Validation of ICD-9-CM coding algorithm for improved identification of hypoglycemia visits
Open accessAbstract
BACKGROUND: Accurate identification of hypoglycemia cases by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes will help to describe epidemiology, monitor trends, and propose interventions for this important complication in patients with diabetes. Prior hypoglycemia studies utilized incomplete search strategies and may be methodologically flawed. We sought to validate a new ICD-9-CM coding algorithm for accurate identification of hypoglycemia visits. METHODS: This was a multicenter, retrospective cohort study using a structured medical record review at three academic emergency departments from July 1, 2005 to June 30, 2006. We prospectively derived a coding algorithm to identify hypoglycemia visits using ICD-9-CM codes (250.3, 250.8, 251.0, 251.1, 251.2, 270.3, 775.0, 775.6, and 962.3). We confirmed hypoglycemia cases by chart review identified by candidate ICD-9-CM codes during the study period. The case definition for hypoglycemia was documented blood glucose 3.9 mmol/l or emergency physician charted diagnosis of hypoglycemia. We evaluated individual components and calculated the positive predictive value. RESULTS: We reviewed 636 charts identified by the candidate ICD-9-CM codes and confirmed 436 (64%) cases of hypoglycemia by chart review. Diabetes with other specified manifestations (250.8), often excluded in prior hypoglycemia analyses, identified 83% of hypoglycemia visits, and unspecified hypoglycemia (251.2) identified 13% of hypoglycemia visits. The absence of any predetermined co-diagnosis codes improved the positive predictive value of code 250.8 from 62% to 92%, while excluding only 10 (2%) true hypoglycemia visits. Although prior analyses included only the first-listed ICD-9 code, more than one-quarter of identified hypoglycemia visits were outside this primary diagnosis field. Overall, the proposed algorithm had 89% positive predictive value (95% confidence interval, 86-92) for detecting hypoglycemia visits. CONCLUSION: The proposed algorithm improves on prior strategies to identify hypoglycemia visits in administrative data sets and will enhance the ability to study the epidemiology and design interventions for this important complication of diabetes care.
AI snapshot
Written from the paper’s full text.
TL;DR
The study validated a new ICD-9-CM coding algorithm for identifying emergency department hypoglycemia visits, reporting an overall positive predictive value of 89% (95% CI 86–92). The algorithm improved on prior strategies by including code 250.8 and excluding visits with alternate co-diagnoses.
Key findings
- Among 679 abstracted charts (the abstract reports 636), 436 (64%) were confirmed hypoglycemia cases; inter-rater agreement for chart review was kappa = 0.97.
- Code 250.8 identified 83% of confirmed hypoglycemia visits; absence of any predetermined co-diagnosis codes improved its PPV from 62% to 92%, while excluding only 10 (2%) true hypoglycemia visits. Code 251.2 identified 13% of confirmed visits.
- The proposed algorithm had 89% PPV (95% CI 86–92); more than one-quarter of confirmed cases had a candidate code outside the first-listed diagnosis field, and first-position codes had higher PPV than other positions (93% vs. 81%, p < 0.01).
- Removing code 962.3 increased the algorithm’s PPV from 89% to 91% (95% CI 88–93) while estimated sensitivity remained 97%.
Methods
- Multicenter, retrospective cohort validation using structured medical record review at three urban academic emergency departments from July 1, 2005 to June 30, 2006; 174,134 ED visits yielded 901 patients and 1,139 candidate visits, with 679 charts abstracted.
- Candidate ICD-9-CM codes were 250.3, 250.8, 251.0, 251.1, 251.2, 270.3, 775.0, 775.6, and 962.3, searched in all diagnosis fields up to ten; hypoglycemia was confirmed by documented blood glucose 3.9 mmol/l or emergency physician charted diagnosis.
- Analyses calculated PPV with 95% confidence intervals, kappa for a 10% double-abstracted subgroup, chi-squared tests for site/disposition/code position, and sensitivity analysis assuming missed cases.
Limitations
- Stated: 25% of charts were missing or incomplete and not abstracted; findings come from three academic EDs and may not generalize; false negatives were not formally evaluated, so only PPV was accurately calculated and sensitivity/specificity/NPV estimates are limited; retrospective chart review may overestimate or underestimate true cases.
