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1.
Braz. J. Pharm. Sci. (Online) ; 58: e181069, 2022. tab, graf
Article in English | LILACS | ID: biblio-1374570

ABSTRACT

Abstract Stomach cancer is the second leading cause of death by cancer worldwide and is even more pronounced in South America. In Brazil, it is estimated that an increase in the number of cases due to this cancer occurred in the biennium 2018-2019. In this study, we investigated the expenditures of the State Health Department of Goiás on hospitalizations and treatment of gastric cancer for the Unified Health System (SUS) from 2008-2016. This is a cross-sectional, descriptive, and analytical study based on secondary data from the Unified Health System computing department (DATASUS) and the System of Management of the Table of Procedures, Medications, Orthosis, Prosthesis, and Special Materials of SUS through CONECTA-SUS related to International Classification of Diseases-10/C16 (ICD-10/C16) procedures for gastric neoplasms. A total of I$ 5,697,958.20 was spent on gastric tumor in the last nine years in Goiás, I$ 4,492,916.67 (0.3%) on hospitalizations, and I$ 1,997,120.91 on treatment. This study presents a current and relevant estimate of the costs of gastric cancer patients in Goiás. Moreover, we provide information on the extent of the cancer issue to public health. Our analysis offers components for service management and studies that reduce resource allocation in more rational ways


Subject(s)
Stomach Neoplasms/economics , Brazil/ethnology , Health Expenditures/statistics & numerical data , Patients/classification , Therapeutics/classification , Unified Health System , Costs and Cost Analysis/statistics & numerical data , Resource Allocation/classification , Hospitalization/economics
2.
Rev Epidemiol Sante Publique ; 66 Suppl 2: S101-S118, 2018 Mar.
Article in French | MEDLINE | ID: mdl-29530442

ABSTRACT

This work addresses the analysis of individual cost data in the setting of interventional or observational studies using statistical analysis software once the costs per patient have been estimated. It is in fact necessary to be able to present and describe data in an appropriate manner in each of the studied health strategies and to test whether the difference in costs observed between treatment groups is due to chance or not. Furthermore, cost analysis differs from conventional statistical analysis in that cost data have a certain number of specific properties, including their use by health decision-makers. This work also addresses the difficulties that generally arise in regard to the distribution of cost; it explains why the mathematical average constitutes the only relevant measure for economists; and it outlines which analyses are required for inter-strategy cost comparisons. It also covers the issue of missing or censored data, features that are inherent to information collected regarding costs and to sensitivity analyses.


Subject(s)
Cost-Benefit Analysis/methods , Health Care Costs , Hospital Costs/organization & administration , Cost-Benefit Analysis/standards , France/epidemiology , Health Care Costs/statistics & numerical data , Hospital Costs/standards , Hospital Costs/statistics & numerical data , Humans , Resource Allocation/classification , Resource Allocation/economics , Resource Allocation/statistics & numerical data
3.
Methods Inf Med ; 52(6): 522-35, 2013.
Article in English | MEDLINE | ID: mdl-24072039

ABSTRACT

OBJECTIVE: The purpose of this study was to improve accessibility to nursing care by clarifying the relationship between patient characteristics and the amount of nursing care for the Diagnosis Procedure Combination system (DPC). METHOD: The subjects included 528 lung cancer patients; 170 gastric cancer patients; and 91 colon cancer patients, who were hospitalized from July 1, 2008, to March 31, 2010, at a university hospital. The patients were categorized into groups according to factors that could affect the amount of nursing care. Next, the relationship between the patient characteristics and the amount of nursing care was analyzed. Then the results from this study were used to classify patient characteristics according to the patient type and the amount nursing care required. RESULTS: The patient characteristics, which affected the amount of nursing care, varied according to each DPC code. The major factors affecting the amount of nursing care were whether the patient had received a surgical (under general anesthetics) treatment or a non-surgical treatment and the level of activities of daily living (ADL) of the hospitalized patients. For those who had received a surgical operation for colon cancer, the patient's age also affected the amount of nursing care. CONCLUSIONS: The findings show that the method for the visualization of the amount of nursing care based on the classification of patient characteristics can be implemented into the electronic health record system. This method can then be used as a management tool to assure appropriate distribution of nursing resources.


Subject(s)
Colonic Neoplasms/nursing , Health Services Accessibility/statistics & numerical data , Hospital Information Systems , Lung Neoplasms/nursing , Nursing Staff, Hospital/statistics & numerical data , Stomach Neoplasms/nursing , Activities of Daily Living/classification , Age Factors , Aged , Current Procedural Terminology , Female , Health Services Accessibility/classification , Hospitals, University , Humans , Japan , Male , Middle Aged , Nursing Assessment/classification , Nursing Assessment/statistics & numerical data , Nursing Records/classification , Nursing Records/statistics & numerical data , Patient Care Planning/standards , Patient Care Planning/statistics & numerical data , Resource Allocation/classification , Resource Allocation/statistics & numerical data
4.
J Behav Health Serv Res ; 30(4): 433-43, 2003.
Article in English | MEDLINE | ID: mdl-14593666

ABSTRACT

This article examines 1997 national expenditures on mental health and substance abuse (MH/SA) treatment by 3 major age groups: 0-17, 18-64, and 65 and older. Of the total $82.4 billion in MH/SA expenditures, 13% went to children, 72% to adults, and 15% to older adults. MH/SA treatment expenditures made up 9% of total health care expenditures on children, 11% of total health care expenditures on adults, and 3% of total health care expenditures on older adults. Across the 3 age groups, distinct differences emerged in the distribution of MH/SA expenditures by provider-type. For example, about 85% of spending for youth was for specialty MH/SA providers, compared to 76% for adults and 51% for older adults. In addition, 33% of MH/SA spending for older adults went to nursing home care, while other age groups had almost no expenditures in nursing homes. Age-specific estimates enable policymakers, providers, and researchers to design programs and studies more appropriately tailored to specific age groups.


Subject(s)
Health Expenditures/statistics & numerical data , Mental Disorders/therapy , Mental Health Services/economics , Substance-Related Disorders/therapy , Adolescent , Adult , Age Factors , Aged , Child , Child, Preschool , Health Care Surveys , Health Expenditures/classification , Humans , Infant , Infant, Newborn , Mental Disorders/economics , Mental Disorders/epidemiology , Mental Health Services/classification , Middle Aged , Prevalence , Resource Allocation/classification , Substance-Related Disorders/economics , Substance-Related Disorders/epidemiology , United States/epidemiology
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