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Viewpoint

Catch Me If You Can: Aligning Quality Measurement With Oncology Innovation

December 2019

Breakthrough treatments in cancer care, including precision therapies tailored to specific patient factors, are driving rapid changes in the definitions of oncology quality and value. Efforts to implement value-based care models in oncology must meet the demands of evolving science, new best care practices, and shifting patient priorities. Quality measures must be up-to-date and relevant. Payment models must recognize the challenges and costs of managing complex patient populations with diverse needs. This Viewpoint originally appeared online as the second installment of the JCP blog series provided by Discern Health called Quality Outlook. 


Cancer care innovation is accelerating, powered by an explosion of transformative cancer treatments and breakthrough diagnostics. The introduction of immune-checkpoint inhibitors led to a flood of approvals,1 including tumor-agnostic indications2 based on patient biomarkers rather than tumor type. Chimeric antigen receptor T-cell (CAR-T) treatment3 accelerates personalized medicine, fighting cancer with genetically engineered immune cells created for individual patients. As science rapidly advances, physicians are challenged with integrating emerging evidence and clinical guidelines into practices, while payers are pressuring them to improve value. 

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Measure developers and measurement program implementers seeking to drive quality and assess the value of care strive to ensure that measures reflect the current practice standard and desired patient outcomes. Because measures historically have been based on clinical guidelines, measure developers sometimes wait to modify or create new measures until guidelines are updated, a process which can take 2 years or more. Guideline development rigor, the range of stakeholders who should be engaged, and sluggish dissemination can all impact how rapidly new recommendations—which may ultimately have a short shelf-life—are produced. In lung cancer, for example, treatment algorithms can become outdated4 within 6 months based on newly identified driver mutations.

Measure development is a similarly complex and lengthy process. According to the Centers for Medicare & Medicaid Services (CMS),5 measure prioritization, conceptualization, specification, testing, endorsement, selection, and implementation can take more than 2 years. Taking the processes of guideline development and measure development sequentially, it could take more than 4 years before quality measures relevant to a given novel treatment are available to benchmark quality, support accurate payment based on performance, and steer quality improvement. When existing evidence changes, lags in measure refinement6 can impact physicians’ ability to use that evidence for quality measurement and improvement. Measure developers should consider strategies to ensure that payers and physicians can meaningfully evaluate and improve care by: (1) more closely aligning measure development to evidence generation and guideline development, (2) using cross-cutting cancer outcome measures, and (3) measuring structures of care or using clinical pathways where outcome and process measures are not feasible.

Aligning Measure Development With Guideline Development and Changing Evidence

Guideline developers should flag emerging evidence of substantial variation in care delivery so that measure developers can prioritize creating or refining meaningful and actionable measures. Better aligning guideline and measure developer processes can help avoid an overabundance of process measures that are burdensome to report and become outdated as treatment evolves. Importantly, every aspect of a guideline does not need accompanying measures or measure refinement.

Guideline and measure developers can also use real-world evidence (RWE) to speed the process of integrating emerging evidence into clinical practice. Developers can fill gaps in current guidelines by generating data7 about how effective treatments are outside of clinical trial settings and identifying treatment challenges8 that can be measured and improved. Appropriate use of RWE to inform care decisions may also become a measurement topic. During a recent National Comprehensive Cancer Network Policy Summit,9 panelists suggested that future quality measures may evaluate whether physicians correctly apply new evidence in practice and use RWE to inform decision-making when randomized clinical trial data are not available.

Using Cross-Cutting Measures of Cancer Outcomes

Measure developers should identify the most durable outcome measures that cut across guidelines and cancer populations. Process measures that are focused on specific aspects of treatment are closely tied to guidelines and therefore may need to change frequently with rapidly changing evidence. In the personalized medicine era, these measures could become focused on narrow, biomarker-specific populations, resulting in denominators that are too small to measure. Cross-cutting clinical outcome measures, on the other hand, are unlikely to change dramatically as guidelines change and can be adopted to decrease the number of measures that need to be tracked. CMS is already prioritizing oncology outcomes for measurement10 such as cure rate, survival rate, and patient-reported outcomes (PROs), including health-related quality of life. The National Quality Forum’s partners leveraging its NQF Measure Incubator™ are also developing and testing survival and PRO performance measures (PRO-PMs) for lung, melanoma, and prostate cancer.11 

While there is a push for more outcome measures, implementing them is challenging because of data collection feasibility as well as accuracy of risk adjustment and attribution. PRO-PMs are complex due to patient and provider data collection burden and potential biases12 that impact the data based on patient sociodemographic and clinical characteristics. Safety measures13 related to cancer “never events,” such as dosing errors or avoidable treatment-related loss of bodily function, may be cross-cutting measurement alternatives to more complex outcomes. 

Leveraging Pathways and Structure Measures to Assess Quality of Care

Rapid development of outcome or process measures in accordance with emerging evidence and new clinical standards is not always feasible, and measurement of clinical pathway use14 and adherence or structure measures15—such as PRO data collection—could serve as a stepping stone toward more robust measurement. Pathways should be rapidly updated to reflect new evidence, and their use can support point-of-care decision-making in ever-changing complex clinical scenarios.16 Measures that track use of, and concordance with, recognized pathways could remain static while the pathways themselves change. These measures should specify that pathways be developed through a transparent and evidence-based process17 that meet criteria established by oncology leaders.

