Wolfgang Himmel

BACKGROUND The inter-contact interval (ICI), defined as the number of days between consecutive practice contacts, measures individual patient contact behavior but requires further validation as a useful tool for primary care research. OBJECTIVE This study applies the ICI to different electronic datasets from primary care practices to characterize individual patients’ contact patterns over time. The ICI and electronic “big data” are then used to develop and refine measures that may signal increased contact frequency and help identify acute care needs. METHODS This retrospective longitudinal observational study used electronic medical records (EMRs) from German primary care practices for a secondary data analysis, comprising (1) all patients from 155 primary care practices over 14 years, (2) all patients from one practice over 24 years, and (3) 100 patients receiving oral anticoagulation from seven practices over 7 years. ICI distributions were summarized using means, standard deviations, medians, 25th and 75th percentiles, interquartile ranges, and boxplots for a random sample. Ordinal time series analysis was used to identify increased practice contact frequency and ICI minima that best reflected a potential new need for acute care and patterns of contact behavior. RESULTS Among 333,610 patients with ≥2 practice contacts, 7,044,653 ICIs were identified across the three datasets. Patients had practice contacts, on average, every 38, 53, and 15 days, respectively. Nearly half of the patients had at least one contact at a 1-day interval every 3 months. ICI frequency distributions consistently showed peaks at 7 days and their multiples and at 90–93 days. Substantial variation in ICI distributions was observed within individual patients, between patients, between practices, and across datasets. Time series analyses and further refinements suggested defining a short ICI minimum as a contact with an ICI shorter than those of its direct neighbors and <8 days, potentially indicating acute care needs. Low ICI values, indicating frequent contacts, were not randomly distributed; instead, they frequently formed clusters (“islands”) of acute care within longer periods of chronic care. Patients could be divided into three groups: patients with a nearly constant consultation rhythm and no urgent practice visit; patients with 1 or more periods of intensified contact, suggesting acute care needs; and patients with frequent short-interval practice contacts. CONCLUSIONS While a high number of contacts is a simple indicator of potentially intensified acute care needs, refined measures, such as ICI minima provide a more stringent indication of care intensity and the severity of acute care needs. Ordinal time series analysis and graphical ICI analysis can identify “islands” of frequent attendance and distinguish acute care episodes from the surrounding chronic care trajectory, demonstrating the usefulness of the ICI as a tool for longitudinal analyses of real-world primary care data. CLINICALTRIAL n.a.

ZUSAMMENFASSUNG: Fragestellung Die Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS) ist eine der häufigsten psychischen Störungen bei Kindern, mit zunehmender Bedeutung auch bei Erwachsenen. Es sollte untersucht werden, welche Bedeutung Neurologen und Psychiater bzw. Hausärzte sowie Kinder- und Jugendärzte bei der Verordnung von ADHS-Medikamenten in Deutschland spielen und ob sich ihre Bedeutung im 10-Jahres-Zeitraum von 2008 und 2018 verändert hat. Methode In dieser Sekundäranalyse von anonymisierten Verordnungsdaten berechneten wir die absoluten und relativen Häufigkeiten der ADHS-Verordnungen von Neurologen und Psychiatern – zusammengefasst als Spezialisten – und Hausärzte sowie Kinder- und Jugendärzte – zusammengefasst als Generalisten – zwischen 2008 und 2018. Ergebnisse Insgesamt 620 Praxen lieferten Daten für 77 504 Patienten mit der Diagnose ADHS, 38% (29 396/77 504) von ihnen hatten im Studienzeitraum mindestens einmal ein Rezept für ein ADHS-Medikament erhalten. Im Laufe der Zeit beobachteten wir eine Verlagerung von Generalisten zu Spezialisten. Erhielten im Jahr 2008 noch 59% der Patientinnen und Patienten ihre Verordnung von einem Generalisten und 41% von einem Spezialisten, so drehte sich das Verhältnis im Jahr 2018 ins Gegenteil: nur noch 37% erhielten ihr Medikament von einem Generalisten und die überwiegende Mehrheit (63%) von einem Spezialisten. Besonders deutlich war diese Entwicklung bei Erwachsenen: 58% von ihnen erhielten ihr ADHS-Medikament im Jahr 2008 von einem Spezialisten, im Jahr 2018 waren es bereits 80%. Der Anteil bei Kindern- und Jugendlichen mit Verordnung vom Spezialisten stieg im gleichen Zeitraum von 38% auf 51%. Schlussfolgerung Es gibt eine Verschiebung in der Arzneimittelversorgung weg von Generalisten hin zu Spezialisten, ohne dass bisher über Vor- oder Nachteile diskutiert wurde. Dies wäre jedoch wünschenswert, nicht zuletzt, weil Spezialisten allein möglicherweise nicht über genügend Ressourcen verfügen, um alle ADHS-Patienten zu versorgen.

