[Chances and risks of conversion to outpatient treatment in trauma surgery and orthopedics]. / Chancen und Risiken in der Ambulantisierung der Unfallchirurgie und Orthopädie.

At the latest since the Medical Services Healthcare Insurance Reform Act (MDK), the declared will of the legislation is the conversion of operations previously carried out in an inpatient setting to an outpatient setting. In trauma surgery and orthopedics numerous operations are carried out that could principally also be performed in an outpatient setting; however, a prerequisite is a medical assessment of the suitability of patients as well as an economic and normative framework that makes outpatient surgery attractive. Both the Outpatient Surgery in Hospitals Catalogue (AOP-Katalog) and the first edition of the Hybrid Diagnosis-related Groups (DRG) define interventions in trauma surgery that could be carried out in an outpatient setting. Hospitals are therefore required to find solutions for these interventions under processual and economic provisos. These range from omission of outpatient operations to the expansion as a separate financial department in the hospital. With the introduction of the hybrid DRG, the legislation enables equal remuneration for outpatient versus short-term inpatient treatment and leaves the case management up to the hospital; however, the performance of the AOP in the setting of a hospital and also hybrid case flat rates are as a rule not economically viable and bear the risk of the failure of all efforts at conversion to outpatient settings. It is necessary to carry out a fundamental revision of the remuneration and framework conditions for outpatient operations in trauma surgery and orthopedics in hospitals, involving practitioners. This is the only way that the conversion to outpatient treatment can succeed.

A Roadmap for Improving Medicare's Application of Coverage With Evidence Development.

The Centers for Medicare and Medicaid Services' coverage with evidence development (CED) policy allows the agency to provide coverage for an item or service through a National Coverage Determination (NCD), conditional upon an agreement to collect evidence designed to address specific questions or uncertainties. The goals of this policy are to expedite beneficiary access to new items and services and to generate additional evidence on the impact of these items or services for Medicare beneficiaries. However, these goals have not been fully realized because of several issues with the way the policy has been implemented, including (1) a lack of clear criteria for when CED will be applied, (2) examples of CED data collection activities placing unnecessary burdens on clinicians and the potential for undue inducement on beneficiaries, and (3) a lack of clarity around the process and timeline for reconsidering and ending CED requirements. Additionally, there are cases in which the application of CED has failed to improve access to services for certain Medicare beneficiaries because no data collection activity was implemented in response to the CED requirement or because the NCD only allows the technology to be provided and studied in certain centers of excellence. We describe a roadmap for addressing these issues, which includes, for example, developing a framework to guide the application of coverage constraints in NCDs with CED requirements. Once these issues are addressed, the Centers for Medicare and Medicaid Services could consider expanding the use of CED to technologies that are not subject to NCDs.

Barriers to Eye Care for Adults in the United States and Solutions for It: A Literature Review.

Vision loss and blindness is a significant public health concern that has had a profound impact on various communities in the United States. Both anticipated and unforeseen barriers have been linked to the rising rates of vision loss and blindness in the country. Extensive research has identified numerous barriers that put many Americans at a disadvantage when trying to seek high-quality eye care services. Not only do the barriers to eye care services create problems for eye health, but also create a poor quality of life. Therefore, understanding and identifying barriers to eye healthcare services is incredibly important. In addition to understanding and identifying barriers, it is also important to identify solutions to the problems created by these barriers. A systematic review of articles characterizing the barriers to eye care was completed which resulted in the identification of the major barriers that affect Americans. The review of previous research was also used to identify available solutions for problems associated with the barriers to eye care services. The major barriers identified were cost, insurance, transport and accessibility, eye health care literacy, and communication. Because of the identification of the major barriers, solutions were also identified. Health education and increased vision screenings were found to be the most used forms of solutions by healthcare professionals promoting good eye health. Telemedicine has also been cited as a possible solution to the growing problem of visual impairment and blindness within the American population.

Healthcare insurance fraud detection using data mining.

