Measuring the Activity of Mental Health Services in England: Variation in Categorising Activity for Payment Purposes

In the context of international interest in reforming mental health payment systems, national policy in England has sought to move towards an episodic funding approach. Patients are categorised into care clusters, and providers will be paid for episodes of care for patients within each cluster. For the payment system to work, clusters need to be appropriately homogenous in terms of financial resource use. We examine variation in costs and activity within clusters and across health care providers. We find that the large variation between providers with respect to costs within clusters mean that a cluster-based episodic payment system would have substantially different financial impacts across providers.

Prospective payment systems and discretionary coding-Evidence from English mental health providers

Reimbursement of English mental health hospitals is moving away from block contracts and towards activity and outcome-based payments. Under the new model, patients are categorised into 20 groups with similar levels of need, called clusters, to which prices may be assigned prospectively. Clinicians, who make clustering decisions, have substantial discretion and can, in principle, directly influence the level of reimbursement the hospital receives. This may create incentives for upcoding. Clinicians are supported in their allocation decision by a clinical clustering algorithm, the Mental Health Clustering Tool, which provides an external reference against which clustering behaviour can be benchmarked. The aims of this study are to investigate the degree of mismatch between predicted and actual clustering and to test whether there are systematic differences amongst providers in their clustering behaviour. We use administrative data for all mental health patients in England who were clustered for the first time during the financial year 2014/15 and estimate multinomial multilevel models of over, under, or matching clustering. Results suggest that hospitals vary systematically in their probability of mismatch but this variation is not consistently associated with observed hospital characteristics.

Specific haplotypes of the CALPAIN-5 gene are associated with polycystic ovary syndrome

BACKGROUND

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in women of reproductive age. The aim of the present study was to investigate the role of CALPAIN-5 (CAPN5) gene in PCOS susceptibility.

METHODS

We analysed four intronic polymorphisms of the CAPN5 gene in 148 well-characterized women with PCOS and 606 unrelated controls. We performed a case-control study and an intracohort analysis of clinical characteristics associated with PCOS.

RESULTS

Analysis of haplotypes distribution between PCOS population compared to controls showed a strong deviation (P = 0.00029). The haplotypes GGCA and GGTG were overrepresented in PCOS patients (P = 0.009 and P = 0.001, respectively). In addition, we identified several CAPN5 haplotypes associated with phenotypic differences observed between PCOS patients, such as the presence of obesity (P = 0.02), cardiovascular complications (P = 0.02), familial antecedents of obesity (P = 0.003) and of hypertension (P = 0.007) and type 2 diabetes mellitus aggregation (P = 0.04).

CONCLUSIONS

These results suggest a role of CAPN5 gene in PCOS susceptibility in humans. Moreover, novel candidate risk alleles have been identified, within CAPN5 gene, which could be associated with important phenotypic and prognosis differences observed in PCOS patients.