{"paper_id":"389c7038-6dbe-406a-bb09-220880bd4e51","body_text":"Brauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nOriginal Article Thieme\nInpatient Endometriosis Care in Germany: Hospital Caseloads and \ntheir Spatial Distribution\nStationäre Endometrioseversorgung in Deutschland – \nKrankenhausfallzahlen und ihre räumliche Verteilung\n  \nAuthors\nLara Brauer , Limei Ji, Max Geraedts\nAffiliations\nInstitut für Gesundheitsversorgungsforschung und Klinische \nEpidemiologie, Philipps-Universität Marburg, Fachbereich 20 \nMedizin, Marburg, Germany\nKeywords\nendometriosis, health services research, spatial distribution, \nGerman hospital quality reports\nSchlüsselwörter\nEndometriose, Gesundheitsversorgungsforschung, räumli -\nche Verteilung, Qualitätsbericht der Krankenhäuser\nreceived 06.03.2025  \naccepted after revision 12.06.2025  \npublished online 2025\nBibliography\nGesundheitswesen\nDOI 10.1055/a-2683-9705\nISSN 0941-3790\n© 2025. The Author(s).\nThis is an open access article published by Thieme under the terms of the \nCreative Commons Attribution License, permitting unrestricted use, \ndistribution, and reproduction so long as the original work is properly cited. \n(https://creativecommons.org/licenses/by/4.0/).\nGeorg Thieme Verlag KG, Oswald-Hesse-Straße 50,  \n70469 Stuttgart, Germany\nCorrespondence\nLara Brauer\nPhilipps-Universitat Marburg, Fachbereich 20 Medizin,\nInstitut für Gesundheitsversorgungsforschung und Klinische \nEpidemiologie\nKarl-von-Frisch-Straße 4\n35032 Marburg\nGermany \nlara.brauer@uni-marburg.de\nSupplementary Material is available under  \nhttps://doi.org/10.1055/a-2683-9705\nAB str Act\nBackground Endometriosis is a chronic gynaecological disease \nwith an estimated prevalence of 10–15 %. The German guide-\nline provides evidence-based recommendations for diagnosis \nand treatment, but care provided is inadequate care due to \nlong diagnostic pathways. Recent German research focused on \nregional variations in outpatient care, however research on \ninpatient endometriosis care is still lacking.\nAim of the Study The aim of the study was to examine inpa\n-\ntient endometriosis care – hospital locations and their case -\nloads. Spatial coverage, caseload distribution patterns and \npossible clusters, including certified endometriosis centres \n(CEC) and non-certified hospitals nationwide were analysed.\nMethod German hospital quality report data from 2021 was used \nas data source. The location, certification status and caseload, \nmeaning coded ICD-10 N80 Endometriosis cases, were collected \nfor all hospitals. Then, 20-, 40- and 60-minutes’ drive radius of \nCEC and non-certified hospitals were determined. Global and \nLocal Moran’s I was calculated to assess spatial clusters in caseload.\nResults A CEC 60-minutes’ drive radius covers 78.15 % of the \narea in Germany. Including all hospital locations that coded \nendometriosis, a maximum driving time of 40-minutes pro\n-\nvides almost nationwide coverage. High caseload clusters ap -\npeared in urban areas and low caseload clusters especially in \neastern Germany.\nConclusion The results indicate spatial clusters in providers \ncaseload and difficulties in access to CEC for patients depending \non location. Further research with patient-level data is needed \nto investigate the spatial distribution of patients and precise \ntravel time for inpatient care.\nZus AMMenf Assun G\nHintergrund Endometriose ist eine chronische gynäkologi sche \nErkrankung mit einer geschätzten Prävalenz von 10–15 %. Die \ndeutsche Leitlinie enthält evidenzbasierte Empfehlungen für \nDiagnose und Behandlung, jedoch scheint es aufgrund langer \nDiagnosewege eine dysfunktionale oder unzureichende Ver\n-\nsorgung zu geben. Aktuelle deutsche Studien befassen sich mit \nden regionalen Unterschieden in der ambulanten Versorgung, \nForschung zu stationärer Endometrioseversorgung fehlt bisher.