BACKGROUND: Healthcare programs and insurance initiatives play a crucial role in ensuring that people have access to medical care. There are many benefits of healthcare insurance programs but fraud in healthcare continues to be a significant challenge in the insurance industry. Healthcare insurance fraud detection faces challenges from evolving and sophisticated fraud schemes that adapt to detection methods. Analyzing extensive healthcare data is hindered by complexity, data quality issues, and the need for real-time detection, while privacy concerns and false positives pose additional hurdles. The lack of standardization in coding and limited resources further complicate efforts to address fraudulent activities effectively. METHODOLGY: In this study, a fraud detection methodology is presented that utilizes association rule mining augmented with unsupervised learning techniques to detect healthcare insurance fraud. Dataset from the Centres for Medicare and Medicaid Services (CMS) 2008-2010 DE-SynPUF is used for analysis. The proposed methodology works in two stages. First, association rule mining is used to extract frequent rules from the transactions based on patient, service and service provider features. Second, the extracted rules are passed to unsupervised classifiers, such as IF, CBLOF, ECOD, and OCSVM, to identify fraudulent activity. RESULTS: Descriptive analysis shows patterns and trends in the data revealing interesting relationship among diagnosis codes, procedure codes and the physicians. The baseline anomaly detection algorithms generated results in 902.24 seconds. Another experiment retrieved frequent rules using association rule mining with apriori algorithm combined with unsupervised techniques in 868.18 seconds. The silhouette scoring method calculated the efficacy of four different anomaly detection techniques showing CBLOF with highest score of 0.114 followed by isolation forest with the score of 0.103. The ECOD and OCSVM techniques have lower scores of 0.063 and 0.060, respectively. CONCLUSION: The proposed methodology enhances healthcare insurance fraud detection by using association rule mining for pattern discovery and unsupervised classifiers for effective anomaly detection.

More patient-centered care, better healthcare: the association between patient-centered care and healthcare outcomes in inpatients.

Objective: The objective of this study is to explore the association between patient-centered care (PCC) and inpatient healthcare outcomes, including self-reported physical and mental health status, subjective necessity of hospitalization, and physician-induced demand behaviors. Methods: A cross-sectional survey was conducted to assess patient-centered care among inpatients in comprehensive hospitals through QR codes after discharge from September 2021 to December 2021 and had 5,222 respondents in Jiayuguan, Gansu. The questionnaire included a translated 6-item version of the PCC questionnaire, physician-induced behaviors, and patients' sociodemographic characteristics including gender, household registration, age, and income. Logistic regression analyses were conducted to assess whether PCC promoted self-reported health, the subjective necessity of hospitalization, and decreased physician-induced demand. The interactions between PCC and household registration were implemented to assess the effect of the difference between adequate and inadequate healthcare resources. Results: PCC promoted the patient's self-reported physical (OR = 4.154, p < 0.001) and mental health (OR = 5.642, p < 0.001) and subjective necessity of hospitalization (OR = 6.160, p < 0.001). Meanwhile, PCC reduced physician-induced demand in advising to buy medicines outside (OR = 0.415, p < 0.001), paying at the outpatient clinic (OR =0.349, p < 0.001), issuing unnecessary or repeated prescriptions and medical tests (OR = 0.320, p < 0.001), and requiring discharge and readmitting (OR = 0.389, p < 0.001). Conclusion: By improving health outcomes for inpatients and reducing the risk of physician-induced demand, PCC can benefit both patients and health insurance systems. Therefore, PCC should be implemented in healthcare settings.

Beyond the Microscope: A Technological Overture for Cervical Cancer Detection.

Cervical cancer is a common and preventable disease that poses a significant threat to women's health and well-being. It is the fourth most prevalent cancer among women worldwide, with approximately 604,000 new cases and 342,000 deaths in 2020, according to the World Health Organization. Early detection and diagnosis of cervical cancer are crucial for reducing mortality and morbidity rates. The Papanicolaou smear test is a widely used screening method that involves the examination of cervical cells under a microscope to identify any abnormalities. However, this method is time-consuming, labor-intensive, subjective, and prone to human errors. Artificial intelligence techniques have emerged as a promising alternative to improve the accuracy and efficiency of Papanicolaou smear diagnosis. Artificial intelligence techniques can automatically analyze Papanicolaou smear images and classify them into normal or abnormal categories, as well as detect the severity and type of lesions. This paper provides a comprehensive review of the recent advances in artificial intelligence diagnostics of the Papanicolaou smear, focusing on the methods, datasets, performance metrics, and challenges. The paper also discusses the potential applications and future directions of artificial intelligence diagnostics of the Papanicolaou smear.

Accessibility to Obstetric Care in South Florida Based on Insurance: A Cross-Sectional Study.

