Cancer Care Sites Research Articles

Closing the distance gap: Evaluating patient travel distances in a community oncology practice.

157 Background: Patient travel distance is an important factor influencing healthcare access, health equity and outcomes. The Rural-Urban Commuting Area (RUCA) classification system categorizes geographic areas based on urbanization and commuting patterns to measure accessibility to healthcare. We study the relationship between RUCA and patient travel distance for a multi-site community-based, medical oncology practice in north-west Chicagoland area. Methods: Using patient ZIP code data and practice locations (clinics) from April 2023 to March 2024, we calculated and compared the straight-line, one-way, patient-clinic travel distance (travel distance) for about 20,000 patients at 5 clinics, using geospatial analysis techniques. We grouped clinics based on location and population characteristics, applied the RUCA classification to patient ZIP codes, and compared travel distances by RUCA categories. Results: The median travel distance for patients was 5.0 miles, with 82% of patients traveling 10 miles or less, and 89% traveling 15 miles or less. Table 1 shows % of patients traveling and travel distance by RUCA categories. Median travel distances for urban metro, suburban metro, and suburban small-town clinics were 4.8mi, 10.8mi and 20.6mi (Kruskal Wallis H-test, p <0.001). Within 50 miles of each clinic, median travel distance for patients from urban ZIP codes (4.8 mi) was lower compared to metropolitan, micropolitan, small town and all other RUCA categories. Conclusions: Preliminary findings indicate a significant association between RUCA and travel distance, with longer travel distances for patients in non-urban locales. Proximity of cancer care sites to the patient’s home reduces distance traveled, minimizing the burden on the patients and their families. Interventions addressing transportation needs (such as improving infrastructure, increasing transportation options, subsidizing healthcare travel, etc.) can be augmented with efforts to strengthen access to community-based sites (expansion of telehealth, incentivizing providers serving non-urban areas, etc.) to reduce patient and caregiver burden. Clinic Site Category % of patients traveling <5 mi <10mi <15mi <50mi >50mi A Suburban Metro 53.8% 30.7% 5.2% 9.1% 0.9% B Suburban Small Town 24.1% 40.6% 21.9% 12.3% 0.4% C Suburban Metro 45.7% 34.3% 5.01% 13.8% 1.0% D Suburban Metro 60.1% 23.9% 6.8% 7.9% 1.2% E Urban Metro 80.3% 9.7% 3.5% 5.2% 1.0% ALL SITES 54.7% 27.1% 7.2% 9.8% 0.9% Clinic Median travel distance in miles (% of patients) by patient RUCA within 50 miles of clinics Urban Metropolitan – High Commute Micropolitan – Flow to Large Urban Cluster Small Town – Flow to Small Urban Cluster All Other A 4.8 (98.2%) 27.5 (1.7%) 48.7 49.4 B 4.0 (42.3%) 8.6 (54.2%) 25.0 20.6 (3.2%) C 5.9 (95.2%) 17.7 (4.5%) 36.7 27.7 D 4.8 (97.1%) 23.7 (2.8%) 48.4 40.1 E 2.7 (98.9%) 32.3 (1.0%) 4.5 ALL 4.8 (91.2%) 10.8 (8.3%) 36.7 (0.1%) 20.6 (0.4%) 4.5

Implementation of social needs screening for minoritized patients newly diagnosed with breast cancer: a mixed methods evaluation in a pragmatic patient navigation trial

