan et al, 201766 | Use of Traumatic Brain Injury Prediction Rules With Clinical Decision Support | “To determine whether implementing the Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) prediction rules and providing risks of clinically important TBIs (ciTBIs) with computerized clinical decision support (CDS) reduces computed tomography (CT) use for children with minor head trauma” |
CDS: CT recommendations and risks of ciTBI, both for patients at very low risk of
ciTBI (no Pediatric Emergency Care Applied Research Network rule factors) and those not at very low
risk Decision: CT head imaging for trauma Implementation: 1-time education consisted of a standard presentation focused on the CDS components and how to navigate to its different components |
Design: Non-randomized multicenter clinical trial with concordant
controls Setting: 5 pediatric emergency departments (PEDs) and 8 general EDs (GEDs) between November 2011 – June 2014 Clinicians: Attending faculty and physician fellows at each of the clinical sites Patients: patients <18 years of age and experienced minor blunt head trauma, defined by Glasgow Coma Scale (GCS) scores of 14 to 15, within 24 hours of ED presentation |
CT rates decreased significantly (P < .05) but modestly (2.3%–3.7%) at 2 of 4
intervention PEDs for children at very low risk The other 2 PEDs had small (0.8%–1.5%) non-significant decreases. CT rates did not decrease consistently at the intervention GEDs, with low baseline CT rates (2.1%–4.0%) in those at very low risk For all children with minor head trauma, intervention sites had small decreases in CT rates (1.7%–6.2%) |
No assessment reported |
Drescher et al, 201767 | Knowledge translation of the PERC rule for suspected pulmonary embolism: A blueprint for reducing the number of CT pulmonary angiograms. | Whether “the adoption of a department-endorsed, evidence-based clinical protocol, a multi-modal educational program, and CDS embedded in our computerized order entry system, would lead to a decrease in the number of CTPA ordered” |
CDS: Providers required to enter clinical information into diagnostic pathway prior
to ordering CT imaging for PE. PERC and Wells’ scores were then calculated and provided a recommended diagnostic
pathway Decision: CT imaging for evaluation of PE Implementation: Education was provided to ordering providers about the clinical rules and how to complete the ordering process at department meetings and grand rounds. Post implementation, providers who ordered CTPA outside the protocol parameters emailed regarding their rationale. A quarterly utilization report was sent to all providers |
Design: Pre-post observational study in which data were collected prospectively
over 12 months starting October 2012 and compared to the previous 12 months Setting: One urban tertiary referral center with an emergency medicine (EM) residency program and with a census of 100,000 visits/year Clinicians: 17 clinical EM faculty and 36 EM residents Patients: All non-pregnant patients aged 18 years or older in whom the providers suspected a diagnosis of PE and who did not have a contraindication to CTPA, including renal insufficiency and allergy to contrast material. |
CTPA declined from 1,033 scans for 98,028 annual visits (10.53 per 1,000 patient visits (95% Cl [9.9–11.2]) to 892 scans for 101,172 annual visits (8.81 per 1,000 patient visits (95% Cl [8.3–9.4]) p<0.001. The absolute reduction in PACT ordered was 1.72 per 1,000 visits (a 16% reduction) | No assessment reported |
Hendrickson et al, 201734 | Implementation of an electronic clinical decision support tool for pediatric appendicitis within a hospital network | “To assess the utility of an electronic health record (EHR)-based clinical decision support system (E-CDS) to optimize the care of children with acute abdominal pain in a general ED in a community hospital” |
CDS: Guideline content built into a CDS order set in the EHR. At time of initial
order placement, 3 steps: (1) common orders for initial evaluation, (2) secondary consideration of imaging after lab info
(absolute neutrophil count) was available, (3) additional orders based on results of
workup Decision: Evaluation and imaging for suspected appendicitis Implementation: Introduction about CDS in grand rounds; informal training sessions to clinicians |
Design: Pre- (3 months) and post-intervention (6 months after) retrospective
analysis of the use of EHR-based CDS order set for pediatric ED patients with suspected
appendicitis Setting: Urban tertiary care children’s hospital with 11,000 pediatric ED visits, also suburban community hospital with about 12,000 children visits to ED Clinicians: No information Patients: 327 eligible visits; age 3–18 with chief complaint of abdominal pain |
In community ED: among patients with any imaging, significant increase in use of ultrasound
