Learning Health Systems: A Paradigm Shift in What We Can Do about Digital Health Inequities.

Learning health systems (LHSs) embed social accountability into everyday workflows and can inform how governments build bridges across the digital health divide. They shape partnerships using rapid cycles of data-driven learning to respond to patients' calls to action for equity from digital health. Adopting the LHS approach involves re-distributing power, which is likely to be met with resistance. We use the LHS example of British Columbia's 811 services to highlight how infrastructure was created to provide care and answer questions about access to digital health, outcomes from it and the financial impact passed on to patients. In the concluding section, we offer an accountability framework that facilitates partnerships in making digital health more equitable.

Trustworthy Evidence to Support Quality Digital Healthcare Policy for Underserved Communities: What Needs to Happen to Translate Evidence into Policy?

In this paper, we explore what is needed to generate quality research to guide evidence-informed digital health policy and call the Canadian community of patients, clinicians, policy (decision) makers and researchers to action in setting digital health research priorities for supporting underserved communities. Using specific examples, we describe how evidence is produced and implemented to guide digital health policy. We study how research environments must change to reflect and include the communities for whom the policy is intended. Our goal is to guide how future evidence reaches policy makers to help them shape healthcare services and how these services are delivered to underserved communities in Canada. Understanding the pathways through which evidence can make a difference to equitable and sustainable digital health policy is vital for guiding the types of research that attract priority resources.

Relational Work Is the Work: Virtual Healthcare Transformation for Rural, Remote and First Nations Communities in British Columbia.

The healthcare crisis across unceded First Nations' territories in rural, remote and Indigenous communities in British Columbia (BC) is marked by persistent barriers to accessing care and support close to home. This commentary describes an exceptional story of how technology, trusted partnerships and relationships came together to create an innovative suite of virtual care programs called "Real-Time Virtual Support" (RTVS). We describe key approaches, learnings and future considerations to improve the equity of healthcare delivery for rural, remote and First Nations communities. The key lessons include the following: (1) moving beyond a biomedical model - the collaboration framework for health service design incorporated First Nations' perspective on health and wellness; (2) relational work is the work - the RTVS collaboration was grounded in building connections and relationships to prioritize cultivating trust in the partnership over specific outputs; and (3) aligning to the core values of co-creation - working from a commitment to do things differently and applying an inclusive approach of engagement to integrate perspectives across different sectors and interest groups.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol.

BACKGROUND: Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD. METHODS AND ANALYSIS: Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep. CONCLUSION: SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

Assessing the impact of psychiatric genetic counseling on psychiatric hospitalizations.

Psychiatric genetic counseling (pGC) can improve patient empowerment and self-efficacy. We explored the relationship between pGC and psychiatric hospitalizations, for which no prior data exist. Using Population Data BC (a provincial dataset), we tested two hypotheses: (1) among patients (>18 years) with psychiatric conditions who received pGC between May 2010 and Dec 2016 (N = 387), compared with the year pre-pGC, in the year post-pGC there would be fewer (a) individuals hospitalized and (b) total hospital admissions; and (2) using a matched cohort design, compared with controls (N = 363, matched 1:4 for sex, diagnosis, time since diagnosis, region, and age, and assigned a pseudo pGC index date), the pGC cohort (N = 91) would have (a) more individuals whose number of hospitalizations decreased and (b) fewer hospitalizations post-pGC/pseudo-index. We also explored total days in hospital. Within the pGC cohort, there were fewer hospitalizations post-pGC than pre- pGC (p = 0.011, OR = 1.69), and total days in hospital decreased (1085 to 669). However, when compared to matched controls, the post-pGC/pseudo index change in hospitalizations among pGC cases was not statistically significant, even after controlling for the higher number of hospitalizations prior. pGC may lead to fewer psychiatric hospitalizations and cost savings; further studies exploring this are warranted.

Health Care Utilization and Costs in Lung Cancer Screening Participants-A Propensity-Matched Economic Analysis.