BackgroundSocial needs inhibit receipt of timely medical care. Social needs screening is a vital part of comprehensive cancer care, and patient navigators are well-positioned to screen for and address social needs. This mixed methods project describes social needs screening implementation in a prospective pragmatic patient navigation intervention trial for minoritized women newly diagnosed with breast cancer.MethodsTranslating Research Into Practice (TRIP) was conducted at five cancer care sites in Boston, MA from 2018 to 2022. The patient navigation intervention protocol included completion of a social needs screening survey covering 9 domains (e.g., food, transportation) within 90 days of intake. We estimated the proportion of patients who received a social needs screening within 90 days of navigation intake. A multivariable log binomial regression model estimated the adjusted rate ratios (aRR) and 95% confidence intervals (CI) of patient socio-demographic characteristics and screening delivery. Key informant interviews with navigators (n = 8) and patients (n = 21) assessed screening acceptability and factors that facilitate and impede implementation. Using a convergent, parallel mixed methods approach, findings from each data source were integrated to interpret study results.ResultsPatients’ (n = 588) mean age was 59 (SD = 13); 45% were non-Hispanic Black and 27% were Hispanic. Sixty-nine percent of patients in the navigators’ caseloads received social needs screening. Patients of non-Hispanic Black race/ethnicity (aRR = 1.25; 95% CI = 1.06–1.48) and those with Medicare insurance (aRR = 1.13; 95% CI = 1.04–1.23) were more likely to be screened. Screening was universally acceptable to navigators and generally acceptable to patients. Systems-based supports for improving implementation were identified.ConclusionsSocial needs screening was acceptable, yet with modest implementation. Continued systems-based efforts to integrate social needs screening in medical care are needed.

Implementing DPYD/UGT1A1testing to prevent treatment related adverse events (TRAE) in patients with gastrointestinal (GI) cancer: Results of a pragmatic implementation trial.

10599 Background: Fluoropyrimidines (FP), 5-FU and capecitabine, are standard treatments for many GI cancers. Irinotecan may be used with FPs in both the curative and palliative settings. 30-40% of patients experience severe TRAEs which can lead to treatment interruption and hospitalization. TRAE risk is higher in patients with pharmacogenetic variants in DPYD and/or UGT1A1. Methods: This is a non-randomized, open-label implementation study at 3 cancer care sites within an academic health system to determine feasibility of integrating DPYD/UGT1A1 testing into clinical care (IMPACT-GI; NCT#04736472). Test ordering and discrete variant resulting were available within the Electronic Health Record. The lab detected 5 DPYD variants with reduced or no function (c.1905+1G>A, c.2846A>T, c.1679T>G, c.1236G>A, c.557A>G) and 2 UGT1A1 (*6, *28) alleles. Patients with a GI cancer initiating treatment with 5-FU, capecitabine, or irinotecan underwent testing along with preemptive chemotherapy dose modifications. Carriers of 1 DPYD variant (i.e., intermediate metabolizers [IM]) and UGT1A1 homozygous carriers (i.e., poor metabolizers [PM]) were recommended a 50% and 30% dose reduction, respectively. The primary endpoints were feasibility (proportion of results available prior to cycle 1) and fidelity (genotype concordant dose modifications). Secondary endpoints included severe TRAE (requiring emergency room visit or hospitalization) comparing variant carriers vs. wildtype over the first 6 cycles. Results: From 3/2021- 12/2022, 224 patients received testing (54% male, 74% White, 18% Black, mean age 62 ±17 years. The most common diagnoses were 47% colorectal and 30% pancreatic cancers. The median lab turnaround time was 10 (IQR 9-13) calendar days with 57.2% of results available prior to cycle 1. Results available prior to cycle 1 varied by distance to lab (64.7% near sites vs. 32.7% far site, p<0.001). We identified 7 (3%) DPYD intermediate metabolizers (IM) and 33 (15%) UGT1A1 poor metabolizers (PM). Four (2%) patients carried a variant in both DPYD and UGT1A1. Chemotherapies were preemptively dose reduced for 6 of 7 DPYD carriers receiving FP and 5 of 8 UGT1A1 PMs receiving irinotecan. 2 (28%) DPYD carriers vs. 71 (33%) wildtype carriers had a severe TRAE. 4 (50%) UGT1A1 PMs vs. 11 (36%) UGT1A1 wildtype carriers experienced a severe TRAE. Conclusions: DPYD/UGT1A1 testing is feasible with oncology providers following the genotype guided dose reductions when results were available prior to cycle 1. Pretreatment DPYD/UGT1A1 testing in conjunction with preemptive dose reductions resulted a similar proportion of severe TRAE as compared with wild-type patients. Further workflow modifications are required to decrease test turnaround time to ensure results are available prior to chemotherapy initiation. Clinical trial information: NCT04736472 .

