Treatment Wait Times Research Articles

Analyzing diagnostic and treatment wait times for lung cancer Patients: Key insights from a provincial registry study

BackgroundLung cancer (LC) remains the leading cause of cancer-related mortality globally, necessitating timely diagnosis and treatment to improve patient outcomes. This study aimed to evaluate the timeliness of care for LC patients at a public hospital in Almería, Spain, assess adherence to guidelines, and explore associations between timeliness and survival. MethodsA retrospective cohort study was conducted, reviewing medical records of LC patients diagnosed between 2019 and 2021. Quality indicators, adapted from prevailing guidelines, facilitated the assessment of care timeliness, with a focus on diagnostic and treatment wait times. Cox regression modeling was employed to explore survival associations, adjusting for covariates including age, performance status, stage, histology, and treatment modalities. ResultsOf 539 patients included, most (79.84 %) had initial specialist contact within 7 days, and 82.25 % received diagnosis within 30 days. However, delays were observed in treatment initiation, with surgery experiencing the longest median wait time (78 days). Survival analysis showed no significant difference between shorter and longer diagnostic (HR: 0.87, 95 % CI: 0.62–1.24) or treatment intervals (HR: 1.14, 95 % CI: 0.83–1.58). Multivariate analysis identified age, performance status, stage, histology, and treatment as prognostic factors. ConclusionThis study highlights the importance of timely diagnosis and treatment in improving lung cancer outcomes. Despite achieving diagnostic targets, treatment delays were common, particularly for surgical interventions. These findings underscore the need for enhanced coordination and efficient care pathways to minimize delays, ultimately improving survival rates and quality of life for lung cancer patients. Addressing these issues is crucial for optimizing lung cancer care delivery in the future.

Terrorism's impact on low and middle-income countries' healthcare services: A perspective.

Terrorism has emerged as an increasingly pressing global issue, giving rise to escalating casualties and devastating implications for peace and security. The low- and middle-income countries (LMICs), already grappling with inadequate healthcare services and an estimated annual mortality toll ranging from 5.7 to 8.4 million, face further setbacks as terrorism exacerbates their prevailing healthcare deficiencies. Among the aspects of how terrorism affects healthcare in LMICs are high morbidity, mortality, and treatment wait times. The four principal areas of reverberation encompass amplified vulnerabilities in healthcare systems, financial shortfalls in LMIC healthcare systems, worsened personnel shortages in healthcare, and the devastating impact on healthcare facilities. In response to these challenges, international organizations and countries have played a pivotal role in mitigating the impact of terrorism on healthcare systems. Additionally, to improve healthcare in these regions, investing in infrastructure, supporting healthcare workers, and ensuring safety are paramount. Implementing mobile health interventions, traditional medicine, and mobile laboratories may enhance healthcare accessibility. Further, employing blockchain technology for data security and supply chain management may strengthen healthcare systems in these areas.

Utilization of Proximate Healthcare Facilities and Children’s Wait Times in Senegal: An IV-Tobit Analysis

Universal health coverage (UHC) defines individuals’ timely access to healthcare services without suffering any health-related financial constraints. The Senegalese government has shown commitments towards achievement of UHC as a way of improving access by the population to quality healthcare services. This is very pertinent for promoting some indicators of under-five health in Senegal. Therefore, this study analyzed the factors influencing sick children’s utilization of the nearest healthcare facilities and their wait times in Senegal. The data were from the Service Provision Assessment (SPA) survey, which was conducted in 2018. The instrumental Tobit regression model was used for data analysis. The results showed that 63.50% and 86.01% of the children utilized health posts and publicly owned facilities, respectively. Also, 98.46% of the children utilized urban facilities. The nearest facilities were utilized by 74.55%, and 78.19% spent less than an hour in the facilities. The likelihood of using the nearest healthcare facilities significantly reduced (p < 0.05) with caregivers’ primary education, higher education, residence in some regions (Fatick, Kaokack, Saint Louis, Sediou, and Tambacounda), and use of private/NGO not-for-profit facilities, but increased with not having visited any other providers, residence in the Kaffrie region, vomiting symptoms, use of health centers, and use of health posts. Moreover, treatment wait times significantly increased (p < 0.05) with the use of nearest facilities, residence in some regions (Diourbel, Kaokack, Matam and Saint Louis), use of private for-profit facilities, use of private not-for-profit facilities, and urban residence, but decreased with secondary education, use of health centers, use of health posts, vomiting symptoms, and showing other symptoms. It was concluded that reduction in wait times and utilization of the nearest healthcare facilities are fundamental to achieving UHC in Senegal. Therefore, more efforts should be integrated at promoting regional and sectoral equities through facilitated public and private healthcare investment.

