The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index; none of the 25 sources its claims cite is checked for support yet.
Prescription Errors and Outcomes Related to Inconsistent Information Transmitted Through Computerized Order Entry: A Prospective Study
Open accessAbstract
BACKGROUND: Although several types of computerized provider order entry (CPOE)-related errors may occur, errors related to inconsistent information within the same prescription (ie, mismatch between the structured template and the associated free-text field) have not been described, to our knowledge. We determined the nature and frequency of such errors and identified their potential predictive variables. METHODS: In this prospective study, we enrolled pharmacists to report prescriptions containing inconsistent communication over a 4-month period at a tertiary care facility. We also electronically retrieved all prescriptions written during the study period containing any comments in the free-text field and then randomly selected 500 for manual review to determine inconsistencies between free-text and structured fields. Of these, prescriptions without inconsistencies were categorized as controls. Data on potentially predictive variables from reported and unreported errors and controls were collected. For all inconsistencies, we determined their nature (eg, drug dosage or administration schedule) and potential harm and used multivariate logistic regression models to identify factors associated with errors and harm. RESULTS: Of 55 992 new prescriptions, 532 (0.95%) were reported to contain inconsistent communication, a rate comparable to that obtained from the unreported group. Drug dosage was the most common inconsistent element among both groups. Certain medications were more likely associated with errors, as was the inpatient setting (odds ratio, 3.30; 95% confidence interval, 2.18-5.00) and surgical subspecialty (odds ratio, 2.45; 95% confidence interval, 1.57-3.82). About 20% of errors could have resulted in moderate to severe harm, for which significant independent predictors were found. CONCLUSIONS: Despite standardization of data entry, inconsistent communication in CPOE poses a significant risk to safety. Improving the usability of the CPOE interface and integrating it with workflow may reduce this risk.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Medications needing a complex order (eg, a tapering dose of prednisone) were highly correlated with error.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:boosted· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Second, comments were transferred to the new prescription when modifying an existing prescription.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Certain medication classes were also more likely to have errors, with the highest odds of error occurring for steroids (OR, 7.62; 95% CI, 3.11–18.63) compared with analgesics.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Most errors (68.3%) occurred in prescriptions for inpatients,”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“112 errors could have resulted in moderate to severe harm (considerable, very serious, serious permanent damage, or death) (20.1%).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Orders with inconsistent communication were most commonly entered by trainees (59.0%), followed by attending physicians (24.9%), physician assistants (10.2%), and nurse practitioners (5.4%).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the 26 unreported errors, dosage inconsistency was also the most common (n=10; data not shown).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedn = 10Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of 55 992 new prescriptions processed and reviewed by the pharmacists in the study period, 532 were reported by pharmacists to contain inconsistent communication (0.95%).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“and 19.0% (n=103) had 2 or more inconsistencies.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedn = 103Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The most common inconsistent element across reported prescriptions was drug dosage (44.9%),”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passes
- It may state two separate claims as one. 17
- Probably not a substantial claim. 15
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Pharmacists used the free-text comment in 88.9% of cases to fill the final prescription, the structured template in 9.2% of cases, and in combination in the remainder (1.9%).”
- Also stated in: § COMMENT · hedged
“in over 90% of cases the pharmacists used the free-text information either by itself or combined it with information from the structured template”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § COMMENT · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Only 2 reported errors were discovered after reaching the patient and did not result in harm.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The following variables differed significantly between the 2 groups: ordering provider type (P=.04) and specialty (P<.001), inpatient vs outpatient setting (P<.001), and medication class (P<.001).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of note, 23.1% of unreported errors could have resulted in moderate to severe harm, statistically no different from reported errors (P=.62).”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Inpatient setting (OR, 3.30; 95% CI, 2.18–5.00) and non–primary care specialties such as surgery (OR, 2.45; 95% CI, 1.57–3.82) were more likely to have errors.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > RESULTS
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“many types of CPOE-related errors have been described in recent years.5–10”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND
What the sources say
- Not checked yetcites [5] Ash JS Berg M Coiera E Some unintended consequences of information technology in health care: the nature of patient care information system-related errors J Am Med Inform Assoc 2004 March 11 2 104 12 14633936 PMC353015
- Not checked yetcites [6] Berger RG Kichak JP Computerized physician order entry: helpful or harmful? J Am Med Inform Assoc 2004 March 11 2 100 3 14633934 PMC353014
- Not checked yetcites [7] Harrison MI Koppel R Bar-Lev S Unintended consequences of information technologies in health care--an interactive sociotechnical analysis J Am Med Inform Assoc 2007 September 14 5 542 9 17600093 PMC1975796
- Not checked yetcites [8] Horsky J Kuperman GJ Patel VL Comprehensive analysis of a medication dosing error related to CPOE Journal Of The American Medical Informatics Association: JAMIA 12 4 377 82 15802485 PMC1174881
- Not checked yetcites [9] Koppel R Metlay JP Cohen A Role of computerized physician order entry systems in facilitating medication errors JAMA 2005 March 9 293 10 1197 203 15755942
- Not checked yetcites [10] Weiner JP Kfuri T Chan K Fowles JB “e-Iatrogenesis”: the most critical unintended consequence of CPOE and other HIT J Am Med Inform Assoc 2007 May 14 3 387 8 17329719 PMC2244888
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We obtained a comparable estimate of error rate (ie, 1%) using both reporting and electronic search, adding strength to our findings.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“approved by the local institutional review board and the MEDVAMC research and development committee.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND > Methods
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although most errors we studied did not reach the patient because of pharmacist intervention, they pose a significant potential risk to patients.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Additional study strengths include a large variety of medications, a large number of providers (>500), and an advanced CPOE system fairly representative of other systems.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The advanced CPOE system used in the study is fairly representative of other CPOE systems.
