How do clinics perform across multiple end of life metrics?
Panattoni, LE; Fedorenko, CR; Greenwood-Hickman, MA; Sun, Q; Walker, JR; Kreizenbeck, KL; McDermott, CL; Conklin, T; Smith, B; Lyman, GH; Ramsey, SD
Published in: Journal of Clinical Oncology
86 Background: National bodies have proposed a number of metrics to measure quality of care at the end of life (EOL). MACRA legislation allows clinics to select the metrics they report to CMS. The self-selection of reported metrics leaves open questions about how representative certain measures, particularly in isolation, may be of overall EOL care in community settings. We examined the consistency of clinical-level performance across three common EOL metrics. Methods: We linked cancer registry records for solid tumor cancer patients diagnosed in Washington State from 2013-2016 with claims from two regional commercial insurers. Representing national recommendations, we compiled 3 EOL quality metrics for each clinic: 1) Chemotherapy in last 14 days of life (DoL); 2) More than 1 ED visit in last 30 DoL; and 3) Admission to ICU in last 30 DoL. Consistency was measured by comparing performance in the top and bottom 3 across metrics. We compared consistency based on unadjusted rates and risk-standardized rates calculated following CMS methods. Results: The study included 1,535 patients across 12 clinics (median 110 [IQR: 54 – 199] patients/clinic). The clinic rates are below. (See Table.) According to both unadjusted and adjusted rankings, no clinics ranked in the top 3 across all metrics. Half of clinics (6 of 12) simultaneously ranked in the top 3 and bottom 3 of a metric, i.e. high/low performers. The number of high/low performers varied when examining discrete pairs of metrics. The overall pattern was mainly driven by inconsistency between performance in the chemotherapy and ED metrics. Of the other discrete pairs, ICU/Chemo and ICU/ED, clinics were more consistent in performance. Conclusions: We found that clinic performance was not consistently in the highest or lowest tertile across common EOL metrics, suggesting that requiring clinics to report a standard set of metrics may provide a more accurate indication of quality. Furthermore, different population management strategies may be required to improve care targeted by each measure. Future work should focus on the development of multi-dimensional EOL quality performance measures. [Table: see text]
