Severe SepsisNCT02376842
Study of an Electronic Health Record-embedded Severe Sepsis Early Warning Alert
A study testing Severe sepsis early warning best practice alert in people with Severe Sepsis, run by Stanford University at 1 site in United States.
Trial summary
The investigators hypothesize that implementing an electronic health record-based early warning system for severe infections (severe sepsis) will decrease the time to antibiotic order. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Severe Sepsis
- What is being tested?
- Severe sepsis early warning best practice alert
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- Yes, some participants may receive a placebo
- How many people
- 1,149 participants
- Where
- 1 siteUnited States
- Study dates
- Nov 2014to Mar 2015
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Admitted to Stanford Hospital (inpatient or observation status) to any medical or surgical service for at least 24 hours during the period of the study
Who cannot join
- Admitted to an intensive-care level service (MICU, SICU, CVICU, CCU)
- Patient code status is DNR/C (comfort care only)
- Patients less than 18 years of age at time of admission.
- Emergency Department patients (may be included in the near future)
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Single-blind Randomized Trial of a Commercially Sold Electronic Health Record Based Severe Sepsis Early Warning Best Practice Alert.
The investigators hypothesize that implementing an electronic health record-based early warning system for severe infections (severe sepsis) will decrease the time to antibiotic order. The study will consist of an algorithm which will monitor lab values, vital signs, and nursing documentation for signs of severe sepsis. When these criteria are met, an alert will be delivered via the electronic health record to a nurse and doctor and simultaneously an alert via pager to another nurse. The investigators plan to randomize which patients will generate these alerts and analyze the data after collecting information for approximately 6 months which will be sufficient to detect a 10% difference in the two patient groups.
Read the detailed description
Sepsis is the leading cause of mortality at Stanford Hospital and ranks only 54th out of 119 hospitals according to UHC data with approximately 60 episodes of documented sepsis per quarter. Based on some preliminary data, there is concern that sepsis is both being recognized late and not treated in a timely enough fashion. In fact, there are evidence and expert guidelines that suggestion-delaying antibiotics in a patient with septic shock can increase mortality by 6.7% per hour (1C recommendation in severe sepsis by the Surviving Sepsis Campaign authors). As part of a hospital wide initiative to improve our treatment of sepsis and ultimately reduce sepsis-related mortality, an EHR-based clinical decision support (aka BPA) will be implemented. This BPA will be an algorithm that will alert practitioners and trigger clinical workflow after criteria are met. Criteria include lab values, vital signs and nursing flow sheet descriptions of perfusion (Table 1). The algorithm will alert when, in a 24 hour period, three criteria from the manifestation group, one criteria from the suspected infection group and one criteria from the organ dysfunction group. Note that one variable (eg creatinine > 2) can fulfill criteria in more than one group. Figure 1 contains details of proposed EHR workflow. After criteria are met, whomever is next in the chart with RN or MD user-type, will receive an interruptive alert via the EHR; simultaneously a page will automatically be sent by the EHR to a crisis nurse who will assess the patient and notify the primary MD and RN.
Electronic early warning systems and predictive analytic tools lack rigorous evaluation and standardization. There are literature demonstrating unintended consequences and even harms from the implementation of electronic health records and clinical decision support tools. As such, this is a situation of clinical equipoise in which it is unclear whether this quality improvement initiative will benefit patient care or not. To evaluate this question, the severe sepsis BPA will be initiated in a randomized fashion with each patient randomly assigned to either potentially generate this alert as described above or to generate this alert silently such that only quality improvement staff will be aware that criteria have been met via the EHR.