Patients' Perspectives on Attributes While Choosing Minimally Invasive Surgery for Benign Prostatic Hyperplasia Procedures: Experience from Men Undergoing Water Vapor Thermal Therapy.

Objective: To understand which attributes men with benign prostatic hyperplasia (BPH) undergoing water vapor thermal therapy (WVTT) find important while considering treatment options for the condition. Methods: Men (n = 170) with lower urinary tract symptoms due to BPH who underwent WVTT between April 2019 and November 2020 in a Toronto urologic clinic were invited to participate in an online survey. The survey included eight attributes of BPH surgical procedures and five attributes of WVTT. Patients were asked how important each attribute was to them before they selected a BPH procedure and decided to undergo WVTT. Results: In total, 128 respondents (75%) completed the survey. A majority of the respondents were White (88%), married (83%), and aged 60-69 years old (45%). Approximately 97% of respondents rated the ability to avoid further BPH treatments as "very important" or "extremely important," followed by duration to return to normal activities (79%), and wait times to receive the procedure (57%). Only 47% of patients reported that postprocedural catheterization was important. For WVTT, 98% of the respondents rated avoiding more invasive surgical treatments and 88% rated a quick recovery as important attributes. Conclusions: Among men with moderate-to-severe BPH undergoing WVTT, the most important attributes for selecting a BPH surgical procedure were avoiding further BPH treatments, returning quickly to normal activities, and reducing treatment wait times. Most men chose WVTT to avoid more invasive procedures and have a quick recovery.

Effect of socioeconomic status on wait times for patients undergoing treatment for laryngeal conditions in a universal healthcare system.

As one of the world's only fully publicly administered, universal healthcare systems, Canada intends to provide equitable access to services for all patients. Socioeconomic status (SES) can affect treatment wait times with implications on health outcomes; however, this has not been evaluated in the setting of laryngeal disease, which incorporates urgent and elective conditions, in a universal healthcare system. This study aims to identify whether SES-affected treatment wait times for laryngeal therapies in this system. A retrospective review was conducted on a cohort of patients with laryngeal disease at an academic, tertiary center who underwent laryngeal surgery over a three-year period. Data retrieved through medical records; surgical and voice therapy wait times were normalized to each practitioner's average wait time for respective diagnostic categories. Income was used to assess SES and was derived from Statistics Canada census information based on patient postal codes. Data analysis identified 578 patients (59% male). Mean wait time to surgery for all conditions was 123.5 (95% confidence interval 113.1-133.9) days. Analysis of variance analysis found no difference in wait times between different SES groups (p= .28), regardless of laryngeal disease category. Patients with cancer or airway obstruction had shorter wait times compared with benign conditions (p< .0001). SES did not affect treatment wait times for laryngeal therapies in a universal healthcare system. Wait times were shorter for oncologic and obstructive conditions compared with benign conditions, reflecting an ability to accommodate clinical needs without impacting care access at the detriment of different SES statuses. 4.

