<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    jssm
   </journal-id>
   <journal-title-group>
    <journal-title>
     Journal of Service Science and Management
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    1940-9893
   </issn>
   <issn publication-format="print">
    1940-9907
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/jssm.2025.181001
   </article-id>
   <article-id pub-id-type="publisher-id">
    jssm-138837
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Business 
     </subject>
     <subject>
       Economics
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Analysis of Pediatric Patient Transfer: Patient Characteristics and Distribution of Departments after Admission
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Yueting
      </surname>
      <given-names>
       Liu
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Wenqiong
      </surname>
      <given-names>
       Chen
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Xiaowei
      </surname>
      <given-names>
       Fan
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Daoju
      </surname>
      <given-names>
       Jiang
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Peiqing
      </surname>
      <given-names>
       Li
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Weijun
      </surname>
      <given-names>
       Li
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Meiling
      </surname>
      <given-names>
       Liao
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Yongxian
      </surname>
      <given-names>
       Liang
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Guangming
      </surname>
      <given-names>
       Liu
      </given-names>
     </name>
    </contrib>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Qiang
      </surname>
      <given-names>
       Wang
      </given-names>
     </name>
    </contrib>
   </contrib-group> 
   <aff id="affnull">
    <addr-line>
     aEmergency Transfer Center, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou, China
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     10
    </day> 
    <month>
     01
    </month>
    <year>
     2025
    </year>
   </pub-date> 
   <volume>
    18
   </volume> 
   <issue>
    01
   </issue>
   <fpage>
    1
   </fpage>
   <lpage>
    8
   </lpage>
   <history>
    <date date-type="received">
     <day>
      9,
     </day>
     <month>
      December
     </month>
     <year>
      2024
     </year>
    </date>
    <date date-type="published">
     <day>
      7,
     </day>
     <month>
      December
     </month>
     <year>
      2024
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      7,
     </day>
     <month>
      January
     </month>
     <year>
      2025
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    <b>Objective:</b> This study aims to analyze the characteristics of inter-hospital transferred pediatric patients and the distribution of departments receiving these patients from January 1, 2024, to October 31, 2024, in order to assess the effectiveness and efficiency of the transfer services and to identify potential areas for improvement. 
    <b>Methods: </b>We conducted a retrospective study, reviewing 731 patient transfers conducted by the pediatric transfer team of the transfer center during the aforementioned period. Data were sourced from electronic medical records of inter-hospital transfers. We analyzed the hospital level of demand for transfer patients, their place of origin, age distribution, diagnostic classification, need for respiratory support, and distribution of admitting departments. 
    <b>Results:</b> The study results showed that the majority of transferred patients came from tertiary hospitals (65.94%), with urban patients accounting for 37.21%, and a smaller proportion of patients from outside the province (5.47%). The age distribution was highest for patients aged 1 month to 1 year (37.94%), with respiratory issues being the most common reason for transfer (31.74%). In terms of respiratory support, patients on invasive ventilation accounted for 23.94%, those on non-invasive ventilation accounted for 8.76%, patients on oxygen therapy accounted for 36.53%, and patients without the need for respiratory support accounted for 30.78%. The Pediatric Intensive Care Unit (PICU) was the primary admitting department (52.53%), followed by the Department of Pediatrics (20.52%) and the Department of Pediatric Surgery (10.53%). 
    <b>Conclusion:</b> Our study revealed the characteristics of transfer demand for pediatric patients requiring inter-hospital transfers. The results highlighted the high demand for transfer services from tertiary hospitals and urban patients from within the province, as well as the reliance of patients with respiratory issues and infants on high-quality, comprehensive medical care and nursing provided by national-level children’s medical centers. These findings are significant for optimizing the allocation of transfer resources and improving service quality.
