Since the 1 January, 2009, newborn hearing screening (NHS) has been obligatory for every child in Germany. NHS is part of the Pediatrics Directive of the Federal Joint Committee. In this directive, details of the procedures and screening quality to be achieved are given. We evaluate if these quality criteria were met in Bavaria in 2016. The NHS data of children born in 2016 in Bavaria were evaluated for quality criteria, such as screening coverage in screening facilities, screening methods, referral rate (rate of failed tests at discharge) and a child’s age at the diagnosis of a hearing disorder. NHS was documented for 116,776 children born in Bavaria in 2016. In the first step, 78,904 newborns were screened with transient evoked otoacoustic emissions and 37,865 with automated auditory brainstem response. Of these, 9182 (7.8%) failed the first test in one or both ears. A second screening before discharge was performed on 53.3% of the newborns with a refer result in the first test, out of which 58.7% received a pass result. After the screening process, 4.6% of the newborns were discharged with a refer result. Only 18% of the first controls after discharge were performed by a pediatric audiologist. In 37.9% of the newborns, the screening center intervened to assure the control of any failed screening test. The median age of diagnosis for bilateral hearing loss was 5.3 months. In Bavaria, NHS was implemented successfully. A tracking system for all children who failed the hearing screening test is pivotal for early diagnosis and therapy of children with hearing deficiency.

Zusammenfassung Hintergrund Das Neugeborenen-Hörscreening (NHS) dient der frühzeitigen Erkennung und Behandlung von angeborenen Hörstörungen. Es ist in der „Kinder-Richtlinie“ geregelt, die eine Evaluation nach 5 Jahren vorsieht. Diese erfolgte erstmals bundesweit für die Jahre 2011 und 2012 in Hinblick auf Struktur-, Prozess- und Ergebnisqualität des NHS. Fragestellung Herausforderungen bei der Ermittlung geeigneter Daten als Grundlage der Evaluation sollen beschrieben und Verbesserungsmöglichkeiten aufgezeigt werden. Methoden Als relevante Leistungserbringer des NHS wurden alle geburtshilflichen und neonatologischen Abteilungen identifiziert und deren Dokumentationen des NHS ausgewertet. Darüber hinaus wurden alle pädaudiologischen Institutionen bundesweit identifiziert, um anonymisierten Daten der Kinder mit beidseitigen, konnatalen, permanenten Hörstörungen aus den relevanten Geburtsjahrgängen abzufragen. Ergebnisse Die vollständige Erfassung der relevanten Leistungserbringer war sehr aufwendig. Über der Hälfte der Leistungserbringer war nicht bekannt, dass für Daten des NHS eine Sammelstatistik zu erstellen ist. Für 15% der zu screenenden Kinder lagen keine Daten zum NHS vor. Bei der Erhebung der Kinder mit beidseitigen konnatalen Hörstörungen wurden nur 60% der erwarteten Fälle erfasst. Schlussfolgerungen Für die Evaluation der Struktur-, Prozess- und Ergebnisqualität des NHS standen teilweise nur lückenhafte Daten zur Verfügung. Die Datengrundlage bei geplanten Evaluationen sollte im Vorhinein in der Richtlinie präzise definiert und Strukturen für die Erhebung der Daten prospektiv geschaffen werden, um noch aussagekräftigere Ergebnisse zu erzielen. Trotz der hier vorgestellten Probleme konnte die bundesweite Evaluation des NHS wichtige Ergebnisse zum Screeningprozess aufzeigen.

In Germany, data of the statutory health insurance system are used, amongst others, in health monitoring and health care research at the district level. For the calculation of exact ratios, the number of those covered by statutory health insurance is needed as denominator. For some federal states, however, this number is not available on a district level. Therefore, ratios based on statutory health care data are calculated using a surrogate defined in terms of visits to the doctor. This leads to uncertainties that limit small area comparisons. Therefore, the aim of the present study was to develop a superior estimation model for the number of those covered by statutory health insurance on a district level. The proportion of those covered by statutory health insurance in the Bavarian districts is estimated by a multiple linear regression model. The model relates data on determinants of the insurance status (income, proportions of civil servants and of self-employed persons) available on district level to data on the number of those covered by statutory health insurance obtained from microcensus on a regional level. The proportion of those covered by statutory health insurance estimated by this model is compared to the surrogate. As an example for practical application, small area estimations for diabetes prevalence are compared to data provided by the Bavarian Association of Statutory Health Insurance Physicians. The proportion of those covered by the statutory health insurance in the Bavarian districts as estimated by the regression model varies between 74.7 and 91.6%. The difference to the currently used surrogate reaches up to 18.6 percentage points. This is also reflected in treatment prevalence, shown here using the example of diabetes mellitus. The present analysis shows the uncertainties of ratios and consequences for small area comparisons based on statutory healthcare data. Providing valid data for the denominator in accordance with the data transparency regulation in the Social Insurance Code (SGB) V should be attempted.