The DOI matches its Crossref record; 26 of the 30 references it cites were found in a registry or an index; none of the 24 sources its claims cite is checked for support yet.
Notification of Abnormal Lab Test Results in an Electronic Medical Record: Do Any Safety Concerns Remain?
Open accessAbstract
Background: Follow-up of abnormal outpatient laboratory test results is a major patient safety concern. Electronic medical records can potentially address this concern through automated notification. We examined whether automated notifications of abnormal laboratory results (alerts) in an integrated electronic medical record resulted in timely follow-up actions. Methods: We studied four alerts: hemoglobin A1c (HbA1c) ≥15%, positive hepatitis C antibody (HCV), prostate specific antigen (PSA) ≥15 ng/mL, and thyroid stimulating hormone (TSH) ≥ 15 mIU/L. An alert tracking system determined whether the alert was acknowledged (i.e. provider clicked on and opened the message) within two weeks of transmission; acknowledged alerts were considered read. Within 30 days of result transmission, record review and provider contact determined follow-up actions (e.g. patient contact, treatment etc.). Multivariable logistic regression models analyzed predictors for lack of timely follow-up. Results: Between May 2008 and December 2008, 78,158 tests (HbA1c, HCV, TSH and PSA) were performed, of which 1163 (1.48%) were transmitted as alerts; 10.2% of these (119/1163) were unacknowledged. Timely follow-up was lacking in 79 (6.8%) and was statistically not different for acknowledged and unacknowledged alerts (6.4% vs. 10.1%; p =.13). Two-hundred two alerts (17.4% of 1163) arose from unnecessarily ordered (redundant) tests. Alerts for a new versus known diagnosis were more likely to lack timely follow-up (OR: 7.35; 95% CI: 4.16-12.97) whereas alerts related to redundant tests were less likely to lack timely follow-up (OR: 0.24; 95% CI: 0.07-0.84). Conclusions: Safety concerns related to timely patient follow-up remain despite automated notification of non-life threatening abnormal laboratory results in the outpatient setting.
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Claims the paper makes
14 Own result · 7 Not checked yet · 5 Own method · 5 Own interpretation
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
“Two-hundred two alerts (17.4% of 1163) arose from unnecessarily ordered (redundant) tests.”
- Also stated in: § RESULTS · plain
“Two-hundred two alerts (17.4% of 1163) were considered redundant”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > Abstract > Results:
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § RESULTS · plain
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
“Timely follow-up was lacking in 79 (6.8%) and was statistically not different for acknowledged and unacknowledged alerts (6.4% vs. 10.1%; p =.13).”
- Also stated in: § Lack of Timely Follow-up · plain
“Statistically, there was no significant difference in rates of lack of timely follow-up between acknowledged and unacknowledged laboratory alerts (6.4% vs. 10.1%; p=.13).”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > Abstract > Results:
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Lack of Timely Follow-up · plain
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
“in only 11 (7%) of these 159 cases would the provider have received a computerized reminder prompting them of potential redundancy based on repetition.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS > Alerts Related to Redundant Tests
hedgedn = 159- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“Timely follow-up was lacking in 79 (6.8%)”
- Also stated in: § RESULTS · plain
“Of these, 79 alerts (6.8% of total) were determined to lack timely follow-up.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > Abstract > Results:
plainn = 94- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § RESULTS · plain
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
“Between May 2008 and December 2008, 27,092 HbA1c, 22,837 PSA, 6271 HCV and 21,958 TSH tests were performed.”
- Also stated in: § Results: · plain
“Between May 2008 and December 2008, 78,158 tests (HbA1c, HCV, TSH and PSA) were performed”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results: · plain
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
“allied health care providers as ordering providers (OR, 4.32; 95% CI: 1.21-15.52) and trainees as ordering providers (OR, 8.39, 95% CI: 2.97-23.68).”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS > Lack of Acknowledgement
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“10.2% of these (119/1163) were unacknowledged.”
- Also stated in: § RESULTS · plain
“Acknowledged alerts constituted 89.8% of the total high-priority alerts (1163).”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > Abstract > Results:
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § RESULTS · plain
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
“A total of 1163 (1.49%) results were electronically transmitted as mandatory high-priority alerts”
- Also stated in: § Results: · plain
“of which 1163 (1.48%) were transmitted as alerts”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Results: · plain
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
“alerts related to redundant tests were less likely to lack timely follow-up (OR: 0.24; 95% CI: 0.07-0.84).”
- Also stated in: § Lack of Timely Follow-up · plain
“Redundant tests were more likely to receive follow-up (p<.01).”
