RESUMO
OBJECTIVE: To assess the effectiveness of different machine learning models in estimating the pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II diagnosis, based on the clinical risk index determined by the analysis of comorbidities. MATERIALS AND METHODS: In this cross-sectional study, we have used data from 11,028 anonymized records of patients admitted to a high-complexity hospital in Bogota, Colombia between 2017-2019 with a primary diagnosis of Diabetes. These cases were classified according to Charlson's comorbidity index in several risk categories. The main variables analyzed in this study are hospitalization costs (which include pharmaceutical and non-pharmaceutical expenditures), age, gender, length of stay, medicines and services consumed, and comorbidities assessed by the Charlson's index. The model's dependent variable is expenditure (composed of pharmaceutical and non-pharmaceutical expenditures). Based on these variables, different machine learning models (Multivariate linear regression, Lasso model, and Neural Networks) were used to estimate the pharmaceutical and non-pharmaceutical expenditures associated with the clinical risk classification. To evaluate the performance of these models, different metrics were used: Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R2). RESULTS: The results indicate that the Neural Networks model performed better in terms of accuracy in predicting pharmaceutical and non-pharmaceutical expenditures considering the clinical risk based on Charlson's comorbidity index. A deeper understanding and experimentation with Neural Networks can improve these preliminary results, therefore we can also conclude that the main variables used and those that were proposed can be used as predictors for the medical expenditures of patients with diabetes type-II. CONCLUSIONS: With the increase of technology elements and tools, it is possible to build models that allow decision-makers in hospitals to improve the resource planning process given the accuracy obtained with the different models tested.
Assuntos
Diabetes Mellitus Tipo 2 , Gastos em Saúde , Aprendizado de Máquina , Humanos , Diabetes Mellitus Tipo 2/economia , Diabetes Mellitus Tipo 2/tratamento farmacológico , Masculino , Feminino , Estudos Transversais , Pessoa de Meia-Idade , Colômbia/epidemiologia , Idoso , Hospitalização/economia , Comorbidade , Adulto , Fatores de RiscoRESUMO
BACKGROUND: In recent years, the rapid development of information and communications technology enabled by innovations in videoconferencing solutions and the emergence of connected medical devices has contributed to expanding the scope of application and expediting the development of telemedicine. OBJECTIVE: This study evaluates the use of teleconsultations (TCs) for specialist consultations at hospitals in terms of costs, resource consumption, and patient travel time. The key feature of our evaluation framework is the combination of an economic evaluation through a cost analysis and a performance evaluation through a discrete-event simulation (DES) approach. METHODS: Three data sets were used to obtain detailed information on the characteristics of patients, characteristics of patients' residential locations, and usage of telehealth stations. A total of 532 patients who received at least one TC and 18,559 patients who received solely physical consultations (CSs) were included in the initial sample. The TC patients were recruited during a 7-month period (ie, 2020 data) versus 19 months for the CS patients (ie, 2019 and 2020 data). A propensity score matching procedure was applied in the economic evaluation. To identify the best scenarios for reaping the full benefits of TCs, various scenarios depicting different population types and deployment strategies were explored in the DES model. Associated break-even levels were calculated. RESULTS: The results of the cost evaluation reveal a higher cost for the TC group, mainly induced by higher volumes of (tele)consultations per patient and the substantial initial investment required for TC equipment. On average, the total cost per patient over 298 days of follow-up was 356.37 (US $392) per TC patient and 305.18 (US $336) per CS patient. However, the incremental cost of TCs was not statistically significant: 356.37 - 305.18 = 51.19 or US $392 - US $336 = US $56 (95% CI -35.99 to 114.25; P=.18). Sensitivity analysis suggested heterogeneous economic profitability levels within subpopulations and based on the intensity of use of TC solutions. In fact, the DES model results show that TCs could be a cost-saving strategy in some cases, depending on population characteristics, the amortization speed of telehealth equipment, and the locations of telehealth stations. CONCLUSIONS: The use of TCs has the potential to lead to a major organizational change in the health care system in the near future. Nevertheless, TC performance is strongly related to the context and deployment strategy involved.
