Costs in conservation: Common costly mistakes and how to avoid them.

There has been an increasingly prevalent message that data regarding costs must be included in conservation planning activities to make cost-efficient decisions. Despite the growing acceptance that socioeconomic context is critical to conservation success, the approaches to embedded economic and financial considerations into planning have not significantly evolved. Inappropriate cost data is frequently included in decisions, with the potential of compromising biodiversity and social outcomes. For each conservation planning step, this essay details common mistakes made when considering costs, proposing solutions to enable conservation managers to know when and how to include costs. Appropriate use of high-quality cost data obtained at the right scale will improve decision-making and ultimately avoid costly mistakes.

Planning cost-effective operational forest inventories.

We address a Bayesian two-stage decision problem in operational forestry where the inner stage considers scheduling the harvesting to fulfill demand targets and the outer stage considers selecting the accuracy of pre-harvest inventories that are used to estimate the timber volumes of the forest tracts. The higher accuracy of the inventory enables better scheduling decisions but also implies higher costs. We focus on the outer stage, which we formulate as a maximization of the posterior value of the inventory decision under a budget constraint. The posterior value depends on the solution to the inner stage problem and its computation is analytically intractable, featuring an NP-hard binary optimization problem within a high-dimensional integral. In particular, the binary optimization problem is a special case of a generalized quadratic assignment problem. We present a practical method that solves the outer stage problem with an approximation which combines Monte Carlo sampling with a greedy, randomized method for the binary optimization problem. We derive inventory decisions for a dataset of 100 Swedish forest tracts across a range of inventory budgets and estimate the value of the information to be obtained.

Behaviour change interventions to improve physical activity in adults: a systematic review of economic evaluations.

BACKGROUND: Behaviour change interventions can result in lasting improvements in physical activity (PA). A broad implementation of behaviour change interventions are likely to be associated with considerable additional costs, and the evidence is unclear whether they represent good value for money. The aim of this study was to investigate costs and cost-effectiveness of behaviour change interventions to increase PA in community-dwelling adults. METHODS: A search for trial-based economic evaluations investigating behaviour change interventions versus usual care or alternative intervention for adults living in the community was conducted (September 2023). Studies that reported intervention costs and incremental cost-effectiveness ratios (ICERs) for PA or quality-adjusted life years (QALYs) were included. Methodological quality was assessed using the Consensus Health Economic Criteria (CHEC-list). A Grading of Recommendations Assessment, Development and Evaluation style approach was used to assess the certainty of evidence (low, moderate or high certainty). RESULTS: Sixteen studies were included using a variety of economic perspectives. The behaviour change interventions were heterogeneous with 62% of interventions being informed by a theoretical framework. The median CHEC-list score was 15 (range 11 to 19). Median intervention cost was US$313 per person (range US$83 to US$1,298). In 75% of studies the interventions were reported as cost-effective for changes in PA (moderate certainty of evidence). For cost per QALY/gained, 45% of the interventions were found to be cost-effective (moderate certainty of evidence). No specific type of behaviour change intervention was found to be more effective. CONCLUSIONS: There is moderate certainty that behaviour change interventions are cost-effective approaches for increasing PA. The heterogeneity in economic perspectives, intervention costs and measurement should be considered when interpreting results. There is a need for increased clarity when reporting the functional components of behaviour change interventions, as well as the costs to implement them.

Challenges of Incorporating Life Cycle Drug Pricing in Cost-Effectiveness Models: A Review of Methods and Modeling Suggestions.

OBJECTIVES: This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA. METHODS: Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue. RESULTS: We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results. CONCLUSION: Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations.

Do Quality-Adjusted Life Years Discriminate Against the Elderly? An Empirical Analysis of Published Cost-Effectiveness Analyses.

OBJECTIVES: Critics of quality-adjusted life-years argue that it discriminates against older individuals. However, little empirical evidence has been produced to inform this debate. This study aimed to compare published cost-effectiveness analyses (CEAs) on patients aged ≥65 years and those aged <65 years. METHODS: We used the Tufts Cost-Effectiveness Analysis Registry to identify CEAs published in MEDLINE between 1976 and 2021. Eligible CEAs were categorized according to age (≥65 years vs <65 years). The distributions of incremental cost-effectiveness ratios (ICERs) were compared between the age groups. We used logistic regression to assess the association between age groups and the cost-effectiveness conclusion adjusted for confounding factors. We conducted sensitivity analyses to explore the impact of mixed age and age-unknown groups and all ICERs from the same CEAs. Subgroup analyses were also conducted. RESULTS: A total of 4445 CEAs categorized according to age <65 years (n = 3784) and age ≥65 years (n = 661) were included in the primary analysis. The distributions of ICERs and the likelihood of concluding that the intervention was cost-effective were similar between the 2 age groups. Adjusted odds ratios ranged from 1.132 (95% CI 0.930-1.377) to 1.248 (95% CI 0.970-1.606) (odds ratio >1 indicating that CEAs for age ≥65 years were more likely to conclude the intervention was cost-effective than those for age <65 years). Sensitivity and subgroup analyses found similar results. CONCLUSION: Our analysis found no systematic differences in published ICERs using quality-adjusted life-years between CEAs for individuals aged ≥65 years and those for individuals aged <65 years.