- Also stated in: § Lack of Timely Follow-up · plain
“redundant tests (OR: 0.24; 95% CI: 0.074-0.84) with appropriately ordered tests as referent”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > Abstract > Results:
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Lack of Timely Follow-up · plain
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
“mental health as a specialty (OR: 2.82; 95% CI: 1.06-7.54) with primary care as referent.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS > Lack of Timely Follow-up
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 8
- Probably not a substantial claim. 5
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
“Trainees were less likely to acknowledge alerts compared to attending/staff physicians and allied health providers (physician assistants and nurse practitioners) whereas specialty services (including mental health) were less likely to acknowledge alerts compared to primary care providers (p<.0001 for both).”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS > Lack of Acknowledgement
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It 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
“we found 28 cases where the provider ordered the test too soon after the last PSA, TSH or HbA1c and in 131 cases a second HCV ELISA test was ordered despite the presence of a previous positive test.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS > Alerts Related to Redundant Tests
plainn = 159- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It 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
“No evidence of documented follow-up action was found in 307 (26.4%) of the alerts, however 213 (18.3% of 1163) cases were categorized as no-impact alerts.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > RESULTS
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It 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
“many factors including a large sample size, multiple clinics, large number of providers (over 500 from different specialties), rigorous methods to determine follow-up, explicit criteria for determination of redundant tests, various types of abnormal lab alerts and an advanced integrated electronic medical record used in VA facilities throughout the US, all add several unique strengths to our study”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It 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
“We also lack comparable data from non-electronic medical record based systems and cannot comment on the effectiveness of automated notification compared to these systems.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > DISCUSSION
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a 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
“notifications of abnormal redundant tests appear to be a distracting influence on providers who are missing essential alerts for newly diagnosed conditions.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > DISCUSSION
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Outpatient care is often busy and fragmented, and therefore follow-up of abnormal laboratory test results is prone to error.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > BACKGROUND
What the sources say
- Not checked yetcites [1] Edelman, 2002, Outpatient diagnostic errors: unrecognized hyperglycemia, Eff Clin Pract
- Not checked yetcites [2] Hickner, 2008, Testing process errors and their harms and consequences reported from family medicine practices: a study of the American Academy of Family Physicians National Research Network, Qual Saf Health Care source
- Not checked yetcites [3] Hickner, 2005, Issues and initiatives in the testing process in primary care physician offices, Jt Comm J Qual Patient Saf
- Not checked yetcites [4] Poon, 2004, “I wish I had seen this test result earlier!”: dissatisfaction with test result management systems in primary care, Arch Intern Med source
- Not checked yetcites [5] Schiff, 2005, Missed hypothyroidism diagnosis uncovered by linking laboratory and pharmacy data, Arch Intern Med source
- Not checked yetcites [6] Wahls, 2007, The continuing problem of missed test results in an integrated health system with an advanced electronic medical record, Jt Comm J Qual Patient Saf
- Not checked yetcites [7] Wahls, 2007, Diagnostic errors and abnormal diagnostic tests lost to follow-up: a source of needless waste and delay to treatment, J Ambul Care Manage source
- Not checked yetcites [8] Bates, 2005, Doing better with critical test results, Jt Comm J Qual Patient Saf
- Not checked yetcites [9] Schiff, 2005, Introduction: communicating critical test results, Jt Comm J Qual Patient Saf
- Not checked yetcites [10] Nepple, 2008, Prevalence of delayed clinician response to elevated prostate-specific antigen values, Mayo Clin Proc source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It 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 second study investigator evaluated the medical record to confirm the findings and contacted the provider by telephone to obtain any additional evidence of undocumented follow-up or a decision to not pursue follow-up.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > METHODS > Data Collection
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“We used objective pre-defined explicit criteria to determine redundancy of tests (criteria specified in Table 3).”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > METHODS > Data Collection
What the sources say
- Not checked yetcites [20] van Walraven, 1998, Do we know what inappropriate laboratory utilization is?, JAMA source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably 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
“Hierarchical multivariable logistic regression models accounting for clustering of laboratory tests by providers were used to identify factors associated with the outcome variables”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > METHODS > Data analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
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 reviewer blinded to acknowledgement status evaluated the medical record using a standardized pre-tested data collection instrument to determine any follow-up actions”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > METHODS > Data Collection
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“In previous work, we found abnormal diagnostic imaging alerts may not always be reviewed by ordering practitioners, and practitioners who review them may not always act upon the transmitted results in a timely manner.”
