The impact of physician-hospital integration on spending and quality of oncology care

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Background: There has been increasing hospital and health system ownership of physician practices in recent years, particularly in oncology. However, relatively little is known about how this impacts care delivery for patients with cancer, who use many hospital-based services that may be impacted by integration. We evaluated the impact of physician-hospital integration in oncology on spending and quality of care for Medicare beneficiaries with cancer. Methods: We used Medicare Fee-for-Service claims from 2005-2019 linked with a unique Health System and Provider Database, developed by National Bureau of Economic Research and Harvard University researchers, to track practice ownership relationships over time. We used a stacked event study to assess outcomes for patients three years before and after oncologists move from independent practices to hospital- or system- owned practices. We compared outcomes to a control group with oncologists who shifted from independent to hospital- or system-owned practices in later years. We focused on two cohorts of patients. The first cohort included cancer patients with presumed incident or recurrent cancer based on ≥2 visits to an oncologist and no visit in the past year. For these patients, we evaluated the impact of physician-hospital integration on the likelihood of receiving chemotherapy following the visit. The second cohort included 6-month episodes for patients receiving chemotherapy. For these patients we evaluated the impact of physician-hospital integration on spending, utilization, and quality. Quality measures included receipt of timely chemotherapy (within 60 days) following surgery, inpatient readmissions, non-use of tamoxifen + strong CYPD26 inhibitors, and end-of-life intensity of care measures. Results: There was no change in the likelihood of receiving chemotherapy with an initial oncology consultation following an oncologist’s transition to hospital-based employment. Total spending during six-month chemotherapy episodes increased by $1391 (95%CI: $465, $2316). The primary contributors to this growth were increases in spending on inpatient care, chemotherapy administration, and office visits. Spending growth, where observed, was driven primarily by higher Medicare prices for care in hospital outpatient settings. We found no positive impact of physician-hospital integration on timeliness of chemotherapy initiation, readmissions, concurrent use of tamoxifen+strong CYPD26 inhibitors, or intensity of end-of-life care. Conclusions: Physician-hospital integration resulted in higher prices and thus higher spending, but had limited impact on utilization and no detectable impacts on measures of quality. These results suggest that claims of quality improvements and concerns regarding overuse associated with physician-hospital integration may be overstated. Our results also support continued movement towards site-neutral payments.

Variation of use of targeted therapies and molecular diagnostic testing by practice type for non-small cell lung cancer and colorectal cancer

6551

Background: Targeted therapies are important first-line treatments for many patients with non-small cell lung cancer (NSCLC) and colorectal cancer (CRC). All patients with newly-diagnosed metastatic NSCLC and CRC should undergo molecular diagnostic testing to guide treatment selection. Methods: We used 100% Medicare fee-for-service data from 2015 through 2019 to identify beneficiaries with incident metastatic NSCLC or CRC receiving systemic therapy and to assign beneficiaries to oncology practices. We then assessed for use of molecular diagnostic testing and targeted therapies in these cohorts. We used linear mixed effects models to assess patient and practice characteristics associated with molecular diagnostic testing and targeted therapy use. Results: Rates of molecular diagnostic testing increased between 2015 and 2019 for NSCLC and CRC. In 2019, rates of molecular diagnostic testing were 85% and 65% for NSCLC and CRC, respectively. Rates of targeted therapy use did not increase over time for NSCLC or CRC, and were 8% and 5%, respectively, in 2019. Compared to National Cancer Institute (NCI)-designated cancer centers, rates of molecular diagnostic testing for CRC were 3.7 percentage points lower at practices associated with non-academic hospitals and 10.6 percentage points lower at small independent practices. Rates of targeted therapy use for NSCLC were 4.8, 5.9 and 5.5 percentage points lower at academic medical centers, large independent practices and small independent practices, respectively, compared to NCI centers. Conclusions: Rates of molecular diagnostic testing for NSCLC and CRC increased in recent years, but testing rates remain below recommended levels, and targeted therapy use remains low. Substantial variation in testing and targeted therapy use by practice type suggest that the practice where a patient is treated may impact access to recommended testing and efficacious treatments. [Table: see text]

Practice consolidation among U.S. medical oncologists over time

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Background: Physician practices across the U.S. are increasingly merging with hospitals and other practices. The extent of such “practice consolidation” varies by specialty and across geography but has not been well characterized within medical oncology. Methods: Utilizing Medicare data, we identified all medical oncologists (MO) who billed for Medicare services each year between 2015 and January 2022. We associated each physician to one or more unique practices via organizational Taxpayer Identification Numbers (TIN), and classified practices by the number of medical oncologists—including solo (1 MO), small (2-10 MOs), medium (11-24 MOs), and large (25+ MOs) practices. We defined the extent of regional healthcare markets according to Hospital Referral Regions (HRRs), and calculated levels of practice consolidation using the Herfindahl-Hirschman Index (HHI). The HHI is a commonly used measure of consolidation, calculated by summing the square of each practice’s market share. HHI values range from 0 to 1 with higher numbers indicating greater consolidation and less competition among practices. Finally, we generated a multivariable linear regression model to determine which regional market factors were associated with changes in levels of medical oncology practice consolidation over time. Results: Between 2015 and 2022, the number of practices with MOs in the U.S. declined 18.0% from 2,774 to 2,276, while the number of practicing MOs increased 14.5% from 11,727 to 13,433. The median medical oncology practice HHI increased from 0.3204 to 0.3480. Over time the proportion of solo practices fell (48.4% in 2015, 43.9% in 2022) while the proportion of medium and large practices increased (medium: 5.7% to 8.4%; large: 2.7% to 4.5%). By 2022, large practices had grown to employ a significantly larger proportion of all medical oncologists (33.6% to 43.7%, p < 0.001). Between 2015 and 2022, the proportion of practices solely comprised of MOs (as opposed to multispecialty practices) decreased from 40.0% to 28.2%. On multivariable analysis, HRRs with higher levels of hospital consolidation (p < 0.001), greater numbers of hospital beds per 1,000 persons (p = 0.02), and a lesser degree of baseline medical oncology practice consolidation in 2015 (p < 0.001) experienced more consolidation during the study period. Conclusions: Medical oncologists across the U.S. are increasingly working in larger practices. By 2022, more than 40% of all practicing MOs were employed at the largest 5% of practices. Consolidation of medical oncology practices occurred more readily in regions with higher levels of hospital consolidation and a greater supply of hospital beds, suggesting that integration into hospital systems may be a leading source of consolidation. Further study is required to determine the impact of practice consolidation on the cost, quality, and accessibility of cancer care.

