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      La gestión financiera hospitalaria y los errores en la creación de grupos relacionados por diagnóstico Translated title: Hospital financial management and errors in the creation of diagnosis-related groups

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          Abstract

          RESUMEN Introducción: La gestión sanitaria requiere herramientas para tomar decisiones a nivel local y sistémico en prestadores de salud, con información de calidad y oportuna, para optimizar procesos organizacionales. Objetivo: Identificar, mediante análisis del estado del conocimiento, la generación de errores en creación de grupos relacionados por diagnóstico que afectan la estrategia de gestión financiera hospitalaria. Desarrollo: Se revisaron 487 trabajos de investigación, 54 de ellos identificaron procesos de generación del constructo estudiado, con errores y evidenciados en su materialización. Estos errores se conglomeraron de acuerdo al modelo original de 3M. Entre los encontrados se precisaron como omisiones en documentación de los registros médicos; mala calidad en conjunto mínimo de datos básicos; inexactitudes en codificación diagnóstica y de procedimientos; insuficiente agrupación de grupos relacionados al diagnóstico, variación del índice casuístico; deficiencias en formación de equipos de trabajo y procesos de auditorías, además discrepancias en asignación de grupos relacionados al diagnóstico. Reconocer y abordar estos errores permitirán optimizar la eficiencia en la gestión sanitaria. Conclusiones: Se identifican errores en implementación de los grupos relacionados al diagnóstico, los que se focalizan en subprocesos de captura; codificación de la producción clínica y en errores del personal sanitario en codificación. Estos tipos de omisiones pueden contribuir en formas claves de evaluación del desempeño de la gestión clínico-asistencial, más aún cuando esta se asocia a estructura de facturación y costo por paciente en el actual sistema de salud chileno.

          Translated abstract

          ABSTRACT Introduction: Healthcare management requires tools to make decisions at the local and systemic level in healthcare providers, with quality and timely information, to optimise organisational processes. Objective: To identify, through analysis of the state of knowledge, the generation of errors in the creation of diagnosis-related groups that affect hospital financial management strategy. Development: 487 research papers were reviewed, 54 of them identified processes of generation of the studied construct, with errors and evidenced in their materialization. These errors were grouped according to the original 3M model. Among those found were omissions in medical record documentation; poor quality in the minimum set of basic data; inaccuracies in diagnostic and procedure coding; insufficient grouping of diagnosis-related groups, variation in the casuistic index; deficiencies in team formation and audit processes; and discrepancies in the assignment of diagnosis-related groups. Recognising and addressing these errors will optimise efficiency in healthcare management. Conclusions: Errors were identified in the implementation of diagnosis-related groups, focusing on capture sub-processes, coding of clinical output and coding errors by healthcare staff. These types of omissions can contribute to key forms of performance evaluation of clinical care management, especially when this is associated with the billing structure and cost per patient in the current Chilean health system.

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          Most cited references55

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          Review of Diagnosis-Related Group-Based Financing of Hospital Care

          Since the 1990s, diagnosis-related group (DRG)-based payment systems were gradually introduced in many countries. The main design characteristics of a DRG-based payment system are an exhaustive patient case classification system (ie, the system of diagnosis-related groupings) and the payment formula, which is based on the base rate multiplied by a relative cost weight specific for each DRG. Cases within the same DRG code group are expected to undergo similar clinical evolution. Consecutively, they should incur the costs of diagnostics and treatment within a predefined scale. Such predictability was proven in a number of cost-of-illness studies conducted on major prosperity diseases alongside clinical trials on efficiency. This was the case with risky pregnancies, chronic obstructive pulmonary disease, diabetes, depression, alcohol addiction, hepatitis, and cancer. This article presents experience of introduced DRG-based payments in countries of western and eastern Europe, Scandinavia, United States, Canada, and Australia. This article presents the results of few selected reviews and systematic reviews of the following evidence: published reports on health system reforms by World Health Organization, World Bank, Organization for Economic Co-operation and Development, Canadian Institute for Health Information, Canadian Health Services Research Foundation, and Centre for Health Economics University of York. Diverse payment systems have different strengths and weaknesses in relation to the various objectives. The advantages of the DRG payment system are reflected in the increased efficiency and transparency and reduced average length of stay. The disadvantage of DRG is creating financial incentives toward earlier hospital discharges. Occasionally, such polices are not in full accordance with the clinical benefit priorities.
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            Diagnosis-related group (DRG)-based case-mix funding system, a promising alternative for fee for service payment in China.

