Reverse Total Shoulder Arthroplasty Is the Most Cost-effective Treatment Strategy for Proximal Humerus Fractures in Older Adults: A Cost-utility Analysis.

BACKGROUND: Proximal humerus fractures are the second-most common fragility fracture in older adults. Although reverse total shoulder arthroplasty (RTSA) is a promising treatment strategy for proximal humerus fractures with favorable clinical and quality of life outcomes, it is associated with much higher, and possibly prohibitive, upfront costs relative to nonoperative treatment and other surgical alternatives. QUESTIONS/PURPOSES: (1) What is the cost-effectiveness of open reduction internal fixation (ORIF), hemiarthroplasty, and RTSA compared with the nonoperative treatment of complex proximal humerus fractures in adults older than 65 years from the perspective of a single-payer Canadian healthcare system? (2) Which factors, if any, affect the cost-effectiveness of ORIF, hemiarthroplasty, and RTSA compared with nonoperative treatment of proximal humerus fractures including quality of life outcomes, cost, and complication rates after each treatment? METHODS: This cost-utility analysis compared RTSA, hemiarthroplasty, and ORIF with the nonoperative management of complex proximal humerus fractures in adults older than 65 years over a lifetime time horizon from the perspective of a single-payer healthcare system. Short-term and intermediate-term complications in the 2-year postoperative period were modeled using a decision tree, with long-term outcomes estimated through a Markov model. The model was initiated with a cohort of 75-year-old patients who had a diagnosis of a comminuted (three- or four-part) proximal humerus fractures; 90% of the patients were women. The mean age and gender composition of the model's cohort was based on a systematic review conducted as part of this analysis. Patients were managed nonoperatively or surgically with either ORIF, hemiarthroplasty, or RTSA. The three initial surgical treatment options of ORIF, hemiarthroplasty, and RTSA resulted in uncomplicated healing or the development of a complication that would result in a subsequent surgical intervention. The model reflects the complications that result in repeat surgery and that are assumed to have the greatest impact on clinical outcomes and costs. Transition probabilities and health utilities were derived from published sources, with costs (2020 CAD) sourced from regional costing databases. The primary outcome was the incremental cost-utility ratio, which was calculated using expected quality-adjusted life years (QALYs) gained and costs. Sensitivity analyses were conducted to explore the impact of changing key model parameters. RESULTS: Based on both pairwise and sequential analysis, RTSA was found to be the most cost-effective strategy for managing complex proximal humerus fractures in adults older than 65 years. Compared with nonoperative management, the pairwise incremental cost-utility ratios of hemiarthroplasty and RTSA were CAD 25,759/QALY and CAD 7476/QALY, respectively. ORIF was dominated by nonoperative management, meaning that it was both more costly and less effective. Sequential analysis, wherein interventions are compared from least to most expensive in a pairwise manner, demonstrated ORIF to be dominated by hemiarthroplasty, and hemiarthroplasty to be extendedly dominated by RTSA. Further, at a willingness-to-pay threshold of CAD 50,000/QALY, RTSA had 66% probability of being the most cost-effective treatment option. The results were sensitive to changes in the parameters for the probability of revision RTSA after RTSA, the treatment cost of RTSA, and the health utilities associated with the well state for all treatment options except ORIF, although none of these changes were found to be clinically realistic based on the existing evidence. CONCLUSION: Based on this economic analysis, RTSA is the preferred treatment strategy for complex proximal humerus fractures in adults older than 65 years, despite high upfront costs. Based on the evidence to date, it is unlikely that the parameters this model was sensitive to would change to the degree necessary to alter the model's outcome. A major strength of this model is that it reflects the most recent randomized controlled trials evaluating the management of this condition. Therefore, clinicians should feel confident recommending RTSA for the management of proximal humerus fractures in adults older than 65 years, and they are encouraged to advocate for this intervention as being a cost-effective practice, especially in publicly funded healthcare systems wherein resource stewardship is a core principle. Future high-quality trials should continue to collect both clinical and quality of life outcomes using validated tools such as the EuroQOL-5D to reduce parameter uncertainty and support decision makers in understanding relevant interventions' value for money. LEVEL OF EVIDENCE: Level III, economic and decision analysis.

Towards Transparency in the Selection of Published Health Utility Inputs in Cost-Utility Analyses: The Health Utility Application Tool (HAT).

