What Factors Do Allied Health Take Into Account When Making Resource Allocation Decisions?

An ethnographic study was conducted in 2 stages to understand how allied health professionals define and apply equity when making resource allocation decisions. Participants were allied health managers and clinicians from Victoria, Australia. Stage 1 included 4 semi-structured forums that incorporated real-life case studies, group discussions, and hypothetical scenarios. The project’s steering committee began a thematic analysis during post-forum discussions. Stage 2 included a key stakeholder working party that further discussed the concept of equity. The forum recordings were transcribed verbatim, and a detailed thematic analysis ensured the initial thematic analysis was complete. Several domains of equity were discussed. Participants would readily identify that equity was a consideration when making resource decisions but were generally silent for a prolonged period when prompted to identify what they meant when using this term. The findings indicate that asking allied health professionals to directly state how they define and apply equity to their decision-making could be too difficult a task, as this did not elicit rich and meaningful discussions. Future research should examine individual domains of equity when applied to resource allocation decisions.

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

Health Research Policy and Systems ◽

10.1186/s12961-020-00662-1 ◽

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.

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

10.21203/rs.2.19845/v1 ◽

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.

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Unexpected Consequences: The Effects on Non-Accelerated Filers of an Accelerated Filing Deadline and SOX Section 404

Accounting Horizons ◽

10.2308/horizons-18-066 ◽

2020 ◽

Vol 34 (3) ◽

pp. 87-112

Author(s):

Bei Dong ◽

Stefanie L. Tate ◽

Le Emily Xu

Keyword(s):

Resource Allocation ◽

Financial Statements ◽

Financial Statement ◽

Negative Consequences ◽

Section 404 ◽

Auditor Change ◽

Time Required ◽

Allocation Decisions ◽

Jel Classifications ◽

Resource Allocation Decisions

SYNOPSIS Regulations implemented by the SEC in 2003 and 2004 simultaneously shortened the financial statement filing deadlines and increased the time required for both the preparation of financial statements and the related audit of accelerated filers (AFs). However, there were indirect, unintended negative consequences for companies not subject to the regulations, namely, non-accelerated filers (NAFs). The new regulations imposed strains on auditor resources requiring auditors to make resource allocation decisions that negatively affected NAFs. We find that NAFs with an auditor who had a high proportion of AF clients (high-AF) had longer audit delays after the regulations were implemented than NAFs of an auditor with a low proportion of AF clients (low-AF). Further, we document that NAFs with high-AF auditors were more likely to change auditors than NAFs with low-AF auditors. Finally, NAFs that switched to auditors with less AFs experienced shorter audit delays after the auditor change. JEL Classifications: M42; M48.

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19 The role of trust in global resource allocation decisions for vaccine preventable diseases

10.1136/bmjopen-2021-qhrn.57 ◽

2021 ◽

Author(s):

P Christen ◽

L Conteh

Keyword(s):

Resource Allocation ◽

Vaccine Preventable Diseases ◽

Allocation Decisions ◽

Resource Allocation Decisions

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Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

Health Care Management Science ◽

10.1007/s10729-021-09548-2 ◽

2021 ◽

Author(s):

G.J. Melman ◽

A.K. Parlikad ◽

E.A.B. Cameron

Keyword(s):

Resource Allocation ◽

Discrete Event Simulation ◽

Elective Surgery ◽

Discrete Event ◽

Specific Patient ◽

Event Simulation ◽

The Impact ◽

Allocation Decisions ◽

Allocation Strategies ◽

Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

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A Common Approach to Risk Analysis Methodology

Pressure Vessel and Piping Codes and Standards ◽

10.1115/pvp2003-1809 ◽

2003 ◽

Author(s):

J. Robert Sims

Keyword(s):

Resource Allocation ◽

Risk Analysis ◽

Broad Spectrum ◽

Analysis Methodology ◽

Risk Ranking ◽

Homeland Defense ◽

Narrow Area ◽

Allocation Decisions ◽

Resource Allocation Decisions

Risk analysis has been used extensively to inform decisions throughout government and industry for many years. Many methodologies have been developed to perform these analyses, resulting in differences in terminology and approach that make it difficult to compare the results of an analysis in one field to that in another. In particular, many approaches result only in a risk ranking within a narrow area or field of interest, so the results cannot be compared to rankings in other areas or fields. However, dealing with terrorist threats requires prioritizing the allocation of homeland defense resources across a broad spectrum of possible targets. Therefore, a common approach is needed to allow comparison of risks. This presentation summarizes an approach that will allow the results of risk analyses based on using current methodologies to be expressed in a common format with common terminology to facilitate resource allocation decisions.

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