In the paper
“Chused et al21 recently reported communication failures resulting from free-text comments entered in response to alert overrides, suggesting that commercial CPOE systems may not also protect against the problem.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
What the sources say
- Not checked yetcites Chused et al21
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although defaults can be helpful, they may not be comprehensive and may be based on inventory rather than clinical guidelines.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The potential for moderate to severe harm is likely more significant given the expected increase in the volume of prescriptions written through future CPOE systems.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
In the paper
“Because poor communication is an often-cited preventable factor in adverse events,15”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND
What the sources say
- Not checked yetcites [15] Joint Commission on Accreditation of Healthcare Organizations Sentinel event statistics, March 31, 2006 Joint Commission on Accreditation of Healthcare Organizations 2005 Available at: URL: http://www.jointcommission.org/NR/rdonlyres/FA465646-5F5F-4543-AC8F-E8AF6571E372/0/root_cause_se.jpg 17139928
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we found errors that could be prevented by minor modifications in the CPOE template regarding administration time or duration and/or stop time for a medication.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“To ensure that the model had stable and precise estimates of ORs, variables with small numbers of patients with a given characteristic (eg, ordering providers listed as clinical support, clinical specialist, or unknown) were removed or combined (eg, geriatrics, other medicine, spinal cord injury, and psychiatry specialties were all combined as “other specialties” in the model to predict harm), and”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND > Data Analysis
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Only slightly more than two-thirds of eligible pharmacists participated in the study, and hence there is almost certainly selection bias.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Strength:boosted· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear? Based: unclearIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Even though most errors of inconsistent communication would have caused inconvenience or minor harm, the potential for more severe harm is significant, given the large volume of prescriptions written.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“A generalized estimating equation approach in which errors were nested within providers allowed us to account for the potential correlation among errors.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND > Data Analysis
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“while it is likely that similar communication breakdowns occur in other Veterans Affairs facilities using the same CPOE system, we ac-knowledge that the true prevalence across Veterans Affairs institutions is unknown.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the free-text comments are printed on the label of the dispensed medication, which may confuse or harm the patient.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
- Rests on an assumption: Free-text comments are printed on the label of the dispensed medication.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“simple training on the use of complex orders for certain prescriptions could reduce errors.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
In the paper
“a study using both qualitative and quantitative methods to study house staff interaction with a CPOE system at a tertiary care facility identified 22 different types of medication errors, including fragmented CPOE displays and inflexible ordering formats.9”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND
What the sources say
- Not checked yetcites [9] Koppel R Metlay JP Cohen A Role of computerized physician order entry systems in facilitating medication errors JAMA 2005 March 9 293 10 1197 203 15755942
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“It was conducted at a single site where all providers used the same CPOE system, and although it involved a large number of patients and providers, including trainees, generalizability may be limited.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Strength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
In the paper
“Two investigators (a physician and pharmacist) assigned harm categories by consensus using the Human Error Consequence Scale20 after evaluating the results from the initial data collection.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND > Data Collection
What the sources say
- Not checked yetcites [20] Gilpatrick E Health Services Mobility Study Final Report (October 1967-March 1972) New York, NY City Univ. of New York Research Foundation 1972 Jan 1 Report No.: ERIC Reports ED066613
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the free text window offers a valuable option to communicate clarifications or nonstandard information.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > COMMENT
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Of 45 pharmacists, 33 agreed to report errors.”
§ Prescription Errors and Outcomes Related to Inconsistent Information Transmitted through Computerized Order-Entry: A Prospective Study > BACKGROUND > Methods
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
Order entry errors related to inconsistent information within the same prescription had not been described before this study.
“To our knowledge, order entry errors related to inconsistent information within the same prescription have not been described.”
The paper relies on this without support.
This is the first study reporting errors of communication due to free-text comments in CPOE systems.
“To our knowledge, this is also the first study reporting errors of communication due to free-text comments in CPOE systems.”
The paper relies on this without support.
All CPOE systems have some method of entering free text.
“All CPOE systems have some method of entering free text.”
The paper relies on this without support.
Underreporting is a well-recognized phenomenon in similar studies.
