Medical ErrorsNCT02876588
Risk of Wrong-Patient Errors With Multiple Records Open
A study testing Unrestricted and Restricted in people with Medical Errors and Medical Order Entry Systems, run by Columbia University at 1 site in United States.
Trial summary
This study is designed to achieve the following aims: 1. Assess the relationship between the number of records open at the time of placing an order, and the risk of placing an order on the wrong patient. 2. Read more about this study
- Who is it for?
- Ages 21 to 100 years
- Conditions the study is for
- Medical Errors, Medical Order Entry Systems
- What is being tested?
- Unrestricted and Restricted
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 3,356 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Oct 2015to 30 Apr 2017
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
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 21 to 100 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Clinician Participant Inclusion Criteria:
-All clinicians (physicians, nurse practitioners, physician assistants) who placed electronic orders during the study period will be included in the study. (Randomization is at the level of the clinician.)
Clinician Exclusion Criteria:
- Clinicians whose workflow requires access to more than one patient record at a time.
Patient Record Inclusion Criteria:
-All inpatient, emergency department, and ambulatory patients for whom electronic orders were placed during the study period will be included in the study.
Trial locations and contacts
1 site in 1 country.
United States1 site
Montefiore Medical Center
The Bronx, New York, 10467
About this study
Official title: Assessing the Risk of Wrong-Patient Errors in an Electronic Health Record That Allows Multiple Records Open
This study is designed to achieve the following aims:
- Assess the relationship between the number of records open at the time of placing an order, and the risk of placing an order on the wrong patient.
- Compare the incidence of wrong-patient orders in a "restricted environment" that limits its providers to only one record open at a time to an "unrestricted environment" where users can open a maximum of four records at once.
- The results of this study will help inform decisions on how to safely implement EHR systems.
- The results of this study will inform a larger scale health IT implementation research project evaluating the balance between the wrong-patient error risks and potential efficiency gains of having multiple records open at once, with rigorous research methodologies.
Read the detailed description
Currently, at least 70,000 U.S. physicians use computerized provider order entry (CPOE) to place orders. This number is expected to rise sharply as hospitals continue to take advantage of federal incentives and adopt electronic health record (EHR) technology. Although CPOE is associated with a reduction in medical errors, when orders are placed electronically certain types of errors, including placing orders on the wrong patient, may occur more frequently.
Although there have been no studies quantifying (or even establishing) an increased risk of wrong-patient errors when providers have multiple records open at once, there have been several articles and expert opinions that warn of this potential risk.
The mechanism by which multiple patient records opened simultaneously can lead to a wrong-patient error may be related to the ease with which users can toggle between patient records and the similar looking computer screens. The magnitude of this risk needs to be established to help Information Technology (IT) leadership decide on how to safely implement CPOE systems.
There have been no studies demonstrating whether multiple records increase the risk of wrong-patient errors, by how much, and if any increase is dependent on the number of records open. This research project is an important first step in quantifying this risk.
In a randomized controlled trial conducted at Montefiore Medical Center, investigators propose to randomize inpatient and outpatient providers to a maximum of one record open at the time of ordering (restricted mode) or a maximum of four records open at the time of ordering (unrestricted mode).
Assignments will be made prior to the start of the study, and will remain constant throughout the study. A computer programmer working in IT, who is not an investigator of this study, will use Microsoft Excel to generate random numbers and assign one number to each provider. Providers assigned odd numbers will be in the restricted cohort, and those assigned even numbers will be in the unrestricted cohort. Providers who join Montefiore after the start of the study will be assigned a random number from Excel when assigned a new user log in for the EHR from a computer programmer not affiliated with the study, and will be added to the appropriate group based on their assigned random number. At the start of the randomized controlled trial, investigators will explain the purpose of the study to clinical staff via email and directly from within their IT systems, using a message crafted by the study team. The message will assure clinicians that data will be kept confidential and cooperation will carry no risk to them.