Development of dynamic health care delivery heatmaps for end-of-life cancer care: a cohort study

OBJECTIVE

Measures of variation in end-of-life (EOL) care intensity across hospitals are typically summarised using unidimensional measures. These measures do not capture the full dimensionality of complex clinical care trajectories over time that are needed to inform quality improvement efforts. The objective is to develop a novel visual map of EOL care trajectories that illustrates multidimensional utilisation over time.

SETTING

United States' National Cancer Institute or National Comprehensive Cancer Network (NCI/NCCN)-designated hospitals.

PARTICIPANTS

We identified Medicare claims for fee-for-service beneficiaries with poor prognosis cancers who died between April and December 2016 and received the preponderance of treatment in the last 6 months of life at an NCI/NCCN-designated hospital.

DESIGN

For each beneficiary, we transformed each Medicare claim into two elements to generate a two-dimensional individual-level heatmap. On the y-axis, each claim was classified into a categorical description of the service delivered by a healthcare resource. On the x-axis, the date for each claim was converted into the day number prior to death it occurred on. We then summed up individual-level heatmaps of patients attributed to each hospital to generate two-dimensional hospital-level heatmaps. We used four case studies to illustrate the feasibility of interpreting these heatmaps and to shed light on how they might be used to guide value-based, quality improvement initiatives.

RESULTS

We identified nine distinct EOL care delivery patterns from hospital-level heatmaps based on signal intensity and patterns for inpatient, outpatient and home-based hospice services. We illustrate that in most cases, heatmaps illustrating patterns of multidimensional healthcare utilisation over time provide more information about care trajectories and highlight more heterogeneity than current unidimensional measures.

CONCLUSIONS

This study illustrates the feasibility of representing multidimensional EOL utilisation over time as a heatmap. These heatmaps may provide potentially actionable insights into hospital-level care delivery patterns, and the approach may generalise to other serious illness populations.

Gambling along the schizotypal spectrum: The associations between schizotypal personality, gambling-related cognitions, luck, and problem gambling

Objective

Schizotypal personality (schizotypy) is a cluster of traits in the general population, including alterations in belief formation that may underpin delusional thinking. The psychological processes described by schizotypy could also fuel cognitive distortions in the context of gambling. This study sought to characterize the relationships between schizotypy, gambling-related cognitive distortions, and levels of problem gambling.

Methods

Analyses were conducted on three groups, a student sample (n = 104) with minimal self-reported gambling involvement, a crowdsourced sample of regular gamblers (via MTurk; n = 277), and an additional crowdsourced sample with a range of gambling involvement (via MTurk; n = 144). Primary measures included the Schizotypal Personality Questionnaire - Brief (SPQ-B), the Peters et al. Delusions Inventory (PDI-21), the Gambling Related Cognitions Scale (GRCS), and the Problem Gambling Severity Index (PGSI). Luck was measured with either the Belief in Good Luck Scale (BIGLS) or the Beliefs Around Luck Scale (BALS).

Results

Small-to-moderate associations were detected between the components of schizotypy, including delusion proneness, and the gambling-related variables. Schizotypy was associated with the general belief in luck and bad luck, but not beliefs in good luck. A series of partial correlations demonstrated that when the GRCS was controlled for, the relationship between schizotypy and problem gambling was attenuated.

Conclusions

This study demonstrates that schizotypy is a small-to-moderate correlate of erroneous gambling beliefs and PG. These data help characterize clinical comorbidities between the schizotypal spectrum and problem gambling, and point to shared biases relating to belief formation and decision-making under chance.

Measuring Racial Inequities In The Quality Of Care Across Oncology Practices In The US

Racial inequities in clinical performance diminish overall health care system performance; however, quality assessments have rarely incorporated reliable measures of racial inequities. We studied care for more than one million Medicare fee-for-service beneficiaries with cancer to assess the feasibility of calculating reliable practice-level measures of racial inequities in chemotherapy-associated emergency department (ED) visits and hospitalizations. Specifically, we used hierarchical models to estimate adjusted practice-level Black-White differences in these events and described differences across practices. We calculated reliable inequity measures for 426 and 322 practices, depending on the measure. These practices reflected fewer than 10 percent of practices treating Medicare beneficiaries with chemotherapy, but they treated approximately half of all White and Black Medicare beneficiaries receiving chemotherapy and two-thirds of Black Medicare beneficiaries receiving chemotherapy. Black patients experienced chemotherapy-associated ED visits and hospitalizations at higher rates (54.2 percent and 35.8 percent, respectively) than White patients (45.7 percent and 31.9 percent, respectively). The median within-practice Black-White difference was 8.1 percentage points for chemotherapy-associated ED visits and 2.7 percentage points for chemotherapy-associated hospitalizations. Additional research is needed to identify other reliable measures of racial inequities in health care quality, measure care inequities in smaller practices, and assess whether providing practice-level feedback could improve equity.

Impact of the Oncology Care Model on Use of Supportive Care Medications During Cancer Treatment

PURPOSE

The Oncology Care Model (OCM) is an episode-based alternative payment model for cancer care that seeks to reduce Medicare spending while maintaining care quality. We evaluated the impact of OCM on appropriate use of supportive care medications during cancer treatment.

METHODS

We evaluated chemotherapy episodes assigned to OCM (n = 201) and comparison practices (n = 534) using Medicare claims (2013-2019). We assessed denosumab use for beneficiaries with bone metastases from breast, lung, or prostate cancer; prophylactic WBC growth factor use for beneficiaries receiving chemotherapy for breast, lung, or colorectal cancer; and prophylactic use of neurokinin-1 (NK1) antagonists and long-acting serotonin antagonists for beneficiaries receiving chemotherapy for any cancer type. Analyses used a difference-in-difference approach.

