Quality Of Care Metrics Research Articles

Variation in Palliative Care Program Performance for Patients with Metastatic Cancer

ContextWhile specialist palliative care is associated with improved end-of-life quality metrics for patients with advanced cancer, its effectiveness may differ between hospitals. ObjectivesTo examine variation in palliative care program performance on end-of-life care quality metrics. MethodsRetrospective cohort study of palliative care programs that participated in the National Palliative Care Registry, 2018-2019. Medicare data for patients age ≥65 who died with metastatic cancer were aggregated on a program-level. Variation in program performance on outcomes (use of hospice, hospice enrollment ≥3 days, use of intensive care in the last 30 days of life, and use of chemotherapy in the last 14 days of life) was quantified by risk-standardized outcome rates (RSOR) and adjusted median odds ratios (aMOR). ResultsThe cohort comprised 235 palliative care programs who delivered care to 33,015 patients. There was substantial variation in use of hospice (median RSOR 65.6%, interquartile range (IQR) 57.5%-74.3%), hospice enrollment ≥3 days (median RSOR 53.6%, IQR 48.6%-58.2%), and use of intensive care (median RSOR 14.1%, IQR 13.1%-15.3%), but not use of chemotherapy (median RSOR 1.5%, IQR 1.4%-1.5%). Variation was greatest for hospice use (aMOR 1.48 [1.39-1.57]), suggesting that patients at programs with high hospice use would be 48% more likely to use hospice than if they received care at programs with low use. ConclusionWe found variation in most end-of-life quality metrics for patients with metastatic cancer. Further work is needed to better understand why variations exist and whether such variations reflect a difference in quality of care.

ASO Visual Abstract: Immigration Status and Breast Cancer Surgery Quality of Care Metrics: A Population-Level Analysis.

ASO Visual Abstract: Immigration Status and Breast Cancer Surgery Quality of Care Metrics: A Population-Level Analysis.

Nutritional care for cancer patients: are we doing enough?

Malnutrition is associated with higher rates of surgical complications, increased anticancer treatment toxicities, longer hospital stays, higher healthcare costs, poorer patient quality of life, and lower survival rates. Nutritional support has been shown to improve all of these outcomes. However, the nutritional care of cancer patients is still suboptimal and several issues remain unresolved. Although the effectiveness of nutritional support depends on the timeliness of intervention, assessment of nutritional status is often delayed and perceived as unimportant. When diagnoses of malnutrition are made, they are rarely recorded in medical records. Hospitals lack medical staff dedicated to clinical nutrition, making it difficult to integrate nutritional care into the multidisciplinary management of cancer patients. Outside the hospital, nutritional support is hampered by heterogeneous reimbursement policies and a lack of adequate community nutrition services. In addition, an increasing number of patients are turning to potentially harmful "anti-cancer" diets as trust in medicine declines. Adopting mandatory nutrition screening, monitoring quality of care metrics, providing nutrition education to care providers, and implementing telehealth systems are some of the most urgent interventions that need to be established in the future.

Immigration Status and Breast Cancer Surgery Quality of Care Metrics: A Population-Level Analysis.

As immigrant women face challenges accessing health care, we hypothesized that immigration status would be associated with fewer women with breast cancer receiving surgery for curable disease, fewer undergoing breast conserving surgery (BCS), and longer wait time to surgery. A population-level retrospective cohort study, including women aged 18-70 years with Stage I-III breast cancer diagnosed between 2010 and 2016 in Ontario was conducted. Multivariable analysis was performed to assess odds of undergoing surgery, receiving BCS and wait time to surgery. A total of 31,755 patients were included [26,253 (82.7%) Canadian-born and 5502 (17.3%) immigrant women]. Immigrant women were younger (mean age 51.6 vs. 56.1 years) and less often presented with Stage I/II disease (87.4% vs. 89.8%) (both p < .001). On multivariable analysis, there was no difference between immigrant women and Canadian-born women in odds of undergoing surgery [Stage I OR 0.93 (95% CI 0.79-1.11), Stage II 1.04 (0.89-1.22), Stage III 1.22 (0.94-1.57)], receiving BCS [Stage I 0.93 (0.82-1.05), Stage II 0.96 (0.86-1.07), Stage III 1.00 (0.83-1.22)], or wait time [Stage I 0.45 (-0.61-1.50), Stage II 0.33 (-0.86-1.52), Stage III 3.03 (-0.05-6.12)]. In exploratory analysis, new immigrants did not have surgery more than established immigrants (12.9% vs. 10.1%), and refugee women had longer wait time compared with economic-class immigrants (39.5 vs. 35.3 days). We observed differences in measures of socioeconomic disadvantage and disease characteristics between immigrant and Canadian-born women with breast cancer. Upon adjusting for these factors, no differences emerged in rate of surgery, rate of BCS, and time to surgery. The lack of disparity suggests barriers to accessing basic components of breast cancer care may be mitigated by the universal healthcare system in Canada.