This is a randomized, single-blind prospective quality improvement study. Patients will be randomized by encounter to have the BPA visible or invisible during hospital admission. If visible, the alert will display to the primary nurse and physician and send a page to a crisis nurse when BPA criteria are met. If invisible, the alert will be triggered but will be invisible to the care team (only visible to quality improvement staff via the EHR)
- Inclusion criteria
- Admitted to Stanford Hospital (inpatient or observation status) to any medical or surgical service for at least 24 hours during the period of the study
- Exclusion criteria
- Admitted to an intensive-care level service (MICU, SICU, CVICU, CCU)
- While ideally we will make this available to ICU patients, the alert is likely to be far less specific in ICU patients and less clinically useful given the high level of care (eg 1:1 nursing and hourly vital signs).
- Patient code status is DNR/C (comfort care only)
- These patients would not be appropriate to treat with antibiotics and aggressive care generally give the comfort care goals of care.
- Emergency Department patients (may be included in the near future)
- Primary endpoints
- Percentage of patients receiving antibiotics within three hours
- Secondary endpoints
- Percentage of patients with hypotension or lactate >= 4 who received at least 30 ml/kg fluid
- Rate of 3 hour sepsis bundle completion (serum lactate, blood cultures, antibiotics)
- Length of hospital stay
- Cost of hospital stay per day and overall cost
- Mortality at hospital discharge
- Sample size and duration
- Based on prior studies, we predict a 10-15% difference in one or more primary endpoints (see Sawyer et. Al, Crit Care Med. 2011 March, 39:469)
- We therefore anticipate enrolling 1500 patients, an estimated 150 of whom will have true sepsis, over approximately six months, to achieve 80% power.
- Analysis will compare endpoints among all patients in the treatment and control groups
- Early stopping will be decided by an oversight committee which will review data at 3 months. If there is statistically significant different of more than 10% between groups, the study will be terminated early and in discussion with hospital quality and safety committee, use whichever strategy is superior for all patients in the hospital.
- Conditions
- Severe Sepsis
- Being tested
- Severe sepsis early warning best practice alert, Standard care
- Keywords
- severe sepsis infection
- Medical subject headings
- Sepsis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Severe sepsis early warning best practice alertBehavioural
Standard careBehavioural
| Study group | Role | What they receive |
|---|---|---|
| Severe sepsis early warning best practice alert | Active comparator | Patients in this arm will actively generate the alert. Receives: Behavioral: Severe sepsis early warning best practice alert |
| Standard care | Placebo comparator | This arm will be the current standard of care and will not generate the alert. Receives: Behavioral: Standard care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Percentage of patients with an antibiotic order within 3 hours of the alert
Time from when the alert fires until appropriate antibiotics are ordered will be measured via the electronic health record and a sample of cases will be verified by manual chart review.
Measured: 3 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted3 Mar 2015 (estimated)
- Study startNov 2014
- Primary completionMar 2015
- Study completionMar 2015
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Severe SepsisStudies of the same condition, open and under way.
- More trials run by Stanford UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind
- Who is masked
- Care provider
- Enrolment
- 1,149 participants (actual)
Sponsor and investigators
- Lead sponsor
- Stanford University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, N. Lance Downing, MD, Stanford University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02376842
- Sponsor's protocol ID
- 3675309
- Status last verified
- Nov 2015
- First submitted
- 3 Oct 2014
- Last updated
- 17 Nov 2015
- Results posted
- No
- Data monitoring committee
- No
Publications
Westphal GA, Koenig A, Caldeira Filho M, Feijo J, de Oliveira LT, Nunes F, Fujiwara K, Martins SF, Roman Goncalves AR. Reduced mortality after the implementation of a protocol for the early detection of severe sepsis. J Crit Care. 2011 Feb;26(1):76-81. doi: 10.1016/j.jcrc.2010.08.001. Epub 2010 Oct 30.
PubMed 21036531Nelson JL, Smith BL, Jared JD, Younger JG. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011 May;57(5):500-4. doi: 10.1016/j.annemergmed.2010.12.008. Epub 2011 Jan 12.