RESULTS

After its launch in 2016, OCM led to a relative reduction in the use of denosumab for beneficiaries with bone metastases receiving bone-modifying medications (eg, 5.0 percentage point relative reduction in breast cancer episodes [90% CI, -7.1 to -2.8]). There was no OCM impact on use of prophylactic WBC growth factors during chemotherapy with high or low risk for febrile neutropenia. Among beneficiaries receiving chemotherapy with intermediate febrile neutropenia risk, OCM led to a 7.6 percentage point reduction in the use of prophylactic WBC growth factors during breast cancer episodes (90% CI, -12.6 to -2.7); there was no OCM impact in lung or colorectal cancer episodes. Among beneficiaries receiving chemotherapy with high or moderate emetic risk, OCM led to reductions in the prophylactic use of NK1 antagonists and long-acting serotonin antagonists (eg, 6.0 percentage point reduction in the use of NK1 antagonists during high emetic risk chemotherapy [90% CI, -9.0 to -3.1]).

CONCLUSION

OCM led to the reduced use of some high-cost supportive care medications, suggesting more value-conscious care.

The Oncology Care Model and Adherence to Oral Cancer Drugs: A Difference-in-Differences Analysis

BACKGROUND

Adherence to oral cancer drugs is suboptimal. The Oncology Care Model (OCM) offers oncology practices financial incentives to improve the value of cancer care. We assessed the impact of OCM on adherence to oral cancer therapy for chronic myelogenous leukemia (CML), prostate cancer, and breast cancer.

METHODS

Using 2014-2019 Medicare data, we studied chemotherapy episodes for Medicare fee-for-service beneficiaries prescribed tyrosine kinase inhibitors (TKIs) for CML, antiandrogens (ie, enzalutamide, abiraterone) for prostate cancer, or hormonal therapies for breast cancer in OCM-participating and propensity-matched comparison practices. We measured adherence as the proportion of days covered and used difference-in-difference (DID) models to detect changes in adherence over time, adjusting for patient, practice, and market-level characteristics.

RESULTS

There was no overall impact of OCM on improved adherence to TKIs for CML (DID = -0.3%, 90% confidence interval [CI] = -1.2% to 0.6%), antiandrogens for prostate cancer (DID = 0.4%, 90% CI = -0.3% to 1.2%), or hormonal therapy for breast cancer (DID = 0.0%, 90% CI = -0.2% to 0.2%). Among episodes for Black beneficiaries in OCM practices, for whom adherence was lower than for White beneficiaries at baseline, we observed small improvements in adherence to high cost TKIs (DID = 3.0%, 90% CI = 0.2% to 5.8%) and antiandrogens (DID = 2.2%, 90% CI = 0.2% to 4.3%).

CONCLUSIONS

OCM did not impact adherence to oral cancer therapies for Medicare beneficiaries with CML, prostate cancer, or breast cancer overall but modestly improved adherence to high-cost TKIs and antiandrogens for Black beneficiaries, who had somewhat lower adherence than White beneficiaries at baseline. Patient navigation and financial counseling are potential mechanisms for improvement among Black beneficiaries.

Association of Participation in the Oncology Care Model With Medicare Payments, Utilization, Care Delivery, and Quality Outcomes

IMPORTANCE

In 2016, the US Centers for Medicare & Medicaid Services initiated the Oncology Care Model (OCM), an alternative payment model designed to improve the value of care delivered to Medicare beneficiaries with cancer.

OBJECTIVE

To assess the association of the OCM with changes in Medicare spending, utilization, quality, and patient experience during the OCM's first 3 years.

DESIGN, SETTING, AND PARTICIPANTS

Exploratory difference-in-differences study comparing care during 6-month chemotherapy episodes in OCM participating practices and propensity-matched comparison practices initiated before (January 2014 through June 2015) and after (July 2016 through December 2018) the start of the OCM. Participants included Medicare fee-for-service beneficiaries with cancer treated at these practices through June 2019.

EXPOSURES

OCM participation.

MAIN OUTCOMES AND MEASURES

Total episode payments (Medicare spending for Parts A, B, and D, not including monthly payments for enhanced oncology services); utilization and payments for hospitalizations, emergency department (ED) visits, office visits, chemotherapy, supportive care, and imaging; quality (chemotherapy-associated hospitalizations and ED visits, timely chemotherapy, end-of-life care, and survival); and patient experiences.

RESULTS

Among Medicare fee-for-service beneficiaries with cancer undergoing chemotherapy, 483 319 beneficiaries (mean age, 73.0 [SD, 8.7] years; 60.1% women; 987 332 episodes) were treated at 201 OCM participating practices, and 557 354 beneficiaries (mean age, 72.9 [SD, 9.0] years; 57.4% women; 1 122 597 episodes) were treated at 534 comparison practices. From the baseline period, total episode payments increased from $28 681 for OCM episodes and $28 421 for comparison episodes to $33 211 for OCM episodes and $33 249 for comparison episodes during the intervention period (difference in differences, -$297; 90% CI, -$504 to -$91), less than the mean $704 Monthly Enhanced Oncology Services payments. Relative decreases in total episode payments were primarily for Part B nonchemotherapy drug payments (difference in differences, -$145; 90% CI, -$218 to -$72), especially supportive care drugs (difference in differences, -$150; 90% CI, -$216 to -$84). The OCM was associated with statistically significant relative reductions in total episode payments among higher-risk episodes (difference in differences, -$503; 90% CI, -$802 to -$204) and statistically significant relative increases in total episode payments among lower-risk episodes (difference in differences, $151; 90% CI, $39-$264). The OCM was not significantly associated with differences in hospitalizations, ED visits, or survival. Of 22 measures of utilization, 10 measures of quality, and 7 measures of care experiences, only 5 were significantly different.

CONCLUSIONS AND RELEVANCE

In this exploratory analysis, the OCM was significantly associated with modest payment reductions during 6-month episodes for Medicare beneficiaries receiving chemotherapy for cancer in the first 3 years of the OCM that did not offset the monthly payments for enhanced oncology services. There were no statistically significant differences for most utilization, quality, and patient experience outcomes.

