We examined risks for first hospitalization and the rate, risk factors, costs, and 1‐year outcome of 30‐day readmission among patients admitted for complications of cirrhosis. Data were retrospectively analyzed for adult patients with cirrhosis residing in Minnesota, Iowa, or Wisconsin and admitted from 2010 through 2013 at both campuses of the Mayo Clinic Hospital in Rochester, MN. Readmission was captured at the two hospitals as well as at community hospitals in the tristate area within the Mayo Clinic Health System. The incidence of hospitalization for complications of cirrhosis was 100/100,000 population, with increasing age and male sex being the strongest risks for hospitalization. For the 2,048 hospitalized study patients, the overall 30‐day readmission rate was 32%; 498 (24.3%) patients were readmitted to Mayo Clinic hospitals and 157 (7.7%) to community hospitals, mainly for complications of portal hypertension (52%) and infections (30%). Readmission could not be predicted accurately. There were 146 deaths during readmission and an additional 105 deaths up to 1 year of follow‐up (50.4% total mortality). Annual postindex hospitalization costs for those with a 30‐day readmission were substantially higher ($73,252) than those readmitted beyond 30 days ($62,053) or those not readmitted ($5,719). At 1‐year follow‐up, only 20.4% of patients readmitted within 30 days were at home. In conclusion, patients with cirrhosis have high rates of hospitalization, especially among men over 65 years, and of unscheduled 30‐day readmission. Readmission cannot be accurately predicted. Postindex hospitalization costs are high; nationally, the annual costs are estimated to be more than $4.45 billion. Only 20% of patients readmitted within 30 days are home at 1 year. (Hepatology Communications 2018;2:188–198)
Obesity is associated with longer hospital stays and higher costs in total knee arthroplasty. The effect of obesity on costs appears to be independent of obesity-related comorbid conditions and complications.
BackgroundResearch addressing value in healthcare requires a measure of cost. While there are many sources and types of cost data, each has strengths and weaknesses. Many researchers appear to create study-specific cost datasets, but the explanations of their costing methodologies are not always clear, causing their results to be difficult to interpret. Our solution, described in this paper, was to use widely accepted costing methodologies to create a service-level, standardized healthcare cost data warehouse from an institutional perspective that includes all professional and hospital-billed services for our patients.MethodsThe warehouse is based on a National Institutes of Research–funded research infrastructure containing the linked health records and medical care administrative data of two healthcare providers and their affiliated hospitals. Since all patients are identified in the data warehouse, their costs can be linked to other systems and databases, such as electronic health records, tumor registries, and disease or treatment registries.ResultsWe describe the two institutions’ administrative source data; the reference files, which include Medicare fee schedules and cost reports; the process of creating standardized costs; and the warehouse structure. The costing algorithm can create inflation-adjusted standardized costs at the service line level for defined study cohorts on request.ConclusionThe resulting standardized costs contained in the data warehouse can be used to create detailed, bottom-up analyses of professional and facility costs of procedures, medical conditions, and patient care cycles without revealing business-sensitive information.After its creation, a standardized cost data warehouse is relatively easy to maintain and can be expanded to include data from other providers. Individual investigators who may not have sufficient knowledge about administrative data do not have to try to create their own standardized costs on a project-by-project basis because our data warehouse generates standardized costs for defined cohorts upon request.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-017-2327-8) contains supplementary material, which is available to authorized users.
Background The number of obese patients undergoing THA is increasing. Previous studies have shown that obesity is associated with an increased likelihood of complications after THA, but there is little information regarding the impact of obesity on medical resource use and direct medical costs in THA. Questions/purposes We sought to examine the relationship between obesity, length of stay, and direct medical costs in a large cohort of patients undergoing THAs. Methods The study included 8973 patients who had undergone 6410 primary and 2563 revision THAs at a large US medical center between January 1, 2000, and September 31, 2008. Patients with bilateral procedures within 90 days after index admission and patients with acute trauma were excluded. Data regarding clinical, surgical characteristics, and complications were obtained from the original medical records and the institutional joint registry. Patients were classified into eight groups based on their BMI at the time of surgery. Direct medical costs were calculated by using standardized, inflation-adjusted costs for services and procedures billed during hospitalization and the 90-day window. Study end points were hospital length of stay, direct medical costs during hospitalization, and the 90-day window. End points were compared across the eight BMI categories in multivariable risk-adjusted linear regression models. Results Mean length of stay and the direct medical costs were lowest for patients with a BMI of 25 to 35 kg/m 2 . Increasing BMI was associated with longer hospital stays and costs. Every five-unit increase in BMI beyond 30 kg/ m 2 was associated with approximately USD $500 higher hospital costs and USD $900 higher 90-day costs in primary THA (p = 0.0001), which corresponded to 5% higher costs. The cost increase associated with BMI was
Purpose: To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. Methods: We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of costeffectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. Results: We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but costeffectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. Conclusion: We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their costeffectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.
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