scholarly journals Reimbursement Decisions for Medical Services in Austria: An Analysis of Influencing Factors for the Hospital Individual Services Catalogue Between 2008 and 2020

2021 ◽  
Author(s):  
Gregor Goetz ◽  
Dimitra Panteli ◽  
Reinhard Busse ◽  
Claudia Wild
Keyword(s):  
Decision Making ◽  
Quality Assurance ◽  
Clinical Evidence ◽  
Reimbursement Decision ◽  
Medical Services ◽  
Structural Quality ◽  
Decision Making Process ◽  
Evidence Based ◽  
Clinical Benefits ◽  
Individual Service

Abstract ObjectivesTo (1) describe the (evidence-based) reimbursement process of hospital individual services, (2) evaluate the accordance between evidence-based recommendations and reimbursement decision of individual services and (3) elaborate potential aspects that play a role in the decision-making process in Austria.Method:The reimbursement process is described based on selected relevant sources such as official documents. Evidence-based recommendations and subsequent reimbursement decisions for the annual maintenance of the hospital individual service catalogue in Austria between 2008 and 2020 were analysed using a mixed methods approach, encompassing descriptive statistics and a focus group with Austrian decision makers. Results:118 evidence-based recommendations were analysed. There were 93 (78.8%) negative and 25 (21.2%) positive evidence-based recommendations. In total, 107 out of 118 evidence-based recommendations (90.1%) did not lead to a deviating reimbursement decision. We identified six aspects that may have played a role in the decision-making process for the annual maintenance of the hospital individual service catalogue, with clinical evidence being the most notable. Further aspects included quality assurance/organisational aspects (i.e., structural quality assurance), costs (if comparable to already existing medical services, not: cost-effectiveness), procedural aspects (e.g., if certain criteria for adoption have not been met formally through the proposals), “other countries” (i.e., taking into account how other countries decided) and situational aspects (such as the COVID-19 pandemic).Conclusions:There is good accordance between evidence-based recommendations and reimbursement decisions regarding hospital individual services in Austria. Beyond clinical evidence, organizational aspects seem to be considered often with regard to quality assurance but costs do not appear to play a major role. The Austrian system has mechanisms in place that can restrict widespread adoption of novel hospital individual services with uncertain clinical benefits. Future studies could investigate how well these mechanisms work and how they compare to other health systems in Europe.

Improving the evidence-based clinical decision-making process: Interactive classification and topic discovery on diabetes-related biomedical literature (Preprint)

2021 ◽  
Author(s):  
Adrian Ahne ◽  
Guy Fagherazzi ◽  
Xavier Tannier ◽  
Thomas Czernichow ◽  
Francisco Orchard
Keyword(s):  
Decision Making ◽  
Active Learning ◽  
Hierarchical Clustering ◽  
Domain Knowledge ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Biomedical Literature ◽  
Decision Making Process ◽  
Evidence Based ◽  
Text Data

BACKGROUND The amount of available textual health data such as scientific and biomedical literature is constantly growing and it becomes more and more challenging for health professionals to properly summarise those data and in consequence to practice evidence-based clinical decision making. Moreover, the exploration of large unstructured health text data is very challenging for non experts due to limited time, resources and skills. Current tools to explore text data lack ease of use, need high computation efforts and have difficulties to incorporate domain knowledge and focus on topics of interest. OBJECTIVE We developed a methodology which is able to explore and target topics of interest via an interactive user interface for experts and non-experts. We aim to reach near state of the art performance, while reducing memory consumption, increasing scalability and minimizing user interaction effort to improve the clinical decision making process. The performance is evaluated on diabetes-related abstracts from Pubmed. METHODS The methodology consists of four parts: 1) A novel interpretable hierarchical clustering of documents where each node is defined by headwords (describe documents in this node the most); 2) An efficient classification system to target topics; 3) Minimized users interaction effort through active learning; 4) A visual user interface through which a user interacts. We evaluated our approach on 50,911 diabetes-related abstracts from Pubmed which provide a hierarchical Medical Subject Headings (MeSH) structure, a unique identifier for a topic. Hierarchical clustering performance was compared against the implementation in the machine learning library scikit-learn. On a subset of 2000 randomly chosen diabetes abstracts, our active learning strategy was compared against three other strategies: random selection of training instances, uncertainty sampling which chooses instances the model is most uncertain about and an expected gradient length strategy based on convolutional neural networks (CNN). RESULTS For the hierarchical clustering performance, we achieved a F1-Score of 0.73 compared to scikit-learn’s of 0.76. Concerning active learning performance, after 200 chosen training samples based on these strategies, the weighted F1-Score over all MeSH codes resulted in satisfying 0.62 F1-Score of our approach, compared to 0.61 of the uncertainty strategy, 0.61 the CNN and 0.45 the random strategy. Moreover, our methodology showed a constant low memory use with increased number of documents but increased execution time. CONCLUSIONS We proposed an easy to use tool for experts and non-experts being able to combine domain knowledge with topic exploration and target specific topics of interest while improving transparency. Furthermore our approach is very memory efficient and highly parallelizable making it interesting for large Big Data sets. This approach can be used by health professionals to rapidly get deep insights into biomedical literature to ultimately improve the evidence-based clinical decision making process.