PubMed 21227543Brandt BN, Gartner AB, Moncure M, Cannon CM, Carlton E, Cleek C, Wittkopp C, Simpson SQ. Identifying severe sepsis via electronic surveillance. Am J Med Qual. 2015 Nov-Dec;30(6):559-65. doi: 10.1177/1062860614541291. Epub 2014 Jun 26.
PubMed 24970280
Study at a glance
From the registry record, last updated by the sponsor on 17 Nov 2015. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Single-blind Randomized Trial of a Commercially Sold Electronic Health Record Based Severe Sepsis Early Warning Best Practice Alert.
- ClinicalTrials.gov ID
- NCT02376842
- Acronym / sponsor ID
- 3675309
- Conditions
- Severe Sepsis
- Keywords
- severe sepsis infection
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 1,149 participants (actual)
- Lead sponsor
- Stanford UniversityUniversity, hospital or other
- Study start
- Nov 2014
- Primary completion
- Mar 2015 (actual)
- Study completion
- Mar 2015 (actual)
- First posted
- 3 Mar 2015 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The investigators hypothesize that implementing an electronic health record-based early warning system for severe infections (severe sepsis) will decrease the time to antibiotic order. The study will consist of an algorithm which will monitor lab values, vital signs, and nursing documentation for signs of severe sepsis. When these criteria are met, an alert will be delivered via the electronic health record to a nurse and doctor and simultaneously an alert via pager to another nurse. The investigators plan to randomize which patients will generate these alerts and analyze the data after collecting information for approximately 6 months which will be sufficient to detect a 10% difference in the two patient groups.
Detailed description
Sepsis is the leading cause of mortality at Stanford Hospital and ranks only 54th out of 119 hospitals according to UHC data with approximately 60 episodes of documented sepsis per quarter. Based on some preliminary data, there is concern that sepsis is both being recognized late and not treated in a timely enough fashion. In fact, there are evidence and expert guidelines that suggestion-delaying antibiotics in a patient with septic shock can increase mortality by 6.7% per hour (1C recommendation in severe sepsis by the Surviving Sepsis Campaign authors). As part of a hospital wide initiative to improve our treatment of sepsis and ultimately reduce sepsis-related mortality, an EHR-based clinical decision support (aka BPA) will be implemented. This BPA will be an algorithm that will alert practitioners and trigger clinical workflow after criteria are met. Criteria include lab values, vital signs and nursing flow sheet descriptions of perfusion (Table 1). The algorithm will alert when, in a 24 hour period, three criteria from the manifestation group, one criteria from the suspected infection group and one criteria from the organ dysfunction group. Note that one variable (eg creatinine > 2) can fulfill criteria in more than one group. Figure 1 contains details of proposed EHR workflow. After criteria are met, whomever is next in the chart with RN or MD user-type, will receive an interruptive alert via the EHR; simultaneously a page will automatically be sent by the EHR to a crisis nurse who will assess the patient and notify the primary MD and RN.
Electronic early warning systems and predictive analytic tools lack rigorous evaluation and standardization. There are literature demonstrating unintended consequences and even harms from the implementation of electronic health records and clinical decision support tools. As such, this is a situation of clinical equipoise in which it is unclear whether this quality improvement initiative will benefit patient care or not. To evaluate this question, the severe sepsis BPA will be initiated in a randomized fashion with each patient randomly assigned to either potentially generate this alert as described above or to generate this alert silently such that only quality improvement staff will be aware that criteria have been met via the EHR.
This is a randomized, single-blind prospective quality improvement study. Patients will be randomized by encounter to have the BPA visible or invisible during hospital admission. If visible, the alert will display to the primary nurse and physician and send a page to a crisis nurse when BPA criteria are met. If invisible, the alert will be triggered but will be invisible to the care team (only visible to quality improvement staff via the EHR)
- Inclusion criteria
- Admitted to Stanford Hospital (inpatient or observation status) to any medical or surgical service for at least 24 hours during the period of the study
- Exclusion criteria
- Admitted to an intensive-care level service (MICU, SICU, CVICU, CCU)
- While ideally we will make this available to ICU patients, the alert is likely to be far less specific in ICU patients and less clinically useful given the high level of care (eg 1:1 nursing and hourly vital signs).
