Globally, many patients with insulin-treated type-2 diabetes are suboptimally controlled. The PDM-ProValue study program evaluated whether integrated personalized diabetes management (iPDM) has the potential to improve clinical outcomes. 101 practices with 907 patients participated in the 12-month, prospective, controlled, cluster-randomized study program. HbA1c levels, therapy changes, frequency of hypoglycemic episodes, patient reported outcomes, and physician satisfaction were assessed. iPDM led to a greater reduction in HbA1c after 12 months vs. usual care (-0.5%, p < 0.0001 vs. -0.3%, p < 0.0001), (Diff. 0.2%, p = 0.0324). Most of the HbA1c reduction occurred after 3 months and remained stable thereafter. The percentage of patients with therapy adjustments was higher in the iPDM group at all visits (p < 0.01 at week 3, month 3, month 6). Patient adherence at month 12 was higher in the iPDM group compared to baseline (Odds ratio = 2.39; p = 0.0003); also, patient treatment satisfaction (DTSQc: 12.2 vs. 10.4, δ = 1.78, p = 0.004; DTSQs: 31.0 vs. 30.0, δ = 0.924, p = 0.02), and physician satisfaction was higher in the intervention group. iPDM improved the use of diagnostic data leading to better glycemic control, more timely treatment adjustments (indicating reduced clinical inertia), and increased patient adherence and treatment satisfaction among patients and physicians.

Objectives: Today, hospitals and other health care-related institutions are accumulating a growing bulk of real world clinical data. Such data offer new possibilities for the generation of disease models for the health economic evaluation. In this article, we propose a new approach to leverage cancer registry data for the development of Markov models. Records of breast cancer patients from a clinical cancer registry were used to construct a real world data driven disease model. Methods: We describe a model generation process which maps database structures to disease state definitions based on medical expert knowledge. Software was programmed in Java to automatically derive a model structure and transition probabilities. We illustrate our method with the reconstruction of a published breast cancer reference model derived primarily from clinical study data. In doing so, we exported longitudinal patient data from a clinical cancer registry covering eight years. The patient cohort (n = 892) comprised HER2-positive and HER2-negative women treated with or without Trastuzumab. Results: The models generated with this method for the respective patient cohorts were comparable to the reference model in their structure and treatment effects. However, our computed disease models reflect a more detailed picture of the transition probabilities, especially for disease free survival and recurrence. Conclusions: Our work presents an approach to extract Markov models semi-automatically using real world data from a clinical cancer registry. Health care decision makers may benefit from more realistic disease models to improve health care-related planning and actions based on their own data. (C) 2016 The Authors. Published by Elsevier Inc.

To date, more than 160 million people have been infected with COVID-19 worldwide. In the present study, we investigated the history of SARS-CoV-2 infection among 3067 healthcare workers (HCW) in a German COVID-19 treatment center during the early phase of the pandemic (July 2020) based on the seroprevalence of SARS-CoV-2 antibodies and self-reported previous PCR results. The results demonstrate a low prevalence of SARS-CoV-2 infection (n = 107 [3.5%]) with no increased risk for employees with a high level of patient exposure in general or working in COVID-19-confined areas in particular. This suggests that the local hygiene standards implemented in our hospital during the first wave of COVID-19 pandemic were effective in preventing patient-to-HCW transmission. No evidence for highly mobile staff serving as a vector for SARS-CoV-2 transmission could be found. In addition, impairment of smell and/or taste was strongly associated with SARS-CoV-2 history.

Background and Objectives: Tonsillar infections are a common reason to see a physician and lead to a reduction in the patients’ health-related quality of life (HRQoL). HRQoL may be an important criterion in decision science and should be taken into account when deciding when to perform tonsillectomy, especially for chronic tonsillitis. The aim of this study was to determine the health utility for different states of tonsillar infections. Materials and Methods: Hospitalized patients with acute tonsillitis or a peritonsillar abscess were asked about their HRQoL with the 15D questionnaire. Patients who had undergone tonsillectomy were reassessed six months postoperatively. Results: In total, 65 patients participated in the study. The health states of acute tonsillitis and peritonsillar abscess had both a utility of 0.72. Six months after tonsillectomy, the mean health utility was 0.95. Conclusions: Our study confirms a substantial reduction in utility due to tonsillar infections. Tonsillectomy significantly improves the utility and therefore HRQoL six months after surgery.

Introduction: Screening for colorectal cancer (CRC) is effective in reducing both incidence and mortality. Colonoscopy and stool tests are most frequently used for this purpose. Sigmoidoscopy is an alternative screening measure with a strong evidence base. Due to its distinct characteristics, it might be preferred by subgroups. The aim of this systematic review is to analyze the cost-effectiveness of sigmoidoscopy for CRC screening compared to other screening methods and to identify influencing parameters. Methods: A systematic literature search for the time frame 01/2010–01/2023 was conducted using the databases MEDLINE, Embase, EconLit, Web of Science, NHS EED, as well as the Cost-Effectiveness Registry. Full economic analyses examining sigmoidoscopy as a screening measure for the general population at average risk for CRC were included. Incremental cost-effectiveness ratios were calculated. All included studies were critically assessed based on a questionnaire for modelling studies. Results: Twenty-five studies are included in the review. Compared to no screening, sigmoidoscopy is a cost-effective screening strategy for CRC. When modelled as a single measure strategy, sigmoidoscopy is mostly dominated by colonoscopy or modern stool tests. When combined with annual stool testing, sigmoidoscopy in 5-year intervals is more effective and less costly than the respective strategies alone. The results of the studies are influenced by varying assumptions on adherence, costs, and test characteristics. Conclusion: The combination of sigmoidoscopy and stool testing represents a cost-effective screening strategy that has not received much attention in current guidelines. Further research is needed that goes beyond a narrow focus on screening technology and models different, preference-based participation behavior in subgroups.