The non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients

The non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients Boaz Hovav, Shuli Brammli-Greenberg This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5714867/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Inter-facility transfers of care during breast cancer treatment occurred in 37% of cases in previous studies, leading to treatment delays and decreased survival. The reasons for such transfers were scarcely studied. The study aimed to identify the factors affecting facility transfers among breast cancer patients. Patients and Methods: 198 Hebrew-speaking Israeli women, aged 32 to 81, diagnosed with breast cancer up to five years earlier, now considered disease-free participated in a mixed-methods study. 19 in-depth qualitative interviews were analyzed and used to construct a ten-part, 78-item questionnaire, which tracked 179 patient's treatment from biopsy to recovery, focusing on treatment decisions and the factors and perceptions influencing them. Results Participants reported high rates of inter-facility transfers. 60% of the participants transferred between biopsy and surgery, motivated by facility type (OR = 15.15) and level of trust (OR = 2.58). 67% transferred between the biopsy and neo-adjuvant chemotherapy, and about 53% of those who had neo-adjuvant chemotherapy transferred prior to surgery. Following surgery, participants requiring radiation therapy transferred 90% of times, driven by the low availability of radiotherapy equipment in rural Israel (OR = 31.87) or by the staff’s attitude (OR = 8.32). Participants who needed adjuvant chemotherapy transferred 49% of cases, motivated by the staff’s attitude (OR = 38.4) and transferred again in 81% of the cases for radiotherapy. Conclusion Lower availability of cancer treatments in rural areas, lack of trust in the facility staff and demographic factors lead to inter-facility transfers that may lead to treatment delays and increased morbidity. Breast Cancer Transfer of care Facility transfer Rural Patient preferences Trust Quantitative research Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Introduction Breast cancer is the leading type of cancer among women worldwide, with 2.3 million new cases diagnosed and 670,000 deaths annually [ 1 ]. In Israel, it is responsible for about one-third of invasive cancer cases annually [ 2 ]. Breast cancer treatment in Israel follows the clinical guidelines issued by ESMO [ 3 ] and NCCN [ 4 ]; A biopsy is followed by surgery to remove the tumor, with chemotherapy before or after surgery according to tumor stage and with radiotherapy when appropriate. Living in a small country (22,145 square kilometers), with universal health coverage and many public and private medical service providers, Israeli breast cancer patients can choose where to receive treatment and can transfer from one care facility to another when they found it appropriate. The study analyzed the non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients. Literature review Transferring from one care facility to another during breast cancer treatment was previously reported to occur in over one third of cases, and were linked to treatment delays and decreased survival: Bleicher and colleagues [ 5 ] studied the files of 622,793 US patients with non-metastatic invasive breast cancer and found that 36.6% of patients transferred care. The transfers added 7.3 days to time to surgery, 7.8 days in the case of chemotherapy, 8.7 days in the case of radiotherapy and 9.8 days in the case of endocrine therapy (p < 0.001 for all). Similarly, Heeg and colleagues [ 6 ] studied the files of 41,413 Dutch patients with breast cancer and found that 8.5% of them transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before neo-adjuvant chemotherapy, especially in the case of patients under 40, thus delaying surgery by 5 to 9 days and neo-adjuvant chemotherapy by 9 days. The effects of treatment delays on breast cancer outcomes were studied by Bleicher and colleagues [ 7 ] who showed that in the cases of 94,544 stage I and II breast-cancer patients, specific mortality increased with every 60-day delay between diagnosis and breast cancer surgery (HR = 1.13 for stage I and HR = 1.06 for stage II). Mateo and colleagues [ 8 ] studied 351,087 breast cancer patients and found that overall survival declined for all patients for every month of operative delay (HR = 1.104, P < 0.001) regardless of hormone receptor status. Ward and colleagues [ 9 ] studied 140,615 patients with ductal carcinoma in situ and found that the added risk of death from all causes for each 30-day delay was 7.4% (HR 1.07; P < 0.0001), regardless of tumor invasiveness. Breast cancer treatment in Israel Inter-facility transfer of care during cancer treatment can be motivated either by the availability of a certain treatment option or by the patient's preference. On the availability side, Israel’s Health Insurance Law, provides high-standard cancer treatment free of charge in any of Israel's 44 public hospitals [ 10 ]. Under Israeli regulations, cancer patients can choose any public hospital but cannot choose the treating physician. In order to overcome the physician choice obstacle and to shorten waiting time, which can sometimes be lengthy in the public healthcare system[ 11 ], patients can turn to private medical services and finance them using private insurance plans, which are carried by some 92% of the Israeli population [ 12 ]. In the Israeli healthcare system, biopsies can be performed either at a general hospital or an HMO clinics (the latter do not offer any other cancer-related services). Most general hospitals perform biopsies, surgery, and chemotherapy treatments, however only 10 hospitals perform radiotherapy (most located in central Israel), thus necessitating a transfer. Since cancer treatment requires a high level of trust between patient and physician, and since Israeli patients can choose their treating hospitals but not their treating physician, Israeli patients who do not fully trust their physician are actively involved in choosing their treating hospital and treating chemotherapy center, in an effort to improve their treatment and survival. [ 13 ] Purpose The Purpose of the study was to identify factors affecting facility transfers among breast cancer patients. We tracked the preferences and decisions of Israeli breast cancer patients in all steps of cancer treatment, as well as the facility transfers and their underlying reasons. While most of the professional literature on the subject focuses on analyzing patient files, we interviewed the women themselves, which helped to illuminate the factors influencing the patient’s transfer decision. Methods Participants The qualitative part of the study began with in-depth interviews held between February and November 2016, with 19 breast cancer survivors recruited from the breast cancer follow-up clinics at two Israeli hospitals. The participants consisted of Hebrew-speaking women aged 43 to 73 (average 58.2) who had been diagnosed with breast cancer up to five years earlier and now considered to be disease-free. The quantitative part of the study involved 179 Hebrew-speaking women aged 30 to 75 (average 57.5) who had also been diagnosed with breast cancer up to five years earlier and were considered disease-free at the time of the study. Participants were recruited between November 2016 and September 2018 from three breast cancer follow-up clinics. Participants had an average of 3.1 children, and all were Jewish. About 87% were members of Clalit Health Services (the largest HMO in Israel covering some 52% of the population) and the distribution of their income levels was similar to that of the general population. Participants were diagnosed with breast cancer at an average age of 55.3 years. About 62% had their biopsy done at a public hospital. All the participants had surgery to remove the tumor: 72% had a lumpectomy, with only a handful having