- Evident: the abstract reports 636 reviewed charts while the results report 679 abstracted charts, a discrepancy that complicates interpretation of the validation sample size.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 8 cited sources checked · 0 supported · 0 flagged
- Findingown data
Chart review confirmed 436 (64%) cases of hypoglycemia among reviewed/abstracted charts.
“We reviewed 636 charts identified by the candidate ICD-9-CM codes and confirmed 436 (64%) cases of hypoglycemia by chart review.”
- Also stated in: § Results · plain
“Based on the chart review, we confirmed 436 (64%) cases of hypoglycemia.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
More than one-quarter of identified hypoglycemia visits had a candidate ICD-9-CM code outside the first-listed/primary diagnosis field.
“Although prior analyses included only the first-listed ICD-9 code, more than one-quarter of identified hypoglycemia visits were outside this primary diagnosis field.”
- Also stated in: § Results · plain
“Over a quarter of confirmed cases had a candidate code outside of the first-listed diagnosis field.”
- Also stated in: § Discussion · hedged
“limitation to the primary diagnosis field would have excluded 27% of hypoglycemia cases.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
The proposed algorithm had 89% positive predictive value (95% CI 86-92) for detecting hypoglycemia visits.
“Overall, the proposed algorithm had 89% positive predictive value (95% confidence interval, 86–92) for detecting hypoglycemia visits.”
- Also stated in: § Results · plain
“Overall, the proposed algorithm had PPV of 89% (95%CI, 86–92) for detecting hypoglycemia visits.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
ICD-9-CM code 250.8 identified 83% of confirmed hypoglycemia visits.
“Diabetes with other specified manifestations (250.8), often excluded in prior hypoglycemia analyses, identified 83% of hypoglycemia visits”
- Also stated in: § Results · plain
“The majority (83%) of confirmed cases of hypoglycemia were coded as 250.8.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
Cases identified by ICD-9-CM code 962.3 had a low PPV of 54%.
“Post-hoc review of the algorithm performance suggested that cases identified by 962.3 demonstrated low PPV (54%)”
Quote in the paperSubstantial claim
- Findingown data
ICD-9-CM code 251.2 identified 13% of hypoglycemia visits.
“unspecified hypoglycemia (251.2) identified 13% of hypoglycemia visits.”
Quote in the paperNot a substantial claim - Findingown data
The absence of any predetermined co-diagnosis codes improved the positive predictive value of code 250.8 from 62% to 92%.
“The absence of any predetermined co-diagnosis codes improved the positive predictive value of code 250.8 from 62% to 92%”
- Also stated in: § Results · plain
“The absence of any co-diagnosis codes improved the positive predictive value of 250.8 from 62% to 92%”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
Excluding visits with co-diagnosis codes excluded only 10 (2%) true hypoglycemia visits.
“while excluding only 10 (2%) true hypoglycemia visits.”
- Also stated in: § Results · plain
“while excluding 10 (2%) of true hypoglycemia visits.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
Cases identified by 962.3 primarily represented patients with excessive insulin or oral hypoglycemic use without development of clinical or laboratory hypoglycemia.
“primarily representing patients with excessive insulin or oral hypoglycemic use without development of clinical or laboratory hypoglycemia.”
Quote in the paperSubstantial claim - Findingown data
Algorithm codes in the first ICD-9-CM position had a higher PPV for confirmed hypoglycemia visits than codes in other positions (93% vs. 81%, p < 0.01).
“Algorithm codes in the first ICD-9-CM position had a higher PPV for confirmed hypoglycemia visits than other positions (93% vs. 81%, p < 0.01).”
Quote in the paperNot a substantial claim - Findingown data
250.8 with exclusion of alternate co-diagnoses and 251.2 comprised >95% of hypoglycemia identified by the algorithm.
“Overall, 250.8 with exclusion of alternate co-diagnoses and 251.2 comprised >95% of hypoglycemia identified by the algorithm.”
Quote in the paperSubstantial claim - Findingown data
Codes 270.3, 775.0, and 775.6 were rare in the ED setting.
“As anticipated, codes 270.3, 775.0 and 775.6 were rare in the ED setting but may have utility for other settings, such as maternity and neonatal units.”
Quote in the paperNot a substantial claim - Premisecitation
Prior hypoglycemia studies did not include ICD-9-CM code 250.8 in their search strategies.
