scholarly journals SHIFTING SOCIAL PREFERENCES TOWARDS MORAL PREJUDICES IN A PROCESS OF RESOURCE ALLOCATION DECISION MAKING

2020 ◽  
pp. 33-36
Author(s):  
Alla Kovalenko ◽  
Albina Holovina
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Social Preferences ◽  
Resource Allocation Decision ◽  
Social Orientation ◽  
Decision Making Process ◽  
Clear Understanding ◽  
Allocation Decision ◽  
Self Interest ◽  
Personal Interests

This paper presents an analysis of the main theories and results of experimental research in the context of the shifting social preferences towards moral prejudices in a process of resource allocation decision making. Researchers of game theory have found that three motives are included in the decision-making process about resource allocation: social preferences, moral prejudices, and self-interest. Personal interests and moral prejudices are strong predictors in the model of predicting people's social orientations. Moral prejudices, being the distortions created by self-interest, can strongly influence people's social preferences, and even change them to the opposite. As a result, an asymmetric relationship is established between personal interest and moral prejudices in the decision-making process about resource allocation. When moral prejudices become an obstacle to achieving a goal, a person unconsciously distorts the information so that it justifies its actions. These distortions can be manifested in the avoidance of information that interferes with personal interests, the selective selection of information, and even recourse to opposing moral principles. In the long run, all this is expressed in the change of a person's social orientation from altruistic to selfish. These changes in people's social preferences are confirmed by the results of numerous experiments not only in social psychology, but also in social neuropsychology and neuroeconomics. The way to overcome these distortions is to have a clear understanding of the limits of personal interests and an understanding of one's own motives in decisions about resource allocation.

Performance Ratio Based Resource Allocation Decision-Making in Genomic Medicine

2017 ◽  
Vol 21 (2) ◽  
pp. 67-73 ◽  
Author(s):  
Vasilios Fragoulakis ◽  
Christina Mitropoulou ◽  
Daphne Katelidou ◽  
Ron H. van Schaik ◽  
Nikolaos Maniadakis ◽  
...  
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Genomic Medicine ◽  
Resource Allocation Decision ◽  
Performance Ratio ◽  
Allocation Decision

CASE STUDIES THAT ILLUSTRATE DISINVESTMENT AND RESOURCE ALLOCATION DECISION-MAKING PROCESSES IN HEALTH CARE: A SYSTEMATIC REVIEW

2013 ◽  
Vol 29 (2) ◽  
pp. 174-184 ◽  
Author(s):  
Julie Polisena ◽  
Tammy Clifford ◽  
Adam G. Elshaug ◽  
Craig Mitton ◽  
Erin Russell ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Resource Allocation ◽  
Case Studies ◽  
Resource Allocation Decision ◽  
Cochrane Library ◽  
Fee For Service ◽  
Allocation Decision ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

Objective:Technological change accounts for approximately 25 percent of health expenditure growth. To date, limited research has been published on case studies of disinvestment and resource allocation decision making in clinical practice. Our research objective is to systematically review and catalogue the application of frameworks and tools for disinvestment and resource allocation decision making in health care.Methods:An electronic literature search was executed for studies on disinvestment, obsolete and ineffective technologies, and priority healthcare setting, published from January 1990 until January 2012. Databases searched were MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, Embase, The Cochrane Library, PubMed, and HEED.Results:Fourteen case studies on the application of frameworks and tools for disinvestment and resource allocation decisions were included. Most studies described the application of program budgeting and marginal analysis (PBMA), and two reports used health technology assessment (HTA) methods for coverage decisions in a national fee-for-service structure. Numerous healthcare technologies and services were covered across the studies. We describe the multiple criteria considered for decision making, and the strengths and limitations of these frameworks and tools are highlighted.Conclusions:Disinvestment and resource allocation decisions require evidence to ensure their transparency and objectivity. PBMA was used to assess resource allocation of health services and technologies in a fixed budget jurisdiction, while HTA reviews focused on specific technologies, principally in fee-for-service structures. Future research can review the data requirements and explore opportunities to increase the quantity of available evidence for disinvestment and resource allocation decisions.

scholarly journals Resource allocation across the dementia continuum: A mixed methods study examining decision making on optimal dementia care among health and social care professionals.

