Introduction. Individuals from older populations tend to have more than 1 health condition (multimorbidity). Current approaches to produce economic evidence for clinical guidelines using decision-analytic models typically use a single-disease approach, which may not appropriately reflect the competing risks within a population with multimorbidity. This study aims to demonstrate a proof-of-concept method of modeling multiple conditions in a single decision-analytic model to estimate the impact of multimorbidity on the cost-effectiveness of interventions. Methods. Multiple conditions were modeled within a single decision-analytic model by linking multiple single-disease models. Individual discrete event simulation models were developed to evaluate the cost-effectiveness of preventative interventions for a case study assuming a UK National Health Service perspective. The case study used 3 diseases (heart disease, Alzheimer’s disease, and osteoporosis) that were combined within a single linked model. The linked model, with and without correlations between diseases incorporated, simulated the general population aged 45 years and older to compare results in terms of lifetime costs and quality-adjusted life-years (QALYs). Results. The estimated incremental costs and QALYs for health care interventions differed when 3 diseases were modeled simultaneously (£840; 0.234 QALYs) compared with aggregated results from 3 single-disease models (£408; 0.280QALYs). With correlations between diseases additionally incorporated, both absolute and incremental costs and QALY estimates changed in different directions, suggesting that the inclusion of correlations can alter model results. Discussion. Linking multiple single-disease models provides a methodological option for decision analysts who undertake research on populations with multimorbidity. It also has potential for wider applications in informing decisions on commissioning of health care services and long-term priority setting across diseases and health care programs through providing potentially more accurate estimations of the relative cost-effectiveness of interventions.
The manner in which health care is delivered to patients has evolved significantly through the years. Technology has played an important role in that evolution. This case study explores one way health care organizations are investing in advanced health care technologies to deliver services to patients when the patients are not in the same room as the providers. This study explores the implementation of an eConsult program, also known as telemedicine, at Avera Medical Group Pierre. This study will discuss the process of implementing an eConsult program, the equipment needed to provide eConsults, privacy, and billing concerns, and the facility’s future plans for expanding the telemedicine services they offer. Overall, this case study strives to show that implementing telemedicine can be a relatively easy process of embracing technology, which can greatly benefit patients.
Designing ethical policies is illustrated with two real examples. The first, allocating cadaver kidneys for transplantation, needs to develop a policy that satisfies the two conflicting fundamental values of equality and efficiency. Equality would require a lottery or a first-come, first-served policy. Efficiency would allocate kidneys to the candidates who would benefit the most. Because neither value may be dismissed, the values must be compromised. That compromise happens in two ways: by compromising the values of equality and efficiency within a policy at a time, and by cycling across policies over time, shifting the preference given to the two values back-and-forth. The second example is an illuminating account of how the National Institute for Health and Clinical Excellence in England and Wales designed a deliberative process for assessing the cost effectiveness of health care technologies.
Modeling the Economic Impact of Interventions for Older Populations with Multimorbidity: A Method of Linking Multiple Single-Disease Models