a mastectomy or a bilateral mastectomy. About 85% of the participants had their surgery at a public hospital. About 45% had chemotherapy, 24% had neo-adjuvant therapy, 21% had adjuvant therapy and 84% had radiotherapy. Procedure A mixed methods study, beginning with 19 in-depth interviews with breast cancer survivors who were recruited from the breast cancer follow-up clinics at two Israeli hospitals. The interviews were carried out by the lead investigator (B.H.) and then recorded, transcribed, and analyzed using the ATLAS.ti qualitative data analysis software. The interviews were analyzed for key themes (Fig. 1 ) and for the relationships between them. Following the qualitative research, we created a ten-part, 78-item questionnaire, which tracked the patient's treatment progress from biopsy to recovery focusing on treatment decisions and the factors and perceptions that influenced them. This was accomplished by combining key patient themes from the qualitative part of the study with questions derived from previous studies of decision making among breast cancer patients [ 14 – 17 ]. Variables - The dependent variable for analysis was hospital transfer between any treatment steps and the independent variables included a variety of demographic and personal variables including age, number of children, education, religiosity, income, HMO, supplementary or private insurance, time since cancer diagnosis, treatment received, treatment location, key treatment decision, involvement levels, key consultant regarding cancer and more. Statistical analysis - The quantitative data was analyzed using IBM SPSS Statistics, release 21.0. The margin of error was set to 5.0% and the study’s power was over 80%. We used Bivariate Analysis to identify the independent variables by correlating with each cancer treatment stage and then used a multinomial logistic regression to produce a model based on the main factors and covariate effects. Since some of the treatment steps had only a small number of patients, we used the McNemar test to detect differences between two related groups for a dichotomous dependent variable. Results The decision-making model used by breast cancer patients: qualitative perspective Following the qualitative interviews, we created a preliminary model of breast cancer decision-making, shown in Fig. 2 , with three main steps: 1) Diagnosis – The first step begins as a women has a routine screening or discovers a lump, has a biopsy, and finally receives a diagnosis of cancer. Several participants found this stage to be overwhelming. 2) Hospital/surgeon choice – Once diagnosed, the patient chooses whether to have treatment at the diagnosing facility or transfer to a different one. Participants were focused on finding a caregiver they could trust. 3) Treatment negotiation – The interviews revealed that some participants took an active role in the treatment decisions while others cooperated with their caregivers in deciding or stayed passive. Once again, the greater their trust in the caregiver at the diagnosing facility, the more likely participants were to accept the treatment recommendations and the less likely they were to choose more extreme treatment, such as a bilateral mastectomy. As shown in Fig. 2 , the main factors influencing decision-making were staff attitude, family, fear, monetary issues, trust, and choice. Facility transfers among breast cancer patients: the quantitative study The quantitative study data revealed that between 48.6% and 90.2% of participants transferred to another facility between treatment steps, with a prominent level of variation across treatment stages. Figure 3 shows the number of participants in each treatment stage and the proportion of participants who transferred to another facility. Transfers between biopsy and neo-adjuvant chemotherapy Facility transfers between diagnosis and first treatment include transfers between the biopsy and neo-adjuvant chemotherapy or between the biopsy and surgery. Of the 43 participants who underwent neo-adjuvant therapy, 29 (67.4%) transferred to a different facility. Of those 29, eight (27.5%) had their biopsy at an HMO clinic and 9 (31%) at a private clinic, requiring all 17 to transfer to a hospital for further therapy. 26 participants had biopsy at a hospital, 12 (46%) transferred to a different hospital to have neo-adjuvant chemotherapy and 14 remained at the same facility. Bivariate chi-square analysis found a correlation between level of education (high school, undergraduate, graduate) and facility transfer (Asymp. Sig = 0.013) and a weak correlation to the distance from the facility to the participant's home (Asymp. Sig = 0.09). The other logistic regressions did not demonstrate correlation. Transfers between the biopsy and surgery Of the 136 participants who had surgery without neo-adjuvant chemotherapy, 82 (60.3%) transferred to a different facility (Fig. 3 ). Of those who transferred, 38 (46.3%) had their biopsy at an HMO clinic, and 13 (15.8%) at a private clinic. One participant had both her biopsy and the surgical procedure at a large private hospital in Tel-Aviv. 84 participants had their biopsy at a general hospital, 27 (30.5%) transferred to a different hospital for surgery. 43 patients had neo-adjuvant chemotherapy before surgery, 23 (53.5%) transferred to a different hospital for surgery. Bivariate chi-square analysis found correlation between hospital transfers and biopsy facility type (clinic / hospital, Asymp. Sig = 0.000), religiosity (secular / religious, Asymp. Sig = 0.034), trust in the treating staff (trust / lack of trust, Asymp. Sig = 0.004) and proximity to the participant's home (low / high, Asymp. Sig = 0.000). Having neo-adjuvant chemotherapy was weakly associated with transferring (Asymp. Sig = 0.055). A multivariate logistic regression found correlations between transferring and treatment facility type (OR = 15.15, 95%CI = 6.35–36.15, Sig = 0.000), not having neoadjuvant chemotherapy (OR = 4.12, 95%CI = 1.57–10.75, Sig = 0.004) and staff mistrust (OR = 2.58, 95%CI = 1.22–5.43, Sig = 0.012). Figure 4 describes the factors influencing facility transfers between breast cancer treatments. Mistrust was defined when a participant reported active involvement in certain treatment decisions and consulting with another physician or with a family member as part of their decision making. A participant who reported low levels of involvement and/or not consulting with another physician or family member was considered to have trust in the staff. As the effect of the treatment facility type was overpowering, a second logistic regression was performed without the biopsy facility type variable. It revealed that participants categorized as lacking trust showed a positive correlation with transferring to a different hospital for surgery (OR = 2.21, 95%CI = 1.20–4.08, Sig = 0.011). Transfers between surgery and adjuvant chemotherapy 37 participants had adjuvant chemotherapy. Of those, 15 (40.5%) transferred to a different facility (Fig. 3 ). Among the four participants who had surgery at a private hospital, three (75%) transferred to a different facility. Among the 33 participants who had surgery at a public hospital, 12 (36.3%) transferred to another facility. Bivariate chi-square analysis found a correlation between the attitude of the treating staff at the operating hospital (good relationship / poor relationship, Asymp. Sig = 0.000) and transferring to a different facility. Weak correlation was found between the participant’s number of children (Asymp. Sig = 0.144), and between the hospital type (public / private, Asymp. Sig = 0.172) and transferring to a different facility. A logistic regression found correlations between the attitude of the treating staff and transferring to a different facility (OR = 38.4, 95%CI = 3.95-373.01, Sig = 0.002). Due to the small number of participants in this stage, we used a McNemar test and could not reject the null hypothesis. Transfers between surgery or adjuvant chemotherapy and radiotherapy 151 participants underwent radiotherapy. Of those, 129 (85.4%) underwent it at a different facility, while 12 (7.9%) had in-surgery radiotherapy as part of the surgical procedure. As mentioned earlier, only 10 hospitals in Israel are authorized to perform radiotherapy, most of them large hospitals located in central Israel. 