Expansion of an advance care planning initiative in patients with metastatic cancer: Successes and challenges.

197 Background: Advance Care Planning (ACP) activities including dialogs about care preferences, patient goals, and advance directives are an important component of cancer care. A pilot ACP initiative has been expanded to include additional sites of cancer care within the Cedars-Sinai Cancer Health System. Methods: The pilot study including two cancer care sites (started July 2017) was expanded to include two additional sites. The prior results were presented to 86 oncologists at all four cancer care sites to promote increased ACP activities for patients with metastatic cancer and/or refer those patients to palliative medicine (PM). ACP activities were defined as one of the following within the last year: 1) an advance directive (AD) or physician’s order for life sustaining therapy (POLST), 2) an ACP note and/or 3) a PM referral. Patients with metastatic cancer were identified by an EMR M1 designation by the oncologist from July 2021 to March 2022. Oncologists received monthly lists of patients with metastatic disease lacking ACP activities and quarterly scorecards with their ACP completion rate compared to their peers. Results: An average of 1302 unique patients with metastatic cancer were identified each month combined from all four sites. System wide ACP activities were unchanged from a baseline 51% in July 2021 to 53% in March 2022. One site representing, an average of 101 patients/month, increased ACP activities from 16% to 65%. Conclusions: This initiative increased ACP activities since July 2021 for patients with metastatic cancer at one of four sites. The remaining three sites, two of which were part of the pilot from 2017, showed a plateauing of ACP activities despite embedded PM providers, ACP education and monthly feedback to the providers. This may have been from a higher baseline and longer PM presence at those sites. The site showing improvement was given economic incentives to meet Cedars-Sinai priorities for ACP activities and started at a lower baseline, both of which may have contributed to the increase. Further improvement in ACP activities may occur with involvement of clinic reception, nursing and social work along with more broad economic incentive for ACP activities. This increase was primarily from ACP note completion of 53% (PM 18% and AD completion 10%).[Table: see text]

Advance Care Planning in Patients With Metastatic Cancer: A Quality Improvement Initiative.

An initiative aimed to increase the rate of advance care planning (ACP) activities for outpatients with metastatic cancer, an essential step to achieving goal concordant care. Patients with metastatic cancer were identified by International Classification of Diseases-10 coding and later by oncologists' electronic health record documentation of metastatic tumor status. ACP activities were defined as either an ACP note, Advance Directive, Physician Orders for Life-Sustaining Therapy (POLST), or a Palliative Medicine (PM) consultation within the prior year. From 2017 to 2020, the initiative screened more than 5,000 total unique cancer patients per year. PM consultants were embedded in tumor boards, oncology care team meetings, and shared oncology clinic space. Quarterly reports were sent to 60 oncologists at three cancer care sites with data of their percentage of ACP activities for patients with metastatic cancer compared with their peers. Oncologists' identities were initially blinded, but later unblinded. Oncologists also received a monthly list of patients with metastatic cancer without ACP activities. The rate of ACP activities for patients with metastatic cancer increased from a baseline of 37% in July 2017 to 57% by the end of 2020. PM consultations increased from 12% to 39% and ACP notes increased from 16% to 29% during the same interval. There was no change in Advance Directive (17%-20%) or POLST completion (7%-6%). ACP activities are an essential step to achieve goal concordant care, and this initiative successfully increased ACP activities for patients with metastatic cancer. However, given that the main source of increased ACP activities during this initiative was PM referrals, further progress will depend upon strengthening the oncology care teams' ACP skills and motivation for completion.