\nArticle published online: 2025-11-03\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nOriginal Article Thieme\nIntroduction\nEndometriosis is a benign, chronic gynaecological disease associ -\nated with painful menstruation, heavy bleeding or infertility [1, 2]. \nThe disease has a significant impact on women’s lives and they \noften experience a lack of understanding from the healthcare sys-\ntem, stigmatisation of their pain and delayed diagnoses [2, 3].\nHowever, the precise healthcare situation of endometriosis pa-\ntients or even reliable rates of endometriosis prevalence are not avail-\nable in Germany due to a lack of data [4]. It is estimated that 10–15 % \nof all women of reproductive age are affected and 40,000 women \ndevelop endometriosis each year [4]. Recent research showed that \nannual prevalence continued to increase from 2012 to 2022, but re-\nmained below epidemiological prevalence estimates [5].\nThe guideline Diagnosis and Therapy of Endometriosis [6] provides \nevidence-based recommendations for diagnosis and treatment. \nStill, on average, it takes 2.3 years from symptom onset to the first \ncontact with providers, and 7.7 years elapse from first contact to \ndiagnosis [7]. This suggests that dysfunctional or inadequate care \nstill seems to exist, particularly due to long diagnostic pathways.\nA certification programme and treatment standards have been \ninitiated in several European countries to improve the quality of care \nfor endometriosis patients [6]. The German guideline states that pa-\ntients should be treated by an interdisciplinary team in a certified \nstructure (e. g. centre) that integrates all necessary specialities across \nsectors. Therefore, the consensus-based care algorithm includes cer-\ntified endometriosis centres (CEC) for diagnosis, operative/interdis-\nciplinary laparoscopy, follow-up and conservative therapy [6]. How-\never, the QS ENDO quality assurance programme for German-speak-\ning countries (DACH region) estimates that around 60 % of \nendometriosis patients are not treated in hospitals with a CEC [8].\nThere is little research on the differences on the quality of pa -\ntient care in a CEC and a non-certified hospital. In general, in certi-\nfied centres, e. g. for cancer care, guideline-conforming care is high-\ner in percentage than in non-certified facilities [9]. Specifically for \nCEC, improved quality of life and lower complication rates were as-\nsociated with certification status [10].\nAlthough the ESHRE Endometriosis Guideline [11] no longer re-\ncommends laparoscopy as the diagnostic gold standard, laparos -\ncopy is still the standard procedure to surgical therapy [6]. Often, \nlaparoscopy is used for diagnostic examination and, if necessary, \ntreatment of endometriosis during the same procedure [6], mean-\ning inpatient care has its irreplaceable importance. However, little \nis known about the structure of inpatient endometriosis care, in \nparticular about the distribution of hospitals providing such care \nin Germany. The need for a regional monitoring to evaluate health-\ncare provision as a first step to healthcare improvement and equi-\nty is well known [12, 13], meaning that investigations on the distri-\nbution of inpatient care and the certified care structure for endo -\nmetriosis are needed.\nTherefore, the aim of this study was to examine the spatial dis-\ntribution and accessibility of CEC and non-certified hospitals and \nto evaluate their caseload in order to show regions with low access \nto specialised care.\nMethods\nThe study uses German hospital quality reports (HQR) 2021 as data \nsource, Isochrones process in OpenRouteService as well as Spatial \nAutocorrelation (Global Moran’s I) and Cluster and Outlier Analysis \n(Anselin Local Moran’s I) processes in ArcGIS Pro 2024 for the spa-\ntial analysis of coded inpatient caseloads\nData sources\nGerman Hospital Quality Reports\nThe HQR are made publicly available by the Federal Joint Commit-\ntee (G-BA), which specified that hospitals must report on inpatient \ncare for each location every year [14].