   </abstract>
   <kwd-group> 
    <kwd>
     Pediatric Transfer
    </kwd> 
    <kwd>
      Patient Destination
    </kwd> 
    <kwd>
      Admitting Department
    </kwd> 
    <kwd>
      Resource Allocation
    </kwd> 
    <kwd>
      Medical Efficiency
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>With the advancement of medical technology and the in-depth development of children’s health needs, transport medicine has evolved from a simple patient transfer into a complex process involving multidisciplinary cooperation, providing continuous medical and nursing care (<xref ref-type="bibr" rid="scirp.138837-#HYPERLINK  l R01">
     Alamshaw et al., 2024
    </xref>). Establishing an efficient transport system not only saves the lives of critically ill children in a timely manner but also provides them with continuous professional medical and nursing services, thereby improving the overall quality of medical services. Transport medicine requires close collaboration between various departments, including the transport center, pediatric emergency, pediatric wards, and pediatric intensive care units. Continuously exploring more effective transport models and methods and coordinating resources from various departments can provide stronger protection for the health of pediatric patients (<xref ref-type="bibr" rid="scirp.138837-12">
     Stroud et al., 2013
    </xref>). In a retrospective study conducted from January 1, 2024, to October 31, 2024, over a period of ten months, we aimed to deeply analyze the characteristics of inter-hospital pediatric patients and the distribution of departments receiving these patients after transfer. This study not only focused on the effectiveness and efficiency of transport services but also identified potential areas for improvement, with the expectation of enhancing the quality of medical services (<xref ref-type="bibr" rid="scirp.138837-8">
     Ljungholm et al., 2022
    </xref>).</p>
   <p>The goal of transport services is to ensure that critically ill and complex pediatric patients can receive appropriate medical resources and professional nursing services in a timely manner (<xref ref-type="bibr" rid="scirp.138837-#HYPERLINK  l R03">
     Gantayet-Mathur et al., 2022
    </xref>). Dedicated pediatric transport teams play a crucial role in this process; they are not only responsible for the safe transfer of patients but also involved in the continuity of patient care and the assurance of medical quality. Dedicated pediatric transport teams can provide better care for pediatric patients and improve their outcomes (<xref ref-type="bibr" rid="scirp.138837-6">
     Khatri et al., 2023
    </xref>).</p>
   <p>The purpose of this study is to analyze the characteristics of inter-hospital pediatric patients and the departments they are admitted to after transfer, as well as how these data reflect the allocation of transport service resources and medical efficiency. By analyzing the transport data of 731 patients, we aim to reveal the characteristics of transported patients, including their age distribution, diagnostic categories, and respiratory support status, thereby providing a basis for optimizing the transport process and resource allocation.</p>
  </sec><sec id="s2">
   <title>2. Materials and Methods</title>
   <p>This study employs a retrospective research design aimed at analyzing the pediatric transport activities carried out by our transport center’s specialized pediatric transport team from January 1, 2024, to October 31, 2024. The study subjects include all pediatric patients transported by this team during the period, covering all age groups from infants to adolescents, but did not include data on newborn patients. We extracted relevant data from the electronic medical records of the transports.</p>
   <p>Data Collection</p>
   <p>Data collection includes the level and geographical location of the hospital where the patient was before transport, the patient’s age, initial diagnosis, respiratory support status during transport, and the final admitting department.</p>
   <p>Patient Screening</p>
   <p>In the initial screening, we excluded cases with incomplete or insufficiently obtainable data. Additionally, we excluded all neonatal transport cases, as these have a fixed age range and admitting departments.</p>
   <p>Data Analysis</p>
   <p>Data analysis primarily focuses on several key indicators: the level and geographical location of the hospital where the patient was before transport, the patient’s age, initial diagnosis, respiratory support status during transport, and the final admitting department. We use the SPSS 26.0 statistical software for statistical analysis, representing count data in terms of frequency and percentage.</p>
  </sec><sec id="s3">
   <title>3. Results</title>
   <p>During the study period from January 1, 2024, to October 31, 2024, our transport center’s specialized pediatric transport team conducted a total of 731 patient transports. The following results provide a detailed description of the transport characteristics of these patients and the admitting departments after a transfer, offering us an in-depth understanding of the utilization of transport services.</p>