Beyond efficacy: a qualitative organizational perspective on key implementation science constructs important to physical activity intervention translation to rural community cancer care sites.

To identify constructs relevant to implementation of evidence-based physical activity (PA) behavior change interventions for rural women cancer survivors from an organizational perspective. During the development of a PA intervention implementation toolkit, 11 potential interventionists and 19 community and organizational stakeholders completed focus groups stratified by role. Narratives were audio recorded, transcribed, and coded for Consolidated Framework for Implementation Research (CFIR) constructs. Multiple CFIR constructs were identified: Implementation Process (i.e., Engaging, Reflecting and Evaluating), Intervention Characteristics (i.e., Design Quality and Packaging, Cost, Evidence Strength and Quality, Adaptability, Complexity), Inner Setting (i.e., Implementation Readiness, Implementation Climate, Structural Characteristics), Outer Setting (i.e., Patient Needs and Resources, Cosmopolitanism), and Characteristics of Individuals (i.e., Knowledge and Beliefs, Stage of Change). Narratives identified rural implementation barriers (e.g., transportation) and facilitators (e.g., community-oriented). Unique needs of the cancer survivor (e.g., coping during cancer treatment and long-term effects on physical abilities) were emphasized as important barriers potentially addressed through Adaptability and Readiness implementation strategies. Narratives identified multi-level (i.e., individual-, organizational-, and community-level) strategies for targeting the identified constructs. Fourteen CFIR constructs emerged as potentially important for organizations to consider when implementing PA interventions. Constructs were integrated into our implementation toolkit and research testing their potential mechanisms of action when implementing PA interventions in rural settings is warranted. Strategies that target the identified constructs may enhance the implementation of PA programs for rural cancer survivors. Cancer survivors can facilitate these efforts by partnering with their health care providers and community organizations. Organizations promoting physical activity programs for cancer survivors must overcome implementation barriers including but not limited to cost, necessary expertise, and lack of awareness. Cancer survivors can facilitate these efforts by partnering with their health care providers, cancer center, and local community organizations to raise awareness and champion these efforts. It will "take a village", with cancer survivors being their own best advocate, to bring physical activity promotion to a broad range of cancer survivors.

Impact of Travel Time on Health Care Costs and Resource Use by Phase of Care for Older Patients With Cancer

Many community cancer clinics closed between 2008 and 2016, with additional closings potentially expected. Limited data exist on the impact of travel time on health care costs and resource use. This retrospective cohort study (2012 to 2015) evaluated travel time to cancer care site for Medicare beneficiaries age 65 years or older in the southeastern United States. The primary outcome was Medicare spending by phase of care (ie, initial, survivorship, end of life). Secondary outcomes included patient cost responsibility and resource use measured by hospitalization rates, intensive care unit admissions, and chemotherapy-related hospitalization rates. Hierarchical linear models with patients clustered within cancer care site (CCS) were used to determine the effects of travel time on average monthly phase-specific Medicare spending and patient cost responsibility. Median travel time was 32 (interquartile range, 18-59) minutes for the 23,382 included Medicare beneficiaries, with 24% of patients traveling longer than 1 hour to their CCS. During the initial phase of care, Medicare spending was 14% higher and patient cost responsibility was 10% higher for patients traveling longer than 1 hour than those traveling 30 minutes or less. Hospitalization rates were 4% to 13% higher for patients traveling longer than 1 hour versus 30 minutes or less in the initial (61 v 54), survivorship (27 v 26), and end-of-life (310 v 286) phases of care (all P < .05). Most patients traveling longer than 1 hour were hospitalized at a local hospital rather than at their CCS, whereas the converse was true for patients traveling 30 minutes or less. As health care locations close, patients living farther from treatment sites may experience more limited access to care, and health care spending could increase for patients and Medicare.

Impact of travel time on healthcare costs and resource utilization by phase of care for older cancer patients.