Introduction: Lung cancer screening (LCS) for high-risk populations has been firmly established to reduce lung cancer mortality, but concerns exist regarding unintended downstream costs. Methods: Mean health care utilization and costs were compared in the Alberta Lung Cancer Screening Study in a cohort undergoing LCS versus a propensity-matched control group who did not. Results: A cohort of 651 LCS participants was matched to 336 unscreened controls. Over the study period (mean 3.6 y), a modest increase in the number of claims (22.4 versus 21.9 per person-year [PY]; Δ 0.50 [95% confidence interval: 0.15-0.86], p = 0.006) and outpatient visits (4.01 versus 3.50 per PY; Δ 0.51 [0.37-0.65], p <0.0001), but not in inpatient admissions, was noted in the screened cohort. Claims payments, inpatient costs, and cancer care costs were similar in the screening arm versus the unscreened. Outpatient encounter costs per participant were higher in the screened group ($2662.18 versus $2040.67 per PY; Δ -$621.51 [-1118.05 to -124.97], p = 0.014). Removing the additional computed tomography screening examinations rendered differences not significant. Mean total costs were not significantly different at $6461.10 per PY in the screening group and $6125.31 in the unscreened group (Δ -$335.79 [-2009.65 to 1338.07], p = 0.69). Conclusions: Modest increases in outpatient costs are noted in individuals undergoing LCS, in part attributable to the screening examinations, without differences in overall health care costs. Health care costs and utilization seem otherwise similar in individuals participating in LCS and those who do not.

Costs of major depression covered / not covered in British Columbia, Canada.

BACKGROUND: Major depressive disorder (MDD) is one of the world's leading causes of disability. Our purpose was to characterize the total costs of MDD and evaluate the degree to which the British Columbia provincial health system meets its objective to protect people from the financial impact of illness. METHODS: We performed a population-based cohort study of adults newly diagnosed with MDD between 2015 and 2020 and followed their health system costs over two years. The expenditure proportion of MDD-related, patient paid costs relative to non-subsistence income was estimated, incidences of financial hardship were identified and the slope index of inequality (SII) between the highest and lowest income groups compared across regions. RESULTS: There were 250,855 individuals diagnosed with MDD in British Columbia over the observation period. Costs to the health system totalled >$1.5 billion (2020 CDN), averaging $138/week for the first 12 weeks following a new diagnosis and $65/week to week 52 and $55/week for weeks 53-104 unless MDD was refractory to treatment ($125/week between week 12-52 and $101/week over weeks 53-104). The proportion of MDD-attributable costs not covered by the health system was 2-15x greater than costs covered by the health system, exceeding $700/week for patients with severe MDD or MDD that was refractory to treatment. Population members in lower-income groups and urban homeowners had disadvantages in the distribution of financial protection received by the health system (SII reached - 8.47 and 15.25, respectively); however, financial hardship and inequities were mitigated province-wide if MDD went into remission (SII - 0.07 to 0.6). CONCLUSIONS: MDD-attributable costs to health systems and patients are highest in the first 12 weeks after a new diagnosis. During this time, lower income groups and homeowners in urban areas run the risk of financial hardship.

Cost-effectiveness of pharmacogenomic-guided treatment for major depression.

BACKGROUND: Pharmacogenomic testing to identify variations in genes that influence metabolism of antidepressant medications can enhance efficacy and reduce adverse effects of pharmacotherapy for major depressive disorder. We sought to establish the cost-effectiveness of implementing pharmacogenomic testing to guide prescription of antidepressants. METHODS: We developed a discrete-time microsimulation model of care pathways for major depressive disorder in British Columbia, Canada, to evaluate the effectiveness and cost-effectiveness of pharmacogenomic testing from the public payer's perspective over 20 years. The model included unique patient characteristics (e.g., metabolizer phenotypes) and used estimates derived from systematic reviews, analyses of administrative data (2015-2020) and expert judgment. We estimated incremental costs, life-years and quality-adjusted life-years (QALYs) for a representative cohort of patients with major depressive disorder in BC. RESULTS: Pharmacogenomic testing, if implemented in BC for adult patients with moderate-severe major depressive disorder, was predicted to save the health system $956 million ($4926 per patient) and bring health gains of 0.064 life-years and 0.381 QALYs per patient (12 436 life-years and 74 023 QALYs overall over 20 yr). These savings were mainly driven by slowing or avoiding the transition to refractory (treatment-resistant) depression. Pharmacogenomic-guided care was associated with 37% fewer patients with refractory depression over 20 years. Sensitivity analyses estimated that costs of pharmacogenomic testing would be offset within about 2 years of implementation. INTERPRETATION: Pharmacogenomic testing to guide antidepressant use was estimated to yield population health gains while substantially reducing health system costs. These findings suggest that pharmacogenomic testing offers health systems an opportunity for a major value-promoting investment.

Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

OBJECTIVE: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. METHODS: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. RESULTS: At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%-14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%-5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037-2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036-2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%-9.4%) in 2066. CONCLUSION: A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Economic impact of using risk models for eligibility selection to the International lung screening Trial.

