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1.
BMJ Open Qual ; 11(3)2022 09.
Article in English | MEDLINE | ID: mdl-36122996

ABSTRACT

Crowding and boarding are common issues facing emergency departments (EDs) in the USA. These issues have negative effects on efficiency, patient care, satisfaction and healthcare team well-being. Data from an audit of the admissions process at a large, urban, academic US ED demonstrated a lengthy process, exceeding national benchmarks in both length of stay and boarding of admitted patients.We performed a pre-post study between July 2019 and July 2021 focused on the first step of the admission process at our institution, the time to bed request. All patients admitted to an internal medicine (IM) floor team from the ED were included in the study. The primary outcome was the time from decision to admit by the emergency medicine physician to placement of the bed request order by the IM physician. Quality improvement (QI) occurred in three phases: an initial preintervention process and electronic health record change to better capture admission times, a primary intervention focused on process change and provider education and a second intervention focused on improvements to provider communication.During the study period, 25 183 patients were admitted to IM floor teams and met inclusion criteria. Prior to the primary intervention, the mean time from ED decision to admit to IM placement of the bed request order was 75.1 min. Postintervention, the mean time decreased to 39.7 min, a statistically significant improvement of 35.4 min (p value <0.0001).This QI project demonstrates the ability of interventions to reduce the time to admission bed request order, a key step in the overall admission process and a contributor to boarding at our institution. In making process changes, the team also reduced provider handoffs and improved provider communication.


Subject(s)
Emergency Medicine , Quality Improvement , Crowding , Emergency Service, Hospital , Hospitalization , Humans
2.
Int J Qual Health Care ; 26(3): 271-7, 2014 Jun.
Article in English | MEDLINE | ID: mdl-24737834

ABSTRACT

OBJECTIVE: To create a simple readmission risk-prediction tool that can be generated easily at the bedside by physicians, nurses, care coordinators and discharge planners. DESIGN: Retrospective cohort study. SETTING: Tertiary academic medical center. PARTICIPANTS: Inpatients aged 18 and older on general internal medicine services. MEASURES: Predictor variables included age, prior hospitalization, high-risk diagnoses, high-risk medications, polypharmacy, depression, use of palliative care and a cumulative score summing these factors (readmission risk score-RRS). The main outcome measure was 30-day readmission. Predictive values were calculated. RESULTS: Readmission increased linearly from 4.9% of those whose RRS score was 0-37.5% of those with highest risk scores (P = 0.0002). We derived a simple formula for readmission risk as 8 and 4% more for each additional readmission risk factor. The positive predictive value for RRS >0 was low, while the negative predictive value for this cutoff was 95%. CONCLUSIONS: An easily calculated 7-point score can be used to estimate readmission risk. This tool may be particularly useful for identifying lower risk patients who may not require intensive intervention, thus aiding in appropriate targeting of resources.


Subject(s)
Hospitals/statistics & numerical data , Patient Readmission/statistics & numerical data , Risk Assessment/methods , Adult , Age Factors , Aged , Comorbidity , Depression/epidemiology , Female , Home Nursing , Humans , Internal Medicine , Male , Middle Aged , Palliative Care , Polypharmacy , Predictive Value of Tests , Retrospective Studies , Risk Factors , United States/epidemiology
4.
Hosp Pharm ; 48(5): 380-8, 2013 May.
Article in English | MEDLINE | ID: mdl-24421494

ABSTRACT

BACKGROUND: The prevalence and cost of hospital readmissions have gained attention. The ability to identify patients at high risk for hospital readmission has implications for quality and costs of care. Medication errors have been shown to increase the risk for readmission. OBJECTIVE: To study the impact of a pharmacist-based predischarge medication reconciliation and counseling program on 30-day readmission rates and determine whether polypharmacy and problem medications are important screening criteria. METHODS: A prospective, nonrandomized cohort study performed at a single medical-surgical unit with telemetry capability at a single academic medical center. The participants were 729 patients, aged 18 years and older, who were discharged between July 1 and October 29, 2010. The intervention was pharmacist medication reconciliation and counseling based on a screening tool. The primary outcome was 30-day readmission rate. Secondary outcomes were the presence of polypharmacy and problem medications and their relationship with observed 30-day readmission rate, including calculation of a problem med/polypharmacy score. RESULTS: The pharmacy review group (n = 537) had a lower 30-day readmission rate than the group receiving usual care (n = 192) (16.8% vs 26.0%; odds ratio [OR] 0.572; 95% CI, 0.387-0.852; P = .006). Polypharmacy, defined as either 5 or more or 10 or more scheduled medications, alone and in combination with at least one problem medication had higher 30-day readmission rates. A score of no factors present exhibited good negative predictive value. CONCLUSIONS: Medication reconciliation and counseling by a pharmacist reduced the 30-day readmission rate. Polypharmacy and problem medications appear to have value individually and together. A pharmacist, guided by a screening tool in predischarge medication reconciliation, is one option to effectively reduce 30-day readmissions.

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