Simulation model for cost estimation of integrated care concepts of heart failure patients

Economic Evaluations of Remote Patient Monitoring for Chronic Disease: A Systematic Review

OBJECTIVES

This study aimed to systematically review and summarize economic evaluations of noninvasive remote patient monitoring (RPM) for chronic diseases compared with usual care.

METHODS

A systematic literature search identified economic evaluations of RPM for chronic diseases, compared with usual care. Searches of PubMed, Embase, CINAHL, and EconLit using keyword synonyms for RPM and economics identified articles published from up until September 2021. Title, abstract, and full-text reviews were conducted. Data extraction of study characteristics and health economic findings was performed. Article reporting quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist.

RESULTS

This review demonstrated that the cost-effectiveness of RPM was dependent on clinical context, capital investment, organizational processes, and willingness to pay in each specific setting. RPM was found to be highly cost-effective for hypertension and may be cost-effective for heart failure and chronic obstructive pulmonary disease. There were few studies that investigated RPM for diabetes or other chronic diseases. Studies were of high reporting quality, with an average Consolidated Health Economic Evaluation Reporting Standards score of 81%. Of the final 34 included studies, most were conducted from the healthcare system perspective. Eighteen studies used cost-utility analysis, 4 used cost-effectiveness analysis, 2 combined cost-utility analysis and a cost-effectiveness analysis, 1 used cost-consequence analysis, 1 used cost-benefit analysis, and 8 used cost-minimization analysis.

CONCLUSIONS

RPM was highly cost-effective for hypertension and may achieve greater long-term cost savings from the prevention of high-cost health events. For chronic obstructive pulmonary disease and heart failure, cost-effectiveness findings differed according to disease severity and there was limited economic evidence for diabetes interventions.

Are Unit Costs the Same? A Case Study Comparing Different Valuation Methods for Unit Cost Calculation of General Practitioner Consultations

OBJECTIVES

To inform allocation decisions in any healthcare system, robust cost data are indispensable. Nevertheless, recommendations on the most appropriate valuation approaches vary or are nonexistent, and no internationally accepted gold standard exists. This costing analysis exercise aims to assess the impact and implications of different calculation methods and sources based on the unit cost of general practitioner (GP) consultations in Austria.

METHODS

Six costing methods for unit cost calculation were explored, following 3 Austrian methodological approaches (AT-1, AT-2, AT-3) and 3 approaches applied in 3 other European countries (Germany, The Netherlands, United Kingdom). Drawing on Austrian data, mean unit costs per GP consultation were calculated in euros for 2015.

RESULTS

Mean unit costs ranged from €15.6 to €42.6 based on the German top-down costing approach (DE) and the Austrian Physicians' Chamber's price recommendations (AT-3), respectively. The mean unit cost was estimated at €18.9 based on Austrian economic evaluations (AT-1) and €17.9 based on health insurance payment tariffs (AT-2). The Dutch top-down (NL) and the UK bottom-up approaches (UK) yielded higher estimates (NL: €25.3, UK: €29.8). Overall variation reached 173%.

CONCLUSIONS

Our study is the first to systematically investigate the impact of differing calculation methods on unit cost estimates. It shows large variations with potential impact on the conclusions in an economic evaluation. Although different methodological choices may be justified by the adopted study perspective, different costing approaches introduce variation in cross-study/cross-country cost estimates, leading to decreased confidence in data quality in economic evaluations.

A novel hybrid modeling approach for the evaluation of integrated care and economic outcome in heart failure treatment

Background

Demographic changes, increased life expectancy and the associated rise in chronic diseases pose challenges to public health care systems. Optimized treatment methods and integrated concepts of care are potential solutions to overcome increasing financial burdens and improve quality of care. In this context modeling is a powerful tool to evaluate potential benefits of different treatment procedures on health outcomes as well as health care budgets. This work presents a novel modeling approach for simulating different treatment procedures of heart failure patients based on extensive data sets from outpatient and inpatient care.

Methods

Our hybrid heart failure model is based on discrete event and agent based methodologies and facilitates the incorporation of different therapeutic procedures for outpatient and inpatient care on patient individual level. The state of health is modeled with the functional classification of the New York Heart Association (NYHA), strongly affecting discrete state transition probabilities alongside age and gender. Cooperation with Austrian health care and health insurance providers allowed the realization of a detailed model structure based on clinical data of more than 25,000 patients.

