The Attributable Costs of Resistant Infections in Hospital Settings: Economic Theory and Application
Robert C. Owens, Lautenbach Ebbing in Antimicrobial Resistance, 2007
These same issues hold true for measuring the excess costs for resistant infections as well (20,38). Controlling for the confounding effects of severity of underlying disease both in patients with susceptible HAIs and in those with resistant HAIs has been a particularly difficult analytic issue to overcome in epidemiologic studies of AR. A number of recommendations have been advanced on the best way to adjust for differences in patient characteristics and severity of disease in studies of HAIs. Haley (43) recommended that researchers use multiple matching criteria, by selecting one or more control patients for every infected patient, in order to obtain a group of control subjects that would have “the same expected length of hospital stay and hospital costs” as infected patients would have had if they had not developed an infection. He further suggested the use of diagnosis-related groups (DRGs) as the best measure to predict patient length of stay and total hospital costs. Alternatively, Gross et al. (49) advocated using the number of comorbidities as a measure to control for severity of disease. Harris et al. (50) suggested that using SOI indexes that possess standardized scores would promote the comparison of results from different studies. Standardized scores that have been used include the Acute Physiology and Chronic Health Evaluation (APACHE) system, the Charlson index, and the McCabe-Jackson scale (51–53). Other indexes specific to a patient diagnosis, like the Zawacki score for burn victims, have also been used (54).
Measuring the Attributable Costs of Resistant Infections in Hospital Settings
Robert C. Owens, Paul G. Ambrose, Charles H. Nightingale in Antibiotic Optimization, 2004
For this reason, these same concerns and issues hold true for measuring the excess costs of resistant infections as well (30,14). Controlling for the confounding effects of severity of underlying disease both in patients with susceptible nosocomial infections and in those with resistant nosocomial infections has been a particularly difficult analytic issue to overcome in epidemiologic studies of antimicrobial resistance. A number of recommendations have been advanced on the best way to adjust for differences in patient characteristics and severity of disease in studies of nosocomial infections. Haley (25) recommended that researchers use multiple matching criteria, by selecting one or more control patients for every infected patient, in order to obtain control subjects that would have “the same expected length of hospital stay and hospital costs” as infected patients would have had if they had not developed an infection. He further suggested the use of diagnosis-related groups (DRGs) as the best measure to predict patient length of stay and total hospital costs. Alternatively, Gross et al. (31) advocated using the number of comorbidities as a measure to control for severity of disease. Harris et al. (32) suggested that using SOI indexes that possess standardized scores would promote the comparison of results from different studies. Standardized scores that have been used include the Acute Physiology and Chronic Health Evaluation (APACHE) system, the Charlson index, and the McCabe-Jackson scale (33-35).
Healthcare Payment Systems
Jennifer Doley, Mary J. Marian in Adult Malnutrition, 2023
The principal diagnosis necessitating hospital admission decides the Major Diagnostic Category (MDC) assigned to the patient for that hospital stay.3 Within this MDC, the individual Diagnosis Related Group (DRG) is determined based on details of the patient’s diagnosis and hospital treatment. If the patient is managed medically, the principal diagnosis determines the DRG assignment; if the patient is primarily managed surgically, then the type of surgery will determine the DRG assignment. Secondary diagnoses, known as Complications or Comorbidities (CCs) and Major Complications or Comorbidities (MCCs), can increase the cost of care above what would have been required if the patient only needed treatment for the principal diagnosis. When these secondary diagnoses are documented, treated, and coded, the patient may be assigned to a different severity level within the DRG grouping; this is then known as the Medicare Severity – DRG (MS-DRG). See Figure 14.1. A higher payment is given to hospitals for MS-DRGs associated with a CC, and an even higher payment for MS-DRGs associated an MCC.3
Cluster analysis identifies unmet healthcare needs among patients with rheumatoid arthritis
Published in Scandinavian Journal of Rheumatology, 2022
N Mars, AM Kerola, MJ Kauppi, M Pirinen, O Elonheimo, T Sokka-Isler
The healthcare utilization data involved a system similar to diagnosis-related group (DRG), one suitable for both inpatient and outpatient care. This was used for grouping all the RA patients’ diagnoses for fiscal year 2014, and for estimating the respective health service-related direct costs (€; price level for 2014). The cost estimation tool acknowledges disease category, age, gender, healthcare unit and provider, and procedures, and comprises all public healthcare contacts: both primary and speciality care, inpatient and outpatient care, the emergency department, and contacts with all healthcare professionals (physicians, nurses, and rehabilitation workers). Additional details of both data sets have been described previously (10). We combined the data sets using the unique Finnish national identification numbers, selecting RA patients with at least one healthcare contact in 2014. As healthcare utilization data were obtained for 2014, our inclusion criteria were patients diagnosed with RA before or in 2014, who had visits to the rheumatology clinic within 5 years prior (2010–2014) to collection of cost data. To capture patterns of persistent disease activity, pain, and physical disability, we used all individual-level clinical data available for these patients within the registry (2007–2016).