“Because underreporting is a well recognized phenomenon in similar studies”
The paper relies on this without support.
Free-text comments are printed on the label of the dispensed medication.
“the free-text comments are printed on the label of the dispensed medication”
The paper relies on this without support.
The advanced CPOE system used in the study is fairly representative of other CPOE systems.
“an advanced CPOE system fairly representative of other systems”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In particular, rapid adoption of electronic health records (EHRs) has revealed potential safety concerns related to EHR design, implementation, and use.12 17–21”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [17]
In the citing paper
“the increasing adoption of electronic health records (EHR) has revealed potential safety implications related to EHR design, implementation, and use.”
From Exploring the sociotechnical intersection of patient safety and electronic health record implementation (2014) · cites this paper as [11]
Citations
Cites
Institute of Medicine (2000) · National Academies Press eBooks · doi:10.17226/9728 · Cited by 14,390
Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention
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Role of Computerized Physician Order Entry Systems in Facilitating Medication Errors
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Ash, J. S. (2003) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1471 · Cited by 1,789 · cited 1×
“Our study adds to the growing body of knowledge that computerized information systems may introduce new types of errors, including those involving communication processes.(5,25) Future studies should address the usability of the CPOE interface to identify breakdown points and maximize the effectiveness, efficiency, an…”
Background(2003) · CRC Press eBooks · doi:10.1201/9780367804787 · Cited by 1,227
Types of Unintended Consequences Related to Computerized Provider Order Entry
Campbell, E. M., Sittig, D. F., Ash, J. S., Guappone, K. P., & Dykstra, R. H. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2042 · Cited by 823
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Measuring errors and adverse events in health care
Thomas, E. J., & Petersen, L. A. (2003) · Journal of General Internal Medicine · doi:10.1046/j.1525-1497.2003.20147.x · Cited by 456 · cited 1×
“17 To overcome some of these disadvantages, we electronically searched for similar types of errors.”
MethodSelf-citationHarnessing the Power of Default Options to Improve Health Care
Halpern, S. D., Ubel, P. A., & Asch, D. A. (2007) · New England Journal of Medicine · doi:10.1056/nejmsb071595 · Cited by 370 · cited 1×
“While default options may improve care in some settings, 22 our results suggest a need for more careful consideration before their use.”
Background
Flagged first, then by citations
1 of the 29 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- [15]Joint Commission on Accreditation of Healthcare Organizations Sentinel event statistics, March 31, 2006 Joint Commission on Accreditation of Healthcare Organizations 2005 Available at: URL: http://www.jointcommission.org/NR/rdonlyres/FA465646-5F5F-4543-AC8F-E8AF6571E372/0/root_cause_se.jpg 17139928
- [26]Schoeffel R The concept of product usability ISO Bulletin 34[3], 6–7 2003 Ref Type: Generic
Cited by
Sorted by citations
Types and Origins of Diagnostic Errors in Primary Care Settings
Singh, H., Giardina, T. D., Meyer, A. N. D., Forjuoh, S. N., Reis, M. D., & Thomas, E. J. (2013) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2013.2777 · Cited by 559
Self-citationHealth IT and Patient Safety: Building Safer Systems for Better Care
Chou, D. (2012) · JAMA · doi:10.1001/jama.308.21.2282-a · Cited by 496
Kim, M. O., Coiera, E., & Magrabi, F. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw154 · Cited by 263
“…(2005)42 548 7 Mortality increased from 2.8% to 6.7%, no further details provided Nanji et al. (2011)40 466 35 N/A Palchuk et al. (2010)39 470 84 N/A Singh et al. (2009)29 558a 71 N/A Walsh et al. (2006)38 20 50 N/A 50 Westbrook et al. (2012)51 and (2013)41 493 2 N/A aErrors analyzed for…”
BackgroundInfluentialAn analysis of electronic health record-related patient safety concerns
Meeks, D. W., Smith, M. W., Taylor, L., Sittig, D. F., Scott, J. M., & Singh, H. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002578 · Cited by 207
Self-citationElectronic health records and national patient-safety goals
Sittig, D. F., & Singh, H. (2012) · New England Journal of Medicine · doi:10.1056/nejmsb1205420 · Cited by 204
Self-citationDefining Health Information Technology–Related Errors
Sittig, D. F. (2011) · Archives of Internal Medicine · doi:10.1001/archinternmed.2011.327 · Cited by 167
“5 mg Mon-Fri only”) that contradict information contained in the structured section of the medication order (eg, “Warfarin tabs 10 mg Q day”).(13) Errors may also arise when 2 or more parts of the HIT system (eg, CPOE application and the pharmacy’s medication-dispensing system) interact in an unpredicted manner, resul…”
Magrabi, F., Ong, M.-S., Runciman, W., & Coiera, E. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2009.002444 · Cited by 162
“Singh and colleagues found that 20% of 532 errors resulting from inconsistent entry of dosage information within a CPOE could have resulted in moderate to severe harm.(16) Reports of patient safety incidents paint a broader picture.”