OBJECTIVES: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013). MATERIALS AND METHODS: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials. The primary outcomes were costs in 2020 International Dollars ($), quality-adjusted life-years (QALY) and incremental net benefit (INB, in $ per QALY). Secondary outcomes were selection characteristics and cancer detection rates (CDR). RESULTS: Compared with the USPSTF-2013 criteria, the PLCOm2012 risk model resulted in $355 of cost savings per 0.2 QALYs gained (INB=$4294 at a willingness-to-pay threshold of $20 000/QALY (95 %CI: $4205-$4383). Using the risk model was more cost-effective in females at both a 1.5 % and 1.7 % 6-year risk threshold (INB=$6616 and $6112, respectively), compared with males ($5221 and $695). The PLCOm2012 model selected more females, more individuals with fewer years of formal education, and more people with other respiratory illnesses in the ILST. The CDR with the risk model was higher in females compared with the USPSTF-2013 criteria (Risk Ratio = 7.67, 95 % CI: 1.87-31.38). CONCLUSION: The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening.

Updated cost-effectiveness analysis of lung cancer screening for Australia, capturing differences in the health economic impact of NELSON and NLST outcomes.

BACKGROUND: A national, lung cancer screening programme is under consideration in Australia, and we assessed cost-effectiveness using updated data and assumptions. METHODS: We estimated the cost-effectiveness of lung screening by applying screening parameters and outcomes from either the National Lung Screening Trial (NLST) or the NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) to Australian data on lung cancer risk, mortality, health-system costs, and smoking trends using a deterministic, multi-cohort model. Incremental cost-effectiveness ratios (ICERs) were calculated for a lifetime horizon. RESULTS: The ICER for lung screening compared to usual care in the NELSON-based scenario was AU$39,250 (95% CI $18,150-108,300) per quality-adjusted life year (QALY); lower than the NLST-based estimate (ICER = $76,300, 95% CI $41,750-236,500). In probabilistic sensitivity analyses, lung screening was cost-effective in 15%/60% of NELSON-like simulations, assuming a willingness-to-pay threshold of $30,000/$50,000 per QALY, respectively, compared to 0.5%/6.7% for the NLST. ICERs were most sensitive to assumptions regarding the screening-related lung cancer mortality benefit and duration of benefit over time. The cost of screening had a larger impact on ICERs than the cost of treatment, even after quadrupling the 2006-2016 healthcare costs of stage IV lung cancer. DISCUSSION: Lung screening could be cost-effective in Australia, contingent on translating trial-like lung cancer mortality benefits to the clinic.

A Systematic Review of Kidney Transplantation Decision Modelling Studies.

BACKGROUND: Genome-based precision medicine strategies promise to minimize premature graft loss after renal transplantation, through precision approaches to immune compatibility matching between kidney donors and recipients. The potential adoption of this technology calls for important changes to clinical management processes and allocation policy. Such potential policy change decisions may be supported by decision models from health economics, comparative effectiveness research and operations management. OBJECTIVE: We used a systematic approach to identify and extract information about models published in the kidney transplantation literature and provide an overview of the status of our collective model-based knowledge about the kidney transplant process. METHODS: Database searches were conducted in MEDLINE, Embase, Web of Science and other sources, for reviews and primary studies. We reviewed all English-language papers that presented a model that could be a tool to support decision making in kidney transplantation. Data were extracted on the clinical context and modelling methods used. RESULTS: A total of 144 studies were included, most of which focused on a single component of the transplantation process, such as immunosuppressive therapy or donor-recipient matching and organ allocation policies. Pre- and post-transplant processes have rarely been modelled together. CONCLUSION: A whole-disease modelling approach is preferred to inform precision medicine policy, given its potential upstream implementation in the treatment pathway. This requires consideration of pre- and post-transplant natural history, risk factors for allograft dysfunction and failure, and other post-transplant outcomes. Our call is for greater collaboration across disciplines and whole-disease modelling approaches to more accurately simulate complex policy decisions about the integration of precision medicine tools in kidney transplantation.

Health utilities for participants in a population-based sample who meet eligibility criteria for lung cancer screening.