“Notably, none of these studies included 250.8 in their search strategies, nor accounted these possible missed episodes of hypoglycemia.”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [11] Shorr RI, Ray WA, Daugherty JR, Griffin MR: Incidence and risk factors for serious hypoglycemia in older persons using insulin or sulfonylureas. Arch Intern Med. 1997, 15: 1681-1687. 10.1001/archinte.157.15.1681. source
Not checked in the free run.
- cites [12] Herings RMC, de Boer A, Stricker BHCh, Leufkens HGM, Porsuis A: Hypoglycemia associated with use of inhibitors of angiotensin converting enzyme. Lancet. 1995, 345: 1195-1198. 10.1016/S0140-6736(95)91988-0. source
Not checked in the free run.
- cites [13] Morris AD, Boyle DIR, McMahon AD, Pearce H, Evans JM, Newton RW, Jung RT, MacDonald TM: ACE inhibitor use is associated with hospitalization for severe hypoglycemia in patients with diabetes. Diabetes Care. 1997, 20: 1363-1367. 10.2337/diacare.20.9.1363. source
Not checked in the free run.
- cites [14] Shorr RI, Ray WA, Daugherty JR, Griffin MR: Antihypertensives and the risk of serious hypoglycemia in older persons using insulin or sulfonylureas. JAMA. 1997, 278: 40-43. 10.1001/jama.278.1.40. source
Not checked in the free run.
- Interpretationreasoning
The proposed ICD-9-CM coding algorithm for hypoglycemia would be expected to perform as well or better than coding strategies for other diagnoses in accurate case identification from administrative data.
“Based on these comparisons, the proposed ICD-9-CM coding algorithm for hypoglycemia would be expected to perform as well or better than coding strategies for other diagnoses in accurate case identification from administrative data.”
Quote in the paperSubstantial claim - Interpretationown data
Exclusion of 250.8 in prior studies likely contributed to substantial underestimates in the incidence of hypoglycemia.
“exclusion of this code in these prior studies likely contributed to substantial underestimates in the incidence of hypoglycemia.”
Quote in the paperSubstantial claim - Study design and conductown data
Confirmation of hypoglycemia by chart review had very high inter-rater agreement (kappa = 0.97).
“Confirmation of hypoglycemia had a very high inter-rater agreement (kappa = 0.97).”
Quote in the paperNot a substantial claim - Study design and conductown data
The study could not formally evaluate false negatives, so sensitivity, specificity, and NPV estimates are significantly limited.
“We were unable to formally evaluate false-negatives in our data set. Thus, we were only able to calculate PPV with accuracy, and our estimates for sensitivity, specificity, and NPV are significantly limited.”
Quote in the paperSubstantial claim - Interpretationown data
The coding accuracy results may not generalize to other areas of the hospital, outpatient providers, and other geographic areas.
“The coding of hypoglycemia visits was based on three academic EDs and may not generalize to other areas of the hospital, outpatient providers, and other geographic areas.”
Quote in the paperNot a substantial claim - Interpretationown data
The proposed algorithm improves on prior strategies to identify hypoglycemia cases in administrative data sets.
“This algorithm improves on prior strategies to identify hypoglycemia cases in administrative data sets”
- Also stated in: § Conclusion · plain
“The proposed algorithm improves on prior strategies to identify hypoglycemia visits in administrative data sets”
Quote in the paperSubstantial claim - Also stated in: § Conclusion · plain
- May combine two claims. 10
- Classified as probably not a substantial claim. 4
May combine two claims.
Findingown dataExclusion of alternate co-diagnoses reliably eliminated 85% of false-positive cases coded as 250.8, while eliminating only a small number of true-positive cases.
“Exclusion of these cases reliably eliminated 85% of false-positive cases coded as 250.8, while eliminating only a small number of true-positive cases.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataRemoving 962.3 as a candidate code and relying only on 250.8 increased the overall algorithm PPV from 89% to 91% (95% CI 88-93) while estimated sensitivity remained at 97%.
“When we removed 962.3 as a candidate code and relied only on coding for 250.8 in these cases, the PPV for the overall algorithm increased from 89% to 91% (95%CI, 88–93) while the estimated sensitivity remained at 97%.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThere was no significant difference in PPV when data were stratified by study site or ED disposition (p = 0.86 and 0.22, respectively).