Sustainability and clinical outcomes of routine screening for pathogenic DPYD gene variants prior to fluoropyrimidine (FP) chemotherapy for gastrointestinal (GI) cancer

216

Background: Dihyropyrimidine dehydrogenase (DPD) deficiency is present in 3-5% of patients, and is associated with substantially increased risk of severe and/or fatal toxicity during standard-dose FP chemotherapy. Genotyping of pathogenic DPYD variants is a readily available screening test for DPD deficiency, and prospective studies show that dose-reduced FP chemotherapy can be used safely in heterozygous DPYD variant carriers. Methods: Following a sentinel toxicity event the GI medical oncology group at the Norris Cotton Cancer Center adopted a shared practice of routine screening for pathogenic DPYD gene variants prior to FP chemotherapy (5-FU or capecitabine). Screening procedures involved physicians, NP/PAs, nurses, pharmacists, and schedulers. Testing was completed at a send-out lab until late 2020, when an in-house test became available. The current test panel evaluates for 3 gene variants: c.1905+1G > A (*2A), c.1679T > G (*13), and c.2846A > T. We report on the sustainability and clinical outcomes of DPYD gene variant screening. We identified all patients starting new FP-containing intravenous chemotherapy regimens (e.g., FOLFOX, CAPOX) for treatment of GI cancer at two sites (LEB & STJ) between Jan. 2019 and May 2021. We used electronic medical records to evaluate for completion of DPYD genotyping, and we describe the prevalence and management of DPYD gene variant carriers. Results: We identified 333 patients starting FP-containing chemotherapy regimens during the study period, including 287 patients without prior history of FP chemotherapy. Screening with DPYD genotyping was completed in 228 of 287 eligible patients (79%). Screening rates increased from 34% in Q1 of 2019 to 90% in Jan-May 2021. Five GI oncology sub-specialists accounted for 89% of screen-eligible patients and 96% of completed tests, but 10 unique physicians ordered ≥1 test. Of 228 screened patients, six (2.6%) were heterozygous carriers of pathogenic DPYD gene variants (*2A [2 patients], *13 [1], and c.2846A > T [3]). Variant carriers started FP chemotherapy with a 33-50% reduction. Two of six patients required further dose reduction due to FP-related toxicity (grade 4 neutropenia, grade 3 diarrhea). All evaluable variant carriers completed planned initial treatment. Implementation challenges included variable insurance coverage of DPYD genotyping, site-specific test ordering and reporting processes, and inconsistent turn-around time for send-out testing (resolved with on-site testing). Conclusions: Routine screening for pathogenic DPYD gene variants prior to FP chemotherapy is feasible and sustainable in the U.S. DPYD genotyping coupled with chemotherapy dose reductions for DPYD variant carriers facilitates safe and timely completion of planned chemotherapy treatments.

Association of rurality and race with surgical treatment and outcomes for nonmetastatic colon cancer

78

Background: Rural cancer patients face limited access to care due to greater travel distance and lack of specialty cancer care. Little is known about the intersection of rurality with well-documented racial disparities in colon cancer treatment and outcomes. Methods: We used fee-for-service Medicare claims to study patients age 65+ diagnosed with incident colon cancer without evidence of metastases who underwent cancer-directed surgery between 04/01/2016 and 09/30/2018. The primary exposure wasrurality of patient’s residence categorized as metropolitan (metro), micropolitan, and small town/rural. Outcomes were non-elective surgery (emergency department visit or transfer within 2 days prior to surgery), receipt of minimally invasive surgery (laparoscopic or robotic), 90-day surgical complications, and 90-day mortality. Logistic regression adjusted for patient demographics, cancer side (right vs left), comorbidities, and Area Deprivation Index. We assessed effect modification by race/ethnicity. Results: Of 57,710 patients with incident non-metastatic colon cancer, 37,691 (65%) underwent surgery. In this surgical cohort, small town/rural and micropolitan residents were more likely to be older, white, and Medicare-Medicaid dual-eligible than metro residents. After risk adjustment, patients in small town/rural areas had higher odds of non-elective surgery (OR =1.24, 95% CI:1.13-1.36) and lower odds of minimally invasive surgery (OR = 0.75, 95% CI:0.71-0.80) than patients living in metro areas. Similar results were seen for micropolitan areas. White rural patients had lower mortality than white urban patients, whereas black rural patients had higher mortality than black metro patients (see Table). Increasing area deprivation was associated with higher odds of non-elective surgery, surgical complications and mortality, and lower odds of minimally invasive surgery, even after adjusting for race and rurality. Conclusions: Small town/rural-residing Medicare beneficiaries undergoing surgery for non-metastatic colon cancer were less likely to receive optimal surgical management and had worse outcomes, especially among non-white patients. The compounded effect of rurality, race/ethnicity, and social deprivation should be incorporated in developing policies and interventions to improve care for rural cancer patients.[Table: see text]

Cancer-related impairments and functional limitations among long-term cancer survivors: Gaps and opportunities for clinical practice

This commentary provides a concise overview of the epidemiology of cancer survivorship and work, common functional limitations experienced by cancer survivors, and evidence‐based recommendations for interventions available to improve function. It also describes the US Social Security Administration's disability claims process, its eligibility requirements, and barriers for long‐term survivors in securing approval for disability claims, and offers insights for practicing clinicians in holistically addressing functional limitations in practice.

Pathogenic DPYD Variants and Treatment-Related Mortality in Patients Receiving Fluoropyrimidine Chemotherapy: A Systematic Review and Meta-Analysis

BACKGROUND

Pathogenic variants of the DPYD gene are strongly associated with grade ≥3 toxicity during fluoropyrimidine chemotherapy. We conducted a systematic review and meta-analysis to estimate the risk of treatment-related death associated with DPYD gene variants.

MATERIALS AND METHODS

We searched for reports published prior to September 17, 2020, that described patients receiving standard-dose fluoropyrimidine chemotherapy (5-fluorouracil or capecitabine) who had baseline testing for at least one of four pathogenic DPYD variants (c.1129-5923C>G [HapB3], c.1679T>G [*13], c.1905+1G>A [*2A], and c.2846A>T) and were assessed for toxicity. Two reviewers assessed studies for inclusion and extracted study-level data. The primary outcome was the relative risk of treatment-related mortality for DPYD variant carriers versus noncarriers; we performed data synthesis using a Mantel-Haenszel fixed effects model.