(36–51%, p<.05) and decrease in use of CT (81–66%, p<.05) and a near significant increase in
use of ultrasound among all patients (26–38%, p=.055) At children’s hospital: no change; use of ultrasound was already high relative to CT Logistic regression done to adjust for gender difference between pre and post: attenuation of CDS effect, leading to marginally non-significant differences No negative impact on care (e.g., missed appendicitis) |
No assessment reported |
Martin Rico et al, 201768 | Electronic alerting and decision support for early sepsis detection and management: Impact on clinical outcomes | “To assess the validity of an electronic alert for identifying severe sepsis and septic shock” |
CDS: EHR alert for the possibility of severe sepsis and septic shock, and direct
access to order panel Decision: Treatment for severe sepsis and septic shock Implementation: Training during first 2 months of implementation of alert of all professionals working the ED |
Design: Pre-post intervention comparison. Pre-implementation from January 2011
– April 2013 and post-implementation from April 2013 – December 2013 Setting: One international site with 54,000 emergency encounters and 10,000 admissions annually Clinicians: All physicians working in ED at single site Patients: Patients aged 14 or older, with discharge diagnosis of ICD-9 codes related to sepsis |
Compared to pre-implementation, mortality rate decreased by 28% and adjusted mortality risk decreased by 36% | No assessment reported |
Mills et al, 201769 | Clinical decision support increases diagnostic yield of computed tomography for suspected pulmonary embolism | “To determine effects of evidence-based clinical decision support (CDS) on the use and yield of computed tomographic pulmonary angiography for suspected pulmonary embolism (CTPE) in Emergency Department (ED) patients” |
CDS: Provider inputs if D-dimer done and level, as well as Wells’ criteria
information, and CDS alert displayed with recommendation of obtaining d-dimer vs
CT-imaging Decision: CT imaging for PE Implementation: Implemented along with leadership focus on reducing inappropriate imaging |
Design: Multi-site, single health care system prospective quality improvement
intervention using a pre/post design of clinical decision support at the time of CTPE
order Setting: 2 community and 1 academic ED, all associated with a single health system Clinicians: Physicians at the community site and attending physicians and residents at the academic site Patients: ED patients older than 18 with order for CT-PE. 34.7% of patients presented pre- and 65.3% post-CDS implementation |
Yield increased a relative 30.8% after CDS implementation (8.1% vs. 10.6%;
p=0.0003) There was no statistically significant change in CTPE utilization (1.4% pre- vs. 1.4% post-implementation; p = 0.25) |
No data reported, but discussion of alert fatigue and “gaming” of CDS |
Min et al, 201770 | Clinical Decision Support Decreases Volume of Imaging for Low Back Pain in an Urban Emergency Department | “To determine whether point-of-care clinical decision support can effectively reduce inappropriate medical imaging of patients who present to the emergency department (ED) with low-back pain (LBP)” |
CDS: A point-of-care checklist of accepted red flags for LBP was embedded in the
existing order entry form for lumbar imaging Decision: Imaging for back pain Implementation: Communication regarding process changes for LBP diagnostic imaging requests and supplementary education material was delivered to physicians |
Design: ED electronic health records from January 2013 – May 2016, were
examined, with implementation March 2015. Retrospective extraction of data Setting: One major acute care and teaching center in Vancouver, British Columbia, Canada Clinicians: 43 emergency physicians at a major acute care center Patients: 4,562 patients with a diagnosis related to lower back pain |
Proportion of LBP patients with an imaging order fell significantly (median: 22% to 17%; mean:
23% to 18%; P ¼ .0002) compared with pre-intervention baseline The percentage of patients without imaging who were later imaged at a hospital outpatient clinic within 30 days was 2.3% before intervention and 2.2% after (P ¼ .974) In addition, the proportion of patients discharged from the ED without imaging who returned to the ED within 30 days was 8.2% before intervention and 6.9% after (P¼.170) |
No assessment reported |
Nicholson et al, 201771 | The Use of a Computerized Provider Order Entry Alert to Decrease Rates of Clostridium difficile Testing in Young Pediatric Patients | “To design a computerized provider order entry (CPOE) alert to decrease testing for C. difficile in young children and infants” |
CDS: Computerized provider order entry alert based on age advising against c.