Consolidated Health Economic Evaluation Reporting Standards for Interventions That Use Artificial Intelligence (CHEERS-AI).

OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner. METHODS: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective. RESULTS: A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported. CONCLUSIONS: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.

Methods for Including Adverse Events in Economic Evaluations: Suggestions for Improvement.

OBJECTIVE: Inclusion of relevant effectiveness and safety outcomes in economic evaluation of health technologies is required to aid efficient healthcare decisions. Our objective was to identify the key issues related to the inclusion of adverse events (AEs) in economic evaluation and explore perspectives for good practice recommendations to handle these issues. METHODS: We focused on the frequently encountered methodological issues related to the integration of AEs in economic evaluations of health technologies. We distinguished the following elements: the incorporation of AEs in decision models, the terminology of AEs, the estimation of AEs consequences in terms of quality of life (QoL) and costs, and the exploration of the uncertainty related to the impact of AEs on the economic results. RESULTS: We illustrated and discussed each of the identified issues by giving health technology assessment examples. We focused on the extent to which the integration of AEs in decision models can be improved by dealing with the lack of relevant real-world safety data, estimating the consequences of AEs (eg, for costs and QoL loss), exploring the impacts of AEs that are not adequately captured in current measurement of health-related QoL, and identifying the need for development of a good terminology of relevant types of AEs to be incorporated in economic evaluation. CONCLUSION: Based on a reflection the key methodological issues related to the incorporation of adverse drug events in economic evaluations, we suggested several recommendations to serve a starting point for health technology assessment agencies and researchers to develop good research practices in this field.

Methods to Include Environmental Impacts in Health Economic Evaluations and Health Technology Assessments: A Scoping Review.

OBJECTIVES: The environmental impacts of healthcare are important factors that should be considered during health technology assessments. This study aims to summarize the evidence that exists about methods to include environmental impacts in health economic evaluations and health technology assessments. METHODS: We identified records for screening using an existing scoping review and a systematic search of academic databases and gray literature up to September 2023. We screened the identified records for eligibility and extracted data using a narrative synthesis approach. The review was conducted following the JBI Manual for Evidence Synthesis and reported according to the Preferred Reporting Items for Systematic Reviews and Meta Analyses Extension for Scoping Reviews checklist. RESULTS: We identified 2898 records and assessed the full text of 114, of which 54 were included in this review. Ten methods were identified to include environmental impacts in health economic evaluations and health technology assessments. Methods included converting environmental impacts to dollars or disability-adjusted life years and including them in a cost-effectiveness, cost-utility, or cost-benefit analysis, calculating an incremental carbon footprint effectiveness ratio or incremental carbon footprint cost ratio, incorporating impacts as one criteria of a multi-criteria decision analysis, and freely considering impacts during health technology assessment deliberation processes. CONCLUSIONS: Methods to include environmental impacts in health economic evaluations and health technology assessments exist but have not been tested for widespread use by health technology assessment agencies. Further research and implementation work is needed to determine which method can best aid decision makers to choose low environmental impact healthcare interventions.

The performance of a Bayesian value-based sequential clinical trial design in the presence of an equivocal cost-effectiveness signal: evidence from the HERO trial.