RESULTS

Of the 2,923 references screened, 35 studies involving 13,929 patients were included. DPYD variants (heterozygous or homozygous) were identified in 566 patients (4.1%). There were 14 treatment-related deaths in 13,363 patients without identified DPYD variants (treatment-related mortality, 0.1%; 95% confidence interval [CI], 0.1-0.2) and 13 treatment-related deaths in 566 patients with any of the four DPYD variants (treatment-related mortality, 2.3%; 95% CI, 1.3%-3.9%). Carriers of pathogenic DPYD gene variants had a 25.6 times increased risk of treatment-related death (95% CI, 12.1-53.9; p < .001). After excluding carriers of the more common but less deleterious c.1129-5923C>G variant, carriers of c.1679T>G, c.1905+1G>A, and/or c.2846A>T had treatment-related mortality of 3.7%.

CONCLUSION

Patients with pathogenic DPYD gene variants who receive standard-dose fluoropyrimidine chemotherapy have greatly increased risk for treatment-related death.

IMPLICATIONS FOR PRACTICE

The syndrome of dihydropyrimidine dehydrogenase (DPD) deficiency is an uncommon but well-described cause of severe toxicity related to fluoropyrimidine chemotherapy agents (5-fluorouracil and capecitabine). Patients with latent DPD deficiency can be identified preemptively with genotyping of the DPYD gene, or with measurement of the plasma uracil concentration. In this systematic review and meta-analysis, the authors study the rare outcome of treatment-related death after fluoropyrimidine chemotherapy. DPYD gene variants associated with DPD deficiency were linked to a 25.6 times increased risk of fluoropyrimidine-related mortality. These findings support the clinical utility of DPYD genotyping as a screening test for DPD deficiency.

Measuring disparities in quality of oncology care across oncology practices

6533

Background: Equity is now recognized as an essential aspect of health care quality. Racial inequities in clinical performance diminish overall system performance. We assessed the feasibility and reliability of practice-level measures of racial disparities in chemotherapy-associated emergency department (ED) visits and hospitalizations. Methods: Using fee-for-service Medicare data, we identified 1,196,970 Black or White fee-for-service Medicare beneficiaries with cancer receiving chemotherapy in 2016-2019, who were attributed to 5511 oncology practices that treated at least 1 Black and 1 White beneficiary (96.4% of all beneficiaries). We studied two CMS quality measures: chemotherapy associated ED visits and chemotherapy associated hospitalizations. For each outcome, we estimated multi-level models with separate practice-level random intercepts for Black and White patients to quantify practice-level Black-White disparities in adjusted rates of these measures and assess the associations of these rates with the proportion of Black patients in the practice. Results: Overall, 108,177 Black and 966,381 White beneficiaries with cancer were treated at 1321 practices with reliable estimates (reliability ≥70%) of Black-White differences in rates of chemotherapy-associated ED visits; 101,411 Black and 915,895 White beneficiaries were treated at 1,012 practices with reliable estimates of chemotherapy-associated hospitalizations. These practices treated 80% or more of all Black and White beneficiaries; 10% of these practices treated 75% of Black beneficiaries. The median adjusted Black-White rate difference across practices was +8.9% [interquartile interval (IQI) +5.0%, +12.8%; 5th, 95th percentile -1.8 to +19.2%] for chemotherapy associated ED visits and +4.4% [IQI +1.3%, +7.7%; 5th, 95th percentile -3.5% to +13.5%] for chemotherapy associated hospitalizations. Chemotherapy-associated ED visit rates were 3.2 percentage points higher for Black vs White patients (P <.001) at the practice with the mean % of Black patients, but the difference was smaller in practices with more Black patients (0.4 percentage points less for each 10% increase in Black share, P <.001). Chemotherapy-associated hospitalization rates were 0.6 percentage points lower for Black vs White patients (P =.01) but did not vary by practice racial composition. Conclusions: Using data from more than 1000 practices over 4 years, we calculated reliable estimates of practice-level racial disparities in chemotherapy-associated ED visits and hospitalizations. Practice-level performance for these quality measures was generally lower for Black versus White beneficiaries. Measuring and providing feedback on practice-level Black-White disparities in oncology performance measures may be one effective tool for advancing racial equity in care quality for cancer patients receiving chemotherapy.

Comparison of clinician and model estimates of risk for hospitalization during systemic therapy for advanced cancer

1530

Background: Patients receiving treatment for advanced cancer are at substantial risk for unplanned hospitalization. A validated two-variable risk model can identify patients at increased risk for hospitalization. However, little is known about how model-based estimates of hospitalization risk compare with assessments of treating clinicians. Methods: We identified patients initiating a new line of systemic therapy for advanced non-hematologic cancer. For each patient, we assigned three categorical estimates of 30-day hospitalization risk. The first risk estimate was generated by a validated two-variable risk prediction model with inputs of pretreatment plasma sodium and albumin (PMID: 30995122); continuous risk scores were converted to risk tertiles. We solicited a second risk estimate by real-time survey of a treating oncology clinician; clinicians were instructed to estimate hospitalization risk as low, intermediate, or high, as compared with other patients. A third hybrid risk estimate retained the highest risk category from either the clinician or model risk assessment. We describe the agreement of clinician and model-based estimates of 30-day hospitalization risk, and we compare the sensitivity and specificity of clinician, model, and hybrid high-risk assessments, using McNemar’s test. We compared discrimination of the three risk estimates via the area under the ROC curve (AUC). Results: We identified 104 patients with valid clinician and model hospitalization risk estimates and complete 30-day follow-up. The most common cancer type was lung cancer (27%), the median age was 68 years, and 62% of patients were male. 30-day hospitalization occurred in 21 patients (20.2%). There was moderate to poor agreement between clinician and model categorical estimates of hospitalization risk (weighted kappa = 0.245). The proportion of patients identified as high-risk by the clinician, model, and hybrid assessments was 15.4%, 26.0%, and 33.7%. Sensitivity and specificity of the high-risk categorization for 30-day hospitalization were 38% and 90% for the clinician assessment, 57% and 82% for the model assessment (NSS for comparison with clinician assessment), and 76% and 77% for the hybrid assessment (greater sensitivity [p = 0.008] and lesser specificity [p = 0.001] than clinician assessment). The AUC values for the clinician, model, and hybrid assessments were 0.674, 0.757, and 0.764, respectively. Conclusions: Compared with the estimate of a treating clinician, a two-variable risk model exhibited similar sensitivity and specificity for 30-day hospitalization risk. A hybrid risk assessment incorporating information from the risk model significantly improved on the sensitivity of the clinician risk assessment. Future research should test strategies to prevent hospitalizations by targeting interventions to high-risk patients.