Introduction Obstetrical research confirms that earlier onset prenatal care significantly improves pregnancy and birth outcomes. Initiating care in the second trimester or having less than 50% of recommended visits has been associated with an increased risk of prematurity, stillbirth, neonatal, and infant death. Studies have shown that women on public health insurance plans initiate prenatal care substantially later into pregnancy than those on private plans. The purpose of this study is to assess whether public health insurance limits Florida patients' access to obstetric care.  Methods  A cross-sectional study was conducted by collecting data on the four most populated zip codes for Medicaid in South Florida using HealthGrades.com. The following search parameters were used: "obstetric care", "four stars and up" and "10-mile distance". Each obstetrician was called three times to assess appointment availability for fictional nulliparous women at eight weeks of gestation requesting prenatal care. Accepted insurance types (Medicaid, Cigna, and United Health Group (UHG)), time to an appointment in business days, and self-pay rates were recorded. Practices with invalid contact information and retired obstetricians were excluded. Summary statistics, chi-squared analysis, and a two-way t-test were conducted for the primary outcome.  Results  Seventy-one out of 178 obstetricians were successfully contacted, of which 31 physicians accepted all three insurances, and 40 physicians did not accept at least one insurance. Of those, 97.2% accepted UnitedHealthcare, 98.6% accepted Cigna, and 45.1% accepted Medicaid. There was a statistically significant difference when comparing acceptance rates between UHC and Medicaid as well as Cigna and Medicaid (p<0.001). There was no statistically significant difference in acceptance rates in the direct comparison of the two private insurances, Cigna and UnitedHealthcare (p=0.559). The average number of days until the next available appointment was 12.7 (SD= 7.2) for UnitedHealthcare, 20.0 (SD=6.7) for Cigna, and 17.0 (SD=8.6) for Medicaid. There was a statistically significant trend between the type of insurance and the time to the earliest appointment (p=0.002).  Conclusion  This study demonstrated patients enrolled in Medicaid in South Florida have significantly less access to prenatal care than those with private insurance. This evidence shows that decreased access to care from Medicaid plans can possibly increase the risk of adverse outcomes associated with inadequate prenatal care. This information should be considered by policymakers when considering future Medicaid expansion.

Validation of Claims-Based Algorithm for Lyme Disease, Massachusetts, USA.

Compared with notifiable disease surveillance, claims-based algorithms estimate higher Lyme disease incidence, but their accuracy is unknown. We applied a previously developed Lyme disease algorithm (diagnosis code plus antimicrobial drug prescription dispensing within 30 days) to an administrative claims database in Massachusetts, USA, to identify a Lyme disease cohort during July 2000-June 2019. Clinicians reviewed and adjudicated medical charts from a cohort subset by using national surveillance case definitions. We calculated positive predictive values (PPVs). We identified 12,229 Lyme disease episodes in the claims database and reviewed and adjudicated 128 medical charts. The algorithm's PPV for confirmed, probable, or suspected cases was 93.8% (95% CI 88.1%-97.3%); the PPV was 66.4% (95% CI 57.5%-74.5%) for confirmed and probable cases only. In a high incidence setting, a claims-based algorithm identified cases with a high PPV, suggesting it can be used to assess Lyme disease burden and supplement traditional surveillance data.

Achievements and Challenges of the Healthcare System in China.

China's healthcare system has made great achievements in the management of medical services and public health challenges for the Chinese people. However, the issue of an aging population in Chinese society is becoming more and more salient. The gap between demand and supply of healthcare is expanding. China's healthcare system is facing unprecedented challenges. These problems include an insufficient medical insurance fund, nonuniform insurance reimbursement policies, a poor integrity system, and a lack of supervision in the management of the medical insurance fund. To address these challenges, some practical solutions are worth considering. A national medical insurance supervision platform should be strengthened. Besides, blacklists for illegal medical institutions and individuals engaged in malicious medical disturbances should be created. The country should also introduce policies to narrow the differences in regional medical insurance policies and balance the reimbursement levels of residents in different regions. Big data and artificial intelligence can be used to monitor the entire process of medical insurance fund utilization. The government needs to establish relevant laws and regulations to optimize the medical insurance system and ensure the safe and effective operation of the medical insurance fund.

Virtual patient identifier (vPID): Improving patient traceability using anonymized identifiers in Japanese healthcare insurance claims database.