Montefiore uses the Epic Systems Corporation, or Epic, EHR system. Epic will implement the Retract-and-Reorder (RAR) tool, an automated method for identifying wrong-patient electronic orders, as well as capture the number of records open at the time of placing an order. This study will examine the effect of having the EHR system in restricted mode vs. unrestricted mode on RAR events. The goal is to obtain an estimate of the effect size and the intra-class correlations to provide preliminary data for a larger-scale health IT implementation research project. The unit of analysis will be the order. First, the RAR event rate for orders placed in the restricted vs. unrestricted mode will be calculated, testing the difference in rates using rank sum tests. Next, the relationship between the RAR event rate in restricted vs. unrestricted mode in subsets of providers and settings will be examined to determine whether specific types of providers or settings carry increased risk. Finally, a mixed-effects logistic regression model will be fitted with RAR event as the outcome and mode of the EHR system (restricted vs. unrestricted) as the independent variable of interest. The model will include random effects at the provider and order-session level because previous work has suggested substantial within-provider and within-session correlation. Orders will be nested in sessions and sessions will be nested in providers. To address the threat of confounding, the model will include fixed-effects variables including provider, patient, order-session, and order level covariates.
To safeguard against the possibility that the intervention actually worsens (increases) the RAR event rate, and to prevent unnecessary continuation of a study that is already conclusive, a data safety monitoring committee will conduct one interim review of the data in the randomized controlled trial.
- Conditions
- Medical Errors, Medical Order Entry Systems
- Being tested
- Unrestricted, Restricted
- Keywords
- Wrong-Patient Errors, Retract-and-Reorder measure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
UnrestrictedOther
Users may open up to 4 patient records at a time.
RestrictedOther
Users are restricted to open 1 patient record at a time.
| Study group | Role | What they receive |
|---|---|---|
| Unrestricted | Active comparator | Users have "unrestricted" access to open up to a maximum of 4 patient records at a time in the EHR Receives: Other: Unrestricted |
| Restricted | Active comparator | Users have "restricted" access to open a maximum of 1 patient record at a time in the EHR Receives: Other: Restricted |
What is being measured
The primary outcome is the main question the study is designed to answer.
Wrong-patient Order Sessions, Defined as Order Sessions That Include at Least One Wrong-Patient Retract-and-Reorder (RAR) Event, As-randomized Analysis
The primary analysis included all order sessions performed by clinicians according to their assigned randomization group. The primary outcome was wrong-patient order sessions, defined as order sessions that include at least 1 wrong-patient Retract-and-Reorder (RAR) event.
Wrong-patient order sessions were identified using the Wrong-Patient Retract-and-Reorder (RAR) measure. The Wrong-Patient RAR measure uses an electronic query to identify wrong-patient RAR events, defined as one or more orders placed for a patient that are retracted (cancelled) by the same provider within 10 minutes, and then reordered by the same provider for a different patient within the next 10 minutes.
Measured: 19-month study period. All order sessions placed by randomized clinicians during the study period were included in the analysis. The time frame for each participant varied.
Secondary outcomes (1)
Wrong-patient Order Sessions, Defined as Order Sessions That Include at Least One Wrong-Patient Retract-and-Reorder (RAR) Event, as Treated Analysis
The outcome was wrong-patient order sessions, defined as order sessions that include at least 1 wrong-patient Retract-and-Reorder (RAR) event. In the as treat analysis, each order was characterized by the clinician's initial configuration at the time an order was placed.
Wrong-patient order sessions were identified using the Wrong-Patient Retract-and-Reorder (RAR) measure. The Wrong-Patient RAR measure uses an electronic query to identify wrong-patient RAR events, defined as one or more orders placed for a patient that are retracted (cancelled) by the same provider within 10 minutes, and then reordered by the same provider for a different patient within the next 10 minutes.
Measured: 19-month study period. All order sessions placed by randomized clinicians during the study period were included in the analysis. The time frame for each participant varied.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Aug 2016 (estimated)
- Study start1 Oct 2015
- Primary completion30 Apr 2017
- Study completion30 Apr 2017
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (9)Papers the sponsor has linked to this study.