Sustainable Approach to Justice, Equity, Diversity, and Inclusion Through Better Quality Measurement.

The US health care industry has broadly adopted performance and quality measures that are extracted from electronic health records and connected to payment incentives that hope to improve declining life expectancy and health status and reduce costs. While the development of a quality measurement infrastructure based on electronic health record data was an important first step in addressing US health outcomes, these metrics, reflecting the average performance across diverse populations, do not adequately adjust for population demographic differences, social determinants of health, or ecosystem vulnerability. Like society as a whole, health care must confront the powerful impact that social determinants of health, race, ethnicity, and other demographic variations have on key health care performance indicators and quality metrics. Tools that are currently available to capture and report the health status of Americans lack the granularity, complexity, and standardization needed to improve health and address disparities at the local level. In this article, we discuss the current and future state of electronic clinical quality measures through a lens of equity.

Electronic Health Record Tracking of Psychosocial Care in the Context of Serious Illness: A Narrative Review.

Objective: The electronic health record (EHR) has emerged as a fundamental tool but has focused on physical care delivery. Psychosocial screenings and interventions are central to palliative care that supports whole person care models; however, EHR innovations to capture psychosocial care have not been optimized. Material and Methods: A narrative review was conducted from 2009 to March 2023. EMBASE, PubMed, and PsychINFO were queried to identify articles that discussed EHR tracking of psychosocial care in palliative care. Results: Eight articles met inclusion criteria representing a broad range of works in palliative care. Three themes emerged in the narrative review: (a) quality improvement strategy to support EHR tracking in collaboration with key stakeholders, (b) clarification of psychosocial domains for documentation and measurement, and (c) lack of standardization in data collection tools and processes. Discussion: This narrative review contributes to a limited body of literature on EHR extraction of complex sources of distress in palliative care. The designation of four domains (social history and distress, psychological symptoms, spiritual needs, and patients' goals and preferences) defines psychosocial practice aligned with palliative care quality metrics. Recommendations highlight the importance of shared priorities and collaboration with key stakeholders to fully execute on the clinical utility of EHRs. Future work will continue to evaluate data collection tools and systematic approaches to capture psychological needs and social environment and its impact on health outcomes and quality of life. Conclusion: This review will expand on opportunities for automated reporting of psychosocial care in the context of seriously ill.

Factors Associated With Hospital Admission in the Last Month: A Retrospective Single Center Analysis

ContextDriven by concerns about care quality, patient experience, and national metrics, health systems are increasingly focusing on identifying risk factors for patients who are hospitalized in the last month of life. ObjectiveTo evaluate patient factors associated with hospital admission in the last month (30 days). MethodsWe analyzed a retrospective cohort of 8488 patients with a primary care visit in a tertiary health system in the last year of life using a linked electronic health record and decedent dataset. We examined healthcare utilization (primary care, emergency, hospital, intensive care unit encounters) and end-of-life related outcomes (palliative care consultation, do-not-resuscitate orders, advance care planning documentation, hospice at hospital discharge, death in health system). Multivariable logistic regressions identified patient factors associated with admission in the last month. ResultsAbout 2202 (25.9%) patients had a hospital admission in the last month. Among the 1282 (15.1%) who died in a health system facility, most (1103/1282, 86.0%) were admitted to the hospital in the last month. Among patients with a hospital admission and discharged in the last month, 60.9% (686/1126) were discharged on hospice. Compared to those without these diseases, metastatic cancer, liver disease, or heart failure had the highest odds of admission in the last month (adjusted OR 2.36 95%CI 2.05–2.72; 2.28, 95%CI 1.98–2.62; and 2.17 95%CI 1.93–2.45 respectively). ConclusionsAs patients with heart or liver disease or metastatic cancer had the highest odds of admission in the last month, collaborative interventions between primary, palliative, and specialty care may improve quality of care at the end of life.

