Temporal trends of hemoglobin A1c testing
Open accessAbstract
OBJECTIVE: The study of utilization patterns can quantify potential overuse of laboratory tests and find new ways to reduce healthcare costs. We demonstrate the use of distributional analytics for comparing electronic health record (EHR) laboratory test orders across time to diagnose and quantify overutilization. MATERIALS AND METHODS: We looked at hemoglobin A1c (HbA1c) testing across 119,000 patients and 15 years of hospital records. We examined the patterns of HbA1c ordering before and after the publication of the 2002 American Diabetes Association guidelines for HbA1c testing. We conducted analyses to answer three questions. What are the patterns of HbA1c ordering? Do HbA1c orders follow the guidelines with respect to frequency of measurement? If not, how and why do they depart from the guidelines? RESULTS: The raw number of HbA1c orderings has steadily increased over time, with a specific increase in low-measurement orderings (<6.5%). There is a change in ordering pattern following the 2002 guideline (p<0.001). However, by comparing ordering distributions, we found that the changes do not reflect the guidelines and rather exhibit a new practice of rapid-repeat testing. The rapid-retesting phenomenon does not follow the 2009 guidelines for diabetes diagnosis either, illustrated by a stratified HbA1c value analysis. DISCUSSION: Results suggest HbA1c test overutilization, and contributing factors include lack of care coordination, unexpected values prompting retesting, and point-of-care tests followed by confirmatory laboratory tests. CONCLUSIONS: We present a method of comparing ordering distributions in an EHR across time as a useful diagnostic approach for identifying and assessing the trend of inappropriate use over time.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
CONCERN EWS's methodological choices, including robust modeling of temporal data patterns and use of nursing assessment and observational data, allowed it to have accurate and robust predictive power and sufficient lead time to alter a patient's clinical trajectory.
“Several methodological choices allowed CONCERN EWS to have accurate and robust predictive power and sufficient lead time to alter a patient’s clinical trajectory as we observed in this trial, including: (1) robust modeling of temporal data patterns40–42 (for example, time of day, day of week and patient hospital day) for health care processes (for example, nurses’ surveillance and medication”
From Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial (2025) · cites this paper as [43]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Handelsman, Y., Mechanick, J. I., Blonde, L., Grunberger, G., Bloomgarden, Z. T., Bray, G. A., Dagogo-Jack, S., Davidson, J. A., Einhorn, D., Ganda, O., et al. (2011) · Endocrine Practice · doi:10.4158/ep.17.s2.1 · Cited by 513 · see citing works
Identifying and mitigating biases in EHR laboratory tests
Pivovarov, R., Albers, D. J., Sepulveda, J. L., & Elhadad, N. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.03.016 · Cited by 91 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 22
- [1]Smith M, Saunders R, Stuckhardt L, et al. Committee on Learning the Health Care System in America. Best care at lower cost: the path to continuously learning health care in America, Washington, DC: Institute of Medicine; 2012. [PubMed] [Google Scholar]
- [2]Sacks DB, Bruns DE, Goldstein DE, et al. Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Clin Chem 2002;48:436–72 [PubMed] [Google Scholar]
- [3]Selvin E, Steffes MW, Zhu H, et al. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med 2010;362:800–11 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [5]Committee IE. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327–34 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [6]American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care 2010;33(Suppl 1):S62–S69 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7]Association AD. Standards of medical care in diabetes–2013. Diabetes Care 2013;36(Suppl 1):S11–66 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8]Laxmisan A, Vaughan-Sarrazin M, Cram P. Repeated Hemoglobin A1C ordering in the VA health system. Am J Med 2011;124:342–9 [DOI] [PubMed] [Google Scholar]
- [9]Driskell OJ, Holland D, Hanna FW, et al. Inappropriate requesting of glycated hemoglobin (Hb A1c) is widespread: assessment of prevalence, impact of national guidance, and practice-to-practice variability. Clin Chem 2012;58:906–15 [DOI] [PubMed] [Google Scholar]
- [10]Akan P, Cimrin D, Ormen M, et al. The inappropriate use of HbA1c testing to monitor glycemia: is there evidence in laboratory data? J Eval Clin Pract 2007;13:21–4 [DOI] [PubMed] [Google Scholar]
- [11]Van Walraven C. Population-based study of repeat laboratory testing. Clin Chem 2003;49:1997–2005 [DOI] [PubMed] [Google Scholar]
