Contemplating case mix

Costa, Andrew P.; Poss, Jeffery W.; McKillop, Ian

doi:10.1177/0840470414551866

Cited by 13 publications

(11 citation statements)

References 18 publications

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“…interRAI systems may also be used to inform decisions about the allocation of health care resources at the person and population levels. In non-mental health settings, interRAI systems have been developed to prioritize access to community and institutional services (301) and for eligibility determination in long-term care (302). Mental health counterparts to this work include a level of care framework based on the interRAI MH (303), analyses of service complexity for children with mental health needs and developmental disability based on the ChYMH-DD (304), and a decision-support algorithm describing resource intensity based on the interRAI ChYMH (305).…”

Section: Resource Allocationmentioning

confidence: 99%

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care

et al. 2020

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The lives of persons living with mental illness are affected by psychological, biological, social, economic, and environmental factors over the life course. It is therefore unlikely that simple preventive strategies, clinical treatments, therapeutic interventions, or policy options will succeed as singular solutions for the challenges of mental illness. Persons living with mental illness receive services and supports in multiple settings across the health care continuum that are often fragmented, uncoordinated, and inadequately responsive. Appropriate assessment is an important tool that health systems must deploy to respond to the strengths, preferences, and needs of persons with mental illness. However, standard approaches are often focused on measurement of psychiatric symptoms without taking a broader perspective to address issues like growth, development, and aging; physical health and disability; social relationships; economic resources; housing; substance use; involvement with criminal justice; stigma; and recovery. Using conglomerations of instruments to cover more domains is impractical, inconsistent, and incomplete while posing considerable assessment burden. interRAI mental health instruments were developed by a network of over 100 researchers, clinicians, and policy experts from over 35 nations. This includes assessment systems for adults in inpatient psychiatry, community mental health, emergency departments, mobile crisis teams, and long-term care settings, as well as a screening system for police officers. A similar set of instruments is available for child/youth mental health. The instruments form an integrated mental health information system because they share a common assessment language, conceptual basis, clinical emphasis, data collection

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Section: Resource Allocationmentioning

confidence: 99%

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care

et al. 2020

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“…4 In other words, there are groups of people with similar characteristics, which will consume similar amount health care resources and, by extension, incur similar costs of care. These groups represent the mix of cases that are observed in a health care system, or a “case-mix,” 5 which can be viewed as a proxy for the types of health care needs of the population.…”

Section: Introductionmentioning

confidence: 99%

“…Case-mix classification systems can be of two types: grouping or index systems. 5 Grouping systems assign cases into relatively homogeneous groups in terms of their expected resource use. 5 Each group has a weight associated to represent its expected resource use relative to the average case in the population, also known as “case-mix index.” 5 For example, the Resource Utilization Group Version III (RUG-III) is commonly used in the United States and Canada for nursing homes reimbursement.…”

Section: Introductionmentioning

confidence: 99%

“…5 Grouping systems assign cases into relatively homogeneous groups in terms of their expected resource use. 5 Each group has a weight associated to represent its expected resource use relative to the average case in the population, also known as “case-mix index.” 5 For example, the Resource Utilization Group Version III (RUG-III) is commonly used in the United States and Canada for nursing homes reimbursement. 7 Index systems, instead, combine different characteristics of a case to produce a numerical value for each case that represents the expected level of resource use, which can then be mapped it to a “case-mix index” value to represent expected level of resource use relative to the average case in the population.…”

Section: Introductionmentioning

confidence: 99%

“…7 Index systems, instead, combine different characteristics of a case to produce a numerical value for each case that represents the expected level of resource use, which can then be mapped it to a “case-mix index” value to represent expected level of resource use relative to the average case in the population. 5 For example, the Outcome and Assessment Information Set (OASIS) is used by Medicare to reimburse home care services. 8 A previous study also provided further discussion of these two types of systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review

Tran

Poss

Perlman

et al. 2019

Health�Serv�Insights

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As mental health care transitions from facility-based care to community-based services, methods to classify patients in terms of their expected health care resource use are an essential tool to balance the health care needs and equitable allocation of health care resources. This study performed a scoping review to summarize the nature, extent, and range of research on case-mix classifications used to predict mental health care resource use in community settings. This study identified 17 eligible studies with 32 case-mix classification systems published since the 1980s. Most of these studies came from the USA Veterans Affairs and Medicare systems, and the most recent studies came from Australia. There were a wide variety of choices of input variables and measures of resource use. However, much of the variance in observed resource use was not accounted for by these case-mix systems. The research activity specific to case-mix classification for community mental health care was modest. More consideration should be given to the appropriateness of the input variables, resource use measure, and evaluation of predictive performance. Future research should take advantage of testing case-mix systems developed in other settings for community mental health care settings, if possible.

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A ‘case-mix’ approach to understand adherence trajectories for a falls prevention exercise intervention: A longitudinal cohort study

et al. 2021

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Contemplating case mix

Cited by 13 publications

References 18 publications

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care

Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review

A ‘case-mix’ approach to understand adherence trajectories for a falls prevention exercise intervention: A longitudinal cohort study

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