“There was no significant difference in PPV when data were stratified by site or by ED disposition (p = 0.86 and 0.22, respectively).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningUnder the assumption that candidate ICD-9-CM codes captured all ED presentations with hypoglycemia, the algorithm had 97% sensitivity, >99% specificity, and >99% NPV.
“Based on the assumption that the candidate ICD-9-CM codes captured all ED presentations with hypoglycemia, we estimate that the algorithm had 97% sensitivity, >99% specificity, and >99% NPV.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The candidate ICD-9-CM codes captured all emergency department presentations with hypoglycemia.
May combine two claims.
InterpretationreasoningAssuming the algorithm missed at most 10% of hypoglycemia visits, the minimum sensitivity was 88% with NPV and specificity remaining >99%.
“Assuming the algorithm missed at most 10% of hypoglycemia visits, we estimate a minimum sensitivity of 88% with NPV and specificity remaining >99%.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The algorithm missed at most 10% of hypoglycemia visits.
May combine two claims.
Study design and conductown dataThere were no significant differences in age, sex, race/ethnicity, and distribution of candidate ICD-9-CM codes between abstracted and excluded patients (all p > 0.05).
“There were no significant differences in age, sex, race/ethnicity, and distribution of candidate ICD-9-CM codes comparing abstracted and excluded patients (all p > 0.05).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationThe glucose threshold for hypoglycemia was 3.9 mmol/l, based on the American Diabetes Association Workgroup on Hypoglycemia consensus recommendation.
“We based the glucose threshold on the consensus recommendation defined by the American Diabetes Association Workgroup on Hypoglycemia [16].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [16] American Diabetes Association Workgroup on Hypoglycemia: Defining and reporting hypoglycemia in diabetes. Diabetes Care. 2005, 28: 1245-1249. 10.2337/diacare.28.5.1245. source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
PremisecitationJohnson et al. reported that ICD-9-CM code 250.8 identified over half of hypoglycemia episodes and had a PPV of 73% for their case definition.
“Johnson, et al. first reported the utility of 250.8 in their strategy to identify ED visits for hypoglycemia [10]. In their analysis, this code also identified over half of hypoglycemia episodes and had a PPV of 73% for their case definition of hypoglycemia.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] Johnson ES, Koepsell TD, Reiber G, Stergachis A, Platt R: Increasing incidence of serious hypoglycemia in insulin users. J Clin Epidemiol. 2002, 55: 253-259. 10.1016/S0895-4356(01)00479-6. source
Not checked in the free run.
Classified as probably not a substantial claim. May combine two claims.
Study design and conductown dataThe study abstracted 679 charts (75% of visits by unique patients) and excluded 222 patients with missing or incomplete documentation.
“We abstracted 679 charts (75% of visits by unique patients) and excluded the remaining 222 patients with missing or incomplete documentation.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationJohnson et al. limited their search to first-listed ICD-9-CM codes and excluded all other diagnosis fields.
“First, Johnson et al. limited their search to first-listed ICD-9-CM codes and excluded all other diagnosis fields.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [10] Johnson ES, Koepsell TD, Reiber G, Stergachis A, Platt R: Increasing incidence of serious hypoglycemia in insulin users. J Clin Epidemiol. 2002, 55: 253-259. 10.1016/S0895-4356(01)00479-6. source
Not checked in the free run.
May combine two claims.
PremisecitationThe ICD-9-CM classification system is imperfect for case identification because it was created for reimbursement rather than research purposes.
“The ICD-9-CM classification system is imperfect for case identification, as it was created for reimbursement rather than research purposes [18].”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [18] O'Malley KJ, Cook KF, Price MD, Wildes KR, Hurdle JF, Ashton CM: Measuring diagnoses: ICD code accuracy. HSR. 2005, 40: 1620-1639.
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningRetrospective chart review for hypoglycemia may overestimate or underestimate the true number of cases.
“the accuracy of case confirmation by chart review depended on a retrospective evaluation for hypoglycemia, which may overestimate or underestimate the true number of cases.”
Quote in the paperNot a substantial claim
The authors state this as an assumption.
The candidate ICD-9-CM codes captured all emergency department presentations with hypoglycemia.
“Under the ideal assumption that no cases were missed, we calculated estimated point estimates for sensitivity, specificity, and negative predictive values (NPV).”
