Predictors of acute muscle loss in the intensive care unit: A secondary analysis of an in-bed cycling trial for critically ill patients

PURPOSE

The purpose of this study was to assist clinicians to identify critically ill patients at greatest risk of acute muscle loss and to analyse the associations between protein intake and exercise on acute muscle loss.

MATERIALS AND METHODS

Secondary analysis of a single-centre randomised clinical trial of in-bed cycling using a mixed effects model was undertaken to examine the association between key variables and rectus femoris cross-sectional area (RFCSA). Groups were combined, and key variables for the cohort were modified Nutrition Risk in the Critically Ill (mNUTRIC) scores within the first days following intensive care unit admission, longitudinal RFCSA measurements, percent of daily recommended protein intake, and group allocation (usual care, in-bed cycling). RFCSA ultrasound measurements were taken at baseline and days 3, 7, and 10 to quantify acute muscle loss. All patients received usual care nutritional intake while in the intensive care unit. Patients allocated to the cycling group commenced in-bed cycling once safety criteria were met.

RESULTS

Analysis included all 72 participants, of which 69% were male, with a mean (standard deviation) age of 56 (17) years. Patients received a mean (standard deviation) of 59% (26%) of the minimum protein dose recommended for critically ill patients. Mixed-effects model results indicated that patients with higher mNUTRIC scores experienced greater RFCSA loss (estimate = -0.41; 95% confidence interval [CI] = -0.59 to -0.23). RFCSA did not share a statistically significant association with cycling group allocation (estimate = -0.59, 95% CI = -1.53 to 0.34), the percentage of protein requirements received (estimate = -0.48; 95% CI = -1.16 to 0.19), or a combination of cycling group allocation and higher protein intake (estimate = 0.33, 95% CI = -0.76 to 1.43).

CONCLUSIONS AND RELEVANCE

We found that a higher mNUTRIC score was associated with greater muscle loss, but we did not observe a relationship between combined protein delivery and in-bed cycling and muscle loss. The low protein doses achieved may have impacted the potential for exercise or nutrition strategies to reduce acute muscle loss.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry (ACTRN 12616000948493).

Identifying barriers and facilitators to successful implementation of computerized clinical decision support systems in hospitals: a NASSS framework-informed scoping review

BACKGROUND

Successful implementation and utilization of Computerized Clinical Decision Support Systems (CDSS) in hospitals is complex and challenging. Implementation science, and in particular the Nonadoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework, may offer a systematic approach for identifying and addressing these challenges. This review aimed to identify, categorize, and describe barriers and facilitators to CDSS implementation in hospital settings and map them to the NASSS framework. Exploring the applicability of the NASSS framework to CDSS implementation was a secondary aim.

METHODS

Electronic database searches were conducted (21 July 2020; updated 5 April 2022) in Ovid MEDLINE, Embase, Scopus, PyscInfo, and CINAHL. Original research studies reporting on measured or perceived barriers and/or facilitators to implementation and adoption of CDSS in hospital settings, or attitudes of healthcare professionals towards CDSS were included. Articles with a primary focus on CDSS development were excluded. No language or date restrictions were applied. We used qualitative content analysis to identify determinants and organize them into higher-order themes, which were then reflexively mapped to the NASSS framework.

RESULTS

Forty-four publications were included. These comprised a range of study designs, geographic locations, participants, technology types, CDSS functions, and clinical contexts of implementation. A total of 227 individual barriers and 130 individual facilitators were identified across the included studies. The most commonly reported influences on implementation were fit of CDSS with workflows (19 studies), the usefulness of the CDSS output in practice (17 studies), CDSS technical dependencies and design (16 studies), trust of users in the CDSS input data and evidence base (15 studies), and the contextual fit of the CDSS with the user's role or clinical setting (14 studies). Most determinants could be appropriately categorized into domains of the NASSS framework with barriers and facilitators in the "Technology," "Organization," and "Adopters" domains most frequently reported. No determinants were assigned to the "Embedding and Adaptation Over Time" domain.

CONCLUSIONS

This review identified the most common determinants which could be targeted for modification to either remove barriers or facilitate the adoption and use of CDSS within hospitals. Greater adoption of implementation theory should be encouraged to support CDSS implementation.

Vital signs-based deterioration prediction model assumptions can lead to losses in prediction performance

OBJECTIVE

Vital signs-based models are complicated by repeated measures per patient and frequently missing data. This paper investigated the impacts of common vital signs modeling assumptions during clinical deterioration prediction model development.

