Performance of claims-based algorithms for identifying heart failure and cardiomyopathy among patients diagnosed with breast cancer

Larry A. Allen, Marianne Ulcickas Yood, Edward H. Wagner, Erin J. Aiello Bowles, Roy Pardee, Robert Wellman, Laurel Habel, Larissa Nekhlyudov, Robert Davis, Adedayo A. Onitilo, David J. Magid

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Abstract

BACKGROUND:: Cardiotoxicity is a known complication of certain breast cancer therapies, but rates come from clinical trials with design features that limit external validity. The ability to accurately identify cardiotoxicity from administrative data would enhance safety information. OBJECTIVE:: To characterize the performance of clinical coding algorithms for identification of cardiac dysfunction in a cancer population. RESEARCH DESIGN:: We sampled 400 charts among 6460 women diagnosed with incident breast cancer, tumor size ≥ 2 cm or node positivity, treated within 8 US health care systems between 1999 and 2007. We abstracted medical records for clinical diagnoses of heart failure (HF) and cardiomyopathy (CM) or evidence of reduced left ventricular ejection fraction. We then assessed the performance of 3 different International Classification of Diseases, 9th Edition (ICD-9)-based algorithms. RESULTS:: The HF/CM coding algorithm designed a priori to balance performance characteristics provided a sensitivity of 62% (95% confidence interval, 40%-80%), specificity of 99% (range, 97% to 99%), positive predictive value (PPV) of 69% (range, 45% to 85%), and negative predictive value (NPV) of 98% (range, 96% to 99%). When applied only to incident HF/CM (ICD-9 codes and gold standard diagnosis both occurring after breast cancer diagnosis) in patients exposed to anthracycline and/or trastuzumab therapy, the PPV was 42% (range, 14% to 76%). CONCLUSIONS:: Claims-based algorithms have moderate sensitivity and high specificity for identifying HF/CM among patients with invasive breast cancer. As the prevalence of HF/CM among the breast cancer population is low, ICD-9 codes have high NPV but only moderate PPV. These findings suggest a significant degree of misclassification due to HF/CM overcoding versus incomplete clinical documentation of HF/CM in the medical record.

Original languageEnglish (US)
JournalMedical care
Volume52
Issue number5
DOIs
StatePublished - Jan 1 2014

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Cardiomyopathies
Heart Failure
Breast Neoplasms
International Classification of Diseases
Medical Records
Anthracyclines
Clinical Coding
Documentation
Stroke Volume
Population
Clinical Trials
Confidence Intervals
Delivery of Health Care
Safety
Sensitivity and Specificity
Therapeutics
Neoplasms

All Science Journal Classification (ASJC) codes

  • Public Health, Environmental and Occupational Health

Cite this

Allen, L. A., Yood, M. U., Wagner, E. H., Aiello Bowles, E. J., Pardee, R., Wellman, R., ... Magid, D. J. (2014). Performance of claims-based algorithms for identifying heart failure and cardiomyopathy among patients diagnosed with breast cancer. Medical care, 52(5). https://doi.org/10.1097/MLR.0b013e31825a8c22

Performance of claims-based algorithms for identifying heart failure and cardiomyopathy among patients diagnosed with breast cancer. / Allen, Larry A.; Yood, Marianne Ulcickas; Wagner, Edward H.; Aiello Bowles, Erin J.; Pardee, Roy; Wellman, Robert; Habel, Laurel; Nekhlyudov, Larissa; Davis, Robert; Onitilo, Adedayo A.; Magid, David J.

In: Medical care, Vol. 52, No. 5, 01.01.2014.

Research output: Contribution to journalArticle

Allen, LA, Yood, MU, Wagner, EH, Aiello Bowles, EJ, Pardee, R, Wellman, R, Habel, L, Nekhlyudov, L, Davis, R, Onitilo, AA & Magid, DJ 2014, 'Performance of claims-based algorithms for identifying heart failure and cardiomyopathy among patients diagnosed with breast cancer', Medical care, vol. 52, no. 5. https://doi.org/10.1097/MLR.0b013e31825a8c22
Allen, Larry A. ; Yood, Marianne Ulcickas ; Wagner, Edward H. ; Aiello Bowles, Erin J. ; Pardee, Roy ; Wellman, Robert ; Habel, Laurel ; Nekhlyudov, Larissa ; Davis, Robert ; Onitilo, Adedayo A. ; Magid, David J. / Performance of claims-based algorithms for identifying heart failure and cardiomyopathy among patients diagnosed with breast cancer. In: Medical care. 2014 ; Vol. 52, No. 5.
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abstract = "BACKGROUND:: Cardiotoxicity is a known complication of certain breast cancer therapies, but rates come from clinical trials with design features that limit external validity. The ability to accurately identify cardiotoxicity from administrative data would enhance safety information. OBJECTIVE:: To characterize the performance of clinical coding algorithms for identification of cardiac dysfunction in a cancer population. RESEARCH DESIGN:: We sampled 400 charts among 6460 women diagnosed with incident breast cancer, tumor size ≥ 2 cm or node positivity, treated within 8 US health care systems between 1999 and 2007. We abstracted medical records for clinical diagnoses of heart failure (HF) and cardiomyopathy (CM) or evidence of reduced left ventricular ejection fraction. We then assessed the performance of 3 different International Classification of Diseases, 9th Edition (ICD-9)-based algorithms. RESULTS:: The HF/CM coding algorithm designed a priori to balance performance characteristics provided a sensitivity of 62{\%} (95{\%} confidence interval, 40{\%}-80{\%}), specificity of 99{\%} (range, 97{\%} to 99{\%}), positive predictive value (PPV) of 69{\%} (range, 45{\%} to 85{\%}), and negative predictive value (NPV) of 98{\%} (range, 96{\%} to 99{\%}). When applied only to incident HF/CM (ICD-9 codes and gold standard diagnosis both occurring after breast cancer diagnosis) in patients exposed to anthracycline and/or trastuzumab therapy, the PPV was 42{\%} (range, 14{\%} to 76{\%}). CONCLUSIONS:: Claims-based algorithms have moderate sensitivity and high specificity for identifying HF/CM among patients with invasive breast cancer. As the prevalence of HF/CM among the breast cancer population is low, ICD-9 codes have high NPV but only moderate PPV. These findings suggest a significant degree of misclassification due to HF/CM overcoding versus incomplete clinical documentation of HF/CM in the medical record.",
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AU - Allen, Larry A.