INTRODUCTION: Trial-based, risk-targeted lung cancer screening with low-dose computed tomography has been shown to reduce lung cancer mortality but implementation may depend on favourable cost-effectiveness evaluations where quality-adjusted life-years are a key metric. Baseline health utility values for a screening population at high risk of lung cancer are not likely to match age-specific population norms, and utilities derived from screening trials may not be representative of real-world screening populations. We estimated utility values for screening-eligible individuals in a population-based cohort study in Australia. METHODS: Cancer-free participants aged 50-80 years in the New South Wales 45 and Up Study completed the 12-Item Short Form Survey (2010-2011). Mean SF-6D utility values were calculated for 19,991 participants and compared across screening criteria defined by the US Preventive Services Task Force (USPSTF-2021/2013), NELSON trial eligibility, and the PLCOm2012 risk tool. RESULTS: Mean SF-6D utility values were comparable across screening criteria: USPSTF-2021, 0.772 (95%CI, 0.768-0.776); USPSTF-2013, 0.764 (95%CI, 0.759-0.770); NELSON, 0.768 (95%CI, 0.763-0.774), and were each lower than among ineligible participants (0.810-0.814). While there was a decline in utilities with increasing risk of lung cancer as measured with the PLCOm2012 risk tool, mean utility values for those with ≥ 1.51% 6-year risk did not differ to other criteria (0.772, 95%CI, 0.767-0.776). CONCLUSION: Risk criteria are necessary for the efficiency of lung cancer screening programs, but they select populations with lower mean health utilities than population norms. We provide baseline values that can be used in cost-effectiveness evaluations of risk-targeted lung cancer screening.

Applying utility values in cost-effectiveness analyses of lung cancer screening: A review of methods.

Lung cancer screening with low-dose computed tomography (LDCT) in high-risk populations has been shown in randomised controlled trials to lead to early diagnosis and reduced lung cancer mortality. However, investment into screening will largely depend on the outcomes of cost-effectiveness analyses that demonstrate acceptable costs for every quality-adjusted life year (QALY) gained. The methods used to apply utility values to measure QALYs can significantly impact the outcomes of cost-effectiveness analyses and if applied inaccurately can lead to unreliable estimates. We reviewed the use of utility values in 26 cost-effectiveness analyses of lung screening with LDCT conducted between 2005 and 2021, and found considerable variation in methods. Specifically, authors made different assumptions made relating to (i) baseline quality-of-life among screening participants, (ii) potential harms from screening, (iii) utilities and disutilities applied to lung cancer health states, and (iv) quality-of-life for lung cancer survivors. We discuss how each of these assumptions can influence incremental cost-effectiveness ratios. Key recommendations for future evaluations are (i) that modelling studies should justify the choice of baseline utilities, especially if patients are assumed to recover fully after curative treatment; (ii) the impact of false positive scans on quality-of-life should be modelled, at least in sensitivity analyses; (iii) modellers should justify assumptions relating to post-operative recovery, preferably based on knowledge of local practices; (iv) utilities applied to a lung cancer diagnosis should be appropriately sourced and calculated; and (v) adjustment for age-related declines in quality-of-life should be considered, especially for models that examine lifetime horizons.

USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study.

