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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Public Health</journal-id>
<journal-title>Frontiers in Public Health</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Public Health</abbrev-journal-title>
<issn pub-type="epub">2296-2565</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpubh.2023.1092182</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Public Health</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Performance assessment of medical service for organ transplant department based on diagnosis-related groups: A programme incorporating ischemia-free liver transplantation in China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Lu</surname>
<given-names>Jianjun</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="fn0003" ref-type="author-notes"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/813994/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Zhuochen</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="fn0003" ref-type="author-notes"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1743179/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xiong</surname>
<given-names>Ying</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="fn0003" ref-type="author-notes"><sup>&#x2020;</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pang</surname>
<given-names>Hui</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Ye</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xin</surname>
<given-names>Ziyi</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Yuelin</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shen</surname>
<given-names>Zhiqing</given-names>
</name>
<xref rid="aff2" ref-type="aff"><sup>2</sup></xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chen</surname>
<given-names>Wei</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="aff3" ref-type="aff"><sup>3</sup></xref>
<xref rid="aff4" ref-type="aff"><sup>4</sup></xref>
<xref rid="c002" ref-type="corresp"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1124609/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Wujun</given-names>
</name>
<xref rid="aff1" ref-type="aff"><sup>1</sup></xref>
<xref rid="c001" ref-type="corresp"><sup>&#x002A;</sup></xref>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Quality Control and Evaluation, The First Affiliated Hospital, Sun Yat-sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country></aff>
<aff id="aff2"><sup>2</sup><institution>Center for Information Technology and Statistics, The First Affiliated Hospital, Sun Yat-sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country></aff>
<aff id="aff4"><sup>4</sup><institution>Center of Hepato-Pancreato-Biliary Surgery, The First Affiliated Hospital, Sun Yat-sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country></aff>
<author-notes>
<fn id="fn0001" fn-type="edited-by"><p>Edited by: Thamara Perera, Queen Elizabeth Hospital Birmingham, United Kingdom</p></fn>
<fn id="fn0002" fn-type="edited-by"><p>Reviewed by: Nicholas Schiltz, Case Western Reserve University, United States; Deborah Verran, Consultant, Sydney, Australia</p></fn>
<corresp id="c001">&#x002A;Correspondence: Wujun Zhang, <email>zhangwuj@mail.sysu.edu.cn</email></corresp>
<corresp id="c002">Wei Chen, <email>chenw57@mail.sysu.edu.cn</email></corresp>
<fn id="fn0003" fn-type="equal"><p><sup>&#x2020;</sup>These authors have contributed equally to this work and share first authorship</p></fn>
<fn id="fn0004" fn-type="other"><p>This article was submitted to Digital Public Health, a section of the journal Frontiers in Public Health</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>06</day>
<month>04</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>11</volume>
<elocation-id>1092182</elocation-id>
<history>
<date date-type="received">
<day>07</day>
<month>11</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>17</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2023 Lu, Lin, Xiong, Pang, Zhang, Xin, Li, Shen, Chen and Zhang.</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Lu, Lin, Xiong, Pang, Zhang, Xin, Li, Shen, Chen and Zhang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>In July 2017, the first affiliated hospital of Sun Yat-sen university carried out the world&#x2019;s first case of ischemia-free liver transplantation (IFLT). This study aimed to evaluate the performance of medical services pre- and post-IFLT implementation in the organ transplant department of this hospital based on diagnosis-related groups, so as to provide a data basis for the clinical practice of the organ transplant specialty.</p>
</sec>
<sec>
<title>Methods</title>
<p>The first pages of medical records of inpatients in the organ transplant department from 2016 to 2019 were collected. The China version Diagnosis-related groups (DRGs) were used as a risk adjustment tool to compare the income structure, service availability, service efficiency and service safety of the organ transplant department between the pre- and post-IFLT implementation periods.</p>
</sec>
<sec>
<title>Results</title>
<p>Income structure of the organ transplant department was more optimized in the post-IFLT period compared with that in the pre-IFLT period. Medical service performance parameters of the organ transplant department in the post-IFLT period were better than those in the pre-IFLT period. Specifically, case mix index values were 2.65 and 2.89 in the pre- and post-IFLT periods, respectively (<italic>p</italic>&#x2009;=&#x2009;0.173). Proportions of organ transplantation cases were 14.16 and 18.27%, respectively (<italic>p</italic>&#x2009;&#x003C;&#x2009;0.001). Compared with that in the pre-IFLT period, the average postoperative hospital stay of liver transplants decreased by 11.40% (30.17 vs. 26.73&#x2009;days, <italic>p</italic>&#x2009;=&#x2009;0.006), and the average postoperative hospital stay of renal transplants decreased by 7.61% (25.23 vs.23.31&#x2009;days, <italic>p</italic>&#x2009;=&#x2009;0.092). Cost efficiency index decreased significantly compared with that in the pre-IFLT period (<italic>p</italic>&#x2009;&#x003C;&#x2009;0.001), while time efficiency index fluctuated around 0.83 in the pre- and post-IFLT periods (<italic>p</italic>&#x2009;=&#x2009;0.725). Moreover, the average postoperative hospital stay of IFLT cases was significantly shorter than that of conventional liver transplant cases (<italic>p</italic>&#x2009;=&#x2009;0.001).</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The application of IFLT technology could contribute to improving the medical service performance of the organ transplant department. Meanwhile, the DRGs tool may help transplant departments to coordinate the future delivery planning of medical service.</p>
</sec>
</abstract>
<kwd-group>
<kwd>diagnosis-related groups</kwd>
<kwd>medical services</kwd>
<kwd>liver transplant</kwd>
<kwd>performance evaluation</kwd>
<kwd>ischemia-free liver transplant</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="6"/>
<equation-count count="6"/>
<ref-count count="42"/>
<page-count count="11"/>
<word-count count="7806"/>
</counts>
</article-meta>
</front>
<body>
<sec id="sec5" sec-type="intro">
<title>Introduction</title>
<p>Liver transplant (LT) is the only effective treatment for patients with end-stage liver disease. However, there are many difficulties in its clinical application. On the one hand, there are many patients in the world who cannot receive transplants due to a shortage of donor organs. For example, the growing demand for liver grafts remains an unsolved challenge for the transplant community (<xref ref-type="bibr" rid="ref1">1</xref>). According to the report of the Organ Procurement and Transplantation Network (OPTN), the number of new liver transplantation waiting list registrations in the United States (12,767 cases) continued to grow in 2019 (<xref ref-type="bibr" rid="ref2">2</xref>). Donor organ shortage is common in various countries to varying degrees, including the persistent shortage of deceased donor organs for transplantation and the limited number of potential donors after brain death (<xref ref-type="bibr" rid="ref3">3</xref>). On the other hand, ischemia during an organ transplant is a temporary interruption of blood flow to the organ during the transplant. This can occur during the organ&#x2019;s removal from the donor and transport to the recipient (known as cold ischemia), and during the surgical implantation process (known as warm ischemia). Ischemia can lead to tissue damage and inflammation, leading to poor transplant outcomes. In liver transplantation, prolonged cold ischemia is associated with an increased risk of graft dysfunction and primary non-function, while warm ischemia during implantation can lead to delayed graft function and reduced graft survival.</p>