STUDY DESIGN AND SETTING

Electronic medical record (EMR) data from five Australian hospitals (1 January 2019-31 December 2020) were used. Summary statistics for each observation's prior vital signs were created. Missing data patterns were investigated using boosted decision trees, then imputed with common methods. Two example models predicting in-hospital mortality were developed, as follows: logistic regression and eXtreme Gradient Boosting. Model discrimination and calibration were assessed using the C-statistic and nonparametric calibration plots.

RESULTS

The data contained 5,620,641 observations from 342,149 admissions. Missing vitals were associated with observation frequency, vital sign variability, and patient consciousness. Summary statistics improved discrimination slightly for logistic regression and markedly for eXtreme Gradient Boosting. Imputation method led to notable differences in model discrimination and calibration. Model calibration was generally poor.

CONCLUSION

Summary statistics and imputation methods can improve model discrimination and reduce bias during model development, but it is questionable whether these differences are clinically significant. Researchers should consider why data are missing during model development and how this may impact clinical utility.

Evaluating the costs and consequences of computerized clinical decision support systems in hospitals: a scoping review and recommendations for future practice

OBJECTIVE

Sustainable investment in computerized decision support systems (CDSS) requires robust evaluation of their economic impacts compared with current clinical workflows. We reviewed current approaches used to evaluate the costs and consequences of CDSS in hospital settings and presented recommendations to improve the generalizability of future evaluations.

MATERIALS AND METHODS

A scoping review of peer-reviewed research articles published since 2010. Searches were completed in the PubMed, Ovid Medline, Embase, and Scopus databases (last searched February 14, 2023). All studies reported the costs and consequences of a CDSS-based intervention compared with current hospital workflows. Findings were summarized using narrative synthesis. Individual studies were further appraised against the Consolidated Health Economic Evaluation and Reporting (CHEERS) 2022 checklist.

RESULTS

Twenty-nine studies published since 2010 were included. Studies evaluated CDSS for adverse event surveillance (5 studies), antimicrobial stewardship (4 studies), blood product management (8 studies), laboratory testing (7 studies), and medication safety (5 studies). All studies evaluated costs from a hospital perspective but varied based on the valuation of resources affected by CDSS implementation, and the measurement of consequences. We recommend future studies follow guidance from the CHEERS checklist; use study designs that adjust for confounders; consider both the costs of CDSS implementation and adherence; evaluate consequences that are directly or indirectly affected by CDSS-initiated behavior change; examine the impacts of uncertainty and differences in outcomes across patient subgroups.

DISCUSSION AND CONCLUSION

Improving consistency in the conduct and reporting of evaluations will enable detailed comparisons between promising initiatives, and their subsequent uptake by decision-makers.

Integrating economic considerations into cutpoint selection may help align clinical decision support toward value-based healthcare

Objective

Clinical prediction models providing binary categorizations for clinical decision support require the selection of a probability threshold, or “cutpoint,” to classify individuals. Existing cutpoint selection approaches typically optimize test-specific metrics, including sensitivity and specificity, but overlook the consequences of correct or incorrect classification. We introduce a new cutpoint selection approach considering downstream consequences using net monetary benefit (NMB) and through simulations compared it with alternative approaches in 2 use-cases: (i) preventing intensive care unit readmission and (ii) preventing inpatient falls.

Materials and methods

Parameter estimates for costs and effectiveness from prior studies were included in Monte Carlo simulations. For each use-case, we simulated the expected NMB resulting from the model-guided decision using a range of cutpoint selection approaches, including our new value-optimizing approach. Sensitivity analyses applied alternative event rates, model discrimination, and calibration performance.

Results

The proposed approach that considered expected downstream consequences was frequently NMB-maximizing compared with other methods. Sensitivity analysis demonstrated that it was or closely tracked the optimal strategy under a range of scenarios. Under scenarios of relatively low event rates and discrimination that may be considered realistic for intensive care (prevalence = 0.025, area under the receiver operating characteristic curve [AUC] = 0.70) and falls (prevalence = 0.036, AUC = 0.70), our proposed cutpoint method was either the best or similar to the best of the compared methods regarding NMB, and was robust to model miscalibration.

Discussion

Our results highlight the potential value of conditioning cutpoints on the implementation setting, particularly for rare and costly events, which are often the target of prediction model development research.