“Based on the assumption that the candidate ICD-9-CM codes captured all ED presentations with hypoglycemia, we estimate that the algorithm had 97% sensitivity, >99% specificity, and >99% NPV.”
The authors state this as an assumption.
The algorithm missed at most 10% of hypoglycemia visits.
“Assuming the algorithm missed at most 10% of hypoglycemia visits, we estimate a minimum sensitivity of 88% with NPV and specificity remaining >99%.”
The authors state this as an assumption.
Chart validation is the gold standard for confirmation of true hypoglycemia visits.
“We considered this chart validation as the gold standard for confirmation of true hypoglycemia visits.”
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 real rate of hypoglycaemia is probably higher than the observed 9.1% because events not captured in claims data were not included, so the incidence is underreported.
“The real rate of hypoglycaemia is probably even higher as hypoglycaemia events that were not captured in claims data were not included, with the result that the incidence of hypoglycaemia is underreported.19,25”
From Early hypoglycaemia and adherence after basal insulin initiation in a nationally representative sample of Medicare beneficiaries with type 2 diabetes (2019) · cites this paper as [19]
Claims data are often inherently prone to underrepresenting hypoglycaemia as only ICD-9-CM/ICD-10-CM codes associated with a healthcare encounter are captured.
“Furthermore, claims data are often inherently prone to underrepresenting hypoglycaemia as only ICD-9-CM/ICD-10-CM codes associated with a healthcare encounter are captured.19,25,31”
From Early hypoglycaemia and adherence after basal insulin initiation in a nationally representative sample of Medicare beneficiaries with type 2 diabetes (2019) · cites this paper as [19]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Abstract case percentage does not match its chart count
MinorThe abstract reports 436 confirmed cases among 636 reviewed charts, which is 68.6%, not 64%. The Results section reports 679 reviewed charts, a denominator that does yield approximately 64%.
Reported 64 · recomputed 68.553459
“We reviewed 636 charts identified by the candidate ICD-9-CM codes and confirmed 436 (64%) cases of hypoglycemia by chart review.”
Share of ED visits with possible hypoglycemia is understated
MinorThe reported 1,139 visits are approximately 0.65% of 174,134 ED visits, which rounds to 0.7% at one decimal place, not 0.5%.
Reported 0.5 · recomputed 0.654094
“Of the 174,134 ED visits at the three institutions during the data collection period, we identified 901 patients with candidate ICD-9-CM codes. These patients accounted for 1,139 visits with possible hypoglycemia (i.e., 0.5% of all ED visits).”
Cites
(1993) · New England Journal of Medicine · doi:10.1056/nejm199309303291401 · Cited by 24,667 · see citing works
Turner, R. C., Fox, C., Matthews, McElroy, H. H., Cull, C. A., Holman, R. R., Neil, P., Hadden, D. R., Wright, D., Manley, E., et al. (1998) · The Lancet · Cited by 8,419 · see citing works
International Classification of Diseases, 10th Revision
Tassé, M. J., & Bush, K. (2018) · The SAGE Encyclopedia of Intellectual and Developmental Disorders · doi:10.4135/9781483392271.n276 · Cited by 1,922 · see citing works
Cryer, P. E., Davis, S. N., & Shamoon, H. (2003) · Diabetes Care · doi:10.2337/diacare.26.6.1902 · Cited by 1,160 · see citing works
Defining and Reporting Hypoglycemia in Diabetes
American Diabetes Association Workgroup on Hypoglycemia (2005) · Diabetes Care · doi:10.2337/diacare.28.5.1245 · Cited by 1,146 · see citing works
Measuring Diagnoses: ICD Code Accuracy
O’Malley, K. J., Cook, K. F., Price, M. D., Wildes, K. R., Hurdle, J. F., & Ashton, C. M. (2005) · Health Services Research · doi:10.1111/j.1475-6773.2005.00444.x · Cited by 1,123 · see citing works
Hypoglycaemia: the limiting factor in the glycaemic management of type I and type II diabetes.