\nThe coded endometriosis caseload, defined as a discharge diag-\nnosis of ICD-10 N80 Endometriosis and all subgroups, of each hos -\npital location in the 2021 HQR was used as the basic population. \nAlso, endometriosis-related inpatient procedures were identified \nusing the operation and procedure code (OPS). According to the en-\ndometriosis guideline, specific OPS exist only in part and mainly for \nthe destruction of endometriosis lesions [6]. Therefore, OPS 5-\n651.b, 5-702.2 and 5-702.4 were included. Other OPS were exclud-\ned as it is not possible to filter out whether they were specifically \ncoded for endometriosis. Each included ICD-10 and OPS Codes are \npresented in the online-Appendix (t able s1).\nThe exact case number is not reported in the HQR for privacy \nreasons, if the caseloads were fewer than four cases [15].Then, the \nZiel der Studie Die Studie untersuchte die räumliche Ver -\nteilung der stationären Endometrioseversorgung, genauer \ngesagt die Krankenhausstandorte und ihre Fallzahlen. Räumli-\nche Abdeckung, Verteilungsmuster der Fallzahlen und mögli -\nche Cluster wurden bei zertifizierten Endometriosezenten \n(CEC) und nicht-zertifizierten Standorten bundesweit evaluiert.\nMethode Datenquelle waren die deutschen Krankenhaus-Qua-\nlitätsberichte aus dem Jahr 2021. Krankenhausstandorte, Zerti\n-\nfizierungsstatus und Fallzahlen (kodierte ICD-10 N80 Endome-\ntriosefälle) wurden erfasst. Danach wurde der 20-, 40- und \n60-Minuten Fahrzeitradius zu den CEC und den nicht-zertifi -\nzierten Krankenhäusern ermittelt. Global und Local Moran’s  \nI wurde berechnet um räumliche Cluster der Fälle zu bestimmen.\nErgebnisse  Ein 60-Minuten Fahrzeitradius zu CEC deckt \n78,15 % der Fläche in Deutschland ab. Unter Einbeziehung aller \nKrankenhausstandorte, die Endometriose kodiert haben, er gibt \nsich bei einer maximalen Fahrtzeit von 40 Minuten eine fast \nlandesweite Abdeckung. Hohe Fallzahlen-Cluster traten in \nstädtischen Gebieten und niedrige Fallzahlen-Cluster vor allem \nin Ostdeutschland auf.\nSchlussfolgerung Die Ergebnisse deuten auf räumliche Cluster \nder Fallzahlen und auf Schwierigkeiten beim Zugang zu den \nCEC für Patientinnen je nach Standort hin. Weitere Untersu\n-\nchungen mit Daten auf Patientinnen-Ebene sind erforderlich, \num die räumliche Verteilung der Personen und die genaue \nFahrtzeit für die stationäre Versorgung zu untersuchen.\n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nodd value of 1.5 cases was assumed, as already applied for HQR \ndata analysis before [16]. The possible error in the calculation of \nthe caseloads was squared using DESTATIS data. According to \nDESTATIS, 32,304 discharged patients were coded as endometrio-\nsis cases in 2021 [17].\nFurthermore, name, hospital location ID and address of the hos-\npital was extracted.\nList of certified endometriosis centres\nThe Endometriosis-Association Germany (Endometriose-Vereinigung \nDeutschland e.V.) has listed all hospitals certified by the Endome-\ntriosis Research Foundation (SEF) on its website [18]. We therefore \ndefined all hospitals listed on this website as CEC. At the time of \ndata collection (15 July 2024), 72 providers were listed as certified, \nof which 68 were identified in the 2021 HQR. The remaining 4 were \neither outpatient providers and probably accidentally listed with \nthe inpatient CEC, or they did not provide their HQR for 2021. \nTherefore, n = 68 hospitals were included in our CEC sample.