Conclusions

This study proposes a cutpoint selection method that may optimize clinical decision support systems toward value-based care.

A Bayesian Approach for Incorporating the EQ-5D Visual Analog Scale When Estimating the Health-Related Quality of Life

OBJECTIVES

The EuroQoL 3-level version of EQ-5D and 5-level version of EQ-5D questionnaires are often used to quantify health states. They include ordinal responses across 5 health dimensions (EQ-5D index) and an EQ-visual analog scale (EQ-VAS) overall health rating. We investigated the value of incorporating the EQ-VAS to update health utility estimates using a Bayesian framework.

METHODS

We created a joint bivariate normal EQ-VAS and EQ-5D index utility model and compared this to a univariate normal EQ-5D index utility model. We tested these models for 1026 Sri Lankan patients with chronic kidney disease and 94 Australian patients with wounds. We validated our approach by simulating EQ-VAS and EQ-5D index responses and applying our Bayesian model and then comparing the modeled estimates to our observed data.

RESULTS

The combined model showed a reduction in estimate uncertainty for all respondents. Compared with the EQ-5D index-only model, the mean utility for Sri Lankan respondents dropped from 0.556 (0.534-0.579) to 0.540 (0.521-0.559) in men and increased from 0.489 (0.461-0.518) to 0.528 (0.506-0.550) in women, with reduced credible interval width by 13% and 23%, respectively. The mean utility in Australian respondents moved from 0.715 (0.633-0.800) to 0.716 (0.652-0.782) in men, and 0.652 (0.581-0.723) to 0.652 (0.593-0.711) in women, with reduced credible interval width by 23% and 17%, respectively. The credible interval width for simulated data also narrowed, ranging from 8.3 to 8.5%.

CONCLUSIONS

Including the EQ-VAS through Bayesian methods can add value by reducing requisite sample sizes and decision uncertainty using small amounts of additional data that is often collected but rarely used.

A scoping review of real-time automated clinical deterioration alerts and evidence of impacts on hospitalised patient outcomes

BACKGROUND

Hospital patients experiencing clinical deterioration are at greater risk of adverse events. Monitoring patients through early warning systems is widespread, despite limited published evidence that they improve patient outcomes. Current limitations including infrequent or incorrect risk calculations may be mitigated by integration into electronic medical records. Our objective was to examine the impact on patient outcomes of systems for detecting and responding to real-time, automated alerts for clinical deterioration.

METHODS

This review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews checklist. We searched Medline, CINAHL and Embase for articles implementing real-time, automated deterioration alerts in hospitalised adults evaluating one or more patient outcomes including intensive care unit admission, length of stay, in-hospital cardiopulmonary arrest and in-hospital death.

RESULTS

Of 639 studies identified, 18 were included in this review. Most studies did not report statistically significant associations between alert implementation and better patient outcomes. Four studies reported statistically significant improvements in two or more patient outcomes, and were the only studies to directly involve the patient's clinician. However, only one of these four studies was robust to existing trends in patient outcomes. Of the six studies using robust study designs, one reported a statistically significant improvement in patient outcomes; the rest did not detect differences.

CONCLUSIONS

Most studies in this review did not detect improvements in patient outcomes following the implementation of real-time deterioration alerts. Future implementation studies should consider: directly involving the patient's physician or a dedicated surveillance nurse in structured response protocols for deteriorating patients; the workflow of alert recipients; and incorporating model features into the decision process to improve clinical utility.

Patient and economic impact of implementing a paediatric sepsis pathway in emergency departments in Queensland, Australia

We examined systems-level costs before and after the implementation of an emergency department paediatric sepsis screening, recognition and treatment pathway. Aggregated hospital admissions for all children aged < 18y with a diagnosis code of sepsis upon admission in Queensland, Australia were compared for 16 participating and 32 non-participating hospitals before and after pathway implementation. Monte Carlo simulation was used to generate uncertainty intervals. Policy impacts were estimated using difference-in-difference analysis comparing observed and expected results. We compared 1055 patient episodes before (77.6% in-pathway) and 1504 after (80.5% in-pathway) implementation. Reductions were likely for non-intensive length of stay (− 20.8 h [− 36.1, − 8.0]) but not intensive care (–9.4 h [− 24.4, 5.0]). Non-pathway utilisation was likely unchanged for interhospital transfers (+ 3.2% [− 5.0%, 11.4%]), non-intensive (− 4.5 h [− 19.0, 9.8]) and intensive (+ 7.7 h, [− 20.9, 37.7]) care length of stay. After difference-in-difference adjustment, estimated savings were 596 [277, 942] non-intensive and 172 [148, 222] intensive care days. The program was cost-saving in 63.4% of simulations, with a mean value of $97,019 [− $857,273, $1,654,925] over 24 months. A paediatric sepsis pathway in Queensland emergency departments was associated with potential reductions in hospital utilisation and costs.