Cryer, P. (2002) · Diabetologia · doi:10.1007/s00125-002-0822-9 · Cited by 794 · see citing works
Hypoglycemia in the Diabetes Control and Complications Trial
The Diabetes Control and Complications Trial Research Group (1997) · Diabetes · doi:10.2337/diab.46.2.271 · Cited by 746 · see citing works
Incidence and risk factors for serious hypoglycemia in older persons using insulin or sulfonylureas
Shorr, R. I. (1997) · Archives of Internal Medicine · doi:10.1001/archinte.1997.00440360095010 · Cited by 459 · see citing works
Laing, S. P., Swerdlow, A. J., Slater, S. D., Botha, J. L., Burden, A. C., Waugh, N. R., Smith, A. W. M., Hill, R. D., Bingley, P. J., Patterson, C. C., et al. (1999) · Diabetic Medicine · doi:10.1046/j.1464-5491.1999.00075.x · Cited by 427 · see citing works
Accuracy of ICD-9-CM Coding for the Identification of Patients With Acute Ischemic Stroke
Goldstein, L. B. (1998) · Stroke · doi:10.1161/01.str.29.8.1602 · Cited by 408 · see citing works
Laing, S. P., Swerdlow, A. J., Slater, S. D., Botha, J. L., Burden, A. C., Waugh, N. R., Smith, A. W. M., Hill, R. D., Bingley, P. J., Patterson, C. C., et al. (1999) · Diabetic Medicine · doi:10.1046/j.1464-5491.1999.00076.x · Cited by 303 · see citing works
Frequency and Morbidity of Severe Hypoglycaemia in Insulin‐treated Diabetic Patients
MacLeod, K. M., Hepburn, D. A., & Frier, B. M. (1993) · Diabetic Medicine · doi:10.1111/j.1464-5491.1993.tb00051.x · Cited by 250 · see citing works
Hypoglycaemia associated with use of inhibitors of angiotensin converting enzyme
Herings, R. M. C., de Boer, A., Leufkens, H. G. M., Porsius, A., & Stricker, B. H. C. (1995) · The Lancet · doi:10.1016/s0140-6736(95)91988-0 · Cited by 217 · see citing works
Accuracy of Mild Traumatic Brain Injury Case Ascertainment Using ICD-9 Codes
Bazarian, J. J., Veazie, P. J., Mookerjee, S., & Lerner, E. B. (2005) · Academic Emergency Medicine · doi:10.1197/j.aem.2005.07.038 · Cited by 193 · see citing works
Guevara, R. E., Butler, J. C., Marston, B. J., et al. (1999) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009804 · Cited by 141 · see citing works
Shorr, R. I., Ray, W. A., Daugherty, J. R., & Griffin, M. R. (1997) · PubMed · Cited by 114 · see citing works
Accuracy of ICD-9 coding for Clostridium difficile infections: a retrospective cohort
Scheurer, D. B., Hicks, L. S., Cook, E. F., et al. (2006) · Epidemiology and Infection · doi:10.1017/s0950268806007655 · Cited by 112 · see citing works
Chronic lung disease secondary to ammonia inhalation injury: A report on three cases
de la Hoz, R. E., Schlueter, D. P., & Rom, W. N. (1996) · American Journal of Industrial Medicine · doi:10.1002/(sici)1097-0274(199602)29:2 · Cited by 110 · see citing works
Morris, A. D., Boyle, D. I., McMahon, A. D., Pearce, H., Evans, J. M. M., Newton, R. W., Jung, R. T., MacDonald, T. M., & The Darts/Memo Collaboration (1997) · Diabetes Care · doi:10.2337/diacare.20.9.1363 · Cited by 109 · see citing works
Shorr, R. I. (1997) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.1997.03550010054039 · Cited by 83 · see citing works
ICD-9-CM codes poorly indentified venous thromboembolism during pregnancy
White, R. H. R., Brickner, L. A., & Scannell, K. A. (2004) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2004.02.003 · Cited by 82 · see citing works
Incidence and Costs of Severe Hypoglycemia
Holstein, A., Plaschke, A., & Egberts, E. ‐. (2002) · Diabetes Care · doi:10.2337/diacare.25.11.2109 · Cited by 72 · see citing works
Accuracy of administrative health data for the diagnosis of upper gastrointestinal diseases
Lopushinsky, S. R., Covarrubia, K. A., Rabeneck, L., et al. (2007) · Surgical Endoscopy · doi:10.1007/s00464-006-9136-1 · Cited by 49 · see citing works
Increasing incidence of serious hypoglycemia in insulin users