<p>Previous studies suggested that longer cold/warm ischemia time was identified as an independent risk factor for moderate to severe ischemia&#x2013;reperfusion injury (<xref ref-type="bibr" rid="ref4">4</xref>). Longer cold ischemia is associated with poorer liver transplantation outcomes (<xref ref-type="bibr" rid="ref5">5</xref>). A similar situation has been reported in kidney transplantation. For example, the current gold standard for preserving donor kidneys is static refrigeration at 4&#x00B0;C. However, this can lead to renal ischemia&#x2013;reperfusion injury, which adversely affects graft survival and function (<xref ref-type="bibr" rid="ref6">6</xref>, <xref ref-type="bibr" rid="ref7">7</xref>). In fact, risk factors associated with primary graft nonfunction include donor age, cold ischemia time, warm ischemia time, and graft quality. A study based on data from the United Kingdom Transplant Registry suggests that cold ischemia duration of more than 8&#x2009;h is a risk factor for primary non-function and reduced graft survival after liver transplantation (<xref ref-type="bibr" rid="ref8">8</xref>). Moreover, currently available donor organs are more likely to come from marginal donors (such as those from older, obese individuals), and these marginal organs tend to have a higher risk of ischemia&#x2013;reperfusion injury. Therefore, how to limit or even reverse graft ischemia is of great significance for improving the success rate of transplantation (<xref ref-type="bibr" rid="ref9">9</xref>).</p>
<p>Hypothermic preservation is the storage of organs or tissues in a relatively low temperature environment (2&#x2009;~&#x2009;8&#x00B0;C), often used to preserve the liver, kidney, heart, etc. Currently, the majority of deceased donor livers are preserved <italic>via</italic> the cold static preservation technique in transport containers with melting ice as the medium for maintaining that temperature. Donor livers usually need to be stored in cold storage for a long period of time during transport from donor to recipient hospital prior to transplantation. Cold ischemia time was defined as the time interval between liver acquisition and liver reperfusion. In the clinical practice of organ transplantation, the cold/warm ischemia process of donor organ after circulatory death may affect the viability of donor organ.</p>
<p>Currently, many measures are used to reduce ischemic damage to candidate organs in order to optimize donor organ quality. For example, normothermic regional perfusion and <italic>ex situ</italic> perfusion techniques can enhance the preservation, evaluation, resuscitation, and/or repair of damaged organs, thereby improving overall organ quality (<xref ref-type="bibr" rid="ref3">3</xref>). Use of hypothermic machine perfusion immediately before liver transplantation reduces the chance of perfusion dysfunction during early transplantation. Hypothermic machine perfusion can also reduce the risk of delayed graft function and improve graft survival (<xref ref-type="bibr" rid="ref10">10</xref>).</p>
<p>In July 2017, the first affiliated hospital of Sun Yat-sen university successfully carried out the first ischemia-free liver transplantation (IFLT) in the world. As ischemia-free organ transplant technology has significantly improved the performance of medical services in the field of liver transplant, a professional team from the organ transplantation department of this hospital was awarded the Grand Prize in the 2020 international quality innovation competition. At present, ischemia-free transplant is considered as a milestone in the history of organ transplant, which could be extended to the transplantation fields of heart, lung and kidney, and has a broad application prospect.</p>
<p>Scientific evaluation of medical service performance is helpful to improve the clinical practice of organ transplant. Diagnosis-related groups (DRGs) are cases combination tools developed by American scholars in the 1970s, which are suitable for the evaluation of short-term hospitalization medical service performance and medical insurance payment (<xref ref-type="bibr" rid="ref11">11</xref>, <xref ref-type="bibr" rid="ref12">12</xref>). Now DRGs were widely used in many countries and regions in North America, Europe, Oceania and Asia (<xref ref-type="bibr" rid="ref13 ref14 ref15">13&#x2013;15</xref>). Previous studies have used DRGs tool to evaluate the service performance and hospitalization cost of care for cancers (<xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref17">17</xref>), spinal surgery (<xref ref-type="bibr" rid="ref18">18</xref>, <xref ref-type="bibr" rid="ref19">19</xref>) and carotid stent implantation (<xref ref-type="bibr" rid="ref20">20</xref>). However, to our knowledge, there have been no studies using the DRGs tool to evaluate the performance of medical care for organ transplant. Therefore, this study aimed to evaluate and compare the overall medical service performance of the organ transplant department between the pre-IFLT and post-IFLT periods.</p>
</sec>
<sec id="sec6" sec-type="methods">
<title>Methods</title>
<sec id="sec7">
<title>Data source</title>
<p>In 2012, medical institutions in Guangdong began to use a universal discharge summary to record the information of hospitalized patients. This summary, known as the First Page of Medical Records (FPMR), contains basic information (demographics, admission date, discharge dates, etc.), diagnostic information (primary diagnosis, other diagnoses, treatment outcomes, etc.), surgical procedure information (primary operation, other operations, etc.), and medical cost information. The 10th International Classification of Diseases (ICD-10) and the ninth International Classification of Diseases (ICD-9-CM-3) were used to code diagnosis and surgical procedures, respectively. The medical service analysis system of hospitalized patients with DRGs provided by the software company (Wuhan Dongfang Succe Software Co., LTD.) was used for data analysis.</p>
<p>In this study, we retrospectively analyzed the FPMR of patients admitted to the organ transplant department at the hospital studied from 2016 to 2019. The inclusion criteria of this study were: (a) date of discharge from hospital between January 2016 and December 2019; (b) The discharged department was organ transplantation department. The exclusion criteria was that key information about the case (diagnosis, surgery, medical costs, etc.) was missing. Based on the above criteria, 9,718 records were collected for further analysis. Meanwhile, since organ re-transplantation cases were not grouped separately in the DRGs system, re-transplantation cases (including liver transplantation and kidney transplantation cases) were not excluded from the study and were included as separate cases. There were 0, 1, 1 and 2 cases of liver re-transplantation, while there were 3, 5, 7 and 8 cases of kidney re-transplantation in 2016, 2017, 2018 and 2019, respectively.</p>
<p>Ischemia of the donor organ during the acquisition and transplantation stage leads to ischemia&#x2013;reperfusion injury. In July 2017, the first affiliated hospital of Sun Yat-sen university was the first worldwide to carry out ischemia-free liver transplantation. This non-ischemic organ transplantation technology pioneered by the first affiliated hospital of Sun Yat-sen university worldwide is a new method that continuously applies local perfusion at normal temperature during the stages of donor organ acquisition, preservation and transplantation to ensure continuous blood supply to organs (<xref rid="SM1" ref-type="supplementary-material">Supplementary Figure S1</xref>). In this study, the period from January 1, 2016 to June 30, 2017 was defined as the &#x201C;pre-IFLT period&#x201D; and the period from July 1, 2017 to December 31, 2019 was defined as the &#x201C;post-IFLT period.&#x201D; Specifically, 3,510 hospitalizations were included in the analysis during the pre-IFLT period, including 497 (14.16%) solid organ recipients, and 6,208 hospitalizations were included in the analysis during the post-IFLT period, including 1,134 (18.27%) solid organ recipients. In addition, there were 54 IFLT transplant recipients in the post-IFLT period.</p>
