Purpose: To demonstrate how budgetary constraints may alter a radiologist’s diagnostic decisions in the pursuit of optimal breast cancer diagnosis as measured by quality adjusted life years (QALYs) from the societal perspective.

Method: We developed a finite-horizon discrete-time Markov decision process (MDP) model to optimize breast cancer diagnosis problem i.e. given the demographic data and mammography features, what is the optimal course of action; routine screening, short-term follow-up or biopsy?  The MDP model uses breast cancer progression probabilities obtained from 62,219 consecutive mammography records reported in Breast Imaging Reporting and Data System (BI-RADS) format. We modify a linear programming formulation of the MDP model to include budgetary restrictions and solve it to maximize the total expected QALYs of a patient. We repeat this experiment for various budget values in a feasible range. We compare actual clinical practice with optimal decisions obtained using the model and conduct incremental cost effectiveness analysis over the range identified. 

Result: We find that the optimal policies are of double-control-limit type i.e. for each age there exists a certain probability of cancer over which the optimal decision is short-term follow-up and a secondary threshold over which the optimal decision is biopsy. Under budgetary restrictions, initially short-term follow-ups are reduced and as the budget gets tighter, the optimal threshold to biopsy increases. The effect of budget in short-term follow-ups and the biopsy thresholds are more pronounced in older ages.  Moreover, diagnostic decisions based on age and breast cancer risk while observing optimal thresholds result in cost savings without sacrificing QALYs. Comparing to actual clinical practice, using optimal thresholds for decision-making may result in approximately 14% cost savings without sacrificing  QALYs.  

Conclusion: In this work, we present a novel framework for evaluating the cost-effectiveness of diagnostic procedures in the context of a sequential decision making problem, namely breast cancer diagnostic decisions after mammography. In conducting our analysis, we only consider maximizing QALYs and consider cost only as a restriction for optimal actions. Under this framework, our analysis indicate that short-term follow ups are the immediate target when budget becomes a concern.

Purpose: A 21-gene recurrence score (RS) assay provides a method of guiding treatment decisions in women with early stage breast cancer. We sought to investigate the cost effectiveness of using the RS assay versus using the Canadian clinical practice guidelines (CCPG).

Method: We developed a Markov model to project the lifetime clinical and economic consequences of the two strategies for patients with early stage breast cancer. The model simulated transitions among the following health states: remission, remission with major chemotherapy-related toxicity, loco-regional recurrence (LR), distant recurrence (DR) and death. We considered 3 scenarios: adjuvant therapy in postmenopausal women with estrogen/progesterone receptor positive (ER+/PR+), axillary lymph node–positive (LN+) early stage breast cancer; postmenopausal women with ER+/PR+, axillary lymph node–negative (LN-) early stage breast cancer; and postmenopausal women with ER+/PR+, LN- early stage breast cancer. We assumed that the RS would independently reclassify patients among risk levels (low, intermediate and high) and corresponding treatment regimens (hormone therapy plus chemotherapy versus hormone therapy alone). The model was parameterized using 5 and 10 year follow up data from the Manitoba cancer registry, cost data from Manitoba administrative databases including the Hospital Discharge Database, the Physician Claims Database and the Drug Program Information Network (DPIN), and secondary sources. Costs are presented in 2010 Canadian dollars, and future costs and benefits were discounted at 5%.

Result: The baseline incremental cost-effectiveness ratio of RS assay versus the CCPG was approximately $3,500/QALY gained for postmenopausal women with ER+/PR+, LN+; $12,000/QALY gained for postmenopausal women with ER+/PR+, LN- ; and $20,000/QALY gained for premenopausal women with ER+/PR+, LN-. Sensitivity analyses revealed that the risk and cost of chemotherapy-related serious adverse effects, the cost of the RS assay and the relative risk reduction of recurrence were the most influential variables.

Conclusion: In all scenarios considered the RS assay appears to be cost effective and should be considered for adoption.

Purpose: In response to the pandemic H1N1 influenza 2009 outbreak, many jurisdictions undertook mass immunization programs that were among the largest in recent history. The objective of this study was to determine the cost-effectiveness of the mass H1N1 immunization program in Ontario, Canada’s most populous province (population 13,000,000).

Methods:  A cost-utility analysis comparing the H1N1 mass immunization program in Ontario to no immunization was performed from the health care payer perspective (Ontario Ministry of Health and Long-Term Care). The economic evaluation used projections from a simulation model of a pandemic H1N1 2009 outbreak in a typical Ontario urban center.  Health outcomes included number of cases, number of deaths and quality adjusted life-years (QALYs). Estimates of health care resource use (office visits, emergency department (ED) visits, hospitalizations) and deaths were based on Ontario pandemic H1N1 surveillance data. Vaccination program cost and health care cost for treating H1N1 cases and were drawn from Ontario administrative data sources. Primary outcomes were QALYs, costs in 2009 Canadian dollars, and cost per QALY gained (incremental cost-effectiveness ratio (ICER)).

Results: We estimated that 4.1 million cases of symptomatic H1N1 influenza would have occurred (31.5% symptomatic attack rate) in the absence of an immunization program. Our model predicted that 22% of symptomatic cases, 22% of office and ED visits, 23% of hospitalizations, and 25% of deaths were prevented by the program. While the program was costly ($180.4 million), it was also highly cost-effective at $9,388/QALY gained. Projections were highly sensitive to the timing of the immunization program and moderately sensitive to immunization program cost and QALYs. The ICER remained well below World Health Organization thresholds for cost-effectiveness in all deterministic sensitivity analyses. Probabilistic uncertainty analysis confirmed the robustness of results with a likelihood of the program to be cost-effective of 100% at a willingness-to-pay of $30,000/QALY.