BACKGROUND: Evaluating the relevance of published health utilities to the context of a cost-utility analysis (CUA) remains an essential, yet often overlooked, task. OBJECTIVE: The objective of this study was to provide guidance on this process through the development of the Health utility Application Tool (HAT). METHODS: We conducted semi-structured telephone interviews with Canadian stakeholders from reimbursement bodies, academia, and the pharmaceutical industry to identify current practices and perspectives of the application of the health utility literature to CUAs. An online survey with international members of the general health economics and outcomes research community was also conducted to gather opinions on key concepts. RESULTS: Based on the themes emerging from the interviews and online questionnaire, the HAT includes questions prompting investigators to consider the following constructs: similarity of the clinical condition in the health utility study and the CUA; similarity of health utility study participant demographics and the demographics of the CUA's target population; similarity of the health state descriptions in the health utility study and the CUA; and the method of assigning utility weights. Considerations of transparency prompted additional items, including: means by which the health utility study was identified; type of respondents; study design; and measure used to collect health utility estimates. CONCLUSION: The HAT is intended to guide the evaluation of the applicability of published health utilities for a CUA, thus promoting transparency and accountability in the selection of model inputs.

Evaluating the conduct and application of health utility studies: a review of critical appraisal tools and reporting checklists.

BACKGROUND: Published health utility studies are increasingly cited in cost-utility analyses to inform reimbursement decision-making. However, there is limited guidance for investigators looking to systematically evaluate the methodological quality of health utility studies or their applicability to decision contexts. OBJECTIVE: To describe how health utility concepts are reflected in tools intended for use with the health economic literature, particularly with respect to the evaluation of methodological quality and context applicability. METHODS: We reviewed the critical appraisal and reporting tools described in a 2012 report published by the Agency for Healthcare Research and Quality (AHRQ), supplemented with a keyword search of MEDLINE and EMBASE, to identify existing tools which include health utility constructs. From these tools, a list of relevant items was compiled and grouped into domain categories based on the methodological or applicability aspect they were directed toward. RESULTS: Of the 24 tools we identified, 12 contained items relevant to the evaluation of health utilities. Sixty-five items were considered relevant to the evaluation of quality, while 44 were relevant to the evaluation of applicability. Items were arranged into four domains: health state descriptions; selection and description of respondents; elicitation and measurement methods; and other considerations. CONCLUSION: As key inputs to cost-utility analyses, health utilities have the potential to significantly impact estimates of cost-effectiveness. Existing tools contain only general items related to the conduct or use of health utility studies. There is a need to develop tools that systematically evaluate the methodological quality and applicability of health utility studies.

Comparing the use of aggregate data and various methods of integrating individual patient data to network meta-analysis and its application to first-line ART.

BACKGROUND: The 2018 World Health Organization HIV guidelines were based on the results of a network meta-analysis (NMA) of published trials. This study employed individual patient-level data (IPD) and aggregate data (AgD) and meta-regression methods to assess the evidence supporting the WHO recommendations and whether they needed any refinements. METHODS: Access to IPD from three trials was granted through ClinicalStudyDataRequest.com (CSDR). Seven modelling approaches were applied and compared: 1) Unadjusted AgD network meta-analysis (NMA) - the original analysis; 2) AgD-NMA with meta-regression; 3) Two-stage IPD-AgD NMA; 4) Unadjusted one-stage IPD-AgD NMA; 5) One-stage IPD-AgD NMA with meta-regression (one-stage approach); 6) Two-stage IPD-AgD NMA with empirical-priors (empirical-priors approach); 7) Hierarchical meta-regression IPD-AgD NMA (HMR approach). The first two were the models used previously. Models were compared with respect to effect estimates, changes in the effect estimates, coefficient estimates, DIC and model fit, rankings and between-study heterogeneity. RESULTS: IPD were available for 2160 patients, representing 6.5% of the evidence base and 3 of 24 edges. The aspect of the model affected by the choice of modeling appeared to differ across outcomes. HMR consistently generated larger intervals, often with credible intervals (CrI) containing the null value. Discontinuations due to adverse events and viral suppression at 96 weeks were the only two outcomes for which the unadjusted AgD NMA would not be selected. For the first, the selected model shifted the principal comparison of interest from an odds ratio of 0.28 (95% CrI: 10.17, 0.44) to 0.37 (95% CrI: 0.23, 0.58). Throughout all outcomes, the regression estimates differed substantially between AgD and IPD methods, with the latter being more often larger in magnitude and statistically significant. CONCLUSIONS: Overall, the use of IPD often impacted the coefficient estimates, but not sufficiently as to necessitate altering the final recommendations of the 2018 WHO Guidelines. Future work should examine the features of a network where adjustments will have an impact, such as how much IPD is required in a given size of network.