BackgroundWestbrook, J. I., Baysari, M. T., Li, L., Burke, R. A., Richardson, K. L., & Day, R. O. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001745 · Cited by 113
Barlev, A. (2010) · Journal of Managed Care Pharmacy · doi:10.18553/jmcp.2010.16.9.693 · Cited by 104
Meeks, D. W., Takian, A., Sittig, D. F., Singh, H., & Barber, N. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001762 · Cited by 91
Self-citationHarrington, L., Kennerly, D., & Johnson, C. (2011) · Journal of Healthcare Management · doi:10.1097/00115514-201101000-00006 · Cited by 93
Grossman, J. M., Cross, D. A., Boukus, E. R., & Cohen, G. R. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000515 · Cited by 86
Cognitive ergonomics, socio-technical systems, and the impact of healthcare information technologies
Lawler, E., Hedge, A., & Pavlovic-Veselinovic, S. (2011) · International Journal of Industrial Ergonomics · doi:10.1016/j.ergon.2011.02.006 · Cited by 79
Palchuk, M. B., Fang, E., Cygielnik, J. M., Labreche, M. J., Shubina, M., Ramelson, H. Z., Hamann, C., Broverman, C. A., Einbinder, J. S., & Turchin, A. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2010.003335 · Cited by 71
“3%) rate of errors among 500 prescriptions with a narrative component.(24) The inter-reviewer agreement on the presence of discrepancies, although good, was less than expected; probably due to the complexity of the underlying data.”
BackgroundMagrabi, F., Li, S. Y. W., Day, R. O., & Coiera, E. W. (2010) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2009.001719 · Cited by 67
“The range of prescribing errors include selection of the wrong patient; missed drug allergies”
BackgroundSalahuddin, L. B., & Ismail, Z. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.07.004 · Cited by 66
Electronic Health Records and Use of Clinical Decision Support
Mills, S. (2019) · Critical Care Nursing Clinics of North America · doi:10.1016/j.cnc.2019.02.006 · Cited by 61
Tortorella, G. L., Fogliatto, F. S., Vijaya Sunder, M., Vergara, A., & Vassolo, R. S. (2021) · International Journal of Production Research · doi:10.1080/00207543.2021.1912429 · Cited by 59
“…demand and supply Patient information/diagnostic References Poor emergency triage system Crellin and Johnston (2003); Pantanowitz, Henricks, and Beckwith (2007); Fraser et al. (2007); Singh et al. (2009); Straus et al. (2011); Wallace (2015); Wager, Lee, and Glaser (2017); Borges et al. (2019).”
BackgroundPrescription writing practices in a rural tertiary care hospital in Western Maharashtra, India
Phalke, V. D. (2011) · Australasian Medical Journal · doi:10.4066/amj.2011.515 · Cited by 56
Nelson, S. D., Poikonen, J., Reese, T., ElHalta, D., & Weir, C. R. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw044 · Cited by 52
Potential medication errors associated with computer prescriber order entry
Villamañán, E., Larrubia, Y., Ruano, M., Vélez, M., Armada, E., Herrero, A., & Álvarez-Sala, R. (2013) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-013-9771-2 · Cited by 52
“Often, this inflexibility, the lack of program management or distrust of the electronic prescription system, leads to an overuse of the free-text field increasing the probability of error [6, 23].”
BackgroundInfluentialEHR‐related medication errors in two ICUs
Carayon, P., Du, S., Brown, R., Cartmill, R. S., Johnson, M., & Wetterneck, T. B. (2017) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.21259 · Cited by 43
Barnett, M. L., Mehrotra, A., & Jena, A. B. (2016) · BMJ · doi:10.1136/bmj.i3835 · Cited by 47
Miller, A. M., Boro, M. S., Korman, N. E., & Davoren, J. B. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000262 · Cited by 41
“However, other studies, including that of Singh et al, have suggested that anticoagulants are associated with the highest risk of potential ADE in the VA environment and are probably deserving of cDDI alerts with improved usability, to improve patient safety.(23) Some data have recently been published regarding the op…”
ResultClinical pharmacy interventions in paediatric electronic prescriptions
Maat, B., Au, Y. S., Bollen, C. W., van Vught, A. J., Egberts, T. C. G., & Rademaker, C. M. A. (2012) · Archives of Disease in Childhood · doi:10.1136/archdischild-2012-302817 · Cited by 36
Improving outpatient safety through effective electronic communication: a study protocol
Hysong, S. J., Sawhney, M. K., Wilson, L., Sittig, D. F., Esquivel, A., Watford, M., Giardina, T. D., Espadas, D., & Singh, H. (2009) · Implementation Science · doi:10.1186/1748-5908-4-62 · Cited by 34
“[25], five scenarios will be created to observe providers' strategies for entering these commonly errorprone prescriptions.”
