Keyword search (4,164 papers available)

"coding" Keyword-tagged Publications:

Title Authors PubMed ID
1 A protocol for trustworthy EEG decoding with neural networks Borra D; Magosso E; Ravanelli M; 39549492
ENCS
2 Generalization limits of Graph Neural Networks in identity effects learning D' Inverno GA; Brugiapaglia S; Ravanelli M; 39426036
ENCS
3 SpeechBrain-MOABB: An open-source Python library for benchmarking deep neural networks applied to EEG signals Borra D; Paissan F; Ravanelli M; 39265481
ENCS
4 Cortical-subcortical interactions underlie processing of auditory predictions measured with 7T fMRI Ara A; Provias V; Sitek K; Coffey EBJ; Zatorre RJ; 39087881
PSYCHOLOGY
5 Transcoding of French numbers for first- and second-language learners in third grade Lafay A; Adrien E; Lonardo Burr SD; Douglas H; Provost-Larocque K; Xu C; LeFevre JA; Maloney EA; Osana HP; Skwarchuk SL; Wylie J; 37129448
EDUCATION
6 Context changes judgments of liking and predictability for melodies Albury AW; Bianco R; Gold BP; Penhune VB; 38034280
PSYCHOLOGY
7 Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; 37385392
IMAGING
8 Decoding of Envelope vs. Fundamental Frequency During Complex Auditory Stream Segregation Greenlaw KM; Puschmann S; Coffey EBJ; 37215227
PSYCHOLOGY
9 Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes MacKeigan PW; Garner RE; Monchamp MÈ; Walsh DA; Onana VE; Kraemer SA; Pick FR; Beisner BE; Agbeti MD; da Costa NB; Shapiro BJ; Gregory-Eaves I; 35287928
BIOLOGY
10 Energy migration control of multi-modal emissions in an Er3+ doped nanostructure toward information encryption and deep learning decoding Song Y; Lu M; Mandl GA; Xie Y; Sun G; Chen J; Liu X; Capobianco JA; Sun L; 34476872
ENCS
11 Coding Public Health Interventions for Health Technology Assessments: A Pilot Experience With WHO's International Classification of Health Interventions (ICHI) Wübbeler M; Geis S; Stojanovic J; Elliott L; Gutierrez-Ibarluzea I; Lenoir-Wijnkoop I; 34222165
HKAP

 

Title:Coding Public Health Interventions for Health Technology Assessments: A Pilot Experience With WHO's International Classification of Health Interventions (ICHI)
Authors:Wübbeler MGeis SStojanovic JElliott LGutierrez-Ibarluzea ILenoir-Wijnkoop I
Link:https://pubmed.ncbi.nlm.nih.gov/34222165/
DOI:10.3389/fpubh.2021.620637
Publication:Frontiers in public health
Keywords:Health Technology AssessmentInternational Classification of Health Interventionscodingfeasibility evaluationpublic health intervention
PMID:34222165 Category: Date Added:2021-07-05
Dept Affiliation: HKAP
1 Department of Nursing Science, University of Applied Sciences, Bochum, Germany.
2 Department of Health, Kinesiology, and Applied Physiology, Faculty of Arts and Science, Concordia University, Montreal, QC, Canada.
3 Montreal Behavioural Medicine Centre, CIUSSS du Nord-de-l'Ile-de-Montréal, Montréal, QC, Canada.
4 Centre for Guidelines, National Institute for Health and Care Excellence, Manchester, United Kingdom.
5 Basque Foundation for Health Innovation and Research (BIOEF), Barakaldo, Spain.
6 Basque Office for HTA (Osteba), Barakaldo, Spain.
7 Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, Netherlands.

Description:

Introduction: An important requirement for successful public health interventions is a standardized classification in order to make these health technologies comparable in all contexts and recognized by all parties. The WHO International Classification of Health Interventions (ICHI), including an integrated public health component, has been developed to propose such an international standard. Methods: To test (a) the translation of public health interventions to ICHI codes and (b) the technical handling and general coding in public health, we used a set of public health interventions from a recent cross-sectional survey among Health Technology Assessment professionals. Results: Our study showed that handling of the ICHI interface is stable, that there is a need for specificity and adequate detail of intervention descriptions and desired outcomes to code adequately with ICHI and that the professional background of the coder, as well as his/her sex might influence the selection of codes. Conclusion: International Classification of Health Interventions provides a good coverage of public health interventions. However, the broader character of system wide interventions, often involving a variety of institutions and stakeholders, may present a challenge to the application of ICHI coding. Based on this experience, we would tailor future surveys more specifically to the needs of the classification and we advise training for health professionals before coding with ICHI. Standards of reporting will likely strengthen insights about the efficiency of primary prevention interventions and thus benefit long-term health of populations and structured HTA reporting process.





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University