Introduction
Hospital readmissions are common and expensive, with nearly 20% of Medicare patients being readmitted to a hospital within 30 days of discharge at an overall cost of nearly 20 billion US dollars per year (Jencks, Williams and Coleman 2009). Because of this high frequency and cost, hospital readmissions within 30 days of discharge are a target for health care cost savings in the Medicare Hospital Readmission Reduction Program (HRRP). The HRRP aims to incentivize hospitals and health systems to reduce readmissions through reductions in payments to hospitals with higher than expected readmission rates (Centers for Medicare and Medicaid Services, 2016). Because of the HRRP initiative, health care organizations are investing considerable resources into efforts to reduce hospital readmission.
The underlying risk factors for hospital readmission are diverse. Studies have identified age, race, having a regular health care provider, major surgery, medical comorbidities, length of hospital stay, previous admissions in the last year, failure to transfer important information to the outpatient setting, discharging patients too soon, the number of medications at discharge, and many other risk factors for hospital readmission within 30 days (Auerbach et al, 2016; Picker et al., 2015; Hasan et al, 2010; Silverstein et al., 2008). Despite identifying with these risk factors, healthcare providers have poor accuracy in predicting which patients are at high risk of hospital readmission without a risk assessment tool (Allaudeen et al., 2011).
Readmission risk assessment can be accomplished with a variety of assessment tools that range from multidisciplinary patient interviews to simple screening tools using a handful of variables (Zhou et al, 2016; Kansagara et al, 2011; Silverstein et al., 2008; Smith et al., 2000). These tools use risk factors such as age, ethnicity, socioeconomic status, severity of illness, previous hospitalizations, and other factors to predict who is likely to be readmitted.
The easy to use HOSPITAL score is one such screening tool (Donzé, Aujesky, William and Schnipper, 2013). The HOSPITAL score uses 7 readily available clinical predictors to accurately identify patients at high risk of potentially avoidable hospital readmission within 30 days. This score has been internationally validated in a population of over 100,000 patients at large academic medical centers (average size of 975 beds) and has been shown to have superior discriminative ability over some prediction tools (Kansagara et al, 2011; Donzé, Aujesky, William and Schnipper, 2013; Donzé et al, 2016).
Another simple prediction model for predicting hospital readmission which uses both administrative and primary data is the LACE index (van Walraven et al., 2010). The LACE index uses four variables to predict the risk of death or nonelective 30-day readmission after hospital discharge among both medical and surgical patients: length of stay (L), acuity of the admission (A), comorbidity of the patient (C) and emergency department use in the duration of 6 months before admission (E) (van Walraven et al., 2010). This model has been internally validated using data collected from 4,812 patients discharged from 11 community hospitals in Ontario, and it was externally validated using administrative data collected randomly from 1,000,000 discharges also in Ontario (van Walraven et al., 2010). The LACE index has variable results in the literature outside Ontario. The LACE index has been shown to have moderate discrimination in studies conducted in North America with over 26,000 Medicare admissions (Garrison, Robelia, Pecina, & Dawson, 2016), 110,000 discharges in the Chicago, Illinois area (Tong, Erdmann, Daldalian, Li, & Esposito, 2016) and 600 patients in a community hospital (Spiva, Hand, VanBrackle, & McVay, 2016). The LACE index had fair discrimination in a study of 5,800 patients in Singapore (Low et al., 2015) and poor discrimination in a study done on about 500 patients in UK with an Direct comparisons between the HOSPITAL score and LACE index in a nationwide sample of Medicare patients admitted to the hospital for any reason showed no significant differences (Garrison, 2016). This is contrasted by comparisons of the HOSPITAL score and LACE index from Denmark (Cooksley et al., 2015) and Switzerland (Aubert et al., 2016) which indicate the HOSPITAL score has superior performance in predicting the risk of hospital readmission.
Recent studies have indicated that single risk factors such as the number of prescribed medications at the time of hospital discharge (Picker et al., 2015) or the presence of any unstable vital signs (Nguyen et al., 2017) may be effective predictors of hospital readmission within 30 days of discharge. Nguyen and colleagues found vital sign instability at the time of hospital discharge in nearly 20% of the study population of nearly 33,000 individuals from Northern Texas, USA. Individuals with vital sign instabilities were at increased risk of death and hospital readmission within 30 days of discharge. The risk of readmission or death was 17% with one unstable vital sign, 21% with two unstable vital signs, and 26% with three or more unstable vital signs.
A study of the association between vital signs instability and adverse clinical outcome is patients admitted with pneumonia showed similar correlations (Halm et al., 2002). The authors looked at 680 patients admitted with pneumonia and found that 13.7% of patients discharged with instability of one vital sign and 46.2% of those with two or more instabilities were readmitted in 30 days compared to 10.5% of patients without instability (p < .003). A study done at the surgical ward showed that patients admitted with hip fractures has higher risk of readmission if they have an active clinical issue at discharge (OR 1.7, CI: 1.2-2.3) (Halm et al., 2003).
This study aims to compare vital sign instability on the day of discharge with the HOSPITAL score and LACE index as predictors of hospital readmission within 30 days of discharge in a moderate sized (507 bed) university affiliated hospital located in the United States of America.