Assuntos
Consulta Remota , Telemedicina , Análise Custo-Benefício , Humanos , Consulta Remota/métodos , Especialização , Comunicação por VideoconferênciaRESUMO
Chimeric antigen receptor T-cells (CAR-T cells) have the potential to be a major innovation as a new type of cancer treatment, but are associated with extremely high prices and a high level of uncertainty. This study aims to assess the cost of the hospital stay for the administration of anti-CD19 CAR-T cells in France. Data were collected from the French Medical Information Systems Program (PMSI) and all hospital stays associated with an administrated drug encoded 9439938 (tisagenlecleucel, Kymriah®) or 9440456 (axicabtagene ciloleucel, Yescarta®) between January 2019 and December 2020 were included. 485 hospital stays associated with an injection of anti-CD19 CAR-T cells were identified, of which 44 (9%), 139 (28.7%), and 302 (62.3%) were for tisagenlecleucel in acute lymphoblastic leukaemia (ALL), tisagenlecleucel in diffuse large B-cell lymphoma (DLBCL), and axicabtagene ciloleucel respectively. The lengths of the stays were 37.9, 23.8, and 25.9 days for tisagenlecleucel in ALL, tisagenlecleucel in DLBCL, and axicabtagene ciloleucel, respectively. The mean costs per hospital stay were 372,400 for a tisagenlecleucel in ALL, 342,903 for tisagenlecleucel in DLBCL, and 366,562 for axicabtagene ciloleucel. CAR T-cells represented more than 80% of these costs. n=13 hospitals performed CAR-T cell injections, with two hospitals accounting for more than 50% of the total number of injections. This study provides original data in a context of limited information regarding the costs of hospitalization for patients undergoing CAR-T cell treatments. In addition to the financial burden, distance may also be an important barrier for accessing CAR T-cell treatment.
Assuntos
Imunoterapia Adotiva/economia , Tempo de Internação/economia , Programas Nacionais de Saúde/economia , Receptores de Antígenos Quiméricos/administração & dosagem , Antineoplásicos Imunológicos/administração & dosagem , Produtos Biológicos/administração & dosagem , Bases de Dados Factuais , Custos de Medicamentos , França , Humanos , Linfoma Difuso de Grandes Células B/terapia , Leucemia-Linfoma Linfoblástico de Células Precursoras/terapia , Receptores de Antígenos de Linfócitos T/administração & dosagemRESUMO
Innovation and health-care funding reforms have contributed to the deployment of Information and Communication Technology (ICT) to improve patient care. Many health-care organizations considered the application of ICT as a crucial key to enhance health-care management. The purpose of this paper is to provide a methodology to assess the organizational impact of high-level Health Information System (HIS) on patient pathway. We propose an integrated performance evaluation of HIS approach through the combination of formal modeling using the Architecture of Integrated Information Systems (ARIS) models, a micro-costing approach for cost evaluation, and a Discrete-Event Simulation (DES) approach. The methodology is applied to the consultation for cancer treatment process. Simulation scenarios are established to conclude about the impact of HIS on patient pathway. We demonstrated that although high level HIS lengthen the consultation, occupation rate of oncologists are lower and quality of service is higher (through the number of available information accessed during the consultation to formulate the diagnostic). The provided method allows also to determine the most cost-effective ICT elements to improve the care process quality while minimizing costs. The methodology is flexible enough to be applied to other health-care systems.
Assuntos
Análise Custo-Benefício , Sistemas de Informação em Saúde/economia , Sistemas de Informação em Saúde/organização & administração , Simulação por Computador , Procedimentos Clínicos , França , Humanos , Neoplasias/economia , Neoplasias/terapia , Oncologistas , Estudos de Casos Organizacionais , Melhoria de Qualidade/organização & administraçãoRESUMO
This paper addresses the modeling and simulation of blood collection systems in France for both fixed site and mobile blood collection with walk in whole blood donors and scheduled plasma and platelet donors. Petri net models are first proposed to precisely describe different blood collection processes, donor behaviors, their material/human resource requirements and relevant regulations. Petri net models are then enriched with quantitative modeling of donor arrivals, donor behaviors, activity times and resource capacity. Relevant performance indicators are defined. The resulting simulation models can be straightforwardly implemented with any simulation language. Numerical experiments are performed to show how the simulation models can be used to select, for different walk in donor arrival patterns, appropriate human resource planning and donor appointment strategies.