Outcomes and care quality metrics for people living with rheumatic heart disease and atrial fibrillation in Uganda

Atrial fibrillation (AF) is a common complication of rheumatic heart disease (RHD) and is challenging to treat in lower-resourced settings in which RHD remains endemic. We characterized demographics, treatment outcomes, and factors leading to care retention for participants with RHD and AF in Uganda. We conducted a retrospective analysis of the Uganda national RHD registry between June 2009 and May 2018. Participants with AF or atrial flutter were included. Demographics, survival, and care metrics were compared with participants without AF. Multivariable logistic regression was used to identify factors associated with retention in care among participants with AF. A total of 1530 participants with RHD were analyzed and 293 (19%) had AF. The median age was 24 (interquartile range 14-38) years. Mortality was similar in both groups (adjusted hazard ratio 1.183, P = .77) over a median follow-up of 203 (interquartile range 98-275) days. A total of 79% of AF participants were prescribed anticoagulation, and 43% were aware of their target international normalized ratio. Retention in care was higher in participants with AF (18% vs 12%, P < .01). Factors associated with decreased retention in care include New York Heart Association functional class III/IV (adjusted odds ratio [OR] 0.48, 95% confidence interval [CI] 0.30-0.76) and distance to nearest health center (adjusted OR 0.94, 95% CI 0.90-0.99). Anticoagulation prescription was associated with enhanced care retention (adjusted OR 1.86, 95% CI 1.24-2.79). Participants with RHD and AF in Uganda do not experience higher mortality than those without AF. Anticoagulation prescription rates are high. Although retention in care is poor among RHD participants, those with concurrent AF are more likely to be retained.

Abstract WP92: Application of a Horizontal Communication Process in Combination With Artificial Intelligence (AI) to Improve Stroke Care in Patients With Large Vessel Occlusion (LVO)

Introduction: Timely acute stroke care in patients with large vessel occlusion (LVO) requires both early detection of LVO and efficient multidisciplinary communication. In this study, we aimed to evaluate the impact of using AI and a horizontal communication system within the RapidAI application platform on acute stroke quality metrics in patients with LVO. Methods: On April 2022, the RapidAI application was launched at our center, which allowed for use of AI as a screening measure for LVO detection with immediate notification to neurology, neuroradiology, and neuro-interventional teams. The various teams used instant messaging within the application to communicate clinical data, imaging findings and shared clinical decision making. In this single center study, we retrospectively evaluated stroke care quality metrics for 167 consecutive patients (mean age: 71.6, 49.1% male) who underwent mechanical thrombectomy (MT) from January 2021 to May 2023. Data were compiled from multiple resources including Get-With-The-Guidelines®, chart abstraction, and internal healthcare databases. The groups were compared using appropriate statistical tests and significance was determined using a two-sided alpha of 0.05. Results: 85 patients underwent MT before implementation of the new system, and 82 patients underwent MT after. Demographic features (age, sex, race), cerebrovascular risk factors (hypertension, diabetes, hyperlipidemia, smoking, BMI) and stroke severity were similar between the two groups (p&gt;0.05). Average door to groin puncture (pre: 97 minutes, post: 82 minutes, p=0.10) and discharge disposition (p=0.02) were significantly different between the two groups. In an adjusted analysis of door to groin puncture time, the difference between pre-RapidAI and post-RapidAI was an average reduction of 19 minutes trending towards significance (p = 0.06). Conclusion: Application of a horizontal communication platform in combination with RapidAI was associated with significant improvements in time to intervention in patients with LVO and a significant improvement in the number of patients discharged home.

Impacts of Telehealth Adoption on the Quality of Care for Individuals With Serious Mental Illness: Retrospective Observational Analysis of Veterans Affairs Administrative Data.