Self-citationPontefract, S. K., Coleman, J. J., Vallance, H. K., Hirsch, C., Shah, S., Marriott, J. F., & Redwood, S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0207450 · Cited by 35
Enabling Medication Management through Health Information Technology
(2011) · SciVee · doi:10.4016/37397.01 · Cited by 35
Arques-Armoiry, E., Cabelguenne, D., Stamm, C., Janoly-Duménil, A., Grosset-Grange, I., Vantard, N., Maire, P. H., & Charpiat, B. (2010) · La Revue de Médecine Interne · doi:10.1016/j.revmed.2010.08.001 · Cited by 34
Effect of E‐Prescribing Systems on Patient Safety
Kannry, J. L. (2011) · Mount Sinai Journal of Medicine A Journal of Translational and Personalized Medicine · doi:10.1002/msj.20298 · Cited by 34
Concomitant prescribing and dispensing errors at a Brazilian hospital: a descriptive study
Silva, M. D. D. G., Rosa, M. B., Franklin, B. D., et al. (2011) · Clinics · doi:10.1590/s1807-59322011001000005 · Cited by 34
“Thus, after implementing an electronic system, hospitals should attempt to identify the critical error points and create appropriate preventive measures.(34)”
How many medication orders are entered through free-text in EHRs?--a study on hypoglycemic agents.
Zhou, L., Mahoney, L. M., Shakurova, A., Goss, F. R., CHANG, F. Y., Bates, D. W., & Rocha, R. A. (2012) · PubMed Central · Cited by 32
The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study
Howlett, M. M., Butler, E., Lavelle, K. M., et al. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1709508 · Cited by 32
Elshayib, M., & Pawola, L. M. (2020) · Health Informatics Journal · doi:10.1177/1460458220941750 · Cited by 33
Towards creating the perfect electronic prescription
Dhavle, A. A., & Rupp, M. T. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-002738 · Cited by 33
Carayon, P., Wetterneck, T. B., Cartmill, R. S., Blosky, M. A., Brown, R., Hoonakker, P., Kim, R., Kukreja, S., Johnson, M., Paris, B. L., et al. (2017) · Journal of Patient Safety · doi:10.1097/pts.0000000000000358 · Cited by 31
“The provision of default values may reduce omitted information, but may be accepted without sufficient thought.(35,36) ↑ Wrong drug orders Medication selection errors due to pick lists of medications Wrong patient Wrong drug for patient Relevant contextual information should be provided during ordering (e.”
Millery, M. P., & Kukafka, R. (2010) · Medical Care Research and Review · doi:10.1177/1077558710373769 · Cited by 30
“Eslami, Abu-Hanna, de Keizer, & de Jonge, 2006; Han et al., 2005; Hsieh et al., 2004; Koppel et al., 2005; Nebeker, Hoffman, Weir, Bennett, & Hurdle, 2005; Singh et al., 2009; van den Bemt, Idzinga, Robertz, Kormelink, & Perls, 2009; Walsh et al., 2006), and other studies that found mixed results.”
Charpiat, B., Bedouch, P., Conort, O., Rose, F.-X., Juste, M., Roubille, R., & Allenet, B. (2012) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2012.02.002 · Cited by 31
Effects of hospital leadership, organizational systems, and ESWOS on medical error reduction
Lee, D., Hong, K. S., & Kim, N. Y. (2014) · Service Business · doi:10.1007/s11628-014-0262-x · Cited by 28
Ruano, M., Villamañán, E., Pérez, E., Herrero, A., & Álvarez-Sala, R. (2015) · World Journal of Pediatrics · doi:10.1007/s12519-015-0067-6 · Cited by 27
Why Test Results Are Still Getting “Lost” to Follow-up: a Qualitative Study of Implementation Gaps
Zimolzak, A. J., Shahid, U., Giardina, T. D., Memon, S. A., Mushtaq, U., Zubkoff, L., Murphy, D. R., Bradford, A. M., & Singh, H. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-021-06772-y · Cited by 27
Self-citationAnalysis of Prescribers’ Notes in Electronic Prescriptions in Ambulatory Practice
Dhavle, A. A., Yang, Y., Rupp, M. T., Singh, H., Ward-Charlerie, S., & Ruiz, J. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2015.7786 · Cited by 25
Self-citationDose Omissions in Hospitalized Patients in a UK Hospital
Coleman, J. J., McDowell, S. E., & Ferner, R. E. (2012) · Drug Safety · doi:10.1007/bf03261964 · Cited by 24
“We and others have demonstrated some differences between coded and free text, which may highlight potential limitations of coding structures from electronic prescribing systems.([17,18])”
BackgroundMeaningful Use and Certification of Health Information Technology: What about Safety?
