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Business Model
Published in Gennadi Saiko, Bringing a Medical Device to the Market A Scientist's Perspective, 2022
The key features of Hospital Inpatient Payment Methodology are: “Payment system: Inpatient Prospective Payment System (IPPS).Method: Medical Severity-Diagnosis Related Groups, MS-DRGs are the predominant method for paying for inpatient hospital services.Coding: ICD-10-CM diagnosis and ICD-10-PCS procedure codes.”29‘There are around 900 DRGs to which any medical or surgical admission will be assigned based on patient diagnoses, procedures. Each DRG has the predetermined resources it should require to take care of the average patient.Each DRG has a “weight” that is multiplied by a conversion factor to determine payment.New Tech Pass Through Payment allows the cost of new tech to be paid at/near the retail price for a period of two years if it meets a cost threshold and achieves “substantial clinical improvement.As a result, hospitals will adopt less expensive technologies wherever they can because their revenue is fixed.”30
Diagnosis-Related Groups: Are Patients in Jeopardy?
Published in Marilyn Sue Bogner, Human Error in Medicine, 2018
In 1983, a new law was enacted that dramatically changed the way hospitals are reimbursed for health-care services. To implement the law, Yale University researchers developed a model to classify patients into groups according to their diagnosis. It was their premise that clinically similar groups of patients would consume similar resources (Curtin & Zurlage, 1984). The classification system became known as Diagnosis Related Groups (DRGs).
Value and Waste
Published in Mark Graban, John Toussaint, Lean Hospitals, 2018
Trends toward “value-based purchasing” (VBP) and other new reimbursement models of paying for outcomes and quality are in line with this thinking and with Lean principles. Capitated payment systems, diagnosis-related groups (DRGs), and accountable care organizations (ACOs) are examples of systems that attempt to pay for results or outcomes instead of paying for activity, often known as “fee for service.”
Patient-centric surgeons’ case mix problem
Published in IISE Transactions on Healthcare Systems Engineering, 2022
The plan could also be used as a baseline for comparison and control of hospital finance. In the US, for example, hospital reimbursements could be based on the Diagnosis-Related Groups (or DRGs) that classify patients according to their medical conditions and morbidity (Davis, 2020). A standard weight is assigned to each DRG that is associated with the resources necessary to provide care for the patient’s condition. Hospitals that accept DRG-based reimbursements can set their budget using the TPV. An actual TPV could be higher than projected if operations performed by surgeons produce good patient outcomes (e.g. minimal medical complications, low hospital readmission, and rapid patient recovery), which could result in cost savings and good financial performance for hospitals. Clearly, accurately forecasting patient demands and planning the surgeons’ case mix to meet those demands with good patient outcomes can be crucial in achieving the hospital’s financial goals.
Prediction of the healthcare resource utilization using multi-output regression models
Published in IISE Transactions on Healthcare Systems Engineering, 2018
Liwen Cui, Xiaolei Xie, Zuojun Shen, Rui Lu, Haibo Wang
Higher efficiency in the healthcare system and improved payment policy are strongly desired worldwide. Predictive analytics of the healthcare resource utilization is instrumental for better allocation and management of medical resources. Furthermore, prediction models with high accuracy can facilitate decision making about pricing and reimbursement policy. Recently, there has been growing interest in healthcare cost prediction using machine learning techniques. However, it is insufficient to use cost as the only measure for healthcare resource utilization. For instance, the Diagnosis Related Group (DRG) system, a widely used management tool to group patients with similar consumption of medical resources, uses both cost and length of stay (LoS) to measure the resource utilization by patients. Moreover, the clinical pathway, created to reduce variations in care delivery to improve care quality and efficiency, also focuses on cost and LoS. These motivate us to jointly consider multiple measures in prediction models, depending on the implementation background and practical purposes (Zhou et al., 2011; Lee et al., 2010).
Exploring clinical metrics to assess the health impact of traffic injuries
Published in International Journal of Injury Control and Safety Promotion, 2018
Sara Ferreira, Marco Amorim, António Couto
In fact, besides ICD, which is used to describe the patient diagnostic, other medical code named diagnosis-related group (DRG) is commonly used in hospitals all over the world as the principal mean of reimbursing hospitals for acute inpatient care. However, in contrast to the ICD for which was developed systematic process to obtain an injury scale for traffic safety analysis, no process was established to a systematic use of DRG to analyse traffic injuries impact. Nevertheless, the DRG and ICD as clinical metrics have the main potential to allow a benchmarking analysis among countries and/or regions because they are supported by international standard codes. The long history and experience on using these metrics ensure the necessary stability of the estimated process to support a robust impact analysis across countries and regions. As such, the present study explored the use of clinical metrics, ICD and DRG as well as the length of hospital stay (LHS), reported by hospitals to assess the impact of traffic injuries. Using these metrics, health care costs, MAIS and injury description (e.g. body region) were obtained. Then, a statistical analysis of these metrics was conducted in order to assess the impact of traffic injuries on victims (type of injury and severity) as well as on medical care (health care costs and length of hospital stay). The objectives were (1) to explore the associations between these various metrics and the consequences of crashes mainly through the costs and severity, and (2) to develop a robust model to easily and routinely estimate the impact of injuries supported by DRG and ICD data.