Telehealth implementation can be challenging for persons with serious mental illness (SMI), which may impact their quality of care and health outcomes. The literature on telehealth's impacts on SMI care outcomes is mixed, necessitating further investigation. We examined the impacts of facility-level telehealth adoption on quality of care metrics over time among patients with SMI. We analyzed Veterans Affairs (VA) administrative data across 138 facilities from January 2021 to December 2022. We performed longitudinal mixed-effects regressions to identify the relationships between the proportion of facility-level telehealth visits and SMI specialty care quality metrics: engagement with primary care; access and continuity of care across a range of mental health services including psychotherapy or psychosocial rehabilitation, SMI-specific intensive outpatient programs, and intensive case management; and continuity of mental health care after a high-risk event (eg, suicide attempt). Facilities with a higher proportion of telehealth visits had reduced access and continuity of physical and mental health care for patients with SMI (P<.05). Higher telehealth adoption was associated with reduced primary care engagement (z=-4.04; P<.001), reduced access to and continuity in SMI-specific intensive case management (z=-4.49; P<.001; z=-3.15; P<.002), reductions in the continuity of care within psychotherapy and psychosocial rehabilitation (z=-3.74; P<.001), and continuity of care after a high-risk event (z=-2.46; P<.01). Telehealth uptake initially increased access to intensive outpatient but did not improve its continuity over time (z=-4.47; P<.001). Except for continuity within SMI-specific intensive case management (z=2.62; P<.009), continuity did not improve over time as telehealth became routinized. Although telehealth helped preserve health care access during the pandemic, telehealth may have tradeoffs with regard to quality of care for some individuals with SMI. These data suggest that engagement strategies used by SMI-specific intensive case management may have preserved quality and could benefit other settings. Strategies that enhance telehealth implementation-selected through a health equity lens-may improve quality of care among patients with SMI.

Developing and validating an abortion care quality metric for facility and out-of-facility settings: an observational cohort study in Bangladesh, Ethiopia, and Nigeria

Despite progress in assuring provision of safe abortion, substantial disparities remain in quality of abortion care around the world. However, no consistent, valid, reliable method exists to routinely measure quality in abortion care across facility and out-of-facility settings, impeding learning and improvement. To address this need, the Abortion Service Quality Initiative developed the first global standard for measuring quality of abortion care in low-income and middle-income countries. This prospective cohort study was conducted in Bangladesh, Ethiopia, and Nigeria in 2020-2022. Participants included sites and providers offering abortion care, including health facilities, pharmacies, proprietary and patent medicine vendors (PPMVs), and hotlines, and clients aged 15-49 receiving abortion care from a selected site. 111 structure and process indicators were tested, which originated from a review of existing abortion quality indicators and from qualitative research to develop additional client-centred quality indicators. The indicators were tested against 12 clinical and client experience outcomes at the site-level (such as abortion-related deaths) and client-level (such as whether the client would recommend the service to a friend) that were expected to result from the abortion quality indicators. Indicators were selected for the final metric based on predictive validity assessed using Bayesian models to test associations between indicators and outcomes, content validity, and performance. We included 1915 abortion clients recruited from 131 sites offering abortion care across the three countries. Among the 111 indicators tested, 44 were associated with outcomes in Bayesian analyses and an additional 8 were recommended for inclusion by the study's Resource Group for face validity. These 52 indicators were evaluated on content validity, predictive validity, and performance, and 29 validated indicators were included in the final abortion care quality metric. The 29 validated indicators were feasibility tested among 53 clients and 24 providers from 9 facility sites in Ethiopia and 57 clients and 6 PPMVs from 9 PPMV sites in Nigeria. The median time required to complete each survey instrument indicated feasibility: 10min to complete the client exit survey, 16min to complete the provider survey, and 11min to complete the site checklist. Overall, the indicators performed well. However, all providers in the feasibility test failed two indicators of provider knowledge to competently complete the abortion procedure, and these indicators were subsequently revised to improve performance. This study provides 29 validated abortion care quality indicators to assess quality in facility, pharmacy, and hotline settings in low-income and middle-income countries. Future research should validate the Abortion Care Quality (ACQ) Tool in additional abortion care settings, such as telemedicine, online medication abortion (MA) sellers, and traditional abortion providers, and in other geographical and legal settings. The David and Lucile Packard Foundation and the Children's Investment Fund Foundation.