Value of Reducing Wait Times for Chimeric Antigen Receptor T-Cell Treatment: Evidence From Randomized Controlled Trial Data on Tisagenlecleucel for Diffuse Large B-Cell Lymphoma

ObjectivesThis study aimed to quantify the value of reducing chimeric antigen receptor T-cell (CAR-T) treatment wait times on patients with refractory and relapsed aggressive blood cancer who can newly gain access to treatment or access treatment earlier in their disease course. MethodsUsing data from the JULIET clinical trial, we first identified the number of additional patients with diffuse large B-cell lymphoma that would have been treated with tisagenlecleucel CAR-T therapy if wait times were shortened. For these patients, we estimated mortality benefits using literature estimates of CAR-T effectiveness. Next, among patients who already received CAR-T, we estimated tumor burden progression over time using a linear probability regression model. The primary outcome variable was an indicator for having above-normal lactate dehydrogenase, and we controlled for time, use of bridging therapy, and time-invariant patient characteristics. The regression results, along with literature estimates relating lactate dehydrogenase to CAR-T effectiveness, were used to compute the survival benefits of earlier CAR-T treatment. ResultsReducing wait times by 2 months increased the number of eligible patients receiving CAR-T by at least 10.7%. For patients already receiving tisagenlecleucel CAR-T, a 2-month reduction in wait times generated a 3.3% increase in survival gains per treated patient. Thus, among patients seeking treatment, the combined treatment efficacy increased by 14%, with approximately one-quarter of survival benefits accruing to existing patients receiving faster treatment. ConclusionsDelays affected not only access to CAR-T treatments but also treatment effectiveness. Our results highlight the survival benefits of expediting treatment access and may help explain some observed differences in CAR-T effectiveness across countries.

Is Korea Prepared for an Alzheimer's Disease-Modifying Therapy? Assessing the Korean Healthcare System Infrastructure and the Effect of Blood-Based Biomarker Tests.

BackgroundWith the rapid demographic change in Korea, Alzheimer’s disease has become a primary concern. Recent developments in disease-modifying therapies provide hope that therapy may become available soon. The high disease prevalence and complex evaluation process will create challenges for the healthcare system already burdened by the current pandemic. This study examined the preparedness of the South Korean healthcare system to identify and treat patients when such a therapy becomes available.MethodsWe used a Markov model to simulate a stylized patient’s journey. Based on national data and expert input, we presented projections of the diagnosis and treatment wait times and respective queues of patients under treatment and no-treatment scenarios and further simulated the possible option of adopting a blood-based biomarker test. ResultsUnder the current system, we estimated a peak waiting time of 14 months when a treatment became available, largely because of the limited number of dementia specialists. Adopting a blood-based biomarker test dramatically reduced the initial wait times by more than half. A disease-modifying therapy was estimated to avert 575,000 incident cases in the first 10 years after the treatment entered the market, and a blood-based test further avoided 86,000 additional cases.ConclusionSouth Korea’s healthcare infrastructure requires more preparation for the introduction of a disease-modifying therapy, with the primary capacity limitation being the low number of dementia specialists. The utilization of a blood-based test for Alzheimer’s disease biomarkers may be an effective solution.

Breast cancer diagnosis and treatment wait times in specialized diagnostic units compared with usual care: a population-based study.

Breast assessment sites (bass) were developed to provide expedited and coordinated care for patients being evaluated for breast cancer (bca) in Ontario. We compared the diagnostic and treatment intervals for patients diagnosed at a bas and for those diagnosed through a usual care (uc) route. This population-based, cross-sectional study of patients diagnosed with bca in Ontario during 2007-2015 used linked administrative data. "Diagnostic interval" was the time from the earliest cancer-related health care encounter before diagnosis to diagnosis; "treatment interval" was the time from diagnosis to treatment. Diagnosis at a bas was determined from the patient's biopsy and mammography institutions. Interval lengths for the bas and uc groups were compared using multivariable quantile regression, stratified by detection method. The diagnostic interval was shorter for patients who were bas-diagnosed than for those who were uc-diagnosed, with adjusted median differences of -4.0 days [95% confidence interval (ci): -3.2 days to -4.9 days] for symptomatic patients and -5.4 days (95% ci: -4.7 days to -6.1 days) for screen-detected patients. That association was modified by stage at diagnosis, with larger differences in patients with early-stage cancers. In contrast, the treatment interval was longer in patients who were bas-diagnosed than in those who were uc-diagnosed, with adjusted median differences of 4.2 days (95% ci: 3.8 days to 4.7 days) for symptomatic patients and 4.2 days (95% ci: 3.7 days to 4.8 days) for screen-detected patients. Diagnosis of bca through a bas was associated with a shorter diagnostic interval, but a longer treatment interval. Although efficiencies in the diagnostic interval might help to reduce distress experienced by patients, the longer treatment intervals for patients who are bas-diagnosed remain a cause for concern.