Resource use and costs associated with epilepsy in the Queensland hospital system: protocol for a population-based data linkage study

INTRODUCTION

Epilepsy places a large burden on health systems, with hospitalisations for seizures alone occurring more frequently than those related to diabetes. However, the cost of epilepsy to the Australian health system is not well understood. The primary aim of this study is to quantify the health service use and cost of epilepsy in Queensland, Australia. Secondary aims are to identify differences in health service use and cost across population and disease subgroups, and to explore the associations between health service use and common comorbidities.

METHODS AND ANALYSIS

This project will use data linkage to identify the health service utilisation and costs associated with epilepsy. A base cohort of patients will be identified from the Queensland Hospital Admitted Patient Data Collection. We will select all patients admitted between 2014 and 2018 with a diagnosis classification related to epilepsy. Two comparison cohorts will also be identified. Retrospective hospital admissions data will be linked with emergency department presentations, clinical costing data, specialist outpatient and allied health occasions of service data and mortality data. The level of health service use in Queensland, and costs associated with this, will be quantified using descriptive statistics. Difference in health service costs between groups will be explored using logistic regression. Linear regression will be used to model the associations of interest. The analysis will adjust for confounders including age, sex, comorbidities, indigenous status, and remoteness.

ETHICS AND DISSEMINATION

Ethical approval has been obtained through the QUT University Human Research Ethics Committee (1900000333). Permission to waive consent has been granted under the Public Health Act 2005, with approval provided by all relevant data custodians. Findings of the proposed research will be communicated through presentations at national and international conferences, presentations to key stakeholders and decision-makers, and publications in international peer-reviewed journals.

The burden of COVID-19 infection in a rural Tamil Nadu community

Background

There have been over 30 million cases of COVID-19 in India and over 430,000 deaths. Transmission rates vary from region to region, and are influenced by many factors including population susceptibility, travel and uptake of preventive measures. To date there have been relatively few studies examining the impact of the pandemic in lower income, rural regions of India. We report on a study examining COVID-19 burden in a rural community in Tamil Nadu.

Methods

The study was undertaken in a population of approximately 130,000 people, served by the Rural Unit of Health and Social Affairs (RUHSA), a community health center of CMC, Vellore. We established and evaluated a COVID-19 PCR-testing programme for symptomatic patients—testing was offered to 350 individuals, and household members of test-positive cases were offered antibody testing. We also undertook two COVID-19 seroprevalence surveys in the same community, amongst 701 randomly-selected individuals.

Results

There were 182 positive tests in the symptomatic population (52.0%). Factors associated with test-positivity were older age, male gender, higher socioeconomic status (SES, as determined by occupation, education and housing), a history of diabetes, contact with a confirmed/suspected case and attending a gathering (such as a religious ceremony, festival or extended family gathering). Amongst test-positive cases, 3 (1.6%) died and 16 (8.8%) suffered a severe illness. Amongst 129 household contacts 40 (31.0%) tested positive. The two seroprevalence surveys showed positivity rates of 2.2% (July/Aug 2020) and 22.0% (Nov 2020). 40 tested positive (31.0%, 95% CI: 23.02 − 38.98). Our estimated infection-to-case ratio was 31.7.

Conclusions

A simple approach using community health workers and a community-based testing clinic can readily identify significant numbers of COVID-19 infections in Indian rural population. There appear, however, to be low rates of death and severe illness, although vulnerable groups may be under-represented in our sample. It’s vital these lower income, rural populations aren’t overlooked in ongoing pandemic monitoring and vaccine roll-out in India.

Economic Analysis of Specialist Referral Patterns in Mackay, Queensland Following HealthPathways Implementation

INTRODUCTION

HealthPathways is a clinical information portal developed in New Zealand that enables general practitioners to manage and refer their patients in a local context. We analyzed specialist outpatient appointment costs in Mackay, Queensland before and after HealthPathways implementation.