Facilitating Lifestyle Choice and Change

2014 ◽  
pp. 137-147
Author(s):  
Judith Aufenthie
Keyword(s):  
Decision Making ◽  
Well Being ◽  
Decision Making Process ◽  
Evidence Based ◽  
Lifestyle Choice ◽  
Complex Process

Creating optimal well being is a multifaceted, complex process. It involves many biological, psychological, physical, behavioral, emotional as well as neurobiological factors which all interact and effect the choices we make and changes that we are able to implement. Research has begun to connect with the decision making process to better understand how our decisions and choices are made. This research coupled with research and evidence based models provides integrative nurses and patients with validated tools to optimize change and wellness.

Evidence-Based Decision Making in Action: Part 2 – Evaluating and Applying the Clinical Evidence

2003 ◽  
Vol 4 (1) ◽  
pp. 42-52 ◽  
Author(s):  
Jane L. Forrest ◽  
Syrene A. Miller
Keyword(s):  
Decision Making ◽  
Critical Appraisal ◽  
Clinical Evidence ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Based ◽  
Online Search ◽  
Case Scenario ◽  
The Third ◽  
Evidence Based Decision Making

Abstract This is the second of a two-part series addressing the use of evidence-based decision making (EBDM) in the use of home bleaching. In Part 1, a case scenario demonstrated the skills involved in (1) structuring a clinical question and (2) conducting an online search using PubMed.1 Part 2 demonstrates the third and fourth steps in the EBDM process, i.e., (3) critical appraisal to assess the validity of a study and (4) applying that information to clinical decision making. This 4-step approach to EBDM recognizes that clinicians can never be completely current with all conditions, medications, materials, and products. Thus, EBDM provides a mechanism for addressing these gaps in knowledge in order to provide the best care possible. Citation Forrest JL, Miller SA. Evidence-Based Decision Making in Action: Part 2 – Evaluating and Applying the Clinical Evidence. J Contemp Dent Pract 2003 February;(4)1:042-052.

scholarly journals Contemporary evidence-based practice in Canadian emergency medical services: a vision for integrating evidence into clinical and policy decision-making

CJEM ◽  
2016 ◽  
Vol 19 (3) ◽  
pp. 220-229
Author(s):  
Jan L. Jensen ◽  
Andrew H. Travers
Keyword(s):  
Decision Making ◽  
Emergency Medical Services ◽  
Evidence Based Practice ◽  
Systems Of Care ◽  
National Level ◽  
Policy Decision ◽  
Medical Services ◽  
Evidence Based ◽  
Emergency Medical ◽  
Patient Health

AbstractNationally, emphasis on the importance of evidence-based practice (EBP) in emergency medicine and emergency medical services (EMS) has continuously increased. However, meaningful incorporation of effective and sustainable EBP into clinical and administrative decision-making remains a challenge. We propose a vision for EBP in EMS: Canadian EMS clinicians and leaders will understand and use the best available evidence for clinical and administrative decision-making, to improve patient health outcomes, the capability and quality of EMS systems of care, and safety of patients and EMS professionals. This vision can be implemented with the use of a structure, process, system, and outcome taxonomy to identify current barriers to true EBP, to recognize the opportunities that exist, and propose corresponding recommended strategies for local EMS agencies and at the national level. Framing local and national discussions with this approach will be useful for developing a cohesive and collaborative Canadian EBP strategy.