Do Moderate Surgical Treatment Delays Influence Survival in Colon Cancer?

Studies examining treatment delay and survival after surgical treatment of colon cancer have varied in quality and outcome, with little evidence available regarding the safety of longer surgical treatment wait times. Our study examined the effect of surgical treatment wait times on survival for patients with stage I to III colon cancer. A subset cohort analysis was performed using data from a prospectively maintained database. The study was conducted at a tertiary referral center. Data on all of the patients undergoing elective surgery for stage I to III colon cancer from 2006 to 2015 were collected from a prospectively maintained clinical and administrative database. We examined the impact of prolonged wait time to surgery on disease-free and overall survival. Patients were divided into 2 groups based on a treatment wait time of ≤30 or >30 days and were compared using a Cox proportional hazards model. A subgroup analysis was performed using alternative treatment delay cutoffs of 60 and 90 days. There were 908 patients with stage I to III colon cancer treated over the study period, with a median treatment wait time of 38 days (interquartile range, 21-61 days); 368 patients were treated within 30 days, and 540 were treated beyond 30 days from diagnosis. In adjusted multivariate analysis, a treatment delay of >30 days was not associated with decreased disease-free survival (HR = 0.89 (95% CI, 0.61-1.3); p = 0.52) or overall survival (HR = 0.82 (95% CI, 0.63-1.1); p = 0.16). Likewise, subgroup analysis using alternative treatment delay cutoffs of 60 and 90 days did not demonstrate an adverse effect on survival. This study was limited by retrospective analysis. Despite longer median treatment wait times from diagnosis to surgery, with the majority of patients exceeding 30 days and many experiencing delays of 2 to 3 months, no adverse impact on survival was observed. Patients who require additional consultations or investigations preoperatively may safely have their surgery moderately delayed to minimize their perioperative risk without any evidence that this will compromise treatment outcomes. See Video Abstract at http://links.lww.com/DCR/A397.

Abstract C20: Racial Disparities in Breast Cancer Diagnosis-to-treatment Waiting Times in South Carolina

Abstract Background: Although incidence of breast cancer is higher among white females, mortality rates remain higher among black women. This disparity has widened despite improved breast cancer survival rates over time. The widening gap in black-white mortality for breast cancer may be related to differences in tumor biology, treatments received and access to care. The objective of this study was to assess racial disparities in breast cancer diagnosis-to-treatment waiting times in South Carolina (SC). Methods: Data for this analysis includes all female breast cancer cases in SC from 2002-2009 derived from linked files from the SC Central Cancer Registry and Office of Revenue and Fiscal Affairs (who maintains the administrative medical claims data for the South Carolina Public Employee Benefits plan and Medicaid). The main outcome variable was diagnosis-to-treatment time (overall and by cancer treatment type) which was defined as the interval between the date of diagnosis and the date of any first course of treatment or the date of receipt of breast cancer-related surgery, radiation, chemotherapy, and hormonal therapy. The main exposure variable was patient race (white vs black). Students' t test with a significance level of 0.05 was used to assess the difference in diagnosis-to-treatment time by patient race. Results: A total of 1611 breast cancer patients including 1205 white and 406 black females were reported in the study period. There was a consistent increase in the mean number of diagnosis to receipt of first course of treatment among blacks compared to whites overall (22.7 vs 18.4); from diagnosis to surgery (27.2 vs 23.1); from diagnosis to radiation therapy (142.2 vs 122.8 radiation); from diagnosis to chemotherapy (65.5 vs 62.3); from diagnosis to hormonal therapy (148.7 vs 85.3). There was also a consistent increase in the median number of days (18 vs 15; 18 vs 15; 140 vs 91; 56 vs 52; and 136 vs 115) from diagnosis to receipt of first course of treatment overall, and by type (surgery, radiation, chemotherapy and hormonal therapy respectively) among blacks compared to whites. This difference was statistically significant for time to any first course of treatment overall (p: &amp;lt;0.01) and by time from diagnosis to radiotherapy (&amp;lt;0.01). Conclusions: Black females experience consistently longer waiting times from diagnosis to treatment (overall and by all subtypes of treatments) than their white counterparts. Further exploration is needed to know the reasons why black females have persistent increase in diagnosis to treatment wait times and particular attention should be placed on reduction of the diagnosis to treatment wait times in an attempt to reduce already existing racial disparities in breast cancer outcomes among Blacks and Whites. Citation Format: Oluwole Adeyemi Babatunde, Swann Arp Adams, Jan Eberth, Erica Sercy, James Hebert. Racial Disparities in Breast Cancer Diagnosis-to-treatment Waiting Times in South Carolina. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr C20.