§ Notification of abnormal lab test results in an electronic medical record: do any safety concerns remain? > BACKGROUND
What the sources say
- Not checked yetcites [19] Singh, 2009, Timely follow-up of abnormal diagnostic imaging test results in an outpatient setting: are electronic medical records achieving their potential?, Arch Intern Med source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper relies on this without support.
Follow-up of an abnormal result depends on providers reviewing and acting on the electronic communication of the result.
“Abnormal result follow-up, however, will occur only if electronic communication of test results (either through alerts or direct access of test result) is reviewed and acted upon by providers.”
The paper relies on this without support.
A substantial share of outpatient lab results are not urgent enough to require verbal reporting to the ordering clinician.
“many laboratory test results in the outpatient setting may not be immediately life threatening and hence not verbally reported to the ordering provider.”
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Efforts to improve EHR-related patient safety rely on identification of underlying risks as well as an appreciation of contributing areas of vulnerability”
From Exploring the sociotechnical intersection of patient safety and electronic health record implementation (2014) · cites this paper as [23]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“On the basis of the anticipated rate of appropriately identified abnormal test results in the literature12,13,14,15,16,17,18,19,20,21 and the anticipated magnitude of the association of the enhanced EHR, we required a sample size of 30 participants, each reviewing 35 test results, to achieve 80% power to detect a statistically significant difference in cognitive workload and performance.”
From Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians (2019) · cites this paper as [21]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Even in the EHR environment, with alerts and reminders in place, physicians continue to often inappropriately manage abnormal test results.12,13,14,15,16,17,18,19,20,21”
From Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians (2019) · cites this paper as [21]
In the citing paper
“The model accounts for the complexities of technology, its users, the involved workflow, and the larger external or organizational policies and context in assessment of EHR-related safety concerns.35 36”
From An analysis of electronic health record-related patient safety concerns (2014) · cites this paper as [36]
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Murphy, D. R., Laxmisan, A., Reis, B., Thomas, E. J., Esquivel, A., Forjuoh, S. N., Parikh, R. C., Khan, M. M., & Singh, H. (2013) · BMJ Quality & Safety · doi:10.1136/bmjqs-2013-001874 · Cited by 125
Self-citationThe Burden of Inbox Notifications in Commercial Electronic Health Records
Murphy, D. R., Meyer, A. N. D., Russo, E. M., Sittig, D. F., Wei, L., & Singh, H. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.0209 · Cited by 116
Self-citationThe Impact of Electronic Health Records on Diagnosis
Graber, M. L., Byrne, C., & Johnston, D. (2017) · Diagnosis · doi:10.1515/dx-2017-0012 · Cited by 108
“In one study, over 10% of critical alerts were never acknowledged within 30 days [53].”
BackgroundExploring situational awareness in diagnostic errors in primary care
Singh, H., Giardina, T. D., Petersen, L. A., Smith, M. W., Paul, L. W., Dismukes, K., Bhagwath, G., & Thomas, E. J. (2011) · BMJ Quality & Safety · doi:10.1136/bmjqs-2011-000310 · Cited by 105
Self-citationLegal, Ethical, and Financial Dilemmas in Electronic Health Record Adoption and Use
Sittig, D. F., & Singh, H. (2011) · Pediatrics · doi:10.1542/peds.2010-2184 · Cited by 100
Self-citationMurphy, D. R., Wu, L., Thomas, E. J., Forjuoh, S. N., Meyer, A. N. D., & Singh, H. (2015) · Journal of Clinical Oncology · doi:10.1200/jco.2015.61.1301 · Cited by 100
“These delays often result from a variety of cognitive and system factors that lead to lack of timely evaluation of red flag signs and symptoms or abnormal test results.(9-21) Despite increasing adoption of electronic health records (EHRs) and greater access to diagnostic information, delays persist(10,18,19,22-26) in…”
BackgroundSelf-citationMeeks, 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-citationStrategies to reduce diagnostic errors: a systematic review
Abimanyi-Ochom, J., Mudiyanselage, S. B., Catchpool, M., Firipis, M., Dona, S. W. A., & Watts, J. J. (2019) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-019-0901-1 · Cited by 92
Singh, H., Spitzmueller, C., Petersen, N. J., Sawhney, M. K., Smith, M. W., Murphy, D. R., Espadas, D., Laxmisan, A., & Sittig, D. F. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001267 · Cited by 92