- Other trials for Medical ErrorsStudies of the same condition, open and under way.
- More trials run by Columbia 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
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 3,356 participants (actual)
Sponsor and investigators
- Lead sponsor
- Columbia University
- Sponsor type
- University, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Responsible party
- Sponsor
- Investigators
- Jason Adelman, MD, MS, Principal investigator, Columbia University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT02876588
- Sponsor's protocol ID
- AAAQ9954
- Other IDs
- R21HS023704
- Status last verified
- Jan 2025
- First submitted
- 3 Aug 2016
- Last updated
- 10 Feb 2025
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Research may request data from the PI (Jason Adelman). Partial, de-identified order data will be made available for research purposes for analyses approved by the researchers' Institutional Review Board and by the PI. Data will be made available upon approval.
Publications
Adelman J, Aschner J, Schechter C, Angert R, Weiss J, Rai A, Berger M, Reissman S, Parakkattu V, Chacko B, Racine A, Southern W. Use of Temporary Names for Newborns and Associated Risks. Pediatrics. 2015 Aug;136(2):327-33. doi: 10.1542/peds.2015-0007. Epub 2015 Jul 13.
PubMed 26169429Adelman JS, Kalkut GE, Schechter CB, Weiss JM, Berger MA, Reissman SH, Cohen HW, Lorenzen SJ, Burack DA, Southern WN. Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. J Am Med Inform Assoc. 2013 Mar-Apr;20(2):305-10. doi: 10.1136/amiajnl-2012-001055. Epub 2012 Jun 29.
PubMed 22753810Adelman JS, Aschner JL, Schechter CB, Angert RM, Weiss JM, Rai A, Parakkattu V, Goffman D, Applebaum JR, Racine AD, Southern WN. Babyboy/Babygirl: A National Survey on the Use of Temporary, Nondistinct Naming Conventions for Newborns in Neonatal Intensive Care Units. Clin Pediatr (Phila). 2017 Oct;56(12):1157-1159. doi: 10.1177/0009922817701178. Epub 2017 Apr 12. No abstract available.
PubMed 28403654Adelman JS, Berger MA, Rai A, Galanter WL, Lambert BL, Schiff GD, Vawdrey DK, Green RA, Salmasian H, Koppel R, Schechter CB, Applebaum JR, Southern WN. A national survey assessing the number of records allowed open in electronic health records at hospitals and ambulatory sites. J Am Med Inform Assoc. 2017 Sep 1;24(5):992-995. doi: 10.1093/jamia/ocx034.
PubMed 28419267Adelman JS, Aschner JL, Schechter CB, Angert RM, Weiss JM, Rai A, Berger MA, Reissman SH, Yongue C, Chacko B, Dadlez NM, Applebaum JR, Racine AD, Southern WN. Evaluating Serial Strategies for Preventing Wrong-Patient Orders in the NICU. Pediatrics. 2017 May;139(5):e20162863. doi: 10.1542/peds.2016-2863.
PubMed 28557730Kannampallil TG, Manning JD, Chestek DW, Adelman J, Salmasian H, Lambert BL, Galanter WL. Effect of number of open charts on intercepted wrong-patient medication orders in an emergency department. J Am Med Inform Assoc. 2018 Jun 1;25(6):739-743. doi: 10.1093/jamia/ocx099.
PubMed 29025090Wachter RM, Murray SG, Adler-Milstein J. Restricting the Number of Open Patient Records in the Electronic Health Record: Is the Record Half Open or Half Closed? JAMA. 2019 May 14;321(18):1771-1773. doi: 10.1001/jama.2019.3835. No abstract available.
PubMed 31087007Adelman JS, Applebaum JR, Schechter CB, Berger MA, Reissman SH, Thota R, Racine AD, Vawdrey DK, Green RA, Salmasian H, Schiff GD, Wright A, Landman A, Bates DW, Koppel R, Galanter WL, Lambert BL, Paparella S, Southern WN. Effect of Restriction of the Number of Concurrently Open Records in an Electronic Health Record on Wrong-Patient Order Errors: A Randomized Clinical Trial. JAMA. 2019 May 14;321(18):1780-1787. doi: 10.1001/jama.2019.3698.
