scholarly journals Database combinations to retrieve systematic reviews in Overviews of reviews: A methodological study

2019 ◽  
Author(s):  
Käthe Goossen ◽  
Simone Hess ◽  
Carole Lunny ◽  
Dawid Pieper
Keyword(s):  
Confidence Interval ◽  
Health Technology Assessment ◽  
Systematic Reviews ◽  
Technology Assessment ◽  
Health Technology ◽  
Bibliographic Databases ◽  
Health Related ◽  
The Mean ◽  
Reference Checking ◽  
Assessment Reports

Abstract Background When conducting an Overviews of Reviews on health-related topics it is unclear which combination of bibliographic databases authors should use for searching for systematic reviews. Our goal was to determine which databases indexed the most systematic reviews and identify an optimal database combination for searching systematic reviews. Methods A set of 86 Overviews of Reviews with 1219 included systematic reviews was extracted from a previous study. Indexing of the systematic reviews was assessed in MEDLINE, CINAHL, DARE, Embase, Epistemonikos, PsycINFO, and TRIP. The mean indexing rate (% of indexed systematic reviews) and corresponding 95% confidence interval were calculated for each database individually, as well as for combinations of MEDLINE with other databases and reference checking. Results Indexing of systematic reviews was higher in MEDLINE than in any other single database (mean indexing rate 89.7%; 95% confidence interval [89.0–90.3%]). Combined with reference checking, this value increased to 93.7% [93.2–94.2%]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (99.2% [99.0–99.3%]). Stratification by Health Technology Assessment reports (97.7% [96.5–98.9%]) vs. Cochrane overviews (100.0%) vs. non-Cochrane overviews (99.3% [99.1–99.4%]) showed that indexing was only slightly lower for Health Technology Assessment reports. However, MEDLINE, Epistemonikos, and reference checking remained the best combination. Among the 10/1219 systematic reviews not identified by this combination, five were published as websites rather than journals, two were indexed in CINAHL and Embase, and one was indexed in the database ERIC. Conclusions MEDLINE/Epistemonikos, complemented by reference checking, is the best database combination to identify systematic reviews on health-related topics.

scholarly journals Database combinations to retrieve systematic reviews in Overviews of reviews: A methodological study

2020 ◽  
Author(s):  
Käthe Goossen ◽  
Simone Hess ◽  
Carole Lunny ◽  
Dawid Pieper
Keyword(s):  
Confidence Interval ◽  
Health Technology Assessment ◽  
Systematic Reviews ◽  
Technology Assessment ◽  
Health Technology ◽  
Bibliographic Databases ◽  
Health Related ◽  
Inclusion Rate ◽  
Reference Checking ◽  
Assessment Reports

Abstract Background When conducting an Overviews of Reviews on health-related topics, it is unclear which combination of bibliographic databases authors should use for searching for SRs. Our goal was to determine which databases included the most systematic reviews and identify an optimal database combination for searching systematic reviews. Methods A set of 86 Overviews of Reviews with 1219 included systematic reviews was extracted from a previous study. Inclusion of the systematic reviews was assessed in MEDLINE, CINAHL, Embase, Epistemonikos, PsycINFO, and TRIP. The mean inclusion rate (% of included systematic reviews) and corresponding 95% confidence interval were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Results Inclusion of systematic reviews was higher in MEDLINE than in any other single database (mean inclusion rate 89.7%; 95% confidence interval [89.0–90.3%]). Combined with reference checking, this value increased to 93.7% [93.2–94.2%]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (99.2% [99.0–99.3%]). Stratification by Health Technology Assessment reports (97.7% [96.5–98.9%]) vs. Cochrane Overviews (100.0%) vs. non-Cochrane Overviews (99.3% [99.1–99.4%]) showed that inclusion was only slightly lower for Health Technology Assessment reports. However, MEDLINE, Epistemonikos, and reference checking remained the best combination. Among the 10/1219 systematic reviews not identified by this combination, five were published as websites rather than journals, two were included in CINAHL and Embase, and one was included in the database ERIC. Conclusions MEDLINE and Epistemonikos, complemented by reference checking of included studies, is the best database combination to identify systematic reviews on health-related topics.