Preoperative triage and multidisciplinary consultation for patients with breast cancer: A pilot study between surgery and medical oncology.

208 Background: Breast cancer management has become exceedingly collaborative across specialties. Preoperative multidisciplinary input in particular is increasingly needed as indications for neoadjuvant therapy (NAT) continue to expand. In British Columbia, as in many other regions, breast cancer surgery is typically performed by community surgeons working in settings away from medical and radiation oncologists, making preoperative multidisciplinary input challenging. Methods: This prospective pilot study was designed to enhance and streamline preoperative breast cancer care at the BC Cancer Agency Vancouver Centre (BCCA) and Mount Saint Joseph’s Hospital (MSJ). Patients with a new diagnosis of breast cancer at the MSJ Breast Clinic are included in this pilot triage project if tumors meet one or more of the following criteria: triple negative, HER2+, clinically palpable ≥ 2cm, or present with positive/palpable nodes. Before the patient has consulted with a surgeon, the pathology, imaging, and GP’s assessment is faxed by a MSJ nurse navigator to BCCA for preoperative triage by a medical oncologist. A BCCA navigator facilitates this confidential electronic triage process, and communicates the medical oncologist’s recommendation [a) urgent referral for NAT, or b) upfront surgery] back to MSJ for appropriate booking and management. Results: Since inception in November 2014, 42 patients have undergone electronic preoperative triage through this pilot project. Of those, 47.6% were recommended to have, and did have, a preoperative medical oncology consult to discuss NAT. 90% of patients who had a NAT consult ultimately received NAT compared to a 66% uptake of NAT through the traditional referral process (P = 0.029). Median wait time from ‘biopsy result’ to ‘start of chemotherapy’ was significantly reduced by 9 days through this novel triage process (P = 0.047). Conclusions: This preoperative multidisciplinary triage project has significantly reduced treatment wait times and improved patient selection for and uptake of NAT for breast cancer. Breast cancer care benefits from increased preoperative navigation to help streamline and expedite care for high-risk patients.

Elective chemotherapy admissions: An opportunity to improve wait times.

240 Background: Chemotherapy wait times are a well-recognized challenge facing cancer hospitals. Recent publications have stated that not only do wait times affect patients but they increase costs and consume hospital resources. Wait times lead to longer lengths of stay and require additional staff attention. Reducing chemotherapy treatment wait times has long been a priority of Sloan Kettering, with this study focusing on inpatient chemo processes. During October and November of 2014, 6 current state observations were performed in chemo nursing verification, chemo pharmacy and an inpatient chemo unit. Metrics measured included submission of electronic chemo orders, blood work availability, clearing for treatment, PICC line placement, bed availability and drug transport. All system components were analyzed from both a clinical and industrial engineering perspective. Future state analysis was conducted from December 2014 through April of 2015. Process improvement techniques including direct observation, process mapping, waste analysis and time studies were used to assess workflow. Methods: Prior to implementing performance improvement interventions, baseline data was compiled. 12% of electronic chemo orders were submitted 24 hours prior to admission, 36% of the time blood work was not available within 72 hours prior to patient arrival, 46% of treatments experienced pending delays due to ‘Proceed to Treat’ order, 0% of PICC lines were placed prior to admission, 34% of patients were discharged before 2pm and time for drug delivery averaged 1 hour and 47 minutes. The average time from patient admission to first chemotherapy treatment was 9.7 hours. Results: Following the rollout of a newly designed pilot unit in January 2015, data was collected for 192 chemo admissions in February through April of 2015. The use of electronic chemo orders rose to 84%, blood work was available 60% of the time, pending orders reduced to 0%, PICC placement occurred prior to day of admission 98% of the time, 46% of patients discharged before 2pm and drug delivery was reduced to 0 minutes. The time from admission to chemo treatment was reduced to 2.1 hours. Conclusions: The amount of patients treated after day of admission reduced from 17% to 8%, saving 18 patient days.

