A systematic review of the accessibility, acceptability, safety, efficiency, clinical effectiveness, and cost-effectiveness of private cataract and orthopedic surgery clinics.

OBJECTIVES: Many publicly funded health systems use a mix of privately and publicly operated providers of care to deliver elective surgical services. The aim of this systematic review was to assess the role of privately operated but publicly funded provision of surgical services for adult patients who had cataract or orthopedic surgery within publicly funded health systems in high-income countries. METHODS: Electronic databases (Ovid MEDLINE, OVID Embase, and EBSCO EconLit) were searched on 26 March 2021, and gray literature sources were searched on 6 April 2021. Two reviewers independently applied inclusion and exclusion criteria to identify studies, and extracted data. The outcomes evaluated include accessibility, acceptability, safety, clinical effectiveness, efficiency, and cost/cost-effectiveness. RESULTS: Twenty-nine primary studies met the inclusion criteria and were synthesized narratively. We found mixed results across each of our reported outcomes. Wait times were shorter for patients treated in private facilities. There was evidence that some private facilities cherry-pick or cream-skim by selecting less complex patients, which increases the postoperative length of stay and costs for public facilities, restricts access to private facilities for certain groups of patients, and increases inequality within the health system. Seven studies found improved safety outcomes in private facilities, noting that private patients had a lower preoperative risk of complications. Only two studies reported cost and cost-effectiveness outcomes. One costing study concluded that private facilities' costs were lower than those of public facilities, and a cost-utility study showed that private contracting to reduce public waiting times for joint replacement was cost-effective. CONCLUSIONS: Limited evidence exists that private-sector contracts address existing healthcare delivery problems. Value for money also remains to be evaluated properly.

A Conceptual Framework for Life-Cycle Health Technology Assessment.

OBJECTIVES: Health technology assessment (HTA) uses evidence appraisal and synthesis with economic evaluation to inform adoption decisions. Standard HTA processes sometimes struggle to (1) support decisions that involve significant uncertainty and (2) encourage continued generation of and adaptation to new evidence. We propose the life-cycle (LC)-HTA framework, addressing these challenges by providing additional tools to decision makers and improving outcomes for all stakeholders. METHODS: Under the LC-HTA framework, HTA processes align to LC management. LC-HTA introduces changes in HTA methods to minimize analytic time while optimizing decision certainty. Where decision uncertainty exists, we recommend risk-based pricing and research-oriented managed access (ROMA). Contractual procurement agreements define the terms of reassessment and provide additional decision options to HTA agencies. LC-HTA extends value-of-information methods to inform ROMA agreements, leveraging routine, administrative data, and registries to reduce uncertainty. RESULTS: LC-HTA enables the adoption of high-value high-risk innovations while improving health system sustainability through risk-sharing and reducing uncertainty. Responsiveness to evolving evidence is improved through contractually embedded decision rules to simplify reassessment. ROMA allows conditional adoption to obtain additional information, with confidence that the net value of that adoption decision is positive. CONCLUSIONS: The LC-HTA framework improves outcomes for patients, sponsors, and payers. Patients benefit through earlier access to new technologies. Payers increase the value of the technologies they invest in and gain mechanisms to review investments. Sponsors benefit through greater certainty in outcomes related to their investment, swifter access to markets, and greater opportunities to demonstrate value.

Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19.

Many epidemiological models of the COVID-19 pandemic have focused on preventing deaths. Questions have been raised as to the frailty of those succumbing to the COVID-19 infection. In this paper we employ standard life table methods to illustrate how the potential quality-adjusted life-year (QALY) losses associated with COVID-19 fatalities could be estimated, while adjusting for comorbidities in terms of impact on both mortality and quality of life. Contrary to some suggestions in the media, we find that even relatively elderly patients with high levels of comorbidity can still lose substantial life years and QALYs. The simplicity of the method facilitates straightforward international comparisons as the pandemic evolves. In particular, we compare five different countries and show that differences in the average QALY losses for each COVID-19 fatality is driven mainly by differing age distributions for those dying of the disease.

Early Initiation of Tumor Necrosis Factor Antagonist-Based Therapy for Patients With Crohn's Disease Reduces Costs Compared With Late Initiation.