PubMed 31087021Southern WN, Applebaum JR, Salmasian H, Kneifati-Hayek J, Carter EJ, Sumner JA, Adelman JS. Clinician Experience of Electronic Health Record Configurations Displaying 1 vs 4 Records at a Time. JAMA Intern Med. 2019 Dec 1;179(12):1723-1725. doi: 10.1001/jamainternmed.2019.3688.
PubMed 31524923
Study at a glance
From the registry record, last updated by the sponsor on 10 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessing the Risk of Wrong-Patient Errors in an Electronic Health Record That Allows Multiple Records Open
- ClinicalTrials.gov ID
- NCT02876588
- Acronym / sponsor ID
- AAAQ9954
- Conditions
- Medical Errors, Medical Order Entry Systems
- Keywords
- Wrong-Patient Errors, Retract-and-Reorder measure
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 3,356 participants (actual)
- Lead sponsor
- Columbia UniversityUniversity, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Study start
- 1 Oct 2015 (actual)
- Primary completion
- 30 Apr 2017 (actual)
- Study completion
- 30 Apr 2017 (actual)
- First posted
- 24 Aug 2016 (estimated)
- Results
- Posted 10 Feb 2025
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study is designed to achieve the following aims:
- Assess the relationship between the number of records open at the time of placing an order, and the risk of placing an order on the wrong patient.
- Compare the incidence of wrong-patient orders in a "restricted environment" that limits its providers to only one record open at a time to an "unrestricted environment" where users can open a maximum of four records at once.
- The results of this study will help inform decisions on how to safely implement EHR systems.
- The results of this study will inform a larger scale health IT implementation research project evaluating the balance between the wrong-patient error risks and potential efficiency gains of having multiple records open at once, with rigorous research methodologies.
Detailed description
Currently, at least 70,000 U.S. physicians use computerized provider order entry (CPOE) to place orders. This number is expected to rise sharply as hospitals continue to take advantage of federal incentives and adopt electronic health record (EHR) technology. Although CPOE is associated with a reduction in medical errors, when orders are placed electronically certain types of errors, including placing orders on the wrong patient, may occur more frequently.
Although there have been no studies quantifying (or even establishing) an increased risk of wrong-patient errors when providers have multiple records open at once, there have been several articles and expert opinions that warn of this potential risk.
The mechanism by which multiple patient records opened simultaneously can lead to a wrong-patient error may be related to the ease with which users can toggle between patient records and the similar looking computer screens. The magnitude of this risk needs to be established to help Information Technology (IT) leadership decide on how to safely implement CPOE systems.
There have been no studies demonstrating whether multiple records increase the risk of wrong-patient errors, by how much, and if any increase is dependent on the number of records open. This research project is an important first step in quantifying this risk.
In a randomized controlled trial conducted at Montefiore Medical Center, investigators propose to randomize inpatient and outpatient providers to a maximum of one record open at the time of ordering (restricted mode) or a maximum of four records open at the time of ordering (unrestricted mode).
Assignments will be made prior to the start of the study, and will remain constant throughout the study. A computer programmer working in IT, who is not an investigator of this study, will use Microsoft Excel to generate random numbers and assign one number to each provider. Providers assigned odd numbers will be in the restricted cohort, and those assigned even numbers will be in the unrestricted cohort. Providers who join Montefiore after the start of the study will be assigned a random number from Excel when assigned a new user log in for the EHR from a computer programmer not affiliated with the study, and will be added to the appropriate group based on their assigned random number. At the start of the randomized controlled trial, investigators will explain the purpose of the study to clinical staff via email and directly from within their IT systems, using a message crafted by the study team. The message will assure clinicians that data will be kept confidential and cooperation will carry no risk to them.