Wait times for prostate cancer treatment and patient perceptions of care in Canada: a mixed-methods report.

Access to cancer care is a significant concern for Canadians. Prolonged delays between cancer diagnosis and treatment have been associated with anxiety, stress, and perceived powerlessness for patients and their family members. Longer wait times can also be associated with poorer prognosis, although the evidence is inconclusive. Here, we report national wait times for radiation therapy and surgery for localized prostate cancer (pca) and the effect of wait time on patient perceptions of their care. Treatment wait times showed substantial interprovincial variation. The longest 90th percentile wait times for radiation therapy and surgery were, respectively, 40 days and 105 days. In all provinces, waits for radiation therapy were longer for pca patients than for patients with breast, colorectal, or lung cancer. In the focus groups and interviews conducted with 47 men treated for pca, many participants did not perceive that wait times for treatment were prolonged. Those who experienced delays between diagnosis and treatment voiced issues with a lack of communication about when they would receive treatment and a lack of support or information to make an informed decision about treatment. Minimizing treatment delays was an aspect of the cancer journey that participants would like to change because of the stress it caused. Although wait time statistics are useful, a review of cancer control in Canada cannot be considered complete unless an effort is made to give voice to the experiences of individuals with cancer. The findings presented here are intended to provide a snapshot of national care delivery for localized pca and to identify opportunities for improvement in clinical practice.

Transforming the Patient Experience through Lean Initiatives: Improving Care for Our Brachytherapy Patients

Transforming the Patient Experience through Lean Initiatives: Improving Care for Our Brachytherapy Patients

Monitoring treatment wait times for cancer patients in Japan.

289 Background: Treatment wait times for cancer patients is among the key performance indicators of cancer policy in Japan, but has never been measured across a large number of patients. We aimed to measure treatment wait times for cancer patients across a large number of hospitals in Japan using health claims data. Methods: We developed a database of claims data (Jan 2011 - Dec 2012) linked to 2011 hospital-based cancer registry data of breast, cervical, colorectal, liver, lung, prostate and stomach cancer patients from 126 designated cancer hospitals in Japan. Treatment wait time was defined as the number of days between the date of diagnosis (the date on which a pathological test or imaging exam that contributed the most to the diagnosis was performed) and initiation of treatment. Dates of diagnostic tests, therapeutic procedures, and chemotherapy (chemo) administration were obtained from health claims data. We calculated wait times by cancer type, treatment, and stage, and investigated if these factors were significantly associated with wait times even after adjusting for age using multiple linear regression. Results: Among 44,102 cancer patients who received cancer treatment, the median wait time was 31 days (IQR=18-50) for all patients, and 32, 42, 31, 22, 22, 55 and 31 days for breast, cervical, colon, liver, lung, prostate and stomach cancer patients, respectively. Wait times were longer for surgery (36 days) compared to radiation (22 days) and chemo (21 days), and shorter for later stage patients: 48, 36, 35, 23, and 14 days for stages 0, I, II, III, and IV, respectively. Cancer type, treatment type, and stages were all independently and significantly associated with treatment wait times even after adjusting for age (p&lt;0.05). Conclusions: This is the first study to investigate treatment wait times across a large number of cancer hospitals in Japan. Treatment wait times were particularly longer for cervical and prostate cancer patients. While the effect of prolonged treatment wait times on clinical outcomes is unknown, longer treatment wait time increases the psychosocial stresses of cancer patients. Continuous monitoring and feedback of study findings to hospitals are required for improvements in the future.