Purpose: To analyse (1) how often patients insured under the statutory health insurance (SHI) scheme received repeated prescriptions for benzodiazepines or Z‐drugs as private prescriptions and (2) how often doctors switched from SHI prescriptions to private prescriptions and vice versa when issuing repeat prescriptions.Methods: On basis of anonymized prescriptions from 874 ambulatory practices in Germany, we analysed the percentage of private prescriptions for Z‐drugs, benzodiazepines/anxiolytics, and benzodiazepines/hypnotics and sedatives over 6 years (2014 to 2020).Results: Of 2 200 446 prescriptions for a benzodiazepine or Z‐drug, 38% were private prescriptions. In case of Z‐drugs, the rate of private prescriptions was 44.1% for single prescriptions and 48.9% for refills. The difference was smaller for anxiolytics (23.3% vs. 26.0%) and, for benzodiazepine/hypnotics and sedatives, the proportion of private prescriptions for refills was even lower than for single prescriptions. In case of Z‐drugs, the proportion of private prescriptions was, on average, 42.7% for the first prescription of a series of repeat prescriptions and 49.6% for the tenth prescription. The increase was smaller for anxiolytics and negligible for benzodiazepine/hypnotics and sedatives. Doctors stayed with their initial decision in more than three quarters of repeat prescriptions, be it a SHI or private prescription.Conclusion: While we observed a large number of private prescriptions for benzodiazepines and Z‐drugs, the proportion was only slightly higher for refills than for single prescriptions. Doctors do not seem to issue private prescriptions as a strategy to mask especially long‐term use of these substances.

Objectives Many patients receive benzodiazepines or Z-drugs during hospitalisation due to sleeping problems. In a pilot study, we aimed to find out whether, and to what degree, a multi-faceted intervention can reduce the use of these drugs, especially in older patients and those without a psychiatric or neurological disorder. The results of this pilot study should inform the design of a randomised controlled trial (RCT). Methods In a quasi-experimental design, we implemented the intervention in a German hospital with the support of the hospital director, medical and nursing staff and employee representatives. We compared prescription data for sleep-inducing drugs before and after the intervention by Fisher’s exact test and used odds ratios (ORs) with their 95% CIs as a measure of effect size. Results The data from 960 patients aged ≥65 years before intervention and 1049 patients after intervention were analysed. Before intervention, 483 (50.3%) of the patients received sleep-inducing drugs at some time during their hospital stay. After the intervention, 381 (36.3%) patients received a sleep-inducing drug, resulting in an OR of 0.56 (95% CI 0.47 to 0.68) (pConclusions A multi-faceted intervention to change the practice of the use of sleep-inducing drugs in one hospital was successful in terms of drug reduction, particularly for benzodiazepines. The intervention was effective especially for target persons—that is, those without a psychiatric or neurological disease. Awareness of the magnitude of the change and the role of important stakeholders could help researchers and hospital staff to design a large RCT, including control hospitals, to evaluate the success of a multi-faceted intervention on a scientifically sound basis.

Background: PCR testing is considered the gold standard for SARS-CoV-2 diagnosis but its results are earliest available hours to days after testing. Rapid antigen tests represent a diagnostic tool enabling testing at the point of care. Rapid antigen tests have mostly been validated by the manufacturer or in controlled laboratory settings only. External validation at the point of care, particularly in general practice where the test is frequently used, is needed. Furthermore, it is unclear how well point of care tests are accepted by the practice staff. Methods: In this prospective multicenter validation study in primary care, general practitioners included adult individuals presenting with symptoms suggesting COVID-19. Each patient was tested by the general practitioner, first with a nasopharyngeal swab for the point of care test (Roche SARS-CoV-2 Rapid Antigen Test) and then with a second swab for PCR testing. Using the RT-PCR result as a reference, we calculated specificity, sensitivity, positive predictive value and negative predictive value, with their 95% confidence intervals. General practitioners and medical assistants completed a survey to assess feasibility and usefulness of the point of care tests. Results: In 40 practices in Würzburg, Germany, 1518 patients were recruited between 12/2020 and 06/2021. The point of care test achieved a sensitivity of 78.3% and a specificity of 99.5% compared to RT-PCR. With a prevalence of 9.5%, the positive predictive value was 93.9% and the negative predictive value was 97.8%. General practitioners rated the point of care test as a helpful tool to support diagnostics in patients with signs and symptoms suggestive for infection, particularly in situations where decision on further care is needed at short notice. Conclusion: The point of care test used in this study showed a sensitivity below the manufacturer’s specification (Sensitivity 96.25%) in the practice but high values for specificity and high positive predictive value and negative predictive value. Although widely accepted in the practice, measures for further patient management require a sensitive interpretation of the point of care test results.

Background: Multimorbidity is common among general practice patients and increases a general practitioner’s (GP’s) workload. But the extent of multimorbidity may depend on its definition and whether a time delimiter is included in the definition or not.Aims: The aims of the study were (1) to compare practice prevalence rates yielded by different models of multimorbidity, (2) to determine how a time delimiter influences the prevalence rates and (3) to assess the effects of multimorbidity on the number of direct and indirect patient contacts as an indicator of doctors’ workload.Methods: This retrospective observational study used electronic medical records from 142 German general practices, covering 13 years from 1994 to 2007. The four models of multimorbidity ranged from a simple definition, requiring only two diseases, to an advanced definition requiring at least three chronic conditions. We also included a time delimiter for the definition of multimorbidity. Descriptive statistics, such as means and correlation coefficients, were applied.Findings: The annual percentage of multimorbid primary care patients ranged between 84% (simple model) and 16% (advanced model) and between 74% and 13% if a time delimiter was included. Multimorbid patients had about twice as many contacts annually than the remainder. The number of contacts were different for each model, but the ratio remained similar. The number of contacts correlated moderately with patient age (r = 0.35). The correlation between age and multimorbidity increased from model to model up to 0.28 while the correlations between contacts and multimorbidity varied around 0.2 in all four models.Conclusion: Multimorbidity seems to be less prevalent in primary care practices than usually estimated if advanced definitions of multimorbidity and a temporal delimiter are applied. Although multimorbidity increases in any model a doctor’s workload, it is especially the older person with multiple chronic diseases who is a challenge for the GP.