An Exploratory Analysis of Predictors of Concordance between Canadian Common Drug Review Reimbursement Recommendations and the Subsequent Decisions by Ontario, British Columbia and Alberta.

BACKGROUND: Concordance between Common Drug Review (CDR) recommendations and provincial plans has been studied previously. However, no study has, to the best of the authors' knowledge, examined the characteristics of CDR recommendations that may be associated with concordance. METHODS: Recommendation-decision pairs were collected from the CDR and the provincial plans of Ontario, British Columbia and Alberta. Concordance was evaluated by province. Characteristics of each CDR recommendation were collected, and associations with concordance were evaluated by logistic regression. RESULTS: Recommendation-listing concordance was high. Positive references to cost and clinical outcomes compared to placebo were statistically associated with concordance. Negative references to cost and to the consistency and certainty of economic evidence were statistically associated with discordance. However, these findings were inconsistent across the jurisdictions studied. CONCLUSION: Although concordance was high, the ability of recommendation characteristics to explain the relationship between province and CDR listing decisions was limited. This exploratory study highlights the complexity of the reimbursement process and possible reasons for drug listing differences across jurisdictions.

How do financial (dis)incentives influence health behaviour and costs? Protocol for a systematic literature review of randomised controlled trials.

INTRODUCTION: In this era of rising healthcare costs, there is a growing interest in understanding how funding policies can be used to improve health and healthcare efficiency. Financial incentives (eg, vouchers or access to health insurance) or disincentives (eg, fines or out-of-pocket costs) affect behaviours. To date, reviews have explored the effects of financial (dis)incentives on patient health and behaviour by focusing on specific behaviours or geographical areas. The objective of this systematic review is to provide a comprehensive overview on the use of financial (dis)incentives as a means of influencing health-related behaviour and costs in randomised trials. METHODS AND ANALYSIS: We will search electronic databases, clinical trial registries and websites of health economic organisations for randomised controlled trials. The initial searches, which were conducted on 13 January 2018, will be updated every 12 months until the completion of data analysis. The reference lists of included studies will be manually screened to identify additional eligible studies. Two researchers will independently review titles, abstracts and full texts to determine eligibility according to a set of predetermined inclusion criteria. Data will be extracted from included studies using a form developed and piloted by the research team. Discrepancies will be resolved through discussion with a third reviewer. Risk of bias will be assessed using the Cochrane Collaboration tool. ETHICS AND DISSEMINATION: Ethics approval is not required since this is a review of published data. Results will be disseminated through publication in peer-reviewed journals and presentations at relevant conferences. PROSPERO REGISTRATION NUMBER: CRD42018097140.

Toward a Centralized, Systematic Approach to the Identification, Appraisal, and Use of Health State Utility Values for Reimbursement Decision Making: Introducing the Health Utility Book (HUB).

Cost-utility analysis (CUA) is a widely recommended form of health economic evaluation worldwide. The outcome measure in CUA is quality-adjusted life-years (QALYs), which are calculated using health state utility values (HSUVs) and corresponding life-years. Therefore, HSUVs play a significant role in determining cost-effectiveness. Formal adoption and endorsement of CUAs by reimbursement authorities motivates methodological advancement in HSUV measurement and application. A large body of evidence exploring various methods in measuring HSUVs has accumulated, imposing challenges for investigators in identifying and applying HSUVs to CUAs. First, large variations in HSUVs between studies are often reported, and these may lead to different cost-effectiveness conclusions. Second, issues concerning the quality of studies that generate HSUVs are increasingly highlighted in the literature. This issue is compounded by the limited published guidance and methodological standards for assessing the quality of these studies. Third, reimbursement decision making is a context-specific process. Therefore, while an HSUV study may be of high quality, it is not necessarily appropriate for use in all reimbursement jurisdictions. To address these issues, by promoting a systematic approach to study identification, critical appraisal, and appropriate use, we are developing the Health Utility Book (HUB). The HUB consists of an HSUV registry, a quality assessment tool for health utility studies, and a checklist for interpreting their use in CUAs. We anticipate that the HUB will make a timely and important contribution to the rigorous conduct and proper use of health utility studies for reimbursement decision making. In this way, health care resource allocation informed by HSUVs may reflect the preferences of the public, improve health outcomes of patients, and maintain the efficiency of health care systems.