136 of the participants were treated at smaller hospitals which do not offer radiation (most of the recruitment was performed by physicians in rural hospitals), thus forcing many patients to transfer to a larger hospital, offering radiotherapy. However, one of the small hospitals offers in-surgery radiotherapy, and 12 participants chose to have it. 15 participants had surgery at a larger hospital that offers radiotherapy, with nine patients (60%) transferring to a different facility for radiotherapy. Bivariate chi-square analysis found correlation between the participant's HMO (Clalit / other, Asymp. Sig = 0.002), the age group of their youngest child (Asymp. Sig = 0.009), radiation equipment at the facility (Asymp. Sig = 0.000), proximity to the participant’s home (High / low, Asymp. Sig = 0.029), attitude of the treating staff (Asymp. Sig = 0.000), the recommendation of a trusted physician (Asymp. Sig = 0.028) and the recommendation of a trusted friend (Asymp. Sig = 0.038) and transferring to another facility. As expected, the first logistic regression found a strong correlation between the lack of radiotherapy equipment at a facility and transferring to a different facility (OR = 31.87, 95%CI = 4.94-205.54, p = 0.000), and the attitude of the treating staff (OR = 8.32, 95%CI = 1.25–55.35, p = 0.028). Since the presence of radiotherapy equipment had such a dominant effect on the findings, we performed a second regression which omitted that variable. It showed a positive correlation between the attitude of the treating staff and transferring to a different facility (OR = 13.74, 95%CI = 2.57–73.38, p = 0.002). Discussion Breast cancer is the leading cause of cancer among women all over the world. In Israel, breast cancer treatment is provided free of charge under the Israeli Health Insurance Law and follows international clinical guidelines such as those of ESMO[ 3 ] and NCCN[ 4 ]. The fact that clinical guidelines and the health system’s structure create leeway in patient decision-making allows us to identify personal, non-medical factors that affect those decisions. The first part of the study involved preliminary qualitative interviews with 19 breast cancer survivors. The interview data analysis focused the study on the relationship with the caregivers and participant’s trust in them, as well as finding the right facility and the right physician. While facility transfer was mentioned only once in the interviews, patients who described bad attitude among the treating staff were more active in treatment decisions and considering more extreme treatments, such as bilateral mastectomy. The quantitative study, on the other hand, revealed high rates of facility transfer among the participants, ranging from 48–90% depending on the treatment stage. The study findings for transfer rates are much higher than those found by Heeg and colleagues [ 6 ] who reported a rate of 4.9% before primary surgery and 24.8% before neo-adjuvant chemotherapy, and those found by Bleicher and colleagues [ 5 ] who reported a transfer rate of 39.6%. Bleicher and colleagues found that each transfer of care could delay treatment by 5–9 days while other studies found that a 30-day treatment delay increases mortality by 7–10% [ 8 , 9 ]. Thus, the high rate of transfer among breast cancer patients in rural Israel may be having a substantial effect on patient's survival and therefore understanding the underlying reasons for transfers of care is of great clinical importance. The study findings point out three key factors: 1. Treatment availability – Many facility transfers were due to a lack of treatment availability. Thus, following a biopsy at an HMO surgical clinic the patient had to transfer to a hospital for surgery or neo-adjuvant chemotherapy, and patients having surgery at a rural hospital had to transfer to a centrally located hospital for radiotherapy. The effect of treatment availability on the regression analysis was so overwhelming that we had to analyze the transfers both with and without it. Since the OECD defines primary care to be a key pillar of a modern healthcare system[ 18 , 19 ], it is likely that additional cancer-related services, such as biopsies, surgical procedures and chemotherapy, will in the future be provided at rural clinics and hospitals; however, other services, such as radiotherapy, are likely to remain available only at secondary and tertiary care facilities, most of them located in metropolitan areas. 2. Trust – Many of the transfers documented in the study were not motivated by availability of treatment and were therefore categorized as motivated by the patient's desire for better treatment. Since most hospitals in Israel provide both surgery and chemotherapy, the high rate of facility transfers between surgery and chemotherapy (53.5% between neo-adjuvant therapy and surgery and 48.6% between surgery and adjuvant therapy) is an indication that personal preference is a key factor. Thus, following a biopsy, many participants who transferred to a different facility were categorized as lacking trust in the staff, transferring to improve treatment outcomes. Similarly, following surgery, both participants needing adjuvant chemotherapy and participants needing radiotherapy reported transferring because of the attitude of the staff. Thus, staff attitude and personal trust appear to play a major role in the transfer decision. 3. Demographics – The bivariate chi-square analysis showed that demographic factors such as religiosity, number and age of children, proximity to the facility and HMO membership influence the decision to transfer. Limitations of the study Previous studies analyzed samples of hundreds of thousands of breast cancer patients, and therefore the study small sample size is a shortcoming. However, this is offset by the depth of the research. We questioned each respondent about her preferences and motivations to understand the effect of the patient's preferences, as compared to the effect of treatment availability. Nonetheless, using a larger sample of patients would improve the analysis. We used questionnaires to track the respondent's treatment process but did not have access to their files or their exact diagnosis. Thus, the study insights may have been biased by the participant's recall ability and their subjective perceptions of the treatment process. Further research A future study in cooperation with one of the leading HMOs is being planned, with the goal of analyzing larger datasets of facility transfers among cancer patients and understanding their effect on a patient's survival. Declarations Acknowledgement The research was conducted under the guidance and supervision of Prof. Manfred Green and Dr. Itzhak Zaidis. Funding This work was supported by the Israel National Institute for Health Policy Research. Grant number r-6-2015. Competing Interests The authors have no financial or non-financial interests to declare. Author Contributions Boaz Hovav - Study conception and design, material preparation, data collection and analysis, draft writing, comments and editing. Shuli Brammli-Greenberg - Study conception and design, writing supervision, comments and editing. Data availability The datasets generated during and/or analyzed during the current study are not publicly available due to medical confidentiality but are available from the corresponding author on reasonable request. Ethics Approval This study was performed in line with the principles of the Declaration of Helsinki. The research protocol was approved by the IRB in each of the recruiting clinics and by the ethical committee of the University of Haifa. Consent to participate Informed consent was obtained from all individual participants included in the study References WHO. Breast cancer. 