Sooner or Later? Health Information Technology, Length of Stay, and Readmission Risk

Abstract

Adequate length of stay (LOS) during hospitalization is not only a critical determinant of quality of care, but can be a useful predictor of the risk of future readmissions. Recent studies have shown alarming evidence that the United States leads developed nations in terms of shorter hospital stays, rendering patients with greater risk of future readmissions. We focus on deviation between hospital LOS and the geometric mean LOS (GMLOS), a guideline for care delivery stipulated by the Centers for Medicare and Medicaid Services (CMS). Our objective is to establish the relationship between LOS and readmission risk, examine the role of health IT in reducing the deviation of LOS, and address cost trade‐offs between early discharges and readmissions. Based on a large panel of congestive heart failure (CHF) patients during a 4‐year period, we find that implementation of health IT applications is associated with a reduction in the deviation between LOS and GMLOS. This deviation is associated with a significant increase in future 30‐day readmission risk. Patients whose inpatient stays are shorter than the GMLOS guideline, by 1 day or more, are likely to exhibit a 1.1% greater risk of readmission, and even shorter stays are likely to further exacerbate their readmission risk. Further, we find that the total readmission costs are much higher than the costs incurred in keeping patients longer during their initial hospital visit. Our results have important policy implications for providers and hospital administrators with respect to their discharge policies of CHF patients.

Health information technology and hospital performance the role of health information quality in teaching hospitals

“…HITs can also increase the efficiency of tracking and following-up insurance coverage, bad debts, and billings ( Garrido et al., 2004 ; Girosi et al., 2005 ; Lee and Choi, 2019 ). Oh, Zheng, and Bardhan (2018) studied the role of IT in hospital operational efficiency based on the deviation between hospital length of stay and the geometric mean LOS (GMLOS) guidelines; they found that implementation of HIT applications for operational coordination of patient care increases hospitals’ adherence capabilities related to standard guidelines on length of stay Thus, it can be argued that HIT can enhance hospital operational efficiency.…”

Telehealth Adoption and Discontinuation by US Hospitals: Results From 2 Quasi-Natural Experiments

“…We included several controls from these data sources to account for rival explanations. Controls and covariates were derived from a literature review [24][25][26][27][28][29][30]. Tables 1 and 2 describe the relevant variables.…”

“…Control group selection and formation is discussed later in this section. This design followed other notable studies that assessed the impact of health information technology adoption and use on outcomes [28][29][30][31] as well as recommendations on effectively estimating causal effects by means of observational data [32,33]. This design is appropriate for estimating causal effects when pre-and posttreatment observational data are available, treatment and control groups with sufficiently balanced covariates and common trends before treatment can be established, and exogenous shocks can be assumed to be consistent between groups [34].…”

Differentiating Interhospital Transfer Types: Varied Impacts and Diverging Coordination Strategies

“…We also include the count of current procedural terminology (CPT, a type of medical procedure and service code used in ED care) in the sender and the count of inpatient chronic conditions (ICC) in the receiver. In addition, we include total charge to control for the amount of care delivered to the patient, and we include LOS to control for the process quality (Oh et al 2018) when the dependent variable is readmission or mortality. The workload in a hospital can be a potential driver of non-clinical transfer decisions.…”