Hoffman, S., & Podgurski, A. (2011) · The Journal of Law Medicine & Ethics · doi:10.1111/j.1748-720x.2011.00572.x · Cited by 21
Evaluation of the NCPDP Structured and Codified Sig Format for e-prescriptions
Liu, H., Burkhart, Q., & Bell, D. S. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2010-000034 · Cited by 21
“A recent study by Singh et al highlighted the potential for new kinds of error, showing that nearly 1% of electronic prescriptions contained inconsistent instructions, with the most common error being conflicting drug dosages.(11) Palchuk et al reported that 16% of electronic prescriptions contained internal discrepan…”
BackgroundYang, Y., Ward-Charlerie, S., Dhavle, A. A., Rupp, M. T., & Green, J. (2018) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2018.17404 · Cited by 21
“However, as with any technology, the benefits from e-prescribing are directly dependent on the manner in which it is implemented and used, and prior research has demonstrated that e-prescribing can elevate the risks of some errors or even introduce new quality challenges.(5-8) Few components of a prescription order ar…”
Background(2011) · American Journal of Health-System Pharmacy · doi:10.2146/sp100011e · Cited by 20
Kinlay, M., Ho, L. M., Zheng, W. Y., Burke, R. A., Juraskova, I., Moles, R. J., & Baysari, M. T. (2021) · Applied Clinical Informatics · doi:10.1055/s-0041-1739196 · Cited by 19
Vélez‐Díaz‐Pallarés, M., Álvarez‐Díaz, A. M., Gramage, T., Oliveros, N. V., Delgado‐Silveira, E., García, M. M., Cruz-Jentoft, A. J., & Bermejo-Vicedo, T. (2017) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-017-0474-y · Cited by 22
Paediatric in-patient prescribing errors in Malaysia: a cross-sectional multicentre study
Khoo, T. B., Tan, J. W., Ng, H. P., Choo, C. M., Shukor, I. N. C. B. A., & Teh, S. H. (2017) · International Journal of Clinical Pharmacy · doi:10.1007/s11096-017-0463-1 · Cited by 18
A red‐flag‐based approach to risk management of EHR‐related safety concerns
Sittig, D. F., & Singh, H. (2013) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.21123 · Cited by 17
Self-citationCoded entry versus free-text and alert overrides: What you get depends on how you ask
Seidling, H. M., Paterno, M. D., Haefeli, W. E., et al. (2010) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2010.08.003 · Cited by 17
Salahuddin, L. B., Ismail, Z., Hashim, U. R., Ikram, R. R. R., Ismail, N. H., & Naim, M. H. (2018) · Health Informatics Journal · doi:10.1177/1460458218759698 · Cited by 17
Khoong, E. C., Nouri, S. S., Tuot, D. S., Nundy, S., Fontil, V., & Sarkar, U. (2021) · Medical Decision Making · doi:10.1177/0272989x211031209 · Cited by 13
“We assessed the potential for meaningful harm based on a scale previously used to classify the harm of errors.(7,29) For each recommendation, we used a binary outcome that focused on the potential for at least moderate meaningful harm, which included initiation or cessation of medications without indication or with co…”
MethodKang, H., Wang, J., Yao, B., Zhou, S., & Gong, Y. (2018) · JAMIA Open · doi:10.1093/jamiaopen/ooy042 · Cited by 17
Cochran, G. L., Klepser, D. G., Morien, M., Lomelin, D. E., Schainost, R., & Lander, L. I. (2013) · BMJ Quality & Safety · doi:10.1136/bmjqs-2013-002089 · Cited by 15
Braund, R., Furlan, H. M., George, K., et al. (2009) · Pharmacy World & Science · doi:10.1007/s11096-009-9343-7 · Cited by 15
“• Whilst computer generated prescriptions may reduce some types of errors (such as legal requirements), they may introduce new errors [ 10 ] such as incorrect dose and dosage form selection and prescribers still need to exercise due care.”
BackgroundSafe use of hospital information systems: an evaluation model based on a sociotechnical perspective
Salahuddin, L. B., Ismail, Z., Ikram, R. R. R., Hashim, U. R., Idris, A., Ismail, N. H., Hassan, N. H., & Rahim, F. A. (2019) · Behaviour and Information Technology · doi:10.1080/0144929x.2019.1597164 · Cited by 14
“For example, inadequate knowledge of the prescription ordering mechanism could cause the healthcare practitioners to use the system in a way in which it was not intended (Blijleven et al. 2017; Singh et al. 2009).”
BackgroundHealth Care Information Technology
Liebovitz, D. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.79 · Cited by 14
Yang, Y., Ward-Charlerie, S., Kashyap, N., deMayo, R., Agresta, T. P., & Green, J. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy100 · Cited by 14
Qian, S., Munyisia, E. N., Reid, D., et al. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104292 · Cited by 13
Hellot-Guersing, M., Jarre, C., Molina, C., Leromain, A., Derharoutunian, C., Gadot, A., & Roubille, R. (2015) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2015.06.001 · Cited by 12
Modeling the mind: How do we design effective decision-support?