2024. National Cancer Registry. Breast cancer among Israeli women - Inforamation updateOctober 2024 . Jerusalem, 2024. Loibl S, André F, Bachelot T et al. Early breast cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up ☆. Annals of Oncology 2024; 35 :159–82. Gradishar WJ, Moran MS, Abraham J et al. Breast Cancer, Version 3.2024, NCCN Clinical Practice Guidelines in Oncology. Journal of the National Comprehensive Cancer Network 2024; 22 :331–57. Bleicher RJ, Chang C, Wang CE et al. Treatment delays from transfers of care and their impact on breast cancer quality measures. Breast Cancer Res Treat 2019; 173 :603–17. Heeg E, Schreuder K, Spronk PER et al. Hospital transfer after a breast cancer diagnosis: A population-based study in the Netherlands of the extent, predictive characteristics and its impact on time to treatment. European Journal of Surgical Oncology 2019; 45 :560–6. Bleicher RJ, Ruth K, Sigurdson ER et al. Time to surgery and breast cancer survival in the United States. JAMA Oncol 2016; 2 :330–9. Mateo AM, Mazor AM, Obeid E et al. Time to Surgery and the Impact of Delay in the Non-Neoadjuvant Setting on Triple-Negative Breast Cancers and Other Phenotypes. Ann Surg Oncol 2020; 27 :1679–92. Ward WH, DeMora L, Handorf E et al. Preoperative Delays in the Treatment of DCIS and the Associated Incidence of Invasive Breast Cancer. Ann Surg Oncol 2020; 27 :386–96. Ben Shetreet I, Woolf LL. Health Services in Israel 6th Edition . Jerusalem, 2015. Bowers L, Chernichovsky D. Your Place in Line Waiting Times in Israel’s Public Hospitals . Jerusalem, 2016. Brammli-Greenberg S, Yaari I, Avni E. דעת הציבור על רמת השירות ותפקוד מערכת הבריאות 2018 . Jerusalem, 2020. Hovav B, Brammli-Greenberg S. Involvement levels of breast cancer patients – seeking trusted hospital and physician. J Health Psychol 2021; Epub ahead , DOI: 10.1177/13591053211062350. Degner LF, Sloan JA, Venkatesh P. The Control Preferences Scale. Canadian Journal of Nursing Research 1997; 29 :21–43. Ballinger RS, Mayer KF, Lawrence G et al. Patients’ decision-making in a UK specialist centre with high mastectomy rates. Breast 2008; 17 :574–9. Collins ED, Moore CP, Clay KF et al. Can women with early-stage breast cancer make an informed decision for mastectomy? Journal of Clinical Oncology 2009; 27 :519–25. Maly RC, Frank JC, Marshall GN et al. Perceived Efficacy in Patient-Physician Interactions (PEPPI): Validation of an instrument in older persons. J Am Geriatr Soc 1998; 46 :889–94. Morgan D, Mueller M. Spending on Primary Care: First Estimates ., 2018. OECD. Realising the Potential of Primary Health Care, OECD Health Policy Studies . Paris: OECD Publishing, 2020. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5714867","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":394671532,"identity":"035ea990-1169-4cde-8901-7068abf68fa9","order_by":0,"name":"Boaz Hovav","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsUlEQVRIiWNgGAWjYBACAyBmZqiAcy2I1XIGzpUgUgtjG5xPhBZz9ubHnwvnHU7sb2B++IGhgAgtlj3HDIxnbjucOOMAm7EEcQ67kWCQzLvtsDHQhWZE+uVG+ofDvHNAWti/Easlx7CZt+GwnAEDD5G2WPacKWbmOZYuJ3GYp1gigRgt5uztmz/z1Fjz8Le3b/zw4Y8NYS1Q0AyKUAaGBKI1MDDUkaB2FIyCUTAKRhwAAL1qL5h7D2aXAAAAAElFTkSuQmCC","orcid":"","institution":"Max Stern Academic College of Emek Yezreel","correspondingAuthor":true,"prefix":"","firstName":"Boaz","middleName":"","lastName":"Hovav","suffix":""},{"id":394671533,"identity":"3d5cb89c-17ba-41dd-9797-c21aaecbd499","order_by":1,"name":"Shuli Brammli-Greenberg","email":"","orcid":"","institution":"Hebrew University of Jerusalem","correspondingAuthor":false,"prefix":"","firstName":"Shuli","middleName":"","lastName":"Brammli-Greenberg","suffix":""}],"badges":[],"createdAt":"2024-12-26 08:53:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5714867/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5714867/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72690135,"identity":"b2de9be2-b94e-4574-84f9-251176dbd38b","added_by":"auto","created_at":"2024-12-31 09:23:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82868,"visible":true,"origin":"","legend":"\u003cp\u003eQualitative interview theme prevalence\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5714867/v1/cfe997064df0c3471c4c84ae.png"},{"id":72690137,"identity":"41d04a75-9889-4a88-bb77-f597cb722047","added_by":"auto","created_at":"2024-12-31 09:23:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153578,"visible":true,"origin":"","legend":"\u003cp\u003ePreliminary model of decision-making in the breast cancer treatment process\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5714867/v1/72435318b59da9e78ffbe090.png"},{"id":72691644,"identity":"eafcb49e-dad2-4314-96ab-1a89ea1239eb","added_by":"auto","created_at":"2024-12-31 09:47:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":161506,"visible":true,"origin":"","legend":"\u003cp\u003eFacility transfers of care through treatment stages (participants in every step)\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5714867/v1/b30655f1fbcf7d0b1e0f56c6.png"},{"id":72690551,"identity":"ff400792-992d-4606-9aca-94d616604e85","added_by":"auto","created_at":"2024-12-31 09:31:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":140378,"visible":true,"origin":"","legend":"\u003cp\u003eThe factors influencing facility transfers between breast cancer treatment stages – Odds ratio and significance levels (*p\u0026lt;0.05; ** p\u0026lt;0.01; *** p\u0026lt;0.001, † McNemar test confirms the null hypothesis)\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5714867/v1/64b5f73684cdf034a2fe8653.png"},{"id":72691645,"identity":"8329bd1c-f89b-438f-afcd-a3f04ecca937","added_by":"auto","created_at":"2024-12-31 09:48:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":817214,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5714867/v1/191b72bb-50e6-4511-a747-335dc7282b91.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients","fulltext":[{"header":"Background","content":"\n\u003ch3\u003eIntroduction\u003c/h3\u003e\n\u003cp\u003eBreast cancer is the leading type of cancer among women worldwide, with 2.3\u0026nbsp;million new cases diagnosed and 670,000 deaths annually [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Israel, it is responsible for about one-third of invasive cancer cases annually [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBreast cancer treatment in Israel follows the clinical guidelines issued by ESMO [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and NCCN [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]; A biopsy is followed by surgery to remove the tumor, with chemotherapy before or after surgery according to tumor stage and with radiotherapy when appropriate. Living in a small country (22,145 square kilometers), with universal health coverage and many public and private medical service providers, Israeli breast cancer patients can choose where to receive treatment and can transfer from one care facility to another when they found it appropriate. The study analyzed the non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients.\u003c/p\u003e\n\u003ch3\u003eLiterature review\u003c/h3\u003e\n\u003cp\u003eTransferring from one care facility to another during breast cancer treatment was previously reported to occur in over one third of cases, and were linked to treatment delays and decreased survival: Bleicher and colleagues [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] studied the files of 622,793 US patients with non-metastatic invasive breast cancer and found that 36.6% of patients transferred care. The transfers added 7.3 days to time to surgery, 7.8 days in the case of chemotherapy, 8.7 days in the case of radiotherapy and 9.8 days in the case of endocrine therapy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all). Similarly, Heeg and colleagues [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] studied the files of 41,413 Dutch patients with breast cancer and found that 8.5% of them transferred to another hospital between diagnosis and first treatment; 4.9% before primary surgery and 24.8% before neo-adjuvant chemotherapy, especially in the case of patients under 40, thus delaying surgery by 5 to 9 days and neo-adjuvant chemotherapy by 9 days.