Care clusters and mental health Payment by Results

Kingdon, David; Solomka, Bohdan; McAllister-Williams, R. Hamish; Turkington, Douglas; Grégoire, Alain; Elnazer, Hesham Y.; Thagadur, Mahesh; Hansen, Lars; Rathod, Shanaya; Gleeson, Stefan; Zoha, Mo; Singh, Pratima; Naeem, Farooq

doi:10.1192/bjp.200.2.162

Cited by 5 publications

(6 citation statements)

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“…The uncertainty regarding the ability of mental disorder diagnoses to predict increased HSU means that this review neither refutes nor supports the argument that reliable mental health clusters can be formed by combining broad diagnoses with care pathways, in a simple and practical manner. 12 …”

Section: Discussionmentioning

confidence: 99%

“…8–11 On the other hand, it has been argued that although mental disorder diagnosis alone is not sufficient for clustering purposes, information about broad diagnoses and care pathways can be combined, in a simple and practical manner, to form reliable clusters with homogenous resource patterns. 12 Moreover, the MHCT has also been criticised because its development did not take HSU and costs into account, 13 and, currently, very little evidence exists for the ability of the MHCT to predict HSU in patient populations.…”

Section: Introductionmentioning

confidence: 99%

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A systematic review of the predictors of health service utilisation by adults with mental disorders in the UK

et al. 2015

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ObjectivesTo identify variables that predict health service utilisation (HSU) by adults with mental disorders in the UK, and to determine the evidence level for these predictors.DesignA narrative synthesis of peer-reviewed studies published after the year 2000. The search was conducted using four databases (ie, PsycINFO, CINAHL Plus with full text, MEDLINE and EMBASE) and completed on 25 March 2014.SettingThe majority of included studies were set in health services across primary, secondary, specialist and inpatient care. Some studies used data from household and postal surveys.ParticipantsIncluded were UK-based studies that predicted HSU by adults with mental disorders. Participants had a range of mental disorders including psychotic disorders, personality disorders, depression, anxiety disorders, eating disorders and dementia.Primary outcomeA wide range of HSU outcomes were examined, including general practitioner (GP) contacts, medication usage, psychiatrist contacts, psychotherapy attendances, inpatient days, accident and emergency admissions and ‘total HSU’.ResultsTaking into account study quality, 28 studies identified a range of variables with good preliminary evidence supporting their ability to predict HSU. Of these variables, comorbidity, personality disorder, age (heterogeneous age ranges), neurotic symptoms, female gender, a marital status of divorced, separated or widowed, non-white ethnicity, high previous HSU and activities of daily living, were associated with increased HSU. Moreover, good preliminary evidence was found for associations of accessing a primary care psychological treatment service and medication use with decreased HSU.ConclusionsThe findings can inform decisions about which variables might be used to derive mental health clusters in ‘payment by results’ systems in the UK. The findings also support the need to investigate whether combining broad diagnoses with care pathways is an effective method for mental health clustering, and the need for research to further examine the association between mental health clusters and HSU.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A systematic review of the predictors of health service utilisation by adults with mental disorders in the UK

et al. 2015

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“…Furthermore clinicians regularly complain that the clusters don't fit an individual's condition and this creates confusion for clinicians asked to ascribe people to "boxes" with no clinical sense behind them (Communitycare, 2013). Kingdon et al (2012) point out that the abandonment of diagnosis-based system makes it difficult to understand how clusters can work in PbR. Finally, with no prior consideration of services, the classification process itself has been criticised as a "labelling process" (Callard et al, 2013;Middleton, 2013) which may result in its own adverse consequences.…”

Section: Strengths and Weaknesses Of The Mhct In Comparison To The Nfcasmentioning

confidence: 99%

Delaying the implementation of Payment by Results in mental health: the application of standardisation