BACKGROUND & AIMS: Antagonists of tumor necrosis factor (TNF) are effective for induction and maintenance of remission of Crohn's disease (CD) and are generally prescribed when patients do not respond to conventional, less-costly medical therapies. Early initiation of anti-TNF therapy reduced rates of surgery and dose escalation due to loss of response. However, these drugs are expensive, so studies are needed on the cost effectiveness of early initiation. We aimed to determine the cost effectiveness of initiating treatment early in the disease course (within 2 years of CD diagnosis) vs later in the disease course (more than 2 years after diagnosis). METHODS: We constructed a Markov model of a hypothetical cohort of patients with CD in Canada to simulate disease progression after initiation of infliximab or adalimumab therapy. We used published loss-of-response rates to compare the lifetime cost effectiveness of early vs late initiation of anti-TNF therapies. Transition probabilities and utilities were obtained through a literature search, and costs were obtained from the Alberta Ministry of Health. Sensitivity analysis was used to characterize uncertainty. RESULTS: Early initiation of infliximab yielded an additional 0.72 quality-adjusted life-years (QALYs) and saved $50,418 compared with late initiation. Early initiation of adalimumab yielded an additional 0.54 QALYs and saved $43,969. At a willingness-to-pay threshold of $50,000, early initiations of infliximab or adalimumab therapy had a 74% chance of being cost effective compared with late initiation. CONCLUSIONS: In a Markov model analysis, we found initiation of either infliximab or adalimumab within 2 years of CD diagnosis to provide significant cost savings and QALYs compared with later initiation (more than 2 years after diagnosis).

Comparative effectiveness and cost-effectiveness analysis of a urine metabolomics test vs. alternative colorectal cancer screening strategies.

PURPOSE: Despite the success of provincial screening programs, colorectal cancer (CRC) is still the third most common cancer in Canada and the second most common cause of cancer-related death. Fecal-based tests, such as fecal occult blood test (FOBT) and fecal immunochemical test (FIT), form the foundation of the provincial CRC screening programs in Canada. However, those tests have low sensitivity for CRC precursors, adenomatous polyps and have low adherence. This study evaluated the effectiveness and cost-effectiveness of a new urine metabolomic-based test (UMT) that detects adenomatous polyps and CRC. METHODS: A Markov model was designed using data from the literature and provincial healthcare databases for Canadian at average risk for CRC; calibration was performed against statistics data. Screening strategies included the following: FOBT every year, FIT every year, colonoscopy every 10 years, and UMT every year. The costs, quality adjusted life years (QALY) gained, and incremental cost-effectiveness ratios (ICERs) for each strategy were estimated and compared. RESULTS: Compared with no screening, a UMT strategy reduced CRC mortality by 49.9% and gained 0.15 life years per person at $42,325/life year gained in the base case analysis. FOBT reduced CRC mortality by 14.9% and gained 0.04 life years per person at $25,011/life year gained. FIT reduced CRC mortality by 35.8% and gained 0.11 life years per person at $25,500/life year while colonoscopy reduced CRC mortality by 24.7% and gained 0.08 life years per person at $50,875/life year. CONCLUSIONS: A UMT strategy might be a cost-effective strategy when used in programmatic CRC screening programs.

Correction to: Comparing methods to estimate incremental inpatient costs and length of stay due to methicillin-resistant Staphylococcus aureus in Alberta, Canada.

In the original publication of this article [1], the authors want to add the following sentence in the Acknowledgement section.

Comparing methods to estimate incremental inpatient costs and length of stay due to methicillin-resistant Staphylococcus aureus in Alberta, Canada.

