Are care experiences associated with survival among cancer patients? An analysis of the SEER-CAHPS data resource.

PURPOSE: Cancer patients' care experiences encompass the range of interactions with the health care system and are an important indicator of care quality, which may influence survival outcomes. This study evaluates relationships between care experiences and survival using a large, nationally representative sample of cancer patients. METHODS: We used linked SEER (Surveillance Epidemiology and End Results)-CAHPS (Consumer Assessment of Healthcare Providers and Systems) data to identify people diagnosed 8/2006-12/2013, focusing on 10 solid tumor cancer sites with the highest mortality rates among those > 65. CAHPS measures included 5 global ratings and 3 composite scores. We used survey-weighted Cox proportional hazard models comparing survival time for those who had lower (0-8) vs higher ratings (9-10) and lower (0-89) vs higher (90-100) composite scores, adjusting for case-mix and additional covariates. RESULTS: We identified 2,263 eligible people; 26% died by 5-year post-survey completion or end of follow-up (12/31/2017). We found lower Prescription Drug Plan (PDP) ratings were significantly associated with lower mortality (adjusted HR = 0.67, p = 0.03). Lower Getting Needed Care scores were also significantly associated with lower mortality (adjusted HR = 0.79, p = 0.04). For other care experience measures, general health status, cancer stage, and comorbidities were more predictive of survival (p < .05). CONCLUSIONS: Except for PDP and Getting Needed Care, survival was similar for those with worse versus better care experiences. Patients with poorer cancer prognoses may perceive better services from their drug plan and more responsive care from clinical providers compared to those with better prognoses. Further research is needed examining processes underlying perceptions of care experiences and survival.

Associations between illness burden and care experiences among Medicare beneficiaries before or after a cancer diagnosis.

INTRODUCTION: To understand associations between a new measure of illness burden and care experiences in a large, national sample of Medicare beneficiaries surveyed before or after a cancer diagnosis. MATERIALS AND METHODS: The SEER-CAHPS Illness Burden Index (SCIBI) was previously developed using Surveillance, Epidemiology, and End Results (SEER)-Consumer Assessment of Healthcare Providers and Systems (CAHPS) linked data. The SCIBI provides a standardized morbidity score based on self- and other-reported information from 8 domains and proxies relative risk of 12-month, all-cause mortality among people surveyed before or after a cancer diagnosis. We analyzed a population of Medicare beneficiaries (n = 116,735; 49% fee-for-service and 51% Medicare Advantage [MA]; 73% post-cancer diagnosis) surveyed 2007-2013 to understand how their SCIBI scores were associated with 12 different care experience measures. Frequentist and Bayesian multivariable regression models adjusted for standard case-mix adjustors, enrollment type, timing of cancer diagnoses relative to survey, and survey year. RESULTS AND DISCUSSION: SCIBl scores were associated (P < .001) in frequentist models with better ratings of Health Plan (coefficient ± standard error: 0.33 ± 0.08) and better Getting Care Quickly scores (0.51 ± 0.09). In Bayesian models, individuals with higher illness burden had similar results on the same two measures and also reported reliably worse Overall Care experiences (coefficient ± posterior SD: -0.17 ± 0.06). Illness burden may influence how people experience care or report those experiences. Individuals with greater illness burdens may need intensive care coordination and multilevel interventions before and after a cancer diagnosis.

Random survival forests using linked data to measure illness burden among individuals before or after a cancer diagnosis: Development and internal validation of the SEER-CAHPS illness burden index.

PURPOSE: To develop and internally validate an illness burden index among Medicare beneficiaries before or after a cancer diagnosis. METHODS: Data source: SEER-CAHPS, linking Surveillance, Epidemiology, and End Results (SEER) cancer registry, Medicare enrollment and claims, and Medicare Consumer Assessment of Healthcare Providers and Systems (Medicare CAHPS) survey data providing self-reported sociodemographic, health, and functional status information. To generate a score for everyone in the dataset, we tabulated 4 groups within each annual subsample (2007-2013): 1) Medicare Advantage (MA) beneficiaries or 2) Medicare fee-for-service (FFS) beneficiaries, surveyed before cancer diagnosis; 3) MA beneficiaries or 4) Medicare FFS beneficiaries surveyed after diagnosis. Random survival forests (RSFs) predicted 12-month all-cause mortality and drew predictor variables (mean per subsample = 44) from 8 domains: sociodemographic, cancer-specific, health status, chronic conditions, healthcare utilization, activity limitations, proxy, and location-based factors. Roughly two-thirds of the sample was held out for algorithm training. Error rates based on the validation ("out-of-bag," OOB) samples reflected the correctly classified percentage. Illness burden scores represented predicted cumulative mortality hazard. RESULTS: The sample included 116,735 Medicare beneficiaries with cancer, of whom 73 % were surveyed after their cancer diagnosis; overall mean mortality rate in the 12 months after survey response was 6%. SEER-CAHPS Illness Burden Index (SCIBI) scores were positively skewed (median range: 0.29 [MA, pre-diagnosis] to 2.85 [FFS, post-diagnosis]; mean range: 2.08 [MA, pre-diagnosis] to 4.88 [MA, post-diagnosis]). The highest decile of the distribution had a 51 % mortality rate (range: 29-71 %); the bottom decile had a 1% mortality rate (range: 0-2 %). The error rate was 20 % overall (range: 9% [among FFS enrollees surveyed after diagnosis] to 36 % [MA enrollees surveyed before diagnosis]). CONCLUSIONS: This new morbidity measure for Medicare beneficiaries with cancer may be useful to future SEER-CAHPS users who wish to adjust for comorbidity.