An assessment of neoadjuvant therapy for breast cancer and treatment wait times at the BC Cancer Agency Vancouver.

140 Background: Neoadjuvant therapy (NAT) is widely considered to be the standard of care for patients diagnosed with locally advanced breast cancer (LABC) or inflammatory breast cancer (IBC). NAT is also considered in patients with more aggressive subtypes (Her2+ or triple negative cancers). However, it remains unclear which patients are being considered for NAT, which patients are indeed receiving NAT, and how long the current wait times for chemotherapy and hormone therapy are in this patient population. This study was designed to characterize the breast cancer patients being referred to the BC Cancer Agency (BCCA) Vancouver’s NAT clinic, and to determine the average wait times for chemotherapy and hormone therapy in these patients. Methods: Between May 13th, 2013 and June 3rd, 2014, a total of 160 potential NAT candidates were seen at the BCCA Vancouver NAT clinic. Breast cancer characteristics and wait times for these patients were assessed prospectively using a secure database. Results: Of these 160 patients, 119 (74%) actually received NAT; 76.7% of these were deemed LABC patients (clinical stage IIB or III), and 6% were “window of opportunity” (WOP) patients (those considered for NAT due to long surgical wait times). NAT patient receptor status differed significantly from the receptor statuses of patients who did not receive NAT (p=0.006), with Her2+ and triple negative breast cancer patients being most likely to receive NAT. Seventy-eight percent of ER+Her2+, 86% of ER-Her2+, 67% of ER+Her2-, and 80% of triple negative patients received NAT. A total of 4 patients (2.5%) presented in clinic with metastatic disease and thus were not considered for NAT. The average wait time between when a patient was referred to the BCCA and when they commenced chemotherapy was 18.1 days (median: 16), while the average wait time to receive hormone therapy alone was 12.3 days (median: 10). Conclusions: These findings suggest a need to expedite screening and care for these high-risk breast cancer patients in order to characterize and treat the disease neoadjuvantly before it has metastasized. Strategies to reduce wait times in this breast cancer population are being further assessed.

Obstacles de l'accès au traitement rapportés par des personnes aux prises avec un trouble anxieux

Our study examined the barriers to treatment experienced by people with anxiety disorders (ADs) who had not received services for their problems. Recommendations to improve treatment access made by participants are reported. A web-based questionnaire on treatment accessibility for anxiety disorders was completed by 610 people living in Quebec reporting an anxiety problem. Chi-square tests were used to compare answers from people who received services (n = 151) with answers from people who had not (n = 434 ). Treatment wait times that were too long (X2 = 29.66, df = 1, P < 0.001 ), difficulties reaching a professional by phone (X2 = 13. 75, df = 1, P < 0.001 ), and geographical distance from service sites (X2 = 4.34, df = 1, P = 0.04) were obstacles that hindered participants who had not received the services they were seeking, more than those who had received services. Participant-reported barriers and recommendations highlight the need to increase access to health care professionals in terms of wait times, to train and inform primary care professionals about screening and treating ADs, and to develop psychotherapeutic services availability in the public health network.

Efficiency of Colorectal Cancer Care Among Veterans: Analysis of Treatment Wait Times at Veterans Affairs Medical Centers

Timeliness of cancer treatment is an important aspect of health care quality. Veterans Affairs Medical Centers (VAMCs) are expected to treat a growing number of patients with cancer. Our objectives were to examine treatment times from diagnosis to first-course therapy for patients with colon and rectal cancers and assess factors associated with prolonged wait times. From the VA Central Cancer Registry, patients who underwent colon or rectal resection for cancer from 1998 to 2008 were identified. Time from diagnosis to definitive cancer-directed therapy was measured, and multivariable regression methods were used to determine predictors of prolonged wait times for colon (≥ 45 days) and rectal (≥ 60 days) cancers. From 124 VAMCs, 14,097 patients underwent colectomy, and 3,390 underwent rectal resection for cancer. For colon cancer, the median time to treatment increased by 68% over time (P < .001). From 2007 to 2008, the median time to colectomy was 32 days. Predictors of prolonged wait times included age ≥ 55 years (v < 55 years), time period (2007 to 2008 v 1998 to 2000), black race (v white), marriage status (married v unmarried), high-volume center status (v low volume), and treatment at a different hospital (v same hospital as initial diagnosis; all P < .05). For rectal cancer, the overall median time to first-course treatment increased by 74% (P < .001). From 2007 to 2008, the median time to proctectomy was 47 days. Similar predictors of prolonged wait times were identified for rectal cancer. Time to first treatment has increased for patients with colon and rectal cancers at VAMCs. Patient, tumor, and hospital factors are associated with prolonged time to treatment.