METHODS

We retrospectively examined specialist outpatient costs for patients referred by Mackay general practitioners for conditions with varying levels of HealthPathways implementation. Ranked from most clinical pathways available to none, chronic diabetes, cardiology, respiratory, and urology visits from January to March 2015, pre-pathways, and January to March 2017, post-pathways, were assessed. Monte Carlo simulation was used to estimate cost changes. Per-visit costs were multiplied by visit numbers to estimate policy impact.

RESULTS

The mean cost per visit increased from $220 to $305 for diabetes and $270 to $323 for respiratory, and decreased from $296 to $257 for cardiology and $444 to $293 for urology. The policy impact for each disease group over 3 months after accounting for visit numbers was a likely saving of $30 360 for diabetes and $10 270 for cardiology, and a likely cost increase of $24 449 for respiratory and $20 536 for urology.

CONCLUSIONS

We observed that conditions with more comprehensive clinical pathways cost Mackay HHS substantially less following implementation. Costs for low and no pathway implementation referrals increased slightly over the same period.

Adherence to best practice: Preventing surgical site infection following caesarean section in Australia

BACKGROUND

Surgical site infection (SSI) following caesarean section is a serious but underreported problem with an estimated incidence of 5-9%. It is essential to identify adherence to established prevention strategies to reduce the incidence rate.

AIMS

The aims of this study were to quantify unwarranted variation from evidence-based practice on the prevention of SSI at caesarean section in Australia; and to identify predictors of not implementing an existing infection prevention bundle: pre-incision antibiotic prophylaxis, vaginal preparation and spontaneous placenta removal.

MATERIALS AND METHODS

An online cross-sectional survey of obstetricians and obstetric Diplomates was conducted in 2016. The primary outcome was adherence to an existing infection prevention bundle, with demographic and clinical variables predicting adherence through multivariable binary logistic regression.

RESULTS

Forty-nine percent of respondents (response rate 39.6%) reported implementing zero or only one element of the infection prevention bundle. The types of respondents most likely to have poor adherence were Diplomates (adjusted odds ratio (aOR) 2.58), obstetricians practising in private hospitals (aOR 3.34), those usually practising in public and private hospitals (aOR 2.23), and those not usually implementing a surgical safety checklist (aOR 3.77).

CONCLUSIONS

Adherence to best practice at caesarean section is low among many Australian obstetricians. Infection control practitioners and obstetricians need to collaboratively implement surgical safety checklists at caesarean section, and monitor implementation using process key performance indicators, and audit and feedback. These strategies will reduce unwarranted variation from evidence-based infection control practice.

151 Optimising Bone Health on Sheffield Frailty Unit Through Quality Improvement

Introduction

NICE and the National Osteoporosis Guidance Group (NOGG) advise on evaluation of fracture risk and osteoporosis treatment1,2, with evidence suggesting that screening and treatment reduces the risk of fragility fractures 3,4,5. However, it is often overlooked in the management of older patients within secondary care. Audit data from Sheffield Frailty Unit (SFU) in 2018 showed that national guidance was not routinely followed. Fracture Risk Assessment Tool (FRAX®) scores were not calculated and bone health was poorly managed. Therefore, we undertook a quality improvement project aiming to optimise bone health in patients presenting to SFU.

Method & Intervention

In January 2019 we collaborated with Sheffield Metabolic Bone Centre (MBC) to develop a pathway aiming to improve bone health assessment and management in patients presenting to SFU with a fall or fragility fracture. This included a user-friendly flow chart with accompanying guidelines, alongside education for staff. Performance was re-evaluated in May 2019, following which a tick box prompt was added to post take ward round documentation. A re-audit was performed in March 2020.

Results

In March 2018 0% of patients presenting with a fall had a FRAX® score calculated and only 40% of those with a new fragility fracture were managed according to guidelines. In May 2019, this had improved to 18% and 100% respectively. In March 2020 86% of patients had a FRAX® score calculated appropriately and 100% of fragility fractures were managed according to guidelines. In both re-audits 100% of FRAX® scores were acted on appropriately.

Conclusions

There has been a significant increase in the number of patients who have their bone health appropriately assessed and managed after presenting to SFU. However, achieving optimum care is under constant review with the aim to deliver more treatment on SFU, thereby reducing the need for repeat visits to the MBC.