\nData Analysis\nDescriptive analysis\nInpatient endometriosis caseloads were analysed descriptively. \nCase numbers were calculated for each ICD-10 code and, in the \ncase of data protection, estimated using the procedure described. \nThen, total cases were calculated by summing all N80.x codes to \nan overall endometriosis caseload for each hospital location. Fre -\nquencies, means and standard deviations of total cases were cal -\nculated for all hospital locations, separately for CEC and non-certi-\nfied hospital locations with at least one coded endometriosis case. \nThese steps were repeated for OPS codes 5-651b and 5-702.2 / \n5-702.4 summed up.\nData was processed with Excel 2019 and SPSS 29.\nSpatial analysis\nWe analysed spatial coverage to provide an initial general estimate \nfor the care situation in Germany (a.). Then, we carried out spatial \nstatistics within a defined radius to identify regions with particu -\nlarly high or low clusters, and therefore gaps in care (b.). Based on \nthe addresses in the HQR, the geographical positions of the hospi-\ntal location ID were determined using OpenStreetMap.\na.  The spatial coverage (drive radius) was calculated separately for \nCEC and for all hospitals with at least one case. A recent study \non pain medicine discussed that a 30 to 45 minutes (min) drive \nis reasonable for specialised pain care in Germany, with up to \n60 min being acceptable in individual cases [19]. Applying this \nto endometriosis care, a maximum driving time (DT) of 60 min \nwas set. Thus, regions with DT less than or equal to 20-, 40- and \n60-min to CEC and other hospitals was determined and present-\ned with Isochrones function/module of OpenRouteService.\nb.  To identify regional spatial clusters in coded cases, Moran’s I \nanalyses were performed [20]. All hospital locations coding en-\ndometriosis in 2021 were included. The number of cases at each \nhospital location was compared with cases at hospitals within a \n45 km radius. A distance of 45 km was set for patients based on \nan assumed driving time of 45 min at an average car speed of \n60 km/h. Global Moran’s I analysis [20] was performed to inves-\ntigate whether caseloads were clustered. If Global Moran's I \nshows a significant spatial correlation, Local Moran’s I [20] can \nbe used to test for local clusters.\nGlobal and Local Moran’s I analysis was performed using ArcGIS Pro \n2024. QGIS Version 3.36.1 was used for visualisation.\nResults\nCaseload\nOverall, 32,440.5 endometriosis cases were coded in 2021. In CEC \n(n = 68), a total of 13,709.5 cases (42.26 %) were observed. In hos-\npital locations without CEC and at least one endometriosis case \n(n = 807), 18,731 cases (57.74 %) were coded. ▶table 1 shows the \ncaseload (including privacy calculations) for CEC and non-CEC, \n▶table 2 the caseload for each included ICD-10 and OPS code.\nThe included OPS codes are not solely specified for endometri-\nosis cases. This suggests that other OPS codes were probably used \nfor endometriosis cases, or that the included OPS were also used \nfor other diseases. Consequently, the determined caseload of en -\ndometriosis and selected OPS codes do not correspond.\nSpatial distribution\nDriving time\nCaseloads and DT were analysed and cartographically presented.\n▶f ig. 1 shows cases and DT for CEC, with most cases coded in Co-\nlogne and Berlin. In Munich, medium caseload was coded in two lo-\ncations. Less than 500 cases were coded in each remaining CEC \n(n = 64). The distribution of CEC varies from state to state, ranging \nfrom zero CEC in Bremen, Mecklenburg-Western Pomerania (M-WP) \nand Saxony-Anhalt (S-A) to 21 in North Rhine-Westphalia (NRW).\nWith a maximum DT of 60 min, the CEC alone do not cover the \nentire country, but 78.15 % of the total area and 91.32 % of the fe-\n▶table 1  Total caseload.\nn ( %) total cases ( %) M sD Md [Min–Max]\nAll hospitals with at least 1 coded \nendometriosis case\n875 (100 %) 32,440.5 (100 %) 37.07 79.93 17.5 [1.5–1135]\nNon-certified hospital locations & at \nleast 1 coded endometriosis case\n807 (92.23 %) 18,731 (57.74 %) 23.21 30.67 15 [1.5–388.5]\nHospitals with certified centre 68 (7.77 %) 13,709.5 (42.26 %) 201.61 205.53 149.52 [15.5–1135]\ntotal cases, number of coded ICD-10-GM N80 endometriosis cases including all subcategories and data protection calculation; M, Mean; SD, standard \ndeprivation; Md, Median; Min, minimum; Max, maximum.