Abstract 12695: An Atrial Fibrillation Treatment Pathway in the Emergency Department Reduces 30-day Cost of Care

Introduction: The annual cost of care for Atrial Fibrillation (AF) is estimated at $6.65 billion, with nearly 75% attributed to costs of hospitalizations. An AF treatment pathway with expedited follow-up to an AF-specialized clinic has been shown to reduce unnecessary admissions for AF and improve AF quality of care metrics. Goal: Evaluate differences in 30-day cost of care and discharge rate for adults presenting with AF to the emergency department (ED) before and after implementation of an AF treatment pathway. Methods: An AF treatment pathway with expedited follow-up to AF-specialized clinic was implemented at seven hospitals in North Carolina between 2017 to 2020. 30-day cost of care was calculated for patients presenting to ED with primary or secondary diagnosis of AF from 2016 to 2020 (N=12,543) by summing inflation-adjusted charges for initial hospital encounter, outpatient follow-up visits, and repeat hospital encounters for AF within 30 days. An adjusted quintile regression analysis and poisson regression, both with covariables of age, sex, race, CHA2DS2-VASc score and hospital site, were used to compare median 30 day cost of care and rates of ED discharge respectively. Results: Following implementation of the AF treatment pathway, the unadjusted median 30-day cost of care (Pre: $11,351, Post: $8,206), median initial hospital charge (Pre: $10,825, Post: $7,760), median repeat hospital encounter charge for those with repeat presentations within 30 days (Pre: $12,532, Post: $9,470) were all significantly lower (p&lt;0.001). The adjusted median 30-day cost of care was lower (-$1532; 95% CI: $ -2001, $ -1064) and the predicted probability of discharge was greater (Pre: 61.7%, 95% CI: 60.2%, 63,2%; Post: 71.6%, 95% CI: 70.7%, 72.6%) following implementation of AF treatment pathway. Conclusions: Implementation of an AF treatment pathway in the ED is associated with an increase in ED discharge rate and decrease in 30 day costs of care.

Access to Care and Healthcare Quality Metrics for Patients with Advanced Genitourinary Cancers in Urban versus Rural Areas.

Compared to the urban population, patients in rural areas face healthcare disparities and experience inferior healthcare-related outcomes. To compare the healthcare quality metrics and outcomes between patients with advanced genitourinary cancers from rural versus urban areas treated at a tertiary cancer hospital, in this retrospective study, eligible patients with advanced genitourinary cancers were treated at Huntsman Cancer Institute, an NCI-Designated Comprehensive Cancer Center in Utah. Rural-urban commuting area codes were used to classify the patients' residences as being in urban (1-3) or rural (4-10) areas. The straight line distances of the patients' residences from the cancer center were also calculated and included in the analysis. The median household income data were obtained and calculated from "The Michigan Population Studies Center", based on individual zip codes. In this study, 2312 patients were screened, and 1025 eligible patients were included for further analysis (metastatic prostate cancer (n = 679), metastatic bladder cancer (n = 184), and metastatic renal cell carcinoma (n = 162). Most patients (83.9%) came from urban areas, while the remainder were from rural areas. Both groups had comparable demographic profiles and tumor characteristics at baseline. The annual median household income of urban patients was $8604 higher than that of rural patients (p < 0.001). There were fewer urban patients with Medicare (44.9% vs. 50.9%) and more urban patients with private insurance (40.4% vs. 35.1%). There was no difference between the urban and rural patients regarding receiving systemic therapies, enrollment in clinical trials, or tumor genomic profiling. The overall survival rate was not significantly different between the two populations in metastatic prostate, bladder, and kidney cancer, respectively. As available in a tertiary cancer hospital, access to care can mitigate the difference in the quality of healthcare and clinical outcomes in urban versus rural patients.

Improving Health Care Quality Measurement to Combat Clinician Burnout

This Viewpoint explores a critical source of administrative burden and physician frustration—the explosive growth of health care quality metrics—and how improving these metrics could combat clinician burnout.

Differences in Use of Clinical Decision Support Tools and Implementation of Aspirin, Blood Pressure Control, Cholesterol Management, and Smoking Cessation Quality Metrics in Small Practices by Race and Sex