difficile in children < 12 months and consider alternative etiologies for ages 12 months – 36
months Decision: C. difficile laboratory testing Implementation: Pediatric healthcare providers given brief educational seminars via PowerPoint |
Design: Pre-post intervention comparison with
cohorts Setting: One, tertiary care children’s hospital with emergency department Clinicians: All clinicians in ED and inpatient setting at pediatric hospital Patients: All patients who were seen in the emergency room or were admitted to any pediatric inpatient setting between July 2012 – July 2013 (pre-CPOE alert) and between September 2013 – September 2014 (post-CPOE alert) |
Average monthly testing rate significantly decreased after the CPOE alert for children 0–11 months old (11.5 pre-alert vs 0 post-alert per 10,000 patient days; P< .001) and 12–35 months old (61.6 pre-alert vs 30.1 post-alert per 10,000 patients days; P< .001), but not for those children ≥36 months old (50.9 pre-alert vs 46.4 post-alert per 10,000 patient days; P= .3) who were not targeted with a CPOE alert | No assessment reported |
Stevens et al, 201772 | Enhancing Quality of Provider Practices for Older Adults in the Emergency Department (EQUiPPED) | “To evaluate the effectiveness and sustainability of individual provider feedback and electronic EDS to reduce the use of potentially inappropriate medications (PIMs), prescribed to older Veterans at the time of emergency department (ED) discharge” |
CDS: Medication order sets for common outpatient geriatric prescriptions with renal
dosing adjustments and alternative options Decision: Medications Implementation: Educational seminars by geriatricians and individual provider feedback |
Design: Pre-post intervention comparison Setting: 4 VA emergency departments Clinicians: Attending and residents at all 4 VA emergency departments Patients: VA patients aged 65 or older discharged from emergency department |
The proportion of PIMs at site one decreased from 11.9% (SD 1.8) pre-intervention to 5.1% (SD 1.4) post-intervention (P < .0001); site 2 from 8.2% (SD 0.8) pre to 4.5% (SD 1.0) post (P < .0001); site 3 from 8.9% (SD 1.9) pre to 6.1% (SD 1.7) post (P = .0007); and site 4 from 7.4% (SD 1.7) pre to 5.7% (SD 0.8) post (P = .04) | No assessment reported |
Yan et al, 201773 | Yield of CT Pulmonary Angiography in the Emergency Department When Providers Override Evidence-based Clinical Decision Support | “The authors hypothesized that the yield of CT pulmonary angiography would be statistically significantly lower when CDS was overridden compared with when the Wells’ decision rule was followed” |
CDS: Wells’ score criteria integrated into the ED radiology CPOE.
Recommended D dimer for Wells’ ≤4 Decision: CT Imaging for PE Implementation: Not discussed |
Design: Retrospective analysis of visits with CT from January 2011 – August
2014. Compared guideline adherent CT’s to “Override Group” Setting: Urban, level-one trauma center with approx. 60,000 visits/year Clinicians: No information Patients: 2,404 CT’s in adherent group, 589 in override group |
Overall diagnostic yield of CT pulmonary angiography: override group = 4.2% vs 11.2% in adherent group. P<001 | No assessment reported |
Sharp et al, 201874 | Implementation of the Canadian CT Head Rule and Its Association With Use of Computed Tomography Among Patients With Head Injury | “To evaluate the association of implementation of the Canadian CT Head Rule on head CT imaging in community emergency departments (EDs) via CDS” |
CDS: Clinical decision support triggered when the physician ordered a CT if
information in the electronic health record indicated the scan was likely avoidable according to the Canadian CT Head
Rule Decision: CT imaging for head injuries Implementation: Electronic learning module distributed via email to all providers along with in-person clinical leadership education |
Design: An interrupted time-series analysis of encounters from January 2014
– December 2015 in 13 Southern California EDs Setting: 13 community EDs within a single integrated health care delivery system Clinicians: All physician providers working at the clinical sites Patients: Adult health plan members with a trauma diagnosis and Glasgow Coma Scale score at ED triage were included |
An absolute 5.3% (95% confidence interval [Cl] 2.5% to 8.1%) reduction in CT use
post-intervention After the intervention, diagnostic yield of CT-identified intracranial injuries increased by 2.3% (95% Cl 1.5% to 3.1%) |
No assessment reported |