\n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nOriginal Article Thieme\nmale population. Only the west of M-WP is covered within 60 min, \nas are the south and eastern parts of S-A. In Brandenburg, the 60 min \nradius around Berlin is covered, the outskirts mainly not. North and \nsouth Thuringia are also not covered, with one CEC in the east. Gaps \nalso exist in the north, east and south of Saxony, as well as in south-\nern Baden-Württemberg (B-W), eastern Bavaria, northern Schleswig-\nHolstein and western Rhineland-Palatinate (R-P). Major cities in NRW, \ne. g. Cologne, Duisburg and Münster, can be reached within 20 min \nDT, with most of the state being accessible within 40 min.\n▶f ig. 2 shows all non-certified hospitals with at least one en -\ndometriosis case. Most cases were coded in the cities of Neuss, \nFrankfurt (n  = 2), Munich and Wuppertal. Caseload > 37.5 − 158 \nwere coded in 138 hospital locations, while caseloads ≤ 37.5 were \ncoded in the remaining 664 hospital locations.\nConsidering all hospitals that coded endometriosis, almost the \nentire country is covered within a 40 min DT, expect for a few areas \nwhere it takes 60 min to reach a hospital (e. g. Ortenau district, the \nBrandenburg border or in frontier regions). NRW, Berlin, Hamburg \nand Bremen are mainly covered with a DT of 20 min and medium \nor large case numbers.\nSpatial cluster\nGlobal Moran’s I test revealed a slightly positive, significant spatial \ncorrelation (I  = 0.028, z = 1.722; p = 0.085) of coded cases, mean -\ning the distribution of caseloads is clustered.\nLocal Moran’s I was performed to assess clusters of high and low \ncase numbers in hospitals. The cartographic visualisation is shown \nin ▶f ig. 3.\nLow-Low clusters can be identified in Saxony, M-WP, S-A, Lower \nSaxony, Thuringia, Brandenburg, Bavaria, Flensburg city, the Hoch-\nsauerland district and R-P. Those clusters are mainly located in east-\nern Germany, with the most clusters in Saxony.\nHigh-High clusters can be found in the city of Munich and its en-\nvirons, Berlin, Brandenburg, the districts of Cologne and Düssel -\ndorf, in B-W in the city of Freiburg and the district of Stuttgart, and \nin Frankfurt.\nDiscussion\nInpatient endometriosis care in Germany shows regional variation. \nA tendency towards clusters with more coded cases in urban areas \nand fewer coded cases in eastern Germany was observed. Particu-\nlarly areas in the eastern German states, which largely correspond to \nthe territory of the former GDR, were not covered with a driving time \n(DT) of 60 min to certified endometriosis centres (CEC). The evalua-\ntion of all hospital locations that coded at least one endometriosis \ncase in the HQR 2021 showed an almost nationwide DT of 40 min.\nTo our knowledge, there is little research on spatial clusters of \ninpatient endometriosis care in Germany. So far, prevalence or in-\ncidence studies [21, 22] or regional trends in outpatient care [5, 23] \nhave mainly been analysed.\nData on outpatient care provide evidence of regional variations \nin prevalence [5] and healthcare structures [23], suggesting that \nendometriosis is more frequently diagnosed in regions with a CEC. \nEach additional centre is associated with 0.28 more cases per 1,000 \nwomen with statutory health insurance [23]. Greater diagnostic \nexpertise at CEC may explain some differences, but certified hos -\npitals alone do not fully account for regional variation. Clusters with \nhigh incidence were identified in NRW and southern Germany, \nwhere most of the CEC are located [23]. Regional clusters with high \nprevalence of diagnosed endometriosis were also found in south -\nern Germany and Lower Saxony [5]. There was no clustering in re-\ngions with many CEC, but a cluster in Saxony with low diagnosis \nprevalence and districts close to CEC had a higher prevalence [5]. \nThis is consistent with our findings, as we identified high clusters \nof inpatient cases in southern Germany, NRW and Berlin and low \nclusters of caseloads in eastern Germany.