Association of rurality and race with surgical treatment and outcomes for nonmetastatic colon cancer

e18536

Background: Rural cancer patients face limited access to care due to greater travel distance and lack of specialty cancer care. Little is known about the intersection of rurality with well-documented racial disparities in colon cancer treatment and outcomes. Methods: We used fee-for-service Medicare claims to study patients age 65+ diagnosed with incident colon cancer without evidence of metastases who underwent cancer-directed surgery between 04/01/2016 and 09/30/2018. The primary exposure was rurality of patient’s residence categorized as metropolitan (metro), micropolitan, and small town/rural. Outcomes were non-elective surgery (emergency department visit or transfer within 2 days of surgery), receipt of minimally invasive surgery (laparoscopic or robotic), 90-day surgical complications, and 90-day mortality. Logistic regression adjusted for patient demographics, cancer side (right vs left), comorbidities, and Area Deprivation Index. We assessed effect modification by race/ethnicity. Results: Of 57,710 patients with incident non-metastatic colon cancer, 37,691 (65%) underwent surgery. In this surgical cohort, small town/rural and micropolitan residents were more likely to be older, white, and Medicare-Medicaid dual-eligible than metro residents. After risk adjustment, patients in small town/rural areas had higher odds of non-elective surgery (OR=1.24, 95% CI:1.13-1.36) and lower odds of minimally invasive surgery (OR=0.75, 95% CI:0.71-0.80) than patients living in metro areas. Similar results were seen for micropolitan areas. The association between rurality and 90-day outcomes differed by race/ethnicity (p-interaction=0.001 for surgical complications and mortality, see Table). Hispanics and other races had higher odds of 90-day surgical complications in non-metro versus metro areas but there was no notable difference for white patients. Likewise, compared to metro areas, racial/ethnic minorities had higher odds of 90-day mortality in small town/rural areas but white patients had lower odds. Conclusions: Small town/rural-residing Medicare beneficiaries undergoing surgery for non-metastatic colon cancer were less likely to receive optimal surgical management and worse outcomes, especially among non-white patients. The compounded effect of sociodemographic factors should be further studied to develop targeted policies and improve care for rural cancer patients.[Table: see text]

Impact of the Oncology Care Model on use of bone supportive medications, antiemetics, and growth factors

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Background: The Oncology Care Model (OCM) is a voluntary, episode-based alternative payment model for cancer care launched by the Centers for Medicare & Medicaid Services in July 2016. OCM incentivizes participating practices to reduce spending during chemotherapy treatment while maintaining quality of care. We evaluated the impact of OCM on the use of costly supportive care medications. Methods: Using 100% Medicare claims (2013-2019), we evaluated use of outpatient supportive care medications during chemotherapy episodes assigned to OCM practices (n = 186) or propensity-matched comparison practices (n = 534). For bone supportive medications, we evaluated use of bisphosphonates and/or denosumab in beneficiaries with bone metastases from breast, lung, or prostate cancer. For anti-emetic drugs, we evaluated prophylactic use of neurokinin-1 (NK1) antagonists and long-acting (LA) serotonin antagonists. For white blood cell growth factors (GCSFs), we evaluated prophylactic use in beneficiaries starting chemotherapy for breast, lung, or colorectal cancer; we separately evaluated use of biosimilar (vs originator) filgrastim. Analyses employed the difference-in-differences (DID) approach, excepting the filgrastim biosimilar analysis where we assessed the adoption trend. Results: There was no OCM impact on receipt of any bone supportive medication (denosumab or bisphosphonate) among beneficiaries with bone metastases; however, OCM led to a relative decrease in use of denosumab for breast cancer (DID = -5.0 percentage points [90% CI -7.1, -2.8]), prostate cancer (-4.0 percentage points [90% CI -5.9, -2.2]), and lung cancer (-4.1 percentage points [90% CI -7.4, -0.9]). In beneficiaries starting chemotherapy regimens with high or moderate emetic risk, OCM led to reductions in prophylactic use of NK1 antagonists and LA serotonin antagonists (e.g. 6.0 percentage point reduction in use of NK1 antagonists during high emetic risk chemotherapy [90% CI -9.0, -3.1]); there was no impact on antiemetic use during low emetic risk chemotherapy. There was no OCM impact on use of prophylactic WBC growth factors among beneficiaries receiving chemotherapy with high risk for febrile neutropenia (FN). Among beneficiaries receiving chemotherapy with intermediate risk for FN, OCM led to a 7.6 percentage point reduction in prophylactic GCSF use for patients with breast cancer (90% CI -12.6, -2.7); however, there was no OCM impact on prophylactic GCSF use in patients with lung or colorectal cancer. Among beneficiaries receiving filgrastim, OCM led to faster adoption of biosimilar vs. originator filgrastim (differential trend estimate 2.6%, 90% CI 1.0, 4.4). Conclusions: OCM led to reduced use of some high cost supportive care medications, with patterns suggesting more value-conscious care. Alternative payment models have potential to drive value-based changes in medication use during cancer care.

Evaluation of Reliability and Correlations of Quality Measures in Cancer Care

IMPORTANCE

Measurement of the quality of care is important for alternative payment models in oncology, yet the ability to distinguish high-quality from low-quality care across oncology practices remains uncertain.