BACKGROUND: There is increasing interest in the capacity of adaptive designs to improve the efficiency of clinical trials. However, relatively little work has investigated how economic considerations - including the costs of the trial - might inform the design and conduct of adaptive clinical trials. METHODS: We apply a recently published Bayesian model of a value-based sequential clinical trial to data from the 'Hydroxychloroquine Effectiveness in Reducing symptoms of hand Osteoarthritis' (HERO) trial. Using parameters estimated from the trial data, including the cost of running the trial, and using multiple imputation to estimate the accumulating cost-effectiveness signal in the presence of missing data, we assess when the trial would have stopped had the value-based model been used. We used re-sampling methods to compare the design's operating characteristics with those of a conventional fixed length design. RESULTS: In contrast to the findings of the only other published retrospective application of this model, the equivocal nature of the cost-effectiveness signal from the HERO trial means that the design would have stopped the trial close to, or at, its maximum planned sample size, with limited additional value delivered via savings in research expenditure. CONCLUSION: Evidence from the two retrospective applications of this design suggests that, when the cost-effectiveness signal in a clinical trial is unambiguous, the Bayesian value-adaptive design can stop the trial before it reaches its maximum sample size, potentially saving research costs when compared with the alternative fixed sample size design. However, when the cost-effectiveness signal is equivocal, the design is expected to run to, or close to, the maximum sample size and deliver limited savings in research costs.

Switching Vancomycin Monitoring From Trough Concentration to Area Under the Curve Estimation by Bayesian Forecasting: A Short Communication on a Cost-Benefit Study in Resource-Limited Settings.

BACKGROUND: This study was conducted to evaluate the cost-benefit indicators of a vancomycin monitoring protocol based on area under the curve estimation using commercial Bayesian software. METHODS: This quasi-experimental study included patients who were aged >18 years with a vancomycin prescription for >24 hours. Patients who were terminally ill or those with acute kidney injury (AKI) ≤24 hours were excluded. During the preintervention period, doses were adjusted based on the trough concentration target of 15-20 mg/L, whereas the postintervention period target was 400-500 mg × h/L for the area under the curve. The medical team was responsible for deciding to stop the antimicrobial prescription without influence from the therapeutic drug monitoring team. The main outcomes were the incidence of AKI and length of stay. Cost-benefit simulation was performed after statistical analysis. RESULTS: There were 96 patients in the preintervention group and 110 in the postintervention group. The AKI rate decreased from 20% (n = 19) to 6% (n = 6; P = 0.003), whereas the number of vancomycin serum samples decreased from 5 (interquartile range: 2-7) to 2 (interquartile range: 1-3) examinations per patient ( P < 0.001). The mean length of hospital stay for patients was 26.19 days after vancomycin prescription, compared with 17.13 days for those without AKI ( P = 0.003). At our institution, the decrease in AKI rate and reduced length of stay boosted yearly savings of up to US$ 369,000 for 300 patients receiving vancomycin therapy. CONCLUSIONS: Even in resource-limited settings, a commercial Bayesian forecasting-based protocol for vancomycin is important for determining cost-benefit outcomes.

A Dutch cost-effectiveness analysis of fremanezumab versus best supportive care in patients with chronic migraine and inadequate response to prior preventive therapy.

BACKGROUND: Chronic migraine (CM) is the most severe and burdensome subtype of migraine. Fremanezumab is a monoclonal antibody that targets the calcitonin gene-related peptide pathway as a migraine preventive therapy. This study aimed to conduct a cost-effectiveness analysis of fremanezumab from a societal perspective in the Netherlands, using a Markov cohort simulation model. METHODS: The base-case cost-effectiveness analysis adhered to the Netherlands Authority guidelines. Fremanezumab was compared with best supportive care (BSC; acute migraine treatment only) in patients with CM and an inadequate response to topiramate or valproate and onabotulinumtoxinA (Dutch patient group [DPG]). A supportive analysis was conducted in the broader group of CM patients with prior inadequate response to 2-4 different classes of migraine preventive treatments. One-way sensitivity, probabilistic sensitivity, and scenario analyses were conducted. RESULTS: Over a lifetime horizon, fremanezumab is cost saving compared with BSC in the DPG (saving of €2514 per patient) and led to an increase of 1.45 quality-adjusted life-years (QALYs). In the broader supportive analysis, fremanezumab was cost effective compared with BSC, with an incremental cost-effectiveness ratio of €2547/QALY gained. Fremanezumab remained cost effective in all sensitivity and scenario analyses. CONCLUSION: In comparison to BSC, fremanezumab is cost saving in the DPG and cost effective in the broader population.

Strategies, processes, outcomes, and costs of implementing experience sampling-based monitoring in routine mental health care in four European countries: study protocol for the IMMERSE effectiveness-implementation study.