\u003c/p\u003e \u003cp\u003eThe effects of treatment delays on breast cancer outcomes were studied by Bleicher and colleagues [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] who showed that in the cases of 94,544 stage I and II breast-cancer patients, specific mortality increased with every 60-day delay between diagnosis and breast cancer surgery (HR\u0026thinsp;=\u0026thinsp;1.13 for stage I and HR\u0026thinsp;=\u0026thinsp;1.06 for stage II). Mateo and colleagues [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] studied 351,087 breast cancer patients and found that overall survival declined for all patients for every month of operative delay (HR\u0026thinsp;=\u0026thinsp;1.104, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) regardless of hormone receptor status. Ward and colleagues [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] studied 140,615 patients with ductal carcinoma in situ and found that the added risk of death from all causes for each 30-day delay was 7.4% (HR 1.07; P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), regardless of tumor invasiveness.\u003c/p\u003e \u003cp\u003eBreast cancer treatment in Israel\u003c/p\u003e \u003cp\u003eInter-facility transfer of care during cancer treatment can be motivated either by the availability of a certain treatment option or by the patient's preference.\u003c/p\u003e \u003cp\u003eOn the availability side, Israel\u0026rsquo;s Health Insurance Law, provides high-standard cancer treatment free of charge in any of Israel's 44 public hospitals [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Under Israeli regulations, cancer patients can choose any public hospital but cannot choose the treating physician. In order to overcome the physician choice obstacle and to shorten waiting time, which can sometimes be lengthy in the public healthcare system[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], patients can turn to private medical services and finance them using private insurance plans, which are carried by some 92% of the Israeli population [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the Israeli healthcare system, biopsies can be performed either at a general hospital or an HMO clinics (the latter do not offer any other cancer-related services). Most general hospitals perform biopsies, surgery, and chemotherapy treatments, however only 10 hospitals perform radiotherapy (most located in central Israel), thus necessitating a transfer. Since cancer treatment requires a high level of trust between patient and physician, and since Israeli patients can choose their treating hospitals but not their treating physician, Israeli patients who do not fully trust their physician are actively involved in choosing their treating hospital and treating chemotherapy center, in an effort to improve their treatment and survival. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe Purpose of the study was to identify factors affecting facility transfers among breast cancer patients. We tracked the preferences and decisions of Israeli breast cancer patients in all steps of cancer treatment, as well as the facility transfers and their underlying reasons.\u003c/p\u003e \u003cp\u003eWhile most of the professional literature on the subject focuses on analyzing patient files, we interviewed the women themselves, which helped to illuminate the factors influencing the patient\u0026rsquo;s transfer decision.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe qualitative part of the study began with in-depth interviews held between February and November 2016, with 19 breast cancer survivors recruited from the breast cancer follow-up clinics at two Israeli hospitals. The participants consisted of Hebrew-speaking women aged 43 to 73 (average 58.2) who had been diagnosed with breast cancer up to five years earlier and now considered to be disease-free. The quantitative part of the study involved 179 Hebrew-speaking women aged 30 to 75 (average 57.5) who had also been diagnosed with breast cancer up to five years earlier and were considered disease-free at the time of the study. Participants were recruited between November 2016 and September 2018 from three breast cancer follow-up clinics.\u003c/p\u003e \u003cp\u003eParticipants had an average of 3.1 children, and all were Jewish. About 87% were members of Clalit Health Services (the largest HMO in Israel covering some 52% of the population) and the distribution of their income levels was similar to that of the general population. Participants were diagnosed with breast cancer at an average age of 55.3 years. About 62% had their biopsy done at a public hospital. All the participants had surgery to remove the tumor: 72% had a lumpectomy, with only a handful having a mastectomy or a bilateral mastectomy. About 85% of the participants had their surgery at a public hospital. About 45% had chemotherapy, 24% had neo-adjuvant therapy, 21% had adjuvant therapy and 84% had radiotherapy.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eA mixed methods study, beginning with 19 in-depth interviews with breast cancer survivors who were recruited from the breast cancer follow-up clinics at two Israeli hospitals. The interviews were carried out by the lead investigator (B.H.) and then recorded, transcribed, and analyzed using the ATLAS.ti qualitative data analysis software. The interviews were analyzed for key themes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and for the relationships between them.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFollowing the qualitative research, we created a ten-part, 78-item questionnaire, which tracked the patient's treatment progress from biopsy to recovery focusing on treatment decisions and the factors and perceptions that influenced them. This was accomplished by combining key patient themes from the qualitative part of the study with questions derived from previous studies of decision making among breast cancer patients [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVariables - The dependent variable for analysis was hospital transfer between any treatment steps and the independent variables included a variety of demographic and personal variables including age, number of children, education, religiosity, income, HMO, supplementary or private insurance, time since cancer diagnosis, treatment received, treatment location, key treatment decision, involvement levels, key consultant regarding cancer and more.\u003c/p\u003e \u003cp\u003eStatistical analysis - The quantitative data was analyzed using IBM SPSS Statistics, release 21.0. The margin of error was set to 5.0% and the study\u0026rsquo;s power was over 80%. We used Bivariate Analysis to identify the independent variables by correlating with each cancer treatment stage and then used a multinomial logistic regression to produce a model based on the main factors and covariate effects. Since some of the treatment steps had only a small number of patients, we used the McNemar test to detect differences between two related groups for a dichotomous dependent variable.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThe decision-making model used by breast cancer patients: qualitative perspective\u003c/h2\u003e \u003cp\u003eFollowing the qualitative interviews, we created a preliminary model of breast cancer decision-making, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, with three main steps: 1) Diagnosis \u0026ndash; The first step begins as a women has a routine screening or discovers a lump, has a biopsy, and finally receives a diagnosis of cancer. Several participants found this stage to be overwhelming. 