Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality
Open accessAbstract
PURPOSE: The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) requires eligible clinicians to report clinical quality measures (CQMs) in the Merit-Based Incentive Payment System (MIPS) to maximize reimbursement. To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS CQMs, EHR data aggregated by ASCO's CancerLinQ platform were analyzed. MATERIALS AND METHODS: Using the CancerLinQ health technology platform, 19 Oncology MIPS (oMIPS) CQMs were evaluated to determine the presence of data elements (DEs) necessary to satisfy each CQM and the DE percent population with patient data (fill rates). At the time of this analysis, the CancerLinQ network comprised 63 active practices, representing eight different EHR vendors and containing records for more than 1.63 million unique patients with one or more malignant neoplasms (1.73 million cancer cases). RESULTS: Fill rates for the 63 oMIPS-associated DEs varied widely among the practices. The average site had at least one filled DE for 52% of the DEs. Only 35% of the DEs were populated for at least one patient record in 95% of the practices. However, the average DE fill rate of all practices was 23%. No data were found at any practice for 22% of the DEs. Since any oMIPS CQM with an unpopulated DE component resulted in an inability to compute the measure, only two (10.5%) of the 19 oMIPS CQMs were computable for more than 1% of the patients. CONCLUSION: Although EHR systems had relatively high DE fill rates for some DEs, underfilling and inconsistency of DEs in EHRs render automated oncology MIPS CQM calculations impractical.
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Poor completion or accuracy of key data items impacts quality of care metrics (eg, in cancer care in the United States) and efficient reporting of data for clinical teams, MOH, and funders.
“Furthermore, it impacts quality of care metrics (eg, in cancer care in the United States [43]) and efficient reporting of data for clinical teams, MOH, and funders [16,42].”
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Cites
(U.S.), N. L. O. M. (2008) · Journal of Pain & Palliative Care Pharmacotherapy · doi:10.1080/15360280801989377 · Cited by 474 · see citing works
Organization of Heterogeneous Scientific Data Using the EAV/CR Representation
Nadkarni, P., Marenco, L. N., Chen, R., Skoufos, E., Shepherd, G. M., & Miller, P. L. (1999) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.1999.0060478 · Cited by 208 · see citing works
Osterman, T. J., Terry, M., & Miller, R. S. (2020) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00059 · Cited by 180 · see citing works
Self-citationCarrell, D., Schoen, R. E., Leffler, D. A., Morris, M. M., Rose, S., Baer, A. B., Crockett, S. D., Gourevitch, R. A., Dean, K. M., & Mehrotra, A. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx039 · Cited by 176 · see citing works
Validity of electronic health record-derived quality measurement for performance monitoring
Parsons, A., McCullough, C., Wang, J., & Shih, S. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000557 · Cited by 137 · see citing works
Idowu, M. O., Bekeris, L. G., Raab, S. S., Ruby, S. G., & Nakhleh, R. E. (2010) · Archives of Pathology & Laboratory Medicine · doi:10.5858/2009-0412-cp.1 · Cited by 68 · see citing works
