Insurance Status of Patients Admitted to Specialty Cardiac and Competing General Hospitals

Cram, Peter; Pham, Hoangmai H.; Bayman, Levent; Vaughan-Sarrazin, Mary

doi:10.1097/mlr.0b013e31816c43d9

Cited by 27 publications

(30 citation statements)

References 32 publications

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“…Data elements include patient demographics, primary and secondary diagnoses as captured by ICD-9-CM codes, insurance type (categorized as Medicare, Medicaid, private, uninsured, no charge, other), and discharge disposition (categorized as routine, short-term hospital, skilled nursing facility, intermediate care facility, another type of facility, home health care, against medical advice, or died). The NIS has been used extensively in prior health services research [15]. Weights for the NIS are provided by AHRQ to allow researchers to calculate nationally representative estimates.…”

Section: Methodsmentioning

confidence: 99%

Insurance Status and the Transfer of Hospitalized Patients

Hanmer¹,

Lü²,

Rosenthal³

et al. 2014

Ann Intern Med

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Background There is little objective evidence to support concerns that patients are transferred between hospitals based upon insurance status. Objective To examine the relationship between patients’ insurance coverage and inter-hospital transfer. Design We analyzed data from the 2010 National Inpatient Sample. Patients All patients aged 18-64 years discharged alive from U.S. acute care hospitals with one of five common diagnoses (biliary tract disease, chest pain, pneumonia, septicemia, skin or subcutaneous infection). Measurements For each diagnosis, we compared the proportion of hospitalized patients who were transferred to another acute-care hospital based upon insurance coverage (private, Medicare, Medicaid, and uninsured). We used logistic regression to estimate the odds of transfer for uninsured patients (reference category- privately insured) while adjusting for patient and hospital level factors. All analyses incorporated sampling and post-stratification weights. Results Among 315,748 patients discharged from 1051 hospitals with our five diagnoses, the percentage of patients transferred to another acute-care hospital varied from 1.3% (skin infection) to 5.1% (septicemia). In unadjusted analyses uninsured patients were significantly less likely to be transferred for three diagnoses (p<.05). In adjusted analyses, uninsured patients were significantly less likely to be transferred than privately insured patients for the four diagnoses: biliary tract disease (Odds Ratio (OR) 0.73 (95% Confidence interval (CI) 0.55-0.96)); chest pain (OR 0.63 (CI 0.44-0.89)); septicemia (OR 0.76 (CI 0.64-0.91)); and skin infections (OR 0.64 (CI 0.46-0.89)). Women were significantly less likely to be transferred than men for all diagnoses. Limitations This analysis relied on administrative data and lacked clinical detail. Conclusions Uninsured patients (and women) were significantly less likely to undergo inter-hospital transfer. Differences in transfer rates may contribute to healthcare disparities.

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Section: Methodsmentioning

confidence: 99%

Insurance Status and the Transfer of Hospitalized Patients

Hanmer¹,

Lü²,

Rosenthal³

et al. 2014

Ann Intern Med

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“…To the extent that patients with similar sociodemographics (and risk for complications) cluster within hospitals, [27][28][29] certain hospitals could benefit by having a relatively low-risk TKA population and see profits from TKA soar; alternatively, other hospitals with a predominantly higher risk TKA population could see TKA as financially detrimental based upon geographic location and catchment area alone. 30 There is certainly reason to be concerned that episode-of-care payments could provide additional incentive for hospitals and physicians to select lower risk patients while avoiding higher risk patients. 31 Of course if bundled payment amounts were adjusted to reflect each hospital's particular patient mix, such problems could be alleviated to some degree.…”

Section: Discussionmentioning

confidence: 99%

Bundled Payments for Elective Primary Total Knee Arthroplasty

Cram

Lü

2014

Geriatr Orthop Surg Rehabil

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Bundled payments have been proposed as a mechanism for restraining health care spending for total knee arthroplasty (TKA), but empirical data are limited. We used Medicare data to examine variation in payments for TKA during a window extending 30 days before to 90 days after TKA for 167 186 patients who underwent elective primary TKA in 2009. Mean Medicare payment was US$23 656. We found that 2.5% of patients incurred payments of >US$50 000 (0.2% >US$100 000). Payments were lower for men and for non-Hispanic whites but higher for patients with greater comorbidity. Episode-of-care payment for primary TKA varies substantially depending upon patient demographics and comorbidity. To the extent that similar patients tend to be clustered within hospitals, bundled payments could inadvertently cause financial harm to certain health systems while rewarding others.

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“…In the current study, we found that there was a higher proportion of transfers accepted into teaching hospitals, greater proportion of admissions on the weekend, and relatively fewer elective procedures performed. While NTH treated a greater proportion of lower socioeconomic status patients compared to teaching hospitals, socioeconomic factors influence outcomes, 20 and thus sicker patients treated at certain hospitals may reflect a different patient population based on nonmedical parameters, 21 and require further investigation. Since 2008, when centers were performing endovascular repair as feasible, and several reports described their long-term experience, the learning curve for transcatheter procedures seems to have stabilized.…”

Section: Discussionmentioning

confidence: 99%