Objective: Japan's national-level healthcare insurance claims database (NDB) is a collective database that contains the entire information on healthcare services being provided to all citizens. However, existing anonymized identifiers (ID1 and ID2) have a poor capability of tracing patients' claims in the database, hindering longitudinal analyses. This study presents a virtual patient identifier (vPID), which we have developed on top of these existing identifiers, to improve the patient traceability. Methods: vPID is a new composite identifier that intensively consolidates ID1 and ID2 co-occurring in an identical claim to allow to collect claims of each patient even though its ID1 or ID2 may change due to life events or clerical errors. We conducted a verification test with prefecture-level datasets of healthcare insurance claims and enrollee history records, which allowed us to compare vPID with the ground truth, in terms of an identifiability score (indicating a capability of distinguishing a patient's claims from another patient's claims) and a traceability score (indicating a capability of collecting claims of an identical patient). Results: The verification test has clarified that vPID offers significantly higher traceability scores (0.994, Mie; 0.997, Gifu) than ID1 (0.863, Mie; 0.884, Gifu) and ID2 (0.602, Mie; 0.839, Gifu), and comparable (0.996, Mie) and lower (0.979, Gifu) identifiability scores. Discussion: vPID is seemingly useful for a wide spectrum of analytic studies unless they focus on sensitive cases to the design limitation of vPID, such as patients experiencing marriage and job change, simultaneously, and same-sex twin children. Conclusion: vPID successfully improves patient traceability, providing an opportunity for longitudinal analyses that used to be practically impossible for NDB. Further exploration is also necessary, in particular, for mitigating identification errors.

Analysis of the annual changes in dental institutions that claimed dental sedatives in Korea and the types of sedatives using health care big data.

Background: Dentists make various efforts to reduce patients' anxiety and fear associated with dental treatment. Dental sedation is an advanced method that dentists can perform to reduce patients' anxiety and fear and provide effective dental treatment. However, dental sedation is different from general dental treatment and requires separate learning, and if done incorrectly, can lead to serious complications. Therefore, sedation is performed by a limited number of dentists who have received specific training. This study aimed to investigate the proportion of dentists who practice sedation and the main sedatives they use in the context of the Republic of Korea. Methods: We used the customized health information data provided by the Korean National Health Insurance. We investigated the number of dental hospitals or clinics that claimed insurance for eight main sedatives commonly used in dental sedation from January, 2007 to September, 2019 at the Health Insurance Review and Assessment Service. We also identified the changes in the number of dental medical institutions by region and year and analyzed the number and proportion of dental medical institutions prescribing each sedative. Results: In 2007, 302 dental hospitals prescribed sedatives, and the number increased to 613 in 2019. In 2007, approximately 2.18% of the total 13,796 dental institutions prescribed sedatives, increasing to 3.31% in 2019. In 2007, 168 institutions (55.6%) prescribed N2O alone, and in 2019, 510 institutions (83.1%) made claims for it. In 2007, 76 (25.1%) hospitals made claims for chloral hydrate, but the number gradually decreased, with only 29 hospitals (4.7%) prescribing it in 2019. Hospitals that prescribed a combination of N2O, chloral hydrate, and hydroxyzine increased from 27 (8.9%) in 2007 to 51 (9%) in 2017 but decreased to 38 (6.1%) in 2019. The use of a combination of N2O and midazolam increased from 20 hospitals (6.6%) in 2007 to 51 hospitals (8.3%) in 2019. Conclusion: While there is a critical limitation to the investigation of dental hospitals performing sedation using insurance claims data, namely exclusion of dental clinics providing non-insured treatments, we found that in 2019, approximately 3.31% of the dental clinics were practicing sedation and that N2O was the most commonly prescribed sedative.

Factors Influencing the Length of Hospital Stay Among Pediatric COVID-19 Patients at Queen Rania Al Abdullah Hospital for Children: A Cross-Sectional Study.