Economic burden of hospital malnutrition and the cost–benefit of supplemental parenteral nutrition in critically ill patients in Latin America
Published in Journal of Medical Economics, 2018
Maria Isabel Toulson Davisson Correia, Mario Ignacio Perman, Lorenzo Pradelli, Abdul Jabbar Omaralsaleh, Dan Linetzky Waitzberg
A cost–benefit analysis based on clinical data from prior studies and country-specific cost data showed that administration of SPN to critically ill adults with persistent caloric deficits on EN alone a meaningful cost benefit which is principally mediated through an improvement in cumulative caloric balance and a corresponding reduction in the risk of HAI. Model-derived estimates for clinical outcomes and resource utilization suggest that the administration of SPN to ICU patients who fail to reach ≥60% of the targeted nutrition delivery with EN would yield an estimated annual cost reduction of $10.2 million across the eight Latin American countries compared with continued administration of EN alone. On average, the use of SPN resulted in net savings of $194.50 per supplemented patient, with the cost of SPN more than offset by the reduced cost of antimicrobial therapy and the shorter duration of stay in the ICU and ward. The latter benefit is particularly important, as limited bed capacity, increased demand and an increasing trend toward the use of diagnosis-related group (DRG)-based reimbursement in Latin America create a powerful incentive for public hospitals to minimize the duration of hospitalization. Coupled with the relatively low rate of SPN use observed in the Latin America Screening Day study26, the cost–benefit analysis suggests that both improved clinical outcomes and significant cost savings can be achieved through the adoption of SPN as a therapeutic strategy in critically ill patients who fail to receive adequate nutrient intake from EN.
Optimizing health system response to patient’s needs: an argument for the importance of functioning information
Published in Disability and Rehabilitation, 2018
Maren Hopfe, Birgit Prodinger, Jerome E. Bickenbach, Gerold Stucki
Health financing, understood as methods of assist in ensuring access to needed services, health coverage, and protection against financial hardship, is another concern for improving the health system response to patients. Given scarcity, financing systems are typically constrained by cost containment measures. As a result, health systems are challenged to generate funding and accumulate and allocate available funds to best cover the health and health-related needs of individuals while at the same time providing financial risk protection for the population. In 2012, curative and rehabilitative health services accounted for more than 50% of the total health expenditures in the EU Member States with hospitals having the highest share of health expenditures (up to 45%), followed by ambulatory health service providers (up to 30%) [38]. The most common reimbursement schemes for these services are fee-for-service, capitation, and per diem, salary, or prospective payment systems, such as casemix systems, the most common of which uses diagnosis-related groups (DRGs). DRGs are often based solely on demographic, diagnostic, and therapeutic information and neglect differences in patient’s needs for services that are not related to diagnosis or treatment. Two patients with the same underlying diagnosis, however, may have different health service needs depending on their level of functioning and the environmental factors that shape their lives.
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