Weir, C. R., Rubin, M. A., Nebeker, J. R., & Samore, M. H. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.06.008 · Cited by 12
Turchin, A., Shubina, M., & Goldberg, S. I. (2011) · PubMed Central · Cited by 11
SAFER Electronic Health Records
Sittig, D. F., & Singh, H. (2015) · Apple Academic Press eBooks · doi:10.1201/b18371 · Cited by 11
Self-citationEffect of EHR User Interface Changes on Internal Prescription Discrepancies
Sawarkar, A., Dementieva, Y. A., Breydo, E. M., Ramelson, H. Z., & Turchin, A. (2014) · Applied Clinical Informatics · doi:10.4338/aci-2014-03-ra-0023 · Cited by 10
Evaluation of a User Guidance Reminder to Improve the Quality of Electronic Prescription Messages
Corley, S. T., Rupp, M. T., Ruiz, J., Smith, J. Y., Gill, R., Sow, M., & Dhavle, A. A. (2014) · Applied Clinical Informatics · doi:10.4338/aci-2014-03-cr-0022 · Cited by 9
Klappe, E. S., van Putten, F. J. P., de Keizer, N. F., & Ronald Cornet, A. (2021) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-021-01477-y · Cited by 7
POP-PL: a patient-oriented prescription programming language
Florence, S. P., Fetscher, B., Flatt, M., Temps, W. H., Kiguradze, T., West, D. P., Niznik, C. M., Yarnold, P. R., Findler, R. B., & Belknap, S. M. (2015) · ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences (GPCE) · doi:10.1145/2814204.2814221 · Cited by 8
“Singh et al. (2009) have shown how physicians struggle with the limited data-field entry programs that current Computerized Physician Order Entry (CPOE) and ePrescribing systems provide.”
BackgroundInteroperable Electronic Patient Records for Health Care Improvement
Balas, E. A., & Sanousi, A. A. (2009) · Studies in health technology and informatics · doi:10.3233/978-1-60750-044-5-19 · Cited by 7
“In the evolution of electronic health records, a synergistic trend is the appearance of personal electronic health record systems include those promoted by major commercial vendors like Google Health, Healthvault and others.”
BackgroundPotential value of electronic prescribing in health economic and outcomes research
Cooke, C. E. (2010) · Patient Related Outcome Measures · doi:10.2147/prom.s13033 · Cited by 7
Minding the Gaps: Assessing Communication Outcomes of Electronic Preconsultation Exchange
Price, E. L., Sewell, J. L., Chen, A. H., & Sarkar, U. (2016) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(16)42048-9 · Cited by 7
Romanelli, R. J., Schwartz, N. R. M., Dixon, W. G., Rodriguez‐Watson, C., Sauer, B. C., Albright, D., & Marcum, Z. A. (2021) · Pharmacoepidemiology and Drug Safety · doi:10.1002/pds.5331 · Cited by 6
Development and Field Testing of a Self-Assessment Guide for Computer-Based Provider Order Entry
Vartian, C. V., Singh, H., Russo, E. M., & Sittig, D. F. (2014) · Journal of Healthcare Management · doi:10.1097/00115514-201409000-00007 · Cited by 6
“…Han et al., 2005; Horsky et al., 2005; Koppel et al., 2005, 2008; Kop-pel, Wetterneck, Telles, & Karsh, 2008; Metzger, Welebob, Bates, Lipsitz, & Classen, 2010; Nanji et al., 2011; Nebeker, Hoffman, Weir, Bennett, & Hurdle, 2005; Singh et al., 2009; Zhan, Hicks, Blanchette, Keyes, & Cousins, 2006).”
Self-citationDefining Health Information Technology-Related Errors
Singh, H. (2013) · Apple Academic Press eBooks · doi:10.1201/b16306-6 · Cited by 6
Self-citationÉvaluation des bases de données médicamenteuses disponibles sur le marché français
Hacin, L., Mainar, A., & Edouard, B. (2013) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2012.12.001 · Cited by 5
Clinician Perceptions on the Use of Free-Text Communication Orders
Kandaswamy, S., Pruitt, Z. M., Kazi, S., Marquard, J. L., Owens, S., Hoffman, D., Ratwani, R. M., & Hettinger, A. Z. (2021) · Applied Clinical Informatics · doi:10.1055/s-0041-1731002 · Cited by 5
Neinstein, A. B., & Cucina, R. J. (2011) · Journal of Diabetes Science and Technology · doi:10.1177/193229681100500614 · Cited by 4
POP-PL: a patient-oriented prescription programming language
Florence, S. P., Fetscher, B., Flatt, M., Temps, W. H., Kiguradze, T., West, D. P., Niznik, C. M., Yarnold, P. R., Findler, R. B., & Belknap, S. M. (2015) · ACM SIGPLAN Notices · doi:10.1145/2936314.2814221 · Cited by 4
Sittig, D. F., Longhurst, C., Russo, E. M., & Singh, H. (2015) · Health informatics · doi:10.1007/978-3-319-20765-0_2 · Cited by 3
Self-citationLow, S. G. (2011) · Proceedings of Singapore Healthcare · doi:10.1177/201010581102000203 · Cited by 3
Effects of hospital leadership, organizational systems, and ESWOS on medical error reduction
LeeKwan, D. (2016) · Cited by 3
Weight and size descriptors for drug dosing: Too many options and too many errors
Erstad, B. L., Romero, A. V., & Barletta, J. F. (2022) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/zxac283 · Cited by 3
Free Text as Part of Electronic Health Record Orders: Context or Concern?