</sec>
<sec id="sec8">
<title>DRGs selection methods</title>
<p>Beijing Institute of Hospital Management pioneered DRGs researches in China. In 2011, Beijing DRGs grouping scheme began to be promoted and applied in China. In 2015, the former National Health and Family Planning Commission launched the 2014 version of the China DRGs (CN-DRGs) grouping scheme applicable to the coded data environment of diseases and surgeries in China based on the Beijing DRG grouping scheme. Subsequently, the National Health Commission of China released a revised version of the 2014 edition: the CN-DRGs Grouping Scheme 2018 edition. As a Guangdong Province specific DRG has not yet been developed, the CN DRG (2018 edition) was used as a risk adjustment tool in this study. CN DRGs were divided into 26 main diagnostic categories (MDC) and 806 DRGs (<xref ref-type="bibr" rid="ref21">21</xref>) according to the characteristics of the cases (age, sex, diagnosis, operation, comorbidities and complications, etc.). <xref rid="fig1" ref-type="fig">Figure 1</xref> shows the group path of the CN DRG.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>CN-DRGs grouping path. MDC, Major Diagnostic Category. CN-DRGs, China diagnosis-related groups.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g001.tif"/>
</fig>
<sec id="sec9">
<title>DRG evaluation indicators</title>
<p>Previous studies suggest that DRGs-based evaluation can help improve the comparability of cases and the reliability of evaluation results. It is an important part of medical performance evaluation in medical service research and can provide a basis for rational decision-making (<xref ref-type="bibr" rid="ref22 ref23 ref24">22&#x2013;24</xref>). According to the evaluation methods of DRGs, we used six objective indicators of medical service performance to evaluate the available scope, efficiency and safety of medical services for the organ transplant specialty. The average levels of DRGs indices of medical institutions in Guangdong Province were used as the standards in the calculation of DRG index data (<xref rid="tab1" ref-type="table">Table 1</xref>).</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Health system performance evaluation indicators based on DRGs.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Dimension</th>
<th align="left" valign="top">Indicators</th>
<th align="left" valign="top">Evaluation contents</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle"><bold>Availability</bold></td>
<td align="left" valign="middle">Number of DRGs</td>
<td align="left" valign="middle">The range of services available</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Total weight</td>
<td align="left" valign="middle">Total output of in-patient services</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Case-mix index (CML)</td>
<td align="left" valign="middle">Average technical difficulty level of treating diseases in each discipline</td>
</tr>
<tr>
<td align="left" valign="middle"><bold>Efficiency</bold></td>
<td align="left" valign="middle">Charge efficiency index (CEI)</td>
<td align="left" valign="middle">Cost of treating similar diseases</td>
</tr>
<tr>
<td/>
<td align="left" valign="middle">Time efficiency index (TEI)</td>
<td align="left" valign="middle">Time for treating similar diseases</td>
</tr>
<tr>
<td align="left" valign="middle"><bold>Safety</bold></td>
<td align="left" valign="middle">Inpatient mortality of low-risk group cases (IMLRG)</td>
<td align="left" valign="middle">Mortality of diseases that are extremely unlikely to cause death</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="sec10">
<title>Service availability indicators</title>
<p>The number of DRGs, total weight, and case mix index (CMI) were used to assess the availability of medical service to reflect the scope of care, total output and the adjusted technical difficulty of case treatment. The total weight and CMI are calculated as follows:</p>
<disp-formula id="E1"><mml:math id="M1"><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mi mathvariant="normal">Total weight</mml:mi><mml:mo>=</mml:mo><mml:mo>&#x2211;</mml:mo><mml:mi mathvariant="normal">Each</mml:mi><mml:mspace width="thickmathspace"/><mml:mi mathvariant="normal">DRG</mml:mi><mml:mspace width="thickmathspace"/><mml:mi mathvariant="normal">weight</mml:mi><mml:mo>&#x00D7;</mml:mo></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mi mathvariant="normal">Number of cases in each</mml:mi><mml:mspace width="thickmathspace"/><mml:mi mathvariant="normal">DRG</mml:mi><mml:mspace width="thickmathspace"/></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula><disp-formula id="E2"><mml:math id="M2"><mml:mrow><mml:mi mathvariant="normal">CMI</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi mathvariant="normal">Total weight</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant="normal">Number of cases in Guangdong</mml:mi></mml:mrow></mml:mfrac></mml:mrow></mml:math></disp-formula>
<p>By dividing the average cost of each DRG group by the average cost of all cases in Guangdong Province, each DRG weight was calculated. DRG weights were averaged to create CMI.</p>
<p>Besides, relative weight (RW) is analyzed in this study. In the DRGs evaluation system, the RW is the weight given to each DRG according to its degree of resource consumption, reflecting the degree of hospital resource consumption of the DRGs relative to other diseases. The higher the value, the higher the resource consumption of the case portfolio. The formula is: RW&#x2009;=&#x2009;average cost of this DRGs/average cost of all disease groups. Therefore, the RW indicator was used in this study as a measure of severity and resource utilization in a particular DRG group.</p>
</sec>
<sec id="sec11">
<title>Service efficiency indicators</title>
<disp-formula id="E3"><mml:math id="M3"><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mi>C</mml:mi><mml:mi>o</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi> </mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>o</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mi>k</mml:mi><mml:mi>c</mml:mi></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mfrac><mml:mrow><mml:mi>a</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi> </mml:mi><mml:mi>c</mml:mi><mml:mi>o</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi> </mml:mi><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>a</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi> </mml:mi><mml:mi>G</mml:mi><mml:mi>u</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>d</mml:mi><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi> </mml:mi><mml:mi>P</mml:mi><mml:mi>r</mml:mi><mml:mi>o</mml:mi><mml:mi>v</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>c</mml:mi><mml:mi>e</mml:mi><mml:mspace width="thickmathspace"/><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mi>c</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mi>a</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi> </mml:mi><mml:mi>c</mml:mi><mml:mi>o</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi> </mml:mi><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>a</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>C</mml:mi><mml:mi>N</mml:mi><mml:mo>&#x2212;</mml:mo><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mi>s</mml:mi><mml:mspace width="thickmathspace"/><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>C</mml:mi><mml:mo>&#x00AF;</mml:mo></mml:mover><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>