Montefiore uses the Epic Systems Corporation, or Epic, EHR system. Epic will implement the Retract-and-Reorder (RAR) tool, an automated method for identifying wrong-patient electronic orders, as well as capture the number of records open at the time of placing an order. This study will examine the effect of having the EHR system in restricted mode vs. unrestricted mode on RAR events. The goal is to obtain an estimate of the effect size and the intra-class correlations to provide preliminary data for a larger-scale health IT implementation research project. The unit of analysis will be the order. First, the RAR event rate for orders placed in the restricted vs. unrestricted mode will be calculated, testing the difference in rates using rank sum tests. Next, the relationship between the RAR event rate in restricted vs. unrestricted mode in subsets of providers and settings will be examined to determine whether specific types of providers or settings carry increased risk. Finally, a mixed-effects logistic regression model will be fitted with RAR event as the outcome and mode of the EHR system (restricted vs. unrestricted) as the independent variable of interest. The model will include random effects at the provider and order-session level because previous work has suggested substantial within-provider and within-session correlation. Orders will be nested in sessions and sessions will be nested in providers. To address the threat of confounding, the model will include fixed-effects variables including provider, patient, order-session, and order level covariates.
To safeguard against the possibility that the intervention actually worsens (increases) the RAR event rate, and to prevent unnecessary continuation of a study that is already conclusive, a data safety monitoring committee will conduct one interim review of the data in the randomized controlled trial.
Study design
- Primary purpose
- Other
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Unrestricted | Active comparator | Other: UnrestrictedUsers have "unrestricted" access to open up to a maximum of 4 patient records at a time in the EHR |
| Restricted | Active comparator | Other: RestrictedUsers have "restricted" access to open a maximum of 1 patient record at a time in the EHR |
Who may qualify
- Ages
- 21 to 100 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
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 |
|---|---|---|
| UnrestrictedUsers may open up to 4 patient records at a time. | Other | Unrestricted |
| RestrictedUsers are restricted to open 1 patient record at a time. | Other | Restricted |
Primary outcome
Wrong-patient Order Sessions, Defined as Order Sessions That Include at Least One Wrong-Patient Retract-and-Reorder (RAR) Event, As-randomized Analysis
Time frame: 19-month study period. All order sessions placed by randomized clinicians during the study period were included in the analysis. The time frame for each participant varied.
The primary analysis included all order sessions performed by clinicians according to their assigned randomization group. The primary outcome was wrong-patient order sessions, defined as order sessions that include at least 1 wrong-patient Retract-and-Reorder (RAR) event. Wrong-patient order sessions were identified using the Wrong-Patient Retract-and-Reorder (RAR) measure. The Wrong-Patient RAR measure uses an electronic query to identify wrong-patient RAR events, defined as one or more orders placed for a patient that are retracted (cancelled) by the same provider within 10 minutes, and then reordered by the same provider for a different patient within the next 10 minutes.
1 secondary outcome
Wrong-patient Order Sessions, Defined as Order Sessions That Include at Least One Wrong-Patient Retract-and-Reorder (RAR) Event, as Treated Analysis
Time frame: 19-month study period. All order sessions placed by randomized clinicians during the study period were included in the analysis. The time frame for each participant varied.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Feb 2025.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 26169429Adelman J, Aschner J, Schechter C, Angert R, Weiss J, Rai A, Berger M, Reissman S, Parakkattu V, Chacko B, Racine A, Southern W. Use of Temporary Names for Newborns and Associated Risks. Pediatrics. 2015 Aug;136(2):327-33. doi: 10.1542/peds.2015-0007. Epub 2015 Jul 13.
- Background: PubMed 22753810Adelman JS, Kalkut GE, Schechter CB, Weiss JM, Berger MA, Reissman SH, Cohen HW, Lorenzen SJ, Burack DA, Southern WN. Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. J Am Med Inform Assoc. 2013 Mar-Apr;20(2):305-10. doi: 10.1136/amiajnl-2012-001055. Epub 2012 Jun 29.