Self-citationGiardina, T. D., King, B. J., Ignaczak, A. P., Paull, D. E., Hoeksema, L. J., Mills, P. D., Neily, J. B., Hemphill, R. R., & Singh, H. (2013) · Health Affairs · doi:10.1377/hlthaff.2013.0130 · Cited by 85
Self-citationEight Recommendations for Policies for Communicating Abnormal Test Results
Singh, H., & Vij, M. S. (2010) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(10)36037-5 · Cited by 83
Self-citationThe patient portal and abnormal test results: An exploratory study of patient experiences
Giardina, T. D., Modi, V., Parrish, D. E., et al. (2015) · Patient Experience Journal · doi:10.35680/2372-0247.1055 · Cited by 74
Self-citationHarmonization of critical result management in laboratory medicine
Campbell, C., & Horvath, A. R. (2013) · Clinica Chimica Acta · doi:10.1016/j.cca.2013.11.004 · Cited by 71
Understanding the management of electronic test result notifications in the outpatient setting
Hysong, S. J., Sawhney, M. K., Wilson, L., Sittig, D. F., Esquivel, A., Singh, S., & Singh, H. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-22 · Cited by 68
Self-citationMeasures to Improve Diagnostic Safety in Clinical Practice
Singh, H., Graber, M. L., & Hofer, T. P. (2016) · Journal of Patient Safety · doi:10.1097/pts.0000000000000338 · Cited by 67
“42 Measurement criteria are better defined for missed test results than other types of missed opportunities.(42,43)”
BackgroundSelf-citationSingh, H., Wilson, L., Petersen, L. A., Sawhney, M. K., Reis, B., Espadas, D., & Sittig, D. F. (2009) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-9-49 · Cited by 64
Self-citationFollow-up Actions on Electronic Referral Communication in a Multispecialty Outpatient Setting
Singh, H., Esquivel, A., Sittig, D. F., Murphy, D., Kadiyala, H., Schiesser, R., Espadas, D., & Petersen, L. A. (2011) · Journal of General Internal Medicine · doi:10.1007/s11606-010-1501-z · Cited by 57
Self-citationClinical quality indicators in laboratory medicine
Barth, J. H. (2011) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1258/acb.2011.011126 · Cited by 55
Reducing Delay in Diagnosis: Multistage Recommendation Tracking
Wandtke, B., & Gallagher, S. (2017) · American Journal of Roentgenology · doi:10.2214/ajr.17.18332 · Cited by 53
“A study of 1196 alerts found no statistically significant difference in the rate of proper follow-up between acknowledged and unacknowledged alerts for abnormal test results [14].”
BackgroundMurphy, D. R. (2012) · Archives of Internal Medicine · doi:10.1001/archinternmed.2011.740 · Cited by 52
Sarkar, U., Bonacum, D., Strull, W. M., Spitzmueller, C., Jin, N., López, A., Giardina, T. D., Meyer, A. N. D., & Singh, H. (2012) · BMJ Quality & Safety · doi:10.1136/bmjqs-2011-000541 · Cited by 53
Self-citationCommunication breakdowns and diagnostic errors: a radiology perspective
Murphy, D. R., Singh, H., & Berlin, L. (2014) · Diagnosis · doi:10.1515/dx-2014-0035 · Cited by 52
“It is estimated that approximately 4%–8% of electronically delivered abnormal test results fail to receive timely follow up [20, 32, 33].”
BackgroundSelf-citationCallen, J. L., Giardina, T. D., Singh, H., Li, L., Paoloni, R., Georgiou, A., Runciman, W. B., & Westbrook, J. I. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3721 · Cited by 47
“More systematic processes for test result follow-up are needed, including the use of electronic information systems [13,17-20].”
BackgroundSelf-citationHow context affects electronic health record-based test result follow-up: a mixed-methods evaluation
Menon, S., Smith, M. W., Sittig, D. F., Petersen, N. J., Hysong, S. J., Espadas, D., Modi, V., & Singh, H. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-005985 · Cited by 45
“Although EHRs appear to reduce the risk of missed test results,(2) 4 5 they do not eliminate the problem.(2) 3 6 Lack of timely follow-up of test results remains a major patient safety concern in most healthcare organisations.”
BackgroundSelf-citationBuilding a bridge to safe diagnosis in health care. The role of the clinical laboratory
Lippi, G., Plebani, M., & Graber, M. L. (2016) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm-2015-1135 · Cited by 43
Ten Strategies to Improve Management of Abnormal Test Result Alerts in the Electronic Health Record
Singh, H., Wilson, L., Reis, B., Sawhney, M. K., Espadas, D., & Sittig, D. F. (2010) · Journal of Patient Safety · doi:10.1097/pts.0b013e3181ddf652 · Cited by 43
Self-citationWorkarounds and Test Results Follow-up in Electronic Health Record-Based Primary Care
Menon, S., Murphy, D. R., Singh, H., Meyer, A. N. D., & Sittig, D. F. (2016) · Applied Clinical Informatics · doi:10.4338/aci-2015-10-ra-0135 · Cited by 40
“In our previous work we found that almost 8% of abnormal imaging results and 7% of laboratory test notifications sent to providers through EHRs lacked timely follow–up [9, 12].”