Review of methods and study designs of evaluations related to clinical pathways

Objective The HealthPathways program is an online information portal that helps clinicians provide consistent and integrated patient care within a local health system through localised pathways for diagnosis, treatment and management of various health conditions. These pathways are consistent with the definition of clinical pathways. Evaluations of HealthPathways programs have thus far focused primarily on website utilisation and clinical users' experience and satisfaction, with limited evidence on changes to patient outcomes. This lack motivated a literature review of the effects of clinical pathways on patient and economic outcomes to inform a subsequent HealthPathways evaluation. Methods A systematic review was performed to summarise the analytical methods, study designs and results of studies evaluating clinical pathways with an economic outcome component published between 1 January 2000 and 31 August 2017 in four academic literature databases. Results Fifty-five relevant articles were identified for inclusion in this review. The practical pre-post study design with retrospective baseline data extraction and prospective intervention data collection was most commonly used in the evaluations identified. Straightforward statistical methods for comparing outcomes, such as the t-test or χ2 test, were frequently used. Only four of the 55 articles performed a cost-effectiveness analysis. Clinical pathways were generally associated with improved patient outcomes and positive economic outcomes in hospital settings. Conclusions Clinical pathways evaluations commonly use pragmatic study designs, straightforward statistical tests and cost-consequence analyses. More HealthPathways program evaluations focused on patient and economic outcomes, clinical pathway evaluations in a primary care setting and cost-effectiveness analyses of clinical pathways are needed. What is known about the topic? HealthPathways is a web-based program that originated from Canterbury, New Zealand, and has seen uptake elsewhere in New Zealand, Australia and the UK. The HealthPathways program aims to assist the provision of consistent and integrated health services through dedicated, localised pathways for various health conditions specific to the health region. Evaluations of HealthPathways program focused on patient and economic outcomes have been limited. What does this paper add? This review synthesises the academic literature of clinical pathways evaluations in order to inform a subsequent HealthPathways evaluation. The focus of the synthesis was on the analytical methods and study designs used in the previous evaluations. The previous clinical pathway evaluations have been pragmatic in nature with relatively straightforward study designs and analysis. What are the implications for practitioners? There is a need for more economic and patient outcome evaluations for HealthPathways programs. More sophisticated statistical analyses and economic evaluations could add value to these evaluations, where appropriate and taking into consideration the data limitations.

Fixation Method for Hip Arthroplasty Stem Following Hip Fracture: A Population-Level Cost-Effectiveness Analysis

BACKGROUND

Hip arthroplasty is increasing in Australia. The number of procedures for fractured neck of femur was 7500 in 2017. Best practices for fixation method and procedure type require scrutiny. This paper is about the costs and health outcomes of cemented and uncemented hemiarthroplasty and total hip arthroplasty at a national level.

METHODS

We created a Markov model for patients <75, aged 75-85, and over 85. Expected costs and health outcomes over 5 years from a decision to change from existing practice to a best practice policy in which all patients with fractured neck of femur received the same fixation method based on age and type of arthroplasty are estimated. The model was populated using prevalence and incidence data from the Australian Orthopedic Association National Joint Replacement Registry, costs from Metro North Hospital and Health Service in Queensland, and probabilities and utilities from the literature. We simulated the uncertainties in outcomes with probabilistic sensitivity analysis.

RESULTS

We found that uncemented stem procedures were more costly and provided worse health outcomes compared to cemented stem fixation for hemiarthroplasty and total hip arthroplasty for all age groups. Moving from existing practice to cemented stem arthroplasty could save the Australian health system $2.0 million over 5 years with a gain of 203 quality-adjusted life years.

CONCLUSION

We suggest that consideration be given to cemented fixation of the femoral stem for patients receiving both hemiarthroplasty and total hip arthroplasty for fractured neck of femur. Best practice guidelines focused on cost-effectiveness should recommend cemented stem fixation to both save costs and improve patient quality of life.

Fits, faints, falls and funny turns: cost and capacity savings in Queensland from the accelerated transient attack pathway initiative (ATAP)

BACKGROUND

falls, seizures, syncope and transient ischaemic attacks (TIA) are common presentations to emergency departments sharing overlapping clinical features and diagnostic uncertainties. These transient attacks can be markers of serious adverse outcomes and are associated with high admission rates. We evaluated the effects of an integrated suite of pathways for transient attacks designed to improve adherence to best practices and reduce costs through fewer admissions.

METHODS

a suite of clinician-designed pathways based on initial presenting diagnosis was developed to support ambulant care in a large hospital in Queensland, Australia. We performed a set of regression analyses to identify the differences in total cost and length of stay (LOS) before and after implementation. We conducted a Monte Carlo simulation to estimate the cost savings of the freed capacity in the patient cohort.

