OBJECTIVE: To evaluate the burden of hyponatremia in terms of hospital resource utilization, costs, and 30-day hospital readmission among patients hospitalized for heart failure (HF) in routine clinical practice. METHODS: Hyponatremic (HN) patients (≥18 years of age) with HF discharged between January 2, 2007 and March 31, 2010 were selected from the Premier Hospital Database and matched to non-HN HF patients using exact and propensity score matching. Univariate and multivariate statistics were utilized to compare hospital resource utilization (total and intensive care unit (ICU)) and associated costs and 30-day hospital readmission among cohorts. RESULTS: The study population included 51,710 subjects (HN = 25,855, non-HN = 25,855). In comparison to the non-HN cohort, length of stay (LOS) (7.7 ± 8.3 vs 6.3 ± 7.6 days, p < 0.001), hospitalization cost ($13,339 ± $19,273 vs $10,475 ± 15,157, p < 0.001), ICU LOS (4.9 ± 5.4 vs 4.2 ± 5.4 days, p < 0.001) and ICU cost ($7195 ± $9522 vs $5618 ± 10,919, p < 0.001) as well as rate of 30-day readmission (all cause: 25.3% vs 22.2%, p < 0.001; hyponatremia-related: 21.4% vs 5.0%, p < 0.001) were greater for the HN cohort. After adjustment, hyponatremia was associated with a 21.5% increase in hospital LOS, a 25.6% increase in hospital cost, a 13.7% increase in ICU LOS and a 24.6% increase in ICU cost. Additionally, hyponatremia was associated with increased risk of ICU admission (Odds Ratio (OR) = 1.58, [CI = 1.37, 1.84], p < 0.001) and 30-day hospital readmission (all cause: OR = 1.19, [CI = 1.14, 1.24], p < 0.001; hyponatremia-related: 5.10 [CI = 4.77, 5.46], p < 0.001). LIMITATIONS: Laboratory data for serum sodium level are not available in the Premier database and the severity of hyponatremia could not be established, although several patient variables were controlled for in this study by exact and propensity score matching techniques. CONCLUSIONS: Hyponatremia in HF patients is a predictor of increased hospital resource use and represents a potential target for intervention to reduce healthcare expenditures.
OBJECTIVE: To evaluate the burden of hyponatremia in terms of hospital resource utilization, costs, and 30-day hospital readmission among patients hospitalized for heart failure (HF) in routine clinical practice. METHODS: Hyponatremic (HN) patients (≥18 years of age) with HF discharged between January 2, 2007 and March 31, 2010 were selected from the Premier Hospital Database and matched to non-HN HFpatients using exact and propensity score matching. Univariate and multivariate statistics were utilized to compare hospital resource utilization (total and intensive care unit (ICU)) and associated costs and 30-day hospital readmission among cohorts. RESULTS: The study population included 51,710 subjects (HN = 25,855, non-HN = 25,855). In comparison to the non-HN cohort, length of stay (LOS) (7.7 ± 8.3 vs 6.3 ± 7.6 days, p < 0.001), hospitalization cost ($13,339 ± $19,273 vs $10,475 ± 15,157, p < 0.001), ICU LOS (4.9 ± 5.4 vs 4.2 ± 5.4 days, p < 0.001) and ICU cost ($7195 ± $9522 vs $5618 ± 10,919, p < 0.001) as well as rate of 30-day readmission (all cause: 25.3% vs 22.2%, p < 0.001; hyponatremia-related: 21.4% vs 5.0%, p < 0.001) were greater for the HN cohort. After adjustment, hyponatremia was associated with a 21.5% increase in hospital LOS, a 25.6% increase in hospital cost, a 13.7% increase in ICU LOS and a 24.6% increase in ICU cost. Additionally, hyponatremia was associated with increased risk of ICU admission (Odds Ratio (OR) = 1.58, [CI = 1.37, 1.84], p < 0.001) and 30-day hospital readmission (all cause: OR = 1.19, [CI = 1.14, 1.24], p < 0.001; hyponatremia-related: 5.10 [CI = 4.77, 5.46], p < 0.001). LIMITATIONS: Laboratory data for serum sodium level are not available in the Premier database and the severity of hyponatremia could not be established, although several patient variables were controlled for in this study by exact and propensity score matching techniques. CONCLUSIONS:Hyponatremia in HFpatients is a predictor of increased hospital resource use and represents a potential target for intervention to reduce healthcare expenditures.
Authors: Melissa O'Connor; Christopher M Murtaugh; Shivani Shah; Yolanda Barrón-Vaya; Kathryn H Bowles; Timothy R Peng; Carolyn W Zhu; Penny H Feldman Journal: Med Care Res Rev Date: 2015-07-14 Impact factor: 3.929
Authors: Mark E Dunlap; Paul J Hauptman; Alpesh N Amin; Sandra L Chase; Joseph A Chiodo; Jun R Chiong; Joseph F Dasta Journal: J Am Heart Assoc Date: 2017-08-03 Impact factor: 5.501