   <p>Referring to Hospital Level and Geographic Distribution</p>
   <p>We first analyzed the level and geographical distribution of the source hospitals for inter-hospital patients to identify the main demand hospitals for inter-hospital transport services and their regions (<xref ref-type="table" rid="table1">
     Table 1
    </xref> and <xref ref-type="table" rid="table2">
     Table 2
    </xref>). The results show that tertiary hospitals contributed the majority of transported patients, which may reflect their professional capabilities in treating complex cases. The proportion of transported patients from urban hospitals is relatively low, while a significant proportion comes from hospitals outside the city but within the province, which may be related to the geographical distribution and cooperative relationships between hospitals.</p>
   <p>Distribution of Ages of Transported Patients</p>
   <p>The analysis of age distribution revealed differences in the demand for transport services among children of different age groups (<xref ref-type="table" rid="table3">
     Table 3
    </xref>). We found that infants and toddlers were the main utilizers of transport services, which may be related to the higher medical needs of children in this age group.</p>
   <table-wrap id="table1">
    <label>
     <xref ref-type="table" rid="table1">
      Table 1
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 1. Hospital level of the transferring party.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="32.34%"><p style="text-align:center">Hospital Level</p></td> 
      <td class="custom-bottom-td acenter" width="44.17%"><p style="text-align:center">Number of Patients Transferred</p></td> 
      <td class="custom-bottom-td acenter" width="23.49%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="32.34%"><p style="text-align:center">Tertiary hospital</p></td> 
      <td class="custom-top-td acenter" width="44.17%"><p style="text-align:center">482</p></td> 
      <td class="custom-top-td acenter" width="23.49%"><p style="text-align:center">65.94%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.34%"><p style="text-align:center">Secondary hospital</p></td> 
      <td class="acenter" width="44.17%"><p style="text-align:center">233</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">31.87%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.34%"><p style="text-align:center">Primary hospital</p></td> 
      <td class="acenter" width="44.17%"><p style="text-align:center">16</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">2.19%</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <table-wrap id="table2">
    <label>
     <xref ref-type="table" rid="table2">
      Table 2
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 2. Distribution of the transferring hospital’s location of ownership.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="42.32%"><p style="text-align:center">Place of Affiliation</p></td> 
      <td class="custom-bottom-td acenter" width="38.47%"><p style="text-align:center">Number of Transferred Patients</p></td> 
      <td class="custom-bottom-td acenter" width="19.21%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="42.32%"><p style="text-align:center">Intra-city</p></td> 
      <td class="custom-top-td acenter" width="38.47%"><p style="text-align:center">272</p></td> 
      <td class="custom-top-td acenter" width="19.21%"><p style="text-align:center">37.21%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="42.32%"><p style="text-align:center">Other cities within the province</p></td> 
      <td class="acenter" width="38.47%"><p style="text-align:center">419</p></td> 
      <td class="acenter" width="19.21%"><p style="text-align:center">57.32%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="42.32%"><p style="text-align:center">Other provinces</p></td> 
      <td class="acenter" width="38.47%"><p style="text-align:center">40</p></td> 
      <td class="acenter" width="19.21%"><p style="text-align:center">5.47%</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <table-wrap id="table3">
    <label>
     <xref ref-type="table" rid="table3">
      Table 3
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 3. Age distribution of transferred patients.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="32.91%"><p style="text-align:center">Age Group</p></td> 
      <td class="custom-bottom-td acenter" width="43.60%"><p style="text-align:center">Number of Transferred Patients</p></td> 
      <td class="custom-bottom-td acenter" width="23.49%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="32.91%"><p style="text-align:center">29 days to 1 year</p></td> 
      <td class="custom-top-td acenter" width="43.60%"><p style="text-align:center">299</p></td> 
      <td class="custom-top-td acenter" width="23.49%"><p style="text-align:center">37.94%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.91%"><p style="text-align:center">1 to 3 years old</p></td> 