Potter, D., Brothers, R., Kolacevski, A., Koskimaki, J. E., McNutt, A., Miller, R. S., Nagda, J., Nair, A., Rubinstein, W. S., Stewart, A. K., et al. (2020) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00064 · Cited by 57 · see citing works
Self-citationSrigley, J. R., Lankshear, S., Brierley, J., McGowan, T. S., Divaris, D. X. G., Yurcan, M., Rossi, R., Yardley, T., King, M. J., Ross, J., et al. (2013) · Journal of Oncology Practice · doi:10.1200/jop.2012.000818 · Cited by 54 · see citing works
Shulman, L. N., Miller, R. S., Ambinder, E. P., Yu, P. P., & Cox, J. V. (2008) · Journal of Oncology Practice · doi:10.1200/jop.0847501 · Cited by 47 · see citing works
Self-citationTorous, V. F., Simpson, R. W., Balani, J. P., Baras, A. S., Berman, M. A., Birdsong, G. G., Giannico, G. A., Paner, G. P., Pettus, J. R., Sessions, Z., et al. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00104 · Cited by 36 · see citing works
Shulman, L. N., Miller, R. S., Ambinder, E. P., Yu, P. P., & Cox, J. V. (2008) · Journal of Oncology Practice · doi:10.1200/jop.0857501 · Cited by 33 · see citing works
Self-citationStructured Data Capture for Oncology
Goel, A. K., Campbell, W. S., & Moldwin, R. (2021) · JCO Clinical Cancer Informatics · doi:10.1200/cci.20.00103 · Cited by 32 · see citing works
Self-citationCancer Biomarkers: The Role of Structured Data Reporting
Simpson, R. W., Berman, M. A., Foulis, P., Divaris, D. X. G., Birdsong, G. G., Mirza, J., Moldwin, R., Spencer, S., Srigley, J. R., & Fitzgibbons, P. L. (2014) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2014-0082-ra · Cited by 27 · see citing works
Self-citationEvans, T. L., Gabriel, P. E., & Shulman, L. N. (2016) · Journal of Oncology Practice · doi:10.1200/jop.2015.007310 · Cited by 27 · see citing works
Completeness, accuracy, and computability of National Quality Forum-specified eMeasures
Amster, A., Jentzsch, J., Pasupuleti, H., & Subramanian, K. G. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-002865 · Cited by 22 · see citing works
Igniting Harmonized Digital Clinical Quality Measurement through Terminology, CQL, and FHIR
McClure, R. C., Macumber, C. L., Skapik, J. L., & Smith, A. M. (2020) · Applied Clinical Informatics · doi:10.1055/s-0039-3402755 · Cited by 22 · see citing works
No Permanent Fix: MACRA, MIPS, and the Politics of Physician Payment Reform
Spivack, S. B., Laugesen, M., & Oberlander, J. B. (2018) · Journal of Health Politics Policy and Law · doi:10.1215/03616878-7104431 · Cited by 14 · see citing works
Ahmad, F. S., Rasmussen, L. V., Persell, S. D., Richardson, J. E., Liss, D. T., Kenly, P., Chung, I., French, D. D., Walunas, T. L., Schriever, A., et al. (2019) · JAMIA Open · doi:10.1093/jamiaopen/ooz038 · Cited by 13 · see citing works
Sinaiko, A. D., Barnett, M. L., Gaye, M., Soriano, M., Mulvey, T. M., & Hochberg, E. P. (2020) · JAMA Network Open · doi:10.1001/jamanetworkopen.2020.15935 · Cited by 11 · see citing works
Development of a Cancer Care Summary Through the Electronic Health Record
Carr, L. L., Zelarney, P. T., Meadows, S. K., Kern, J. A., Long, M. B., & Kern, E. O. (2016) · Journal of Oncology Practice · doi:10.1200/jop.2015.006890 · Cited by 5 · see citing works
Weiskopf, N. G., Khan, F. J., Woodcock, D., Dorr, D. A., Cigarroa, J. E., & Cohen, A. M. (2016) · PubMed Central · Cited by 4 · see citing works
Barriers to MACRA among a cohort of community oncologists.