Better

Policymakers should consider implementing structure measures for cancer that assess whether providers have systems in place to account for patients’ perspectives.
Measures that evaluate whether physicians collect and use PRO data and/or facilitate meaningful shared decision-making conversations to guide personalized treatment could inform the next generation of quality measures. Notably, the CMS Innovation Center included gradual implementation of electronic PROs in its recent Request for Information about the next version of their Oncology Care Model. 

Conclusion

Appropriate clinical standards of care should be defined through thorough evidence- and consensus-based processes. While necessary, this creates a barrier to rapid quality measure development and refinement when transformative treatments are introduced and existing measures become outdated. Streamlining guideline and measure development processes while integrating RWE, focusing on cross-cutting outcomes that are guideline agnostic, and creating measures that recognize pathway use could mitigate the measurement challenges associated with rapid innovation. 

This Viewpoint was originally published as a blog. To read the Counterpoint, click here.

References

1. Alexander W. The checkpoint immunotherapy revolution: what started as a trickle has become a flood, despite some daunting adverse effects; new drugs, indications, and combinations continue to emerge. P T. 2016;41(3):185-191. 

2. Mulcahy N. FDA approves another tumor-agnostic cancer drug. Medscape. August 15, 2019.  https://www.medscape.com/viewarticle/916911. Accessed November 25, 2019. 

3. Memorial Sloan Kettering Cancer Center (MSKCC). What is CAR T? mskcc.org website.  https://www.mskcc.org/car-cell-therapy. Accessed November 25, 2019.

4. B Melosky. Rapidly changing treatment algorithms for metastatic nonsquamous non-small-cell lung cancer. Curr Oncol. 2018;25:s68-s76. doi:10.3747/co.25.3839 

5. Centers for Medicare & Medicaid Services (CMS). Quality measure development and management overview. cms.gov website. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Measure-Development-by-Phase. Updated August 24, 2017. Accessed November 25, 2019.

6. Valuck TB, Sampsel S, Sloan DM, Van Meter J. Am J Manag Care. 2019;25(6):e188-e191. 

7. Chew SY, Koh MS, Loo CM, Thumboo J, Shantakumar S, Matchar DB. Making clinical practice guidelines pragmatic: how big data and real world evidence can close the gap. Ann Acad Med Singapore. 2018;47(12):523-527. 

8. Wbster J, Smith BD. The case for real-world evidence in the future of clinical research on chronic myeloid leukemia. Clin Therapeutics. 2019;41(2):336-349. doi:10.1016/j.clinthera.2018.12.013 

9. Patient priorities should be paramount when measuring quality in cancer care according to panelists at NCCN policy summit [news release]. Washington, DC: National Comprehensive Cancer Network; September 12, 2019. https://www.prnewswire.com/news-releases/patient-priorities-should-be-paramount-when-measuring-quality-in-cancer-care-according-to-panelists-at-nccn-policy-summit-300916177.html. Accessed November 25, 2019.

10. Centers for Medicare & Medicaid Services (CMS). CMS quality measure development plan: environmental scan and gap analysis report (MACRA, section 102). https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/MACRA-MIPS-and-APMs/MDP_EScan_GapAnalysis_Report.pdf.
Published February 17, 2017. Accessed November 25, 2019.

11. National Quality Forum. NQF Measure Incubator® projects. qualityforum.org website. https://www.qualityforum.org/Proving_the_Concept.aspx. Accessed November 25, 2019.

12. National Pharmaceutical Council; Discern Health. Improving patient-reported measures in oncology. https://discernhealth.com/wp-content/uploads/2019/02/2019-improving-patient-reported-measures-in-oncology.pdf. Published 2019. Accessed November 25, 2019.

13. Valuck T, Blaisdell D, Dugan DP, et al. Improving oncology quality measurement in accountable care: filling gapes with cross-cutting measures. J Manag Care Spec Pharm. 2017;23(2):174-181.  

14. Chiang AC, Ellis P, Zon R. Perspectives on the use of clinical pathways in oncology care. Am Soc Clin Oncol Ed Book. 2018;37:155-159. doi:10.1200/EDBK_175533 https://ascopubs.org/doi/full/10.1200/EDBK_175533

15. Centers for Medicare & Medicaid Services (CMS). Measures management system. cms.gov website. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/MMS/Downloads/Structural-Measures.pdf. Published February 2018. Accessed November 25, 2019.

16. Rodríguez-Lopéz JL, Ling DC, Heron DE, Beriwal S. Lag time between evidence and guidelines: can clinical pathways bridge the gap? J Oncol Pract. 2019;15(3):e195-e201. doi:10.1200/JOP.18.00430

17. Zon RT, Edge SB, Page RD, et al. American Society for Clinical Oncology criteria for high-quality clinical pathways in oncology. J Oncol Pract. 2017;13(3):207-210. doi:10.1200/JOP.2016.019836