{"paper_id":"3eb24e52-926b-4dae-9781-522a29219b5a","body_text":"Real-world data to improve Organ and Tissue Donation Policies: Lessons learned from the Tissue and Organ Donor Epidemiology Study | 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 Real-world data to improve Organ and Tissue Donation Policies: Lessons learned from the Tissue and Organ Donor Epidemiology Study Melissa A. Greenwald, Hussein Ezzeldin, Emily A. Blumberg, Barbee I Whitaker, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4293660/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Nov, 2024 Read the published version in Health Research Policy and Systems → Version 1 posted 9 You are reading this latest preprint version Abstract Background: The transplantation of human organs, and some human tissues, is often the only life-saving therapy available for serious and life-threatening congenital, inherited, or acquired diseases. However, it is associated with a risk of transmission of communicable diseases from donor to recipient. It is imperative to understand the characteristics of the donor population to inform policies that protect recipient safety. The Tissue and Organ Donor Epidemiology Study (TODES) was a pilot project designed to identify and collect standardized information on deceased persons referred for organ, tissue, and/or eye donation, and to estimate (to the extent possible) infectious disease prevalence and incidence of HIV, HBV, and/or HCV in this population. TODES is summarized here to shed light on addressable limitations on accessing data needed for transplant recipient safety. Limitations, future research needs, and potential pathways to solve the remaining data needs are explored. Methods: Retrospective data for all deceased donors during a 5-year period from 2009 to 2013 were obtained from participating organ procurement organizations (OPOs), tissue establishments, and eye banks. These decedent data on actual donors and potential donors were used to ascertain whether the available real-world data (RWD) could be used to inform donor screening and testing policy. Results: The TODES database contains 291,848 records received from nine OPOs and 42,451 records received from four eye banks. Data were analyzed from deceased donors with at least one organ, tissue, or ocular tissue recovered with the intent to transplant. Results for potential donors were not analyzed. Available RWD at the time of the TODES study were not fit-for-purpose to help characterize the organ- and tissue eye donor populations and/or to inform donor screening policy. Conclusions: Recent advances in electronic data collection systems make it more realistic to now collect fit-for-purpose RWD that address the research needed to improve transplant safety. organ transplantation tissue transplantation communicable diseases donor screening donor testing real world data health information exchange interoperability patient safety traceability Figures Figure 1 Figure 2 Background Human organ, tissue, and eye (OTE) transplants provide tremendous individual and societal benefits. However, they are also associated with the risk of disease transmission to OTE transplant recipients. Many risk mitigation strategies are currently in place, including extensive donor screening and testing for active and latent infections. Nevertheless, donor-derived infections have occurred ( 1 – 8 ) and are not anticipated to be fully preventable, highlighting the need for continued reassessment of how to best evaluate donors to optimally balance safety with availability. To assess the effectiveness of current donor screening and testing policies and to further optimize those policies, data regarding the background rates of communicable diseases in donor populations are necessary. The need for such data has been emphasized by federal and non-federal stakeholders alike in public workshops and white papers (Table 1 ). Table 1 Summary of forums by federal and non-federal stakeholders and recommendation and findings Forum Recommendation The joint CDC, FDA, and HRSA 2005 workshop ( 31 ) • Communication networks should be improved • A unique donor identifier for both organs and tissues should be created • Education and dissemination of information to clinicians and transplant patients should be strengthened • A framework for clinicians to report transplant-associated adverse events should be clearly delineated • A notification algorithm for tracking among and between organs and tissues should be designed Advisory Committee on Blood Safety and Availability (ACBSA) 2006 ( 32 , 33 ) • Called for a public-private partnership “biovigilance” initiative to collect analyze and report on the outcomes of collection and transfusion and/or transplantation of blood components and derivatives, cells, tissues, and organs. 2007 workshop, “Organ and Tissue Safety Workshop 2007: Advances and Challenges ( 34 ) • Review the epidemiology of transmission of infection and malignancy associated with allografts (i.e., organs, tissues, eyes) • Understand existing reporting standards and requirements, and enhance communication regarding safety issues between the organ and tissue communities, regulatory agencies, and other stakeholders • Evaluate progress on development of the TTSN, and other interventions to detect and prevent transmission events • Examine advances in diagnostic and screening technologies that could be applied to the enhancement of safety of allograft transplantation 2009 PHS White paper ( 32 ) • Identified 8 gaps for biovigilance in HCT/P and solid organ. Given the policy challenges, the recommendations were: o Government resource support for a national biovigilance program to monitor and enhance safety of blood, organs, and HCT/Ps o Integration of systems within the government and those within the private sector, involving blood, organs, and HCT/Ps, including all related voluntary and mandatory adverse event reporting systems o Enhance mechanisms for surveillance, including sentinel reporting and investigation, and comprehensive surveillance that features benchmarking 2010 Emerging Infectious Diseases Workshop ( 5 , 35 ) • The unknown sensitivity and specificity of current medical and behavioral history tools to screen donors for risk factors associated with infectious agents • The difficulty in distinguishing acute from chronic or persistent infections using standard testing modalities, especially given the prolonged window period of many serological assays and the limited sensitivity and specificity of NAT for some infections especially those acquired within days of donation • The limited ability of NAT to identify infections not associated with active bloodstream involvement • The variability in performance between different assays, including those used for donor screening and those used for diagnostic reasons, where performance characteristics have not been evaluated in the deceased donor setting; this may limit the ability of transplant personnel to compare and interpret some tests 2013 PHS guideline to improve organ recipient outcomes ( 36 ) • Updated 1994 guideline that covered only HIV in organs and tissues • Reduce the risk of HIV, HBV, and HCV transmission through organ transplantation • Gaps in the literature and quality of evidence affected the ability to reach firm conclusions for organs in certain interventions • Emphasized the need for putting a system in place allowing tracking between a common deceased donor and ( 1 ) recovered organs, ( 2 ) recovered associated blood vessel conduits, and ( 3 ) recovered tissues and eyes to facilitate notification when a donor-derived disease transmission is suspected • Further research was recommended in numerous areas, including estimating incidence and prevalence of HIV, HBV, and HCV among deceased donors, and developing standardized algorithms for discrimination of initially reactive (positive) organ donor immunoassay and NAT results 2020 PHS Guideline Assessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection ( 18 , 37 – 39 ) • Updated evidence review of recent organ-transplant–specific evidence, intended to increase the use of organs while continuing to maintain transplant recipient safety • Changes from the 2013 PHS guideline: o Identifying a timeframe for recipient pretransplant testing o Updating the criteria for identifying donors at risk for undetected donor HIV, HBV, or HCV infection; the removal of any specific term to characterize donors with HIV, HBV, or HCV infection risk factors; universal organ donor HIV, HBV, and HCV nucleic acid testing; and universal posttransplant monitoring of transplant recipients for HIV, HBV, and HCV infections • Removing the following risk criteria as no longer applicable for assessing potential disease transmission from donors to recipients: o Woman who has had sex with a man who has had sex with another man o Newly diagnosed or treated syphilis, gonorrhea, chlamydia, or genital ulcers o Hemodialysis o Hemodiluted blood specimen used for donor HIV, HBV, and HCV testing o Child (aged ≤ 18 months) born to a mother at increased risk for HIV, HBV, or HCV infection o Child breastfed by a mother at increased risk for HIV infection Abbreviations: TTSN, Transplantation Transmission Sentinel Network; HCT/P, Human cells, tissues, and cellular and tissue-based products; NAT, nucleic acid test; HBV, hepatitis B virus; HIV, human immunodeficiency virus; HCV, hepatitis C virus; PHS, Public Health Services The Department of Health and Human Services (HHS) is charged with taking measures to minimize the risk of transmission of disease from donated OTE while optimizing product availability through relevant agencies, including the Health Resources and Services Administration (HRSA), Centers for Disease Control and Prevention (CDC) ( 9 ), Food and Drug Administration (FDA), and the Centers for Medicare and Medicaid Services (CMS). From 2012–2016, HHS conducted the Tissue and Organ Donor Epidemiology Study (TODES , ) ( 10 ), a demonstration project designed to evaluate the ability to identify and collect data on deceased persons referred for OTE donation in a standardized manner. This evaluation was accomplished by estimating prevalence and (to the extent possible) incidence of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV), using existing data sources (namely, real-world data (RWD)) ( 11 ), and to determine whether these data were suitable (or “fit-for-purpose”) for assessing donor communicable disease risk factors and informing donor screening and testing policy. If the available data sources were not fit-for-purpose, TODES would identify and propose solutions for those gaps. TODES provides a broad overview of the transplantation data collection infrastructure, highlights the complexity of the OTE donation processes, identifies gaps in data collection systems, and underscores the challenges to implementing standardized data collection. Bridging these gaps is important, especially given that donors may donate OTE within systems that are not able to identify and communicate transplantation transmission risks effectively and efficiently. For example, recent tuberculosis (TB) transmissions via human bone tissue containing viable cells ( 2 , 8 ) demonstrated that the current donor screening practices failed to prevent TB transmission. There were significant challenges faced in identifying all recipients of the contaminated product (( 12 ), which further resulted in challenges identifying secondary transmissions to healthcare workers ( 13 ). In this manuscript, we provide an overview of the transplant process, explain the TODES approach in collecting RWD, and highlight relevant findings from the collected data. Given the lessons learned from TODES, we explore current strategies that can pave way for future studies to overcome industry challenges and identify practical solutions that can improve the balance between safety and availability of OTE transplantation. Methods Study Overview The HHS-sponsored TODES study had three overarching goals: ( 1 ) develop a study design or framework to effectively collect and analyze demographic, screening, and infectious disease testing data obtained from deceased OTE donors, including referral-only donors, in a standardized manner; ( 2 ) identify challenges to obtaining such data in a consistent and standardized format; and ( 3 ) identify limitations and sources of biases from data captured in this study. HHS funding was announced in 2011, the study contract was awarded in 2012, and the final report was published in July 2016 ( 10 ). The TODES working group (WG) comprised multiple federal and non-federal stakeholders with experience in OTE transplantation. Prospective OTE establishments were contacted for recruitment. Characteristics of potential study participants are listed in Table 2 . Table 2 Characteristics of TODES Participant Records by Org Type Org Type Org Code All Records Referrals only Records Records Representing Potential Donors n Records with UNOS Data/OPO Linked Data n Record with any Test Results n Organ Donor Records with any Test Results n Tissue Donor Records with any Test Results n Eye Donor Records with any Test Results n Referrals- Only Records with any Test Results n OPO A 5,611 1,455 4,156 751 1,158 751 691 491 104 B 169,760 164,347 5,413 1,381 1,716 1,384 663 2 238 c 3,967 42 3,925 652 3,949 652 3,621 0 33 D 1,867 2 1,865 618 1,860 618 1,370 562 2 F 8,302 0 8,302 1,135 8,299 1,134 7,636 4,196 0 I 4,234 235 3,999 1,366 4,060 1,371 3,180 345 117 K 760 82 678 644 644 644 205 199 0 L 96,386 89,703 6,683 724 870 725 359 252 101 M 961 61 900 870 954 870 380 318 60 Total 291,848 255,927 35,921 81,41 23,510 8,149 18,105 6,365 655 Eye-bank E 23,044 0 23,044 0 22,924 0 9,266 22,924 0 G 11,083 417 10,666 0 9,873 0 0 9,663 210 H 2,644 70 2,574 0 2,500 0 0 2,434 66 J 5,680 0 5,680 0 5,168 203 2,399 5,168 0 Total 42,451 487 41,964 0 40,465 203 11,665 40,189 276 Source: adapted from TODES report Referrals-only records, UNOS Matches records, Records with any test results, Organ, tissue, and eye records with any Test Results. Based on all records received; includes known duplicates that were removed in subsequent analyses. The Organ, Tissue, and Eye Donors with any Test Results are not mutually exclusive, so the record totals may add up to a value greater than that reported in the Records with any Test Results column. OPO B and Eye Bank E were the only participants that submitted records that could be linked. Linkage of the 169,760 records submitted by OPO B and the 23,044 records submitted by Eye Bank E, resulted in 7,534 records in each dataset that were determined to be matching organ and/or tissue/eye donors. For organs, information about potential donors, also called “referrals-only records,” is entered into one of the OPO’s computer systems and is assigned a UNOS ID. However, if the donor is found ineligible to donate organs, the donor records are not shared with UNOS and therefore would be unavailable in the OPTN dataset; if eligible for tissue donation, a UNOS ID is used, and other donor ID coding is also used. The “referrals-only records” column contains records with no indication of donor type (organ, tissue, or eye), defined to have not resulted in donation. Abbreviations: OPO, organ procurement organization; org, organization; UNOS, United Network for Organ Sharing; OPTN, Organ Procurement and Transplantation Network A staff member from each participating establishment provided feedback about their organization, data collection methods, and donor population. As noted in Table 3 , some potential participants were unable to provide the data required or were unable to participate for other reasons. Significant variation in the practice of procuring information about testing for infections impacted the ability to accrue accurate and reliable RWD. As a result of the provided feedback, several sources of retrospectively deidentified RWD were obtained and reviewed for both referred potential donors and actual donors during the 5-year period from 2009 to 2013. Table 3 Prospective TODES Participants by OPTN Region and Final Participant Types OPTN Region No. and Type of Prospective Participants No. and Type of Final Participants a 1 1 (one OPO) 9 OPOs 4 Eye Banks 2 2 (two OPOs) 3 5 (four OPOs; one eye bank) 4 2 (two OPOs) 5 4 (three OPOs; one eye bank) 6 2 (one OPO; one eye bank) 7 2 (two OPOs) 8 2 (one OPO; one