BACKGROUND: Methicillin-resistant Staphylococcus aureus (MRSA) is an opportunistic bacterial organism resistant to first line antibiotics. Acquisition of MRSA is often classified as either healthcare-associated or community-acquired. It has been shown that both healthcare-associated and community-acquired infections contribute to the spread of MRSA within healthcare facilities. The objective of this study was to estimate the incremental inpatient cost and length of stay for individuals colonized or infected with MRSA. Common analytical methods were compared to ensure the quality of the estimate generated. This study was performed at Alberta Ministry of Health (Edmonton, Alberta), with access to clinical MRSA data collected at two Edmonton hospitals, and ministerial administrative data holdings. METHODS: A retrospective cohort study of patients with MRSA was identified using a provincial infection prevention and control database. A coarsened exact matching algorithm, and two regression models (semilogarithmic ordinary least squares model and log linked generalized linear model) were evaluated. A MRSA-free cohort from the same facilities and care units was identified for the matched method; all records were used for the regression models. Records span from January 1, 2011 to December 31, 2015, for individuals 18 or older at discharge. RESULTS: Of the models evaluated, the generalized linear model was found to perform the best. Based on this model, the incremental inpatient costs associated with hospital-acquired cases were the most costly at $31,686 (14,169 - 60,158) and $47,016 (23,125 - 86,332) for colonization and infection, respectively. Community-acquired MRSA cases also represent a significant burden, with incremental inpatient costs of $7397 (2924 - 13,180) and $14,847 (8445 - 23,207) for colonization and infection, respectively. All costs are adjusted to 2016 Canadian dollars. Incremental length of stay followed a similar pattern, where hospital-acquired infections had the longest incremental stays of 35.2 (16.3-69.5) days and community-acquired colonization had the shortest incremental stays of 3.0 (0.6-6.3) days. CONCLUSIONS: MRSA, and in particular, hospital-acquired MRSA, places a significant but preventable cost burden on the Alberta healthcare system. Estimates of cost and length of stay varied by the method of analysis and source of infection, highlighting the importance of selecting the most appropriate method.

Improving Transparency of Decision Models Through the Application of Decision Analytic Models with Omitted Objects Displayed (DAMWOOD).

The coronavirus disease 2019 (COVID-19) pandemic has increased public awareness of the influence of epidemiological and economic decision models on public policy decisions. Alongside this is an increased scrutiny on the development, analysis, reporting and utilisation of decision models for public policy making. Therefore, it is important that model developers can clearly explain and justify to all stakeholders what is included and excluded from a model developed to support decision-making, to both improve transparency and trust in decision-making. Our aim is to provide tools for improving communication between modellers and decision-makers, leading to improved transparency in decision-making. To do so, we extend the recently described directed acyclic graphs with omitted objects displayed (DAGWOOD) approach from Haber et al. (Ann Epidemiol 68:64-71, 2022) to decision analytic models, giving the decision analytic models with omitted objects displayed (DAMWOOD) approach. DAMWOOD is a framework for the identification of objects omitted from a decision model, as well as for consideration of the effects of omissions on model outcomes. Objects omitted from a decision model are classed as either an exclusion (known and unknown confounders), misdirection (alternative model pathways) or structure (e.g. model type, methods for estimating relationships between objects). DAMWOOD requires model developers to use explicit statements and provide illustration of included and omitted objects, supporting communication with model users and stakeholders, allowing them to provide input and feedback to modellers about which objects to include or omit in a model. In developing DAMWOOD, we considered two challenges we encountered in modelling for pandemic policy response. First, the scope of the decision problem is not always made sufficiently explicit by decision-makers, requiring modellers to intuit which policy options should be considered, and/or which outcomes should be considered in their evaluation. Second, there is rarely sufficient transparency to ensure stakeholders can see what is included in models and why. This limits stakeholders' ability to advocate to decision-makers for the prioritisation of specific outcomes and challenge the model results. To illustrate the application of DAMWOOD, we apply it to a previously published COVID-19 vaccine allocation optimisation model. The DAMWOOD diagrams illustrate the ways in which it is possible to improve the communication of model assumptions. The diagrams make explicit which outcomes are omitted and provide information on the expected impact of the omissions on model results. We discuss the usefulness of DAMWOOD for framing the decision problem, communicating the model structure and results and engaging with those making and affected by the decisions the model is developed to inform.

Healthcare costs and effects of post-COVID-19 condition in Canada.