scholarly journals Database combinations to retrieve systematic reviews in Overviews of reviews: A methodological study

2020 ◽  
Author(s):  
Käthe Goossen ◽  
Simone Hess ◽  
Carole Lunny ◽  
Dawid Pieper
Keyword(s):  
Confidence Interval ◽  
Health Technology Assessment ◽  
Systematic Reviews ◽  
Technology Assessment ◽  
Health Technology ◽  
Bibliographic Databases ◽  
Health Related ◽  
Inclusion Rate ◽  
Reference Checking ◽  
Assessment Reports

Abstract Background: When conducting an Overviews of Reviews on health-related topics, it is unclear which combination of bibliographic databases authors should use for searching for SRs. Our goal was to determine which databases included the most systematic reviews and identify an optimal database combination for searching systematic reviews. Methods: A set of 86 Overviews of Reviews with 1219 included systematic reviews was extracted from a previous study. Inclusion of the systematic reviews was assessed in MEDLINE, CINAHL, Embase, Epistemonikos, PsycINFO, and TRIP. The mean inclusion rate (% of included systematic reviews) and corresponding 95% confidence interval were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Results: Inclusion of systematic reviews was higher in MEDLINE than in any other single database (mean inclusion rate 89.7%; 95% confidence interval [89.0–90.3%]). Combined with reference checking, this value increased to 93.7% [93.2–94.2%]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (99.2% [99.0–99.3%]). Stratification by Health Technology Assessment reports (97.7% [96.5–98.9%]) vs. Cochrane Overviews (100.0%) vs. non-Cochrane Overviews (99.3% [99.1–99.4%]) showed that inclusion was only slightly lower for Health Technology Assessment reports. However, MEDLINE, Epistemonikos, and reference checking remained the best combination. Among the 10/1219 systematic reviews not identified by this combination, five were published as websites rather than journals, two were included in CINAHL and Embase, and one was included in the database ERIC.Conclusions: MEDLINE and Epistemonikos, complemented by reference checking of included studies, is the best database combination to identify systematic reviews on health-related topics.

scholarly journals Developing a quality management system for the European Network for Health Technology Assessment (EUnetHTA): toward European HTA collaboration

2021 ◽  
Vol 37 (1) ◽  
Author(s):  
Miriam Luhnen ◽  
Sari Susanna Ormstad ◽  
Anne Willemsen ◽  
Chaienna Schreuder-Morel ◽  
Catharina Helmink ◽  
...  
Keyword(s):  
Quality Management ◽  
Health Technology Assessment ◽  
Technology Assessment ◽  
Management System ◽  
Quality Management System ◽  
Health Technology ◽  
European Network ◽  
Joint Work ◽  
Working Groups ◽  
Assessment Reports

Abstract Objectives The European Network for Health Technology Assessment (EUnetHTA) was established in 2006 and comprises over eighty organizations from thirty European countries. In its fifth project phase (Joint Action 3), EUnetHTA set up a quality management system (QMS) to improve the efficiency and standardization of joint work. This article presents EUnetHTA's new QMS and outlines experiences and challenges during its implementation. Methods Several working groups defined processes and methods to support assessment teams in creating high-quality assessment reports. Existing guidelines, templates, and tools were refined and missing parts were newly created and integrated into the new QMS framework. EUnetHTA has contributed to Health Technology Assessment (HTA) capacity building through training and knowledge sharing. Continuous evaluation helped to identify gaps and shortcomings in processes and structures. Results Based on a common quality management concept and defined development and revision procedures, twenty-seven partner organizations jointly developed and maintained around forty standard operating procedures and other components of the QMS. All outputs were incorporated into a web-based platform, the EUnetHTA Companion Guide, which was launched in May 2018. Concerted efforts of working groups were required to ensure consistency and avoid duplication. Conclusions With the establishment of a QMS for jointly produced assessment reports, EUnetHTA has taken a significant step toward a sustainable model for scientific and technical collaboration within European HTA. However, the definition of processes and methods meeting the numerous requirements of healthcare systems across Europe remains an ongoing and challenging task.

