{"id":{"repo_id":"wayne-thes","oai_identifier":"oai:digitalcommons.wayne.edu:oa_dissertations-1531"},"canonical_url":"https://search.dev.ndltd.org/etd/wayne-thes/oai:digitalcommons.wayne.edu:oa_dissertations-1531","repository":{"repo_id":"wayne-thes","name":"Wayne State University","base_url":"https://digitalcommons.wayne.edu/do/oai/"},"display":{"title":"Robustness of the achievable benchmark of care method","abstract":"<p>The Achievable Benchmark of Care Method is a process of care performance improvement measurement approach for identifying top performing healthcare providers. The purpose of this study was to investigate the robustness of the method. This was achieved by comparing the robustness of the standard ABC method, which uses the mean to calculate the benchmark, to versions of the ABC method where the mean was replaced with either a 5%, 10%, or 20% trimmed mean, a 15% Winsorized mean or the one-step Huber ø1.28 calculation. Monte Carlo simulations where conducted using publically available, Medicare process of care data. The mean was found to perform as well as or better than the other measures when compared based on the root mean squared error estimate calculation. Cause for these results was found through examination of the sample distributions. Each distribution in the study was strongly, negatively, skewed revealing the benchmark provider comparison data to be uniform.</p>","abstract_html":"&lt;p&gt;The Achievable Benchmark of Care Method is a process of care performance improvement measurement approach for identifying top performing healthcare providers. The purpose of this study was to investigate the robustness of the method. This was achieved by comparing the robustness of the standard ABC method, which uses the mean to calculate the benchmark, to versions of the ABC method where the mean was replaced with either a 5%, 10%, or 20% trimmed mean, a 15% Winsorized mean or the one-step Huber ø1.28 calculation. Monte Carlo simulations where conducted using publically available, Medicare process of care data. The mean was found to perform as well as or better than the other measures when compared based on the root mean squared error estimate calculation. Cause for these results was found through examination of the sample distributions. Each distribution in the study was strongly, negatively, skewed revealing the benchmark provider comparison data to be uniform.&lt;/p&gt;","abstract_has_math":false,"creators":["Capobianco, Jeff Arthur"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Education Evaluation and Research","degree_department":null,"school":null,"contributors":["Shlomo S. Sawilowsky"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-01-01T08:00:00Z","date_published":"2012-01-01T08:00:00Z","updated_at":"2026-07-24T05:59:11Z","subjects":["Clinical Psychology","Educational Assessment, Evaluation, and Research"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/532","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Shlomo S. 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The purpose of this study was to investigate the robustness of the method. This was achieved by comparing the robustness of the standard ABC method, which uses the mean to calculate the benchmark, to versions of the ABC method where the mean was replaced with either a 5%, 10%, or 20% trimmed mean, a 15% Winsorized mean or the one-step Huber ø1.28 calculation. Monte Carlo simulations where conducted using publically available, Medicare process of care data. The mean was found to perform as well as or better than the other measures when compared based on the root mean squared error estimate calculation. Cause for these results was found through examination of the sample distributions. Each distribution in the study was strongly, negatively, skewed revealing the benchmark provider comparison data to be uniform.</p>"]},{"key":"dc:title","label":"Title","values":["Robustness of the achievable benchmark of care method"]}]}],"canonical_facts":{"dc:contributor":["Shlomo S. 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