Background:
The effects of sleep deprivation are vast, ranging from increased stress responses, to lowered immunity and delayed wound healing. However, sleep disruptions are common in the inpatient setting. This study sought to quantify the number and frequency of inpatient sleep disturbances and analyze post-discharge outcomes (emergency department visit, readmission, death) among congestive heart failure (CHF) patients.
Methods:
Data were collected retrospectively from 30 randomly selected patients admitted for CHF and referred to a cardiac transitional care clinic from 2014 to 2017. Each night over the course of the hospitalization was broken into 12 one-hour intervals (1900-0659 hours), and the electronic health record was examined for 20 variables indicative of sleep disruption (e.g. vitals taken, medications dispensed, wound care) (Figure 1). Demographics and outcomes were compared between high (above median) and low (below median) groups for average number of nightly interval interruptions and average longest uninterrupted sleep interval (LUSI).
Results:
On average, patients had a length of admission of 5.4 nights, a LUSI of 2.9 hours (range: 1-4), and 6.3 disruptions between 1900-0659 hours (range: 3-8). The readmission rates for the total population were 23% at 30 days and 63% at 180 days. No significant differences were seen in demographics or outcomes up to 180 days post-discharge when comparing high and low patient groups in either average nightly interval interruptions or average LUSI.
Conclusion:
Although no differences were seen between groups, the majority of patients had poor outcomes (23% were readmitted at 30 days; 63% at 180 days) as well as poor sleep during their admission. The lack of sleep across the entire patient population may be contributing to the poor outcomes observed. Many of the variables reviewed (e.g. vitals taken, medications dispensed, etc.) had potentially elective timing, which suggests actionable changes to the inpatient process may be possible to improve sleep quantity and quality. This was an exploratory pilot study to determine the ability to use electronic health record data for this purpose. As such, the sample size was too small to detect differences. A larger sample size is needed to better understand the extent to which sleep disruptions impact patient outcomes.
Validation of Heart Failure Risk Equations in a Large, Contemporary Electronic Health Record Cohort