2) Hospital/surgeon choice \u0026ndash; Once diagnosed, the patient chooses whether to have treatment at the diagnosing facility or transfer to a different one. Participants were focused on finding a caregiver they could trust. 3) Treatment negotiation \u0026ndash; The interviews revealed that some participants took an active role in the treatment decisions while others cooperated with their caregivers in deciding or stayed passive. Once again, the greater their trust in the caregiver at the diagnosing facility, the more likely participants were to accept the treatment recommendations and the less likely they were to choose more extreme treatment, such as a bilateral mastectomy. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the main factors influencing decision-making were staff attitude, family, fear, monetary issues, trust, and choice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFacility transfers among breast cancer patients: the quantitative study\u003c/h3\u003e\n\u003cp\u003eThe quantitative study data revealed that between 48.6% and 90.2% of participants transferred to another facility between treatment steps, with a prominent level of variation across treatment stages. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the number of participants in each treatment stage and the proportion of participants who transferred to another facility.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTransfers between biopsy and neo-adjuvant chemotherapy\u003c/p\u003e \u003cp\u003eFacility transfers between diagnosis and first treatment include transfers between the biopsy and neo-adjuvant chemotherapy or between the biopsy and surgery.\u003c/p\u003e \u003cp\u003eOf the 43 participants who underwent neo-adjuvant therapy, 29 (67.4%) transferred to a different facility. Of those 29, eight (27.5%) had their biopsy at an HMO clinic and 9 (31%) at a private clinic, requiring all 17 to transfer to a hospital for further therapy. 26 participants had biopsy at a hospital, 12 (46%) transferred to a different hospital to have neo-adjuvant chemotherapy and 14 remained at the same facility. Bivariate chi-square analysis found a correlation between level of education (high school, undergraduate, graduate) and facility transfer (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.013) and a weak correlation to the distance from the facility to the participant's home (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.09). The other logistic regressions did not demonstrate correlation.\u003c/p\u003e \u003cp\u003eTransfers between the biopsy and surgery\u003c/p\u003e \u003cp\u003eOf the 136 participants who had surgery without neo-adjuvant chemotherapy, 82 (60.3%) transferred to a different facility (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Of those who transferred, 38 (46.3%) had their biopsy at an HMO clinic, and 13 (15.8%) at a private clinic. One participant had both her biopsy and the surgical procedure at a large private hospital in Tel-Aviv. 84 participants had their biopsy at a general hospital, 27 (30.5%) transferred to a different hospital for surgery.\u003c/p\u003e \u003cp\u003e43 patients had neo-adjuvant chemotherapy before surgery, 23 (53.5%) transferred to a different hospital for surgery.\u003c/p\u003e \u003cp\u003eBivariate chi-square analysis found correlation between hospital transfers and biopsy facility type (clinic / hospital, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.000), religiosity (secular / religious, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.034), trust in the treating staff (trust / lack of trust, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.004) and proximity to the participant's home (low / high, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.000). Having neo-adjuvant chemotherapy was weakly associated with transferring (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.055). A multivariate logistic regression found correlations between transferring and treatment facility type (OR\u0026thinsp;=\u0026thinsp;15.15, 95%CI\u0026thinsp;=\u0026thinsp;6.35\u0026ndash;36.15, Sig\u0026thinsp;=\u0026thinsp;0.000), not having neoadjuvant chemotherapy (OR\u0026thinsp;=\u0026thinsp;4.12, 95%CI\u0026thinsp;=\u0026thinsp;1.57\u0026ndash;10.75, Sig\u0026thinsp;=\u0026thinsp;0.004) and staff mistrust (OR\u0026thinsp;=\u0026thinsp;2.58, 95%CI\u0026thinsp;=\u0026thinsp;1.22\u0026ndash;5.43, Sig\u0026thinsp;=\u0026thinsp;0.012). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e describes the factors influencing facility transfers between breast cancer treatments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMistrust was defined when a participant reported active involvement in certain treatment decisions and consulting with another physician or with a family member as part of their decision making. A participant who reported low levels of involvement and/or not consulting with another physician or family member was considered to have trust in the staff.\u003c/p\u003e \u003cp\u003eAs the effect of the treatment facility type was overpowering, a second logistic regression was performed without the biopsy facility type variable. It revealed that participants categorized as lacking trust showed a positive correlation with transferring to a different hospital for surgery (OR\u0026thinsp;=\u0026thinsp;2.21, 95%CI\u0026thinsp;=\u0026thinsp;1.20\u0026ndash;4.08, Sig\u0026thinsp;=\u0026thinsp;0.011).\u003c/p\u003e \u003cp\u003eTransfers between surgery and adjuvant chemotherapy\u003c/p\u003e \u003cp\u003e37 participants had adjuvant chemotherapy. Of those, 15 (40.5%) transferred to a different facility (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the four participants who had surgery at a private hospital, three (75%) transferred to a different facility. Among the 33 participants who had surgery at a public hospital, 12 (36.3%) transferred to another facility. Bivariate chi-square analysis found a correlation between the attitude of the treating staff at the operating hospital (good relationship / poor relationship, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.000) and transferring to a different facility. Weak correlation was found between the participant\u0026rsquo;s number of children (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.144), and between the hospital type (public / private, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.172) and transferring to a different facility. A logistic regression found correlations between the attitude of the treating staff and transferring to a different facility (OR\u0026thinsp;=\u0026thinsp;38.4, 95%CI\u0026thinsp;=\u0026thinsp;3.95-373.01, Sig\u0026thinsp;=\u0026thinsp;0.002). Due to the small number of participants in this stage, we used a McNemar test and could not reject the null hypothesis.\u003c/p\u003e \u003cp\u003eTransfers between surgery or adjuvant chemotherapy and radiotherapy\u003c/p\u003e \u003cp\u003e151 participants underwent radiotherapy. Of those, 129 (85.4%) underwent it at a different facility, while 12 (7.9%) had in-surgery radiotherapy as part of the surgical procedure. As mentioned earlier, only 10 hospitals in Israel are authorized to perform radiotherapy, most of them large hospitals located in central Israel. 136 of the participants were treated at smaller hospitals which do not offer radiation (most of the recruitment was performed by physicians in rural hospitals), thus forcing many patients to transfer to a larger hospital, offering radiotherapy. However, one of the small hospitals offers in-surgery radiotherapy, and 12 participants chose to have it. 15 participants had surgery at a larger hospital that offers radiotherapy, with nine patients (60%) transferring to a different facility for radiotherapy.