- Background: PubMed 28403654Adelman JS, Aschner JL, Schechter CB, Angert RM, Weiss JM, Rai A, Parakkattu V, Goffman D, Applebaum JR, Racine AD, Southern WN. Babyboy/Babygirl: A National Survey on the Use of Temporary, Nondistinct Naming Conventions for Newborns in Neonatal Intensive Care Units. Clin Pediatr (Phila). 2017 Oct;56(12):1157-1159. doi: 10.1177/0009922817701178. Epub 2017 Apr 12. No abstract available.
- Background: PubMed 28419267Adelman JS, Berger MA, Rai A, Galanter WL, Lambert BL, Schiff GD, Vawdrey DK, Green RA, Salmasian H, Koppel R, Schechter CB, Applebaum JR, Southern WN. A national survey assessing the number of records allowed open in electronic health records at hospitals and ambulatory sites. J Am Med Inform Assoc. 2017 Sep 1;24(5):992-995. doi: 10.1093/jamia/ocx034.
- Background: PubMed 28557730Adelman JS, Aschner JL, Schechter CB, Angert RM, Weiss JM, Rai A, Berger MA, Reissman SH, Yongue C, Chacko B, Dadlez NM, Applebaum JR, Racine AD, Southern WN. Evaluating Serial Strategies for Preventing Wrong-Patient Orders in the NICU. Pediatrics. 2017 May;139(5):e20162863. doi: 10.1542/peds.2016-2863.
- Background: PubMed 29025090Kannampallil TG, Manning JD, Chestek DW, Adelman J, Salmasian H, Lambert BL, Galanter WL. Effect of number of open charts on intercepted wrong-patient medication orders in an emergency department. J Am Med Inform Assoc. 2018 Jun 1;25(6):739-743. doi: 10.1093/jamia/ocx099.
- Background: PubMed 31087007Wachter RM, Murray SG, Adler-Milstein J. Restricting the Number of Open Patient Records in the Electronic Health Record: Is the Record Half Open or Half Closed? JAMA. 2019 May 14;321(18):1771-1773. doi: 10.1001/jama.2019.3835. No abstract available.
- Results publication: PubMed 31087021Adelman JS, Applebaum JR, Schechter CB, Berger MA, Reissman SH, Thota R, Racine AD, Vawdrey DK, Green RA, Salmasian H, Schiff GD, Wright A, Landman A, Bates DW, Koppel R, Galanter WL, Lambert BL, Paparella S, Southern WN. Effect of Restriction of the Number of Concurrently Open Records in an Electronic Health Record on Wrong-Patient Order Errors: A Randomized Clinical Trial. JAMA. 2019 May 14;321(18):1780-1787. doi: 10.1001/jama.2019.3698.
- Derived from this study: PubMed 31524923Southern WN, Applebaum JR, Salmasian H, Kneifati-Hayek J, Carter EJ, Sumner JA, Adelman JS. Clinician Experience of Electronic Health Record Configurations Displaying 1 vs 4 Records at a Time. JAMA Intern Med. 2019 Dec 1;179(12):1723-1725. doi: 10.1001/jamainternmed.2019.3688.
- Individual participant dataSharing planned: Yes. Research may request data from the PI (Jason Adelman). Partial, de-identified order data will be made available for research purposes for analyses approved by the researchers' Institutional Review Board and by the PI. Data will be made available upon approval.
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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.
Jason Adelman, MD, MS principal investigator
Columbia University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Unrestricted and Restricted in people with Medical Errors and Medical Order Entry Systems, run by Columbia 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?
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 10 Feb 2025. 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. 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?
Yes. Results are posted in the registry (first posted 10 Feb 2025). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
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?
Wrong-patient Order Sessions, Defined as Order Sessions That Include at Least One Wrong-Patient Retract-and-Reorder (RAR) Event, As-randomized Analysis (time frame: 19-month study period. All order sessions placed by randomized clinicians during the study period were included in the analysis. The time frame for each participant varied.). 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 NCT02876588, which also lists 9 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 10 Feb 2025; AzTrials last refreshed its copy on 28 Oct 2026.