eye bank) 9 1 (one OPO) 10 4 (two OPOs; two eye banks) 11 4 (two OPOs; two eye banks) Initial information was obtained from 29 potential study participants:21 OPOs selected by AOPO and work group participants representing all 11 OPTN regions, and eight eye banks identified by EBAA. While six of the largest tissue processors also discussed their process of donor data collection, it is notable the working group determined that due to lack of a common donor identification across organ, eye, and tissues, obtaining data directly from tissue processors or from testing laboratories would likely result in duplicate donor data reporting. After RWD sources were identified for the study, 13 study participants were able to provide tissue donor-level data for analysis (9 OPOs and 4 eye banks). a Final Participants’ OPTN regions were not provided. Abbreviations: EBAA, Eye Bank Association of America; No..number; OPO, organ procurement organization; OPTN, Organ Procurement and Transplantation Network; RWD, real-world data The study also collected retrospective data from 2009 through 2013 for decedent donors. The final organ donor data was obtained from the Organ Procurement and Transplantation Network (OPTN) and organ procurement organizations (OPOs). While the final tissue donor data was obtained from eye banks and OPOs that recovered tissue, no usable data were available from tissue establishments (TEs). These data included basic demographic information, limited medical history and behavioral risk data, and infectious disease test results, if available. A data dictionary was developed, data were obtained, a TODES database was established, and data were analyzed. The data dictionary and other details about the study are available for review in the original study report ( 10 ). Overview of Organ, Eye and Tissue Transplantation Process Figures 1 and 2 illustrate the complex process of OTE donation and transplantation. This context is essential to understanding the challenges encountered in obtaining data and subsequently, TODES results. OTE donation processes are similar except for some differences in the timing of donor screening and testing, as organs and eyes must be procured and transplanted in a short time window, whereas most tissues can be stored for longer periods of time. Results Table 2 summarizes all records received by TODES, stratified by organization type (Org Type: OPO or eye bank) and participant (Org Code: A-M and E-J, where the letters are used to deidentify the organization). The TODES database contains 291,848 records received from nine OPOs and 42,451 records received from four eye banks. The majority of the donor records are males (average 63%, range 62.6–63.9%). Most of the OPO records received (88%, 255,927/291,848) do not indicate donor type; of those, 254,050 (87%) are from two participants (B and L). About 1% (487/42,451) of the records received from eye banks have no indication of donor type. The link between records received from OPO and United Network for Organ Sharing (UNOS) is indicated in Table 4 . While 8,141 OPO records can be linked to OPTN donor data received from UNOS, 1,158 UNOS records with IDs in the OPTN data cannot be linked to OPO data (OPO- UNOS+, Table 4 ). This mismatch occurs because OPOs typically assign a UNOS ID when a patient is identified as a potential donor, but many potential donors fail to become candidate organ donors during the screening process. However, some of those candidates may still become tissue donors, depending on the reason for not recovering organs. Records of actual organ donors are provided to UNOS; a total of 88% (range: 60.2–100%, OPO + UNOS+, Table 5 ) of records in UNOS dataset were found in datasets shared by OPOs. Table 4 Linkage Between Data from UNOS and OPOs Org Code Total Records in UNOS Dataset Record Count: OPO + UNOS- Record Count: OPO- UNOS+ Record Count: OPO + UNOS+(%) Record Count: Discrepant Data in Variable Fields A 1248 4860 497 751 (60.2) 229 B 1382 168379 1 1381 (99.9) 29 C 654 3315 2 652 (99.7) 0 D 629 1249 11 618 (98.3) 57 F 1135 7167 0 1135 (100) 1 I 1458 2868 92 1366 (93.7) 490 K 644 116 0 644 (100) 50 L 724 74534 0 724 (100) 0 M 1425 91 555 870 (61.1) 0 Source: adapted from TODES report Data records provided by each OPO were merged with records obtained from UNOS. The linkage between data from UNOS and OPOs was produced from merging the data records. % = percent of all the records found in UNOS that were matched with OPO; + = present; - = absent Abbreviations: OPO, organ procurement organization; org, organization; UNOS, United Network for Organ Sharing Table 5 Characteristics of Potential Donors in the TODES Database by Year Year Records n Male % Female % Organ Donors %* Tissue Donors %† Eye Donors %¶ Consent/ Authorization Documented % 2009 12,871 62.6 37.4 10.2 51.3 74.0 97.2 2010 13,527 63.3 36.7 10.5 53.1 71.5 97.4 2011 14,198 63.9 36.1 13.3 54.1 71.7 94.1 2012 16,272 63.3 36.7 11.5 49.9 74.0 91.8 2013 17,876 63.2 36.8 11.1 49.7 75.1 90.1 2009–2013 74,744 63.3 36.7 11.3 51.5 73.4 93.8 Source: adapted from TODES report Based on all records received; excludes known duplicates * % of donors with at least one organ recovered for transplant † % of donors with at least one tissue recovered for transplant ¶ % of donors with at least one ocular tissue recovered for transplant About 8% (23,510/291,848; range 1%-100%) of total OPO records received had at least one infectious disease test result compared to 93% (40,465/42,451; range 89%-99%) of total eye bank records received (Table 2 ). The records with any test results were stratified into three groups by donor type (organ donors, tissue donors, and eye donors); if donor type was not indicated, it was defined as a referrals-only record for any test results. Such low percentages of referral-only records (e.g., no organs were recovered) with at least one test in an OPO dataset occurred because tissue donor test results were not commonly shared with the OPO at that time, even when individuals from whom tissue was recovered were identified as tissue donors. If the individual was determined to be HIV, HBV, or HCV positive, the donated tissues were deemed ineligible for tissue transplantation purposes per FDA regulations. Among the 23,510 records with test results in the OPO dataset, only 8,149 (approximately 35%) were organ donor records; by contrast, among the 40,465 recorded in the eye-bank dataset, only 203 (< 1%) were organ donors. For tissue-donor records with at least one test result, 18,105 records were from OPOs and 11,665 from eye banks. For eye-donor records only, 6,365 were from OPOs and 40,189 from eye banks. A small number of referrals-only records, 655 from OPOs and 276 from eye banks, had at least one test result. In this study, the referrals-only data were ultimately excluded from analysis because a) most did not have any test results associated with the test data, and b) the data came from a subset of the organizations in the dataset. This indicates that, with the current system, reliable data cannot be obtained about all potential organ or tissue donors, which is important information contributing to understanding the baseline infectious disease risks associated with OTE donor populations. As a result, data were analyzed only from deceased donors with at least one recovered organ, tissue, or ocular tissue with the intent to transplant. The Public Health Service (PHS) 2013 guideline ( 14 ) provides 11 risk factors associated with an increased likelihood of recent HIV, HBV, or HCV infection amongst organ donors. Organ donors with one or more of these risk factors were identified as at “increased risk” for infections in the UNOS dataset. Table 6 summarizes the increased-risk indicator stratified by year in the UNOS dataset, which was available for almost all organ donors (99.8%). According to the five-year-period dataset, 10.1–16.2% of organ donors per year (with an average of 13.9%) were classified as increased-risk donors. Donors missing this information did not exceed 0.2% per year. Donating with a risk factor is permissible only for organ donors. Per 21 CFR Part 1271 (not applicable to organs), potential tissue (including ocular) donors with risk factors for certain infectious diseases are ineligible for donation, so data regarding “increased risk” donors for tissue and eye donation do not exist. Table 6 Infectious Disease Risk Status * of Organ Donors by Year Year Records n † Yes n (%) No n (%) Not Done n (%) Missing n (%) 2009 1,266 128 (10.1) 1,132 (89.4) 4 (0.3) 2 (0.2) 2010 1,359 178 (13.1) 1,179 (86.7) 0 (0.0) 2 (0.2) 2011 1,830 250 (13.7) 1,578 (86.2) 0 (0.0) 2 (0.1) 2012 1,809 276 (15.3) 1,532 (84.7) 0 (0.0) 1 (0.1) 2013 1,877 304 (16.2) 1,573 (83.8) 0 (0.0) 0 (0.0) 2009–2013 8,141 1,136 (13.9) 6,994 (85.9) 4 (0.1) 7 (0.1) Source: adapted from TODES report Risk status of infectious disease was obtained from UNOS data * Infectious disease risk status is an assessment of risk for blood-borne disease transmission per 2010 PHS guidelines, i.e., the organ donors who met one or more criteria considered as behavioral or medical risk factors for recent HIV infection. † Represents donor records from OPOs that can be linked to donor records received from UNOS Discussion and Conclusions This effort highlights multiple lessons learned regarding knowledge gaps and challenges of using RWD that can better inform regulatory decision-making. Importantly, findings from the data captured by TODES led to precluding its use for policy decisions. First, the data were determined to not be fit-for-purpose, which was not surprising given the data provided by the organizations were collected to support business operations rather than to address research and surveillance questions. Specifically, available RWD data could not identify duplicate data among tissue donors, provide a tissue donation denominator, or ascertain a representative sample of donors. Second, it was not possible to ascertain a comprehensive understanding of the true infectious disease status. Supplemental tests were rarely performed to verify positive or indeterminate test results, presumably because of the lack of appropriately labeled supplemental (i.e., “confirmatory”) tests, lack of adequate specimen volume, inability to sequentially follow deceased donors to document the evolution of infectious disease test markers, and lack of regulatory or policy requirements to perform supplemental testing. Furthermore, testing data of potential non-transplantation donors—e.g., that likely had positive test results or identified communicable disease risks—were largely unavailable, and if available, data were incomplete. Third, the various testing protocols that estimated infectious disease marker prevalence lacked standardization and included a variety of assay types such as donor screening and diagnostic assays (ST 1). Fourth, donors from OPO- and TE- evaluated datasets cannot be uniquely identified in large part because donors lack a common identifier between the organ and tissue/eye transplantation pathways as well as within the tissue/eye pathway when tissues go to more than one establishment. As such, any assembled dataset contains a mixture of test results (i.e., positive results with no further testing, inconclusive results with no further testing, positive results with subsequent testing, and negative results with subsequent testing), severely impacting the interpretability and usefulness of the data. TODES focused on data available for OTE donors that might be used to characterize the donor populations to inform donor screening and testing policy. However, determining how these data are part of an interconnected system needed to maximize overall OTE transplantation safety is also important. Multiple facets contribute to maximize transplantation safety. These include: i) donor selection (defining and identifying potential donors, donor screening and testing information); ii) careful manufacturing practices (processing practices that both prevent contamination and cross-contamination and that remove or inactivate contamination to the extent possible while maintaining utility of the product); and iii) identifying and investigating adverse events (to learn about the causes to inform improved policies and practice, and to quickly identify other recipients to prevent further adverse event occurrence). These facets of transplant safety require traceability of tissues from the time of considering a potential donor all the way through to the transplantation/ implantation to a recipient. Ideally, donor evaluation and transplantation outcomes data collection could also be used as part of efforts to proactively identify emerging infectious disease threats. The TODES study participants agreed that interventions that can yield benefits to transplantation safety include better communication, better identification methods, better education, etc. A comprehensive list is presented in ST 2. These interventions are consistent with the conclusions of the Transplantation Transmission Sentinel Network (TTSN) pilot program that was developed to collect data on donation, tissue implantation, and adverse events ( 15 ). The authors of the TTSN program concluded that eye and tissue tracking from recovery to implantation will be necessary before a sentinel network system can be operable, which would require common identifiers and nomenclature. They further stated that the absence of a U.S. sentinel network may result in future transmission events that could have been otherwise preventable. There is a clear need for such an integrated system for OTE transplantation data collection. The ways in which this can be accomplished is further explored in this discussion. Study limitations TODES had some limitations. Data integration from different sources (e.g., eye banks, large TEs, and large laboratories that provide infectious disease testing) was challenging, which resulted in excluding those sources and procuring tissue donor data only from OPOs that were also tissue recovery establishments. Thus, TODES data is not representative of national organ and tissue donor/donation data. Also, the 2009–2013 donor data collected by TODES reflect the recommendations in the 1994 PHS guidelines ( 16 ) that do not address later guideline development (Table 1 ) in defining “increased risk” organ donors. While the 1994 PHS guidelines were designed to reduce the risk of HIV transmission by screening organ and tissue donors to capture behaviors and medical history placing them at increased risk for HIV infection ( 17 ), the subsequent 2013 PHS guideline, limited to organ donors ( 14 ), recommends additional donor and recipient screening for HBV and HCV, including more sensitive testing methodologies, revised risk factors, and more robust informed consent discussions about accepting or rejecting organs from donors known to be infected with HBV or HCV. A new PHS guideline published in June 2020 ( 18 ), \\was implemented on March 1, 2021 ( 19 ) ( 20 ). Future Research TODES highlighted the need for a more integrated transplantation data collection system. The blood donation REDS program provides a model that addresses relevant challenges in organ and tissue safety can be found in the blood donation REDS program. Over 30 years ago, the National Heart, Lung, and Blood Institute (NHLBI) established the Retrovirus Epidemiological Donor Studies (REDS-I, 1989–2001( 21 ), REDS-II, 2004–2012 ( 22 )), and the subsequent Recipient Epidemiology and Donor Evaluation Studies (REDS III 2011–2018 ( 23 ) and REDS-IV-P 2019–2026 ( 24 )) to prospectively evaluate the safety and availability of the blood supply, in addition to the safety and effectiveness of transfusion therapies. At the time of the funding of REDS-1 (1989), questions arose about the residual risk of infectious diseases, including HIV, HCV, and HBV, in the blood supply. Using a distributed research model, multiple entities (blood collectors, hospitals, testing centers, and analytical coordinating centers) contributed and analyzed data and biospecimens to track blood safety. As a result of the REDS program, donor testing platforms have matured, and new threats have been identified (e.g., West Nile Virus). Over the past 20 years, the risks of acquiring HIV or HCV infection through transfusion have decreased from about 1:200,000-300,000 donations to 1:1.5-2.0 million donations ( 10 ). Much of the decline was attributed to nucleic acid amplification testing (NAT), which was implemented based on data from all REDS protocols and analyses of comprehensive donor and donation data captured from participating blood centers. Consequently, the REDS studies have informed regulatory decision-making and public health policies for more than a quarter century. This type of existing research database enables quick assessment of blood safety risk after a new threat or pathogen has emerged. Such a model could be used to establish a baseline of infectious risk for OTE, enabling the evaluation of risk/benefit of interventions upon identification of new threats. To build such an integrated transplant data collection system, an appropriate funding sponsor should be identified, harmonized definitions and testing approaches should be established, unique donor identifiers assigned, labeling to facilitate traceability implemented, and OPO, TE, and eye bank engagement assured. In addition, hospitals and clinician users of tissues and organs must understand the need to populate the system with additional data (i.e., improve recording of tissue provided to patients, respond to information requests and tissue utilization cards provided by TEs, monitor for and promptly report potential recipient adverse events) ( 7 ), the value of additional research, and associated costs. There is no standard for data collection and different establishments use their own systems for collection of data. Costs of establishing an integrated transplant data collection system can be daunting. However, data that would be used to streamline and optimize donor evaluation, prevent transmission events, and identify transmission events quickly to facilitate rapid response to minimize recipient morbidity and mortality could likely decrease overall costs to TEs and the entire healthcare system over time. Currently, these types of prospective data collection and analyses are viable, and as described below, need not be unduly burdensome because of healthcare IT evolution. Automated data collection capacity has now far exceeded the data and testing infrastructure of the 1990’s, 2000’s, and even 2010’s. A system could be designed to prospectively collect the data required to estimate incidence, prevalence, and risk factors of tissue and organ donors. It could also provide input to benefit-risk assessment models supporting policy evaluation. As described above, data collection and analysis cannot be supported by the electronic information currently available and stored by the organizations surveyed. As described and consistent with the TTSN experience, these issues reinforce the need to involve all stakeholders in the standards and systems development process to ensure the availability and accuracy of the appropriate and consistently defined data elements. Healthcare IT Solutions Recent Healthcare Information Technology advancements ( 25 ) ( 26 ) position RWD as a potential prospect for better informing regulatory decision-making, even as the current system for collecting and tracking donor data remains largely unchanged. The intersection of the following three factors gives rise to RWD as a potential solution: 1) increasing adoption of electronic health records (EHRs) ( 27 ); 2) emerging HL7® Fast Healthcare Interoperability Resources (FHIR®) standards ( 28 ); and 3) 21st Century Cures Act mandates to promote interoperability with FHIR R4 as the standard ( 29 ). Embedding information about both the donation/recovery and the transplantation with specific Biologically Derived Product (BDP) codes and donor identifiers in the EHR would enable forward and backward traceability from an impacted (e.g., infected) patient or product of concern to other patients or products from the same donor. The U.S. Core Data for Interoperability, the standardized set of health data classes and data elements, is poised to include BDP in a future release, requiring all EHR systems to make these data available to other systems, including those internal and external to the transplanting hospital provider. The changing landscape of healthcare IT and the continuous development of interoperability standards are the foundation for a sustainable and robust solution to improve organ and tissue safety. Therefore, it is paramount to invite all stakeholders to discuss how these data can be streamlined by standardizing, capturing, storing, and transmitting quickly and confidentially to establish RWD for the purposes of donor-to-recipient traceability and to improve transplantation safety. Abbreviations BDP Biologically Derived Product CDC Centers for Disease Control and Prevention DED Donor eligibility determination DHQ donor history questionnaire FDA Food and Drug Administration HER Electronic Health Record HHS Health and Human Services HRSA Health Resources and Services Administration TODES Tissue and Organ Donor Epidemiology Study HIV human immunodeficiency virus HBV hepatitis B virus HCV hepatitis C virus NAT nucleic acid test OPO Organ Procurement Organization OPTN Organ Procurement and Transplantation Network REDS Retrovirus Epidemiological Donor Studies RWD real world data TC Transplant Center TE Tissue Establishment UNOS United Network for Organ Sharing WG working group Declarations Ethics approval and consent to participate All TODES data were collected on deceased donors, who are not included in the definition of human subjects (45 CFR § 46.102(e)). Additionally, OPTN data are collected with the intention of making data available for public and scientific uses (30). Consent for publication N/A Availability of data and materials All data collected and analyzed for TODES are summarized in the publicly available report at https://www.hhs.gov/sites/default/files/tissue-and-organ-donor-epidemiology-study.pdf Competing interests None Funding This research was funded by the US Department of Health and Human Services HHS Contract No. HHSP23320095651WC Authors' contributions MG and HE wrote the original draft, reviewed, and edited the manuscript; HE generated figures; EB provided methodology, reviewed, and edited the draft; BJW and RF provided methodology, reviewed, and edited the draft, and supervised the project. Acknowledgements We would like to acknowledge John Matthews (Rosser), Kelly Stimpert, and Monika Deshpande for editorial support, and Matthew Kuehnert, Scott Brubaker, and Safa Karandish for discussions, initial review, and feedback. References Kaul DR, Vece G, Blumberg E, La Hoz RM, Ison MG, Green M, et al. Ten years of donor-derived disease: A report of the disease transmission advisory committee. Am J Transplant. 2021;21(2):689-702. Schwartz NG, Hernandez-Romieu AC, Annambhotla P, Filardo TD, Althomsons SP, Free RJ, et al. Nationwide tuberculosis outbreak in the USA linked to a bone graft product: an outbreak report. Lancet Infect Dis. 2022;22(11):1617-25. Tugwell BD, Patel PR, Williams IT, Hedberg K, Chai F, Nainan OV, et al. Transmission of hepatitis C virus to several organ and tissue recipients from an antibody-negative donor. Ann Intern Med. 2005;143(9):648-54. Centers for Disease C, Prevention. Transmission of hepatitis C virus through transplanted organs and tissue--Kentucky and Massachusetts, 2011. MMWR Morb Mortal Wkly Rep. 2011;60(50):1697-700. Greenwald MA, Kuehnert MJ, Fishman JA. Infectious disease transmission during organ and tissue transplantation. Emerg Infect Dis. 2012;18(8):e1. Lu XX, Zhu WY, Wu GZ. Rabies virus transmission via solid organs or tissue allotransplantation. Infect Dis Poverty. 2018;7(1):82. CDC. Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells — United States, 2023. Morbidity and Mortality Weekly Report (MMWR). 2024;72(5253):1385–9. Wortham JM, Haddad MB, Stewart RJ, Annambhotla P, Basavaraju SV, Nabity SA, et al. Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells - United States, 2023. MMWR Morb Mortal Wkly Rep. 2024;72(5253):1385-9. CDC. Transplant Safety 2022 [Available from: https://www.cdc.gov/transplantsafety/index.html. HHS. Tissue and Organ Donor Epidemiology Study (TODES). U.S. Department of Health and Human Services; 2016. FDA. Real-World Evidence 2024 [Available from: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence. Marshall KE, Free RJ, Filardo TD, Schwartz NG, Hernandez-Romieu AC, Thacker TC, et al. Incomplete tissue product tracing during an investigation of a tissue-derived tuberculosis outbreak. Am J Transplant. 2023. Li R, Deutsch-Feldman M, Adams T, Law M, Biak C, Pitcher E, et al. Transmission of Mycobacterium tuberculosis to Healthcare Personnel Resulting From Contaminated Bone Graft Material, United States, June 2021-August 2022. Clin Infect Dis. 2023;76(10):1847-9. Seem DL, Lee I, Umscheid CA, Kuehnert MJ. PHS guideline for reducing human immunodeficiency virus, hepatitis B virus, and hepatitis C virus transmission through organ transplantation. Public Health Rep. 2013;128(4):247-343. Strong DM, Seem D, Taylor G, Parker J, Stewart D, Kuehnert MJ. Development of a transplantation transmission sentinel network to improve safety and traceability of organ and tissues. Cell Tissue Bank. 2010;11(4):335-43. Martha F. Rogers RJS, Kay E. Lawton, M.N. Robin, R. Moseley, Wanda K. Jones. Guidelines for Preventing Transmission of Human Immunodeficiency Virus Through Transplantation of Human Tissue and Organs. In: CDC, editor. 1994. Guidelines for preventing transmission of human immunodeficiency virus through transplantation of human tissue and organs. Centers for Disease Control and Prevention. MMWR Recomm Rep. 1994;43(Rr-8):1-17. Jones JM, Kracalik I, Levi ME, Bowman JS, 3rd, Berger JJ, Bixler D, et al. Assessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection - U.S. Public Health Service Guideline, 2020. MMWR Recomm Rep. 2020;69(4):1-16. UNOS. Policies implemented to align with PHS guideline 2021 [Available from: https://unos.org/news/updated-resources-implementation-info-for-policies-phs-guideline/. CDC. Current Guideline for Organ Transplants 2022 [Available from: https://www.cdc.gov/transplantsafety/hc-providers/guidelines.html. Zuck TF, Thomson RA, Schreiber GB, Gilcher RO, Kleinman SH, Murphy EL, et al. The Retrovirus Epidemiology Donor Study (REDS): rationale and methods. Transfusion. 1995;35(11):944-51. Cable RG, Glynn SA, Kiss JE, Mast AE, Steele WR, Murphy EL, et al. Iron deficiency in blood donors: the REDS-II Donor Iron Status Evaluation (RISE) study. Transfusion. 2012;52(4):702-11. Kleinman S, Busch MP, Murphy EL, Shan H, Ness P, Glynn SA. The National Heart, Lung, and Blood Institute Recipient Epidemiology and Donor Evaluation Study (REDS-III): a research program striving to improve blood donor and transfusion recipient outcomes. Transfusion. 2014;54(3 Pt 2):942-55. Josephson CD, Glynn S, Mathew S, Birch R, Bakkour S, Baumann Kreuziger L, et al. The Recipient Epidemiology and Donor Evaluation Study-IV-Pediatric (REDS-IV-P): A research program striving to improve blood donor safety and optimize transfusion outcomes across the lifespan. Transfusion. 2022;62(5):982-99. Collaborative QLH. Quantum Leap Healthcare Collaborative™ Announces OneSource as a Grand Prize Winner in the 2022 Bio-IT World Innovative Practices Awards 2022 [Available from: https://www.quantumleaphealth.org/media/quantum-leap-healthcare-collaborative-tm-announces-onesource-as-a-grand-prize-winner-in-the-2022-bio-it-world-innovative-practices-awards. ASPE. SHIELD - Standardization of Lab Data to Enhance Patient-Centered Outcomes Research and Value-Based Care. 2023. Charles D KJ, Furukawa MF, Patel V. Hospital Adoption of Electronic Health Record Technology to Meet Meaningful Use Objectives: 2008-2012. In: ONC Data Brief nW, DC: Office of the National Coordinator for Health Information Technology., editor. 2013. FHIR H. FHIR Specification (v5.0.0: R5 - STU) 2023 [Available from: https://hl7.org/fhir/. HHS. 21st Century Cures Act: Interoperability, Information Blocking, and the ONC Health IT Certification Program. In: (ONC) OotNCfHIT, editor. 2020. p. 25642-961 (320 pages). OPTN. Uses of data [Available from: https://hrsa.unos.org/data/about-data/uses-of-data/. CDC. Workshop on Preventing Organ and Tissue Allograft-tranmitted Infection. 2005. (PHS) PHS, Biovigilance Task Group; Matthew Kuehnert (chair) CJGc-c, formerly of FDA currently with NHLBI; Alan Williams (co-chair), FDA; James Bowman, formerly of CMS currently with HRSA; Simone Glynn, NIH, NHLBI; Harvey Klein, NIH; Laura St. Martin, FDA; Robert Wise, FDA; Jerry Holmberg, HHS/OPHS; James Burdick, formerly of HRSA; Elizabeth Ortiz-Rios, HRSA; Jay Epstein, FDA; Robyn Ashton, HRSA; Karen Deasy, CDC; Bernard Kozlovsky, HRSA; Ellen Lazarus, FDA; Susan Leitman, NIH. Biovigilance in the United States: Efforts to Bridge a Critical Gap in Patient Safety and Donor Health. In: HHS, editor. 2009. Arthur Bracey C, Advisory Committee on Blood Safety and Availability. ACBTSA recommendations. 2016. Fishman JA, Strong DM, Kuehnert MJ. Organ and tissue safety workshop 2007: advances and challenges. Cell Tissue Bank. 2009;10(3):271-80. Atreya C, Nakhasi H, Mied P, Epstein J, Hughes J, Gwinn M, et al. FDA workshop on emerging infectious diseases: evaluating emerging infectious diseases (EIDs) for transfusion safety. Transfusion. 2011;51(8):1855-71. Seem DL, Lee I, Umscheid CA, Kuehnert MJ. Excerpt from PHS guideline for reducing HIV, HBV and HCV transmission through organ transplantation. Am J Transplant. 2013;13(8):1953-62. Request for Information: Regarding a Revision to U.S. Public Health Service Guideline: Assessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection. In: HHS, editor.: National Archives; 2022. OPTN. Align OPTN Policy with U.S. Public Health Service. 2021. OPTN. Update Data Collection to Align with U.S. Public Health Service Guideline. 2020. Benamu E, Wolfe CR, Montoya JG. Donor-derived infections in solid organ transplant patients: toward a holistic approach. Curr Opin Infect Dis. 2017;30(4):329-39. Footnotes The Center for Biologics Evaluation and Research (CBER) regulates the human cells, tissues, and cellular and tissue-based products (HCT/Ps) under 21 CFR Parts 1270 and 1271. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 12 Nov, 2024 Read the published version in Health Research Policy and Systems → Version 1 posted Editorial decision: Revision requested 23 Jun, 2024 Reviews received at journal 16 Jun, 2024 Reviews received at journal 10 Jun, 2024 Reviewers agreed at journal 26 May, 2024 Reviewers agreed at journal 20 May, 2024 Reviewers invited by journal 20 May, 2024 Submission checks completed at journal 21 Apr, 2024 Editor assigned by journal 21 Apr, 2024 First submitted to journal 19 Apr, 2024 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4293660\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":293836166,\"identity\":\"0240a542-73c6-4a0a-b164-542938d8e0d5\",\"order_by\":0,\"name\":\"Melissa A. Greenwald\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"\",\"institution\":\"Uniformed Services University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Melissa\",\"middleName\":\"A.\",\"lastName\":\"Greenwald\",\"suffix\":\"\"},{\"id\":293836168,\"identity\":\"db446344-367f-4350-9816-c55cb18382ca\",\"order_by\":1,\"name\":\"Hussein Ezzeldin\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"United States Food and Drug Administration\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Hussein\",\"middleName\":\"\",\"lastName\":\"Ezzeldin\",\"suffix\":\"\"},{\"id\":293836170,\"identity\":\"13216098-3750-44a1-b750-bab7609752d4\",\"order_by\":2,\"name\":\"Emily A. Blumberg\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Pennsylvania\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Emily\",\"middleName\":\"A.