\u003c/p\u003e \u003cp\u003eBivariate chi-square analysis found correlation between the participant's HMO (Clalit / other, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.002), the age group of their youngest child (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.009), radiation equipment at the facility (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.000), proximity to the participant\u0026rsquo;s home (High / low, Asymp. Sig\u0026thinsp;=\u0026thinsp;0.029), attitude of the treating staff (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.000), the recommendation of a trusted physician (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.028) and the recommendation of a trusted friend (Asymp. Sig\u0026thinsp;=\u0026thinsp;0.038) and transferring to another facility.\u003c/p\u003e \u003cp\u003eAs expected, the first logistic regression found a strong correlation between the lack of radiotherapy equipment at a facility and transferring to a different facility (OR\u0026thinsp;=\u0026thinsp;31.87, 95%CI\u0026thinsp;=\u0026thinsp;4.94-205.54, p\u0026thinsp;=\u0026thinsp;0.000), and the attitude of the treating staff (OR\u0026thinsp;=\u0026thinsp;8.32, 95%CI\u0026thinsp;=\u0026thinsp;1.25\u0026ndash;55.35, p\u0026thinsp;=\u0026thinsp;0.028). Since the presence of radiotherapy equipment had such a dominant effect on the findings, we performed a second regression which omitted that variable. It showed a positive correlation between the attitude of the treating staff and transferring to a different facility (OR\u0026thinsp;=\u0026thinsp;13.74, 95%CI\u0026thinsp;=\u0026thinsp;2.57\u0026ndash;73.38, p\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eBreast cancer is the leading cause of cancer among women all over the world. In Israel, breast cancer treatment is provided free of charge under the Israeli Health Insurance Law and follows international clinical guidelines such as those of ESMO[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and NCCN[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The fact that clinical guidelines and the health system\u0026rsquo;s structure create leeway in patient decision-making allows us to identify personal, non-medical factors that affect those decisions.\u003c/p\u003e \u003cp\u003eThe first part of the study involved preliminary qualitative interviews with 19 breast cancer survivors. The interview data analysis focused the study on the relationship with the caregivers and participant\u0026rsquo;s trust in them, as well as finding the right facility and the right physician. While facility transfer was mentioned only once in the interviews, patients who described bad attitude among the treating staff were more active in treatment decisions and considering more extreme treatments, such as bilateral mastectomy.\u003c/p\u003e \u003cp\u003eThe quantitative study, on the other hand, revealed high rates of facility transfer among the participants, ranging from 48\u0026ndash;90% depending on the treatment stage. The study findings for transfer rates are much higher than those found by Heeg and colleagues [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] who reported a rate of 4.9% before primary surgery and 24.8% before neo-adjuvant chemotherapy, and those found by Bleicher and colleagues [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] who reported a transfer rate of 39.6%. Bleicher and colleagues found that each transfer of care could delay treatment by 5\u0026ndash;9 days while other studies found that a 30-day treatment delay increases mortality by 7\u0026ndash;10% [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Thus, the high rate of transfer among breast cancer patients in rural Israel may be having a substantial effect on patient's survival and therefore understanding the underlying reasons for transfers of care is of great clinical importance.\u003c/p\u003e \u003cp\u003eThe study findings point out three key factors:\u003c/p\u003e \u003cp\u003e1. Treatment availability \u0026ndash; Many facility transfers were due to a lack of treatment availability. Thus, following a biopsy at an HMO surgical clinic the patient had to transfer to a hospital for surgery or neo-adjuvant chemotherapy, and patients having surgery at a rural hospital had to transfer to a centrally located hospital for radiotherapy. The effect of treatment availability on the regression analysis was so overwhelming that we had to analyze the transfers both with and without it. Since the OECD defines primary care to be a key pillar of a modern healthcare system[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], it is likely that additional cancer-related services, such as biopsies, surgical procedures and chemotherapy, will in the future be provided at rural clinics and hospitals; however, other services, such as radiotherapy, are likely to remain available only at secondary and tertiary care facilities, most of them located in metropolitan areas.\u003c/p\u003e \u003cp\u003e2. Trust \u0026ndash; Many of the transfers documented in the study were not motivated by availability of treatment and were therefore categorized as motivated by the patient's desire for better treatment. Since most hospitals in Israel provide both surgery and chemotherapy, the high rate of facility transfers between surgery and chemotherapy (53.5% between neo-adjuvant therapy and surgery and 48.6% between surgery and adjuvant therapy) is an indication that personal preference is a key factor. Thus, following a biopsy, many participants who transferred to a different facility were categorized as lacking trust in the staff, transferring to improve treatment outcomes. Similarly, following surgery, both participants needing adjuvant chemotherapy and participants needing radiotherapy reported transferring because of the attitude of the staff. Thus, staff attitude and personal trust appear to play a major role in the transfer decision.\u003c/p\u003e \u003cp\u003e3. Demographics \u0026ndash; The bivariate chi-square analysis showed that demographic factors such as religiosity, number and age of children, proximity to the facility and HMO membership influence the decision to transfer.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of the study\u003c/h2\u003e \u003cp\u003ePrevious studies analyzed samples of hundreds of thousands of breast cancer patients, and therefore the study small sample size is a shortcoming. However, this is offset by the depth of the research. We questioned each respondent about her preferences and motivations to understand the effect of the patient's preferences, as compared to the effect of treatment availability. Nonetheless, using a larger sample of patients would improve the analysis.\u003c/p\u003e \u003cp\u003eWe used questionnaires to track the respondent's treatment process but did not have access to their files or their exact diagnosis. Thus, the study insights may have been biased by the participant's recall ability and their subjective perceptions of the treatment process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFurther research\u003c/h2\u003e \u003cp\u003eA future study in cooperation with one of the leading HMOs is being planned, with the goal of analyzing larger datasets of facility transfers among cancer patients and understanding their effect on a patient's survival.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThe research was conducted under the guidance and supervision of Prof. Manfred Green and Dr. Itzhak Zaidis.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Israel National Institute for Health Policy Research. Grant number r-6-2015.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors have no financial or non-financial interests to declare.\u0026emsp;\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eBoaz Hovav - Study conception and design, material preparation, data collection and analysis, draft writing, comments and editing.\u003c/p\u003e\n\u003cp\u003eShuli Brammli-Greenberg - Study conception and design, writing supervision, comments and editing.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are not publicly available due to medical confidentiality but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eEthics Approval\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the principles of the Declaration of Helsinki. The research protocol was approved by the IRB in each of the recruiting clinics and by the ethical committee of the University of Haifa.