Background COVID-19 caused by SARS-CoV-2 is a worldwide epidemic. Children are less commonly infected and have less severe symptoms than adults. However, they are at risk for COVID-19-associated severe sickness and hospitalization. The duration of stay is a major driver of effective health treatment during hospitalization; thus, it is only logical to attempt to comprehend the factors influencing the length of stay (LOS) for these patients, particularly in light of the ongoing pandemic caused by the new SARS-CoV-2 virus. As predictors of hospital LOS, several variables, including age, gender, disease severity, hospital mortality, insurance type, and hospital location, have been discovered. In our study, we focused on the severity of the patient's condition, the presence of comorbidities, and the necessary therapeutic regimen to predict the duration of stay. This study aimed to answer the following questions: If a patient has comorbidity and has COVID-19 requiring hospital treatment, will the patient's comorbidity elongate the duration of stay at the hospital for further management in the pediatric age group? What are the risk factors that play a significant role in the hospital stay duration in pediatrics? Methodology We gathered data from 100 hospitalized children aged up to 14 years who tested positive for COVID-19, which was not specific to variants of SARS-CoV-2, over 24 months (February 2020-February 2022) at Queen Rania Al Abdullah Hospital for Children, one of the Health Care Accreditation Council accredited facilities. Clinical symptoms, signs, oxygen demand, imaging study results, laboratory data, and usage of corticosteroid and antiviral medication were all taken from patients' medical records. There were no limitations in taking the sample of patients. All patients in the duration mentioned were included. Results Clinical data of 100 COVID-19-positive pediatric patients were analyzed; 52% of the patients had associated chronic illnesses, while 48% were medically free. The longest duration of LOS was 28 days, the shortest was one day, the median was eight days, and five days was the most frequent among patients owing to 21% of patients, using mean descriptive statistics. We compared LOS to having or not having comorbidities. The mean LOS of patients with the comorbid disease was 6.15 days, with a maximum of 28 days, while for patients without chronic illnesses, the mean was 4.81 days with a maximum of 14 days. The significance was 0.07. Our results also showed a significant correlation between using steroids and LOS, as it had an advantageous effect by decreasing it with a significance value of 0.04. Having abnormal findings on chest computed tomography (CT) scan was also associated with increased LOS with a significant value of 0.00. Conclusions According to our research, there was no direct association between comorbidity and hospital LOS, which is counterintuitive, as it was influenced by multiplayers of variables such as using steroids, which decreased the LOS, and abnormal findings on chest CT, which resulted in lengthening of the hospital stay. Our findings cannot be proven without further research and a larger patient sample.

Characteristics of medicine use for children with asthma in China: a nationwide population-based study.

OBJECTIVE: To analyze the asthma medication use in Chinese children of different age groups, regions, and levels of cities in China, based on the 2015 Healthcare Insurance Data in China. METHODS: The China Healthcare Insurance Research Association (CHIRA) database was searched for children from 0 to 14 years old diagnosed as asthma based on the "J45" and "J46" coded in ICD-10. A cross-sectional study design was employed. RESULTS: A total of 308,550 children were identified, all of whom were treated under the coverage of healthcare insurance. Among them, 2,468 children were eligible for inclusion in the present study. Compared with the current status of asthma care in European and American countries, under the guidelines for the diagnosis and treatment of asthma in China, the use percentages of ICS and short-acting ß2 receptor agonist in children with asthma in China were lower, but the use percentages of oral corticosteroids, long-acting ß2 receptor agonist, and theophylline (especially intravenous theophylline) were higher, especially in the Central and West China. CONCLUSION: The asthma medication use was attributed to many factors, thus efforts are still needed to further popularize the GINA programs and China's guidelines for asthma diagnosis and treatment, especially in the Central and West China.

Radiologist burnout: Trends in medical imaging utilization under the national health insurance system with the universal code bundling strategy in an academic tertiary medical centre.

PURPOSE: The utilization of diagnostic medical imaging has been growing worldwide. However, no study has investigated the trend in image utilization and the corresponding workload of radiologists under the National Healthcare Insurance (NHI) system with a code-bundling-based reimbursement strategy. We will analyse the trend in diagnostic imaging utilization and the corresponding workload of the radiologists at a single tertiary medical centre using the NHI system. MATERIALS AND METHODS: This was a retrospective study recruiting the diagnostic medical images, including X-rays, CT, and MR performed between 2005 and 2020 at a single medical centre. We investigated the change over time in image utilization and workload for interpreting the images. The two-sided Mann-Kendall test was used for the monotonic trend analysis and Sen's slope estimate was calculated for the annual mean change with the 95% confidence interval (CI). A P value < 0.05 was considered significant. RESULTS: A total of 10,069,583 examinations were performed at our institute from 2005 to 2020, including 7,821,880 X-rays, 1,665,787 CT, and 581,916 MR examinations. The numbers of examinations of X-rays, CT, and MR increased with average annual changes of 13,411.3 (95% CI = 11,875.0-14,773.8), 9,496.7 (95% CI = 8,845.3-9,828.7), and 2,417.1 (95% CI = 2,209.8-2,668.9) respectively, all P < 0.001. The proportion of cases including multiple examinations increased, growing from 21.5% (6,627 in 30,878 cases) to 43.8% (39,417 in 90,032 cases) for CT and from 8.9% (1,316 in 14,791 cases) to 15.7% (6,083 in 38,865 cases) for MR. The average time spent on interpreting each diagnostic image decreased significantly from 16.0 to 2.9 sec. (P < 0.001). CONCLUSION: Imaging utilization increased significantly under the NHI system at a medical centre. The corresponding demand for image interpretation also placed a significant workload on radiologists, potentially contributing to radiologist burnout.

