Gesundheitswesen最新文献

Introduction: The care of children and adolescents in need of care at home is exacerbated by the shortage of skilled workers in the care sector, which leads to bottlenecks in care and presents caring families with major challenges. The implementation of new care approaches in existing structures in the healthcare system is proving to be a key development task in order to provide targeted support for affected families in the future.

Methods: Qualitative explorative interview study to record the perspective of families with (seriously) ill children and adolescents on the current care situation and possible helpful support services. The sampling was criteria-driven and the analysis and evaluation was content-analytical. Respondents were given a short questionnaire to record socio-demographic characteristics.

Results: In particular, the transmission of the diagnosis, the everyday challenges and the impact on quality of life were named as stress factors by n=10 participating parents. Improved access to information, voluntary structures and central contact points as well as digital services were named as key development needs.

Conclusion: The interviews from real life and needs-oriented perspective show that there is a need to expand low-threshold care coordination services, strengthen voluntary structures and use telemedical services. Meeting these needs should enable access to specialized treatment and helpful services, especially in rural areas.

Background: The principle of "rehabilitation before care" is a principle of social law. The recommendation of the Medical Service (MD) as part of the assessment (§ 31 SGB XI) plays an important role in rehabilitation recommendations. In around 3% of its assessments, the MD recommends implementation of rehabilitation. Only every fourth to fifth recommendation is actually carried out. The aim of the study was to find out if rehabilitation recommendations are utilized and exploited.

Materials and methods: This study aimed to examine the perspective of insured persons whose recommended rehabilitation was actually carried out. After evaluating 586,228 routine data records with care assessments by the MD, 1,972 survey questionnaires were sent out in March 2023, and 1,116 analyzable questionnaires were included in the data analysis. In seven questions, the respondents were asked to retrospectively assess the overall success and satisfaction with rehabilitation procedures carried out.

Results: The evaluation of the results showed that 87% of the study participants would be ready to undergo repeat rehabilitation. The assessment of the success of rehabilitation in terms of remaining at home for a longer period of time also carried weight. On the other hand, only around 10% of rehabilitation was carried out on an outpatient basis.

Conclusions: One previously assumed reason for the low rate of patients taking advantage of recommended rehabilitation was that those in need of care had already received rehabilitation in the previous year. In this study focussing on whether recommended rehabilitation is taken advantage of, this assumption was found not to be correct. The question needs to be raised whether the strong focus in Germany on inpatient rehabilitation is up-to-date, both medically and with regard to the preferences of those entitled to rehabilitation. In contrast to inpatient rehabilitation, individual, outpatient and, if necessary, mobile rehabilitation offers might be more suitable, and these would also take into consideration issues of individual mobility and patient autonomy. The offer of different modes of rehabilitation also enables meeting the wish of those patients who prefer to have rehabilitation carried out in a home environment.

Diabetic kidney disease and renal replacement therapy are long-term complications of diabetes mellitus and significantly contribute to disease burden. The aim of the analysis was to develop case definitions for diabetic kidney complications in routine data as part of the diabetes surveillance and to internally validate them.Based on an age- and sex-stratified sample of persons covered by the Barmer health insurance, individuals with documented diabetes (E10-E14) were included and differentiated by type 1 (T1D) and type 2 diabetes (T2D). Case definitions were developed for persons with diabetic nephropathy (DNP; ICD: N08.3, E1x.2), chronic kidney disease (CKD; ICD: N18) and renal replacement therapy (RRT) with long-term dialysis (EBM: 40815-40819, 40823-40828 / OPS: 8-853, 8-854, 8-855, 8-857) or kidney transplantation (OPS: 5-555; EBM: 04561, 13601; ICD Z94.0). The temporal persistence of DNP and CKD was examined by considering different observation periods, and the internal validity was assessed using additional information from the data set for DNP, CKD, and RRT.In 2018, DNP was documented in 15.4% of individuals with diabetes (T1D: 18.3%; T2D: 15.2%), and CKD in 21.8% (T1D: 14.4%, T2D: 22.2%). Considering an observation period of five years (2014-2018), the prevalence estimates increased by 22 and 23%, respectively. RRT was documented in 7.5 per 1,000 individuals with diabetes. Internal validity assessment showed that 96.6% of DNP cases, 93.5% of CKD cases, and all RRT cases met at least one validation criterion.With high internal validity, and prevalence estimate consistent across age groups, the case definition of CKD can be considered suitable for use in surveillance. However, we assume that prevalence is underestimated when considering a 1-year period. For the depiction of RRT (kidney transplantation or long-term dialysis) via routine data, documentation of services must be employed.

