Chronological development of in-patient oncology in times of COVID-19: a retrospective analysis of hospitalized oncology and COVID-19 patients of a German University Hospital.

PURPOSE: The goal of this study is to examine the chronological development of hospitalized oncology and COVID-19 patients, and compare effects on oncology sub-disciplines for pre-pandemic (2017-19) and pandemic (2020-21) years in the setting of a German university maximum care provider. METHODS: Data were retrospectively retrieved from the hospital performance controlling system for patient collectives with oncological main (nOnco) and COVID-19 secondary diagnosis (nCOVID-19). Data analysis is based on descriptive statistical assessment. RESULTS: The oncology patient collective (nOnco = 27,919) shows a decrease of hospitalized patients for the whole pandemic (- 4% for 2020 and - 2,5% for 2021 to 2019). The number of hospitalized COVID-19 patients increases from first to second pandemic year by + 106.71% (nCOVID-19 = 868). Maximum decline in monthly hospitalized oncology patients amounts to - 19% (May 2020) during the first and - 21% (December 2020) during the second lockdown. Relative monthly hospitalization levels of oncology patients reverted to pre-pandemic levels from February 2021 onwards. CONCLUSION: The results confirm a decline in hospitalized oncology patients for the entire pandemic in the setting of a maximum care provider. Imposed lockdown and contact restrictions, rising COVID-19 case numbers, as well as discovery of new virus variants have a negative impact on hospitalized treated oncological patients.

Gesundheitsökonomischer Vergleich von onkologischen und COVID-19-Patienten

Aim This study examines the impact of the COVID-19 pandemic on hospitalized patients with cancer and/or COVID-19 disease at a university-based maximum care provider. Do the patient collectives differ in terms of health economics and do the results yield administrative implications for proactive management of regional cancer care. Method A retrospective, descriptive data analysis of clinical and health economic parameters of all oncological and COVID-19-postive patients admitted as in-patients at Marburg University Hospital and the combination of oncological patients with COVID-19 disease within the observation period from 2017 to 2021 was performed. Results A decrease in oncology-treated patients was observed throughout the COVID-19 pandemic period. Oncology patients with COVID-19 disease represent the patient population with the highest severity of disease, followed by COVID-19 and oncology-only patients. This is reflected in the economic performance measures. The chronological progression of DRG revenue and Case Mix Index per COVID-19 patient shows differences for time periods of the pandemic in Germany. Conclusion The comparison of the patient collectives confirms the particularly high-risk potential of oncological patients, which is reflected in a health economic costly treatment. National measures, contact restrictions or pandemic events can be traced by the chronological progression of clinical and economic parameters. Despite the international decline in out-patient and in-patient oncological patients, "state-of-the-art " cancer care is feasible in pandemic times. Because of this, there is a need for action for an inpatient maximum care provider to manage oncology care more proactively through communication and care modeling.

Impact of the COVID-19 Pandemic on Gyne-Oncological Treatment-A Retrospective Single-Center Analysis of a German University Hospital with 30,525 Patients.

The study pursues the objective of drawing a comparison between the data of gyne-oncology, gynecology, and obstetrics patient collectives of a German university hospital regarding the progression of patient number and corresponding treatment data during the five-year period of 2017-2021 to assess the impact of the COVID-19 pandemic on gyne-oncological treatment. Descriptive assessment is based on data extracted from the database of the hospital controlling system QlikView® for patients hospitalized at the Department of Gynecology and Obstetrics of Marburg University Hospital. Gynecology and gyne-oncology experience a maintained decline in patient number (nGynecology: -6% 2019 to 2020, -5% 2019 to 2021; nGyne-Oncology: -6% 2019 to 2020, -2% 2019 to 2021) with varying effects on the specific gyne-oncological main diagnoses. Treatment parameters remain unchanged in relative assessment, but as gyne-oncology constitutes the dominating revenue contributor in gynecology (35.1% of patients, 52.9% of revenue, 2021), the extent of the decrease in total revenue (-18%, 2019 to 2020, -14%, 2019 to 2021) surpasses the decline in patient number. The study displays a negative impact on the gynecology care situation of a German university hospital for the entire pandemic, with an even greater extent on gyne-oncology. This development not only endangers the quality of medical service provision but collaterally pressurizes gynecology service providers.