Conclusions: This analysis suggests that a mass immunization program as carried out in Ontario and many other high-income health care systems in response to H1N1 2009 was effective in preventing influenza cases and health care resource use and was also highly cost-effective despite the substantial program cost.

Purpose: Trauma is the leading cause of death among Americans aged 1-44. Survival can be enhanced by prompt transport to trauma centers. Compared to ground ambulance transport, helicopters can further shorten transport times and provide a higher level of care. However, recently, concerns have been raised about the safety and high costs of helicopter trauma transport. The objective of this study is to determine the required mortality reduction achieved by helicopter transport of trauma victims from the scene of injury to a trauma center to justify their higher costs.

Method: We developed a decision-analytic Markov model to compare the costs and outcomes of two strategies: helicopter vs. ground ambulance transport from scene of injury to a Level I trauma center when expected ground transport time is >30 minutes. The model follows patients from injury through transport, during their hospitalization and first year post-discharge, and until death.  We applied the model to a population of trauma victims (age 18-85 with serious injury (Abbreviated Injury Score [AIS] >=3) treated at U.S. Level I trauma centers based on the National Study on Costs and Outcomes of Trauma (NSCOT), with transport costs and safety data derived from the published literature. The analysis was conducted from a societal perspective over a lifetime horizon. The primary outcome measure is the threshold relative risk (RR) reduction in inpatient mortality by helicopter transport needed to achieve incremental cost-effectiveness ratios (ICER) of $50,000 and $100,000/QALY compared to ground transport.  We assessed robustness with one-way sensitivity and probabilistic sensitivity analyses. 

Result: Helicopter trauma transport must provide a 5% RR reduction in mortality for patients with mean characteristics of the NSCOT cohort to achieve an ICER below $100,000/QALY and a reduction of 12% to be below $50,000/QALY.  Greater RR reductions are needed for less severely injured and older patients. However, very slight improvements in long-term disability outcomes for helicopter transport would reduce the RR reduction needed for cost-effectiveness. Results were relatively insensitive to the risk of fatal helicopter crash or to helicopter transport costs.

Conclusion: Compared to ground ambulance transport, helicopter transport is cost-effective if the relative risk of death can be reduced by more than 5% in seriously injured patients.  Further study of the effectiveness of helicopter transport, especially of long-term disability outcomes, is warranted.

Purpose: Hepatitis B virus (HBV) infection is a significant health issue with risk for a number of costly and debilitating disease complications. In industrialized nations such as the United States, there is a significant and disproportionate burden of chronic HBV infection among the foreign-born population. The purpose of this study was to determine the cost-effectiveness of universal screening for HBV infection among new immigrants to the United States.

Method: A Markov decision model was developed to compare screening and usual care strategies for a hypothetical cohort of immigrants entering the United States in one year. We considered direct health care costs and quality-adjusted life years (QALYs) for the immigrant cohort over a 20-year horizon. Patients could progress through the early stages of HBV infection to cirrhosis, hepatic decompensation, hepatocellular carcinoma (HCC), and death, as well as receive treatment or undergo liver transplant. We used prevalence of HBV infection among the foreign-born population from the National Health and Nutrition Examination Survey (NHANES) and obtained cost, utility, natural history and treatment effectiveness estimates from the literature. Costs and QALYs were discounted at 3% per year. Probabilistic sensitivity analyses were performed using 1,000 Monte Carlo simulations.

Results: The incremental cost-effectiveness ratio for the screening strategy compared to usual care was $45,570 per quality-adjusted life year (QALY) gained. For a willingness-to-pay (WTP) of $100,000/QALY, screening was cost-effective in 67% of Monte Carlo simulations. Our analysis identified key areas of uncertainty in the epidemiology and management of chronic HBV infection that could potentially benefit from future research.

Conclusion: Early detection and treatment of HBV infection through screening appears to substantially impact both health outcomes and health service utilization for new immigrants and their receiving country. Given the potential for health gains for the immigrant cohort as well as the economic attractiveness of the intervention, some consideration might be given to the introduction of a universal HBV screening program to the U.S. immigration medical exam.

Purpose: Each year a small number of expectant mothers with high-risk pregnancies in British Columbia (BC) are sent to the United States (US) because of a lack of neonatal intensive care unit (NICU) beds. We sought to determine the impact of changing the number of NICU beds in BC on the probability of transfer to the US and on overall system costs.

Method: We developed a discrete event simulation model to determine the probability of transfer to the US based on bed availability at each hospital in BC.  We modeled four types of NICU beds (Level I, IIA, IIB and III) which were differentiated by their ability to handle different levels of patient acuity. We used a Markov chain to model daily changes in a neonate’s health status and assumed that inter-hospital transfers were based on geographic distance. We obtained data on the current number of beds of each type from the BC Health System, and we obtained data on birth rates, length of stay and costs from the Canadian Institute for Health Information and published reports. We varied the number of beds of each type at each hospital and observed the impact on total costs and the probability that a baby would be transferred to the US.

Result: Adding a total of 13 Level II beds province-wide caused yearly system costs to be reduced by $803,000.  In addition, the combined average Level II and Level III bed utilization was reduced from 88% to 83% and the probability of transfer to the US was reduced from 0.018% to 0.0074%.  Adding 3 Level III beds caused system costs to be reduced by $278,000, reduced average Level III bed utilization from 87% to 84%, and reduced the probability of US treatment from 0.018% to 0.012%.  Adding Level I beds increased system costs but had no effect on the probability of transfer to the US. 

Conclusion: Adding a small number of Level II or Level III beds results in a reduction in the probability of transfer to the US. It also results in cost savings because of the significant cost of treatment in the US relative to Canada. We believe that the BC Health System should consider a modest increase in province-wide NICU capacity.