<disp-formula id="E4"><mml:math id="M4"><mml:mtable columnalign="left"><mml:mtr><mml:mtd><mml:mi>A</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi> </mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>t</mml:mi><mml:mi>h</mml:mi><mml:mi> </mml:mi><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mi> </mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi>a</mml:mi><mml:mi>y</mml:mi><mml:mspace width="thickmathspace"/><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>A</mml:mi><mml:mi>L</mml:mi><mml:mi>O</mml:mi><mml:mi>S</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mspace width="thickmathspace"/><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>t</mml:mi><mml:mi>i</mml:mi><mml:mi>o</mml:mi><mml:mspace width="thickmathspace"/><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msup><mml:mi>k</mml:mi><mml:mi>l</mml:mi></mml:msup></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo></mml:mtd></mml:mtr><mml:mtr><mml:mtd><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mspace width="0.25em"/><mml:mfrac><mml:mrow><mml:mi>a</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi> </mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>t</mml:mi><mml:mi>h</mml:mi><mml:mi> </mml:mi><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>a</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi> </mml:mi><mml:mi>G</mml:mi><mml:mi>u</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>d</mml:mi><mml:mi>o</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi> </mml:mi><mml:mi>P</mml:mi><mml:mi>r</mml:mi><mml:mi>o</mml:mi><mml:mi>v</mml:mi><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mi>c</mml:mi><mml:mi>e</mml:mi></mml:mrow><mml:mrow><mml:mi>a</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi><mml:mi>a</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi> </mml:mi><mml:mi>l</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>g</mml:mi><mml:mi>t</mml:mi><mml:mi>h</mml:mi><mml:mi> </mml:mi><mml:mi>o</mml:mi><mml:mi>f</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>a</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>i</mml:mi><mml:mi>n</mml:mi><mml:mspace width="thickmathspace"/><mml:mi>C</mml:mi><mml:mi>N</mml:mi><mml:mo>&#x2212;</mml:mo><mml:mi>D</mml:mi><mml:mi>R</mml:mi><mml:mi>G</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msub><mml:mover accent="true"><mml:mi>L</mml:mi><mml:mo>&#x00AF;</mml:mo></mml:mover><mml:mi>i</mml:mi></mml:msub></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mtd></mml:mtr></mml:mtable></mml:math></disp-formula>
<p>The Cost efficiency index (CEI) and the Time efficiency index (TEI) were used to evaluate the efficiency of medical services. The CEI and TEI are the results of individual medical institutions compared to the average of all hospitals included in the CN DRG assessment in terms of medical costs and length of stay (LOS). Therefore, the higher the CEI and TEI values, the lower the efficiency of medical services. TEI and CEI greater than 1, respectively, indicate that the time efficiency and cost efficiency required to treat the same diseases are lower than the standard samples (<xref ref-type="bibr" rid="ref22">22</xref>). CEI and TEI are calculated as follows:</p>
<disp-formula id="E5"><mml:math id="M5"><mml:mrow><mml:mi mathvariant="normal">CEI</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mstyle displaystyle="true"><mml:mo>&#x2211;</mml:mo></mml:mstyle><mml:mi mathvariant="normal">j</mml:mi></mml:msub><mml:msubsup><mml:mi mathvariant="normal">k</mml:mi><mml:mi mathvariant="normal">j</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msubsup><mml:msub><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">j</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mstyle displaystyle="true"><mml:mo>&#x2211;</mml:mo></mml:mstyle><mml:mi mathvariant="normal">j</mml:mi></mml:msub><mml:msub><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">j</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:math></disp-formula>
<disp-formula id="E6"><mml:math id="M6"><mml:mrow><mml:mi mathvariant="normal">TEI</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mstyle displaystyle="true"><mml:mo>&#x2211;</mml:mo></mml:mstyle><mml:mi mathvariant="normal">j</mml:mi></mml:msub><mml:msubsup><mml:mi mathvariant="normal">k</mml:mi><mml:mi mathvariant="normal">j</mml:mi><mml:mi mathvariant="normal">l</mml:mi></mml:msubsup><mml:msub><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">j</mml:mi></mml:msub></mml:mrow><mml:mrow><mml:msub><mml:mstyle displaystyle="true"><mml:mo>&#x2211;</mml:mo></mml:mstyle><mml:mi mathvariant="normal">j</mml:mi></mml:msub><mml:msub><mml:mi mathvariant="normal">n</mml:mi><mml:mi mathvariant="normal">j</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:mrow></mml:math></disp-formula>
<p>where n<sub>j</sub> represents the number of cases in DRGj. The weighted averages of k<sup>c</sup> and k<sup>l</sup> represent TEI and CEI.</p>
</sec>
<sec id="sec12">
<title>Medical safety indicators</title>
<p>Inpatient mortality of low-risk group cases (IMLRP) is the mortality cases from a disease that is highly unlikely to cause death and can therefore be used to reflect the safety of medical services (<xref ref-type="bibr" rid="ref25">25</xref>). IMLRP is calculated as follows: (a) Calculation of in-hospital mortality rates (Mi) for each DRG, (b) Calculate the logarithm of Mi (Ln (Mi)), (c) Calculate the mean and standard deviation of L (Mi), and (d) Calculation of a mortality risk score. A mortality risk score of 1 was defined as a low-risk group.</p>
<p>In the DRGs evaluation system, the low-risk group of cases refers to the low risk of death cases generated by the DRGs grouping in a certain year. Specifically, the low-risk group is the DRG group in which the mortality rate of cases is less than minus one standard deviation. In DRG evaluation system, low-risk group mortality is often used to measure the safety of medical services. The basic principle is that once a non-critical case of death occurs, it means that the cause of death is likely to lie not in the disease itself but in the clinical or managerial process.</p>
</sec>
</sec>
<sec id="sec13">
<title>Statistical analysis</title>
<p>Comparing independent samples was done using Mann&#x2013;Whitney U tests with continuous variables expressed as average values. Chi-square tests or Fisher exact tests are used to compare categorical variables expressed as counts or percentages (%). Statistical significance was judged based on <italic>p</italic>&#x2009;&#x003C;&#x2009;0.05 values (bilaterally). The time trend of continuous variables can be represented by line charts. The analyses were conducted using SPSS version 22.0 (IBM Corp., Armonk, NY, United States).</p>
</sec>
</sec>
<sec id="sec14" sec-type="results">
<title>Results</title>
<sec id="sec15">
<title>Sample characteristics</title>
<p>In this study, we collected the medical records of 9,718 inpatients admitted to the organ transplant department of this hospital between January 2016 and December 2019. Of those, 3,510 were hospitalized during the pre-IFLT period and 6,208 were hospitalized during the post-IFLT period. The demographic characteristics of liver and renal transplant recipients in the pre- and post-IFLT periods were analyzed, respectively. As shown in <xref rid="tab2" ref-type="table">Table 2</xref>, there was no significant difference in the age and gender distribution of liver transplant patients before and after IFLT. Meanwhile, the proportion of kidney transplant patients older than 40&#x2009;years increased after IFLT compared with those before IFLT (<italic>p</italic> =&#x2009;0.027), with no significant difference in gender distribution.</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Demographic characteristics of organ transplant recipients in the pre- and post-IFLT periods.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" colspan="2" rowspan="2">Demographic characteristics</th>
<th align="center" valign="top">Pre-IFLT</th>
<th align="center" valign="top">Post-IFLT</th>
<th align="center" valign="top" rowspan="2"><italic>&#x03C7;</italic><sup>2</sup> value</th>
<th align="center" valign="top" rowspan="2"><italic>p</italic> value</th>
</tr>
<tr>
<th align="center" valign="top"><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>n</italic> (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom" colspan="6"><italic>LT</italic></td>
</tr>
<tr>
<td align="left" valign="bottom">Age</td>
<td align="left" valign="top">&#x003C;40</td>
<td align="char" valign="top" char="(">41 (20.92)</td>
<td align="char" valign="top" char="(">75 (20.83)</td>
<td align="char" valign="middle" char="." rowspan="2">0.001</td>
<td align="char" valign="middle" char="." rowspan="2">0.981</td>
</tr>
<tr>
<td/>
<td align="left" valign="top">&#x003E;&#x2009;=&#x2009;40</td>
<td align="char" valign="top" char="(">155 (79.08)</td>
<td align="char" valign="top" char="(">285 (79.17)</td>
</tr>
<tr>
<td align="left" valign="bottom">Gender</td>
<td align="left" valign="bottom">Female</td>
<td align="char" valign="top" char="(">29 (14.80)</td>
<td align="char" valign="top" char="(">49 (13.61)</td>
<td align="char" valign="middle" char="." rowspan="2">0.148</td>
<td align="char" valign="middle" char="." rowspan="2">0.701</td>
</tr>
<tr>
<td/>
<td align="left" valign="bottom">Male</td>
<td align="char" valign="top" char="(">167 (85.20)</td>
<td align="char" valign="top" char="(">311 (86.39)</td>
</tr>
<tr>
<td align="left" valign="bottom" colspan="6"><italic>RT</italic></td>