BackgroundSelf-citationPatients as diagnostic collaborators: sharing visit notes to promote accuracy and safety
Blease, C., & Bell, S. K. (2019) · Diagnosis · doi:10.1515/dx-2018-0106 · Cited by 33
Processing of discharge summaries in general practice: a retrospective record review
Spencer, R. A., Spencer, S. E. F., Rodgers, S., Campbell, S., & Avery, A. J. (2018) · British Journal of General Practice · doi:10.3399/bjgp18x697877 · Cited by 36
Georgiou, A., Li, J., Thomas, J., Dahm, M. R., & Westbrook, J. I. (2019) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz032 · Cited by 40
“The authors noted that the procedures for management of results were not uniform, with only 55% of respondents reporting use of the electronic notification system for results management.38 Observational studies by Singh et al.32,34 and Bhise et al.57 reported a range of between 0.2% and 16.7% failure to follow up test…”
BackgroundInfluentialLaboratory testing in primary care: A systematic review of health IT impacts
Maillet, É., Paré, G., Currie, L. M., Raymond, L., de Guinea, A. O., Trudel, M.-C., & Marsan, J. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.05.009 · Cited by 30
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
Self-citationPowell, L., Sittig, D. F., Chrouser, K. L., & Singh, H. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.6752 · Cited by 34
Self-citationGeorgiou, A., Lymer, S. J., Forster, M., Strachan, M., Graham, S. M., HIRST, G. H. L., Callen, J. L., & Westbrook, J. I. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002466 · Cited by 31
Murphy, D. R., Meyer, A. N. D., Vaghani, V., Russo, E. M., Sittig, D. F., Wei, L., Wu, L., & Singh, H. (2017) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2017.08.007 · Cited by 31
Self-citationGosselin, R. C., Adcock, D. M., Dorgalaleh, A., et al. (2019) · Seminars in Thrombosis and Hemostasis · doi:10.1055/s-0039-1697677 · Cited by 32
Electronic Health Record Use Issues and Diagnostic Error: A Scoping Review and Framework
Dixit, R. A., Boxley, C. L., Samuel, S., Mohan, V., Ratwani, R. M., & Gold, J. A. (2022) · Journal of Patient Safety · doi:10.1097/pts.0000000000001081 · Cited by 32
Smith, M., Murphy, D., Laxmisan, A., Sittig, D., Reis, B., Esquivel, A., & Singh, H. (2013) · Applied Clinical Informatics · doi:10.4338/aci-2013-04-ra-0019 · Cited by 31
“In order to address this in a multifaceted sociotechnical context, we intended the functional prototype design to meet the following goals, many of which were conceived based on previous research findings: [1, 3, 4, 27–29, 33–37] 1.”
BackgroundMethodSelf-citationAmroze, A., Field, T. S., Fouayzi, H., Sundaresan, D., Burns, L., Garber, L., Sadasivam, R. S., Mazor, K. M., Gurwitz, J. H., & Cutrona, S. L. (2019) · JMIR Medical Informatics · doi:10.2196/12650 · Cited by 25
“This is especially relevant for noninterruptive EHR alerts, where assessments of the effectiveness of these alerts have found mixed results [9-12].”
BackgroundSaw, S., Loh, T. P., Ang, S. B. L., Yip, J., & Sethi, S. K. (2011) · American Journal of Clinical Pathology · doi:10.1309/ajcpuz53xzwqfyis · Cited by 31
Electronic health record–related safety concerns: A cross‐sectional survey
Menon, S., Singh, H., Meyer, A. N. D., Belmont, E., & Sittig, D. F. (2014) · Journal of Healthcare Risk Management · doi:10.1002/jhrm.21146 · Cited by 29
Self-citationAn Automated Clinical Alert System for Newly-Diagnosed Atrial Fibrillation
Cook, D. A., Enders, F., Caraballo, P. J., Nishimura, R. A., & Lloyd, F. J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122153 · Cited by 27
“[1–5] Such clinical alerts have been used to identify potential drug-drug interactions or dose adjustments when prescribing[1] and to notify providers of critical test results[4, 6] or unexpected changes in clinical status.”