In contrast to statutory health insurance (SHI) data, private health insurance (PHI) billing data have scarcely been used for scientific purposes in health and healthcare-related research and epidemiology. To date, findings can be obtained for 87.3% of people with health insurance in Germany based on analyses of SHI data. Often, however, only parts of the entire range of services covered by the SHI are depicted on a project-specific basis, depending on the data provided by the various cooperating health insurance funds. This means that statements can be made about the vast majority of the insured population. Nevertheless, a substantial proportion of the insured population is missing, meaning that no general validity for the entire population has been achieved to date. In addition to the 10% of people with comprehensive PHI, it has not been possible with the previous study focus on SHI data to conduct empirical research on the approximately 29 million people who have statutory health insurance and supplementary private insurance. This gap can be closed by supplementing the data on those with SHI with data on those with PHI. Accordingly, the research data center (FDZ) for health is planning to include private health insurance billing data. Yet there is a number of differences between SHI and PHI data, especially regarding the outpatient physician data, knowledge of which is a prerequisite for the proper analysis and interpretation of PHI data. This first article in a three-part series on the scientific use of PHI data on outpatient care and pharmaceutical prescriptions provides a systematic overview of the methodologically and analytically relevant similarities and differences between the two insurance systems based knowledge gained to date. In addition, the most important terms for the PHI sector are listed in the form of a glossary and the administrative and pragmatic requirements for the scientific use of PHI data are explained.

A dataset can be called "anonymous" only if its content cannot be related to a person, not by any means and not even ex post or by combination with other information. Free text entries highly impede "factual anonymization" for secondary research. Using two source datasets from GPs' electronic medical records (EMR), we aimed at de-identification in an iterative and systematic search for potentially identifying field content (PIF).EMR data of 14,285 to 100 GP patients with 40 variables (parameters, fields) in 5,918,321 resp. 363,084 data lines were analyzed at four levels: field labels, their combination, field content, dataset as a whole. Field labels were arranged into eleven semantic groups according to field type, their frequencies examined and their combination evaluated by GP experts rating the re-identification risk. Iteratively we searched for free text PIFs and masked them for the subsequent steps. The ratio of PIF data lines' number over total number yielded final probability estimators. In addition, we processed a whole dataset using ARX open source software for anonymizing sensitive personal data. Results were evaluated in a data protection impact assessment according to article 35 GDPR, with respect to the severity of privacy breach and to its estimated probability.We found a high risk of re-identification with free text entries into "history", "current diagnosis", "medication" and "findings" even after repeated algorithmic text-mining and natural language processing. Scrupulous pre-selection of variables, data parsimony, privacy by design in data processing and measures described here may reduce the risk considerably, but will not result in a "factually anonymized" research dataset.To identify and assess re-identifying field content is mandatory for privacy protection but anonymization can be reached only partly by reasonable efforts. Semantic structuring of data is pre-conditional but does not help with erroneous entries.