</tr>
<tr>
<td align="left" valign="bottom">Age</td>
<td align="left" valign="bottom">&#x003C;40</td>
<td align="char" valign="top" char="(">186 (63.05)</td>
<td align="char" valign="top" char="(">424 (55.57)</td>
<td align="char" valign="middle" char="." rowspan="2">4.877</td>
<td align="char" valign="middle" char="." rowspan="2">0.027</td>
</tr>
<tr>
<td/>
<td align="left" valign="bottom">&#x003E;&#x2009;=&#x2009;40</td>
<td align="char" valign="top" char="(">109 (36.95)</td>
<td align="char" valign="top" char="(">339 (44.43)</td>
</tr>
<tr>
<td align="left" valign="bottom">Gender</td>
<td align="left" valign="bottom">Female</td>
<td align="char" valign="top" char="(">89 (30.17)</td>
<td align="char" valign="top" char="(">267 (34.99)</td>
<td align="char" valign="middle" char="." rowspan="2">2.217</td>
<td align="char" valign="middle" char="." rowspan="2">0.136</td>
</tr>
<tr>
<td/>
<td align="left" valign="bottom">Male</td>
<td align="char" valign="top" char="(">206 (69.83)</td>
<td align="char" valign="top" char="(">496 (65.01)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>LT, liver transplant; RT, renal transplant; IFLT, ischemia-free liver transplant.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec16">
<title>Comparison of clinical income structure</title>
<p>Compared with the pre-IFLT period, the income structure during the post-IFLT period was significantly optimized (<italic>p</italic> &#x003C;&#x2009;0.001). Specifically, although the average hospitalization cost increased by 11.44% during the post-IFLT period, the proportion of drug costs decreased by 17.65%. In addition, the proportion of material expense, examination expense, service expense and treatment income increased by 46.62, 4.14, 21.62 and 51.64%, respectively, (<xref rid="tab3" ref-type="table">Table 3</xref>).</p>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Comparison of clinical income structure of the organ transplant department between the pre- and post-IFLT periods.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Income structure</th>
<th align="center" valign="top">Pre-IFLT</th>
<th align="center" valign="top">Post-IFLT</th>
<th align="center" valign="top">Percentage change (%)</th>
<th align="center" valign="top"><italic>&#x03C7;</italic><sup>2</sup> value</th>
<th align="center" valign="top"><italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">Average cost (Yuan)</td>
<td align="center" valign="top">28780</td>
<td align="center" valign="top">32073</td>
<td align="char" valign="top" char=".">11.44</td>
<td align="center" valign="top">&#x2014;</td>
<td align="center" valign="top">&#x2014;</td>
</tr>
<tr>
<td align="left" valign="bottom">Drug cost (%)</td>
<td align="char" valign="top" char=".">47.42</td>
<td align="char" valign="top" char=".">39.05</td>
<td align="char" valign="top" char=".">&#x2212;17.65</td>
<td align="char" valign="middle" char="." rowspan="6">938.783</td>
<td align="char" valign="middle" char="." rowspan="6">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="bottom">Material cost (%)</td>
<td align="char" valign="top" char=".">7.55</td>
<td align="char" valign="top" char=".">11.07</td>
<td align="char" valign="top" char=".">46.62</td>
</tr>
<tr>
<td align="left" valign="bottom">Examination cost (%)</td>
<td align="char" valign="top" char=".">20.99</td>
<td align="char" valign="top" char=".">21.86</td>
<td align="char" valign="top" char=".">4.14</td>
</tr>
<tr>
<td align="left" valign="bottom">Service income (%)</td>
<td align="char" valign="top" char=".">6.29</td>
<td align="char" valign="top" char=".">7.65</td>
<td align="char" valign="top" char=".">21.62</td>
</tr>
<tr>
<td align="left" valign="bottom">Treatment income (%)</td>
<td align="char" valign="top" char=".">9.78</td>
<td align="char" valign="top" char=".">14.83</td>
<td align="char" valign="top" char=".">51.64</td>
</tr>
<tr>
<td align="left" valign="bottom">Other costs (%)</td>
<td align="char" valign="top" char=".">7.97</td>
<td align="char" valign="top" char=".">5.53</td>
<td align="char" valign="top" char=".">&#x2212;30.61</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>IFLT, ischemia-free liver transplant.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec17">
<title>Application of the ischemia-free transplant technique</title>
<p>The Sankey chart was used to visualize the application of ischemia-free transplantation technique in the organ transplant department during the post-IFLT period (<xref rid="fig2" ref-type="fig">Figure 2</xref>). A total of 1,132 organ transplants were performed, including 363 liver transplants, 763 kidney transplants, 6 combined liver and kidney transplants and 2 other organ transplants. Specifically, of the 363 liver transplants in the post-ILFT period, 54 were IFLTs and 309 were conventional liver transplants (CLT).</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Sankey diagram depicting the selection of surgical methods in a tertiary hospital from July 2017 to December 2019. LT, liver transplant. RT, renal transplant. COT, conventional organ transplant. IFOT, ischemia-free organ transplant.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g002.tif"/>
</fig>
</sec>
<sec id="sec18">
<title>Promotion of clinical service capacity by the new technique</title>
<p>As shown in <xref rid="fig3" ref-type="fig">Figure 3</xref>, the clinical service capability parameters of the organ transplantation department of this hospital in the post-IFLT period were better than those in the pre-IFLT period, suggesting that the implementation of ischemia-free liver transplantation improved the clinical service capability of this specialty in the hospital where this study was conducted.</p>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>Comparison the medical service performance for department of organ transplant between 2016 and 2019. DRGs, diagnosis-related groups. CMI, Case Mix Index. TMI, time efficiency index. CEI, charge efficiency index.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g003.tif"/>
</fig>
</sec>
<sec id="sec19">
<title>Availability of medical services</title>
<sec id="sec20">
<title>DRGs, CMI and RW comparison</title>
<p>As shown in <xref rid="tab4" ref-type="table">Table 4</xref>, the number of DRGs in the organ transplantation department during the pre-IFLT period and post-IFLT period was 149 and 188, respectively. The CMI value in pre-IFLT period and post-IFLT period was 2.65 and 2.89, respectively. There was no significant difference in CMI between the two periods (<italic>p</italic>&#x2009;=&#x2009;0.173, <xref rid="fig4" ref-type="fig">Figure 4A</xref>). The distribution of RW values in the post-IFLT period changed significantly compared with that in the pre-IFLT period (<italic>p</italic> &#x003C;&#x2009;0.001). In the post-IFLT period, the proportion of RW 5&#x2013;10 cases increased by 3.81 (8.38% vs. 12.19%), while the proportion of RW 1.5&#x2013;5 cases decreased by 2.42% (10.91% vs. 8.49%). The proportion of cases with RW&#x2009;&#x003C;&#x2009;1.5 and RW&#x2009;&#x003E;&#x2009;10 showed only slight changes. In addition, there were no low-risk deaths in either period.</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Evaluation of clinical competence of the organ transplant department in the pre- and post-IFLT periods by DRGs.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Clinical competence evaluation</th>
<th align="center" valign="top">Pre-IFLT</th>
<th align="center" valign="top">Post-IFLT</th>
<th align="center" valign="top"><italic>&#x03C7;</italic><sup>2</sup>/<italic>Z</italic> value</th>
<th align="center" valign="top"><italic>p</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle"><italic>Diagnosis and treatment ability</italic></td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Discharge patients</td>
<td align="center" valign="middle">3510</td>
<td align="center" valign="middle">6208</td>
<td align="center" valign="middle">&#x2014;</td>
<td align="center" valign="middle">&#x2014;</td>
</tr>
<tr>
<td align="left" valign="middle">DRGs</td>
<td align="center" valign="middle">149</td>
<td align="center" valign="middle">188</td>
<td align="center" valign="middle">&#x2014;</td>
<td align="center" valign="middle">&#x2014;</td>
</tr>
<tr>
<td align="left" valign="middle">CMI</td>
<td align="char" valign="middle" char=".">2.65</td>
<td align="char" valign="middle" char=".">2.89</td>
<td align="char" valign="middle" char=".">&#x2212;1.363</td>
<td align="char" valign="middle" char=".">0.173</td>
</tr>
<tr>