\",\"lastName\":\"Blumberg\",\"suffix\":\"\"},{\"id\":293836172,\"identity\":\"fd30b54e-33dd-49d5-9ee3-d1a12c8afb34\",\"order_by\":3,\"name\":\"Barbee I Whitaker\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"United States Food and Drug Administration\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Barbee\",\"middleName\":\"I\",\"lastName\":\"Whitaker\",\"suffix\":\"\"},{\"id\":293836173,\"identity\":\"a728b6dc-60d5-447c-ae98-dde53dac591f\",\"order_by\":4,\"name\":\"Richard A Forshee\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"United States Food and Drug Administration\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Richard\",\"middleName\":\"A\",\"lastName\":\"Forshee\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-04-19 14:14:33\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4293660/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4293660/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12961-024-01237-0\",\"type\":\"published\",\"date\":\"2024-11-12T15:57:29+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":55282922,\"identity\":\"68fb819d-01c7-41e2-8e9a-06018434b1da\",\"added_by\":\"auto\",\"created_at\":\"2024-04-25 07:18:05\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":556055,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSteps Involved in Organ Transplant. Organ transplant process simplified into nine steps includes: 1) Admission, 2) Identification, 3) Referral, 4) Screening, 5) Notification, 6) Decision, 7) Procurement, 8) Transportation, and 9) Transplantation. Solid lines denote forward data flow/communication. Dashed lines denote feedback to OPOs.\\u003c/p\\u003e\\n\\u003cp\\u003e*\\u003cstrong\\u003e \\u003c/strong\\u003eOPO checks state and national donor registries as mandated by law to honor first-person authorization.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e†\\u003c/sup\\u003e Donor eligibility determination (DED), including donor screening and testing, where data about the donor risk is collected from family, medical records, infectious disease testing, etc.\\u003c/p\\u003e\\n\\u003cp\\u003eAbbreviations: OPO, Organ Procurement Organization; OPTN, Organ Procurement and Transplantation Network; TC, transplant center; DHQ, donor history questionnaire\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4293660/v1/e090d1c02a95045d27e61b68.jpeg\"},{\"id\":55282923,\"identity\":\"e32c144e-5b93-45fb-a90c-a79799a43719\",\"added_by\":\"auto\",\"created_at\":\"2024-04-25 07:18:05\",\"extension\":\"jpeg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":491019,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSteps Involved in Tissue and Eye Transplant. The\\u003cstrong\\u003e \\u003c/strong\\u003etissue and eye transplant process simplified into nine steps includes: 1) a. Admission, b. Out-of-hospital-deaths (at-home, or by medical examiner/coroner), 2) Identification, 3) Referral, 4) Procurement, 5) Donor eligibility determination (DED), 6) Processing, 7) Release, 8) Distribution, and 9) Transplant. Solid lines denote forward data flow/communication. Dashed line denotes feedback to OPOs/ recovery partners.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e*\\u003c/sup\\u003e\\u003cstrong\\u003e \\u003c/strong\\u003eOPO/ recovery partners check state and national donor registries as mandated by law to honor first-person authorization and notify families of the individual’s registration status; families are contacted for authorization in the absence of first-person donor registration.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e†\\u003c/sup\\u003e Tissue and eye procurement could take place in the hospital, funeral home, medical examiner/coroner office, or OPO procurement center. In most cases, the donor history questionnaire (DHQ) is completed before the tissue is procured; however, procurement could take place while DHQ is conducted as part of the DED.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e¶\\u003c/sup\\u003e At-risk processing takes place when TEs process tissue(s) pending the DED results used to make final determination regarding distribution.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003csup\\u003e§\\u003c/sup\\u003e One or more tissue processors might be involved in the processing step depending on the procured tissue(s) and the requesting TEs.\\u003c/p\\u003e\\n\\u003cp\\u003eAbbreviations: DED, Donor eligibility determination; DHQ, donor history questionnaire; OPO, Organ Procurement Organization; OPTN, Organ Procurement and Transplantation Network; TC, Transplant Center; TEs, Tissue Establishments\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4293660/v1/b80aba9bb16b9b0f826d3c3a.jpeg\"},{\"id\":69275003,\"identity\":\"62295152-4e9d-4153-90c3-0403acae2fdb\",\"added_by\":\"auto\",\"created_at\":\"2024-11-18 16:44:06\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1911508,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4293660/v1/38586aa0-5f56-4873-817a-832dcd53d536.pdf\"},{\"id\":55282921,\"identity\":\"0060c3af-e712-4ae9-a124-2442b5730f94\",\"added_by\":\"auto\",\"created_at\":\"2024-04-25 07:18:05\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":18709,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"SupplementaryMaterial.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4293660/v1/b71f085fc65ac940f263f320.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Real-world data to improve Organ and Tissue Donation Policies: Lessons learned from the Tissue and Organ Donor Epidemiology Study\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eHuman organ, tissue, and eye (OTE) transplants provide tremendous individual and societal benefits. However, they are also associated with the risk of disease transmission to OTE transplant recipients. Many risk mitigation strategies are currently in place, including extensive donor screening and testing for active and latent infections. Nevertheless, donor-derived infections have occurred (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e) and are not anticipated to be fully preventable, highlighting the need for continued reassessment of how to best evaluate donors to optimally balance safety with availability. To assess the effectiveness of current donor screening and testing policies and to further optimize those policies, data regarding the background rates of communicable diseases in donor populations are necessary. The need for such data has been emphasized by federal and non-federal stakeholders alike in public workshops and white papers (Table \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eSummary of forums by federal and non-federal stakeholders and recommendation and findings\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eForum\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecommendation\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eThe joint CDC, FDA, and HRSA 2005 workshop (\\u003cspan class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Communication networks should be improved\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; A unique donor identifier for both organs and tissues should be created\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Education and dissemination of information to clinicians and transplant patients should be strengthened\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; A framework for clinicians to report transplant-associated adverse events should be clearly delineated\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; A notification algorithm for tracking among and between organs and tissues should be designed\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAdvisory Committee on Blood Safety and Availability (ACBSA) 2006 (\\u003cspan class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Called for a public-private partnership \\u0026ldquo;biovigilance\\u0026rdquo; initiative to collect analyze and report on the outcomes of collection and transfusion and/or transplantation of blood components and derivatives, cells, tissues, and organs.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2007 workshop, \\u0026ldquo;Organ and Tissue Safety Workshop 2007: Advances and Challenges (\\u003cspan class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Review the epidemiology of transmission of infection and malignancy associated with allografts (i.e., organs, tissues, eyes)\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Understand existing reporting standards and requirements, and enhance communication regarding safety issues between the organ and tissue communities, regulatory agencies, and other stakeholders\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Evaluate progress on development of the TTSN, and other interventions to detect and prevent transmission events\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Examine advances in diagnostic and screening technologies that could be applied to the enhancement of safety of allograft transplantation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2009 PHS White paper (\\u003cspan class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Identified 8 gaps for biovigilance in HCT/P and solid organ. Given the policy challenges, the recommendations were:\\u003c/p\\u003e\\n \\u003cp\\u003eo Government resource support for a national biovigilance program to monitor and enhance safety of blood, organs, and HCT/Ps\\u003c/p\\u003e\\n \\u003cp\\u003eo Integration of systems within the government and those within the private sector, involving blood, organs, and HCT/Ps, including all related voluntary and mandatory adverse event reporting systems\\u003c/p\\u003e\\n \\u003cp\\u003eo Enhance mechanisms for surveillance, including sentinel reporting and investigation, and comprehensive surveillance that features benchmarking\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2010 Emerging Infectious Diseases Workshop (\\u003cspan class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; The unknown sensitivity and specificity of current medical and behavioral history tools to screen donors for risk factors associated with infectious agents\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; The difficulty in distinguishing acute from chronic or persistent infections using standard testing modalities, especially given the prolonged window period of many serological assays and the limited sensitivity and specificity of NAT for some infections especially those acquired within days of donation\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; The limited ability of NAT to identify infections not associated with active bloodstream involvement\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; The variability in performance between different assays, including those used for donor screening and those used for diagnostic reasons, where performance characteristics have not been evaluated in the deceased donor setting; this may limit the ability of transplant personnel to compare and interpret some tests\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2013 PHS guideline\\u003c/p\\u003e\\n \\u003cp\\u003eto improve organ recipient outcomes (\\u003cspan class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Updated 1994 guideline that covered only HIV in organs and tissues\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Reduce the risk of HIV, HBV, and HCV transmission through organ transplantation\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Gaps in the literature and quality of evidence affected the ability to reach firm conclusions for organs in certain interventions\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Emphasized the need for putting a system in place allowing tracking between a common deceased donor and (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e) recovered organs, (\\u003cspan class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e) recovered associated blood vessel conduits, and (\\u003cspan class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e) recovered tissues and eyes to facilitate notification when a donor-derived disease transmission is suspected\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Further research was recommended in numerous areas, including estimating incidence and prevalence of HIV, HBV, and HCV among deceased donors, and developing standardized algorithms for discrimination of initially reactive (positive) organ donor immunoassay and NAT results\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2020 PHS Guideline\\u003c/p\\u003e\\n \\u003cp\\u003eAssessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection (\\u003cspan class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e\\u0026ndash;\\u003cspan class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u0026bull; Updated evidence review of recent organ-transplant\\u0026ndash;specific evidence, intended to increase the use of organs while continuing to maintain transplant recipient safety\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Changes from the 2013 PHS guideline:\\u003c/p\\u003e\\n \\u003cp\\u003eo Identifying a timeframe for recipient pretransplant testing\\u003c/p\\u003e\\n \\u003cp\\u003eo Updating the criteria for identifying donors at risk for undetected donor HIV, HBV, or HCV infection; the removal of any specific term to characterize donors with HIV, HBV, or HCV infection risk factors; universal organ donor HIV, HBV, and HCV nucleic acid testing; and universal posttransplant monitoring of transplant recipients for HIV, HBV, and HCV infections\\u003c/p\\u003e\\n \\u003cp\\u003e\\u0026bull; Removing the following risk criteria as no longer applicable for assessing potential disease transmission from donors to recipients:\\u003c/p\\u003e\\n \\u003cp\\u003eo Woman who has had sex with a man who has had sex with another man\\u003c/p\\u003e\\n \\u003cp\\u003eo Newly diagnosed or treated syphilis, gonorrhea, chlamydia, or genital ulcers\\u003c/p\\u003e\\n \\u003cp\\u003eo Hemodialysis\\u003c/p\\u003e\\n \\u003cp\\u003eo Hemodiluted blood specimen used for donor HIV, HBV, and HCV testing\\u003c/p\\u003e\\n \\u003cp\\u003eo Child (aged\\u0026thinsp;\\u0026le;\\u0026thinsp;18 months) born to a mother at increased risk for HIV, HBV, or HCV infection\\u003c/p\\u003e\\n \\u003cp\\u003eo Child breastfed by a mother at increased risk for HIV infection\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"2\\\"\\u003eAbbreviations: TTSN, Transplantation Transmission Sentinel Network; HCT/P, Human cells, tissues, and cellular and tissue-based products; NAT, nucleic acid test; HBV, hepatitis B virus; HIV, human immunodeficiency virus; HCV, hepatitis C virus; PHS, Public Health Services\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe Department of Health and Human Services (HHS) is charged with taking measures to minimize the risk of transmission of disease from donated OTE while optimizing product availability through relevant agencies, including the Health Resources and Services Administration (HRSA), Centers for Disease Control and Prevention (CDC) (\\u003cspan class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e), Food and Drug Administration (FDA), and the Centers for Medicare and Medicaid Services (CMS). From 2012\\u0026ndash;2016, HHS conducted the Tissue and Organ Donor Epidemiology Study (TODES\\u003csup\\u003e,\\u003c/sup\\u003e) (\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e), a demonstration project designed to evaluate the ability to identify and collect data on deceased persons referred for OTE donation in a standardized manner. This evaluation was accomplished by estimating prevalence and (to the extent possible) incidence of human immunodeficiency virus (HIV), hepatitis B virus (HBV), and hepatitis C virus (HCV), using existing data sources (namely, real-world data (RWD)) (\\u003cspan class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e), and to determine whether these data were suitable (or \\u0026ldquo;fit-for-purpose\\u0026rdquo;) for assessing donor communicable disease risk factors and informing donor screening and testing policy. If the available data sources were not fit-for-purpose, TODES would identify and propose solutions for those gaps.\\u003c/p\\u003e\\n\\u003cp\\u003eTODES provides a broad overview of the transplantation data collection infrastructure, highlights the complexity of the OTE donation processes, identifies gaps in data collection systems, and underscores the challenges to implementing standardized data collection. Bridging these gaps is important, especially given that donors may donate OTE within systems that are not able to identify and communicate transplantation transmission risks effectively and efficiently. For example, recent tuberculosis (TB) transmissions via human bone tissue containing viable cells (\\u003cspan class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e) demonstrated that the current donor screening practices failed to prevent TB transmission. There were significant challenges faced in identifying all recipients of the contaminated product ((\\u003cspan class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e), which further resulted in challenges identifying secondary transmissions to healthcare workers (\\u003cspan class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eIn this manuscript, we provide an overview of the transplant process, explain the TODES approach in collecting RWD, and highlight relevant findings from the collected data. Given the lessons learned from TODES, we explore current strategies that can pave way for future studies to overcome industry challenges and identify practical solutions that can improve the balance between safety and availability of OTE transplantation.