PRE-COVERAGE ASSESSMENTS OF NEW HOSPITAL INTERVENTIONS ON AUSTRIA: METHODOLOGY AND 3 YEARS OF EXPERIENCE

2012 ◽  
Vol 28 (2) ◽  
pp. 171-179 ◽  
Author(s):  
Philipp Mad ◽  
Sabine Geiger-Gritsch ◽  
Gerda Hinterreiter ◽  
Stefan Mathis-Edenhofer ◽  
Claudia Wild
Keyword(s):  
Decision Making ◽  
New Technologies ◽  
Decision Makers ◽  
Medical Services ◽  
Decision Making Process ◽  
Relevant Evidence ◽  
Objective Evidence ◽  
The Status ◽  
Set Up ◽  
Grade Methodology

Objectives: A new decision-making process was set up by the Austrian Ministry of Health to regulate coverage of new proposed Extra Medical Services (EMS; German: Medizinische Einzel-Leistung [MEL]) in 2008. As part of the annual decision-making process an independent academic institution (LBI-HTA) is evaluating relevant evidence on these new technologies and provides HTAs, including evidence-based recommendations for decision makers.Methods: About ten EMS assessments are performed annually by the LBI-HTA simultaneously between January and March. Each peer-reviewed report consists of a systematic literature review and critical appraisal of evidence using the GRADE methodology. The generation of numerous reports of good quality standards within the short timeframe is achieved by a standardized workflow with predefined assignment of tasks for all participants.Results: In total, the LBI-HTA performed twenty-five EMS assessments on thirty-three different interventions in the last three years. Coverage was recommended with limitation for eleven (33%) interventions, and not recommended for twenty-two (66%) interventions. The federal health commission decided on acceptance or preliminary acceptance of coverage in seven (22%) cases, rejection in eighteen (55%) cases and changed the status to “subject to approval” in seven (24%) cases.Conclusions: Pre-coverage assessment of new hospital interventions was implemented successfully in Austria. It has proved to be a useful tool to support decision makers with objective evidence when deciding whether or not to reimburse medical services.

scholarly journals Vaccine hesitancy: evidence from an adverse events following immunization database, and the role of cognitive biases

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hossein Azarpanah ◽  
Mohsen Farhadloo ◽  
Rustam Vahidov ◽  
Louise Pilote
Keyword(s):  
Decision Making ◽  
Adverse Events ◽  
Cognitive Biases ◽  
Vaccine Safety ◽  
Vaccine Hesitancy ◽  
Decision Making Process ◽  
Evidence Based ◽  
Vaccine Acceptance ◽  
Vaccination Decision ◽  
Vaccine Information