Impact of the COVID-19 Pandemic on Delivery of Gynecology and Obstetrics Services at a Maximum Care University Hospital in Germany.

Einleitung Die COVID-19-Pandemie bedeutet einschneidende Maßnahmen für das nationale Gesundheitssystem. Dies bot den Anlass, die klinischen und ökonomischen Leistungsindikatoren der gynäkologischen und geburtshilflichen Versorgung des Universitätsklinikums Marburg als regionaler universitärer Maximalversorger zu analysieren. Hierzu wurden die Auswirkungen auf die monatlichen stationären und ambulanten Fallzahlvolumina sowie die entsprechenden ICD- und DRG-Kodierungen ausgewertet, um etwaige Versorgungsdefizite aufzudecken. Material und Methoden Die Studie basiert auf einer retrospektiven Datenanalyse therapierter stationären und ambulanten Fälle der Jahre 2016 bis 2020. Hierzu wurden über das klinikinterne Leistungscontrolling-Programm QlikView die Daten von 9487 Fällen der Klinik für Gynäkologie und 19597 Fällen der Klinik für Geburtshilfe ausgewertet. Ergebnisse Es bildet sich eine der nationalen Pandemiedynamik folgende Abnahme der gynäkologischen stationären Fallzahlen um -6% ab, während das geburtshilfliche Fallzahlvolumen um +11% im Jahr 2020 steigt. Insgesamt fallen die Effekte für die ambulante Versorgung geringer aus. Zudem lässt sich eine standortbezogene Abnahme der C50 "Bösartige Neubildungen der Brustdrüse" und C56 "Bösartige Ovarialtumoren" Diagnosen um -7,4% bzw. -14% feststellen. Eine Rückkehr zu dem Leistungsniveau des Vorjahres konnte im ambulanten in 3 und im stationären Sektor in 5 Monaten erreicht werden. Schlussfolgerung Die negativen Auswirkungen der COVID-19-Pandemie treffen vorwiegend die Klinik für Gynäkologie. Durch das Vertrauen in die Sicherheit der universitären Versorgung und das Serviceangebot, werdende Väter nach Schnelltestung am Geburtsprozess teilhaben zu lassen, konnte eine Fallzunahme in der Geburtshilfe erreicht werden. Die Rückkehr zu präpandemischen Leistungsniveaus gestaltet sich weiterhin schleppend, während sich der ohnehin weniger betroffene ambulante Sektor zügiger erholt. Der standortbezogene Rückgang der Diagnosen C50 und C56 ist besorgniserregend und bedarf epidemiologischer Aufarbeitung. Die fallzahlbezogenen Auswirkungen der Pandemie bilden sich gleichsam in den ökonomischen Leistungskennzahlen ab.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic.

Pandemic scenarios like SARS-Cov-2 require rapid information aggregation. In the age of eHealth and data-driven medicine, publicly available symptom tracking tools offer efficient and scalable means of collecting and analyzing large amounts of data. As a result, information gains can be communicated to front-line providers. We have developed such an application in less than a month and reached more than 500 thousand users within 48 hours. The dataset contains information on basic epidemiological parameters, symptoms, risk factors and details on previous exposure to a COVID-19 patient. Exploratory Data Analysis revealed different symptoms reported by users with confirmed contacts vs. no confirmed contacts. The symptom combination of anosmia, cough and fatigue was the most important feature to differentiate the groups, while single symptoms such as anosmia, cough or fatigue alone were not sufficient. A linear regression model from the literature using the same symptom combination as features was applied on all data. Predictions matched the regional distribution of confirmed cases closely across Germany, while also indicating that the number of cases in northern federal states might be higher than officially reported. In conclusion, we report that symptom combinations anosmia, fatigue and cough are most likely to indicate an acute SARS-CoV-2 infection.