Results

Simulation results of conventional care and a telemonitoring program underline the unfavorable prognosis for heart failure and reveal the correlation of NYHA classes with health and economic outcomes. Average expenses for the treatment of NYHA class IV patients of €10,077 ± €165 were more than doubled compared to other classes. The selected use case of a telemonitoring program demonstrated potential cost savings within two years of application. NYHA classes II and III revealed most potential for additional treatment measures.

Conclusion

The presented model allows performing extensive simulations of established treatment procedures for heart failure patients and evaluating new holistic methods of care and innovative study designs. This approach offers health care providers a unique, adaptable and comprehensive tool for decision making in the complex and socioeconomically challenging field of cardiovascular diseases.

Health Economic Impact of a Pulmonary Artery Pressure Sensor for Heart Failure Telemonitoring: A Dynamic Simulation

AIMS

Recently, a permanently implantable wireless system, designed to monitor and manage pulmonary artery (PA) pressures remotely, demonstrated significant reductions in heart failure (HF) hospitalizations in high-risk symptomatic patients, regardless of ejection fraction. The objectives of this study were to simulate the estimated clinical and economic impact in Germany of generalized use of this PA pressure monitoring system considering reductions of HF hospitalizations and the improvement in Quality of Life.

MATERIALS AND METHODS

Based on the Prospective Health Technology Assessment approach, we simulated the potential of the widespread application of PA pressure monitoring on the German healthcare system for the period 2009-2021.

RESULTS

This healthcare economic simulation formulated input assumptions based on results from the CHAMPION Trial, a multicenter, prospective, randomized controlled U.S. trial that demonstrated a 37% reduction of hospitalizations in persistently symptomatic previous HF patients. Based on these results, an estimated 114,800 hospitalizations would expected to be avoided. This effect would potentially save an estimated €522 million, an equivalent of $575 million, during the entire simulation period.

CONCLUSION

This healthcare economic modeling of the PA pressure monitoring system's impact demonstrates substantial clinical and economic benefits in the German healthcare system.

A systematic review of modelling approaches in economic evaluations of health interventions for drug and alcohol problems

Background

The overarching goal of health policies is to maximize health and societal benefits. Economic evaluations can play a vital role in assessing whether or not such benefits occur. This paper reviews the application of modelling techniques in economic evaluations of drug and alcohol interventions with regard to (i) modelling paradigms themselves; (ii) perspectives of costs and benefits and (iii) time frame.

Methods

Papers that use modelling approaches for economic evaluations of drug and alcohol interventions were identified by carrying out searches of major databases.

Results

Thirty eight papers met the inclusion criteria. Overall, the cohort Markov models remain the most popular approach, followed by decision trees, Individual based model and System dynamics model (SD). Most of the papers adopted a long term time frame to reflect the long term costs and benefits of health interventions. However, it was fairly common among the reviewed papers to adopt a narrow perspective that only takes into account costs and benefits borne by the health care sector.

Conclusions

This review paper informs policy makers about the availability of modelling techniques that can be used to enhance the quality of economic evaluations for drug and alcohol treatment interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-016-1368-8) contains supplementary material, which is available to authorized users.

Modeling for critically ill patients: An introduction for beginners

Models are mathematical tools used to describe real-world features. Therapeutic interventions in the field of critical care medicine may easily be translated into such models. Indeed, numerous variables influencing drug pharmacokinetics and pharmacodynamics are systematically documented in the intensive care unit over time. Organ failure, fluid shifts, other drug administration, and renal replacement therapy may cause changes in physiological values, such as body weight and composition, temperature, serum protein levels, arterial pH, and renal or hepatic function. Trials assessing the efficacy and safety of novel drugs usually exclude critically ill patients, and guidelines regarding drug dosage rarely apply to such patients. Modeling in the critically ill may allow physicians to inform decisions related to therapeutic interventions, particularly relating to infectious diseases. However, few clinicians are familiar with these methods. Here, we present a current overview of population pharmacokinetic and pharmacodynamic models applicable in critically ill patients aimed at nonspecialists and then emphazize recent potential of modeling for optimizing treatments and care in the intensive care unit.