BackgroundEstablishing an Evidence Base for Critical Laboratory Value Thresholds
Doering, T. A., Plapp, F., & Crawford, J. M. (2014) · American Journal of Clinical Pathology · doi:10.1309/ajcpdi0fyz4unweq · Cited by 27
“3) 17 3 18-21 12,095 (11) 2,480 (8) 60.”
Giardina, T. D., Hunte, H. E. R., Hill, M. A., Heimlich, S. L., Singh, H., & Smith, K. M. (2022) · Journal of Patient Safety · doi:10.1097/pts.0000000000000999 · Cited by 33
Self-citationShneiderman, B. (2011) · interactions · doi:10.1145/2029976.2029992 · 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-citationLaxmisan, A., Sittig, D. F., Pietz, K., Espadas, D., Krishnan, B., & Singh, H. (2012) · Medical Care · doi:10.1097/mlr.0b013e31825f6619 · Cited by 26
Self-citationLaxmisan, A., McCoy, A. B., Wright, A. T., & Sittig, D. F. (2012) · Applied Clinical Informatics · doi:10.4338/aci-2011-11-ra-0066 · Cited by 26
Self-citationColicchio, T. K., Facelli, J. C., Fiol, G. D., Scammon, D. L., Bowes, W., & Narus, S. P. (2016) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2016.07.018 · Cited by 25
Asynchronous automated electronic laboratory result notifications: a systematic review
Slovis, B. H., NAHASS, T. A., Salmasian, H., Kuperman, G. J., & Vawdrey, D. K. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx047 · Cited by 24
“Other studies have demonstrated a lack of improvement or a reduction in adverse events,(42) and still others have demonstrated continued safety concerns associated with automated notifications, even increased rates of adverse events.(44,46) Yet in many instances, noteworthy clinical improvements have been demonstrated.”
BackgroundCutrona, S. L., Fouayzi, H., Burns, L., Sadasivam, R. S., Mazor, K. M., Gurwitz, J. H., Garber, L., Sundaresan, D., Houston, T. K., & Field, T. S. (2017) · Journal of General Internal Medicine · doi:10.1007/s11606-017-4146-3 · Cited by 24
“new diagnosis.(8) The type of report(7) and the manner in which the alert appears in the InBasket are also influential.”
BackgroundMurphy, D. R., Satterly, T., Rogith, D., Sittig, D. F., & Singh, H. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.04.004 · Cited by 21
Self-citationDanforth, K. N., Hahn, E. E., Slezak, J. M., Chen, L. H., Li, B. H., Munoz‐Plaza, C. E., Luong, T. Q., Harrison, T. N., Mittman, B. S., Sim, J. J., et al. (2019) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2019.05.003 · Cited by 24
Self-citationPerrotta, P. L., & Karcher, D. S. (2016) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2015-0320-cp · Cited by 23
Sarkar, U., Simchowitz, B., Bonacum, D., Strull, W. M., López, A., Rotteau, L., & Shojania, K. G. (2014) · The Joint Commission Journal on Quality and Patient Safety · doi:10.1016/s1553-7250(14)40059-x · Cited by 20
Beyond the threshold: real-time use of evidence in practice
Jones, J. B., Stewart, W. F., Darer, J. D., & Sittig, D. F. (2013) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-13-47 · Cited by 22
“Observational data may also be valuable in providing guidance on what forms of CDS do and do not work [77].”
BackgroundSelf-citationAdoption of electronic health records in Saudi Arabia hospitals: Knowledge and usage
Alharbi, R. (2022) · Journal of King Saud University - Science · doi:10.1016/j.jksus.2022.102470 · Cited by 21
The burden of inbox-messaging systems and its effect on work-life balance in dermatology
Bittar, P. G., & Nicholas, M. W. (2017) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2017.12.026 · Cited by 20
“However, increasing use raises concerns for their potential to contribute to burnout.(1-3) While prior studies have assessed the burden these systems cause on primary care providers, little is known about the factors driving use or the impact on physician burnout, and scant data about use by specialists is available.”
BackgroundDalal, A. K., Schaffer, A. C., Gershanik, E., Papanna, R., Eibensteiner, K., Nolido, N. V., Yoon, C. S., Williams, D. H., Lipsitz, S. R., Roy, C. L., et al. (2018) · Journal of General Internal Medicine · doi:10.1007/s11606-018-4393-y · Cited by 23
Veinot, T. C., Senteio, C. R., Hanauer, D. A., & Lowery, J. C. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx085 · Cited by 19
Barbieri, A. L., Fadare, O., Fan, L. L., Singh, H., & Parkash, V. (2018) · Journal of Pathology Informatics · doi:10.4103/jpi.jpi_70_17 · Cited by 19
Self-citationFarzandipour, M., Meidani, Z., Jabali, M. S., & Banadaki, R. D. (2018) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.13074 · Cited by 17
Duplicate patient records--implication for missed laboratory results.
