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2. The utility of functioning in predicting health service use by people with common mental disorders

Author

Twomey, Conal and Cieza, Alarcos

Subjects
362.2
Abstract

Background: Mental health services are under-resourced in countries around the world. It is essential therefore that the scarce resources are allocated fairly and efficiently. To facilitate this process, extensive knowledge of the variables associated with health service use (HSU) by people with mental disorders is required. As diagnoses and symptoms may not explain a large proportion of the variance in this HSU, there is a need to investigate the relevant associations of other variables. The term ‘functioning’ relates to physical and mental functions and the ability to undertake activities and participate in all of life. The studies described within this thesis were to determine the utility of functioning in predicting HSU by people with common mental disorders. It was hypothesised that functioning would have good utility in this prediction. Methods: A systematic review was initially undertaken, followed by three empirical studies: one set in low- and middle-income countries (LMICs) and two within the English National Health Service (NHS). Results: (1) Systematic Review: There is a lack of existing research into the association of functioning with HSU. The available evidence was mixed: three functioning variables (i.e. cognitive deficits, social withdrawal and activities of daily living) were significantly associated with HSU, but only in 55% of the assessments conducted on them. (2) Cross-sectional study: For older people with depression living in LMICs (n=4,590), functioning was significantly associated with one HSU outcome (i.e. hospital admission) but not another (i.e. “any community HSU”). (3) Historical cohort study: the seven functioning items from the HoNOS instrument were not associated with mental health service costs for patients with common mental disorders, over one year (n=1,343). (4) Prospective cohort study: functioning predicted total NHS costs for patients with mood and anxiety disorders over a six month period (n=102). Discussion: The mixed findings provide partial support for the hypothesised predictive ability of functioning. Narrow operationalisations of functioning evidently have limited utility in predicting HSU. However, the positive findings of the final study support the predictive ability of ‘multi-domain’ functioning. Multi-domain functioning information could therefore be useful for the formation of patient clusters within mental health payment systems.

Published
2017

8. The utility of functioning in predicting health service use by people with common mental disorders

Author

Twomey, Conal. and Twomey, Conal.

Abstract

Background Mental health services are under-resourced in countries around the world. It is essential therefore that the scarce resources are allocated fairly and efficiently. To facilitate this process, extensive knowledge of the variables associated with health service use (HSU) by people with mental disorders is required. As diagnoses and symptoms may not explain a large proportion of the variance in this HSU, there is a need to investigate the relevant associations of other variables. The term ‘functioning’ relates to physical and mental functions and the ability to undertake activities and participate in all of life. The studies described within this thesis were to determine the utility of functioning in predicting HSU by people with common mental disorders. It was hypothesised that functioning would have good utility in this prediction. Methods A systematic review was initially undertaken, followed by three empirical studies: one set in low- and middle-income countries (LMICs) and two within the English National Health Service (NHS). Results (1) Systematic Review: There is a lack of existing research into the association of functioning with HSU. The available evidence was mixed: three functioning variables (i.e. cognitive deficits, social withdrawal and activities of daily living) were significantly associated with HSU, but only in 55% of the assessments conducted on them. (2) Cross-sectional study: For older people with depression living in LMICs (n=4,590), functioning was significantly associated with one HSU outcome (i.e. hospital admission) but not another (i.e. “any community HSU”). (3) Historical cohort study: the seven functioning items from the HoNOS instrument were not associated with mental health service costs for patients with common mental disorders, over one year (n=1,343). (4) Prospective cohort study: functioning predicted total NHS costs for patients with mood and anxiety disorders

Published
2017

9. 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

Author

Twomey, Conal, primary, Prina, A. Matthew, additional, Baldwin, David S., additional, Das-Munshi, Jayati, additional, Kingdon, David, additional, Koeser, Leonardo, additional, Prince, Martin J., additional, Stewart, Robert, additional, Tulloch, Alex D., additional, and Cieza, Alarcos, additional

Published
2016
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15. Capturing patients' needs in casemix: a systematic literature review on the value of adding functioning information in reimbursement systems.

Author

Hopfe, Maren, Stucki, Gerold, Marshall, Ric, Twomey, Conal D., Üstün, T. Bedirhan, and Prodinger, Birgit

Subjects
PATIENTS, MEDICAL needs assessment, HEALTH planning, HEALTH insurance reimbursement, REIMBURSEMENT, CINAHL database, MEDICAL information storage & retrieval systems, MEDICAL care use, MEDLINE, ONLINE information services, PEOPLE with disabilities, RESEARCH funding, SYSTEMATIC reviews, ACTIVITIES of daily living
Abstract

Background: Contemporary casemix systems for health services need to ensure that payment rates adequately account for actual resource consumption based on patients' needs for services. It has been argued that functioning information, as one important determinant of health service provision and resource use, should be taken into account when developing casemix systems. However, there has to date been little systematic collation of the evidence on the extent to which the addition of functioning information into existing casemix systems adds value to those systems with regard to the predictive power and resource variation explained by the groupings of these systems. Thus, the objective of this research was to examine the value of adding functioning information into casemix systems with respect to the prediction of resource use as measured by costs and length of stay.Methods: A systematic literature review was performed. Peer-reviewed studies, published before May 2014 were retrieved from CINAHL, EconLit, Embase, JSTOR, PubMed and Sociological Abstracts using keywords related to functioning ('Functioning', 'Functional status', 'Function*, 'ICF', 'International Classification of Functioning, Disability and Health', 'Activities of Daily Living' or 'ADL') and casemix systems ('Casemix', 'case mix', 'Diagnosis Related Groups', 'Function Related Groups', 'Resource Utilization Groups' or 'AN-SNAP'). In addition, a hand search of reference lists of included articles was conducted. Information about study aims, design, country, setting, methods, outcome variables, study results, and information regarding the authors' discussion of results, study limitations and implications was extracted.Results: Ten included studies provided evidence demonstrating that adding functioning information into casemix systems improves predictive ability and fosters homogeneity in casemix groups with regard to costs and length of stay. Collection and integration of functioning information varied across studies. Results suggest that, in particular, DRG casemix systems can be improved in predicting resource use and capturing outcomes for frail elderly or severely functioning-impaired patients.Conclusion: Further exploration of the value of adding functioning information into casemix systems is one promising approach to improve casemix systems ability to adequately capture the differences in patient's needs for services and to better predict resource use. [ABSTRACT FROM AUTHOR]

Published
2016
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