The costs of risk and fear: a qualitative study of risk conceptualisations in allied health resource allocation decision-making

2019 ◽  
Vol 21 (7-8) ◽  
pp. 373-389
Author(s):  
Kellie Grant ◽  
Jenni White ◽  
Jenny Martin ◽  
Terry Haines
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Qualitative Study ◽  
Allied Health ◽  
Resource Allocation Decision ◽  
Health Resource ◽  
Allocation Decision ◽  
Health Resource Allocation

scholarly journals Translating evidence into practice: a longitudinal qualitative exploration of allied health decision-making

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jennifer White ◽  
◽  
Kellie Grant ◽  
Mitchell Sarkies ◽  
Terrence Haines
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Allied Health ◽  
Health Resource ◽  
Health Resource Allocation ◽  
Randomized Controlled ◽  
Group 2 ◽  
Allocation Decisions ◽  
Resource Allocation Decisions ◽  
Health Managers

Abstract Background Health policy and management decisions rarely reflect research evidence. As part of a broader randomized controlled study exploring implementation science strategies we examined how allied health managers respond to two distinct recommendations and the evidence that supports them. Methods A qualitative study nested in a larger randomized controlled trial. Allied health managers across Australia and New Zealand who were responsible for weekend allied health resource allocation decisions towards the provision of inpatient service to acute general medical and surgical wards, and subacute rehabilitation wards were eligible for inclusion. Consenting participants were randomized to (1) control group or (2) implementation group 1, which received an evidence-based policy recommendation document guiding weekend allied health resource allocation decisions, or (3) implementation group 2, which received the same policy recommendation document guiding weekend allied health resource allocation decisions with support from a knowledge broker. As part of the trial, serial focus groups were conducted with a sample of over 80 allied health managers recruited to implementation group 2 only. A total 17 health services participated in serial focus groups according to their allocated randomization wave, over a 12-month study period. The primary outcome was participant perceptions and data were analysed using an inductive thematic approach with constant comparison. Thematic saturation was achieved. Results Five key themes emerged: (1) Local data is more influential than external evidence; (2) How good is the evidence and does it apply to us? (3) It is difficult to change things; (4) Historically that is how we have done things; and (5) What if we get complaints? Conclusions This study explored implementation of strategies to bridge gaps in evidence-informed decision-making. Results provide insight into barriers, which prevent the implementation of evidence-based practice from fully and successfully occurring, such as attitudes towards evidence, limited skills in critical appraisal, and lack of authority to promote change. In addition, strategies are needed to manage the risk of confirmation biases in decision-making processes. Trial registration This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) (ACTRN12618000029291). Universal Trial Number (UTN): U1111-1205-2621.

scholarly journals Translating evidence into practice: A longitudinal qualitative exploration of allied health decision making.

2020 ◽  
Author(s):  
Jennifer White ◽  
Kellie Grant ◽  
Mitchell Sarkies ◽  
Terrence Haines
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Focus Groups ◽  
Allied Health ◽  
Policy Recommendation ◽  
Health Resource ◽  
Health Resource Allocation ◽  
Allocation Decisions ◽  
Resource Allocation Decisions ◽  
Health Managers

Abstract BackgroundHealth policy and management decisions rarely reflect research evidence. In response, it is important to determine how to improve evidence-informed decision-making. As part of a broader study exploring implementation science strategies we examined how allied health managers respond to two distinct recommendations and the evidence that supports them. MethodsAllied health managers across Australia and New Zealand who were responsible for weekend allied health resource allocation decisions towards the provision of inpatient service to acute general medical and surgical wards, and sub-acute rehabilitation wards were eligible for inclusion. Consenting participants were randomised to: (1) control group or; (2) Implementation Group 1: received an evidence-based policy recommendation document guiding weekend allied health resource allocation decisions, or (3) Implementation Group 2: received the same policy recommendation document guiding weekend allied health resource allocation decisions with support from a knowledge broker. Serial focus groups were conducted with a sample of over 80 allied health managers recruited to Implementation Group 2 only. Out of 6 waves of recruitment, up to four focus groups were conducted with each wave during the 12 months study period. In total 17 health services participated in serial focus groups according to their allocated wave, over a 12-month study period. Data were analysed using an inductive thematic approach with constant comparison. Thematic saturation was achieved.ResultsResults provide insights into resource allocation and decision-making, including the interplay between barriers and facilitators concerning implementation of recommendations outlined in evidence-based policy recommendation document. Five key themes emerged: (1) Local data trumps, or is more influential; (2) How good is the evidence and does it apply to us; (3) It is difficult to change things; (4) Historically that’s how we have done things; and (5) What if we get complaints?ConclusionsThis study explored implementation of strategies to bridge gaps in evidence-informed decision-making. Results provide insight into barriers, which prevent the implementation of evidence base practice from fully, and successfully occurring such as attitudes towards evidence, limited skills in critical appraisal, and lack of authority to promote change. In addition, strategies are needed to manage the risk of confirmation biases in decision-making processes.

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.

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