BACKGROUND: Recent years have seen a growing interest in the use of digital tools for delivering person-centred mental health care. Experience Sampling Methodology (ESM), a structured diary technique for capturing moment-to-moment variation in experience and behaviour in service users' daily life, reflects a particularly promising avenue for implementing a person-centred approach. While there is evidence on the effectiveness of ESM-based monitoring, uptake in routine mental health care remains limited. The overarching aim of this hybrid effectiveness-implementation study is to investigate, in detail, reach, effectiveness, adoption, implementation, and maintenance as well as contextual factors, processes, and costs of implementing ESM-based monitoring, reporting, and feedback into routine mental health care in four European countries (i.e., Belgium, Germany, Scotland, Slovakia). METHODS: In this hybrid effectiveness-implementation study, a parallel-group, assessor-blind, multi-centre cluster randomized controlled trial (cRCT) will be conducted, combined with a process and economic evaluation. In the cRCT, 24 clinical units (as the cluster and unit of randomization) at eight sites in four European countries will be randomly allocated using an unbalanced 2:1 ratio to one of two conditions: (a) the experimental condition, in which participants receive a Digital Mobile Mental Health intervention (DMMH) and other implementation strategies in addition to treatment as usual (TAU) or (b) the control condition, in which service users are provided with TAU. Outcome data in service users and clinicians will be collected at four time points: at baseline (t0), 2-month post-baseline (t1), 6-month post-baseline (t2), and 12-month post-baseline (t3). The primary outcome will be patient-reported service engagement assessed with the service attachment questionnaire at 2-month post-baseline. The process and economic evaluation will provide in-depth insights into in-vivo context-mechanism-outcome configurations and economic costs of the DMMH and other implementation strategies in routine care, respectively. DISCUSSION: If this trial provides evidence on reach, effectiveness, adoption, implementation and maintenance of implementing ESM-based monitoring, reporting, and feedback, it will form the basis for establishing its public health impact and has significant potential to bridge the research-to-practice gap and contribute to swifter ecological translation of digital innovations to real-world delivery in routine mental health care. TRIAL REGISTRATION: ISRCTN15109760 (ISRCTN registry, date: 03/08/2022).

Health-economic evaluation of orthogeriatric co-management for patients with pelvic or vertebral fragility fractures.

BACKGROUND: Orthogeriatric co-management (OGCM) addresses the special needs of geriatric fracture patients. Most of the research on OGCM focused on hip fractures while results concerning other severe fractures are rare. We conducted a health-economic evaluation of OGCM for pelvic and vertebral fractures. METHODS: In this retrospective cohort study, we used German health and long-term care insurance claims data and included cases of geriatric patients aged 80 years or older treated in an OGCM (OGCM group) or a non-OGCM hospital (non-OGCM group) due to pelvic or vertebral fractures in 2014-2018. We analyzed life years gained, fracture-free life years gained, healthcare costs, and cost-effectiveness within 1 year. We applied entropy balancing, weighted gamma and two-part models. We calculated incremental cost-effectiveness ratios and cost-effectiveness acceptability curves. RESULTS: We included 21,036 cases with pelvic (71.2% in the OGCM, 28.8% in the non-OGCM group) and 33,827 with vertebral fractures (72.8% OGCM, 27.2% non-OGCM group). 4.5-5.9% of the pelvic and 31.8-33.8% of the vertebral fracture cases were treated surgically. Total healthcare costs were significantly higher after treatment in OGCM compared to non-OGCM hospitals for both fracture cohorts. For both fracture cohorts, a 95% probability of cost-effectiveness was not exceeded for a willingness-to-pay of up to €150,000 per life year or €150,000 per fracture-free life year gained. CONCLUSION: We did not obtain distinct benefits of treatment in an OGCM hospital. Assigning cases to OGCM or non-OGCM group on hospital level might have underestimated the effect of OGCM as not all patients in the OGCM group have received OGCM.

Insights and networks: methodological assessment and scientometric analysis of economic evaluations in dentistry.

INTRODUCTION: Assessing the methodological quality of economic evaluations (EEs) is crucial for evidence-based decision-making. The study aimed to evaluate EEs in restorative dentistry and endodontics, while also analyzing the scientific landscape of researchers and publications through co-authorship and citation network analysis providing an insight into the distribution of scientific expertise. METHODOLOGY: A systematic search for relevant articles from 2012 to 2022 was conducted using PubMed, Scopus, and EBSCO. The ten-point Drummond checklist was used to appraise the methodological quality of included studies. Bibliometric data for network analysis were extracted from the Dimensions database and visualized using VOSviewer software. RESULTS: Of the 37 articles, 81.08% scored good, 16.21% average, and 2.7% poor on the methodological rating scale. Most of the included studies were in Q1 journals, with limited representation in Q2 and Q3 journals. Compliance was highest in Q2 journals (95%), followed by Q1 (88.36%), while it dropped to 40% for Q3 journals. Co-authorship analysis revealed a dense network of researchers, with Prof. Falk Schwendicke V. having a significant influence. Moreover, the Journal of Dentistry had the highest impact, followed by Journal of Endodontics and BMC Oral Health. CONCLUSIONS: Despite a diverse scientific landscape, participation from developing countries was limited emphasizing the need for inclusivity and diversity in the scientific network. While the quantity of good-quality studies was encouraging, the overall quality of evidence remains paramount for decision-making in healthcare policy and practice. Therefore, continuous efforts to improve methodological rigor and reporting practices are essential to contribute robust evidence.