      <td class="acenter" width="43.60%"><p style="text-align:center">105</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">13.32%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.91%"><p style="text-align:center">3 to 6 years old</p></td> 
      <td class="acenter" width="43.60%"><p style="text-align:center">124</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">15.74%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.91%"><p style="text-align:center">6 to 12 years old</p></td> 
      <td class="acenter" width="43.60%"><p style="text-align:center">158</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">20.05%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.91%"><p style="text-align:center">12 to 15 years old</p></td> 
      <td class="acenter" width="43.60%"><p style="text-align:center">40</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">5.08%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="32.91%"><p style="text-align:center">15 to 18 years old</p></td> 
      <td class="acenter" width="43.60%"><p style="text-align:center">5</p></td> 
      <td class="acenter" width="23.49%"><p style="text-align:center">0.63%</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <p>Diagnosis Categories of Transported Patients</p>
   <p>The analysis of diagnosis categories revealed the main medical issues that necessitate pediatric transport (<xref ref-type="table" rid="table4">
     Table 4
    </xref>). Respiratory issues topped the list of reasons for transport, which may be related to the high prevalence of respiratory diseases among children.</p>
   <p>Respiratory Support Status of Transported Patients</p>
   <p>The analysis of respiratory support status revealed the demand for different levels of respiratory support among transported patients (<xref ref-type="table" rid="table5">
     Table 5
    </xref>). The proportion of patients on invasive ventilation is relatively high, which may be related to the proportion of critical cases among the transported patients.</p>
   <p>Admission Department Distribution of Transported Patients</p>
   <p>The analysis of admission department distribution revealed the main destinations of transported patients upon arrival at the destination hospital (<xref ref-type="table" rid="table6">
     Table 6
    </xref>). The PICU (Pediatric Intensive Care Unit), being the primary admitting department, reflects the high proportion of critical cases among transported patients.</p>
   <table-wrap id="table4">
    <label>
     <xref ref-type="table" rid="table4">
      Table 4
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 4. Diagnostic categories of transferred patients.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="46.60%"><p style="text-align:center">Diagnostic Classification</p></td> 
      <td class="custom-bottom-td acenter" width="32.05%"><p style="text-align:center">Number of Transferred Patients</p></td> 
      <td class="custom-bottom-td acenter" width="21.35%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="46.60%"><p style="text-align:center">Respiratory</p></td> 
      <td class="custom-top-td acenter" width="32.05%"><p style="text-align:center">232</p></td> 
      <td class="custom-top-td acenter" width="21.35%"><p style="text-align:center">31.74%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Neurologic/psychiatric</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">85</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">11.63%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Pediatric Surgery/Surgical/trauma</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">85</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">11.63%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Metabolic disease/Diabetic ketoacidosis</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">18</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">2.46%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Hematology/oncology</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">37</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">5.06%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Cardiac</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">44</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">6.02%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Infection</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">86</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">11.76%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Shock/organ failure/CPR</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">93</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">12.72%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Ingestion/overdose/poisoning</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">4</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">0.55%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Gastrointestinal</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">31</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">4.25%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Foreign body</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">4</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">0.55%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="46.60%"><p style="text-align:center">Kidney</p></td> 