Abstract Background Vaccine hesitancy has been a growing challenge for public health in recent decades. Among factors contributing to vaccine hesitancy, concerns regarding vaccine safety and Adverse Events (AEs) play the leading role. Moreover, cognitive biases are critical in connecting such concerns to vaccine hesitancy behaviors, but their role has not been comprehensively studied. In this study, our first objective is to address concerns regarding vaccine AEs to increase vaccine acceptance. Our second objective is to identify the potential cognitive biases connecting vaccine hesitancy concerns to vaccine-hesitant behaviors and identify the mechanism they get triggered in the vaccine decision-making process. Methods First, to mitigate concerns regarding AEs, we quantitatively analyzed the U.S. Vaccine Adverse Event Reporting System (VAERS) from 2011 to 2018 and provided evidence regarding the non-severity of the AEs that can be used as a communicable summary to increase vaccine acceptance. Second, we focused on the vaccination decision-making process. We reviewed cognitive biases and vaccine hesitancy literature to identify the most potential cognitive biases that affect vaccine hesitancy and categorized them adopting the Precaution Adoption Process Model (PAPM). Results Our results show that the top frequent AEs are expected mild reactions like injection site erythema (4.29%), pyrexia (3.66%), and injection site swelling (3.21%). 94.5% of the reports are not serious and the average population-based serious reporting rate over the 8 years was 25.3 reports per 1 million population. We also identified 15 potential cognitive biases that might affect people’s vaccination decision-making and nudge them toward vaccine hesitancy. We categorized these biases based on the factors that trigger them and discussed how they contribute to vaccine hesitancy. Conclusions This paper provided an evidence-based communicable summary of VAERS. As the most trusted sources of vaccine information, health practitioners can use this summary to provide evidence-based vaccine information to vaccine decision-makers (patients/parents) and mitigate concerns over vaccine safety and AEs. In addition, we identified 15 potential cognitive biases that might affect the vaccination decision-making process and nudge people toward vaccine hesitancy. Any plan, intervention, and message to increase vaccination uptake should be modified to decrease the effect of these potential cognitive biases.

Training trainers in risk assessment

1997 ◽  
Vol 170 (S32) ◽  
pp. 35-36 ◽  
Author(s):  
Michael Harris
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Scientific Evidence ◽  
Rapid Assessment ◽  
The Other ◽  
Decision Making Process ◽  
Evidence Based ◽  
Apprenticeship Model ◽  
Based Medicine ◽  
Early Training

Risk assessment has always been an essential part of all medical practice, and doctors have always been trained to make rapid assessment of risk. Much of the early training of doctors in both medicine and surgery centres on risk assessment. However, the method of acquiring that knowledge is predominantly through the apprenticeship model with observation by the trainee of the trainer's decision-making process. Those decisions, however, are often skewed and biased by a whole variety of influences, rather than always being based on scientific evidence. Clearly the increasing influence of evidence-based medicine will help this. At one extreme, however, there are heroic surgeons taking unnecessary risk or taking on cases which might more appropriately have been left without treatment, and at the other extreme, consultants who may feel demoralised or depressed might well become nihilistic about medicine and therefore might not attempt to treat cases that are treatable.

The Effect of Previsit Education in Breast Cancer Patients: A Study of a Shared-decision-making Tool

2016 ◽  
Vol 82 (3) ◽  
pp. 259-265 ◽  
Author(s):  
Victoria Serpico ◽  
Amy E. Liepert ◽  
Kenneth Boucher ◽  
Diane L. Fouts ◽  
Layla Anderson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Shared Decision Making ◽  
Cancer Biology ◽  
Decision Making Process ◽  
Evidence Based ◽  
Shared Decision ◽  
Group 2 ◽  
New Diagnosis ◽  
Group 1

To enhance shared decision-making for patients with breast cancer, we developed an evidence-based educational breast cancer video (BCV) providing an overview of breast cancer biology, prognostic indicators, and surgical treatment options while introducing health care choice. By providing patients access to a BCV with information necessary to make informed surgical decisions before seeing a surgeon, we aimed to increase patient participation in the decision-making process, while decreasing distress. Patients with a new diagnosis of breast cancer were provided a link to the BCV. Group 1 participated in online pre- and postvideo questionnaires, with the BCV embedded in between. The questionnaires evaluated self-reported baseline knowledge of breast cancer and perceived distress related to the diagnosis. Changes in self-reported responses were analyzed using the Wilcoxon matched pairs test. Group 2 received a survey collecting demographics, decision-making information, and perceptions of the BCV at the time of clinic visit before meeting the surgeon. Group 1 included 69 subjects with 62 per cent reporting improved knowledge and 30 per cent reporting reduced distress in regard to their breast cancer diagnosis. Group 2 included 87 subjects; 94 to 98 per cent felt the BCV provided information and stimulated thoughts and questions to assist in breast cancer treatment decision-making. The BCV was positively received by participants and feasible to implement into clinical practice. Evidence-based media tools improve knowledge and reduce distress in patients with a new diagnosis of breast cancer as well as contributing to the shared decision-making process.

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