JOHNSON, E., KOEPSELL, T., REIBER, G., STERGACHIS, A., & PLATT, R. (2002) · Journal of Clinical Epidemiology · doi:10.1016/s0895-4356(01)00479-6 · Cited by 46 · see citing works
Ireland, J. T. (1986) · Diabetic Medicine · doi:10.1111/j.1464-5491.1986.tb00767.x · Cited by 25 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Hypoglycemic episodes and risk of dementia in older patients with type 2 diabetes mellitus
Whitmer, R. A. (2009) · JAMA · doi:10.1001/jama.2009.460 · Cited by 1,128 · see citing works
Prevalence and co-prevalence of comorbidities among patients with type 2 diabetes mellitus
Iglay, K., Hannachi, H., Joseph Howie, P., Xu, J., Li, X., Engel, S. S., Moore, L. M., & Rajpathak, S. (2016) · Current Medical Research and Opinion · doi:10.1185/03007995.2016.1168291 · Cited by 511 · see citing works
Frequency of hypoglycemia and its significance in chronic kidney disease
Moen, M. F., Zhan, M., Hsu, V. D., Walker, L. D., Einhorn, L. M., Seliger, S. L., & Fink, J. C. (2009) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.00800209 · Cited by 423 · see citing works
Trends in drug utilization, glycemic control, and rates of severe hypoglycemia, 2006–2013
Lipska, K. J., Yao, X., Herrin, J., McCoy, R. G., Ross, J. S., Steinman, M. A., Inzucchi, S. E., Gill, T. M., Krumholz, H. M., & Shah, N. D. (2017) · Diabetes Care · doi:10.2337/dc16-0985 · Cited by 306 · see citing works
Lee, A. K., Warren, B., Lee, C. J., McEvoy, J. W., Matsushita, K., Huang, E. S., Sharrett, A. R., Coresh, J., & Selvin, E. (2018) · Diabetes Care · doi:10.2337/dc17-1669 · Cited by 226 · see citing works
Silbert, R., Salcido-Montenegro, A., Rodriguez-Gutierrez, R., Katabi, A., & McCoy, R. G. (2018) · Current Diabetes Reports · doi:10.1007/s11892-018-1018-0 · Cited by 229 · see citing works
Karter, A. J., Warton, E. M., Lipska, K. J., Ralston, J. D., Moffet, H. H., Jackson, G. G., Huang, E. S., & Miller, D. R. (2017) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2017.3844 · Cited by 150 · see citing works
Intensive treatment and severe hypoglycemia among adults with type 2 diabetes
McCoy, R. G., Lipska, K. J., Yao, X., Ross, J. S., Montori, V. M., & Shah, N. D. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.2275 · Cited by 143 · see citing works
Pathak, R. D., Schroeder, E. B., Seaquist, E. R., Zeng, C., Lafata, J. E., Thomas, A., Desai, J., Waitzfelder, B., Nichols, G. A., Lawrence, J. M., et al. (2016) · Diabetes Care · doi:10.2337/dc15-0858 · Cited by 140 · see citing works
McCoy, R. G., Lipska, K. J., Van Houten, H. K., & Shah, N. D. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.19099 · Cited by 141 · see citing works
Lee, A. K., Lee, C. J., Huang, E. S., Sharrett, A. R., Coresh, J., & Selvin, E. (2017) · Diabetes Care · doi:10.2337/dc17-0819 · Cited by 119 · see citing works
Basu (2017) · doi:10.1097/mlr.0000000000000728 · Cited by 77 · see citing works
Hypoglycemia after antimicrobial drug prescription for older patients using sulfonylureas
Parekh, T. M., Raji, M., Lin, Y.-L., Tan, A., Kuo, Y.-F., & Goodwin, J. S. (2014) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2014.3293 · Cited by 75 · see citing works
Lipska, K. J., Parker, M. M., Moffet, H. H., Huang, E. S., & Karter, A. J. (2018) · JAMA · doi:10.1001/jama.2018.7993 · Cited by 76 · see citing works
Surveillance of hypoglycemia-limitations of emergency department and hospital utilization data
Karter, A. J., Moffet, H. H., Liu, J. Y., & Lipska, K. J. (2018) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2018.1014 · Cited by 73 · see citing works
Karter, A. J., Lipska, K. J., O’Connor, P. J., Liu, J. Y., Moffet, H. H., Schroeder, E. B., Lawrence, J. M., Nichols, G. A., Newton, K. M., Pathak, R. D., et al. (2017) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2017.02.009 · Cited by 53 · see citing works