- [12]Salvagno GL, Lippi G, Targher G, et al. Monitoring glycaemic control: is there evidence for appropriate use of routine measurement of glycated haemoglobin? Clin Chem Lab Med 2007;45:1065–7 [DOI] [PubMed] [Google Scholar]
- [13]Massey FJ, Jr. The Kolmogorov-Smirnov test for goodness of fit. J Am Stat Assoc 1951;46:68–78 [Google Scholar]
- [14]Goldstein DE, Little RR, Lorenz RA, et al. Tests of glycemia in diabetes. Diabetes Care 2004;27:1761–73 [DOI] [PubMed] [Google Scholar]
- [15]Singer DE, Coley CM, Samet JH, et al. Tests of glycemia in diabetes mellitus. Their use in establishing a diagnosis and in treatment. Ann Intern Med 1989;110:125–37 [DOI] [PubMed] [Google Scholar]
- [16]Peters AL, Davidson MB, Schriger DL, et al. A clinical approach for the diagnosis of diabetes mellitus: an analysis using glycosylated hemoglobin levels. Meta-analysis Research Group on the Diagnosis of Diabetes Using Glycated Hemoglobin Levels. JAMA J Am Med Assoc 1996;276:1246–52 [PubMed] [Google Scholar]
- [17]Lyon AW, Higgins T, Wesenberg JC, et al. Variation in the frequency of hemoglobin A1c (HbA1c) testing: population studies used to assess compliance with clinical practice guidelines and use of HbA1c to screen for diabetes. J Diabetes Sci Technol 2009;3:411–17 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18]Stewart BA, Fernandes S, Rodriguez-Huertas E, et al. A preliminary look at duplicate testing associated with lack of electronic health record interoperability for transferred patients. J Am Med Inform Assoc JAMIA 2010; 17:341–4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [19]Baron JM, Dighe AS. The role of informatics and decision support in utilization management. Clin Chim Acta Int J Clin Chem 2014;427:196–201 [DOI] [PubMed] [Google Scholar]
- [21]Miyakis S, Karamanof G, Liontos M, et al. Factors contributing to inappropriate ordering of tests in an academic medical department and the effect of an educational feedback strategy. Postgrad Med J 2006;82:823–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [22]Huang ES, Basu A, O'Grady M, et al. Projecting the future diabetes population size and related costs for the U.S. Diabetes Care 2009;32:2225–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23]Zhi M, Ding EL, Theisen-Toupal J, et al. The landscape of inappropriate laboratory testing: a 15-year meta-analysis. PLoS ONE 2013;8:e78962. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24]Bates DW, Boyle DL, Rittenberg E, et al. What proportion of common diagnostic tests appear redundant? Am J Med 1998;104:361–8 [DOI] [PubMed] [Google Scholar]
Cited by
Sorted by citations
Mining Electronic Health Records (EHRs): A Survey
Yadav, P., Steinbach, M., Kumar, V., & Simon, G. (2018) · ACM Computing Surveys · doi:10.1145/3127881 · Cited by 299 · see citing works
Rossetti, S. C., Dykes, P. C., Knaplund, C., Cho, S., Withall, J., Lowenthal, G., Albers, D., Lee, R. Y., Jia, H., Bakken, S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03609-7 · Cited by 54 · see citing works
Self-citationRossetti, S. C., Knaplund, C., Albers, D., Dykes, P. C., Kang, M. J., Korach, T. Z., Zhou, L., Schnock, K., Garcia, J., Schwartz, J., et al. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab006 · Cited by 42 · see citing works
Self-citationZhou, Y., Shi, J., Stein, R., Liu, X., Baldassano, R. N., Forrest, C. B., Chen, Y., & Huang, J. (2023) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocad066 · Cited by 33 · see citing works
- Authors
- Pivovarov, R., Albers, D. J., Hripcsak, G., Sepulveda, J. L., & Elhadad, N.
- Affiliations
- Columbia University (US)
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-11
- Volume
- 21
- Issue
- 6
- Pages
- 1038-1044
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC4215045
- OpenAlex
- W2160555924
- Cited by
- 41
- References
- 2
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 2 · 2023: 3 · 2022: 1 · 2021: 3 · 2020: 5 · 2019: 2 · 2018: 8 · 2017: 5 · 2016: 1 · 2015: 4 · 2014: 1
- FWCI
- 6.64
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (1144854)
- U.S. National Library of Medicine (R01:LM06910, LM06910, R01LM006910, R01LM010027)
- Topics
- Health Sciences › Health Professions › General Health Professions › Healthcare cost, quality, practices
- Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Keywords
- hemoglobin A1c testing, temporal trends, guideline adherence, diabetes diagnosis, electronic health records, point-of-care testing, care coordination, health care costs
- MeSH terms
- Academic Medical Centers, Blood Chemical Analysis, Diabetes Mellitus, Glycated Hemoglobin, Humans, Longitudinal Studies, Medical Audit, New York City, Patient Care Management, Models, Statistical, Practice Guidelines as Topic, Statistics, Nonparametric, Unnecessary Procedures, Organizational Case Studies, Guideline Adherence, 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.
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