            Fee for services (FFS) is the prevailing method of payment in most Chinese public hospitals. Under this retrospective payment system, medical care providers are paid based on medical services and tend to over-treat to maximize their income, thereby contributing to rising medical costs and uncontrollable health expenditures to a large extent. Payment reform needs to be promptly implemented to move to a prospective payment plan. The diagnosis-related group (DRG)-based case-mix payment system, with its superior efficiency and containment of costs, has garnered increased attention and it represents a promising alternative. This article briefly describes the DRG-based case-mix payment system, it comparatively analyzes differences between FFS and case-mix funding systems, and it describes the implementation of DRGs in China. China's social and economic conditions differ across regions, so establishment of a national payment standard will take time and involve difficulties. No single method of provider payment is perfect. Measures to monitor and minimize the negative ethical implications and unintended effects of a DRG-based case-mix payment system are essential to ensuring the lasting social benefits of payment reform in Chinese public hospitals.
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              Early prediction of diagnostic-related groups and estimation of hospital cost by processing clinical notes

              As healthcare providers receive fixed amounts of reimbursement for given services under DRG (Diagnosis-Related Groups) payment, DRG codes are valuable for cost monitoring and resource allocation. However, coding is typically performed retrospectively post-discharge. We seek to predict DRGs and DRG-based case mix index (CMI) at early inpatient admission using routine clinical text to estimate hospital cost in an acute setting. We examined a deep learning-based natural language processing (NLP) model to automatically predict per-episode DRGs and corresponding cost-reflecting weights on two cohorts (paid under Medicare Severity (MS) DRG or All Patient Refined (APR) DRG), without human coding efforts. It achieved macro-averaged area under the receiver operating characteristic curve (AUC) scores of 0·871 (SD 0·011) on MS-DRG and 0·884 (0·003) on APR-DRG in fivefold cross-validation experiments on the first day of ICU admission. When extended to simulated patient populations to estimate average cost-reflecting weights, the model increased its accuracy over time and obtained absolute CMI error of 2·40 (1·07%) and 12·79% (2·31%), respectively on the first day. As the model could adapt to variations in admission time, cohort size, and requires no extra manual coding efforts, it shows potential to help estimating costs for active patients to support better operational decision-making in hospitals.
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                Author and article information

                Journal
                infd
                Infodir
                Infodir
                Editorial de Ciencias Médicas (La Habana, , Cuba )
                1996-3521
                August 2023
                : 41
                : e1326
                Affiliations
                [3] Castilla y León orgnameUniversidad Católica de Ávila Spain
                [1] Santiago de Chile orgnameAcadémica de Universidad Andrés Bello Chile
                [2] orgnameUniversidad Católica de Santiago de Guayaquil Ecuador
                [4] Malleco orgnameUniversidad Arturo Prat, Sede Victoria Chile
                Article
                S1996-35212023000200001 S1996-3521(23)00004100001
                da48e573-7ac1-4f26-ac34-2ef7be3ffef3

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 23 August 2022
                : 14 April 2023
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 55, Pages: 0
                Product

                SciELO Cuba

                Categories
                ARTÍCULO DE REVISIÓN

                grupos relacionados por el diagnóstico,codificación clínica,atención médica,diagnosis-related groups,clinical coding,medical care

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