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Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality
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 adequat...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9848533/ https://www.ncbi.nlm.nih.gov/pubmed/34985912 http://dx.doi.org/10.1200/CCI.21.00128 |
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author | Schorer, Anna E. Moldwin, Richard Koskimaki, Jacob Bernstam, Elmer V. Venepalli, Neeta K. Miller, Robert S. Chen, James L. |
author_facet | Schorer, Anna E. Moldwin, Richard Koskimaki, Jacob Bernstam, Elmer V. Venepalli, Neeta K. Miller, Robert S. Chen, James L. |
author_sort | Schorer, Anna E. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9848533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-98485332023-01-19 Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality Schorer, Anna E. Moldwin, Richard Koskimaki, Jacob Bernstam, Elmer V. Venepalli, Neeta K. Miller, Robert S. Chen, James L. JCO Clin Cancer Inform ORIGINAL REPORTS 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. Wolters Kluwer Health 2022-01-05 /pmc/articles/PMC9848533/ /pubmed/34985912 http://dx.doi.org/10.1200/CCI.21.00128 Text en © 2022 by American Society of Clinical Oncology https://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution Non-Commercial No Derivatives 4.0 License: https://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | ORIGINAL REPORTS Schorer, Anna E. Moldwin, Richard Koskimaki, Jacob Bernstam, Elmer V. Venepalli, Neeta K. Miller, Robert S. Chen, James L. Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title | Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title_full | Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title_fullStr | Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title_full_unstemmed | Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title_short | Chasm Between Cancer Quality Measures and Electronic Health Record Data Quality |
title_sort | chasm between cancer quality measures and electronic health record data quality |
topic | ORIGINAL REPORTS |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9848533/ https://www.ncbi.nlm.nih.gov/pubmed/34985912 http://dx.doi.org/10.1200/CCI.21.00128 |
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