\\u003c/p\\u003e\"},{\"header\":\"Methods\",\"content\":\"\\u003cp\\u003eStudy Overview\\u003c/p\\u003e\\n\\u003cp\\u003eThe HHS-sponsored TODES study had three overarching goals: (\\u003cspan class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e) develop a study design or framework to effectively collect and analyze demographic, screening, and infectious disease testing data obtained from deceased OTE donors, including referral-only donors, in a standardized manner; (\\u003cspan class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e) identify challenges to obtaining such data in a consistent and standardized format; and (\\u003cspan class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e) identify limitations and sources of biases from data captured in this study. HHS funding was announced in 2011, the study contract was awarded in 2012, and the final report was published in July 2016 (\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). The TODES working group (WG) comprised multiple federal and non-federal stakeholders with experience in OTE transplantation. Prospective OTE establishments were contacted for recruitment. Characteristics of potential study participants are listed in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eCharacteristics of TODES Participant Records by Org Type\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOrg Type\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOrg Code\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eAll Records\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eReferrals only Records\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\n \\u003cp\\u003eRecords Representing Potential Donors\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003ctable id=\\\"Taba\\\" border=\\\"1\\\"\\u003e\\u003c/table\\u003e\\n \\u003c/div\\u003e\\n \\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecords with UNOS Data/OPO Linked Data\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecord with any Test Results\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOrgan Donor Records with any Test Results\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTissue Donor Records with any Test Results\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEye Donor Records with any Test Results\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eReferrals- Only Records with any Test Results\\u003c/p\\u003e\\n \\u003cp\\u003en\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"10\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eOPO\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,611\\u003c/p\\u003e\\n 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\\u003cp\\u003e169,760\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e164,347\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,413\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,381\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,716\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,384\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e663\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e238\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003ec\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,967\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e42\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,925\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e652\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,949\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e652\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,621\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,867\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,865\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e618\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,860\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e618\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,370\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e562\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8,302\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8,302\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,135\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8,299\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,134\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e7,636\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4,196\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4,234\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e235\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,999\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,366\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4,060\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,371\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3,180\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e345\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e117\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eK\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e760\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e82\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e678\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e644\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e644\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e644\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e205\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e199\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eL\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e96,386\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e89,703\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6,683\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e724\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e870\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e725\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e359\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e252\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e101\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e961\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e61\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e900\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e870\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e954\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e870\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e380\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e318\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e60\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eTotal\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e291,848\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e255,927\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e35,921\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e81,41\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e23,510\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e8,149\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e18,105\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e6,365\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e655\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"5\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEye-bank\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eE\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e23,044\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e23,044\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e22,924\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9,266\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e22,924\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eG\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11,083\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e417\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e10,666\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9,873\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e9,663\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e210\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eH\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2,644\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e70\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2,574\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2,500\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2,434\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e66\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eJ\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,680\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,680\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,168\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e203\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2,399\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e5,168\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eTotal\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e42,451\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e487\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e41,964\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e40,465\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e203\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e11,665\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e40,189\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e276\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"11\\\"\\u003eSource: adapted from TODES report\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"11\\\"\\u003eReferrals-only records, UNOS Matches records, Records with any test results, Organ, tissue, and eye records with any Test Results. Based on all records received; includes known duplicates that were removed in subsequent analyses. The Organ, Tissue, and Eye Donors with any Test Results are not mutually exclusive, so the record totals may add up to a value greater than that reported in the Records with any Test Results column. OPO B and Eye Bank E were the only participants that submitted records that could be linked. Linkage of the 169,760 records submitted by OPO B and the 23,044 records submitted by Eye Bank E, resulted in 7,534 records in each dataset that were determined to be matching organ and/or tissue/eye donors. For organs, information about potential donors, also called \\u0026ldquo;referrals-only records,\\u0026rdquo; is entered into one of the OPO\\u0026rsquo;s computer systems and is assigned a UNOS ID. However, if the donor is found ineligible to donate organs, the donor records are not shared with UNOS and therefore would be unavailable in the OPTN dataset; if eligible for tissue donation, a UNOS ID is used, and other donor ID coding is also used. The \\u0026ldquo;referrals-only records\\u0026rdquo; column contains records with no indication of donor type (organ, tissue, or eye), defined to have not resulted in donation.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"11\\\"\\u003eAbbreviations: OPO, organ procurement organization; org, organization; UNOS, United Network for Organ Sharing; OPTN, Organ Procurement and Transplantation Network\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eA staff member from each participating establishment provided feedback about their organization, data collection methods, and donor population. As noted in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, some potential participants were unable to provide the data required or were unable to participate for other reasons. Significant variation in the practice of procuring information about testing for infections impacted the ability to accrue accurate and reliable RWD. As a result of the provided feedback, several sources of retrospectively deidentified RWD were obtained and reviewed for both referred potential donors and actual donors during the 5-year period from 2009 to 2013.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab3\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 3\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eProspective TODES Participants by OPTN Region and Final Participant Types\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOPTN Region\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNo. and Type of Prospective Participants\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNo. and Type of Final Participants\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1 (one OPO)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\" rowspan=\\\"11\\\"\\u003e\\n \\u003cp\\u003e9 OPOs\\u003c/p\\u003e\\n \\u003cp\\u003e4 Eye Banks\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 (two OPOs)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5 (four OPOs; one eye bank)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 (two OPOs)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4 (three OPOs; one eye bank)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 (one OPO; one eye bank)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 (two OPOs)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2 (one OPO; one eye bank)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1 (one OPO)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4 (two OPOs; two eye banks)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e4 (two OPOs; two eye banks)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"3\\\"\\u003eInitial information was obtained from 29 potential study participants:21 OPOs selected by AOPO and work group participants representing all 11 OPTN regions, and eight eye banks identified by EBAA. While six of the largest tissue processors also discussed their process of donor data collection, it is notable the working group determined that due to lack of a common donor identification across organ, eye, and tissues, obtaining data directly from tissue processors or from testing laboratories would likely result in duplicate donor data reporting. After RWD sources were identified for the study, 13 study participants were able to provide tissue donor-level data for analysis (9 OPOs and 4 eye banks).\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"3\\\"\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e Final Participants\\u0026rsquo; OPTN regions were not provided.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"3\\\"\\u003eAbbreviations: EBAA, Eye Bank Association of America; No..number; OPO, organ procurement organization; OPTN, Organ Procurement and Transplantation Network; RWD, real-world data\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eThe study also collected retrospective data from 2009 through 2013 for decedent donors. The final organ donor data was obtained from the Organ Procurement and Transplantation Network (OPTN) and organ procurement organizations (OPOs). While the final tissue donor data was obtained from eye banks and OPOs that recovered tissue, no usable data were available from tissue establishments (TEs). These data included basic demographic information, limited medical history and behavioral risk data, and infectious disease test results, if available. A data dictionary was developed, data were obtained, a TODES database was established, and data were analyzed. The data dictionary and other details about the study are available for review in the original study report (\\u003cspan class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eOverview of Organ, Eye and Tissue Transplantation Process\\u003c/p\\u003e\\n\\u003cp\\u003eFigures \\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e illustrate the complex process of OTE donation and transplantation. This context is essential to understanding the challenges encountered in obtaining data and subsequently, TODES results. OTE donation processes are similar except for some differences in the timing of donor screening and testing, as organs and eyes must be procured and transplanted in a short time window, whereas most tissues can be stored for longer periods of time.