- Patient code status is DNR/C (comfort care only)
- These patients would not be appropriate to treat with antibiotics and aggressive care generally give the comfort care goals of care.
- Emergency Department patients (may be included in the near future)
- Primary endpoints
- Percentage of patients receiving antibiotics within three hours
- Secondary endpoints
- Percentage of patients with hypotension or lactate >= 4 who received at least 30 ml/kg fluid
- Rate of 3 hour sepsis bundle completion (serum lactate, blood cultures, antibiotics)
- Length of hospital stay
- Cost of hospital stay per day and overall cost
- Mortality at hospital discharge
- Sample size and duration
- Based on prior studies, we predict a 10-15% difference in one or more primary endpoints (see Sawyer et. Al, Crit Care Med. 2011 March, 39:469)
- We therefore anticipate enrolling 1500 patients, an estimated 150 of whom will have true sepsis, over approximately six months, to achieve 80% power.
- Analysis will compare endpoints among all patients in the treatment and control groups
- Early stopping will be decided by an oversight committee which will review data at 3 months. If there is statistically significant different of more than 10% between groups, the study will be terminated early and in discussion with hospital quality and safety committee, use whichever strategy is superior for all patients in the hospital.
Study design
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (care provider)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Severe sepsis early warning best practice alert | Active comparator | Behavioral: Severe sepsis early warning best practice alertPatients in this arm will actively generate the alert. |
| Standard care | Placebo comparator | Behavioral: Standard careThis arm will be the current standard of care and will not generate the alert. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (1 listed)
- Admitted to Stanford Hospital (inpatient or observation status) to any medical or surgical service for at least 24 hours during the period of the study
Key exclusion criteria (4 listed)
- Admitted to an intensive-care level service (MICU, SICU, CVICU, CCU)
- Patient code status is DNR/C (comfort care only)
- Patients less than 18 years of age at time of admission.
- Emergency Department patients (may be included in the near future)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Severe sepsis early warning best practice alert | Behavioural | Severe sepsis early warning best practice alert |
| Standard care | Behavioural | Standard care |
Primary outcome
Percentage of patients with an antibiotic order within 3 hours of the alert
Time frame: 3 hours
Time from when the alert fires until appropriate antibiotics are ordered will be measured via the electronic health record and a sample of cases will be verified by manual chart review.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Nov 2015.
- Background: PubMed 21036531Westphal GA, Koenig A, Caldeira Filho M, Feijo J, de Oliveira LT, Nunes F, Fujiwara K, Martins SF, Roman Goncalves AR. Reduced mortality after the implementation of a protocol for the early detection of severe sepsis. J Crit Care. 2011 Feb;26(1):76-81. doi: 10.1016/j.jcrc.2010.08.001. Epub 2010 Oct 30.
- Background: PubMed 21227543Nelson JL, Smith BL, Jared JD, Younger JG. Prospective trial of real-time electronic surveillance to expedite early care of severe sepsis. Ann Emerg Med. 2011 May;57(5):500-4. doi: 10.1016/j.annemergmed.2010.12.008. Epub 2011 Jan 12.
- Results publication: PubMed 24970280Brandt BN, Gartner AB, Moncure M, Cannon CM, Carlton E, Cleek C, Wittkopp C, Simpson SQ. Identifying severe sepsis via electronic surveillance. Am J Med Qual. 2015 Nov-Dec;30(6):559-65. doi: 10.1177/1062860614541291. Epub 2014 Jun 26.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Severe sepsis early warning best practice alert in people with Severe Sepsis, run by Stanford University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 17 Nov 2015. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. Some participants in this study may receive a placebo. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Percentage of patients with an antibiotic order within 3 hours of the alert (time frame: 3 hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT02376842, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Nov 2015.