Adverse Events Experienced by Patients Hospitalized without Definite Medical Acuity: A Retrospective Cohort Study
Physicians often consider various nonmedical factors in hospital admission decision-making and may admit socially tenuous patients despite low-acuity medical needs. Evidence showing whether these patients are subject to the same risks of hospitalization as those considered definitely medically appropriate is limited. Our study sought to inform this risk/benefit discussion by quantifying the number of adverse events (AEs) experienced by both patient populations by using the Institute for Healthcare Improvement Global Trigger Tool methodology. We found no difference in the percentage of admissions with AEs between the two groups (27.3% vs 29.3%; risk ratio 0.93, 95% CI 0.65-1.34, P = .70) nor in AEs per 1,000-patient days (76.8 vs 70.4; incidence rate ratio = 1.09, 95% CI 0.77-1.55, P = .61). Thus, the number of AEs experienced during hospitalization does not appear to be related to the appropriateness of admission based on the level of medical acuity.
© 2020 Society of Hospital Medicine
Evidence exists that physicians consider what may be called “social” or “nonmedical” factors (lack of social support or barriers to access) in hospital admission decision-making and that patients are hospitalized even in the absence of a level of medical acuity warranting admission.1-3 Although hospitalization is associated with the risk of adverse events (AEs),4 whether this risk is related to the medical acuity of admission remains unclear. Our study sought to quantify the AEs experienced by patients hospitalized without definite medical acuity compared with those experienced by patients hospitalized with a definite medically appropriate indication for admission.
METHODS
Setting and Database Used for Analysis
This study was conducted at an urban, safety-net, public teaching hospital. At our site, calls for medical admissions are always answered by a hospital medicine attending physician (“triage physician”) who works collaboratively with the referring physician to facilitate appropriate disposition. Many of these discussions occur via telephone, but the triage physician may also assess the patient directly if needed. This study involved 24 triage physicians who directly assessed the patient in 65% of the cases.
At the time of each admission call, the triage physician logs the following information into a central triage database: date and time of call, patient location, reason for admission, assessment of appropriateness for medical floor, contributing factors to admission decision-making, and patient disposition.
Admission Appropriateness Group Designation
To be considered for inclusion in this study, calls must have originated from the emergency department and resulted in admission to the general medicine floor on either a resident teaching or hospitalist service from February 1, 2018 to June 1, 2018. This time frame was selected to avoid the start of a new academic cycle in late June that may confound AE rates.
The designation of appropriateness was determined by the triage physician’s logged response to triage database questions at the time of the admission call. Of the 748 admissions meeting inclusion criteria, 513 (68.6%) were considered definitely appropriate on the basis of the triage physician’s response to the question “Based ONLY on the medical reason for hospitalization, in your opinion, how appropriate is this admission to the medicine floor service?” Furthermore, 169 (22.6%) were considered without definite medical acuity on the basis of the triage physician’s indication that “severity of medical problems alone may not require inpatient hospitalization” (Appendix Figure 1).
Study Design
Following a retrospective cohort study design, we systematically sampled 150 admissions from those “admitted without definite medical acuity” to create the exposure group and 150 from the “definitely medically appropriate” admissions to create the nonexposure group. Our sampling method involved selecting every third record until reaching the target sample size. This method and group sizes were determined prior to beginning data collection. Given the expected incidence of 33% AEs in the unexposed group (consistent with previous reports of AEs using the trigger tool5), we anticipated that a total sample size of 300 would be appropriate to capture a relative risk of at least 1.5 with 80% power and 95% confidence level.