<td align="left" valign="middle">RW value</td>
<td/>
<td/>
<td align="char" valign="middle" char=".">44.929</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">RW&#x2009;&#x003C;&#x2009;1.5</td>
<td align="char" valign="middle" char="(">2669 (76.04)</td>
<td align="char" valign="middle" char="(">4630 (74.58)</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">RW 1.5&#x2013;5</td>
<td align="char" valign="middle" char="(">383 (10.91)</td>
<td align="char" valign="middle" char="(">527 (8.49)</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">RW 5&#x2013;10</td>
<td align="char" valign="middle" char="(">294 (8.38)</td>
<td align="char" valign="middle" char="(">757 (12.19)</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">RW&#x2009;&#x003E;&#x2009;10</td>
<td align="char" valign="middle" char="(">164 (4.67)</td>
<td align="char" valign="middle" char="(">294 (4.74)</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">Number of organ transplant surgeries, n (%)</td>
<td align="char" valign="top" char="(">497 (14.16)</td>
<td align="char" valign="top" char="(">1134 (18.27)</td>
<td align="char" valign="top" char=".">27.082</td>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">LT</td>
<td align="char" valign="top" char="(">196 (39.44)</td>
<td align="char" valign="top" char="(">360 (31.75)</td>
<td align="char" valign="top" char=".">9.096</td>
<td align="char" valign="top" char=".">0.003</td>
</tr>
<tr>
<td align="left" valign="middle">RT</td>
<td align="char" valign="top" char="(">295 (59.36)</td>
<td align="char" valign="top" char="(">763 (67.28)</td>
<td align="char" valign="top" char=".">9.530</td>
<td align="char" valign="top" char=".">0.002</td>
</tr>
<tr>
<td align="left" valign="middle">LT&#x0026;RT</td>
<td align="char" valign="top" char="(">3 (0.60)</td>
<td align="char" valign="top" char="(">6 (0.53)</td>
<td align="char" valign="top" char=".">0.035</td>
<td align="char" valign="top" char=".">0.852</td>
</tr>
<tr>
<td align="left" valign="middle">Other organs</td>
<td align="char" valign="top" char="(">3 (0.60)</td>
<td align="char" valign="top" char="(">5 (0.44)</td>
<td align="char" valign="top" char=".">0.187</td>
<td align="char" valign="top" char=".">0.665</td>
</tr>
<tr>
<td align="left" valign="middle"><italic>Mean postoperative hospital stay (day)</italic></td>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="middle">LT</td>
<td align="char" valign="middle" char=".">30.17</td>
<td align="char" valign="middle" char=".">26.73</td>
<td align="char" valign="middle" char=".">&#x2212;2.758</td>
<td align="char" valign="middle" char=".">0.006</td>
</tr>
<tr>
<td align="left" valign="middle">RT</td>
<td align="char" valign="middle" char=".">25.23</td>
<td align="char" valign="middle" char=".">23.31</td>
<td align="char" valign="middle" char=".">&#x2212;1.682</td>
<td align="char" valign="middle" char=".">0.092</td>
</tr>
<tr>
<td align="left" valign="middle">TEI</td>
<td align="char" valign="middle" char=".">0.83</td>
<td align="char" valign="middle" char=".">0.83</td>
<td align="char" valign="middle" char=".">&#x2212;0.352</td>
<td align="char" valign="middle" char=".">0.725</td>
</tr>
<tr>
<td align="left" valign="middle">CEI</td>
<td align="char" valign="middle" char=".">1.40</td>
<td align="char" valign="middle" char=".">1.21</td>
<td align="char" valign="middle" char=".">&#x2212;3.794</td>
<td align="char" valign="middle" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="middle">IMLRG rate</td>
<td align="char" valign="middle" char=".">0.00</td>
<td align="char" valign="middle" char=".">0.00</td>
<td align="center" valign="middle">&#x2014;</td>
<td align="center" valign="middle">&#x2014;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>DRGs, diagnosis-related groups; LT, liver transplant; RT, renal transplant; CMI, case-mix index; RW, risk weight; CEI, cost efficiency index; TEI, time efficiency index. IMLRG, inpatient mortality of low-risk group cases.</p>
</table-wrap-foot>
</table-wrap>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Trend of point estimates of DRGs indicators from 2016 to 2019. <bold>(A)</bold> Trend of point estimates for CMI (pre- vs. post-IFLT, <italic>p</italic>&#x2009;=&#x2009;0.173). <bold>(B)</bold> Trend of point estimates for TEI (pre- vs. post-IFLT, <italic>p</italic>&#x2009;=&#x2009;0.0.725). <bold>(C)</bold> Trend of point estimates for CEI (pre- vs. post-IFLT, <italic>p</italic> &#x003C;&#x2009;0.001). DRGs, diagnosis-related groups. CMI, Case Mix Index. TMI, time efficiency index. CEI, charge efficiency index.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g004.tif"/>
</fig>
</sec>
<sec id="sec21">
<title>Distribution of transplant operations</title>
<p>The total number of pre-IFLT period and post-IFLT period transplant cases was 497 and 1,134, respectively. The proportion of pre-IFLT period and post-IFLT period transplant cases in the total number of discharged cases was 14.16 and 18.27%, respectively (<italic>p</italic> &#x003C;&#x2009;0.001). Meanwhile, the number of liver transplantation cases with pre-IFLT period and post-IFLT period accounted for 39.44 and 31.75% of total organ transplantation cases, respectively (<italic>p</italic> =&#x2009;0.003). The number of kidney transplantation cases with pre-IFLT period and post-IFLT period accounted for 59.36 and 67.28% of total organ transplantation cases, respectively (<italic>p</italic>&#x2009;=&#x2009;0.002). In addition, the number of combined liver and kidney transplantation cases with pre-IFLT period and post-IFLT period accounted for 0.60 and 0.53% of the total number of transplantation cases, respectively (<italic>p</italic> =&#x2009;0.852).</p>
</sec>
<sec id="sec22">
<title>Postoperative hospitalization days</title>
<p>Compared with the pre-IFLT period, the mean postoperative hospital stay was reduced by 11.40% (30.17 vs. 26.73&#x2009;days) for liver transplant cases and 7.61% (25.23 vs. 23.31&#x2009;days) for kidney transplant cases.</p>
</sec>
<sec id="sec23">
<title>Distribution of major DRGs</title>
<p>As shown in <xref rid="fig5" ref-type="fig">Figure 5</xref>, there were six DRG groups associated with the majority of cases throughout the study period. Specifically, the six DRGs are AB19 (Liver transplant), AE19 (Renal transplant), HZ15 (Other liver diseases without comorbidities and concomitant diseases), LZ15 (Other urinary system diseases, without comorbidities and concomitant diseases), LJ13 (other operations of the urinary system with comorbidities and concomitant diseases) and XS23 (followed up patients with complications and concomitant diseases). The total number of cases in the above six DRGs accounts for more than half of the total number of cases.</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>The ratio of major DRGs varies monthly from 2016 to 2019. DRGs, Diagnosis-related groups. Definition of main DRGs in the organ transplant department: AB19, Liver transplant. AE19. Renal transplant. HZ15, Other liver diseases without comorbidities and concomitant diseases. LZ15, Other urinary system diseases, without comorbidities and concomitant diseases. LJ13, other operations of the urinary system with comorbidities and concomitant diseases. XS23, followed up patients with complications and concomitant diseases.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g005.tif"/>
</fig>
</sec>
</sec>
<sec id="sec24">
<title>Efficiency of medical services</title>
<p>As shown in <xref rid="fig4" ref-type="fig">Figure 4B</xref>, TEI fluctuated around 0.83 throughout the study period, and there is no significant difference between TEIs in pre-IFLT and pre-IFLT periods (<italic>p</italic>&#x2009;=&#x2009;0.725). At the same time, CEI showed a downward trend, and there was a significant statistical difference between the pre-IFLT period and the pre-IFLT period (<italic>p</italic> &#x003C;&#x2009;0.001, <xref rid="fig4" ref-type="fig">Figure 4C</xref>).</p>
</sec>
<sec id="sec25">
<title>Safety of medical services</title>
<p>In this study, the low-risk group was the DRG group admitted to the organ transplantation department with a low risk of death. As shown in <xref rid="tab4" ref-type="table">Table 4</xref>, the mortality rate of low-risk cases in the organ transplant department was 0.00 both in the pre- and post-IFLT periods. During the study period, the distribution of patients at different risk grades of death in the organ transplant department was analyzed. As shown in <xref rid="tab5" ref-type="table">Table 5</xref>, compared with the pre-IFLT period, the proportion of low-risk cases admitted to the organ transplantation department in the post-IFLT period decreased, while the proportion of high-risk cases increased (<italic>p</italic> &#x003C;&#x2009;0.001), suggesting that more high-risk cases were admitted to the department after the application of IFLT technology.</p>
