BACKGROUND: Virginia Mason Medical Center (Seattle) employed the Lean concept of Jidoka (automation with a human touch) to plan for and deploy bar code medication administration (BCMA) to hospitalized patients. METHODS: Integrating BCMA technology into the nursing work flow with minimal disruption was accomplished using three steps ofJidoka: (1) assigning work to humans and machines on the basis of their differing abilities, (2) adapting machines to the human work flow, and (3) monitoring the human-machine interaction. Effectiveness of BCMA to both reinforce safe administration practices and reduce medication errors was measured using the Collaborative Alliance for Nursing Outcomes (CALNOC) Medication Administration Accuracy Quality Study methodology. Trained nurses observed a total of 16,149 medication doses for 3,617 patients in a three-year period. RESULTS: Following BCMA implementation, the number of safe practice violations decreased from 54.8 violations/100 doses (January 2010-September 2011) to 29.0 violations/100 doses (October 2011-December 2012), resulting in an absolute risk reduction of 25.8 violations/100 doses (95% confidence interval [CI]: 23.7, 27.9, p < .001). The number of medication errors decreased from 5.9 errors/100 doses at baseline to 3.0 errors/100 doses after BCMA implementation (absolute risk reduction: 2.9 errors/100 doses [95% CI: 2.2, 3.6,p < .001]). The number of unsafe administration practices (estimate, -5.481; standard error 1.133; p < .001; 95% CI: -7.702, -3.260) also decreased. CONCLUSION: As more hospitals respond to health information technology meaningful use incentives, thoughtful, methodical, and well-managed approaches to technology deployment are crucial. This work illustrates how Jidoka offers opportunities for a smooth transition to new technology.
BACKGROUND: Virginia Mason Medical Center (Seattle) employed the Lean concept of Jidoka (automation with a human touch) to plan for and deploy bar code medication administration (BCMA) to hospitalized patients. METHODS: Integrating BCMA technology into the nursing work flow with minimal disruption was accomplished using three steps ofJidoka: (1) assigning work to humans and machines on the basis of their differing abilities, (2) adapting machines to the human work flow, and (3) monitoring the human-machine interaction. Effectiveness of BCMA to both reinforce safe administration practices and reduce medication errors was measured using the Collaborative Alliance for Nursing Outcomes (CALNOC) Medication Administration Accuracy Quality Study methodology. Trained nurses observed a total of 16,149 medication doses for 3,617 patients in a three-year period. RESULTS: Following BCMA implementation, the number of safe practice violations decreased from 54.8 violations/100 doses (January 2010-September 2011) to 29.0 violations/100 doses (October 2011-December 2012), resulting in an absolute risk reduction of 25.8 violations/100 doses (95% confidence interval [CI]: 23.7, 27.9, p < .001). The number of medication errors decreased from 5.9 errors/100 doses at baseline to 3.0 errors/100 doses after BCMA implementation (absolute risk reduction: 2.9 errors/100 doses [95% CI: 2.2, 3.6,p < .001]). The number of unsafe administration practices (estimate, -5.481; standard error 1.133; p < .001; 95% CI: -7.702, -3.260) also decreased. CONCLUSION: As more hospitals respond to health information technology meaningful use incentives, thoughtful, methodical, and well-managed approaches to technology deployment are crucial. This work illustrates how Jidoka offers opportunities for a smooth transition to new technology.
Authors: Noa Segall; Alberto S Bonifacio; Atilio Barbeito; Rebecca A Schroeder; Sharon R Perfect; Melanie C Wright; James D Emery; B Zane Atkins; Jeffrey M Taekman; Jonathan B Mark Journal: Jt Comm J Qual Patient Saf Date: 2016-09