Kazi, S., Handley, J. L., Milicia, A. P., et al. (2024) · Patient Safety · doi:10.33940/001c.118587 · Cited by 2
A Continuous Quality Improvement Initiative for Electronic Prescribing in Ambulatory Care
Dhavle, A. A., Rupp, M. T., Sow, M., et al. (2014) · American Journal of Medical Quality · doi:10.1177/1062860614562948 · Cited by 2
Quality improvement and patient safety in the age of reform: preconditions for success.
Mj, G. (2013) · PubMed · Cited by 2
Florence, S. P., Fetscher, B., Flatt, M., Temps, W. H., St-Amour, V., Kiguradze, T., West, D. P., Niznik, C. M., Yarnold, P. R., Findler, R. B., et al. (2018) · ACM Transactions on Programming Languages and Systems · doi:10.1145/3210256 · Cited by 2
“A large study of CPOE systems found that 1% of prescriptions contained free-text instructions that were inconsistent with the contents of the structured data fields, and 20% of these inconsistencies risked moderate or severe patient injury (Singh et al. 2009).”
BackgroundDose Omissions in Hospitalized Patients in a UK Hospital
Coleman, J. J., McDowell, S. E., & Ferner, R. E. (2012) · Drug Safety · doi:10.2165/11630750-000000000-00000 · Cited by 2
Malk, M., Mooses, K., Oja, M., et al. (2026) · Online Journal of Public Health Informatics · doi:10.2196/83465 · Cited by 1
Pharmacy Data Integrity for Optimal Analytics
Butler, C. D. (2014) · International Journal of Knowledge Discovery in Bioinformatics · doi:10.4018/ijkdb.2014070103 · Cited by 1
CONCEPTUAL FOUNDATION OF SAFER GUIDES
Sittig, D. F., & Singh, H. (2015) · Apple Academic Press eBooks · doi:10.1201/b18371-5 · Cited by 1
Self-citationClinical decision support systems in the care of hospitalised patients with diabetes
Nirantharakumar, K. (2013) · University of Birmingham Institutional Research Archive (University of Birmingham)
Safety in health care systems : a synthesis of the literature
Weatherby, J. (2015) · doi:10.6083/m4cf9n4s
Myers, R. B., Jones, S. L., Sittig, D. F., Meeks, D. W., Takian, A., Singh, H., Barber, N., Smith, M. W., Taylor, L., & Scott, J. (2015) · Apple Academic Press eBooks · doi:10.1201/b18371-3
Self-citationTHE CONTEXT OF EHR SAFETY AND THE NEED FOR RISK ASSESSMENT
Sittig, D. F., Singh, H., Menon, S., Meyer, A. N. D., & Belmont, E. (2015) · Apple Academic Press eBooks · doi:10.1201/b18371-2
Self-citationSafety Considerations in Ambulatory Care Informatics
Rose, E. A. (2016) · Springer eBooks · doi:10.1007/978-3-319-31123-4_15
Enforcing Data Integrity in Pharmacy
Butler, C. D. (2012) · Advances in bioinformatics and biomedical engineering book series · doi:10.4018/978-1-4666-0309-7.ch015
Pontefract, S. K. (2018) · University of Birmingham Institutional Research Archive (University of Birmingham)
Metadata
- Authors
- Singh, H., Mani, S., Espadas, D., Petersen, N., Franklin, V., & Petersen, L. A.
- Affiliations
- Michael E. DeBakey VA Medical Center (US)
- Venue
- Archives of Internal Medicine
- Publisher
- American Medical Association (AMA)
- Published
- 2009-05-25
- Volume
- 169
- Issue
- 10
- Pages
- 982
- ISSN
- 0003-9926 (ISSN-L)
- PMC
- PMC2919338
- OpenAlex
- W2077178507
- Semantic Scholar
- ec2c80787b615a3670292bc6644dbb7d00e3d068
- Cited by
- 104
- References
- 29
- Citations by year
- 2026: 1 · 2024: 1 · 2022: 1 · 2021: 8 · 2020: 3 · 2019: 2 · 2018: 7 · 2017: 5 · 2016: 7 · 2015: 13 · 2014: 9 · 2013: 11 · 2012: 7
- FWCI
- 25.33
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Archives of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (K23CA125585)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Patient Safety and Medication Errors
- Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Keywords
- computerized physician order entry, prescribing errors, data inconsistency, structured templates, medication errors, drug dosage errors, inpatient prescriptions, surgical subspecialties, drug safety
- MeSH terms
- Group Practice, Humans, Medication Errors, Drug Prescriptions, Prospective Studies, Quality Assurance, Health Care, Clinical Pharmacy Information Systems, Medical Order Entry Systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-07, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-07 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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