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eTable \\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e summarizes all records received by TODES, stratified by organization type (Org Type: OPO or eye bank) and participant (Org Code: A-M and E-J, where the letters are used to deidentify the organization). The TODES database contains 291,848 records received from nine OPOs and 42,451 records received from four eye banks. The majority of the donor records are males (average 63%, range 62.6\\u0026ndash;63.9%). Most of the OPO records received (88%, 255,927/291,848) do not indicate donor type; of those, 254,050 (87%) are from two participants (B and L). About 1% (487/42,451) of the records received from eye banks have no indication of donor type. The link between records received from OPO and United Network for Organ Sharing (UNOS) is indicated in Table \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e. While 8,141 OPO records can be linked to OPTN donor data received from UNOS, 1,158 UNOS records with IDs in the OPTN data cannot be linked to OPO data (OPO- UNOS+, Table \\u003cspan class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). This mismatch occurs because OPOs typically assign a UNOS ID when a patient is identified as a potential donor, but many potential donors fail to become candidate organ donors during the screening process. However, some of those candidates may still become tissue donors, depending on the reason for not recovering organs. Records of actual organ donors are provided to UNOS; a total of 88% (range: 60.2\\u0026ndash;100%, OPO\\u0026thinsp;+\\u0026thinsp;UNOS+, Table \\u003cspan class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e) of records in UNOS dataset were found in datasets shared by OPOs.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eLinkage Between Data from UNOS and OPOs\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOrg Code\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTotal Records in UNOS Dataset\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecord Count: OPO\\u0026thinsp;+\\u0026thinsp;UNOS-\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecord Count: OPO- UNOS+\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecord Count: OPO\\u0026thinsp;+\\u0026thinsp;UNOS+(%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecord Count: Discrepant Data in Variable Fields\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eA\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1248\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4860\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e497\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e751 (60.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e229\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1382\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e168379\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1381 (99.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e29\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eC\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e654\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e3315\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e652 (99.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eD\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1249\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e618 (98.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e57\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eF\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1135\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e7167\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1135 (100)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eI\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1458\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2868\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e92\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e1366 (93.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e490\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eK\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e644\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e116\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e644 (100)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e50\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eL\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e724\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e74534\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e724 (100)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1425\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e91\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e555\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e870 (61.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eSource: adapted from TODES report\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eData records provided by each OPO were merged with records obtained from UNOS. The linkage between data from UNOS and OPOs was produced from merging the data records.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003e% = percent of all the records found in UNOS that were matched with OPO; + = present; - = absent\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eAbbreviations: OPO, organ procurement organization; org, organization; UNOS, United Network for Organ Sharing\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003cdiv align=\\\"char\\\" class=\\\"colspec\\\"\\u003e\\u003cbr\\u003e\\u003c/div\\u003e\\n \\u003ctable id=\\\"Tab5\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 5\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eCharacteristics of Potential Donors in the TODES Database by Year\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eYear\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecords n\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMale\\u003c/p\\u003e\\n \\u003cp\\u003e%\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eFemale\\u003c/p\\u003e\\n \\u003cp\\u003e%\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eOrgan Donors\\u003c/p\\u003e\\n \\u003cp\\u003e%*\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eTissue Donors\\u003c/p\\u003e\\n \\u003cp\\u003e%\\u0026dagger;\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eEye Donors\\u003c/p\\u003e\\n \\u003cp\\u003e%\\u0026para;\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eConsent/ Authorization Documented\\u003c/p\\u003e\\n \\u003cp\\u003e%\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e12,871\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e62.6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e37.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e10.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e51.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e74.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e97.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e13,527\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e10.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e53.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e71.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e97.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e14,198\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e13.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e54.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e71.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e94.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e16,272\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e49.9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e74.0\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e91.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e17,876\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63.2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e49.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e75.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e90.1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2009\\u0026ndash;2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e74,744\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e63.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e36.7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e11.3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e51.5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e73.4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e93.8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\"\\u003eSource: adapted from TODES report\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\"\\u003eBased on all records received; excludes known duplicates\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\"\\u003e* % of donors with at least one organ recovered for transplant\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\"\\u003e\\u0026dagger; % of donors with at least one tissue recovered for transplant\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"8\\\"\\u003e\\u0026para; % of donors with at least one ocular tissue recovered for transplant\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eAbout 8% (23,510/291,848; range 1%-100%) of total OPO records received had at least one infectious disease test result compared to 93% (40,465/42,451; range 89%-99%) of total eye bank records received (Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). The records with any test results were stratified into three groups by donor type (organ donors, tissue donors, and eye donors); if donor type was not indicated, it was defined as a referrals-only record for any test results. Such low percentages of referral-only records (e.g., no organs were recovered) with at least one test in an OPO dataset occurred because tissue donor test results were not commonly shared with the OPO at that time, even when individuals from whom tissue was recovered were identified as tissue donors. If the individual was determined to be HIV, HBV, or HCV positive, the donated tissues were deemed ineligible for tissue transplantation purposes per FDA regulations.\\u003c/p\\u003e\\n\\u003cp\\u003eAmong the 23,510 records with test results in the OPO dataset, only 8,149 (approximately 35%) were organ donor records; by contrast, among the 40,465 recorded in the eye-bank dataset, only 203 (\\u0026lt;\\u0026thinsp;1%) were organ donors. For tissue-donor records with at least one test result, 18,105 records were from OPOs and 11,665 from eye banks. For eye-donor records only, 6,365 were from OPOs and 40,189 from eye banks. A small number of referrals-only records, 655 from OPOs and 276 from eye banks, had at least one test result. In this study, the referrals-only data were ultimately excluded from analysis because a) most did not have any test results associated with the test data, and b) the data came from a subset of the organizations in the dataset. This indicates that, with the current system, reliable data cannot be obtained about all \\u003cem\\u003epotential\\u003c/em\\u003e organ or tissue donors, which is important information contributing to understanding the baseline infectious disease risks associated with OTE donor populations. As a result, data were analyzed only from deceased donors with at least one recovered organ, tissue, or ocular tissue with the intent to transplant.\\u003c/p\\u003e\\n\\u003cp\\u003eThe Public Health Service (PHS) 2013 guideline (\\u003cspan class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e) provides 11 risk factors associated with an increased likelihood of recent HIV, HBV, or HCV infection amongst organ donors. Organ donors with one or more of these risk factors were identified as at \\u0026ldquo;increased risk\\u0026rdquo; for infections in the UNOS dataset. Table \\u003cspan class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e summarizes the increased-risk indicator stratified by year in the UNOS dataset, which was available for almost all organ donors (99.8%). According to the five-year-period dataset, 10.1\\u0026ndash;16.2% of organ donors per year (with an average of 13.9%) were classified as increased-risk donors. Donors missing this information did not exceed 0.2% per year. Donating with a risk factor is permissible only for organ donors. Per 21 CFR Part 1271 (not applicable to organs), potential tissue (including ocular) donors with risk factors for certain infectious diseases are ineligible for donation, so data regarding \\u0026ldquo;increased risk\\u0026rdquo; donors for tissue and eye donation do not exist.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n \\u003ctable id=\\\"Tab6\\\" border=\\\"1\\\"\\u003e\\n \\u003ccaption language=\\\"En\\\"\\u003e\\n \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 6\\u003c/div\\u003e\\n \\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n \\u003cp\\u003eInfectious Disease Risk Status * of Organ Donors by Year\\u003c/p\\u003e\\n \\u003c/div\\u003e\\n \\u003c/caption\\u003e\\n \\u003cthead\\u003e\\n \\u003ctr\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eYear\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eRecords n \\u0026dagger;\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eYes n (%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNo n (%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eNot Done n (%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003cth align=\\\"left\\\"\\u003e\\n \\u003cp\\u003eMissing n (%)\\u003c/p\\u003e\\n \\u003c/th\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/thead\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2009\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,266\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e128 (10.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,132 (89.4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4 (0.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2 (0.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2010\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,359\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e178 (13.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,179 (86.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2 (0.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2011\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,830\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e250 (13.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,578 (86.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e2 (0.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2012\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,809\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e276 (15.3)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,532 (84.7)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1 (0.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,877\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e304 (16.2)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,573 (83.8)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e0 (0.0)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd align=\\\"left\\\"\\u003e\\n \\u003cp\\u003e2009\\u0026ndash;2013\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e8,141\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e1,136 (13.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e6,994 (85.9)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e4 (0.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd align=\\\"char\\\"\\u003e\\n \\u003cp\\u003e7 (0.1)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n \\u003ctfoot\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eSource: adapted from TODES report\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003eRisk status of infectious disease was obtained from UNOS data\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003e* Infectious disease risk status is an assessment of risk for blood-borne disease transmission per 2010 PHS guidelines, i.e., the organ donors who met one or more criteria considered as behavioral or medical risk factors for recent HIV infection.