Joffe, E., Bearden, C. F., Byrne, M. J., & Bernstam, E. V. (2012) · PubMed Central · Cited by 18
Implementation of Electronic Triggers to Identify Diagnostic Errors in Emergency Departments
Vaghani, V., Gupta, A., Mir, U., Wei, L., Murphy, D. R., Mushtaq, U., Sittig, D. F., Zimolzak, A. J., & Singh, H. (2024) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2024.6214 · Cited by 18
Self-citationDalal, A. K., Pesterev, B. M., Eibensteiner, K., Newmark, L. P., Samal, L., & Rothschild, J. M. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv007 · Cited by 17
Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism
Meyer, A. N. D., Murphy, D. R., Al-Mutairi, A., Sittig, D. F., Wei, L., Russo, E. M., & Singh, H. (2017) · Journal of General Internal Medicine · doi:10.1007/s11606-017-3988-z · Cited by 14
“However, in our prior work on determining delayed follow-up of abnormal laboratory (including TSH) and imaging results, we found that most instances without documented follow-up were truly instances where no follow-up occurred, as confirmed with the providers.(12,13,15) Second, due to limited resources, our study did…”
BackgroundResultSelf-citationDo not assume that no news is good news: test result management and communication in primary care
Kwan, J. L., & Cram, P. M. (2015) · BMJ Quality & Safety · doi:10.1136/bmjqs-2015-004645 · Cited by 16
“11 Furthermore, most EHRs currently lack even rudimentary sophistication in test result interpretation, such as the ability to differentiate an elevated serum creatinine in a patient with previously normal renal function (an urgent/emergent result) from an elevated creatinine in a patient on…”
BackgroundSittig, D. F., Salimi, M., Aiyagari, R. M., Banas, C. A., Clay, B. J., Gibson, K., Goel, A., Hines, R. B., Longhurst, C., Mishra, V. K., et al. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy033 · Cited by 16
Self-citationEffects of laboratory data exchange in the care of patients with HIV
Bell, D. S., Cima, L., Seiden, D. S., Nakazono, T. T., Alcouloumre, M. S., & Cunningham, W. E. (2012) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.07.012 · Cited by 11
“Recent efforts to decompose the tasks of laboratory result management represent an important step toward the broader goal of improving EHR support for these tasks [3, 23] These efforts will need to be paired with ongoing evaluation and monitoring of delays in test result follow-up [24].”
BackgroundTarkan, S., Catherine Plaisant, B., Shneiderman, B., & Hettinger, A. Z. (2011) · PubMed Central · Cited by 14
Application of Human Factors Methods to Understand Missed Follow-up of Abnormal Test Results
Rogith, D., Satterly, T., Singh, H., Sittig, D. F., Russo, E. M., Smith, M. W., Roosan, D., Bhise, V., & Murphy, D. R. (2020) · Applied Clinical Informatics · doi:10.1055/s-0040-1716537 · Cited by 13
Self-citationImproving patient safety via automated laboratory-based adverse event grading
Niland, J. C., Stiller, T., Neat, J., Londrc, A., Johnson, D., & Pannoni, S. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000513 · Cited by 13
“Deployment will require an appropriate workflow in clinic, and avoidance of ‘alert fatigue’ among caregivers.(25) 26 Adding a configurable rules engine interface to incorporate protocol-specific rules to ‘fine tune’ the algorithms will provide additional efficiency in future.”
BackgroundBernard, R., Benhamou, D., & Beloeil, H. (2010) · Annales Françaises d Anesthésie et de Réanimation · doi:10.1016/j.annfar.2010.09.010 · Cited by 12
Were My Diagnosis and Treatment Correct? No News is Not Necessarily Good News
Singh, H., & Sittig, D. F. (2014) · Journal of General Internal Medicine · doi:10.1007/s11606-014-2890-1 · Cited by 12
Self-citationEvidence that electronic health records can promote physician counseling for healthy behaviors
Bae, J., Hockenberry, J. M., Rask, K. J., & Becker, E. R. (2016) · Health Care Management Review · doi:10.1097/hmr.0000000000000108 · Cited by 12
Lau, B., Overby, C. L., Wirtz, H. S., & Devine, E. B. (2013) · Applied Clinical Informatics · doi:10.4338/aci-2013-06-ra-0041 · Cited by 13
A Sociotechnical Approach to Electronic Health Record Related Safety
Sittig, D. F., & Singh, H. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-809523-2.00014-5 · Cited by 11
Self-citationMazur, L. M., Marks, L. B., McLeod, R., Karwowski, W., Mosaly, P. R., Tracton, G. S., Adams, R., Hoyle, L., Das, S. K., & Chera, B. S. (2018) · Advances in Radiation Oncology · doi:10.1016/j.adro.2018.01.002 · Cited by 11
“(and unnecessary) cognitive effort and confusion on health care providers, which increases the potential for patient harm.(6-10) Indeed, there are reports that link patient harm to the suboptimal design and use of health IT,(11-15) including in radiation oncology.”