BACKGROUND: Lung cancer is a major health problem. CT lung screening can reduce lung cancer mortality through early diagnosis by at least 20%. Screening high-risk individuals is most effective. Retrospective analyses suggest that identifying individuals for screening by accurate prediction models is more efficient than using categorical age-smoking criteria, such as the US Preventive Services Task Force (USPSTF) criteria. This study prospectively compared the effectiveness of the USPSTF2013 and PLCOm2012 model eligibility criteria. METHODS: In this prospective cohort study, participants from the International Lung Screening Trial (ILST), aged 55-80 years, who were current or former smokers (ie, had ≥30 pack-years smoking history or ≤15 quit-years since last permanently quitting), and who met USPSTF2013 criteria or a PLCOm2012 risk threshold of at least 1·51% within 6 years of screening, were recruited from nine screening sites in Canada, Australia, Hong Kong, and the UK. After enrolment, patients were assessed with the USPSTF2013 criteria and the PLCOm2012 risk model with a threshold of at least 1·70% at 6 years. Data were collected locally and centralised. Main outcomes were the comparison of lung cancer detection rates and cumulative life expectancies in patients with lung cancer between USPSTF2013 criteria and the PLCOm2012 model. In this Article, we present data from an interim analysis. To estimate the incidence of lung cancers in individuals who were USPSTF2013-negative and had PLCOm2012 of less than 1·51% at 6 years, ever-smokers in the Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCO) who met these criteria and their lung cancer incidence were applied to the ILST sample size for the mean follow-up occurring in the ILST. This trial is registered at ClinicalTrials.gov, NCT02871856. Study enrolment is almost complete. FINDINGS: Between June 17, 2015, and Dec 29, 2020, 5819 participants from the International Lung Screening Trial (ILST) were enrolled on the basis of meeting USPSTF2013 criteria or the PLCOm2012 risk threshold of at least 1·51% at 6 years. The same number of individuals was selected for the PLCOm2012 model as for the USPSTF2013 criteria (4540 [78%] of 5819). After a mean follow-up of 2·3 years (SD 1·0), 135 lung cancers occurred in 4540 USPSTF2013-positive participants and 162 in 4540 participants included in the PLCOm2012 of at least 1·70% at 6 years group (cancer sensitivity difference 15·8%, 95% CI 10·7-22·1%; absolute odds ratio 4·00, 95% CI 1·89-9·44; p<0·0001). Compared to USPSTF2013-positive individuals, PLCOm2012-selected participants were older (mean age 65·7 years [SD 5·9] vs 63·3 years [5·7]; p<0·0001), had more comorbidities (median 2 [IQR 1-3] vs 1 [1-2]; p<0·0001), and shorter life expectancy (13·9 years [95% CI 12·8-14·9] vs 14·8 [13·6-16·0] years). Model-based difference in cumulative life expectancies for those diagnosed with lung cancer were higher in those who had PLCOm2012 risk of at least 1·70% at 6 years than individuals who were USPSTF2013-positive (2248·6 years [95% CI 2089·6-2425·9] vs 2000·7 years [1841·2-2160·3]; difference 247·9 years, p=0·015). INTERPRETATION: PLCOm2012 appears to be more efficient than the USPSTF2013 criteria for selecting individuals to enrol into lung cancer screening programmes and should be used for identifying high-risk individuals who benefit from the inclusion in these programmes. FUNDING: Terry Fox Research Institute, The UBC-VGH Hospital Foundation and the BC Cancer Foundation, the Alberta Cancer Foundation, the Australian National Health and Medical Research Council, Cancer Research UK and a consortium of funders, and the Roy Castle Lung Cancer Foundation for the UK Lung Screen Uptake Trial.

The cost-effectiveness of adding tomosynthesis to mammography-based breast cancer screening: an economic analysis.

BACKGROUND: Observational studies show that digital breast tomosynthesis (DBT) combined with digital mammography (DM) can reduce recall rates and increases rates of breast cancer detection. The objective of this study was to examine the cost-effectiveness of DBT plus DM versus DM alone in British Columbia and to identify parameters that can improve the efficiency of breast cancer screening programs. METHODS: We conducted an economic analysis based on data from a cohort of screening participants in the BC Cancer Breast Screening Program. The decision model simulated lifetime costs and outcomes for participants in breast cancer screening who were aged 40-74 years between 2012 and 2017. We analyzed rates of health care resource utilization, health state costs and estimated incremental cost-effectiveness ratios (ICERs), to measure incremental cost differences per quality-adjusted life years (QALYs) gained from the addition of DBT to DM-based screening, from the government payer's perspective. RESULTS: The model simulated economic outcomes for 112 249 screening participants. We found that the ICER was highly sensitive to recall rate reductions and insensitive to parameters related to cancer detection. If DBT plus DM can reduce absolute recall rates by more than 2.1%, the base-case scenario had an ICER of $17 149 per QALY. At a willingness-to-pay threshold of $100 000 per QALY, more than 95% of the probabilistic simulations favoured the adoption of DBT plus DM versus DM alone. The ICER depended heavily on the ability of DBT plus DM to reduce recall rates. INTERPRETATION: The addition of DBT to DM would be considered cost-effective owing to the low positive predictive value of screening with DM alone. Reductions in false-positive recall rates should be monitored closely.

Quality of life and socioeconomic indicators associated with survival of myeloid leukemias in Canada.

Understanding how patient-reported quality of life (QoL) and socioeconomic status (SES) relate to survival of acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) may improve prognostic information sharing. This study explores associations among QoL, SES, and survival through administration of the Euro-QoL 5-Dimension, 3-level and Functional Assessment of Cancer Therapy-Leukemia and financial impact questionnaires to 138 adult participants with newly diagnosed AML or MDS in a longitudinal, pan-Canadian study. Cox regression and lasso variable selection models were used to explore associations among QoL, SES, and established predictors of survival. Secondary outcomes were changes in QoL, performance of the QoL instruments, and lost income. We found that higher QoL and SES were positively associated with survival. The Lasso model selected the visual analog scale of the EQ-5D-3L as the most important predictor among all other variables (P = .03; 92% selection). Patients with AML report improved QoL after treatment, despite higher mean out-of-pocket expenditures compared with MDS (up to $599 CDN/month for AML vs $239 for MDS; P = .05), greater loss of productivity-related income (reaching $1786/month for AML vs $709 for MDS; P < .05), and greater caregiver effects (65% vs 35% caregiver productivity losses for AML vs MDS; P < .05). Our results suggest that including patient-reported QoL and socioeconomic indicators can improve the accuracy of survival models.