P1-11-11: Wait Times for Breast Cancer Care in Manitoba 2009–2010. Time To Face the Challenge.

Abstract Background: Wait times for patients with breast cancer to receive oncological treatment vary significantly. In Manitoba, the radiation treatment wait times improved in the year 2005 compared to 2001. However, other parts of the patient's journey have lengthened and negated the reduction seen in radiation treatment wait times. Aims: To examine the overall time from disease suspicion to treatment of breast cancer patients from June 2009 to June 2010 and to compare to the previously published wait times. Methods: This population-based retrospective study looked at representative samples of women newly diagnosed with breast cancer. Patients were followed from the time of first presentation, either to their family physician or after a suspicious screening mammogram, to the time adjuvant treatment was started. Each patient's journey was subdivided into different chronological stages. The data was compared to the wait times reported in 2005. Results: 363 patients’ data was collected and analyzed. The median elapsed time in days for each phase of the journey was calculated. Total wait times from suspicion to diagnosis were also calculated. The wait times of most stages of the patients’ journey have worsened when compared to 2005. However, there was some improvement in the diagnostic part of the journey. Delays to surgery and pathology have contributed to lengthening of the total journey. There was also a systematic and repetitive administration delay at each transition. Screen-detected cases had a shorter journey than those who presented through a family physician. Conclusions: In spite of improvements achieved in the wait times at some stages of the journey, the total length of the patient journey has not been shortened. This represents not only individual team failures but also a built in complexity in the health system. In order to achieve a meaningful cut in wait times for breast cancer patients, the entire trajectory of care needs to be addressed. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-11-11.

Who are the users of publicly reported cancer treatment wait times (WT)?

6043 Background: Greater participation by patients in health care decision-making and public concerns about WT led Cancer Care Ontario (CCO) to post radiation WT by cancer type and treatment centre on its website http://www.cancercare.on.ca anticipating patients and referring physicians (MDs) would use WT information to access facilities with shorter waits. The availability of more radiation treatment facilities in Southern Ontario provides patients and MDs with more options for location of treatment. Methods: The usefulness of this approach was evaluated by an on-line survey, patient focus groups, physician interviews and usability lab testing. Results: 1,043 on-line surveys were completed by patients/family members (35%), media (24%) and others, including health professionals (HP) and administrators (AD). HP found the information useful and clear but patients were less satisfied, wanting information on the effect of WT on their illness. 45 individuals (40 treated patients, 5 family) participated in 8 geographically dispersed focus groups. Facilitator-led conversations were recorded, transcribed verbatim and content grouped in themes by 4 researchers. Most patients were unaware of the CCO WT information. Patients indicated that MDs should have and use WT information and determine speed of access to care based on urgency of condition. Patients would accept MD advice to travel to a more distant treatment facility but patients questioned why WT existed and why health care system not managed more efficiently. 15 MD phone interviews indicated MDs were distrustful of WT data, did not use the web data for referral, preferring usual practice patterns. MDs were reluctant to share WT information with patients for fear of creating unnecessary anxiety. AD found data useful as a stimulus for performance improvement. Usability lab testing uncovered numerous user preferences for redesign of the site, including its content. Conclusions: Current Ontario patients and MDs are not ‘consumers’ of WT information but AD see value in this information for system improvement. As society increasingly uses the internet as an information resource, future patients and MDs will likely utilize WT information in the decision-making for location of care. Supported by Cancer Care Ontario and grant 03110 from the Change Foundation. No significant financial relationships to disclose.