6560 Background: Closures of hospitals and clinics may have unintended consequences, including increasing patient travel time. Increased patient travel time to healthcare facilities has the potential to adversely impact patient outcomes. Limited data exist on the impact of travel time on healthcare costs and resource utilization. Methods: This retrospective cohort study from 2012-2015 evaluated drive time to cancer care site for Medicare beneficiaries age ≥ 65 in the Southeastern US. The primary outcome was Medicare spending by phase of care (initial, survivorship, end of life [EOL]). Secondary outcomes included resource utilization measured by hospitalization rates, hospitalization sites, intensive care unit (ICU) admissions, and chemotherapy-related hospitalization rates. Hierarchical linear models with patients clustered within cancer care site and adjusted for pertinent covariates were used to determine the effects of drive time on average monthly phase-specific Medicare spending. Results: Median drive time was 32 minutes (IQR 18-59) for the 23,382 included Medicare beneficiaries, with 24% of patients driving &gt; 1 hour to their cancer care site. During the initial phase of care, Medicare spending was 14% higher for patients traveling &gt; 1 hour than those traveling ≤ 30 minutes.Hospitalizationrates were 4-13% higher for patients traveling &gt; 1 hour vs. ≤ 30 minutes in the initial (61 vs. 54), survivorship (27 vs. 26), and EOL (310 vs. 86) phases of care (all p &lt; .05). The majority of patients traveling &gt; 1 hour were hospitalized at a local hospital rather than at their cancer care site, whereas the converse was true for patients traveling ≤ 30 minutes. Conclusions: As healthcare locations close, patients living farther from treatment sites may experience more limited access to care, and healthcare spending could increase for Medicare.

Impact of travel time on hospitalizations and patient cost responsibility by phase of care for older patients with cancer.

37 Background: Healthcare reimbursement changes are contributing to increased closures of community hospitals and oncology practices, which may lead cancer patients to travel greater distances for care. Limited data exists on the impact of travel time on hospitalization rates and patient cost responsibility by phase of care for older cancer patients. Methods: This was a secondary analysis of Medicare claims from 2012-2015 for cancer patients age ≥65 receiving care in the University of Alabama at Birmingham Cancer Community Network. Patient addresses were obtained from network data, hospitalizations from inpatient claims, and patient cost responsibility from inpatient, outpatient, skilled nursing facility, carrier, and durable medical equipment claims. Drive time was calculated from patient home to cancer care site (CCS). Phase of care-specific (initial, survivorship, end-of-life [EOL]) rates of hospitalizations overall and by CCS vs. other care site (OCS) were calculated per 100 person-years. Hierarchical linear models compared average monthly phase-specific costs by drive time to CCS. Results: Of 23,605 older cancer patients, median drive time to CCS was 32 minutes (IQR 18-59), with 24% driving ≥1 hour to CCS. Rates of hospitalizations by initial (n = 14,225), survivorship (n = 18,805), and EOL (n = 8,211) phases of care were 54, 26, and 301 per 100 person-years, respectively. Higher rates of hospitalizations at OCS vs. CCS were shown for patients traveling ≥1 hour to CCS (initial, survivorship, and EOL rate of 41 vs. 20, 21 vs. 6, and 220 vs. 95 per 100 person-years, respectively). Median monthly costs by phase were $401 (IQR $182-$814) for initial, $369 (IQR $123-$1046) for survivorship, and $2075 (IQR $1123-$3723) for EOL. Patients traveling ≥1 hour to their CCS had higher cost responsibility, with patients in initial, survivorship, and EOL phases having $303 (95% CI $130-$476), $75 (95% CI $46-$105), and $736 (95% CI $308-$1164) higher average costs per month than those traveling &lt; 1 hour, respectively. Conclusions: Cancer patients traveling further to receive care are potentially vulnerable to higher cost responsibility and limited access to care if community hospitals close, especially at EOL.

Impact of the 340B Drug Pricing Program on Cancer Care Site and Spending in Medicare.

