The Experts below are selected from a list of 22197 Experts worldwide ranked by ideXlab platform
Corinne Alberti - One of the best experts on this subject based on the ideXlab platform.
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using and reporting the Delphi Method for selecting healthcare quality indicators a systematic review
PLOS ONE, 2011Co-Authors: Rym Boulkedid, Hendy Abdoul, Marine Loustau, O Sibony, Corinne AlbertiAbstract:Objective Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi Method to develop quality indicators, 2) to discuss specific Methodological skills for quality indicators selection 3) to give guidance about this practice. Methodology and Main Finding Three electronic data bases were searched over a 30 years period (1978–2009). All articles that used the Delphi Method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of Methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the Method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. Conclusion The use and reporting of the Delphi Method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the Method in future surveys.
Hendy Abdoul - One of the best experts on this subject based on the ideXlab platform.
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using and reporting the Delphi Method for selecting healthcare quality indicators a systematic review
PLOS ONE, 2011Co-Authors: Rym Boulkedid, Hendy Abdoul, Marine Loustau, O Sibony, Corinne AlbertiAbstract:Objective Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi Method to develop quality indicators, 2) to discuss specific Methodological skills for quality indicators selection 3) to give guidance about this practice. Methodology and Main Finding Three electronic data bases were searched over a 30 years period (1978–2009). All articles that used the Delphi Method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of Methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the Method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. Conclusion The use and reporting of the Delphi Method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the Method in future surveys.
Ellen J Hahn - One of the best experts on this subject based on the ideXlab platform.
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building consensus using the policy Delphi Method
Policy Politics & Nursing Practice, 2000Co-Authors: Mary Kay Rayens, Ellen J HahnAbstract:This article describes the use of the policy Delphi Method in building consensus for public policy and proposes a technique for measuring the degree of consensus. The policy Delphi Method is a systematic Method for obtaining, exchanging, and developing informed opinion on an issue. It can be used to develop consensus either for or against policy issues. The Method includes a multistage process involving the initial measurement of opinions (first stage), followed by data analysis, design of a new questionnaire, and a second measurement of opinions (second stage). The interquartile deviation is presented as one way of measuring consensus, and the McNemar test is described as a way to quantify the degree of shift in responses from the first to second stage. The application of the Method is illustrated by a case example from a study of state legislators’ views on tobacco policy.
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Consensus for tobacco policy among former state legislators using the policy Delphi Method.
Tobacco Control, 1999Co-Authors: Ellen J Hahn, Mary Kay RayensAbstract:OBJECTIVE—To test a novel approach for building consensus about tobacco control policies among legislators. DESIGN—A pilot study was conducted using a two-round, face-to-face policy Delphi Method. PARTICIPANTS—Randomly selected sample of 30 former Kentucky legislators (60% participation rate). MAIN OUTCOME MEASURE—Consensus on tobacco control and tobacco farming policies. RESULTS—Former state legislators were more supportive of tobacco control policies than expected, and highly supportive of lessening the state's dependence on tobacco. Former state legislators were in agreement with 43% of the second-round items for which there was no agreement at the first round, demonstrating a striking increase in consensus. With new information from their colleagues, former lawmakers became more supportive of workplace smoking restrictions, limitations on tobacco promotional items, and modest excise tax increases. CONCLUSIONS—The policy Delphi Method has the potential for building consensus for tobacco control and tobacco farming policies among state legislators. Tobacco control advocates in other states might consider using the policy Delphi Method with policymakers in public and private sectors. Keywords: policy Delphi Method; legislators; tobacco farming; policymaking
Akira Ishikawa - One of the best experts on this subject based on the ideXlab platform.
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the max min Delphi Method and fuzzy Delphi Method via fuzzy integration
Fuzzy Sets and Systems, 1993Co-Authors: Akira Ishikawa, Michio Amagasa, Tetsuo Shiga, Giichi Tomizawa, Rumi Tatsuta, Hiroshi MienoAbstract:Abstract The traditional Delphi Method is one of the effective Methods which enables forecasting by converging a possibility value through the feedback mechanism of the results of questionnaires, based on experts' judgments. Some points needing revision are: (1) By pinpointing the intuition of the first response on the part of experts, feasible inference values need to be extracted so that the quality-oriented and semantic structure of the responses may be analyzed. (2) By removing the effect caused by feedback in the Delphi Method, natural and non-converged results need to be acquired; Moreover, two and more repetitive surveys are likely to cause a decline in the response rate, which may produce negative effects in the ensuing analyses. (3) In general, as it is repeated, the survey becomes more costly and time-consuming. In order to resolve these issues, we have identified two kinds of membership functions in regard to ‘the attainable period with a high degree’ and ‘the unattainable period with a high degree’. Next, through the implementation of the Max-Min Fuzzy Delphi Method and the New Delphi Method via Fuzzy Integration, we have developed algorithms which enable forecasting attainable periods. Third, we have applied such algorithms to two concrete questions, compared the result with one obtained from the Delphi Method, and ascertained the feasible outcome. While more examination needs to be undertaken, the new Methods look valid and applicable to further analyses of other questions and items on questionnaires. While both Methods can forecast attainable periods, using these Methods simultaneously as well as the traditional Delphi Method, may prove a really effective result.
Rym Boulkedid - One of the best experts on this subject based on the ideXlab platform.
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using and reporting the Delphi Method for selecting healthcare quality indicators a systematic review
PLOS ONE, 2011Co-Authors: Rym Boulkedid, Hendy Abdoul, Marine Loustau, O Sibony, Corinne AlbertiAbstract:Objective Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi Method to develop quality indicators, 2) to discuss specific Methodological skills for quality indicators selection 3) to give guidance about this practice. Methodology and Main Finding Three electronic data bases were searched over a 30 years period (1978–2009). All articles that used the Delphi Method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of Methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the Method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. Conclusion The use and reporting of the Delphi Method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the Method in future surveys.