Inclusion of phase III clinical trial costs in health economic evaluations.

INTRODUCTION: Protocol-driven trial activities contribute to the utility gain demonstrated in the phase III clinical trial of a new drug. If this utility gain cannot be distinguished from the effects of the new drug itself, protocol-driven trial costs cannot be easily dismissed for consistency reasons. This study aims to estimate the impact of including per-patient costs of phase III clinical trials on the incremental cost-effectiveness ratio (ICER). METHODS: The analysis utilized a modeling approach with secondary data from an ad-hoc literature review, considering both societal and payer perspectives. While the costs of phase III clinical trials may cancel out during the period of "normal" life-years due to the incremental cost calculation, they do not cancel out when differential early treatment termination occurs (e.g., due to differential mortality). Assuming the presence of differential mortality, per-patient phase III trial costs were calculated for the period of added life-years. These costs were then included in the ICER of a new drug, under the assumption that direct patient-related costs constitute 30-70% of the total trial costs. Capital costs were also incorporated from a societal perspective. RESULTS: Based on assumptions of $40,000 out-of-pocket expenses per patient enrolled in a phase III trial and a life expectancy gain of three months, incremental costs increased by $27,000 from a societal perspective. From a payer perspective, the estimate was $12,000. CONCLUSIONS: The costs of phase III trials are a relevant component of the ICER, and excluding it is generally not appropriate for consistency reasons. Properly considering these trial costs is essential for a comprehensive evaluation of a new drug's cost-effectiveness.

Cashing in: cost-benefit analysis framework for digital hospitals.

BACKGROUND: For many countries, especially those outside the USA without incentive payments, implementing and maintaining electronic medical records (EMR) is expensive and can be controversial given the large amounts of investment. Evaluating the value of EMR implementation is necessary to understand whether or not, such investment, especially when it comes from the public source, is an efficient allocation of healthcare resources. Nonetheless, most countries have struggled to measure the return on EMR investment due to the lack of appropriate evaluation frameworks. METHODS: This paper outlines the development of an evidence-based digital health cost-benefit analysis (eHealth-CBA) framework to calculate the total economic value of the EMR implementation over time. A net positive benefit indicates such investment represents improved efficiency, and a net negative is considered a wasteful use of public resources. RESULTS: We developed a three-stage process that takes into account the complexity of the healthcare system and its stakeholders, the investment appraisal and evaluation practice, and the existing knowledge of EMR implementation. The three stages include (1) literature review, (2) stakeholder consultation, and (3) CBA framework development. The framework maps the impacts of the EMR to the quadruple aim of healthcare and clearly creates a method for value assessment. CONCLUSIONS: The proposed framework is the first step toward developing a comprehensive evaluation framework for EMRs to inform health decision-makers about the economic value of digital investments rather than just the financial value.

A palliative care approach for adult non-cancer patients with life-limiting illnesses is cost-saving or cost-neutral: a systematic review of RCTs.