OBJECTIVE

To assess the reliability of cancer care quality measures across oncology practices using registry and claims-based measures of process, utilization, end-of-life (EOL) care, and survival, and to assess the correlations of practice-level performance across measure and cancer types.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used the Surveillance, Epidemiology, and End Results (SEER) Program registry linked to Medicare administrative data to identify individuals with lung cancer, breast cancer, or colorectal cancer (CRC) that was newly diagnosed between January 1, 2011, and December 31, 2015, and who were treated in oncology practices with 20 or more patients. Data were analyzed from January 2018 to December 2020.

MAIN OUTCOMES AND MEASURES

Receipt of guideline-recommended treatment and surveillance, hospitalizations or emergency department visits during 6-month chemotherapy episodes, care intensity in the last month of life, and 12-month survival were measured. Summary measures for each domain in each cohort were calculated. Practice-level rates for each measure were estimated from hierarchical linear models with practice-level random effects; practice-level reliability (reproducibility) for each measure based on the between-measure variance, within-measure variance, and distribution of patients treated in each practice; and correlations of measures across measure and cancer types.

RESULTS

In this study of SEER registry data linked to Medicare administrative data from 49 715 patients with lung cancer treated in 502 oncology practices, 21 692 with CRC treated in 347 practices, and 52 901 with breast cancer treated in 492 practices, few practices had 20 or more patients who were eligible for most process measures during the 5-year study period. Patients were 65 years or older; approximately 50% of the patients with lung cancer and CRC and all of the patients with breast cancer were women. Most measures had limited variability across practices. Among process measures, 0 of 6 for lung cancer, 0 of 6 for CRC, and 3 of 11 for breast cancer had a practice-level reliability of 0.75 or higher for the median-sized practice. No utilization, EOL care, or survival measure had reliability across practices of 0.75 or higher. Correlations across measure types were low (r ≤ 0.20 for all) except for a correlation between the CRC process and 1-year survival summary measures (r = 0.35; P < .001). Summary process measures had limited or no correlation across lung cancer, breast cancer, and CRC (r ≤ 0.16 for all).

CONCLUSIONS AND RELEVANCE

This study found that quality measures were limited by the small numbers of Medicare patients with newly diagnosed cancer treated in oncology practices, even after pooling 5 years of data. Measures had low reliability and had limited to no correlation across measure and cancer types, suggesting the need for research to identify reliable quality measures for practice-level quality assessments.

Cost effectiveness of DPYD genotyping to screen for dihydropyrimidine dehydrogenase (DPD) deficiency prior to adjuvant chemotherapy for colon cancer

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Background: Fluoropyrimidine chemotherapy agents, including 5-fluorouracil and capecitabine, are the backbone of adjuvant treatment for colon cancer, and adjuvant chemotherapy substantially reduces recurrence and mortality after surgical resection of stage 3 colon cancer. While fluoropyrimidine chemotherapy is generally safe, the risk of severe, potentially fatal chemotherapy toxicity is substantially increased for the 2-3% of U.S. patients with DPD deficiency caused by pathogenic variants in the DPYD gene. DPYD genotype testing is readily available in the U.S. but has not been widely adopted. We evaluated the cost effectiveness of DPYD genotyping prior to adjuvant chemotherapy for colon cancer in the U.S. Methods: We constructed a Markov model to simulate screening for DPD deficiency with DPYD genotyping (versus no screening) among patients receiving fluoropyrimidine-based adjuvant chemotherapy for stage 3 colon cancer. Screen-positive patients were modeled to receive dose-reduced fluoropyrimidine chemotherapy. Model transition probabilities for treatment-related toxicities were derived from published clinical trial data with annotation of DPYD genotype and chemotherapy dosing strategy. Our analysis is from the healthcare perspective, with a time horizon of five years and an annual discount rate of 3% for future costs and benefits. Direct healthcare costs and health utilities were estimated from published sources and converted to 2020 US dollars, and post-treatment survival was modeled from SEER data. The primary outcome was the incremental cost-effectiveness ratio (ICER), defined as dollars per quality-adjusted life year (QALY). We used a value of $100,000/QALY as the cost-effectiveness threshold. One-way sensitivity analyses were used to examine model uncertainty. Results: Compared with no screening, screening for DPD deficiency with DPYD genotyping increased per-patient costs by $106 and improved quality-adjusted survival by 0.0028 QALYs, leading to an ICER of $37,300/QALY. In one-way sensitivity analyses, the ICER exceeded $100,000/QALY when the carrier frequency of pathogenic DPYD gene variants was less than 1.17%, and when the specificity of DPYD genotyping was less than 98.9%. Cost-effectiveness estimates were not sensitive to the cost of DPYD genotyping, the cost of toxicity-related hospitalizations, or the health utility associated with grade 3-4 toxicity. Conclusions: Among patients receiving adjuvant chemotherapy for stage 3 colon cancer, screening for DPD deficiency with DPYD genotyping is a cost-effective strategy for preventing infrequent but severe, sometimes fatal toxicities of fluoropyrimidine chemotherapy.

How Do Claims-Based Measures of End-of-Life Care Compare to Family Ratings of Care Quality?

OBJECTIVES

Assess whether frequently-used claims-based end-of-life (EOL) measures are associated with higher ratings of care quality.

DESIGN

Retrospective cohort study.

SETTING/PARTICIPANTS

Deceased fee-for-service Medicare beneficiaries with cancer who underwent chemotherapy during July 2016 to January 2017 and died within 12 months and their caregiver respondents to an after-death survey (n = 2,559).

MEASUREMENTS

We examined claims-based measures of EOL care: chemotherapy 14 days or more before death; inpatient admissions, intensive care unit (ICU) use, and emergency department (ED) visits 30 days or more before death; hospice election and the timing of election before death. Primary outcomes are family ratings of "excellent" care in the last month of life and reports that hospice care began "at the right time." Associations were assessed with logistic regression, adjusted by patient characteristics.

RESULTS

Family rated EOL care as excellent less often, if within 30 days before death the cancer patient had inpatient admissions (1 hospitalization = 41.5% vs 51.5% none, adjusted difference -10.1 percentage points), ICU use (38.6% for any ICU use vs 47.4% none; adjusted difference -8.8 percentage points), ED visits (41.0% 1 visit vs 51.6% no visits; adjusted difference -10.6 percentage points), or elected hospice within 7 days before death. Among hospice enrollees, family more often reported that hospice began at the right time if it started at least 7 days before death (hospice 1-2 days before death 60.2% vs hospice 7-13 days 74.9%; adjusted difference +14.7 percentage points).