AU - Yood, Marianne Ulcickas

AU - Wagner, Edward H.

AU - Aiello Bowles, Erin J.

AU - Pardee, Roy

AU - Wellman, Robert

AU - Habel, Laurel

AU - Nekhlyudov, Larissa

AU - Davis, Robert

AU - Onitilo, Adedayo A.

AU - Magid, David J.

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N2 - BACKGROUND:: Cardiotoxicity is a known complication of certain breast cancer therapies, but rates come from clinical trials with design features that limit external validity. The ability to accurately identify cardiotoxicity from administrative data would enhance safety information. OBJECTIVE:: To characterize the performance of clinical coding algorithms for identification of cardiac dysfunction in a cancer population. RESEARCH DESIGN:: We sampled 400 charts among 6460 women diagnosed with incident breast cancer, tumor size ≥ 2 cm or node positivity, treated within 8 US health care systems between 1999 and 2007. We abstracted medical records for clinical diagnoses of heart failure (HF) and cardiomyopathy (CM) or evidence of reduced left ventricular ejection fraction. We then assessed the performance of 3 different International Classification of Diseases, 9th Edition (ICD-9)-based algorithms. RESULTS:: The HF/CM coding algorithm designed a priori to balance performance characteristics provided a sensitivity of 62% (95% confidence interval, 40%-80%), specificity of 99% (range, 97% to 99%), positive predictive value (PPV) of 69% (range, 45% to 85%), and negative predictive value (NPV) of 98% (range, 96% to 99%). When applied only to incident HF/CM (ICD-9 codes and gold standard diagnosis both occurring after breast cancer diagnosis) in patients exposed to anthracycline and/or trastuzumab therapy, the PPV was 42% (range, 14% to 76%). CONCLUSIONS:: Claims-based algorithms have moderate sensitivity and high specificity for identifying HF/CM among patients with invasive breast cancer. As the prevalence of HF/CM among the breast cancer population is low, ICD-9 codes have high NPV but only moderate PPV. These findings suggest a significant degree of misclassification due to HF/CM overcoding versus incomplete clinical documentation of HF/CM in the medical record.

AB - BACKGROUND:: Cardiotoxicity is a known complication of certain breast cancer therapies, but rates come from clinical trials with design features that limit external validity. The ability to accurately identify cardiotoxicity from administrative data would enhance safety information. OBJECTIVE:: To characterize the performance of clinical coding algorithms for identification of cardiac dysfunction in a cancer population. RESEARCH DESIGN:: We sampled 400 charts among 6460 women diagnosed with incident breast cancer, tumor size ≥ 2 cm or node positivity, treated within 8 US health care systems between 1999 and 2007. We abstracted medical records for clinical diagnoses of heart failure (HF) and cardiomyopathy (CM) or evidence of reduced left ventricular ejection fraction. We then assessed the performance of 3 different International Classification of Diseases, 9th Edition (ICD-9)-based algorithms. RESULTS:: The HF/CM coding algorithm designed a priori to balance performance characteristics provided a sensitivity of 62% (95% confidence interval, 40%-80%), specificity of 99% (range, 97% to 99%), positive predictive value (PPV) of 69% (range, 45% to 85%), and negative predictive value (NPV) of 98% (range, 96% to 99%). When applied only to incident HF/CM (ICD-9 codes and gold standard diagnosis both occurring after breast cancer diagnosis) in patients exposed to anthracycline and/or trastuzumab therapy, the PPV was 42% (range, 14% to 76%). CONCLUSIONS:: Claims-based algorithms have moderate sensitivity and high specificity for identifying HF/CM among patients with invasive breast cancer. As the prevalence of HF/CM among the breast cancer population is low, ICD-9 codes have high NPV but only moderate PPV. These findings suggest a significant degree of misclassification due to HF/CM overcoding versus incomplete clinical documentation of HF/CM in the medical record.

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