The value of data collection within a palliative care program

Kamal, AH; Currow, DC; Ritchie, C; Bull, J; Wheeler, JL; Abernethy, AP

The value of data collection within a palliative care program

Kamal, AH Currow, DC

Ritchie, C Bull, J Wheeler, JL Abernethy, AP

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Publication Type:: Journal Article
Citation:: Current Oncology Reports, 2011, 13 (4), pp. 308 - 315
Issue Date:: 2011-08-01

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Field	Value	Language
dc.contributor.author	Kamal, AH	en_US
dc.contributor.author	Currow, DC https://orcid.org/0000-0003-1988-1250	en_US
dc.contributor.author	Ritchie, C	en_US
dc.contributor.author	Bull, J	en_US
dc.contributor.author	Wheeler, JL	en_US
dc.contributor.author	Abernethy, AP	en_US
dc.date.issued	2011-08-01	en_US
dc.identifier.citation	Current Oncology Reports, 2011, 13 (4), pp. 308 - 315	en_US
dc.identifier.issn	1523-3790	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118194
dc.description.abstract	Collecting reliable and valid data is an increasing expectation within palliative care. Data remain the crux for demonstrating value and quality of care, which are the critical steps to program sustainability. Parallel goals of conducting research and performing quality assessment and improvement can also ensure program growth, financial health, and viability in an increasingly competitive environment. Mounting expectations by patients, hospitals, and payers and inevitable pay-for-performance paradigms have transitioned data collection procedures from novel projects to expected standard operation within usual palliative care delivery. We present types of data to collect, published guides for data collection, and how data can inform quality, value, and research within a palliative care organization. Our experiences with the Quality Data Collection Tool (QDACT) in the Carolinas Palliative Care Consortium to collect data on quality have led to valuable lessons learned in creating a data collection system. Suggested steps in forming data-sharing collaborations and building data collection procedures are shared. © 2011 Springer Science+Business Media, LLC.	en_US
dc.relation.ispartof	Current Oncology Reports	en_US
dc.relation.isbasedon	10.1007/s11912-011-0178-8	en_US
dc.subject.classification	Oncology & Carcinogenesis	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Palliative Care	en_US
dc.subject.mesh	Data Collection	en_US
dc.subject.mesh	Delivery of Health Care	en_US
dc.subject.mesh	Quality of Health Care	en_US
dc.subject.mesh	Outcome Assessment (Health Care)	en_US
dc.subject.mesh	Outcome Assessment, Health Care	en_US
dc.title	The value of data collection within a palliative care program	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	13	en_US
utslib.for	1110 Nursing	en_US
utslib.for	1112 Oncology and Carcinogenesis	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
pubs.organisational-group	/University of Technology Sydney/Faculty of Health/IMPACCT
utslib.copyright.status	closed_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	13	en_US

Abstract:

Collecting reliable and valid data is an increasing expectation within palliative care. Data remain the crux for demonstrating value and quality of care, which are the critical steps to program sustainability. Parallel goals of conducting research and performing quality assessment and improvement can also ensure program growth, financial health, and viability in an increasingly competitive environment. Mounting expectations by patients, hospitals, and payers and inevitable pay-for-performance paradigms have transitioned data collection procedures from novel projects to expected standard operation within usual palliative care delivery. We present types of data to collect, published guides for data collection, and how data can inform quality, value, and research within a palliative care organization. Our experiences with the Quality Data Collection Tool (QDACT) in the Carolinas Palliative Care Consortium to collect data on quality have led to valuable lessons learned in creating a data collection system. Suggested steps in forming data-sharing collaborations and building data collection procedures are shared. © 2011 Springer Science+Business Media, LLC.

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http://hdl.handle.net/10453/118194