CONCLUSIONS

Claims-based measures of EOL care for cancer patients that reflect avoidance of hospital-based care and earlier hospice enrollment are associated with higher ratings of care quality by bereaved family members.

Design of eSyM: An ePRO-based symptom management tool fully integrated in the electronic health record (Epic) to foster patient/clinician engagement, sustainability, and clinical impact

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Background: Chemotherapy and surgery can cause distressing symptoms, which can be a burden for health systems to address. Programs that directly engage patients, including electronic tracking of patient-reported outcomes (ePROs), can improve symptom control and decrease the need for acute care. Previous ePRO programs have relied on third party vendors with limited EHR integration, constraining their clinical utility and scalability. An integrated solution could offer distinct advantages. Methods: As part of NCI’s Moonshot-funded IMPACT consortium, 6 health systems and Epic built an electronic symptom management program (eSyM) based on the PRO-CTCAE questionnaire that is fully integrated into the EHR. The agile, user-centered design process engaged patients, clinicians, and institutions. The core functional components include: 1) symptom surveys in the postoperative period or between chemotherapy visits, 2) self-management tip sheets, 3) clinician alerts, and 4) dashboards for population management. Critical points of integration with supporting EHR functions and workflow impacts were identified; and major challenges of integration and implementation were described. Results: eSyM, which was implemented at two health systems (Baptist Memorial in Tennessee and Mississippi and West Virginia University Health) in the fall of 2019, required multiple supporting EHR functions: 1) access a secure, HIPPA-compliant patient portal/messaging system (MyChart); 2) record diagnosis, procedure and chemotherapy treatment plan data; 3) identify target populations and track metrics/events; 4) define and execute autonomous logic-based workflow rules; 5) generate reports for clinicians/patients; and 6) documentation. Major challenges included: 1) working within pre-existing EHR system standards and capabilities, which limited the ability to customize interfaces and workflows specifically for the eSyM use case; and 2) adapting to different EHR configurations and polices across multiple health systems. Conclusions: The eSyM build leveraged many existing EHR capabilities and overcame regulatory hurdles; but it required design and workflow compromise. Integration of ePRO-based symptom management programs into the EHR could help overcome barriers, consolidate clinical workflows, and foster scalability/sustainability. Ongoing efforts include launching eSyM at four more sites and evaluating its adoption, usability, and impact on clinical outcomes.

Role of norms in variation in cancer centers' end-of-life quality: qualitative case study protocol

Background

A critical barrier to improving the quality of end-of-life (EOL) cancer care is our lack of understanding of the mechanisms underlying variation in EOL treatment intensity. This study aims to fill this gap by identifying 1) organizational and provider practice norms at major US cancer centers, and 2) how these norms influence provider decision making heuristics and patient expectations for EOL care, particularly for minority patients with advanced cancer.

Methods

This is a multi-center, qualitative case study at six National Comprehensive Cancer Network (NCCN) and National Cancer Institute (NCI) Comprehensive Cancer Centers. We will theoretically sample centers based upon National Quality Forum (NQF) endorsed EOL quality metrics and demographics to ensure heterogeneity in EOL intensity and region. A multidisciplinary team of clinician and non-clinician researchers will conduct direct observations, semi-structured interviews, and artifact collection. Participants will include: 1) cancer center and clinical service line administrators; 2) providers from medical, surgical, and radiation oncology; palliative or supportive care; intensive care; hospital medicine; and emergency medicine who see patients with cancer and have high clinical practice volume or high local influence (provider interviews and observations); and 3) adult patients with metastatic solid tumors and whom the provider would not be surprised if they died in the next 12 months and their caregivers (patient and caregiver interviews). Leadership interviews will probe about EOL institutional norms and organization. We will observe inpatient and outpatient care for two weeks. Provider interviews will use vignettes to probe explicit and implicit motivations for treatment choices. Semi-structured interviews with patients near EOL, or their family members and caregivers will explore past, current, and future decisions related to their cancer care. We will import transcribed field notes and interviews into Dedoose software for qualitative data management and analysis, and we will develop and apply a deductive and inductive codebook to the data.

Discussion

This study aims to improve our understanding of organizational and provider practice norms pertinent to EOL care in U.S. cancer centers. This research will ultimately be used to inform a provider-oriented intervention to improve EOL care for racial and ethnic minority patients with advanced cancer.

Trial registration

Clinicaltrials.gov; NCT03780816; December 19, 2018.

A Systematic Review of Clinical Decision Support Systems for Clinical Oncology Practice

BACKGROUND

Electronic health records are central to cancer care delivery. Electronic clinical decision support (CDS) systems can potentially improve cancer care quality and safety. However, little is known regarding the use of CDS systems in clinical oncology and their impact on patient outcomes.

METHODS

A systematic review of peer-reviewed studies was performed to evaluate clinically relevant outcomes related to the use of CDS tools for the diagnosis, treatment, and supportive care of patients with cancer. Peer-reviewed studies published from 1995 through 2016 were included if they assessed clinical outcomes, patient-reported outcomes (PROs), costs, or care delivery process measures.

RESULTS

Electronic database searches yielded 2,439 potentially eligible papers, with 24 studies included after final review. Most studies used an uncontrolled, pre-post intervention design. A total of 23 studies reported improvement in key study outcomes with use of oncology CDS systems, and 12 studies assessing the systems for computerized chemotherapy order entry demonstrated reductions in prescribing error rates, medication-related safety events, and workflow interruptions. The remaining studies examined oncology clinical pathways, guideline adherence, systems for collection and communication of PROs, and prescriber alerts.

CONCLUSIONS

There is a paucity of data evaluating clinically relevant outcomes of CDS system implementation in oncology care. Currently available data suggest that these systems can have a positive impact on the quality of cancer care delivery. However, there is a critical need to rigorously evaluate CDS systems in oncology to better understand how they can be implemented to improve patient outcomes.