Background: As evidence of the long-term health impacts of coronavirus disease 2019 (COVID-19) continues to grow across Canada, a key concern is the costs and health impacts of post-COVID-19 condition (PCC), especially while the healthcare system remains under substantial strain. The objective of this study is to estimate healthcare costs and quality-adjusted life year (QALY) decrements per PCC case and per acute COVID-19 case by vaccination status. Methods: First, we conducted a rapid review of the literature to estimate 1) the probability of developing PCC following COVID-19 infection by vaccination status, 2) the probability of each condition commonly associated with PCC, 3) healthcare costs and QALY decrements associated with each condition and 4) the number of PCC cases currently in Canada. Second, using the data gathered from the literature, we built a tool to estimate the cost and QALY decrements per PCC and COVID-19 case. Results: Post-COVID-19 condition costs per COVID-19 case ranged from CAD 1,675 to CAD 7,340, and QALY decrements ranged between 0.047 to 0.206, in the first year following COVID-19 infection. Overall, individuals who were unvaccinated when they were infected had higher costs and QALY decrements. We estimated the total burden of PCC to the Canadian healthcare system based on PCC estimates up until spring 2023 would be between CAD 7.8 and CAD 50.6 billion. Conclusion: This article demonstrates the large potential health and economic burden of PCC for Canadians, and the importance of vaccination and other infection control strategies in reducing the longer-term costs and effects.

The diagonal approach: A theoretic framework for the economic evaluation of vertical and horizontal interventions in healthcare.

The diagonal approach is a health system funding concept wherein vertical approaches targeting specific diseases are combined with horizontal approaches intended to strengthen health systems broadly. This taxonomy can also be used to classify health system interventions as either vertical or horizontal. Previous studies have used mathematical programming to evaluate horizontal interventions, but these models have not allowed concurrent evaluation of different types of horizontal interventions or captured spillovers and intertemporal effects. This paper aims to develop a theoretic framework for the diagonal approach. The framework is articulated through integer programming, maximizing health benefits given constraints by identifying the optimal set of both vertical and horizontal interventions to fund. The theoretic framework for the diagonal approach is developed by synthesizing and expanding three prior works. The decision problem is synthesised to allow concurrent evaluation of three different types of horizontal interventions, those: (i) improving health system efficiency, (ii) improving capacity, and (iii) investing in new platforms. Linear programs are converted to integer form, relaxing previous assumptions related to constant returns to scale and divisibility of interventions. The framework is expanded to evaluate multiple budget constraints and options for new platforms. A new form for the value function is used to estimate the benefits of intervention combinations, capturing spillovers between vertical and horizontal interventions and dynamic returns to scale. The decision problem is specified inferotemporally, explicitly capturing the impact of the time horizon on the optimal choice set. Dynamic examples are provided to demonstrate the advantages of the diagonal approach over prior frameworks. This framework extends existing works, enabling simultaneous comparison of various combinations of both vertical and horizontal interventions, capturing spillovers and intertemporal effects. The diagonal approach framework defines decision problems flexibly and realistically, forming the basis for future applied work. Implementation would improve resource allocation and patient health outcomes.

Vaccine rollout strategies: The case for vaccinating essential workers early.

In vaccination campaigns against COVID-19, many jurisdictions are using age-based rollout strategies, reflecting the much higher risk of severe outcomes of infection in older groups. In the wake of growing evidence that approved vaccines are effective at preventing not only adverse outcomes, but also infection, we show that such strategies are less effective than strategies that prioritize essential workers. This conclusion holds across numerous outcomes, including cases, hospitalizations, Long COVID (cases with symptoms lasting longer than 28 days), deaths and net monetary benefit. Our analysis holds in regions where the vaccine supply is limited, and rollout is prolonged for several months. In such a setting with a population of 5M, we estimate that vaccinating essential workers sooner prevents over 200,000 infections, over 600 deaths, and produces a net monetary benefit of over $500M.

A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine.

OBJECTIVE: The objective of this study was to implement a model-based approach to identify the optimal allocation of a coronavirus disease 2019 (COVID-19) vaccine in the province of Alberta, Canada. METHODS: We developed an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness and cost of vaccine. The model simulated hypothetical immunisation scenarios within a dynamic context, capturing concurrent public health strategies and population behavioural changes. RESULTS: In a scenario with 80% vaccine effectiveness, 40% population coverage and prioritisation of those over the age of 60 years at high risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs $292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs $118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies. CONCLUSIONS: Our results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised.