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Am J Health Syst Pharm ; 76(13): 964-969, 2019 Jun 18.
Article in English | MEDLINE | ID: mdl-31361882

ABSTRACT

PURPOSE: To evaluate the benefits of technology-assisted workflow (TAWF) compared to manual workflow (non-TAWF) on i.v. room efficiency, costs, and safety at community hospitals with less than 200 beds. METHODS: Four hospitals in the United States (2 with and 2 without TAWF) were evaluated, and characteristics of medication errors and frequency of each error type were measured across the institutions. The average turnaround time per workflow step and cost to prepare each compounded sterile product (CSP) were also calculated. The results were evaluated using descriptive and inferential statistics. RESULTS: The TAWF hospital sites detected errors at a significantly higher rate (3.78%) compared to the non-TAWF hospital sites (0.13%) (p < 0.05). The top error-reporting category for the TAWF sites was incorrect medication (71.66%), whereas the top error-reporting category for the non-TAWF sites could not be determined because of the small number of errors detected. Use of TAWF may be associated with a decrease in turnaround time and a decrease in overall cost to prepare a CSP. CONCLUSION: Significantly more errors were detected in small community hospitals that use TAWF in the i.v. room compared to those not using it. There were differences in error types observed between technology and nontechnology groups. The use of TAWF was associated with faster preparation times and lower costs of preparation per CSP.


Subject(s)
Efficiency, Organizational , Hospitals, Community/organization & administration , Pharmacy Service, Hospital/organization & administration , Technology Assessment, Biomedical , Workflow , Hospitals, Community/economics , Hospitals, Community/statistics & numerical data , Humans , Infusions, Intravenous/economics , Medication Errors/prevention & control , Medication Errors/statistics & numerical data , Patient Safety , Pharmacy Service, Hospital/economics , Pharmacy Service, Hospital/statistics & numerical data , Time Factors , United States
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