\nWith regard to CEC, the QS ENDO quality assurance programme \nwas developed for the DACH region to provide further insights, \nwhich showed that about 60 % of endometriosis patients are not \ntreated in CEC [8]. Based on our results, it is possible that accessi -\nbility of centres may play a role. We were able to show that CEC \nalone are not accessible to all patients within 60 min DT, so we as-\nsume that patients either accept a longer DT or seek care in non-\ncertified hospitals and may receive less specialised care.\nHowever, specialised care is guideline-conform as the care al -\ngorithm includes a CEC for diagnosis, laparoscopy, and follow-up \nor conservative therapy [6]. CEC were also associated with im -\nproved quality of life and low major complication rates [10]. There-\nfore, access to CEC should be available to all patients. A possible \nsolution would be a better spatial distribution or more CEC. How -\never, we assume that staff shortages, financial barriers (e. g. the \n▶table 2  Caseload for each ICD-10 and OPS code (see appendix for code \nexplanations).\nc aseload \ncalculations \n(including data \nprotection)\nin hospitals \nwith certified \ncentre \n(n = 68)\nin hospitals \nwithout \ncertified \ncentre \n(n = 807)\ntotal ( %)\nIc D-10-GM  \nn80.x total\n13,709.5 \n(42.26 %)\n18,731 \n(57.74 %)\n32,440.5 \n(100 %)\n→ N80.- 0 7 7 (0.02 %)\n→ N80.0 2,724.5 4,954 7,678.5 \n(23.67 %)\n→ N80.1 2,638.5 6,322.5 8,961 \n(27.62 %)\n→ N80.2 54.5 187 241.5 \n(0.74 %)\n→ N80.3 6,545.5 4,477 11,022.5 \n(33.98 %)\n→ N80.4 355.5 255 610.5 \n(1.88 %)\n→ N80.5 383 285.5 668.5 \n(2.06 %)\n→ N80.6 199.5 604 723.5 \n(2.23 %)\n→ N80.8 729 1,268.5 1,997.5 \n(6.16 %)\n→ N80.9 159.5 370.5 530 \n(1.63 %)\nOPs 5-651.b  1,342.5 \n(30.19 %)\n3,104 \n(69.81 %)\n4,446.5 \n(100 %)\nOPs \n5-702.2 + 5-702.4\n13,686.5 \n(51.86 %)\n12,704 \n(48.14 %)\n26,390.5 \n(100 %)\n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\ncost of the certification process) and/or structural factors (e. g. a \nlack of regional cooperation) may influence hospitals in regions \nwithout a CEC to decide not to pursue or achieve certification. Tele-\nmedicine networks may hereby be a possible tool for providing \nmedical infrastructure and improving quality, presumably also for \nendometriosis care, particularly in regions without a CEC [24].\nResearch on certified centres for other gynaecological condi -\ntions underlines their importance. In oncology care, centres can \nimprove cost-effectiveness while optimising quality [25], which ad-\nvocates treatment in certified centres to meet quality indicators \n[9] and in terms of health economics [25]. These factors may also \napply to CEC.\nInternational research also found heterogeneous incidence pat-\ntern in hospitalisation, suggesting changing practices, awareness, \ninequalities and environmental factors [26]. Similarly in Italy, en -\ndometriosis incidence showed a spatial gradient, with a cluster of \nhigh-risk municipalities [27].\n15.5 – 500\n500 – 1000\n1000 – 1135\nCaseload ICD-10 N80\ncertified centres (n=68)\n20 minutes driving time\n40 minutes driving time\n60 minutes driving time\nDriving times\nto certified centres\n▶f ig. 1 Driving time and caseload of certified centres.\n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nOriginal Article Thieme\nIn our study, environmental factors and socio-economic struc-\ntures are likely to explain some of the spatial patterns. However, HQR \ndata cannot be used to identify individual patients, so we do not have \ninformation on, e. g., socioeconomic status (SES). Yet SES may have \nan impact on patients’ choice of hospital, as patients with higher SES \nmay have less difficulty in choosing or travelling to specialised care, \nwhile those with lower SES may lack access or information [28].