COVID-19 pandemic and waiting times in outpatient specialist care in Germany: an empirical analysis

Abstract

Background International healthcare systems face the challenge that waiting times may create barriers to accessing medical care, and that those barriers are unequally distributed between different patient groups. The disruption of healthcare systems caused by the COVID-19 pandemic could exacerbate this already strained demand situation. Using the German healthcare system as an example, this study aims to analyze potential effects of the COVID-19 pandemic on waiting times for outpatient specialist care and to evaluate differences between individual patient groups based on their respective insurance status and the level of supply. Methods We conducted an experiment in which we requested appointments by telephone for different insurance statuses in regions with varying levels of supply from 908 outpatient specialist practices in Germany before and during the COVID-19 pandemic. Data from 589 collected appointments were analyzed using a linear mixed effect model. Results The data analysis revealed two main counteracting effects. First, the average waiting time has decreased for both patients with statutory (mandatory public health insurance) and private health insurance. Inequalities in access to healthcare, however, remained and were based on patients’ insurance status and the regional level of supply. Second, the probability of not receiving an appointment at all significantly increased during the pandemic. Conclusions Patient uncertainty due to the fear of a potential COVID-19 infection may have freed up capacities in physicians’ practices, resulting in a reduction of waiting times. At the same time, the exceptional situation caused by the pandemic may have led to uncertainty among physicians, who might thus have allocated appointments less frequently. To avoid worse health outcomes in the long term due to a lack of physician visits, policymakers and healthcare providers should focus more on regular care in the current COVID-19 pandemic.

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“…This exposes a limit of robustness in the health care systems with regards to compensatory means that might have reached an upper limit in many centers at that time. Although the data material obtained in this study was largely explorative, allowing only for descriptive statistical analysis, the gradually attenuating waiting lists during the first year of COVID-19 were convincing, and in general corresponded to similar reports from adult surgery waiting lists in the same period (21)(22)(23)(24).…”

COVID-19 related decline in cancer screenings most pronounced for elderly patients and women in Germany: a claims data analysis

“…Mammography screenings were also suspended in Germany at the beginning of the pandemic (Ärztezeitung 2020 ), which is reflected in our data set with a decrease of 98.71% in April 2020. At the same time, there is evidence that the likelihood of receiving appointments in outpatient practices in Germany decreased at the onset of the pandemic (Muschol and Gissel 2021 ), which may also have contributed to the change in case numbers for preventive health services. (3) The different multiyear eligibility of each screening may have had an influence on utilization.…”

Motivo de consulta y tiempo de espera en establecimientos de salud públicos durante la pandemia por COVID-19, Perú 2020.

“…Para ello, debe considerarse que el sistema de salud tiene menos desventajas de inequidad a comparación de nuestro sistema sanitario. [13] En nuestro estudio, la mayor cantidad de pacientes que acuden al establecimiento del MINSA, esperan 20 minutos más en comparación de los pacientes asegurados en EsSalud. Datos similares se obtuvieron de los análisis realizados por parte de INEI, en los cuales el tiempo de espera es mayor en pacientes que acuden a establecimientos pertenecientes al MINSA a comparación de EsSalud.…”

“…[9] Se recalca estas asociaciones debido a la importancia de implementar programas o medidas de mejora, para con ello disminuir los tiempos de espera, con lo cual se pueden tener mejores resultados en las atenciones; además, que al considerar que un tiempo de espera largo puede conducir a resultados de salud inferiores es motivo de preocupación. [9,12,13] Este es uno de los primeros estudios que evalúan la asociación de los determinantes identificados que pueden asociarse a mayor tiempo de espera en la población durante el tiempo de la pandemia por COVID-19 en el Perú, realizado a partir de la encuesta ENAHO. Sin embargo, al tratarse de un estudio transversal y de fuente secundaria, presenta limitaciones, en particular con respecto al control del llenado adecuado al momento de realización de las encuestas, así mismo, la pérdida de datos que se puede presentar.…”