Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
ObjectivesTo develop a minimum dataset to be routinely collected across a heterogenous population within a subacute rehabilitation service to guide best care and outcomes for patients, and value for the health service.DesignThree-round e-Delphi exercise, followed by consensus meetings.SettingMulticentre study in Brisbane, Australia.ParticipantsRehabilitation decision-makers, researchers and clinicians were invited to participate in the e-Delphi exercise. A multidisciplinary project steering committee (rehabilitation decision makers, researchers, clinicians and consumers) participated in consensus meetings.MethodsIn round 1 of the e-Delphi, participants responded to an open-ended question, generating data and outcomes that should be routinely collected in rehabilitation. In rounds 2 and 3, participants rated the importance of collecting each item on a nine-point scale. Consensus was defined a priori, as items rated as ‘essential’ by at least 70%, and of ‘limited importance’ by less than 15%, of respondents. Consensus meetings were held to further refine and define the dataset for implementation.ResultsIn total, 38 participants completed round 1 of the e-Delphi. Qualitative content analysis of their responses generated 1072 codes, which were condensed into 39 categories and 209 subcategories. Following two rounds of rating (round 2: n=32 participants; round 3: n=28 participants), consensus was reached for 124 items. Four consensus meetings (n=14 participants) resulted in the final dataset which included 42 items across six domains: (1) patient demographics, (2) premorbid health and psychosocial information, (3) admission information, (4) service delivery and interventions, (5) outcomes and (6) caregiver information and outcomes.ConclusionsWe identified 42 items that reflect the values and experiences of rehabilitation stakeholders. Items unique to this dataset include caregiver information and outcomes, and detailed service delivery and intervention data. Future research will establish the feasibility of collection in practice.
ObjectivesTo develop a minimum dataset to be routinely collected across a heterogenous population within a subacute rehabilitation service to guide best care and outcomes for patients, and value for the health service.DesignThree-round e-Delphi exercise, followed by consensus meetings.SettingMulticentre study in Brisbane, Australia.ParticipantsRehabilitation decision-makers, researchers and clinicians were invited to participate in the e-Delphi exercise. A multidisciplinary project steering committee (rehabilitation decision makers, researchers, clinicians and consumers) participated in consensus meetings.MethodsIn round 1 of the e-Delphi, participants responded to an open-ended question, generating data and outcomes that should be routinely collected in rehabilitation. In rounds 2 and 3, participants rated the importance of collecting each item on a nine-point scale. Consensus was defined a priori, as items rated as ‘essential’ by at least 70%, and of ‘limited importance’ by less than 15%, of respondents. Consensus meetings were held to further refine and define the dataset for implementation.ResultsIn total, 38 participants completed round 1 of the e-Delphi. Qualitative content analysis of their responses generated 1072 codes, which were condensed into 39 categories and 209 subcategories. Following two rounds of rating (round 2: n=32 participants; round 3: n=28 participants), consensus was reached for 124 items. Four consensus meetings (n=14 participants) resulted in the final dataset which included 42 items across six domains: (1) patient demographics, (2) premorbid health and psychosocial information, (3) admission information, (4) service delivery and interventions, (5) outcomes and (6) caregiver information and outcomes.ConclusionsWe identified 42 items that reflect the values and experiences of rehabilitation stakeholders. Items unique to this dataset include caregiver information and outcomes, and detailed service delivery and intervention data. Future research will establish the feasibility of collection in practice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.