To examine the impact of the 340B drug discount program on the site of cancer drug administration and cancer care spending in Medicare. 2010-2013 Medicare claims data for a random sample of Medicare Fee-for-Service beneficiaries with cancer. We identified the 340B effect using variation in the availability of 340B hospitals across markets. We considered beneficiaries from markets that newly gained a 340B hospital during the study period (new 340B markets) as the treatment group. Beneficiaries in markets with no 340B hospital were the control group. We used a difference-in-differences approach with market fixed effects. Secondary data analysis. The probability of a patient receiving cancer drug administration in hospital outpatient departments (HOPDs) versus physician offices increased 7.8 percentage points more in new 340B markets than in markets with no 340B hospital. Per-patient spending on other cancer care increased $1,162 more in new 340B markets than in markets with no 340B hospital. The 340B program shifted the site of cancer drug administration to HOPDs and increased spending on other cancer care. As the program expands, continuing assessment of its impact on service utilization and spending would be needed.

Abstract A28: Closing the disparity gap: Attributes of patients referred to a community cancer program

Abstract Background: Evidence suggests that the experience of cancer differs across racial and ethnic underserved populations. We describe the referral patterns and clinical characteristics of patients receiving care at Dana-Farber Cancer Institute's clinical outreach community cancer program, an initiative established to improve access to quality cancer care across the spectrum of the disease for medically underserved patients. Methods: Two hundred and twenty five patients, receiving care at our community cancer care site, based within a Federally Qualified Health Center in Boston, were consented to research and enrolled between January 2012 and June 2015. The program accommodates all oncology and hematology referrals from primary care providers (PCP) at the health center. Variables of interest were collected through medical chart review and a patient intake survey that was developed for the program, and included age, gender, ethnicity, health insurance coverage, reasons for referral, presence of co-morbidity (defined by the International Classification of Disease-9th edition codes) and type of resolution attained. Due to the wide range of services provided by the program, resolution was defined as the number of days from the patient's initial appointment with an oncologist at the center until one of the following events occurred: an initial appointment with a medical specialist at the Dana-Farber Cancer Institute/Brigham and Women's Hospital (DFCI/BWH) to establish a treatment plan; establishment of a surveillance plan; or direction back to his or her PCP. Descriptive statistical analysis was performed using JMP Pro (version 11, SAS Institute Inc., Cary, NC) Results: The mean age of the study population was 52 (SD±13.9) years and 44% were men. The majority of participants (70%) were Blacks/African Americans, 15% were Hispanic Whites, 11% were non-Hispanic Whites and 1% were two or more races. Forty eight percent had Medicaid insurance, 24% had Medicare while 13% and 15% had other public and private insurance, respectively. The reasons for referral include hematologic consultation (22%), evaluation for cancer (20%), cancer genetics counseling and testing (20%), lung cancer screening/smoking cessation counseling (19%), follow up care for cancer (15%), cancer treatment (1%) and others (2%). Of the 54 participants with a cancer diagnosis, 76% were previously diagnosed elsewhere and the most common cancer sites were prostate (35%) breast (13%) and colon/rectum (11%). Hypertension (52%), diabetes (31%) and psychological disorders (22%) were the most frequent co-morbidities in participants with cancer. Surveillance plans were established for 44% of genetic counseling/ testing referrals and 86% of lung cancer screening referrals. Those requiring treatment (33%) and active surveillance (43%) plans for cancer had a median time to resolution of 17 (SD±91.1) days and 12(SD±34.5) days, respectively. Overall, treatment plans were required for 9% of participants, 55% had surveillance plans established while 34% were directed back to their PCP for continued care and only 2% of referrals were unresolved. Conclusion: Our findings highlight the wide spectrum of cancer care concerns and needs in underserved populations receiving care within the community. Interventions targeted at eliminating cancer disparities should take into account services that span the continuum of care from prevention to survivorship. Citation Format: Ruth N. Akindele, Ludmila A. Svoboda, Yolanda Martins, Rachel A. Freedman, Aymen Elfiky, Suzanne T. Berlin, Christopher S. Lathan. Closing the disparity gap: Attributes of patients referred to a community cancer program. [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr A28.