Scientific research with claims data provided by private health insurance companies (PHI companies) requires a basic understanding of the regulatory processes of the utilisation of health-related services by persons with private health insurance, the submission of invoices for healthcare services rendered/prescriptions redeemed to a PHI company, their billing and storage of data. Previous research projects have shown that, with knowledge of the special features of data from PHI companies, these can be used in projects involving claims data in a similar way to data from statutory health insurers. This second part of the series of articles on the scientific utilisation of private health insurance claims data focuses on the creation and flow of insured person and associated billing data in the private health insurance system for the sector of outpatient medical care, including medication. Using an exemplary data flow model for the sectors mentioned, processes and special features in the private health insurance system are systematically illustrated. Taking into account the process-related particularities of data generation and the associated content-related consequences, this article is intended to provide a basic understanding of these data. The information gathered can help decision-makers when planning a study with PHI data. The description of the data flow should support data analysts to consider the administrative and data content challenges in data preparation and evaluation. It is also essential for data analysts to be familiar with the data flow as well as with certain administrative and data content-related challenges. The evaluation of data availability and quality is necessary on an individual basis for each PHI company due to the divergent IT infrastructures and insurance rates. Future research projects with health-related claims data from individual or several PHI companies will expand expertise and empirical knowledge. The use of linkage methods is of particular importance here. The additional use of primary or survey data from privately insured persons will allow the realisation of validation studies that are designed, for instance, to examine the plausibility of recorded diagnoses. The increasing digitalisation of the healthcare system, for example through electronic invoicing and electronic prescriptions, can contribute to improving data content and availability in the future.

Dental child health records have an informal character and act as a reminder of early dental visits (FU1a-c, FUPr, FLA). Long-term prevention should take place from newborns to the age of 6. However, each chamber area (n=17) has its own dental child health record (n=14). The evaluation of the formalities and the content was the aim of this study.Fourteen dental child health records were evaluated by 12 dentists with different specializations (2 each in pediatric dentistry, periodontics, prosthetics, tooth preservation, orthodontics, no specialization) from July 1st, 2023 - November 30th, 2023. The dentists used a catalogue of criteria with 81 items. The validated criteria catalogue consisted of questions about quality (Witten List, DISCERN, Hamburg Model of Comprehensibility) and other relevant topics. A descriptive analysis and statistical evaluations (Kruskal-Wallis test, asymptomatic significance test), a correlation analysis of the quality of patient information (Spearman correlation), a binary logistic regression analysis of the variables specialization of the examiner (in pediatric dentistry/not in pediatric dentistry), gender (female/male), professional experience (≤7 years/>7 years) and chamber area (eastern/western chamber areas) were carried out.The dental child health record from Bremen/Schleswig-Holstein (identical) was rated best in terms of content median (25%/75% percentile): 100.50(100.00/101.75), the dental child health record of Brandenburg was rated the worst 69, 00(66.50/73.00); p>1.00). There was good correlation between DISCERN and the Hamburg Model of Comprehensibility (ρ=0.565 (p<0.001)). According to the regression analysis, only the chamber area showed a significant influence on the content (p<0.001).There was a strong discrepancy in the quality and quantity of the dental child health records. It is important to strive towards a standardized form and congruence in content similar to that which already exists for the children's medical examination booklets.

Physicians in primary care practices encounter social problems among their patients on a daily basis. Physicians can refer these patients to social services to improve their health and reduce pressure on the health care system. Open questions remain about how these referral practices are carried out and what areas have potential for improvement.An online survey with 21 closed or open-ended questions was conducted among primary care physicians (general practitioners and paediatricians) in Bremen, Germany. Data from closed questions were analysed for frequency distributions, while responses to open-ended questions were coded and interpreted using qualitative content analysis.Out of 580 primary care physicians in Bremen, 45 (8%) participated in the survey. Most of the respondents considered it important to be able to refer patients to support services outside the medical care system. Physicians referred a median of 10% of patients for whom they identified a need for social support. The most common reasons for not referring patients included a lack of knowledge about available services or the absence of such services, as well as time constraints. A total of 33 physicians (73%) reported feeling highly burdened when unable to refer patients. Furthermore, 34 respondents (76%) anticipated that a central contact point for social issues would greatly improve their job satisfaction. More general practitioners than paediatricians considered support services related to finances, unemployment, and housing to be important, while paediatricians were more open to providing external social support services in their own practices or using a "Gesundheitskiosk" (health kiosk).This is the first study to compare general practitioners and paediatricians regarding social issues in patient care. Given the low response rate, the results should be interpreted with caution. Notably, physicians reported that they did not refer most patients with identified social needs and experienced this as a burden. The majority indicated that, if available, they would use various forms of collaboration with social services.