<table-wrap position="float" id="tab5">
<label>Table 5</label>
<caption>
<p>Distribution of patients with different risk grades of death admitted to the organ transplant department in the pre- and post-IFLT periods.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Mortality risk grade</th>
<th align="center" valign="top">Pre-IFLT</th>
<th align="center" valign="top">Post-IFLT</th>
<th align="center" valign="top" rowspan="2"><italic>&#x03C7;<sup>2</sup></italic> value</th>
<th align="center" valign="top" rowspan="2"><italic>p</italic> value</th>
</tr>
<tr>
<th align="center" valign="top"><italic>n</italic> (%)</th>
<th align="center" valign="top"><italic>n</italic> (%)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="bottom">No risk</td>
<td align="char" valign="bottom" char="(">247 (7.04)</td>
<td align="char" valign="bottom" char="(">405 (6.52)</td>
<td align="char" valign="middle" char="." rowspan="5">119.738</td>
<td align="char" valign="middle" char="." rowspan="5">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="bottom">Low risk</td>
<td align="char" valign="bottom" char="(">877 (24.98)</td>
<td align="char" valign="bottom" char="(">1096 (17.66)</td>
</tr>
<tr>
<td align="left" valign="bottom">Low-middle risk</td>
<td align="char" valign="bottom" char="(">1280 (36.47)</td>
<td align="char" valign="bottom" char="(">2878 (46.36)</td>
</tr>
<tr>
<td align="left" valign="bottom">Middle-high risk</td>
<td align="char" valign="bottom" char="(">750 (21.37)</td>
<td align="char" valign="bottom" char="(">1166 (18.78)</td>
</tr>
<tr>
<td align="left" valign="bottom">High risk</td>
<td align="char" valign="bottom" char="(">356 (10.14)</td>
<td align="char" valign="bottom" char="(">663 (10.68)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>LT, liver transplant; RT, renal transplant; IFLT, ischemia-free liver transplant.</p>
</table-wrap-foot>
</table-wrap>
<p>The annual number of transplant operations performed by the organ transplant department during the study period was analyzed. As shown in <xref rid="tab6" ref-type="table">Table 6</xref>, the total number of organ transplantation cases increased year by year from 2016 to 2019. Specifically, the annual number of implementation cases of CLT fluctuates between 110 and 130; The annual number of IFLT implementation cases fluctuates between 15 and 20; The annual number of RT cases has increased from 203 in 2016 to 353 in 2019.</p>
<table-wrap position="float" id="tab6">
<label>Table 6</label>
<caption>
<p>Annual number of transplants performed in the department during the study period.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top"><bold>Number of organ transplant surgeries n (%)</bold></th>
<th align="center" valign="top"><bold>2016</bold></th>
<th align="center" valign="top"><bold>2017</bold></th>
<th align="center" valign="top"><bold>2018</bold></th>
<th align="center" valign="top"><bold>2019</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="middle">CLT</td>
<td align="char" valign="top" char="(">124 (37.35)</td>
<td align="char" valign="top" char="(">131 (34.47)</td>
<td align="char" valign="top" char="(">131 (30.61)</td>
<td align="char" valign="top" char="(">116 (23.63)</td>
</tr>
<tr>
<td align="left" valign="middle">IFLT</td>
<td align="char" valign="top" char="(">0 (0.00)</td>
<td align="char" valign="top" char="(">16 (4.21)</td>
<td align="char" valign="top" char="(">19 (4.44)</td>
<td align="char" valign="top" char="(">19 (3.87)</td>
</tr>
<tr>
<td align="left" valign="middle">RT</td>
<td align="char" valign="top" char="(">203 (61.15)</td>
<td align="char" valign="top" char="(">232 (61.05)</td>
<td align="char" valign="top" char="(">270 (63.08)</td>
<td align="char" valign="top" char="(">353 (71.89)</td>
</tr>
<tr>
<td align="left" valign="middle">LT&#x0026;RT</td>
<td align="char" valign="top" char="(">2 (0.60)</td>
<td align="char" valign="top" char="(">1 (0.26)</td>
<td align="char" valign="top" char="(">5 (1.17)</td>
<td align="char" valign="top" char="(">1 (0.20)</td>
</tr>
<tr>
<td align="left" valign="middle">Other organs</td>
<td align="char" valign="top" char="(">3 (0.90)</td>
<td align="char" valign="top" char="(">0 (0.00)</td>
<td align="char" valign="top" char="(">3 (0.70)</td>
<td align="char" valign="top" char="(">2 (0.41)</td>
</tr>
<tr>
<td align="left" valign="middle">Total</td>
<td align="char" valign="top" char="(">332 (100.0)</td>
<td align="char" valign="top" char="(">380 (100.0)</td>
<td align="char" valign="top" char="(">428 (100.0)</td>
<td align="char" valign="top" char="(">491 (100.0)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>LT, liver transplant; RT, renal transplant; IFLT, ischemia-free liver transplant.</p>
</table-wrap-foot>
</table-wrap>
<p>In addition, the composition of the top five DRGs groups in the low- and high-risk groups admitted to the organ transplant department during the pre-IFLT and post-IFLT periods was explored, respectively. As shown in <xref rid="SM1" ref-type="supplementary-material">Supplementary Table S1</xref>, the top three patients in the low-risk group admitted to the department were LZ15, LJ13 and LJ15, while the top three patients in the high-risk group admitted to the department were AB19, HR15 and HJ13 both in the pre-IFLT and post-IFLT periods.</p>
</sec>
<sec id="sec26">
<title>Ischemia-free transplant improves postoperative recovery</title>
<p>The length of hospital stay after surgical treatment reflects the recovery of patients after surgery. Therefore, the mean length of postoperative hospital stay was compared between patients with CLT and those with IFLT. As shown in <xref rid="fig6" ref-type="fig">Figure 6</xref>, the average length of postoperative hospital stay in patients with IFLT was significantly shorter than that in patients with CLT, suggesting that patients with IFLT had better postoperative recovery than those with CLT (<italic>p</italic>&#x2009;=&#x2009;0.001).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>Comparison of postoperative hospital stay between CLT and IFLT in 2016&#x2009;~&#x2009;2019. CLT, conventional liver transplant. IFLT, ischemia-free liver transplant. LT, liver transplant. <sup>&#x002A;</sup><italic>p</italic>&#x2009;&#x003C;&#x2009;0.05. <sup>&#x002A;&#x002A;</sup><italic>p</italic>&#x2009;&#x003C;&#x2009;0.01. <sup>&#x002A;&#x002A;&#x002A;</sup><italic>p</italic>&#x2009;&#x003C;&#x2009;0.001.</p>
</caption>
<graphic xlink:href="fpubh-11-1092182-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="sec27" sec-type="discussions">
<title>Discussion</title>
<p>Ischemia-free transplantation technology can effectively improve the clinical outcome of organ transplant (<xref ref-type="bibr" rid="ref26">26</xref>). In order to assess the impact of this innovative technology on the medical service performance, we used the DRGs tool to evaluate the medical service performance in the organ transplant department of Sun Yat-sen university&#x2019;s first hospital from 2016 to 2019. The results showed that after the IFLT implementation, the medical service performance indicators of organ transplant department showed an improvement trend, suggesting that the IFLT implementation of improved the medical service capacity of the department.</p>
<p>Normal machine perfusion (NMP) is a method of organ preservation that protects donor organs between acquisition and transplantation (<xref ref-type="bibr" rid="ref27">27</xref>), contributes to organ utilization and improves post-transplant outcomes (<xref ref-type="bibr" rid="ref28">28</xref>, <xref ref-type="bibr" rid="ref29">29</xref>). Previous studies have shown that the application of NMP can prevent the occurrence of IRI by inhibiting inflammation and promoting graft regeneration (<xref ref-type="bibr" rid="ref30">30</xref>). However, as we know, the combination of NRP and HMP is often used for machine perfusion in the clinical practice of organ transplant (<xref ref-type="bibr" rid="ref31">31</xref>). In this case, IRI may still occur in donor organs. Therefore, the hospital where this study was conducted successfully carried out the first IFLT in the world. IFLT enables the donor organ to obtain blood supply and support throughout the whole process, avoiding the IRI of the donor organ and reducing the risk of delayed graft function recover and acute rejection after surgery, thus further improving the transplant effect (<xref ref-type="bibr" rid="ref32">32</xref>). The clinical practice shows that this innovative technology plays a positive role in promoting the medical service performance of the organ transplant department.</p>