\u003c/p\u003e\n\u003cp\u003eConsent to participate\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. Breast cancer. 2024.\u003c/li\u003e\n\u003cli\u003eNational Cancer Registry. \u003cem\u003eBreast cancer among Israeli women - Inforamation updateOctober 2024\u003c/em\u003e. Jerusalem, 2024.\u003c/li\u003e\n\u003cli\u003eLoibl S, Andr\u0026eacute; F, Bachelot T \u003cem\u003eet al.\u003c/em\u003e Early breast cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up ☆. \u003cem\u003eAnnals of Oncology\u003c/em\u003e 2024;\u003cstrong\u003e35\u003c/strong\u003e:159\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eGradishar WJ, Moran MS, Abraham J \u003cem\u003eet al.\u003c/em\u003e Breast Cancer, Version 3.2024, NCCN Clinical Practice Guidelines in Oncology. \u003cem\u003eJournal of the National Comprehensive Cancer Network\u003c/em\u003e 2024;\u003cstrong\u003e22\u003c/strong\u003e:331\u0026ndash;57.\u003c/li\u003e\n\u003cli\u003eBleicher RJ, Chang C, Wang CE \u003cem\u003eet al.\u003c/em\u003e Treatment delays from transfers of care and their impact on breast cancer quality measures. \u003cem\u003eBreast Cancer Res Treat\u003c/em\u003e 2019;\u003cstrong\u003e173\u003c/strong\u003e:603\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eHeeg E, Schreuder K, Spronk PER \u003cem\u003eet al.\u003c/em\u003e Hospital transfer after a breast cancer diagnosis: A population-based study in the Netherlands of the extent, predictive characteristics and its impact on time to treatment. \u003cem\u003eEuropean Journal of Surgical Oncology\u003c/em\u003e 2019;\u003cstrong\u003e45\u003c/strong\u003e:560\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eBleicher RJ, Ruth K, Sigurdson ER \u003cem\u003eet al.\u003c/em\u003e Time to surgery and breast cancer survival in the United States. \u003cem\u003eJAMA Oncol\u003c/em\u003e 2016;\u003cstrong\u003e2\u003c/strong\u003e:330\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eMateo AM, Mazor AM, Obeid E \u003cem\u003eet al.\u003c/em\u003e Time to Surgery and the Impact of Delay in the Non-Neoadjuvant Setting on Triple-Negative Breast Cancers and Other Phenotypes. \u003cem\u003eAnn Surg Oncol\u003c/em\u003e 2020;\u003cstrong\u003e27\u003c/strong\u003e:1679\u0026ndash;92.\u003c/li\u003e\n\u003cli\u003eWard WH, DeMora L, Handorf E \u003cem\u003eet al.\u003c/em\u003e Preoperative Delays in the Treatment of DCIS and the Associated Incidence of Invasive Breast Cancer. \u003cem\u003eAnn Surg Oncol\u003c/em\u003e 2020;\u003cstrong\u003e27\u003c/strong\u003e:386\u0026ndash;96.\u003c/li\u003e\n\u003cli\u003eBen Shetreet I, Woolf LL. \u003cem\u003eHealth Services in Israel 6th Edition\u003c/em\u003e. Jerusalem, 2015.\u003c/li\u003e\n\u003cli\u003eBowers L, Chernichovsky D. \u003cem\u003eYour Place in Line Waiting Times in Israel\u0026rsquo;s Public Hospitals\u003c/em\u003e. Jerusalem, 2016.\u003c/li\u003e\n\u003cli\u003eBrammli-Greenberg S, Yaari I, Avni E. \u003cem\u003e\u003cspan dir=\"RTL\"\u003eדעת הציבור על רמת השירות ותפקוד מערכת הבריאות 2018\u003c/span\u003e\u003c/em\u003e. Jerusalem, 2020.\u003c/li\u003e\n\u003cli\u003eHovav B, Brammli-Greenberg S. Involvement levels of breast cancer patients \u0026ndash; seeking trusted hospital and physician. \u003cem\u003eJ Health Psychol\u003c/em\u003e 2021;\u003cstrong\u003eEpub ahead\u003c/strong\u003e, DOI: 10.1177/13591053211062350.\u003c/li\u003e\n\u003cli\u003eDegner LF, Sloan JA, Venkatesh P. The Control Preferences Scale. \u003cem\u003eCanadian Journal of Nursing Research\u003c/em\u003e 1997;\u003cstrong\u003e29\u003c/strong\u003e:21\u0026ndash;43.\u003c/li\u003e\n\u003cli\u003eBallinger RS, Mayer KF, Lawrence G \u003cem\u003eet al.\u003c/em\u003e Patients\u0026rsquo; decision-making in a UK specialist centre with high mastectomy rates. \u003cem\u003eBreast\u003c/em\u003e 2008;\u003cstrong\u003e17\u003c/strong\u003e:574\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eCollins ED, Moore CP, Clay KF \u003cem\u003eet al.\u003c/em\u003e Can women with early-stage breast cancer make an informed decision for mastectomy? \u003cem\u003eJournal of Clinical Oncology\u003c/em\u003e 2009;\u003cstrong\u003e27\u003c/strong\u003e:519\u0026ndash;25.\u003c/li\u003e\n\u003cli\u003eMaly RC, Frank JC, Marshall GN \u003cem\u003eet al.\u003c/em\u003e Perceived Efficacy in Patient-Physician Interactions (PEPPI): Validation of an instrument in older persons. \u003cem\u003eJ Am Geriatr Soc\u003c/em\u003e 1998;\u003cstrong\u003e46\u003c/strong\u003e:889\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eMorgan D, Mueller M. \u003cem\u003eSpending on Primary Care: First Estimates\u003c/em\u003e., 2018.\u003c/li\u003e\n\u003cli\u003eOECD. \u003cem\u003eRealising the Potential of Primary Health Care, OECD Health Policy Studies\u003c/em\u003e. Paris: OECD Publishing, 2020.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast Cancer, Transfer of care, Facility transfer, Rural, Patient preferences, Trust, Quantitative research","lastPublishedDoi":"10.21203/rs.3.rs-5714867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5714867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eInter-facility transfers of care during breast cancer treatment occurred in 37% of cases in previous studies, leading to treatment delays and decreased survival. The reasons for such transfers were scarcely studied. The study aimed to identify the factors affecting facility transfers among breast cancer patients.\u003c/p\u003e\u003ch2\u003ePatients and Methods:\u003c/h2\u003e \u003cp\u003e198 Hebrew-speaking Israeli women, aged 32 to 81, diagnosed with breast cancer up to five years earlier, now considered disease-free participated in a mixed-methods study. 19 in-depth qualitative interviews were analyzed and used to construct a ten-part, 78-item questionnaire, which tracked 179 patient's treatment from biopsy to recovery, focusing on treatment decisions and the factors and perceptions influencing them.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eParticipants reported high rates of inter-facility transfers. 60% of the participants transferred between biopsy and surgery, motivated by facility type (OR\u0026thinsp;=\u0026thinsp;15.15) and level of trust (OR\u0026thinsp;=\u0026thinsp;2.58). 67% transferred between the biopsy and neo-adjuvant chemotherapy, and about 53% of those who had neo-adjuvant chemotherapy transferred prior to surgery. Following surgery, participants requiring radiation therapy transferred 90% of times, driven by the low availability of radiotherapy equipment in rural Israel (OR\u0026thinsp;=\u0026thinsp;31.87) or by the staff\u0026rsquo;s attitude (OR\u0026thinsp;=\u0026thinsp;8.32). Participants who needed adjuvant chemotherapy transferred 49% of cases, motivated by the staff\u0026rsquo;s attitude (OR\u0026thinsp;=\u0026thinsp;38.4) and transferred again in 81% of the cases for radiotherapy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eLower availability of cancer treatments in rural areas, lack of trust in the facility staff and demographic factors lead to inter-facility transfers that may lead to treatment delays and increased morbidity.\u003c/p\u003e","manuscriptTitle":"The non-medical factors affecting the level of inter-facility transfers of care among rural Israeli breast cancer patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-31 09:23:52","doi":"10.21203/rs.3.rs-5714867/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b4cd94f0-24de-40c6-a4ba-48f3aecb74b3","owner":[],"postedDate":"December 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-31T09:23:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-31 09:23:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5714867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5714867","identity":"rs-5714867","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}