Thoughts and recommendations on cancer care site of service

Within community practice, we are faced with the dual challenge of providing health care and operating a viable business entity. This problem is not unique to oncology; however, the specialty has been unfairly burdened with preferential payment incentives that favor treatment in hospital outpatient departments (HOPDs) over independent communitybased clinics. This trend toward HOPD care has caused a shift in the model of delivery of care and remains a problem for those who practice in community clinics. Furthermore, the shift is driving spending for oncology care higher at a time when payers and patients are contending with rising, unsustainable costs. Providers in individual practices who are focused on the daily responsibilities of caring for cancer patients understandably may find it difficult to keep abreast of national policy changes and understand how those changes might affect their ability to take care of patients. The US Oncology Network and the Community Oncology Alliance (COA) are collaborating to interpret this proposed policy change and to make recommendations for improvement to empower community oncologists to comprehend the impact of this policy and to work toward a better outcome. We will present this proposed policy change in 2 parts: first, an analysis of the impact of current policies on community oncology practice, and second, recommendations for proposed changes to ensure balanced payment amounts for delivery of equivalent services and strategic initiatives for valuebased cost reduction.

Abstract A42: Optimizing health care systems recruitment and retention practices for medically underserved populations: Impact of ENACCT cancer clinical trial staff training

Abstract Cancer clinical trials (CCTs) are essential to making progress in cancer care, yet many cancer care sites within health care systems struggle with improving adult trial participation, which nationally is less than 5%, even lower among communities of color. Challenges to improving participation include patient barriers such as fear, lack of awareness and costs as well as institutional barriers (limited staff and resources, study design, provider attitudes and behaviors) that can limit patient access to trials, particularly among minority and medically underserved populations. The Education Network to Advance Cancer Clinical Trials (ENACCT) seeks to improve access to CCTs through education and collaboration with communities, health care providers, and researchers. ENACCT's Pilot Education Program (PEP), was a 3-year community-based intervention designed to enhance access, awareness and accrual to trials. Implemented in three communities nationwide, training was targeted to key stakeholders in trial participation, including CCTs staff. Using an interactive learning format, PEP training for CCT staff focused on the impact of culture and changing demographics within the clinical research setting; the relationship of cultural competency and Culturally and Linguistically Appropriate Services (CLAS) Standards to CCTs participation; and assisted CCT staff to design an action plan to adopt CLAS Standards in the conduct of research at one's own institution. Additionally, local sites addressed policy barriers to enhance access. PEP impact was evaluated using pre and post tests, follow-up assessments, as well as interview and focus group data. PEP trained 61 CCTs staff (70% nurses). Post-training, at first assessment, 94% of CCT staff indicated increased commitment to advocate for adoption of CLAS standards within their institutions and 84% indicated intention to discuss with their peers the importance of cultural competency on patient recruitment and retention. Site initiatives to address access barriers included implementation of consent short forms for limited English proficiency patients, use of Six Sigma quality improvement measures to improve hospital recruitment processes and launching city-wide symposia on CCTs reaching community leaders and health care providers. A total of 3027 website sessions and 88 unique patient profiles were created with a national CCTs matching service associated with PEP. Results from PEP suggest that training CCT staff in strategies to enhance cultural competency in the research setting may positively impact awareness and access to CCTs among medically underserved populations. Citation Information: Cancer Epidemiol Biomarkers Prev 2010;19(10 Suppl):A42.

Integrating the Healthcare Enterprise in Radiation Oncology Plug and Play—The Future of Radiation Oncology?