2020 ◽  
Author(s):  
Fiona Keogh ◽  
Tom Pierse ◽  
David Challis ◽  
Eamon O'Shea
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Mixed Methods ◽  
Social Care ◽  
Severe Case ◽  
Decision Making Process ◽  
Care Provision ◽  
Allocation Decision ◽  
Health And Social Care ◽  
Case Type

Abstract Background: The understanding of appropriate or optimal care is particularly important for dementia, characterised by multiple, long-term, changing needs and the increasing expectations of people using services, within a wider context of resource constrained health and social care services. This study sought to determine the optimal level, mix and cost of services for different dementia case types across the dementia continuum and to gain a greater understanding of the resource allocation decision making process among health and social care professionals (HSCPs).Methods: A balance of care (BoC) framework was applied to the study questions and developed in three important ways; firstly by considering optimality across the course of dementia and not just at the margin with residential care; secondly, through the introduction of a fixed budget to reveal constrained optimisation strategies; and thirdly through the use of a mixed methods design whereby qualitative data was collected at workshops using nominal group technique and analysed to obtain a more detailed understanding of the decision-making process. Twenty four HSCPs from a variety of disciplines participated in the resource allocation decision-making exercise.Results: HSCPs differentiated between case type severity; providing about 2.6 times more resources to case types with higher level needs than those with lower level needs. When a resource constraint was introduced there was no evidence of any disproportionate rationing of services on the basis of need, i.e. more severe case types were not favoured over less severe case types. However, the fiscal constraint led to a much greater focus on meeting physical and clinical dependency needs through conventional social care provision. There was less emphasis on day care and psychosocial provision when resources were scarcer following the introduction of a fixed budget constraint.Conclusions: HSCPs completed complex resource allocation exercises for people with dementia, including expected differentiation across case type severity. When rationing was introduced, HSCPs did not discriminate in favour of case types with high levels of need. They did, however, support conventional home care provision over psychosocial care, although participants were still keen to provide some residual cover for the latter, especially for case types that might benefit.

Case Manager Resource Allocation Decision-Making for Adult Home Care Clients: With Comparisons to a High Needs Pediatric Home Care Clients

2018 ◽  
Vol 30 (4) ◽  
pp. 164-174 ◽  
Author(s):  
Kimberly Fraser ◽  
Garland Baird Lisa ◽  
Daley Laing ◽  
Jonathan Lai ◽  
Neelam Saleem Punjani
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Collection ◽  
Home Care ◽  
Quality Care ◽  
Case Manager ◽  
Care Program ◽  
Ethnographic Study ◽  
Resource Allocation Decision ◽  
Allocation Decision

Home care programs have become integral parts of the overall health service system in Canada and in many other developed nations. Resource allocation decision-making by home care case managers (CM) is a complex task where CMs are challenged to meet the dual responsibilities for clients, in order that they achieve high quality care, and to the system to contain costs. The purpose of this study was to extend what is known about resource allocation decision-making factors identified in a previous systematic literature review and ethnographic study within a high needs pediatric context conducted by the principal investigator in Western Canada. Spradley’s ethnoscience method was used in this research. The study sample consisted of 17 home care CMs, professional practice leads, and their managers from two separate home care offices. All participating CMs had assigned caseloads and were involved in the assessment and implementation of care planning for clients. Purposive sampling methods were employed. In keeping with Spradley’s ethnoscience approach, data collection occurred in three distinct phases or rounds. The first round of data collection began with a series of one-on-one interviews with card sorts, the second round of data collection was another series of one-on-one interviews with CMs who were not interviewed in the prior round, and the third and final round of data collection was a focus group to accomplish further refinement and verification of our established categories. Participants identified five categories of factors that effected their resource allocation decision-making. The categories were related to one of five main areas: the client, the CM, the home care program, community resources, or the health care system. The findings of this study reinforced the complexity of CM resource allocation decision-making in home care. This study provides new insights into CM resource allocation decision-making based on multidisciplinary, integrated home care teams caring for adults, the majority of whom are 65 years and older. This study also provides the comparison of taxonomy that differs between pediatric and adult home care populations that influence resource allocation decision-making.

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