BackgroundStelling, B. E. V., Halvorsen, A. J., Dupras, D. M., Kearns, L., Kisielewski, M., Martin, S. K., Uthlaut, B. S., & Leasure, E. L. (2023) · Journal of Graduate Medical Education · doi:10.4300/jgme-d-23-00165.1 · Cited by 10
Thomas, J., Dahm, M. R., Li, J., Smith, P., Irvine, J., Westbrook, J. I., & Georgiou, A. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa093 · Cited by 12
Are Amended Surgical Pathology Reports Getting to the Correct Responsible Care Provider?
Parkash, V., Domfeh, A. B., Cohen, P., et al. (2014) · American Journal of Clinical Pathology · doi:10.1309/ajcpy55evinjclgx · Cited by 9
Li, J., Paoloni, R., Li, L., Callen, J. L., Westbrook, J. I., Runciman, W. B., & Georgiou, A. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01135-9 · Cited by 9
Failure to review STAT clinical laboratory requests and its economical impact
Borja, E. R., Martínez, C. V., Barba-Serrano, E., & Carratalá, A. (2016) · Biochemia Medica · doi:10.11613/bm.2016.005 · Cited by 7
“In addition to this, new information technology need to be developed in order to reduce errors in follow up requests and improve patient safety, given the volume of information that clinicians both generate and review (17,18).”
BackgroundContributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE
Dadlez, N. M., Adelman, J. S., Bundy, D. G., Singh, H., Applebaum, J. R., & Rinke, M. L. (2020) · Pediatric Quality and Safety · doi:10.1097/pq9.0000000000000299 · Cited by 7
Self-citationQian, Y., Ni, Z., Gui, W., & Liu, Y. (2021) · International Journal of Computational Intelligence Systems · doi:10.2991/ijcis.d.210203.006 · Cited by 7
“[37, 38] and Sittig and Singh [39] have made important contributions to patient safety.”
BackgroundMefford, M. T., Zhou, M. M., Zhou, H. C., Derakhshan, H., Harrison, T. N., Zia, M., Kanter, M. H., Scott, R. D., Imley, T. M., Sanders, M. A., et al. (2023) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2023.04.009 · Cited by 6
Metadata
- Authors
- Singh, H., Thomas, E. J., Sittig, D. F., Wilson, L., Espadas, D., Khan, M. M., & Petersen, L. A.
- Affiliations
- Michael E. DeBakey VA Medical Center (US)
- Memorial Hermann (US)
- Corresponding author
- Singh, Hardeep
- Venue
- The American Journal of Medicine
- Publisher
- Elsevier BV
- Published
- 2010-03
- Volume
- 123
- Issue
- 3
- Pages
- 238-244
- ISSN
- 0002-9343 (ISSN-L)
- PMC
- PMC2878665
- OpenAlex
- W1981106602
- Semantic Scholar
- 6cb4dbf1bbfb77ebcb84cea2013870878498f97c
- Cited by
- 160
- References
- 30
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 2 · 2023: 4 · 2022: 9 · 2021: 6 · 2020: 10 · 2019: 13 · 2018: 12 · 2017: 14 · 2016: 11 · 2015: 12 · 2014: 11 · 2013: 16 · 2012: 10
- FWCI
- 28.08
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The American Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- Funders
- National Institutes of Health (K23CA125585)
- VA National Center for Patient Safety (R18 HS17244-02)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Medical Laboratory Technology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Patient Safety and Medication Errors
- Keywords
- laboratory abnormalities, electronic health records, patient safety, HbA1c, anti-HCV antibodies, prostate-specific antigen, thyroid-stimulating hormone, outpatient care
- MeSH terms
- Communication, Diagnostic Errors, Female, Follow-Up Studies, Hepatitis C, Humans, Male, Practice Patterns, Physicians', Primary Health Care, Retrospective Studies, United States, Medical Records Systems, Computerized
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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