To describe the processes and benefits of the integrating healthcare enterprises in radiation oncology (IHE-RO). The IHE-RO process includes five basic steps. The first step is to identify common interoperability issues encountered in radiation treatment planning and the delivery process. IHE-RO committees partner with vendors to develop solutions (integration profiles) to interoperability problems. The broad application of these integration profiles across a variety of vender platforms is tested annually at the Connectathon event. Demonstration of the seamless integration and transfer of patient data to the potential users are then presented by vendors at the public demonstration event. Users can then integrate these profiles into requests for proposals and vendor contracts by institutions. Incorporation of completed integration profiles into requests for proposals can be done when purchasing new equipment. Vendors can publish IHE integration statements to document the integration profiles supported by their products. As a result, users can reference integration profiles in requests for proposals, simplifying the systems acquisition process. These IHE-RO solutions are now available in many of the commercial radiation oncology-related treatment planning, delivery, and information systems. They are also implemented at cancer care sites around the world. IHE-RO serves an important purpose for the radiation oncology community at large.

Usability and acceptance of automated home-based symptom monitoring by urban and rural cancer patients in community-based care settings in Indiana

8085 Background: Experts recommend that providers routinely and regularly ask patients about pain, depression, fatigue and other cancer-related symptoms, using brief, validated assessment tools. Current paper-based symptom assessment is costly, inefficient, and limited to the point of care. We tested the usability and acceptance by patients of an automated symptom assessment system, incorporating interactive voice response (IVR) telephone technology and the Internet, to track symptoms while patients are away from the clinic. Methods: We recruited 120 cancer patients at 7 community-based, urban and rural cancer care sites to test the system. Patients were instructed to use the system and asked to choose the day and time of day to receive scheduled calls to their home, work, or mobile phone. Patients could also call a toll-free number or log onto a secure site on the Internet to provide a self-report. The M.D. Anderson Symptom Inventory was used to measure severity and interference of 13 common cancer symptoms. After using the system, we called each participant for debriefing. Results: Participants used the system from one to 13 weeks. Over 67% of patients used the system more than 5 times. Participants averaged 10 self-reports each. Ages ranged from 28 to 87 years. Participants preferred the telephone to complete their surveys - 95 percent of surveys were done by IVR; 5 of surveys were completed on the Internet. Patient satisfaction with the system was high –8.2 on a 0 (lowest) to 10 (highest) scale; 74 percent of patients rated their satisfaction at 8 or higher. The system was easy to use for 86%; 81% found it convenient. Over 65% of patients said they would participate in automated symptom monitoring if it were offered as standard care. Conclusions: Community-based cancer patients of all ages readily accept automated symptom monitoring as part of their routine cancer care. They prefer to self-report using the telephone. Patients of all ages have little difficulty learning to use the system; they are very willing and able to provide regular, complete symptom severity self-reports. They would welcome such a system as an integral part of their standard care. No significant financial relationships to disclose.

Caregivers' descriptions of sleep changes and depressive symptoms.

To describe caregiver sleep and depression using caregiver narratives. To compare qualitative descriptions with quantitative scores. Descriptive, one-time, open-ended interview followed by structured sleep and depression questions. Interview conducted in person or via telephone at caregiver's preference. 47 caregivers of patients with advanced stage cancer. Caregivers had a mean age of 54 years, and most were female (81%), Caucasian (82%), and spouses (61%). They provided care for a mean of 24 months. Patients' diagnoses were lung cancer (36%), colorectal cancer (13%), or recurrences (51%). Two cancer care sites in southern California provided participants. After consent, the researcher conducted interviews. The Pittsburgh Sleep Quality Index (PSQI) and Center for Epidemiological Studies-Depression (CES-D) instruments were administered following interviews. Sleep pattern changes and depression levels over time as defined by caregivers. Caregivers described severe fluctuations in sleep patterns over time and how these changes affected caregiver depressive symptoms. PSQI and CES-D scores matched narrative comments. Caregivers' narratives suggest they suffer progressive sleep deprivation that affects their emotions and ability to continue as caregivers. Nurses must recognize the severe sleep problems experienced by caregivers and respond with interventions to increase sleep quality and decrease depression.