Conducting clinical trials-costs, impacts, and the value of clinical trials networks: A scoping review.

BACKGROUND: A significant barrier to conducting clinical trials is their high cost, which is driven primarily by the time and resources required to activate trials and reach accrual targets. The high cost of running trials has a substantial impact on their long-term feasibility and the type of clinical research undertaken. METHODS: A scoping review of the empirical literature on the costs associated with conducting clinical trials was undertaken for the years 2001-2015. Five reference databases were consulted to elicit how trials costs are presented in the literature. A review instrument was developed to extract the content of in-scope papers. Findings were characterized by date and place of publication, clinical disease area, and network/cooperative group designation, when specified. Costs were captured and grouped by patient accrual and management, infrastructure, and the opportunity costs associated with industry funding for trials research. Cost impacts on translational research and health systems were also captured, as were recommendations to reduce trial expenditures. Since articles often cited multiple costs, multiple cost coding was used during data extraction to capture the range and frequency of costs. RESULTS: A total of 288 empirical articles were included. The distribution of reported costs was: patient management and accrual costs (132 articles), infrastructure costs (118 articles) and the opportunity costs of industry sponsorship (72 articles). 221 articles reported on the impact of undertaking costly trials on translational research and health systems; of these, the most frequently reported consequences were to research integrity (52% of articles), research capacity (36% of articles) and running low-value trials (34% of articles). 254 articles provided recommendations to reduce trial costs; of these, the most frequently reported recommendations related to improvements in: operational efficiencies (33% of articles); patient accrual (24% of articles); funding for trials and transparency in trials reporting (18% of articles, each). CONCLUSION: Key findings from the review are: 1) delayed trial activation has costs to budgets and research; 2) poor accrual leads to low-value trials and wasted resources; 3) the pharmaceutical industry can be a pragmatic, if problematic, partner in clinical research; 4) organizational know-how and successful research collaboration are benefits of network/cooperative groups; and 5) there are spillover benefits of clinical trials to healthcare systems, including better health outcomes, enhanced research capacity, and drug cost avoidance. There is a need for more economic evaluations of the benefits of clinical research, such as health system use (or avoidance) and health outcomes in cities and health authorities with institutions that conduct clinical research, to demonstrate the affordability of clinical trials, despite their high cost.

Health-related quality of life and anxiety in the PAN-CAN lung cancer screening cohort.

OBJECTIVES: The impact of lung cancer screening with low-dose chest CT (LDCT) on participants' anxiety levels and health-related quality of life (HRQoL) is an important consideration in the implementation of such programmes. We aimed to describe changes in anxiety and HRQoL in a high-risk Canadian cohort undergoing LDCT lung cancer screening. METHODS: 2537 subjects who had 2% or greater lung cancer risk over 6 years using a risk prediction tool were recruited from eight centres across Canada in the Pan-Canadian Early Detection of Lung Cancer Study (2008-2010). We compared HRQoL and anxiety levels before and after screening of 1237 participants with LDCT (excluding a subset of 1300 participants who also underwent autofluorescence bronchoscopy screening), as well as after investigations performed because of a positive screening examination. The 12-item short-form Physical and Mental Component Scales (SF-12), EQ-5D-3L scores and State Trait Anxiety Inventory-State anxiety were used at each assessment. RESULTS: Overall, there were no clinically significant differences in HRQoL outcomes between baseline and each of the survey time points following initial screening. No mean change in anxiety in the overall cohort was noted following baseline LDCT, but more participants had clinically significant increase in anxiety versus decrease after baseline screening (increase >minimal clinically important difference (MCID) (n=180) vs decrease >MCID (n=50), p<0.001). This finding persisted but to a lesser degree at the 12 month time point (increase >MCID (n=146) vs decrease >MCID (n=87), p<0.001). CONCLUSIONS: CT screening for lung cancer has no major overall impact on HRQoL among participants, although a minority of participants (number-needed-to-harm=7 after baseline screening and 18 at 1 year) demonstrated clinically significant increased anxiety levels. TRIALREGISTRATION NUMBER: NCT00751660; Results.