\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd colspan=\\\"6\\\"\\u003e\\u0026dagger; Represents donor records from OPOs that can be linked to donor records received from UNOS\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tfoot\\u003e\\n \\u003c/table\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Discussion and Conclusions\",\"content\":\"\\u003cp\\u003eThis effort highlights multiple lessons learned regarding knowledge gaps and challenges of using RWD that can better inform regulatory decision-making. Importantly, findings from the data captured by TODES led to precluding its use for policy decisions. First, the data were determined to not be fit-for-purpose, which was not surprising given the data provided by the organizations were collected to support business operations rather than to address research and surveillance questions. Specifically, available RWD data could not identify duplicate data among tissue donors, provide a tissue donation denominator, or ascertain a representative sample of donors. Second, it was not possible to ascertain a comprehensive understanding of the true infectious disease status. Supplemental tests were rarely performed to verify positive or indeterminate test results, presumably because of the lack of appropriately labeled supplemental (i.e., “confirmatory”) tests, lack of adequate specimen volume, inability to sequentially follow deceased donors to document the evolution of infectious disease test markers, and lack of regulatory or policy requirements to perform supplemental testing. Furthermore, testing data of potential non-transplantation donors—e.g., that likely had positive test results or identified communicable disease risks—were largely unavailable, and if available, data were incomplete. Third, the various testing protocols that estimated infectious disease marker prevalence lacked standardization and included a variety of assay types such as donor screening and diagnostic assays (ST 1). Fourth, donors from OPO- and TE- evaluated datasets cannot be uniquely identified in large part because donors lack a common identifier between the organ and tissue/eye transplantation pathways as well as within the tissue/eye pathway when tissues go to more than one establishment. As such, any assembled dataset contains a mixture of test results (i.e., positive results with no further testing, inconclusive results with no further testing, positive results with subsequent testing, and negative results with subsequent testing), severely impacting the interpretability and usefulness of the data.\\u003c/p\\u003e\\u003cp\\u003eTODES focused on data available for OTE donors that might be used to characterize the donor populations to inform donor screening and testing policy. However, determining how these data are part of an \\u003cem\\u003einterconnected system\\u003c/em\\u003e needed to maximize overall OTE transplantation safety is also important. Multiple facets contribute to maximize transplantation safety. These include: i) donor selection (defining and identifying potential donors, donor screening and testing information); ii) careful manufacturing practices (processing practices that both prevent contamination and cross-contamination and that remove or inactivate contamination to the extent possible while maintaining utility of the product); and iii) identifying and investigating adverse events (to learn about the causes to inform improved policies and practice, and to quickly identify other recipients to prevent further adverse event occurrence). These facets of transplant safety require traceability of tissues from the time of considering a potential donor all the way through to the transplantation/ implantation to a recipient. Ideally, donor evaluation and transplantation outcomes data collection could also be used as part of efforts to proactively identify emerging infectious disease threats. The TODES study participants agreed that interventions that can yield benefits to transplantation safety include better communication, better identification methods, better education, etc. A comprehensive list is presented in ST 2. These interventions are consistent with the conclusions of the Transplantation Transmission Sentinel Network (TTSN) pilot program that was developed to collect data on donation, tissue implantation, and adverse events (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). The authors of the TTSN program concluded that eye and tissue tracking from recovery to implantation will be necessary before a sentinel network system can be operable, which would require common identifiers and nomenclature. They further stated that the absence of a U.S. sentinel network may result in future transmission events that could have been otherwise preventable. There is a clear need for such an integrated system for OTE transplantation data collection. The ways in which this can be accomplished is further explored in this discussion.\\u003c/p\\u003e\\u003ch2\\u003eStudy limitations\\u003c/h2\\u003e\\u003cp\\u003eTODES had some limitations. Data integration from different sources (e.g., eye banks, large TEs, and large laboratories that provide infectious disease testing) was challenging, which resulted in excluding those sources and procuring tissue donor data only from OPOs that were also tissue recovery establishments. Thus, TODES data is not representative of national organ and tissue donor/donation data. Also, the 2009–2013 donor data collected by TODES reflect the recommendations in the 1994 PHS guidelines (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e) that do not address later guideline development (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e) in defining “increased risk” organ donors. While the 1994 PHS guidelines were designed to reduce the risk of HIV transmission by screening organ and tissue donors to capture behaviors and medical history placing them at increased risk for HIV infection (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e), the subsequent 2013 PHS guideline, limited to organ donors (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e), recommends additional donor and recipient screening for HBV and HCV, including more sensitive testing methodologies, revised risk factors, and more robust informed consent discussions about accepting or rejecting organs from donors known to be infected with HBV or HCV. A new PHS guideline published in June 2020 (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e), \\\\was implemented on March 1, 2021 (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e) (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eFuture Research\\u003c/p\\u003e\\u003cp\\u003eTODES highlighted the need for a more integrated transplantation data collection system. The blood donation REDS program provides a model that addresses relevant challenges in organ and tissue safety can be found in the blood donation REDS program. Over 30 years ago, the National Heart, Lung, and Blood Institute (NHLBI) established the Retrovirus Epidemiological Donor Studies (REDS-I, 1989–2001(\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e), REDS-II, 2004–2012 (\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e)), and the subsequent Recipient Epidemiology and Donor Evaluation Studies (REDS III 2011–2018 (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e) and REDS-IV-P 2019–2026 (\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e)) to prospectively evaluate the safety and availability of the blood supply, in addition to the safety and effectiveness of transfusion therapies. At the time of the funding of REDS-1 (1989), questions arose about the residual risk of infectious diseases, including HIV, HCV, and HBV, in the blood supply. Using a distributed research model, multiple entities (blood collectors, hospitals, testing centers, and analytical coordinating centers) contributed and analyzed data and biospecimens to track blood safety. As a result of the REDS program, donor testing platforms have matured, and new threats have been identified (e.g., West Nile Virus).\\u003c/p\\u003e\\u003cp\\u003eOver the past 20 years, the risks of acquiring HIV or HCV infection through transfusion have decreased from about 1:200,000-300,000 donations to 1:1.5-2.0\\u0026nbsp;million donations (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). Much of the decline was attributed to nucleic acid amplification testing (NAT), which was implemented based on data from all REDS protocols and analyses of comprehensive donor and donation data captured from participating blood centers. Consequently, the REDS studies have informed regulatory decision-making and public health policies for more than a quarter century. This type of existing research database enables quick assessment of blood safety risk after a new threat or pathogen has emerged.\\u003c/p\\u003e\\u003cp\\u003eSuch a model could be used to establish a baseline of infectious risk for OTE, enabling the evaluation of risk/benefit of interventions upon identification of new threats. To build such an integrated transplant data collection system, an appropriate funding sponsor should be identified, harmonized definitions and testing approaches should be established, unique donor identifiers assigned, labeling to facilitate traceability implemented, and OPO, TE, and eye bank engagement assured. In addition, hospitals and clinician users of tissues and organs must understand the need to populate the system with additional data (i.e., improve recording of tissue provided to patients, respond to information requests and tissue utilization cards provided by TEs, monitor for and promptly report potential recipient adverse events) (\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e), the value of additional research, and associated costs. There is no standard for data collection and different establishments use their own systems for collection of data. Costs of establishing an integrated transplant data collection system can be daunting. However, data that would be used to streamline and optimize donor evaluation, prevent transmission events, and identify transmission events quickly to facilitate rapid response to minimize recipient morbidity and mortality could likely decrease overall costs to TEs and the entire healthcare system over time.\\u003c/p\\u003e\\u003cp\\u003eCurrently, these types of prospective data collection and analyses are viable, and as described below, need not be unduly burdensome because of healthcare IT evolution. Automated data collection capacity has now far exceeded the data and testing infrastructure of the 1990’s, 2000’s, and even 2010’s. A system could be designed to prospectively collect the data required to estimate incidence, prevalence, and risk factors of tissue and organ donors. It could also provide input to benefit-risk assessment models supporting policy evaluation. As described above, data collection and analysis cannot be supported by the electronic information currently available and stored by the organizations surveyed. As described and consistent with the TTSN experience, these issues reinforce the need to involve all stakeholders in the standards and systems development process to ensure the availability and accuracy of the appropriate and consistently defined data elements.\\u003c/p\\u003e\\u003cp\\u003eHealthcare IT Solutions\\u003c/p\\u003e\\u003cp\\u003eRecent Healthcare Information Technology advancements (\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e) (\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e) position RWD as a potential prospect for better informing regulatory decision-making, even as the current system for collecting and tracking donor data remains largely unchanged. The intersection of the following three factors gives rise to RWD as a potential solution: 1) increasing adoption of electronic health records (EHRs) (\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e); 2) emerging HL7® Fast Healthcare Interoperability Resources (FHIR®) standards (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e); and 3) 21st Century Cures Act mandates to promote interoperability with FHIR R4 as the standard (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e). Embedding information about both the donation/recovery and the transplantation with specific Biologically Derived Product (BDP) codes and donor identifiers in the EHR would enable forward and backward traceability from an impacted (e.g., infected) patient or product of concern to other patients or products from the same donor. The U.S. Core Data for Interoperability, the standardized set of health data classes and data elements, is poised to include BDP in a future release, requiring all EHR systems to make these data available to other systems, including those internal and external to the transplanting hospital provider.\\u003c/p\\u003e\\u003cp\\u003eThe changing landscape of healthcare IT and the continuous development of interoperability standards are the foundation for a sustainable and robust solution to improve organ and tissue safety. Therefore, it is paramount to invite all stakeholders to discuss how these data can be streamlined by standardizing, capturing, storing, and transmitting quickly and confidentially to establish RWD for the purposes of donor-to-recipient traceability and to improve transplantation safety.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBDP\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eBiologically Derived Product\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCDC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCenters for Disease Control and Prevention\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDED\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eDonor eligibility determination\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDHQ\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003edonor history questionnaire\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eFDA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFood and Drug Administration\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHER\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eElectronic Health Record\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHHS\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHealth and Human Services\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHRSA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHealth Resources and Services Administration\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eTODES\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTissue and Organ Donor Epidemiology Study\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHIV\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ehuman immunodeficiency virus\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHBV\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ehepatitis B virus\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHCV\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ehepatitis C virus\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eNAT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003enucleic acid test\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eOPO\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOrgan Procurement Organization\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eOPTN\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOrgan Procurement and Transplantation Network\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eREDS\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRetrovirus Epidemiological Donor Studies\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eRWD\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ereal world data\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eTC\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTransplant Center\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eTE\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTissue Establishment\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eUNOS\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eUnited Network for Organ Sharing\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eWG\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eworking group\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll TODES data were collected on deceased donors, who are not included in the definition of human subjects (45 CFR \\u003cstrong\\u003e\\u0026sect;\\u003c/strong\\u003e46.102(e)). Additionally, OPTN data are collected with the intention of making data available for public and scientific uses (30).