Impact of nationwide hepatocellular carcinoma surveillance on the prognosis in patients with chronic liver disease.

BACKGROUND/AIMS: This study aimed to investigate the effect of hepatocellular carcinoma (HCC) surveillance using the Korea National Liver Cancer Screening Program on the receipt of curative treatment for HCC and mortality in patients with chronic liver disease. METHODS: This population-based cohort study from the Korean National Health Insurance Service included 2003 to 2015 claims data collected from 1,209,825 patients aged ≥40 years with chronic hepatitis B, chronic hepatitis C, and liver cirrhosis. Patients were divided according to HCC surveillance using ultrasonography and serum alpha-fetoprotein every 6-12 months. The study outcomes were the receipt of curative treatment (surgical resection, radiofrequency ablation, or liver transplantation) and all-cause mortality. RESULTS: The study population consisted of 1,209,825 patients with chronic hepatitis B, chronic hepatitis C, and liver cirrhosis (median age, 52.0 years; interquartile range, 46-55 years; 683,902 men [56.5%]). The proportion of participants who underwent HCC surveillance was 52.7% (n=657,889). During 10,522,940 person-years of follow-up, 74,433 HCC cases developed, including 36,006 patients who underwent curative treatment. The surveillance group had a significantly higher proportion of curative treatment for HCC than the non-surveillance group after adjusting for confounding factors (adjusted hazard ratio [HR], 5.64; 95% confidence interval [CI], 5.48-5.81). The surveillance group had a significantly lower mortality rate than the non-surveillance group (adjusted HR, 0.56; 95% CI, 0.55-0.56). CONCLUSION: HCC surveillance using the national screening program in patients with chronic viral hepatitis or liver cirrhosis provides better opportunity for curative treatment for HCC and improves overall survival.

Predicting demand for long-term care using Japanese healthcare insurance claims data.

BACKGROUND: Driven by the rapid aging of the population, Japan introduced public long-term care insurance to reinforce healthcare services for the elderly in 2000. Precisely predicting future demand for long-term care services helps authorities to plan and manage their healthcare resources and citizens to prevent their health status deterioration. METHODS: This paper presents our novel study for developing an effective model to predict individual-level future long-term care demand using previous healthcare insurance claims data. We designed two discriminative models and subsequently trained and validated the models using three learning algorithms with medical and long-term care insurance claims and enrollment records, which were provided by 170 regional public insurers in Gifu, Japan. RESULTS: The prediction model based on multiclass classification and gradient-boosting decision tree achieved practically high accuracy (weighted average of Precision, 0.872; Recall, 0.878; and F-measure, 0.873) for up to 12 months after the previous claims. The top important feature variables were indicators of current health status (e.g., current eligibility levels and age), risk factors to worsen future healthcare status (e.g., dementia), and preventive care services for improving future healthcare status (e.g., training and rehabilitation). CONCLUSIONS: The intensive validation tests have indicated that the developed prediction method holds high robustness, even though it yields relatively lower accuracy for specific patient groups with health conditions that are hard to distinguish.

An International Aircraft Transport of a Neonate From Georgia to Japan.

International air transport over long distances necessitates considerable effort. It is even more challenging when the patient is a neonate and has a congenital disease. We hereby report a case of an international aircraft transport of a neonate from Tbilisi, Georgia to Osaka, Japan. The patient was transported to Osaka University Hospital after being diagnosed with a double outlet right ventricle (DORV), requiring surgical intervention. This unique experience has raised four issues: 1) language issues for referral and consultation; 2) medical equipment and healthcare professionals required to accompany the transport for adequate care; 3) scheduling of the international flight; and 4) the administrative procedures such as birth certificate, passport, and healthcare insurance. In this report, we describe how the patient was successfully transported, received treatment, and discharged home.