RESULTS

pathway implementation was associated with reduced admitted LOS and costs. Falls patients admitted LOS declined by 32.5%, and admission costs by 19.5%. Syncope, seizure, and TIA patients admitted LOS declined by 22% with no change in admitted costs. Despite a small increase in 90-day representations, total emergency department LOS was unchanged. Emergency department costs were similar between falls and non-falls patients. The Monte Carlo analysis showed that the most likely outcome was a cost savings in freed capacity of $71 per patient episode.

CONCLUSION

the ATAP suite of pathways was associated with reduction in LOS, release of capacity and reduction in costs. Further study is needed to evaluate mechanisms and clinical outcomes in this vulnerable population.

Development and pilot of a multicriteria decision analysis (MCDA) tool for health services administrators

INTRODUCTION

Health administration is complex and serves many masters. Value, quality, infrastructure and reimbursement are just a sample of the competing interests influencing executive decision-making. This creates a need for decision processes that are rational and holistic.

METHODS

We created a multicriteria decision analysis tool to evaluate six fields of healthcare provision: return on investment, capacity, outcomes, safety, training and risk. The tool was designed for prospective use, at the beginning of each funding round for competing projects. Administrators were asked to rank their criteria in order of preference. Each field was assigned a representative weight determined from the rankings. Project data were then entered into the tool for each of the six fields. The score for each field was scaled as a proportion of the highest scoring project, then weighted by preference. We then plotted findings on a cost-effectiveness plane. The project was piloted and developed over successive uses by the hospital's executive board.

RESULTS

Twelve projects competing for funding at the Royal Brisbane and Women's Hospital were scored by the tool. It created a priority ranking for each initiative based on the weights assigned to each field by the executive board. Projects were plotted on a cost-effectiveness plane with score as the x-axis and cost of implementation as the y-axis. Projects to the bottom right were considered dominant over projects above and to the left, indicating that they provided greater benefit at a lower cost. Projects below the x-axis were cost-saving and recommended provided they did not harm patients. All remaining projects above the x-axis were then recommended in order of lowest to highest cost-per-point scored.

CONCLUSION

This tool provides a transparent, objective method of decision analysis using accessible software. It would serve health services delivery organisations that seek to achieve value in healthcare.

Scepticaemia: The impact on the health system and patients of delaying new treatments with uncertain evidence; a case study of the sepsis bundle

BACKGROUND

A sepsis care bundle of intravenous vitamin C, thiamine, and hydrocortisone was reported to improve treatment outcomes. The data to support it are uncertain and decision makers are likely to be cautious about adopting it. The objective of this study was to model the opportunity costs in dollars and lives of waiting for better information before adopting the bundle.

METHODS

A decision tree was built using information from the literature. We modelled the impact of bundle adoption under three scenarios using a simulation in which the bundle was effective as reported in the primary trial, less effective based on other information, and ineffective. The measurements were health services costs, quality-adjusted life years, and transition probabilities.

RESULTS

If the bundle proves to be effective under either scenario, it will save billions of dollars and millions of life-years in the United States. This is the opportunity cost of delaying an adoption decision and waiting for better quality evidence. We suggest that hospital decision-makers consider implementing the bundle on a trial basis while monitoring costs and outcomes data even while the evidence base is uncertain.

CONCLUSIONS

If the decision maker is unwilling to use the best available evidence now, but rather wishes to wait for definitive evidence they are risking incurring large costs for health care systems and for the patients they serve. An explicit analysis of uncertain clinical outcomes is a useful adjunct to guide decision making where there is clinical ambiguity. This approach offers a valid alternative to the default of clinical inactivity when faced with uncertainty.

Infusion confusion brought to book

While thanking Douglas Middleton for his positive and constructive review of our book, Guidelines for Clinical Nursing Practices viewpoint, August 18), we would like to make a couple of points.

Infrared images of natural subjects

Images of a number of natural subjects have for some time been made using wavelengths longer than those to which film is sensitive. This has been done by use of instruments employing mechanical scanning and cooled semiconductor detectors. Some of this imagery is now becoming available for general use. In this paper, we describe some of the physical effects causing observable changes in the imagery, comment upon some of those factors observed in a selected set of images of both natural and man-made features recorded by the Bendix thermal mapper, and suggest some uses and potential uses for such data for some scientific and general purposes.