Niederschwelliges Screening versus multidimensionales Assessment von Symptomen und psychosozialen Belastungen bei Krebspatienten ab dem Zeitpunkt der Inkurabilität (SCREBEL)

Alt-Epping, Bernd; Solar, Stefanie; Lordick, Florian; Mehnert‐Theuerkauf, Anja; Oorschot, B. van; Thomas, Michael; Asendorf, Thomas

doi:10.1007/s12312-020-00769-0

Cited by 4 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, it is being investigated whether patients should be better identified with low-threshold screening or multidimensional symptom assessment. 32 Basch et al 33 showed that patients receiving routine symptom assessment have a significantly longer survival than patients without. Whether these data are transferable to palliative care patients should be of interest in further research.…”

Section: Discussionmentioning

confidence: 99%

Screening for Palliative Care Needs: Pilot Data From German Comprehensive Cancer Centers

Roch

Heckel

Oorschot

et al. 2021

JCO Oncology Practice

View full text Add to dashboard Cite

PURPOSE: Guidelines recommend several screening tools to identify patients with complex palliative needs. This diversity and lack of structural recommendations offer a wide scope for implementing screening. Against this background, the current status of implementation at German Comprehensive Cancer Centers (CCCs) funded by the German Cancer Aid has not yet been investigated. METHODS: e-mail survey of the 17 hospital sites of the 13 CCCs. The questionnaire asked for structural characteristics of the centers as well as preconditions of the screening process. Structurally established screening procedures (one item) and standardized workflows, modes of performance, screening tools (four items), modes of training how to screen, and responsibilities (two items) were assessed. RESULTS: In a 2-month period, 15 hospital sites responded; seven hospital sites conducted a palliative care needs (PCN) screening. Only one hospital site carried out PCN screening in almost all oncology departments, but only with the distress thermometer. Other hospital sites determined palliative needs by assessing physical symptoms using the Integrated Palliative Care Outcome Scale or the Minimal Documentation System, and two hospital sites combined tools to determine both physical and psychological stress. The type of screening varied from paper-pencil–based to tablet computer–based documentation. The main barriers to implementation were identified as a lack of human resources and a lack of structural conditions. CONCLUSION: There is a lack of consensus among palliative care specialists and oncologists in the CCCs supported by the German Cancer Aid in PCN screening as well as of structured guidelines and the professional association. Structural requirements should be adapted to these needs, which include both technical and human resources. A combined psycho-oncologic and palliative care screening might help to formulate best practice recommendations.

show abstract

Section: Discussionmentioning

confidence: 99%

Screening for Palliative Care Needs: Pilot Data From German Comprehensive Cancer Centers

Roch

Heckel

Oorschot

et al. 2021

JCO Oncology Practice

View full text Add to dashboard Cite

show abstract

“…An integration of the outcome from such PROMs into AI-based Clinical Decision Supports Systems (CDSS) may provide a significant contribution towards the identification of PC needs, as was recently indicated by Sandham et al [ 16 ]. To date, numerous studies have been conducted to test screening tools that combine prognostic criteria (e.g., diagnosis, functional status, complications, comorbidities) with symptoms and needs (symptom management, distress, and support of family) [ 17 , 18 , 19 , 20 ]. Study results show limitations in the feasibility of the tools due to time-consuming questionnaires [ 20 ].…”

Section: Introduction and Definition Of Palliative Carementioning

confidence: 99%

“…Study results show limitations in the feasibility of the tools due to time-consuming questionnaires [ 20 ]. Currently, the German SCREBEL trial compares a simple screening with a symptom assessment tool (IPOS and DT) to a more detailed assessment [ 17 ]. The era of electronic health records may facilitate referrals by providing electronic alerts, pre-populated note templates, and order sets [ 21 ].…”

Section: Introduction and Definition Of Palliative Carementioning

confidence: 99%

Contribution of Synthetic Data Generation towards an Improved Patient Stratification in Palliative Care

Hahn

Schütte

Schultz

et al. 2022

JPM

View full text Add to dashboard Cite

AI model development for synthetic data generation to improve Machine Learning (ML) methodologies is an integral part of research in Computer Science and is currently being transferred to related medical fields, such as Systems Medicine and Medical Informatics. In general, the idea of personalized decision-making support based on patient data has driven the motivation of researchers in the medical domain for more than a decade, but the overall sparsity and scarcity of data are still major limitations. This is in contrast to currently applied technology that allows us to generate and analyze patient data in diverse forms, such as tabular data on health records, medical images, genomics data, or even audio and video. One solution arising to overcome these data limitations in relation to medical records is the synthetic generation of tabular data based on real world data. Consequently, ML-assisted decision-support can be interpreted more conveniently, using more relevant patient data at hand. At a methodological level, several state-of-the-art ML algorithms generate and derive decisions from such data. However, there remain key issues that hinder a broad practical implementation in real-life clinical settings. In this review, we will give for the first time insights towards current perspectives and potential impacts of using synthetic data generation in palliative care screening because it is a challenging prime example of highly individualized, sparsely available patient information. Taken together, the reader will obtain initial starting points and suitable solutions relevant for generating and using synthetic data for ML-based screenings in palliative care and beyond.

show abstract

Von der „frühen“ zur „zeitgerechten“ Integration der Palliativversorgung in die Behandlung onkologischer Patient:innen

et al. 2022

View full text Add to dashboard Cite

Niederschwelliges Screening versus multidimensionales Assessment von Symptomen und psychosozialen Belastungen bei Krebspatienten ab dem Zeitpunkt der Inkurabilität (SCREBEL)

Cited by 4 publications

References 0 publications

Screening for Palliative Care Needs: Pilot Data From German Comprehensive Cancer Centers

Screening for Palliative Care Needs: Pilot Data From German Comprehensive Cancer Centers

Contribution of Synthetic Data Generation towards an Improved Patient Stratification in Palliative Care

Von der „frühen“ zur „zeitgerechten“ Integration der Palliativversorgung in die Behandlung onkologischer Patient:innen

Contact Info

Product

Resources

About