The development of Version 2áof the AN-SNAP casemix classification system

Green, Janette; Gordon, Robert

doi:10.1071/ah070s68

Cited by 26 publications

(39 citation statements)

References 3 publications

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“…It was borne out of growing recognition patients should be classified by functional ability, rather than diagnosis and procedure codes as in the acute sector. 11 analysed by independent sample t-tests and between subjects analysis of variance (ANOVA) with post-hoc pairwise comparisons using Tukey adjustments for significant results. Results of descriptive analysis are presented as a mean and 95% confidence interval (95% CI).…”

Section: Designmentioning

confidence: 99%

“…Lower-limb amputee data were identified using AROC impairment codes 5.3 to 5.7 1 (definitions of impairment codes in The AROC data set includes 42 items: sociodemographic, funding and employment details, episode items (admission and discharge), medical (impairment codes, comorbidities, complications), and outcome data (patient level of function at admission and discharge). 10,11 Data within the AROC database are classified under the AN-SNAP casemix classification system which was developed at the University of Wollongong in 1997. 10 The purpose of AN-SNAP was to provide a casemix classification system for sub and non-acute care provided in a number of treatment settings.…”

Section: Designmentioning

confidence: 99%

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Lower-limb amputee rehabilitation in Australia: analysis of a national data set 2004 - 10

Stevermuer

Simmonds

Crotty

et al. 2013

Aust. Health Review

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This study investigates amputee rehabilitation at a national level over a seven year observation period (2004 to 2010) and comprises 6,588 episodes. It reports the national demographics, clinical characteristics and rehabilitation outcomes, with the aim of identifying findings that have implications for practitioners. What are the implications for practitioners?Although only a small proportion of all episodes in the AROC database, this subset of lower-limb amputee episodes has provided a useful snapshot of the current state of amputee rehabilitation in Australia. We believe these findings have significant implications for practitioners in delivery of amputee rehabilitation services across Australia. Practitioners may benefit from adjusting service delivery based upon the decreasing age of lower limb amputees. Findings from this study also indicate that AN-SNAP classifications are effective in discriminating amputee rehabilitation outcomes and may be used to streamline rehabilitation services and provide a more efficient and effective rehabilitation service. Conclusion:Whilst amputees represented a comparatively small proportion of all rehabilitation episodes in Australia, their LOS was significant. Unlike many other rehabilitation conditions, there was no evidence of decreasing LOS over time. AN-SNAP classes were effective in distinguishing rehabilitation outcomes, and could potentially be used more effectively in planning rehabilitation programs.

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Section: Designmentioning

confidence: 99%

Section: Designmentioning

confidence: 99%

Lower-limb amputee rehabilitation in Australia: analysis of a national data set 2004 - 10

Stevermuer

Simmonds

Crotty

et al. 2013

Aust. Health Review

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“…27 The blended payment model has significant advantages over the more rigid US prospective payment system, as it provides flexibility for longer stay rehabilitation programmes, where clinicians and commissioners agree that these are required.…”

Section: The Australian Systemmentioning

confidence: 99%

International casemix and funding models: lessons for rehabilitation

et al. 2011

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The development of casemix in rehabilitation poses similar challenges for healthcare systems all around the world. Well-established casemix systems in the United States and Australia have afforded valuable lessons for other countries to learn from, but have not provided all the answers. A range of casemix and payment models is required to cater for different healthcare cultures, and casemix tools must capture all the key cost-determinants of treatment for patients with complex needs.

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“…Many of the international casemix models use global disability measures (such as the Functional Independence Measure (FIM [11] or the Barthel index [12]) not only as a measure of outcome but also as a proxy of needs for rehabilitation intervention. However, although these instruments correlate broadly with needs for care in hospital and community settings [13], they do not directly measure the requirement for nursing, therapy or medical intervention in terms of staff time.…”

Section: Introductionmentioning

confidence: 99%

“…The UKROC data set development is undertaken in collaboration with the British Society of Rehabilitation Medicine (BSRM) and the Australasian Rehabilitation Outcome Centre (AROC), which is now 10 years into a similar programme [11]. Learning from their experience, as well as from other large international data collation programmes (such as the Uniform Data Systems [UDS] database in the United States), we have taken a novel approach to the type of data that are gathered.…”

Section: Introductionmentioning

confidence: 99%

Engaging the hearts and minds of clinicians in outcome measurement – the UK rehabilitation outcomes collaborative approach

Turner-Stokes¹,

Williams

Sephton

et al. 2012

Disability and Rehabilitation

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PurposeThis article explores the rationale for choosing the instruments included within the UK Rehabilitation Outcomes Collaborative (UKROC) data set. Using one specialist neuro-rehabilitation unit as an exemplar service, it describes an approach to engaging the hearts and minds of clinicians in recording the data.Key messages and implicationsMeasures included within a national data set for rehabilitation should be psychometrically robust and feasible to use in routine clinical practice; they should also support clinical decision-making so that clinicians actually want to use them. Learning from other international casemix models and benchmarking data sets, the UKROC team has developed a cluster of measures to inform the development of effective and cost-efficient rehabilitation services. These include measures of (1) “needs” for rehabilitation (complexity), (2) inputs provided to meet those needs (nursing and therapy intervention), and (3) outcome, including the attainment of personal goals as well as gains in functional independence.ConclusionsBy integrating the use of the data set measures in everyday clinical practice, we have achieved a very high rate of compliance with data collection. However, staff training and ongoing commitment from senior staff and managers are critical to the maintenance of effort required to provide assurance of data quality in the longer term.

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The development of Version 2áof the AN-SNAP casemix classification system

Cited by 26 publications

References 3 publications

Lower-limb amputee rehabilitation in Australia: analysis of a national data set 2004 - 10

Lower-limb amputee rehabilitation in Australia: analysis of a national data set 2004 - 10

International casemix and funding models: lessons for rehabilitation

Engaging the hearts and minds of clinicians in outcome measurement – the UK rehabilitation outcomes collaborative approach

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