Wang

Shaw

Middleton

2015

Mental Health Review Journal

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Design/methodology/approach -PbR relies upon "standardisation" of conditions and treatments. This depends upon a scheme of classification that can realistically predict resources required to execute treatment of any one case. Plans to fund NHS mental health services on the basis of tariffs derived in this way have been delayed, and a key reason is the lack of high-quality data. This would require effective "standardisation-to the-average" of both a system of classification and a repertoire of costed treatment pathways. This paper investigated the delay implementation by exploring the difficulties in applying standardisation principles to service provision and tariff calculation.Findings -The paper identified the fundamental difficulty with PbR's implementation in applying "standardisation" to practice. This is defining the mental disorder that the patient is suffering and designing care pathways at clinical level considering the balance between practical applicability and conceptual/constructional validity. This is necessary to enable the calculation of a national tariff. The conceptual flaws of the Health of the Nation Outcome Scale led to the constructional shortcomings which compromised the credibility and validity of Mental Health Clustering Tool regarding making accurate classification in a standardised way. The validity and credibility of calculating a national tariff thus became contentious on the basis of this inaccurate clinical classification system. Originality/value -This paper explored the driving factors of delay in implementing PbR in mental health through connecting the recent reform with the fundamental assumptions of "standardisation-to the-average", which provided another perspective to illustrate the current obstacles.

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“…These concerns are compounded by the lack of robust evidence from other studies for associations of HoNOS scores with costs,[17–19,21–23] operationalisation and validity issues [28,29], and the fact that the HoNOS were designed to measure clinical outcome rather than need for care. [49]…”

Section: Discussionmentioning

confidence: 99%

“…[4] Although the lack of utility of diagnostic related groups in predicting mental health service costs is well-documented, [7–11] it would be feasible to investigate the predictive ability of the combination of broad diagnostic categories with clinical pathways. [49] Multi-domain approaches to patient clustering that make use of a wide range of patient-related variables alongside clinical outcome measures could also be examined. This approach has produced promising results in (ultimately unsuccessful) attempts to implement casemix classification systems in Australia and New Zealand [15,16].…”

Section: Discussionmentioning

confidence: 99%

Utility of the Health of the Nation Outcome Scales (HoNOS) in Predicting Mental Health Service Costs for Patients with Common Mental Health Problems: Historical Cohort Study

et al. 2016

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BackgroundFew countries have made much progress in implementing transparent and efficient systems for the allocation of mental health care resources. In England there are ongoing efforts by the National Health Service (NHS) to develop mental health ‘payment by results’ (PbR). The system depends on the ability of patient ‘clusters’ derived from the Health of the Nation Outcome Scales (HoNOS) to predict costs. We therefore investigated the associations of individual HoNOS items and the Total HoNOS score at baseline with mental health service costs at one year follow-up.MethodsAn historical cohort study using secondary care patient records from the UK financial year 2012–2013. Included were 1,343 patients with ‘common mental health problems’, represented by ICD-10 disorders between F32-48. Costs were based on patient contacts with community-based and hospital-based mental health services. The costs outcome was transformed into ‘high costs’ vs ‘regular costs’ in main analyses.ResultsAfter adjustment for covariates, 11 HoNOS items were not associated with costs. The exception was ‘self-injury’ with an odds ratio of 1.41 (95% CI 1.10–2.99). Population attributable fractions (PAFs) for the contribution of HoNOS items to high costs ranged from 0.6% (physical illness) to 22.4% (self-injury). After adjustment, the Total HoNOS score was not associated with costs (OR 1.03, 95% CI 0.99–1.07). However, the PAF (33.3%) demonstrated that it might account for a modest proportion of the incidence of high costs.ConclusionsOur findings provide limited support for the utility of the self-injury item and Total HoNOS score in predicting costs. However, the absence of associations for the remaining HoNOS items indicates that current PbR clusters have minimal ability to predict costs, so potentially contributing to a misallocation of NHS resources across England. The findings may inform the development of mental health payment systems internationally, especially since the vast majority of countries have not progressed past the early stages of this development. Discrepancies between our findings with those from Australia and New Zealand point to the need for further international investigations.

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Care clusters and mental health Payment by Results

Cited by 5 publications

References 1 publication

A systematic review of the predictors of health service utilisation by adults with mental disorders in the UK

A systematic review of the predictors of health service utilisation by adults with mental disorders in the UK

Delaying the implementation of Payment by Results in mental health: the application of standardisation

Utility of the Health of the Nation Outcome Scales (HoNOS) in Predicting Mental Health Service Costs for Patients with Common Mental Health Problems: Historical Cohort Study

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