\nThis shows case numbers from the HQR have limitations. First, \nthey can only be used to determine general coding frequencies, \nnot person-specific codes, and coding practices may influence case-\nload. It is not possible to estimate diagnoses prevalence using the \nHQR. The 2021 data may also be biased by reduced use of health \nservices during the pandemic [29]. We did not consider population \nor female density for spatial case clusters. Besides, this investiga -\n1.5 – 37.5\n37.5 – 158\n158 – 388.5\nCaseload ICD-10 N80\nnon-certified hospitals\nn=807\n20 minutes driving time\n40 minutes driving time\n60 minutes driving time\nDriving times\nto all hospital locations\n▶f ig. 2 Driving time to all hospitals and caseload of non-certified hospitals.\n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nHigh-High cluster:\nhospital with high caseload surrounded \nby hospitals with high caseload  \nwithin 45 km\nLocal Moran's  I (radius=45km)\nIncluded hospital locations: n=875\nLow-Low cluster :\nhospital with low caseload surrounded \nby hospitals with low caseload  \nwithin 45 km\nHoch-Niedrig Cluster:\nhospital with high caseload surrounded \nby hospitals with low caseload  \nwithin 45 km\nNiedrig-Hoch Cluster:\nhospital with low caseload surrounded \nby hospitals with high caseload  \nwithin 45 km\nNon-significant hospital\nLocation of certifie d\nendometriosis centre\n▶f ig. 3 Local Moran’s I (radius = 45 km) for all hospital locations.\ntion does not allow conclusions about waiting times for treatment, \nwhich seems likely in regions with high clusters.\nOur case calculations resulted in a slightly higher total than re -\nported by DESTATIS [17] for 2021 (32,440.5 estimated cases vs. \n32,304 reported cases), which may have led to an overestimate in \nsome hospitals. However, it also shows that our calculations are \nwithin a good range, meaning our study provides a robust overview \nof caseloads and spatial patterns. Another strength is the analysis \nof DT to CEC, which has not been investigated before.\nConclusion\nThe spatial distribution of coded endometriosis cases from the HQR \nvaried, with higher clusters in urban areas and lower clusters in east-\nern Germany. Assuming a driving time of 60 min to a certified en-\ndometriosis centre, there is no nationwide coverage, mainly for the \neastern German states. Including the non-certified hospitals, a driv-\ning time of 40 min was found almost nationwide. The results show \nthe importance of either more certified centres or a better distri -\nbution to cover all areas. Further research with person-related data \n\n\nBrauer L et al. Inpatient endometriosis care in … Gesundheitswesen | © 2025. The Author(s).\nOriginal Article Thieme\nlinked to population is needed for precise statements about the \nspatial distribution of inpatient cases, diagnoses and endometrio -\nsis-related surgery. These investigations could ensure barrier-free \naccess to inpatient endometriosis care, regardless of the person or \nlocation, in line with the principle of equity in health care.\nData Availability\nThe dataset generated in this study is available from the correspond -\ning author on reasonable request. German Hospital Quality Report \ndata is publicly available.\nContributions\nLB, LJ and MG developed the study concept and design. Analyses were \ncarried out by LB and LJ. The results were interpreted by LB. LB wrote \nthe first draft of the manuscript; LJ and MG revised and approved it.\nConflict of Interest\nThe authors declare that they have no conflict of interest.\nReferences\n[1] Wren G, Mercer J. 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