BACKGROUND: Patients living with life-limiting illnesses other than cancer constitute the majority of patients in need of palliative care globally, yet most previous systematic reviews of the cost impact of palliative care have not exclusively focused on this population. Reviews that tangentially looked at non-cancer patients found inconclusive evidence. Randomised controlled trials (RCTs) are the gold standard for treatment efficacy, while total health care costs offer a comprehensive measure of resource use. In the sole review of RCTs for non-cancer patients, palliative care reduced hospitalisations and emergency department visits but its effect on total health care costs was not assessed. The aim of this study is to review RCTs to determine the difference in costs between a palliative care approach and usual care in adult non-cancer patients with a life-limiting illness. METHODS: A systematic review using a narrative synthesis approach. The protocol was registered with PROSPERO prospectively (no. CRD42020191082). Eight databases were searched: Medline, CINAHL, EconLit, EMBASE, TRIP database, NHS Evidence, Cochrane Library, and Web of Science from inception to January 2023. Inclusion criteria were: English or German; randomised controlled trials (RCTs); adult non-cancer patients (> 18 years); palliative care provision; a comparator group of standard or usual care. Quality of studies was assessed using Drummond's checklist for assessing economic evaluations. RESULTS: Seven RCTs were included and examined the following diseases: neurological (3), heart failure (2), AIDS (1) and mixed (1). The majority (6/7) were home-based interventions. All studies were either cost-saving (3/7) or cost-neutral (4/7); and four had improved outcomes for patients or carers and three no change in outcomes. CONCLUSIONS: In a non-cancer population, this is the first systematic review of RCTs that has demonstrated a palliative care approach is cost-saving or at least cost-neutral. Cost savings are achieved without worsening outcomes for patients and carers. These findings lend support to calls to increase palliative care provision globally.

Cost-utility analysis of a palliative care program in Colombia.

BACKGROUND: The economic assessment of health care models in palliative care promotes their global development. The purpose of the study is to assess the cost-effectiveness of a palliative care program (named Contigo) with that of conventional care from the perspective of a health benefit plan administrator company, Sanitas, in Colombia. METHODS: The incremental cost-utility ratio (ICUR) and the incremental net monetary benefit (INMB) were estimated using micro-costing in a retrospective, analytical cross-sectional study on the care of terminally ill patients enrolled in a palliative care program. A 6-month time horizon prior to death was used. The EQ-5D-3 L questionnaire (EQ-5D-3 L) and the McGill Quality of Life Questionnaire (MQOL) were used to measure the quality of life. RESULTS: The study included 43 patients managed within the program and 16 patients who received conventional medical management. The program was less expensive than the conventional practice (difference of 1,924.35 US dollars (USD), P = 0.18). When compared to the last 15 days, there is a higher perception of quality of life, which yielded 0.25 in the EQ-5D-3 L (p < 0.01) and 1.55 in the MQOL (P < 0.01). The ICUR was negative and the INMB was positive. CONCLUSION: Because the Contigo program reduces costs while improving quality of life, it is considered to be net cost-saving and a model with value in health care. Greater availability of palliative care programs, such as Contigo, in Colombia can help reduce existing gaps in access to universal palliative care health coverage, resulting in more cost-effective care.

Return on Investment: Explanation and a Case Study.

Nurses are uniquely positioned to significantly impact organizational and system improvement through improving quality and reducing costs. Using an evidenced based tool to identify costs and the financial benefit involved in any quality improvement project is invaluable in developing and evaluating proposals and allocation of resources to support the organization's financial health and viability. The return on investment analysis is an essential accounting tool that will provide nurse leaders with critical information quantifying costs and benefits of both financial and nonfinancial metrics to identify the feasibility, efficacy, risk or efficiency of a proposed project.

The Use of Cost-Effectiveness Thresholds for Evaluating Health Interventions in Low- and Middle-Income Countries From 2015 to 2020: A Review.

OBJECTIVES: Evidence-informed priority setting, in particular cost-effectiveness analysis (CEA), can help target resources better to achieve universal health coverage. Central to the application of CEA is the use of a cost-effectiveness threshold. We add to the literature by looking at what thresholds have been used in published CEA and the proportion of interventions found to be cost-effective, by type of threshold. METHODS: We identified CEA studies in low- and middle-income countries from the Global Health Cost-Effectiveness Analysis Registry that were published between January 1, 2015, and January 6, 2020. We extracted data on the country of focus, type of interventions under consideration, funder, threshold used, and recommendations. RESULTS: A total of 230 studies with a total 713 interventions were included in this review; 1 to 3× gross domestic product (GDP) per capita was the most common type of threshold used in judging cost-effectiveness (84.3%). Approximately a third of studies (34.2%) using 1 to 3× GDP per capita applied a threshold at 3× GDP per capita. We have found that no study used locally developed thresholds. We found that 79.3% of interventions received a recommendation as "cost-effective" and that 85.9% of studies had at least 1 intervention that was considered cost-effective. The use of 1 to 3× GDP per capita led to a higher proportion of study interventions being judged as cost-effective compared with other types of thresholds. CONCLUSIONS: Despite the wide concerns about the use of 1 to 3× GDP per capita, this threshold is still widely used in the literature. Using this threshold leads to more interventions being recommended as "cost-effective." This study further explore alternatives to the 1 to 3× GDP as a decision rule.