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Record W2272260317 · doi:10.1186/s13643-015-0181-5

The quality of reporting methods and results of cost-effectiveness analyses in Spain: a methodological systematic review

2016· review· en· W2272260317 on OpenAlexafffund
Ferrán Catalá-López, Manuel Ridao-López, Adolfo Alonso‐Arroyo, Anna García‐Altés, Chris Cameron, Diana González‐Bermejo, Rafael Aleixandre‐Benavent, Enrique Bernal‐Delgado, Salvador Peiró, Rafael Tabarés‐Seisdedos, Brian Hutton

Bibliographic record

VenueSystematic Reviews · 2016
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersInstituto de Salud Carlos IIICanadian Institutes of Health ResearchUniversity of OxfordRed de Investigación en Servicios de Salud en Enfermedades CrónicasCentro de Investigación Biomédica en Red de Salud MentalGeneralitat ValencianaINCLIVA Instituto de Investigación Sanitaria
KeywordsMedicineSystematic reviewQuality (philosophy)MEDLINE

Abstract

fetched live from OpenAlex

BACKGROUND: Cost-effectiveness analysis has been recognized as an important tool to determine the efficiency of healthcare interventions and services. There is a need for evaluating the reporting of methods and results of cost-effectiveness analyses and establishing their validity. We describe and examine reporting characteristics of methods and results of cost-effectiveness analyses conducted in Spain during more than two decades. METHODS: A methodological systematic review was conducted with the information obtained through an updated literature review in PubMed and complementary databases (e.g. Scopus, ISI Web of Science, National Health Service Economic Evaluation Database (NHS EED) and Health Technology Assessment (HTA) databases from Centre for Reviews and Dissemination (CRD), Índice Médico Español (IME) Índice Bibliográfico Español en Ciencias de la Salud (IBECS)). We identified cost-effectiveness analyses conducted in Spain that used quality-adjusted life years (QALYs) as outcome measures (period 1989-December 2014). Two reviewers independently extracted the data from each paper. The data were analysed descriptively. RESULTS: In total, 223 studies were included. Very few studies (10; 4.5 %) reported working from a protocol. Most studies (200; 89.7 %) were simulation models and included a median of 1000 patients. Only 105 (47.1 %) studies presented an adequate description of the characteristics of the target population. Most study interventions were categorized as therapeutic (189; 84.8 %) and nearly half (111; 49.8 %) considered an active alternative as the comparator. Effectiveness of data was derived from a single study in 87 (39.0 %) reports, and only few (40; 17.9 %) used evidence synthesis-based estimates. Few studies (42; 18.8 %) reported a full description of methods for QALY calculation. The majority of the studies (147; 65.9 %) reported that the study intervention produced "more costs and more QALYs" than the comparator. Most studies (200; 89.7 %) reported favourable conclusions. Main funding source was the private for-profit sector (135; 60.5 %). Conflicts of interest were not disclosed in 88 (39.5 %) studies. CONCLUSIONS: This methodological review reflects that reporting of several important aspects of methods and results are frequently missing in published cost-effectiveness analyses. Without full and transparent reporting of how studies were designed and conducted, it is difficult to assess the validity of study findings and conclusions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.398
metaresearch head score (Gemma)0.691
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.602
Threshold uncertainty score0.743

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3980.691
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0120.014
Bibliometrics0.0320.031
Science and technology studies0.0020.004
Scholarly communication0.0110.007
Open science0.0050.005
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.930
GPT teacher head0.702
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainReporting
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2016
Admission routes2
Has abstractyes

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