Practice-level evidence is needed to clarify the value of population-based clinical decision support (CDS) tools in reducing racial and sex disparities in cardiovascular care. To evaluate the association between CDS tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices. This cross-sectional study used practice-level data from the Agency for Healthcare Research and Quality-funded EvidenceNOW initiative. The national initiative from May 1, 2015, to April 30, 2021, spanned 12 US states and focused on improving cardiovascular preventive care by providing quality improvement support to smaller primary care practices. A total of 576 primary care practices in EvidenceNOW submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex. Practice-level estimates of disparities between Black and White patients and between male and female patients were calculated as the difference in proportions of eligible patients within each practice meeting ABCS care quality metrics. The association between CDS tools (EHR prompts, standing orders, and clinical registries) and disparities was evaluated by multiply imputed multivariable models for each CDS tool, adjusted for practice rurality, ownership, and size. Across the 576 practices included in the analysis, 219 (38.0%) had patient panels that were more than half White and 327 (56.8%) had panels that were more than half women. The proportion of White compared with Black patients meeting metrics for blood pressure (difference, 5.16% [95% CI, 4.29%-6.02%]; P < .001) and cholesterol management (difference, 1.49% [95% CI, 0.04%-2.93%] P = .04) was higher; the proportion of men meeting metrics for aspirin use (difference, 4.36% [95% CI, 3.34%-5.38%]; P < .001) and cholesterol management (difference, 3.88% [95% CI, 3.14%-4.63%]; P < .001) was higher compared with women. Conversely, the proportion of women meeting practice blood pressure control (difference, -1.80% [95% CI, -2.32% to -1.28%]; P < .001) and smoking cessation counseling (difference, -1.67% [95% CI, -2.38% to -0.95%]; P < .001) metrics was higher compared with men. Use of CDS tools was not associated with differences in race or sex disparities except for the smoking metric. Practices using CDS tools showed a higher proportion of men meeting the smoking counseling metric than women (coefficient, 3.82 [95% CI, 0.95-6.68]; P = .009). The findings of this cross-sectional study suggest that practices using CDS tools had small disparities that were not statistically significant, but CDS tools were not associated with reductions in disparities. More research is needed on effective practice-level interventions to mitigate disparities.

Impact of Telemedicine Modality on Quality Metrics in Diverse Settings: Implementation Science-Informed Retrospective Cohort Study.

Video-based telemedicine (vs audio only) is less frequently used in diverse, low socioeconomic status settings. Few prior studies have evaluated the impact of telemedicine modality (ie, video vs audio-only visits) on clinical quality metrics. The aim of this study was to assess telemedicine uptake and impact of visit modality (in-person vs video and phone visits) on primary care quality metrics in diverse, low socioeconomic status settings through an implementation science lens. Informed by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, we evaluated telemedicine uptake, assessed targeted primary care quality metrics by visit modality, and described provider-level qualitative feedback on barriers and facilitators to telemedicine implementation. We found marginally better quality metrics (ie, blood pressure and depression screening) for in-person care versus video and phone visits; de-adoption of telemedicine was marked within 2 years in our population. Following the widespread implementation of telemedicine during the COVID-19 pandemic, the impact of visit modality on quality outcomes, provider and patient preferences, as well as technological barriers in historically marginalized settings should be considered.

The Volume and Cost of Quality Metric Reporting

US hospitals report data on many health care quality metrics to government and independent health care rating organizations, but the annual cost to acute care hospitals of measuring and reporting quality metric data, independent of resources spent on quality interventions, is not well known. To evaluate externally reported inpatient quality metrics for adult patients and estimate the cost of data collection and reporting, independent of quality-improvement efforts. Retrospective time-driven activity-based costing study at the Johns Hopkins Hospital (Baltimore, Maryland) with hospital personnel involved in quality metric reporting processes interviewed between January 1, 2019, and June 30, 2019, about quality reporting activities in the 2018 calendar year. Outcomes included the number of metrics, annual person-hours per metric type, and annual personnel cost per metric type. A total of 162 unique metrics were identified, of which 96 (59.3%) were claims-based, 107 (66.0%) were outcome metrics, and 101 (62.3%) were related to patient safety. Preparing and reporting data for these metrics required an estimated 108 478 person-hours, with an estimated personnel cost of $5 038 218.28 (2022 USD) plus an additional $602 730.66 in vendor fees. Claims-based (96 metrics; $37 553.58 per metric per year) and chart-abstracted (26 metrics; $33 871.30 per metric per year) metrics used the most resources per metric, while electronic metrics consumed far less (4 metrics; $1901.58 per metric per year). Significant resources are expended exclusively for quality reporting, and some methods of quality assessment are far more expensive than others. Claims-based metrics were unexpectedly found to be the most resource intensive of all metric types. Policy makers should consider reducing the number of metrics and shifting to electronic metrics, when possible, to optimize resources spent in the overall pursuit of higher quality.