Misra-Hebert, A. D., Pantalone, K. M., Ji, X., Milinovich, A., Dey, T., Chagin, K. M., Bauman, J. M., Kattan, M. W., & Zimmerman, R. S. (2018) · Diabetes Care · doi:10.2337/dc17-1834 · Cited by 46 · see citing works
Revalidation of the hypoglycemia risk stratification tool using ICD-10 codes
Karter, A. J., Warton, E. M., Moffet, H. H., Ralston, J. D., Huang, E. S., Miller, D. R., & Lipska, K. J. (2019) · Diabetes Care · doi:10.2337/dc18-2154 · Cited by 42 · see citing works
Recurrent hospitalizations for severe hypoglycemia and hyperglycemia among U.S. adults with diabetes
McCoy, R. G., Herrin, J., Lipska, K. J., & Shah, N. D. (2018) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2018.04.007 · Cited by 40 · see citing works
Ratzki‐Leewing, A., Black, J. E., Kahkoska, A. R., Ryan, B. L., Zou, G., Klar, N., Timcevska, K., & Harris, S. B. (2023) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.15268 · Cited by 24 · see citing works
Hypoglycemia communication in primary care visits for patients with diabetes
Pilla, S. J., Park, J., Schwartz, J. L., Albert, M. C., Ephraim, P. L., Boulware, L. E., Mathioudakis, N. N., Maruthur, N. M., Beach, M. C., & Greer, R. C. (2021) · Journal of General Internal Medicine · doi:10.1007/s11606-020-06385-x · Cited by 23 · see citing works
Real-World Evaluation of the Effects of Counseling and Education in Diabetes Management
Dalal, M. R., Robinson, S. B., & Sullivan, S. D. (2014) · Diabetes Spectrum · doi:10.2337/diaspect.27.4.235 · Cited by 18 · see citing works
Pilla, S. J., Kraschnewski, J. L., Lehman, E. B., Kong, L., Francis, E., Poger, J. M., Bryce, C. L., Maruthur, N. M., & Yeh, H.-C. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002153 · Cited by 16 · see citing works
Bajpai, S., Wong-Jacobson, S., Liu, D., Mitchell, B., Haynes, G., Syring, K., Ali, A. K., & Chinthammit, C. (2021) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2021.27.3.385 · Cited by 14 · see citing works
Lee, S., Ock, M., Kim, H., & Kim, H. (2020) · Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy · doi:10.1002/phar.2450 · Cited by 13 · see citing works
Li, P., Geng, Z., Ladage, V. P., Wu, J., Lorincz, I., & Doshi, J. A. (2019) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.13832 · Cited by 13 · see citing works
Hood, R. C., Borra, S., Fan, L., Pollom, R. D., Huang, A., & Chen, J. (2021) · Endocrine Practice · doi:10.1016/j.eprac.2021.05.006 · Cited by 9 · see citing works
Wong, C. K. H., Tong, T., Cheng, G. H. L., Tang, E. H. M., Thokala, P., Tse, E. T. Y., & Lam, C. L. K. (2019) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.13657 · Cited by 7 · see citing works
- Authors
- Ginde, A. A., Blanc, P. G., Lieberman, R. M., & Camargo, C. A.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Massachusetts General Hospital (US)
- Corresponding author
- Ginde, Adit A
- Venue
- BMC Endocrine Disorders
- Published
- 2008-04-01
- Volume
- 8
- Issue
- 1
- Pages
- 4-4
- ISSN
- 1472-6823 (ISSN-L)
- PMC
- PMC2323001
- OpenAlex
- W2048981123
- Cited by
- 234
- References
- 29
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 7 · 2023: 13 · 2022: 12 · 2021: 21 · 2020: 17 · 2019: 24 · 2018: 28 · 2017: 20 · 2016: 20 · 2015: 18 · 2014: 19 · 2013: 11 · 2012: 3
- FWCI
- 9.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Endocrine Disorders (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Keywords
- hypoglycemia, diabetes mellitus, emergency department visits, positive predictive value, case definition, blood glucose, chart review validation, diabetes epidemiology, electronic health records
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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
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 ›
Are you an author, or do you see a problem with this page? Request a review
