Factors influencing the length of hospital stay of patients with heart failure

Abstract

Introduction: Heart failure (HF) is characterised by frequent hospital admissions and prolonged length of hospital stay. Admissions for HF have increased over the last decade while length of stay has decreased; the reasons for this change in length of stay are uncertain. This study investigates the effect of patient-related variables, in-hospital progress and complications on length of stay. Methods: Patients admitted to Auckland Hospital general medical service and randomised into the Auckland Heart Failure Management Programme were included in this study. Results: One hundred and ninety-seven patients were included in this study. Mean age 73 years, mean left ventricular ejection fraction 32%; 52% had one or more previous HF admissions and 75% were New York Heart Association class IV at admission. Median length of hospital stay was 6 days (IQR 4, 9) which is comparable to the national average from New Zealand admission databases. Longer than average length of stay, defined as )6 days, was associated with the presence of peripheral congestion, duration of treatment with intravenous diuretic, the development of renal impairment, other acute medical problems at admission, iatrogenic complications during hospital stay, and social problems requiring intervention. Factors independently associated with length of stay in the top quartile ()10 days) on logistic regression included the presence of oedema at admission (OR 10.5), change in weight during stay (OR 1.3), duration of treatment with iv diuretic (OR 7.5), the development of renal impairment (OR 9.8), concurrent respiratory problems requiring specific treatment (OR 3.8), and social problems requiring intervention (OR 6.8). Conclusions: Peripheral congestion, concomitant acute medical problems requiring specific treatment, the development of renal impairment and the presence of social problems were related to a longer than average length of hospital stay. Multivariate models only partly explained variance in hospital stay, suggesting the importance of pre-admission and post-discharge factors, including the healthcare environment, the availability of primary and secondary care resources, and the threshold for hospital admission.

Loop Diuretic Therapy in Heart Failure: The Need for Solid Evidence on a Fluid Issue

“…21 The duration of diuretic therapy may be a prognostic factor and predictor of morbidity by impacting hospital length of stay. 22 Hospital length of stay can be due to extent of congestion, but several actions exerted by parenteral diuretics may independently contribute to in-hospital complications. 22 Loop diuretics have been associated with worsening renal function (WRF).…”

“…22 Hospital length of stay can be due to extent of congestion, but several actions exerted by parenteral diuretics may independently contribute to in-hospital complications. 22 Loop diuretics have been associated with worsening renal function (WRF). However, elevated central venous pressure leading to venous congestion may be a stronger factor driving WRF in ADHF patients than intravascular volume depletion from diuretic overuse.…”

Factors Affecting the Average Length of Stay of the Patients in the Inpatient Department in a Tertiary Care Centre in North India

“…[19] Age: The analysis of the data revealed that the mean age of the patients admitted in IPD in the Fortis Escorts Hospital was 56.15 years (SD ± 17.70), the minimum age was 7 years and maximum age was 92 years. Wright SP et al (2003) in his study reported a mean age of 73 years (S.D. 10.8).…”

“…10.8). [20] Agboado G et al (2012) in a cross-sectional study of factors influencing the length of hospital stay among patients admitted with chronic obstructive airway disease reported a mean age of 70.1 years. [21] Sex: The analysis of the data revealed that out of 100 patients, 62 (62%) were males and 38 (38%) was females.…”

“…Wright SP et al 2003 in their study of factors influencing the length of hospital stay of patients with heart failure found that 60% were males, 40% were females and a male: female ratio of 1.5: 1. [20] Residence: Out of 100 patients, 55 (55%) were from rural areas and 45 (45%) were from urban areas. The association of the place of residence with LOS was not statistically significant (p=0.36).…”