      <td class="acenter" width="32.05%"><p style="text-align:center">12</p></td> 
      <td class="acenter" width="21.35%"><p style="text-align:center">1.64%</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <table-wrap id="table5">
    <label>
     <xref ref-type="table" rid="table5">
      Table 5
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 5. Respiratory support status of transferred patients.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="41.78%"><p style="text-align:center">Respiratory Support Status</p></td> 
      <td class="custom-bottom-td acenter" width="41.14%"><p style="text-align:center">Number of Transferred Patients</p></td> 
      <td class="custom-bottom-td acenter" width="17.08%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="41.78%"><p style="text-align:center">None</p></td> 
      <td class="custom-top-td acenter" width="41.14%"><p style="text-align:center">225</p></td> 
      <td class="custom-top-td acenter" width="17.08%"><p style="text-align:center">30.78%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="41.78%"><p style="text-align:center">Oxygen therapy</p></td> 
      <td class="acenter" width="41.14%"><p style="text-align:center">267</p></td> 
      <td class="acenter" width="17.08%"><p style="text-align:center">36.53%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="41.78%"><p style="text-align:center">Non-invasive ventilation</p></td> 
      <td class="acenter" width="41.14%"><p style="text-align:center">64</p></td> 
      <td class="acenter" width="17.08%"><p style="text-align:center">8.76%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="41.78%"><p style="text-align:center">Invasive ventilation</p></td> 
      <td class="acenter" width="41.14%"><p style="text-align:center">175</p></td> 
      <td class="acenter" width="17.08%"><p style="text-align:center">23.94%</p></td> 
     </tr> 
    </table>
   </table-wrap>
   <table-wrap id="table6">
    <label>
     <xref ref-type="table" rid="table6">
      Table 6
     </xref></label>
    <caption>
     <title>
      <xref ref-type="bibr" rid="scirp.138837-"></xref>Table 6. Distribution of admitted departments for transferred patients.</title>
    </caption>
    <table class="MsoTableGrid custom-table" border="0" cellspacing="0" cellpadding="0"> 
     <tr> 
      <td class="custom-bottom-td acenter" width="40.18%"><p style="text-align:center">Admitted Department</p></td> 
      <td class="custom-bottom-td acenter" width="40.62%"><p style="text-align:center">Number of Transferred Patients</p></td> 
      <td class="custom-bottom-td acenter" width="19.20%"><p style="text-align:center">Percentage</p></td> 
     </tr> 
     <tr> 
      <td class="custom-top-td acenter" width="40.18%"><p style="text-align:center">CICU</p></td> 
      <td class="custom-top-td acenter" width="40.62%"><p style="text-align:center">16</p></td> 
      <td class="custom-top-td acenter" width="19.20%"><p style="text-align:center">2.19%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">NICU</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">14</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">1.92%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">PICU</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">384</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">52.53%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">SICU</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">23</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">3.15%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">Pediatric Emergency</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">67</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">9.17%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">Pediatric Internal Medicine</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">150</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">20.52%</p></td> 
     </tr> 
     <tr> 
      <td class="acenter" width="40.18%"><p style="text-align:center">Pediatric Surgery</p></td> 
      <td class="acenter" width="40.62%"><p style="text-align:center">77</p></td> 
      <td class="acenter" width="19.20%"><p style="text-align:center">10.53%</p></td> 
     </tr> 
    </table>
   </table-wrap>
  </sec><sec id="s4">
   <title>4. Discussion</title>
   <p>This study analyzes the data of 731 pediatric patient transfers from January 1, 2024, to October 31, 2024, revealing the utilization of transfer services and the characteristics of patient destinations upon admission. Our findings provide valuable insights for understanding and optimizing the transfer process.</p>
   <p>The Demand and Supply of Transfer Services</p>
   <p>The study results indicate that tertiary hospitals are the primary source of pediatric patient transfers, which may be related to these hospitals’ ability to handle complex cases (<xref ref-type="bibr" rid="scirp.138837-5">
     Handley &amp; Lorch, 2022
