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Payment by results: validating care cluster allocation in the real world

  • Stavros Bekas (a1) and Orlin Michev (a2)
Abstract
Aims and method

To validate care cluster allocation for payment by results (PbR) in mental health and to evaluate clustering and auditing methodologies. We applied exclusion criteria to the patient population of a mental health trust. An automated validation compared cluster with expected ICD-10 codes or scores on the Health of the Nation Outcome Scales (HoNOS) and Mental Health Clustering Tool (MHCT). Six hundred ‘mismatched’ cases were reviewed in depth to better understand the reasons why these cases appeared misclustered.

Results

There was a significant mismatch between ICD-10 codes, HoNOS and MHCT scores and allocated care cluster, with differences between services and localities. Some clusters appeared to be more accurately allocated. The ‘deep dive’ analysis indicated that most mismatches occurred because psychosis was allocated to a non-psychotic cluster and vice versa, but also as a result of inherent weaknesses of the MHCT.

Clinical implications

High levels of inappropriate care cluster allocation highlight the need to improve practice. Weaknesses in the MHCT and ICD-10 coding mean that the final arbiter should be clinical judgement. Auditing will, by necessity, have a significant margin of error.

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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
Stavros Bekas (stavros.bekas@nhs.net)
Footnotes
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Declaration of interest

S.B. has been involved in HoNOS and MHCT training with the Royal College of Psychiatrists and is currently on the PbR team in West London Mental Health NHS Trust.

Footnotes
References
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1 Self, R, Painter, J, Davis, R. A Report on the Development of a Mental Health Currency Model. Department of Health, 2008.
2 Department of Health. Mental Health Payment by Results Guidance for 2013–14. Department of Health, 2013.
3 Department of Health. Mental Health Clustering Booklet v2.01 2011/12. Department of Health, 2011.
4 Department of Health. Equity and Excellence: Liberating the NHS. Department of Health, 2010.
5 World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Description and Diagnostic Guidelines. WHO, 1992.
6 The Sainsbury Centre for Mental Health. Payment by Results: What Does it Mean for Mental Health? Policy Paper 4. SCMH, 2004.
7 Self, R, Painter, J. Study: To Improve and Demonstrate the Structural Properties of the Care clusters that form the basis of the PbR Currency Development Programme. Care Pathways and Packages Project, 2009.
8 Mason, A, Goddard, M, Myers, L, Verzulli, R. Navigating uncharted waters? How international experience can inform the funding of mental health care in England. J Ment Health 2011; 20: 234–48.
9 Tulloch, AD. Care clusters and mental health Payment by Results. Br J Psychiatry 2012; 200: 161.
10 Buckingham, W, Burgess, P, Solomon, S, Pirkis, J. Eagar, K. Developing a Casemix Classification for Mental Health Services. Volume 1: Main Report. Commonwealth Department of Health and Family Services, 1998.
11 Cotterill, PG, Thomas, FG. Prospective payment for Medicare inpatient psychiatric care: assessing the alternatives. Health Care Financ Rev 2004; 26: 85101.
12 Health and Social Care Information Centre. Casemix Service. Mental Health Casemix Classification Development: End Stage Report. Health and Social Care Information Centre, 2006.
13 Audit Commission. Maximising Resources in Adult Mental Health. Audit Commission, 2010.
14 Self, R, Rigby, A, Leggett, C, Paxton, R. Clinical Decision Support Tool: a rational needs-based approach to making clinical decisions. J Ment Health 2008; 17: 3348.
15 Green, C, Daniel, D. Payment by Results Quality and Outcomes Indicators: Report for Product Review Group Quality & Outcomes Sub Group. Department of Health, 2011.
16 Macdonald, AJD, Elphick, M. Combining routine outcomes measurement and ‘Payment by Results’: will it work and is it worth it? Br J Psychiatry 2011; 199: 178–9.
17 Kingdon, DG, Solomka, B, McAllister-Williams, H, Turkington, D, Gregoire, A, Elnazer, H, et al. Care clusters and mental health Payment by Results. Br J Psychiatry 2012; 200: 162.
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BJPsych Bulletin
  • ISSN: 1758-3209
  • EISSN: 1758-3217
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Payment by results: validating care cluster allocation in the real world

  • Stavros Bekas (a1) and Orlin Michev (a2)
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eLetters

Quality Assurance in Mental Health Clustering for PbR or the 'National Tariff' - A slave with many masters

Rahul Bhattacharya, Consultant Psychiatrist
29 January 2014

I believe the quality assurance of the clustering process (using the Mental Health Clustering Tool [MHCT] incorporating the HoNOS) is a complex field. Bekas and Michev (1) have approached it from the MHCT 'red rule' perspective and the ICD 10 coding perspective. What the results show is potentially to comply with one you might be in breach of the other. We face this in clinical practice, for example, Bipolar Affective Disorder (BPAD) is considered to be a 'psychotic' condition although as clinicians we all know there are times when patients with BPAD are not psychotic. On such occasions if you rate them on MHCT they might score '0' and then if you cluster them in a psychotic cluster you breach the 'red rule' and if you don't,you breach the ICD 10 coding expectations.

There would be another layer of complexity added when all the 'care packages' are agreed between the commissioners and providers. I am sure there would be interest to ensure that the care provided or offered reflects the package agreed. The elusive 'gold standard' that the authors alludeto if developed cannot be a one dimensional one. It needs to clarify, whenthere are conflicting standards, that the clinician has to adhere to the one which takes priority and therefore in my opinion should be hierarchical. In fact the authors of the MHCT might consider dropping the 'red rules' which might have out lived their usefulness when there are agreed care packages in place.

Until then MHCT and the clustering process remains an imperfect tool that clinicians have to navigate to communicate with the commissioners.

References:1. Bekas S and Michev O.Payment by results: validating care cluster allocation in the real world.Psychiatric Bulletin 2013; 37: 349-355

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Conflict of interest: Dr Bhattacharya is one of the clinical leads in PbR for Eastlondon NHS Foundation Trust

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Not everything that counts can be counted and not everything that can be counted counts

Salwa Khalil, Consultant Psychiatrist
29 January 2014

Bekas and Michev in their excellent paper (1), present a sober assessment of the inherent weakness of the Mental Health Clustering tool and ICD 10 coding.

Although clustering has already been used for many years in acute care, what is suitable for acute care is not necessary applicable to psychiatry. We are expected to cluster patients with similar symptoms, needs and disabilities in 21 clusters which are used as the basis for financial funding.

However, subjectivity in psychiatry is a fact and it does not really matter how many tools and scales we implement to change this fact. It may reduce the chance of subjectivity but never eliminates it. Diagnosis and formulations vary between clinicians within the same profession and even between members of the same team. One can identify quite easily a sizeable number of patients with an ever-changing diagnosis over a number of admissions. It follows that clustering is not a static tag but a changeable process that ought to be regularly updated. I agree wholeheartedly with Bekas and Michev that the final arbiter should be clinical judgement. It is not uncommon practice for clinicians such as myself to override the cluster concluded by other members of the team, relying on and trusting my clinical judgment.

References:

1. Bekas S, Michev O. Payment by results: validating care cluster allocation in the real world. Psychiatric Bulletin 2013; 37: 349-355

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Conflict of interest: None declared

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