PP100 Unraveling Hospital-Based Health Technology Assessment In Brazil

2019 ◽  
Vol 35 (S1) ◽  
pp. 57-57
Author(s):  
Ricardo Bertoglio Cardoso ◽  
Luciane Cruz ◽  
Marina Aziz ◽  
Sandro Miguel ◽  
Mírian Cohen ◽  
...  
Keyword(s):  
Health Technology Assessment ◽  
Technology Assessment ◽  
Health Technology ◽  
Importance Score ◽  
Score Threshold ◽  
Wide Range ◽  
Decision Making Processes ◽  
Work Production ◽  
The Mean ◽  
Survey Questionnaires

IntroductionIn Brazil, hospital-based health technology assessment (HB-HTA) units have been implemented countrywide since early 2000 to improve decision-making processes. Multiple-criteria decision analysis (MCDA) can provide a deeper understanding of a given subject. The present study used MCDA to evaluate capacity building among HB-HTA units in Brazil.MethodsThis study analyzed preliminary data from a survey developed and sent to all HB-HTA units in Brazil in 2018. The survey comprised 116 questions covering a wide range of aspects. Initially, an expert panel was organized, and 46 objective questions (out of 116) were selected by four experts. Next, these experts classified the selected questions by weighting them according to their relative importance. A Likert scale was used to identify the levels of importance, which were converted to weights ranging from zero to one. The experts then defined a final importance score threshold of 60 percent to classify units as fully operational. Grades below this threshold indicated the need for a more detailed evaluation. Of the 80 survey questionnaires, 23 were evaluated by the proposed method.ResultsImportance weights for each classification were defined as follows: personnel (25%); level of expertise (31%); work production (31%); and infrastructure (13%). The mean final importance score for the HB-HTA units was 68 percent. The maximum and minimum scores achieved were 95 percent and 15 percent, respectively. The HB-HTA units had been established for an average of 6 years, and ten of the 23 units were classified as fully operational.ConclusionsThe multicriteria method presented by this study simplified HB-HTA unit evaluation, reducing the subjectivity of results. Final importance scores for each unit's categories indicated which areas need improvement. Results from the study indicated that infrastructure and personnel could be greatly enhanced, even though the production profile was satisfactory.

PP65 Methods Applied For Systematic Reviews Of Economic Evaluations In Health Technology Assessment

2019 ◽  
Vol 35 (S1) ◽  
pp. 49-50
Author(s):  
Miriam Luhnen ◽  
Barbara Prediger ◽  
Edmund A.M. Neugebauer ◽  
Tim Mathes
Keyword(s):  
Health Technology Assessment ◽  
Systematic Reviews ◽  
Technology Assessment ◽  
Data Extraction ◽  
Reporting Quality ◽  
Health Technology ◽  
Economic Evaluations ◽  
Study Selection ◽  
Data Extraction Form ◽  
Literature Search Strategy

IntroductionWhen making decisions in health care, it is essential to consider economic evidence about an intervention. The objective of this study was to analyze the methods applied for systematic reviews of economic evaluations in Health Technology Assessment (HTA) and to identify common challenges.MethodsWe manually searched the webpages of HTA organizations and included HTA-reports published since 2015. Prerequisites for inclusion were the conduct of a systematic review of economic evaluations in at least one electronic database and the use of the English, German, French, or Spanish language. Methodological features were extracted in standardized tables. We prepared descriptive statistical (e.g., median, range) measures to describe the applied methods. Data were synthesized in a structured narrative way.ResultsEighty-three reports were included in the analysis. We identified inexplicable heterogeneity, particularly concerning literature search strategy, data extraction, assessment of quality, and applicability. Furthermore, process steps were often missing or reported in a nontransparent way. The use of a standardized data extraction form was indicated in one-third of reports (32 percent). Fifty-four percent of authors systematically appraised included studies. In 10 percent of reports, the applicability of included studies was assessed. Involvement of two reviewers was rarely reported for the study selection (43 percent), data extraction (28 percent), and quality assessment (39 percent).ConclusionsThe methods applied for systematic reviews of economic evaluations in HTA and their reporting quality are very heterogeneous. Efforts toward a detailed, standardized guidance for the preparation of systematic reviews of economic evaluations definitely seem necessary. A general harmonization and improvement of the applied methodology would increase their value for decision makers.

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