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eN/A\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data collected and analyzed for TODES are summarized in the publicly available report at\\u0026nbsp;\\u003ca href=\\\"https://www.hhs.gov/sites/default/files/tissue-and-organ-donor-epidemiology-study.pdf\\\"\\u003ehttps://www.hhs.gov/sites/default/files/tissue-and-organ-donor-epidemiology-study.pdf\\u003c/a\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNone\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research was funded by the US Department of Health and Human Services HHS Contract No. HHSP23320095651WC\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMG and HE wrote the original draft, reviewed, and edited the manuscript; HE generated figures; EB provided methodology, reviewed, and edited the draft; BJW and RF provided methodology, reviewed, and edited the draft, and supervised the project.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe would like to acknowledge John Matthews (Rosser), Kelly Stimpert, and Monika Deshpande for editorial support, and Matthew Kuehnert, Scott Brubaker, and Safa Karandish for discussions, initial review, and feedback.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eKaul DR, Vece G, Blumberg E, La Hoz RM, Ison MG, Green M, et al. Ten years of donor-derived disease: A report of the disease transmission advisory committee. Am J Transplant. 2021;21(2):689-702.\\u003c/li\\u003e\\n\\u003cli\\u003eSchwartz NG, Hernandez-Romieu AC, Annambhotla P, Filardo TD, Althomsons SP, Free RJ, et al. Nationwide tuberculosis outbreak in the USA linked to a bone graft product: an outbreak report. Lancet Infect Dis. 2022;22(11):1617-25.\\u003c/li\\u003e\\n\\u003cli\\u003eTugwell BD, Patel PR, Williams IT, Hedberg K, Chai F, Nainan OV, et al. Transmission of hepatitis C virus to several organ and tissue recipients from an antibody-negative donor. Ann Intern Med. 2005;143(9):648-54.\\u003c/li\\u003e\\n\\u003cli\\u003eCenters for Disease C, Prevention. Transmission of hepatitis C virus through transplanted organs and tissue--Kentucky and Massachusetts, 2011. MMWR Morb Mortal Wkly Rep. 2011;60(50):1697-700.\\u003c/li\\u003e\\n\\u003cli\\u003eGreenwald MA, Kuehnert MJ, Fishman JA. Infectious disease transmission during organ and tissue transplantation. Emerg Infect Dis. 2012;18(8):e1.\\u003c/li\\u003e\\n\\u003cli\\u003eLu XX, Zhu WY, Wu GZ. Rabies virus transmission via solid organs or tissue allotransplantation. Infect Dis Poverty. 2018;7(1):82.\\u003c/li\\u003e\\n\\u003cli\\u003eCDC. Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells \\u0026mdash; United States, 2023. Morbidity and Mortality Weekly Report (MMWR). 2024;72(5253):1385\\u0026ndash;9.\\u003c/li\\u003e\\n\\u003cli\\u003eWortham JM, Haddad MB, Stewart RJ, Annambhotla P, Basavaraju SV, Nabity SA, et al. Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells - United States, 2023. MMWR Morb Mortal Wkly Rep. 2024;72(5253):1385-9.\\u003c/li\\u003e\\n\\u003cli\\u003eCDC. Transplant Safety 2022 [Available from: https://www.cdc.gov/transplantsafety/index.html.\\u003c/li\\u003e\\n\\u003cli\\u003eHHS. Tissue and Organ Donor Epidemiology Study (TODES). U.S. Department of Health and Human Services; 2016.\\u003c/li\\u003e\\n\\u003cli\\u003eFDA. Real-World Evidence 2024 [Available from: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence.\\u003c/li\\u003e\\n\\u003cli\\u003eMarshall KE, Free RJ, Filardo TD, Schwartz NG, Hernandez-Romieu AC, Thacker TC, et al. Incomplete tissue product tracing during an investigation of a tissue-derived tuberculosis outbreak. Am J Transplant. 2023.\\u003c/li\\u003e\\n\\u003cli\\u003eLi R, Deutsch-Feldman M, Adams T, Law M, Biak C, Pitcher E, et al. Transmission of Mycobacterium tuberculosis to Healthcare Personnel Resulting From Contaminated Bone Graft Material, United States, June 2021-August 2022. Clin Infect Dis. 2023;76(10):1847-9.\\u003c/li\\u003e\\n\\u003cli\\u003eSeem DL, Lee I, Umscheid CA, Kuehnert MJ. PHS guideline for reducing human immunodeficiency virus, hepatitis B virus, and hepatitis C virus transmission through organ transplantation. Public Health Rep. 2013;128(4):247-343.\\u003c/li\\u003e\\n\\u003cli\\u003eStrong DM, Seem D, Taylor G, Parker J, Stewart D, Kuehnert MJ. Development of a transplantation transmission sentinel network to improve safety and traceability of organ and tissues. Cell Tissue Bank. 2010;11(4):335-43.\\u003c/li\\u003e\\n\\u003cli\\u003eMartha F. Rogers RJS, Kay E. Lawton, M.N. Robin, R. Moseley, Wanda K. Jones. Guidelines for Preventing Transmission of Human Immunodeficiency Virus Through Transplantation of Human Tissue and Organs. In: CDC, editor. 1994.\\u003c/li\\u003e\\n\\u003cli\\u003eGuidelines for preventing transmission of human immunodeficiency virus through transplantation of human tissue and organs. Centers for Disease Control and Prevention. MMWR Recomm Rep. 1994;43(Rr-8):1-17.\\u003c/li\\u003e\\n\\u003cli\\u003eJones JM, Kracalik I, Levi ME, Bowman JS, 3rd, Berger JJ, Bixler D, et al. Assessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection - U.S. Public Health Service Guideline, 2020. MMWR Recomm Rep. 2020;69(4):1-16.\\u003c/li\\u003e\\n\\u003cli\\u003eUNOS. Policies implemented to align with PHS guideline 2021 [Available from: https://unos.org/news/updated-resources-implementation-info-for-policies-phs-guideline/.\\u003c/li\\u003e\\n\\u003cli\\u003eCDC. Current Guideline for Organ Transplants 2022 [Available from: https://www.cdc.gov/transplantsafety/hc-providers/guidelines.html.\\u003c/li\\u003e\\n\\u003cli\\u003eZuck TF, Thomson RA, Schreiber GB, Gilcher RO, Kleinman SH, Murphy EL, et al. The Retrovirus Epidemiology Donor Study (REDS): rationale and methods. Transfusion. 1995;35(11):944-51.\\u003c/li\\u003e\\n\\u003cli\\u003eCable RG, Glynn SA, Kiss JE, Mast AE, Steele WR, Murphy EL, et al. Iron deficiency in blood donors: the REDS-II Donor Iron Status Evaluation (RISE) study. Transfusion. 2012;52(4):702-11.\\u003c/li\\u003e\\n\\u003cli\\u003eKleinman S, Busch MP, Murphy EL, Shan H, Ness P, Glynn SA. The National Heart, Lung, and Blood Institute Recipient Epidemiology and Donor Evaluation Study (REDS-III): a research program striving to improve blood donor and transfusion recipient outcomes. Transfusion. 2014;54(3 Pt 2):942-55.\\u003c/li\\u003e\\n\\u003cli\\u003eJosephson CD, Glynn S, Mathew S, Birch R, Bakkour S, Baumann Kreuziger L, et al. The Recipient Epidemiology and Donor Evaluation Study-IV-Pediatric (REDS-IV-P): A research program striving to improve blood donor safety and optimize transfusion outcomes across the lifespan. Transfusion. 2022;62(5):982-99.\\u003c/li\\u003e\\n\\u003cli\\u003eCollaborative QLH. Quantum Leap Healthcare Collaborative\\u0026trade; Announces OneSource as a Grand Prize Winner in the 2022 Bio-IT World Innovative Practices Awards 2022 [Available from: https://www.quantumleaphealth.org/media/quantum-leap-healthcare-collaborative-tm-announces-onesource-as-a-grand-prize-winner-in-the-2022-bio-it-world-innovative-practices-awards.\\u003c/li\\u003e\\n\\u003cli\\u003eASPE. SHIELD - Standardization of Lab Data to Enhance Patient-Centered Outcomes Research and Value-Based Care. 2023.\\u003c/li\\u003e\\n\\u003cli\\u003eCharles D KJ, Furukawa MF, Patel V. Hospital Adoption of Electronic Health Record Technology to Meet Meaningful Use Objectives: 2008-2012. In: ONC Data Brief nW, DC: Office of the National Coordinator for Health Information Technology., editor. 2013.\\u003c/li\\u003e\\n\\u003cli\\u003eFHIR H. FHIR Specification (v5.0.0: R5 - STU) 2023 [Available from: https://hl7.org/fhir/.\\u003c/li\\u003e\\n\\u003cli\\u003eHHS. 21st Century Cures Act: Interoperability, Information Blocking, and the ONC Health IT Certification Program. In: (ONC) OotNCfHIT, editor. 2020. p. 25642-961 (320 pages).\\u003c/li\\u003e\\n\\u003cli\\u003eOPTN. Uses of data [Available from: https://hrsa.unos.org/data/about-data/uses-of-data/.\\u003c/li\\u003e\\n\\u003cli\\u003eCDC. Workshop on Preventing Organ and Tissue Allograft-tranmitted Infection. 2005.\\u003c/li\\u003e\\n\\u003cli\\u003e(PHS) PHS, Biovigilance Task Group; Matthew Kuehnert (chair) CJGc-c, formerly of FDA currently with NHLBI; Alan Williams (co-chair), FDA; James Bowman, formerly of CMS currently with HRSA; Simone Glynn, NIH, NHLBI; Harvey Klein, NIH; Laura St. Martin, FDA; Robert Wise, FDA; Jerry Holmberg, HHS/OPHS; James Burdick, formerly of HRSA; Elizabeth Ortiz-Rios, HRSA; Jay Epstein, FDA; Robyn Ashton, HRSA; Karen Deasy, CDC; Bernard Kozlovsky, HRSA; Ellen Lazarus, FDA; Susan Leitman, NIH. Biovigilance in the United States: Efforts to Bridge a Critical Gap in Patient Safety and Donor Health. In: HHS, editor. 2009.\\u003c/li\\u003e\\n\\u003cli\\u003eArthur Bracey C, Advisory Committee on Blood Safety and Availability. ACBTSA recommendations. 2016.\\u003c/li\\u003e\\n\\u003cli\\u003eFishman JA, Strong DM, Kuehnert MJ. Organ and tissue safety workshop 2007: advances and challenges. Cell Tissue Bank. 2009;10(3):271-80.\\u003c/li\\u003e\\n\\u003cli\\u003eAtreya C, Nakhasi H, Mied P, Epstein J, Hughes J, Gwinn M, et al. FDA workshop on emerging infectious diseases: evaluating emerging infectious diseases (EIDs) for transfusion safety. Transfusion. 2011;51(8):1855-71.\\u003c/li\\u003e\\n\\u003cli\\u003eSeem DL, Lee I, Umscheid CA, Kuehnert MJ. Excerpt from PHS guideline for reducing HIV, HBV and HCV transmission through organ transplantation. Am J Transplant. 2013;13(8):1953-62.\\u003c/li\\u003e\\n\\u003cli\\u003eRequest for Information: Regarding a Revision to U.S. Public Health Service Guideline: Assessing Solid Organ Donors and Monitoring Transplant Recipients for Human Immunodeficiency Virus, Hepatitis B Virus, and Hepatitis C Virus Infection. In: HHS, editor.: National Archives; 2022.\\u003c/li\\u003e\\n\\u003cli\\u003eOPTN. Align OPTN Policy with U.S. Public Health Service. 2021.\\u003c/li\\u003e\\n\\u003cli\\u003eOPTN. Update Data Collection to Align with U.S. Public Health Service Guideline. 2020.\\u003c/li\\u003e\\n\\u003cli\\u003eBenamu E, Wolfe CR, Montoya JG. Donor-derived infections in solid organ transplant patients: toward a holistic approach. Curr Opin Infect Dis. 2017;30(4):329-39.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"Footnotes\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003e The Center for Biologics Evaluation and Research (CBER) regulates the human cells, tissues, and cellular and tissue-based products (HCT/Ps) under 21 CFR Parts 1270 and 1271.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"health-research-policy-and-systems\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"hrps\",\"sideBox\":\"Learn more about [Health Research Policy and Systems](http://health-policy-systems.biomedcentral.com/)\",\"snPcode\":\"12961\",\"submissionUrl\":\"https://submission.nature.com/new-submission/12961/3\",\"title\":\"Health Research Policy and Systems\",\"twitterHandle\":\"@HarpsJournal\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"organ transplantation, tissue transplantation, communicable diseases, donor screening, donor testing, real world data, health information exchange, interoperability, patient safety, traceability\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4293660/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4293660/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground:\\u003c/strong\\u003e The transplantation of human organs, and some human tissues, is often the only life-saving therapy available for serious and life-threatening congenital, inherited, or acquired diseases.\\u003cstrong\\u003e \\u003c/strong\\u003eHowever, it is associated with a risk of transmission of communicable diseases from donor to recipient. It is imperative to understand the characteristics of the donor population to inform policies that protect recipient safety. The Tissue and Organ Donor Epidemiology Study (TODES) was a pilot project designed to identify and collect standardized information on deceased persons referred for organ, tissue, and/or eye donation, and to estimate (to the extent possible) infectious disease prevalence and incidence of HIV, HBV, and/or HCV in this population. TODES is summarized here to shed light on addressable limitations on accessing data needed for transplant recipient safety. Limitations, future research needs, and potential pathways to solve the remaining data needs are explored.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods: \\u003c/strong\\u003eRetrospective data for all deceased donors during a 5-year period from 2009 to 2013 were obtained from participating organ procurement organizations (OPOs), tissue establishments, and eye banks. These decedent data on actual donors and potential donors were used to ascertain whether the available real-world data (RWD) could be used to inform donor screening and testing policy.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults: \\u003c/strong\\u003eThe TODES database contains 291,848 records received from nine OPOs and 42,451 records received from four eye banks.\\u003cstrong\\u003e \\u003c/strong\\u003eData were analyzed from deceased donors with at least one organ, tissue, or ocular tissue recovered with the intent to transplant. Results for potential donors were not analyzed.\\u003cstrong\\u003e \\u003c/strong\\u003eAvailable RWD at the time of the TODES study were not fit-for-purpose to help characterize the organ- and tissue eye donor populations and/or to inform donor screening policy.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusions: \\u003c/strong\\u003eRecent advances in electronic data collection systems make it more realistic to now collect fit-for-purpose RWD that address the research needed to improve transplant safety.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Real-world data to improve Organ and Tissue Donation Policies: Lessons learned from the Tissue and Organ Donor Epidemiology Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-04-25 07:18:01\",\"doi\":\"10.21203/rs.3.rs-4293660/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-06-23T14:19:50+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-06-16T22:11:01+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-06-10T22:47:47+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"127333718004910841687273595179035416898\",\"date\":\"2024-05-26T18:42:02+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"55004990078969331264677102747461031236\",\"date\":\"2024-05-21T01:59:29+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-05-20T23:04:58+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-04-22T03:26:52+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-04-22T03:26:52+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Health Research Policy and Systems\",\"date\":\"2024-04-19T14:11:58+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"health-research-policy-and-systems\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"hrps\",\"sideBox\":\"Learn more about [Health Research Policy and Systems](http://health-policy-systems.biomedcentral.com/)\",\"snPcode\":\"12961\",\"submissionUrl\":\"https://submission.nature.com/new-submission/12961/3\",\"title\":\"Health Research Policy and Systems\",\"twitterHandle\":\"@HarpsJournal\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"cba046c0-781e-4a6a-b7af-9882ae12ba91\",\"owner\":[],\"postedDate\":\"April 25th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-11-18T16:01:47+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-4293660\",\"link\":\"https://doi.org/10.1186/s12961-024-01237-0\",\"journal\":{\"identity\":\"health-research-policy-and-systems\",\"isVorOnly\":false,\"title\":\"Health Research Policy and Systems\"},\"publishedOn\":\"2024-11-12 15:57:29\",\"publishedOnDateReadable\":\"November 12th, 2024\"},\"versionCreatedAt\":\"2024-04-25 07:18:01\",\"video\":\"\",\"vorDoi\":\"10.1186/s12961-024-01237-0\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12961-024-01237-0\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4293660\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4293660\",\"identity\":\"rs-4293660\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}