<p>The payment method based on the DRGs case mix is a promising way for medical charging services (<xref ref-type="bibr" rid="ref33">33</xref>, <xref ref-type="bibr" rid="ref34">34</xref>). It is reported that DRGs can help shorten hospital stay (<xref ref-type="bibr" rid="ref35">35</xref>), reduce operations requiring expensive surgical instruments (<xref ref-type="bibr" rid="ref36">36</xref>), and reduce medical costs (<xref ref-type="bibr" rid="ref37">37</xref>). Although a lot of basic work needs to be carried out to realize DRG, including establishing adequate infrastructure, improving human resource capacity and improving the information management system (<xref ref-type="bibr" rid="ref38">38</xref>, <xref ref-type="bibr" rid="ref39">39</xref>), these works are of great value, because scientific evaluation of medical service performance helps to improve clinical practice. At present, the DRGs tool has been widely concerned and applied to several clinical professional medical service evaluation (<xref ref-type="bibr" rid="ref40">40</xref>). As far as we know, there is no research on the medical performance evaluation of organ transplant specialty using DRGs. Our research showed that DRG was an effective tool to evaluate the medical service performance of organ transplant specialty.</p>
<p>In this study, we used the CN-DRGs tool to analyze the medical service performance of organ transplant cases in the hospital. The results showed that the medical service performance in the organ transplant department showed an upward trend after the IFLT implementation. Specifically, in terms of medical income, the income structure of organ transplant department was more optimized. In terms of medical service capacity, both the number of DRGs and CMI showed an upward trend. The proportion of cases with higher RW (such as RW 5&#x2013;10) increased, indicating that the type, scope and average technical difficulty of cases treated by organ transplantation department improved. It is worth mentioning that the proportion of organ transplant cases increased significantly during the post-IFLT period, indicating that the performance of professional medical service in this department improved. In terms of service efficiency, there was no statistical difference of TEIs between pre- and post-IFLT implementation, suggesting that the organ transplant department should pay more attention to the LOS in the future clinical practice. Meanwhile, the difference of CEIs pre- and post-IFLT was statistically significant, indicating that the cost of treating the same disease in organ transplantation department was significantly reduced. In terms of service safety, the mortality rate of low-risk cases in the organ transplant department was 0 throughout the study period, reflecting that the service safety of the department was good. Therefore, the indicators of DRGs, including TW, DRGs, CMI, TEI and CEI, have improved to varying degrees after the application of IFLT, suggesting that IFLT can help improve the medical service performance of the organ transplantation department. It is worth mentioning that, as shown in <xref rid="fig4" ref-type="fig">Figure 4C</xref>, compared with the CEI in 2016, the CEI in 2019 was significantly reduced, suggesting significant optimization in terms of hospitalization cost indicators. This may be related to the fact that IFLT recipients recover better after surgery, resulting in lower costs. The above results suggest that the application of IFLT can improve the medical service performance of organ transplantation department. Meanwhile, DRGs tools can accurately assess medical service performance.</p>
<p>Moreover, compared with CLT cases, the average postoperative LOS decreased significantly, suggesting that IFLT can effectively improve the postoperative recovery of patients. Previous studies suggest that there is a difference in the LOS after LT between China and the United States. According to data released by the Scientific Registry of Transplant Recipients (SRTR, <ext-link xlink:href="https://www.srtr.org/" ext-link-type="uri">https://www.srtr.org/</ext-link>) on January 5, 2023, the median postoperative LOS after LT in the United States was 10&#x2009;days. Meanwhile, the postoperative LOS after LT varies by medical institution in the United States. For example, the median postoperative LOS after LT at Mayo Clinic Hospital Arizona was 6&#x2009;days, while median postoperative LOS after LT at UF Health Shands Hospital was 14&#x2009;days. Compared with that in the United States, the median postoperative LOS after LT in China was relatively longer. For example, a retrospective study from Beijing suggested that the median postoperative LOS after LT was 16&#x2009;days (<xref ref-type="bibr" rid="ref41">41</xref>). In addition, a retrospective study from Shanghai suggested that the median postoperative LOS after pediatric living donor LT was 24&#x2009;days (<xref ref-type="bibr" rid="ref42">42</xref>). In the present study, the mean postoperative LOS after LT in the post-IFLT period was 26.73&#x2009;days, which was similar to the data reported by other medical institutions in China.</p>
<p>We believe that the reasons why LT patients in China have longer postoperative LOS compared to that in the United States may include the following: Firstly, there are differences in the medical systems of the two countries. Medical institutions in China have different practices in terms of care and management after LT, which may require a longer hospital stay. Secondly, there are differences in the characteristics of patients. Chinese patients may have different risk factors, which may require more intensive in-hospital monitoring, thus extending the LOS. Thirdly, there is a difference in cultural and social factors. Chinese families are likely to become more involved in caring for their family members during hospital stays, which could extend the LOS. Finally, differences in alternative therapy or medication use may also affect LOS.</p>
<p>There were several potential limitations in this study. Firstly, medical service performance evaluation based on DRGs requires high-precision FPMR. FPMR data used in this work was provided by the medical record management department of the hospital studied. Although the disease and surgery coding in FPMR had been under standard quality control, there is still the possibility of inaccurate coding, which may affect the accuracy of the evaluation results. Secondly, there was a lack of localized DRGs suitable for Guangdong Province, which may affect the accuracy of medical service performance evaluation data.</p>
<p>In conclusion, this study showed that medical performance indicators including total weight, CMI, CEI, and TEI of patients admitted to the organ transplant department in the post-IFLT period were improved to varying degrees compared with those in the pre-IFLT period, suggesting that the application of IFLT technology could contribute to improving the medical service performance of the organ transplant department. Meanwhile, the DRGs tool may help transplant departments to coordinate the future delivery planning of medical service.</p>
</sec>
<sec id="sec28" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref rid="SM1" ref-type="supplementary-material">Supplementary material</xref>, further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="sec29">
<title>Author contributions</title>
<p>WZ and WC designed the study and revised the manuscript. JL, ZL, and YX collected and analyzed the data. JL interpreted the data and drafted the manuscript. HP, YZ, ZX, YL, and ZS revised the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="conf1" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="sec100" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
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<sec id="sec31" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fpubh.2023.1092182/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fpubh.2023.1092182/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Data_Sheet_1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
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