    </xref>). This finding emphasizes the central role of tertiary hospitals in the transfer network and the high dependence of these hospitals on transfer services. At the same time, the high proportion of transfers from hospitals outside the city but within the province suggests that our transfer services have wide coverage, which is of great significance for providing regional medical services.</p>
   <p>Age Distribution and Transfer Demand</p>
   <p>The age distribution data shows that infants and toddlers (1 month to 1 year) are the main users of transfer services, which may be related to the higher medical needs of children in this age group (<xref ref-type="bibr" rid="scirp.138837-2">
     Black et al., 2016
    </xref>). This finding suggests that transfer services should pay special attention to the unique needs of the infant and toddler population, including the provision of appropriate medical equipment and professional personnel.</p>
   <p>Diagnostic Categories and Reasons for Transfer</p>
   <p>Respiratory issues, as the most common reason for transfer, highlight the high incidence and severity of respiratory diseases in children (<xref ref-type="bibr" rid="scirp.138837-7">
     Kjærgaard et al., 2019
    </xref>). This result is consistent with global studies on the burden of pediatric diseases, where respiratory diseases are one of the leading causes of hospitalization and death in children (<xref ref-type="bibr" rid="scirp.138837-4">
     GBD 2021 Lower Respiratory Infections and Antimicrobial Resistance Collaborators, 2024
    </xref>). Therefore, our transfer services should prioritize equipping the capability and resources to handle respiratory emergencies.</p>
   <p>Respiratory Support Needs and Patient Severity of Illness</p>
   <p>Data on respiratory support indicate that a significant proportion of patients require invasive or non-invasive ventilation support, which further emphasizes the severity of the conditions of the patients being transferred (<xref ref-type="bibr" rid="scirp.138837-9">
     Miura et al., 2024
    </xref>). This finding suggests that the transfer team should be capable of handling various respiratory support needs to ensure the safety and stability of the patients throughout the entire transfer process.</p>
   <p>Admission Department Distribution and Patient Destinations</p>
   <p>The fact that the Pediatric Intensive Care Unit (PICU) is the primary admitting department reflects the high proportion of critical cases among transferred patients. This finding indicates that our transfer services play a crucial role in ensuring that critically ill children can quickly receive appropriate medical treatment and care (<xref ref-type="bibr" rid="scirp.138837-11">
     Steffen et al., 2020
    </xref>). At the same time, it also suggests that the planning of transfer services should be closely coordinated with the hospital’s resource allocation and departmental capabilities (<xref ref-type="bibr" rid="scirp.138837-10">
     Slater et al., 2021
    </xref>).</p>
  </sec><sec id="s5">
   <title>5. Summary</title>
   <p>In summary, this study provides a comprehensive understanding of pediatric patient transfer services, including the origin, age, diagnosis, respiratory support needs, and admitting departments of the patients. This data is crucial for evaluating the effectiveness of transfer services and guiding future resource allocation. The results of our study provide an empirical basis for the optimization of pediatric patient transfer services. By identifying the main demands of transfer services and patient destinations, we can better plan resource allocation, improve service quality, and ultimately improve patient outcomes.</p>
  </sec><sec id="s6">
   <title>Authors’ Contribution</title>
   <p>Yueting Liu contributed to the manuscript draft. Wenqiong Chen carried out a statistical analysis. Xiaowei Fan and Daoju Jiang contributed to data collection. Peiqing Li contributed to the formal analysis. Weijun Li, Meiling Liao and Yongxian Liang for clinical quality control. Guangming Liu contributed to editing the manuscript. Qiang Wang contributed to the study design and review of the manuscript. All authors read and approved the final manuscript.</p>
  </sec><sec id="s7">
   <title>Acknowledgements</title>
   <p>We would like to thank the members of our specialized pediatric transport team. Additionally, we are grateful for the support of our colleagues in pediatric critical care, pediatric emergency, pediatric internal medicine, and pediatric surgery for this study.</p>
  </sec><sec id="s8">
   <title>Data Availability Statement</title>
   <p>All data generated or analyzed during this study are included in this published article.</p>
  </sec><sec id="s9">
   <title>Funding Statement</title>
   <p>The study was supported by the 2025 Annual City-University (Institute)-Enterprise Joint Funding Project (Grant Number SL2024A03J0154).</p>
  </sec><sec id="s10">
   <title>NOTES</title>
   <p>*These authors are co-first authors.</p>
   <p><sup>#</sup>Corresponding authors.</p>
  </sec>
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