OBJECTIVE: Electronic prescribing (e-prescribing) may substantially improve health care quality and efficiency, but the available systems are complex and their heterogeneity makes comparing and evaluating them a challenge. The authors aimed to develop a conceptual framework for anticipating the effects of alternative designs for outpatient e-prescribing systems. DESIGN: Based on a literature review and on telephone interviews with e-prescribing vendors, the authors identified distinct e-prescribing functional capabilities and developed a conceptual framework for evaluating e-prescribing systems' potential effects based on their capabilities. Analyses of two commercial e-prescribing systems are presented as examples of applying the conceptual framework. MEASUREMENTS: Major e-prescribing functional capabilities identified and the availability of evidence to support their specific effects. RESULTS: The proposed framework for evaluating e-prescribing systems is organized using a process model of medication management. Fourteen e-prescribing functional capabilities are identified within the model. Evidence is identified to support eight specific effects for six of the functional capabilities. The evidence also shows that a functional capability with generally positive effects can be implemented in a way that creates unintended hazards. Applying the framework involves identifying an e-prescribing system's functional capabilities within the process model and then assessing the effects that could be expected from each capability in the proposed clinical environment. CONCLUSION: The proposed conceptual framework supports the integration of available evidence in considering the full range of effects from e-prescribing design alternatives. More research is needed into the effects of specific e-prescribing functional alternatives. Until more is known, e-prescribing initiatives should include provisions to monitor for unintended hazards.
OBJECTIVE: Electronic prescribing (e-prescribing) may substantially improve health care quality and efficiency, but the available systems are complex and their heterogeneity makes comparing and evaluating them a challenge. The authors aimed to develop a conceptual framework for anticipating the effects of alternative designs for outpatient e-prescribing systems. DESIGN: Based on a literature review and on telephone interviews with e-prescribing vendors, the authors identified distinct e-prescribing functional capabilities and developed a conceptual framework for evaluating e-prescribing systems' potential effects based on their capabilities. Analyses of two commercial e-prescribing systems are presented as examples of applying the conceptual framework. MEASUREMENTS: Major e-prescribing functional capabilities identified and the availability of evidence to support their specific effects. RESULTS: The proposed framework for evaluating e-prescribing systems is organized using a process model of medication management. Fourteen e-prescribing functional capabilities are identified within the model. Evidence is identified to support eight specific effects for six of the functional capabilities. The evidence also shows that a functional capability with generally positive effects can be implemented in a way that creates unintended hazards. Applying the framework involves identifying an e-prescribing system's functional capabilities within the process model and then assessing the effects that could be expected from each capability in the proposed clinical environment. CONCLUSION: The proposed conceptual framework supports the integration of available evidence in considering the full range of effects from e-prescribing design alternatives. More research is needed into the effects of specific e-prescribing functional alternatives. Until more is known, e-prescribing initiatives should include provisions to monitor for unintended hazards.
Authors: D W Bates; D J Cullen; N Laird; L A Petersen; S D Small; D Servi; G Laffel; B J Sweitzer; B F Shea; R Hallisey Journal: JAMA Date: 1995-07-05 Impact factor: 56.272
Authors: L L Leape; D W Bates; D J Cullen; J Cooper; H J Demonaco; T Gallivan; R Hallisey; J Ives; N Laird; G Laffel Journal: JAMA Date: 1995-07-05 Impact factor: 56.272
Authors: Jonathan M Teich; Jerome A Osheroff; Eric A Pifer; Dean F Sittig; Robert A Jenders Journal: J Am Med Inform Assoc Date: 2005-03-31 Impact factor: 4.497
Authors: Robyn Tamblyn; Allen Huang; Laurel Taylor; Yuko Kawasumi; Gillian Bartlett; Roland Grad; André Jacques; Martin Dawes; Michal Abrahamowicz; Robert Perreault; Nancy Winslade; Lise Poissant; Alain Pinsonneault Journal: J Am Med Inform Assoc Date: 2008-04-24 Impact factor: 4.497