Health care resource utilization, quality metrics, and costs of bladder cancer within the Oncology Care Model.

New and emerging therapies have significantly changed the bladder cancer (BC) treatment landscape and can potentially affect spending and patient care in CMS' Oncology Care Model (OCM), a service delivery and payment model for voluntarily participating practices. The objectives of this analysis were to estimate health care resource utilization (HCRU) and benchmark spending per OCM episode of BC, and to model spending drivers and quality metrics. Retrospective cohort study. A retrospective cohort study was conducted of OCM episodes triggered by receipt of anticancer therapy among Medicare beneficiaries from 2016 to 2018. Based on this, an average performance estimation was conducted to assess the impact of hypothetical changes in novel therapy use by OCM practices. BC accounted for approximately 3% (n = 60,099) of identified OCM episodes. Relative to low-risk episodes, high-risk episodes were associated with greater HCRU and worse OCM quality metrics. Mean spending per high-risk episode was $37,857 (low-risk episode: $9204), with $11,051 spent on systemic therapies and $7158 on inpatient services. In the estimation, high- and low-risk BC exceeded the spending target by 1.7% and 9.4%, respectively. This did not affect payments to practices and no retrospective payments were necessary. As 3% of OCM episodes were attributed to BC, with only one-third classified as high-risk, controlling expenditure on novel therapies for advanced BC is unlikely to affect overall practice performance. The average performance estimation further emphasized the minimal impact that novel therapy spending in high-risk BC has on OCM payments to practices.

Geographical Disparities in Esophageal Cancer Incidence and Mortality in the United States.

Our previous research on neuroendocrine and gastric cancers has shown that patients living in rural areas have worse outcomes than urban patients. This study aimed to investigate the geographic and sociodemographic disparities in esophageal cancer patients. We conducted a retrospective study on esophageal cancer patients between 1975 and 2016 using the Surveillance, Epidemiology, and End Results database. Both univariate and multivariable analyses were performed to evaluate overall survival (OS) and disease-specific survival (DSS) between patients residing in rural (RA) and urban (MA) areas. Further, we used the National Cancer Database to understand differences in various quality of care metrics based on residence. N = 49,421 (RA [12%]; MA [88%]). The incidence and mortality rates were consistently higher during the study period in RA. Patients living in RA were more commonly males (p < 0.001), Caucasian (p < 0.001), and had adenocarcinoma (p < 0.001). Multivariable analysis showed that RA had worse OS (HR = 1.08; p < 0.01) and DSS (HR = 1.07; p < 0.01). Quality of care was similar, except RA patients were more likely to be treated at a community hospital (p < 0.001). Our study identified geographic disparities in esophageal cancer incidence and outcomes despite the similar quality of care. Future research is needed to understand and attenuate such disparities.

Access to care and health care quality metrics in urban versus rural patients (pts) with advanced prostate cancer (aPC).

37 Background: Compared to the urban population, pts in rural areas face healthcare disparities and experience inferior healthcare-related outcomes. Herein we aimed to compare the health care quality metrics and outcomes between pts with aPC from rural versus urban areas treated at a tertiary cancer hospital. Methods: In this IRB approved retrospective study, eligibility criteria were: presence of aPC, treatment at a single center (NCI-Designated Comprehensive Cancer Center (NCI-CCC), between 10/2017 to 9/2021). Rural-urban commuting area (RUCA) codes from the 2010 census /were used to classify the pts’ residences as urban (1-3) or rural (4-10) areas. The straight-line to distance of the pts’ place of residence from our institute was also calculated and included in the analysis. The median household income data were obtained and calculated from “The Michigan Population Studies Center”, based on individual zip codes. Results: A total of 994 pts were eligible and included (83.9% urban vs 16.1% rural). The baseline demographic profile and tumor characteristics were similar between the two groups. The median household income of pts from urban areas was higher by $8604/annum than that from rural areas (p&lt;0.0001). There was no difference between urban versus rural pts in terms of receipt of lines of systemic therapies, clinical trial accrual, and receipt of tumor genomic profiling. No significant difference was found in the median overall survival between the two population (83.7 versus 92.8 months; p=0.14). Conclusions: These hypothesis generating data show that access to quality care, as available in an NCI-CCC can mitigate the disparities in the quality of health care delivery and clinical outcomes in urban versus rural pts with aPC. [Table: see text]