Nabhan, C., Smith, Y., Ernst, F. R., Fillman, J., & Feinberg, B. A. (2017) · Journal of Clinical Oncology · doi:10.1200/jco.2017.35.15_suppl.6613 · Cited by 3 · see citing works
2017 Merit-based Incentive Payment System Data Validation and Auditing
Hess, C. T. (2017) · Advances in Skin & Wound Care · doi:10.1097/01.asw.0000522274.96887.f8 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [15]RxNorm. U.S. National Library of Medicine. https://www.nlm.nih.gov/research/umls/rxnorm/ 28792816
Cited by
Sorted by citations
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Wang, L., Chen, X., Zhang, L., Li, L., Huang, Y., Sun, Y., & Yuan, X. (2022) · International Journal of Medical Sciences · doi:10.7150/ijms.77205 · Cited by 115 · see citing works
Lee, B., Gately, L., Lok, S. W., Tran, B., Lee, M., Wong, R., Markman, B., Dunn, K., Wong, V., Loft, M., et al. (2022) · Cancers · doi:10.3390/cancers14174131 · Cited by 37 · see citing works
Ebbers, T., Takes, R. P., Smeele, L. E., Kool, R. B., van den Broek, G. B., & Dirven, R. J. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105344 · Cited by 29 · see citing works
Fraser, H. S. F., Mugisha, M., Bacher, I., Ngenzi, J. L., Seebregts, C., Umubyeyi, A., & Condo, J. (2024) · JMIR Public Health and Surveillance · doi:10.2196/49127 · Cited by 20 · see citing works
Emamekhoo, H., Carroll, C. B., Stietz, C., Pier, J., Lavitschke, M. D., Mulkerin, D. L., Sesto, M. E., & Tevaarwerk, A. J. (2022) · JCO Clinical Cancer Informatics · doi:10.1200/cci.22.00020 · Cited by 9 · see citing works
Gabriel, P. E., Singh, A. P., & Shulman, L. N. (2023) · JAMA Oncology · doi:10.1001/jamaoncol.2022.6842 · Cited by 8 · see citing works
Priou, S., Kempf, E., Flicoteaux, R., Janković, M., Châtellier, G., Tournigand, C., Daniel, C., & Lamé, G. (2024) · Health Policy and Technology · doi:10.1016/j.hlpt.2024.100893 · Cited by 6 · see citing works
Guével, É., Priou, S., Flicoteaux, R., Lamé, G., Bey, R., Tannier, X., Cohen, A., Châtellier, G., Daniel, C., Tournigand, C., et al. (2023) · Revue d Épidémiologie et de Santé Publique · doi:10.1016/j.respe.2023.102189 · Cited by 4 · see citing works
The Utility of Oncology Information Systems for Prognostic Modelling in Head and Neck Cancer
Kotevski, D. P., Smee, R. I., Field, M., Broadley, K., & Vajdic, C. M. (2023) · Journal of Medical Systems · doi:10.1007/s10916-023-01907-6 · Cited by 3 · see citing works
DeStefano, C. B., Thornton, J. A., Gibson, S. J., Pham, K. M., Miller, R. S., & Sunderland, K. W. (2023) · American Journal of Hematology · doi:10.1002/ajh.26921 · Cited by 2 · see citing works
Self-citationKersey, E., Li, J., Adler‐Milstein, J., Yazdany, J., SHIBOSKI, S. C., & Schmajuk, G. (2025) · Journal of Medical Internet Research · doi:10.2196/72709 · Cited by 1 · see citing works
Enhancing the Ability of Primary Care Practices to Report on Age-Friendly Quality of Care Measures
Park, A. A., Phelan, E. A., Bennett, K. A., Cochrane, B. B., Vitiello, M. V., Verrall, A. M., & Cole, A. (2025) · Journal of Ambulatory Care Management · doi:10.1097/jac.0000000000000533
- Authors
- Schorer, A. E., Moldwin, R., Koskimaki, J., Bernstam, E. V., Venepalli, N. K., Miller, R. S., & Chen, J. L.
- Affiliations
- Oncology Analytics, Atlanta, GA
- College of American Pathologists (US)
- American Society of Clinical Oncology (US)
- The University of Texas Health Science Center at Houston (US)
- University of Illinois Chicago (US)
- The Ohio State University (US)
- Corresponding author
- Chen, James L.
- ORCID
- Venue
- JCO Clinical Cancer Informatics
- Published
- 2022-05
- Volume
- 6
- Issue
- 6
- Pages
- e2100128-e2100128
- ISSN
- 2473-4276 (ISSN-L)
- PMC
- PMC9848533
- OpenAlex
- W4205166723
- Cited by
- 12
- References
- 24
- Citations by year
- 2025: 2 · 2024: 2 · 2023: 5 · 2022: 3
- FWCI
- 2.25
- Type
- journal article
- Language
- en
- Update notices
- correction (2022-03-23)
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- JCO Clinical Cancer Informatics (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (UL1TR003167, U01TR002393)
- Centers for Disease Control and Prevention
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
- Health Sciences › Health Professions › Health Information Management › Healthcare Quality and Management
- Keywords
- clinical quality indicators, Merit-based Incentive Payment System, MACRA, CancerLinQ
- MeSH terms
- Data Accuracy, Aged, Medicare, Humans, Neoplasms, United States, Quality Indicators, Health Care, Electronic Health Records
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