OBJECTIVES: To understand how community pharmacists use electronic prescribing (e-prescribing) technology and to describe the workflow challenges pharmacy personnel encounter as a result of using e-prescribing technology. DESIGN: Cross-sectional qualitative study. SETTING: Seven community pharmacies in Wisconsin from December 2010 to March 2011. PARTICIPANTS: 16 pharmacists and 14 pharmacy technicians (in three chain and four independent pharmacies). INTERVENTIONS: Think-aloud protocols and pharmacy group interviews. MAIN OUTCOME MEASURES: Pharmacy staff descriptions of their use of e-prescribing technology and challenges encountered in their daily workflow related to this technology. RESULTS: Two contributing factors were perceived to influence e-prescribing workflow: issues stemming from prescribing or transmitting software and issues from within the pharmacy. Pharmacies experienced both delayed and inaccurate e-prescriptions from physician offices. An overwhelming number of e-prescriptions with inaccurate or unclear information resulted in serious time delays for patients as pharmacists contacted physicians to clarify wrong information. In addition, lack of formal training and the disconnect between pharmacy procedures for verifying prescription accuracy and presentation of e-prescription information on the computer screen influenced the speed of processing an e-prescription. CONCLUSION: E-prescriptions processing can hinder pharmacy workflow. As the number of e-prescriptions transmitted to pharmacies increases because of legislative mandates, it is essential that the technology supporting e-prescriptions (both on the prescriber and pharmacy operating systems) be redesigned to facilitate pharmacy workflow processes and to prevent unintended increase in medication errors, user frustration, and stress.
OBJECTIVES: To understand how community pharmacists use electronic prescribing (e-prescribing) technology and to describe the workflow challenges pharmacy personnel encounter as a result of using e-prescribing technology. DESIGN: Cross-sectional qualitative study. SETTING: Seven community pharmacies in Wisconsin from December 2010 to March 2011. PARTICIPANTS: 16 pharmacists and 14 pharmacy technicians (in three chain and four independent pharmacies). INTERVENTIONS: Think-aloud protocols and pharmacy group interviews. MAIN OUTCOME MEASURES: Pharmacy staff descriptions of their use of e-prescribing technology and challenges encountered in their daily workflow related to this technology. RESULTS: Two contributing factors were perceived to influence e-prescribing workflow: issues stemming from prescribing or transmitting software and issues from within the pharmacy. Pharmacies experienced both delayed and inaccurate e-prescriptions from physician offices. An overwhelming number of e-prescriptions with inaccurate or unclear information resulted in serious time delays for patients as pharmacists contacted physicians to clarify wrong information. In addition, lack of formal training and the disconnect between pharmacy procedures for verifying prescription accuracy and presentation of e-prescription information on the computer screen influenced the speed of processing an e-prescription. CONCLUSION: E-prescriptions processing can hinder pharmacy workflow. As the number of e-prescriptions transmitted to pharmacies increases because of legislative mandates, it is essential that the technology supporting e-prescriptions (both on the prescriber and pharmacy operating systems) be redesigned to facilitate pharmacy workflow processes and to prevent unintended increase in medication errors, user frustration, and stress.
Authors: Adrienne M Gilligan; Kimberly Miller; Adam Mohney; Courtney Montenegro; Jacob Schwarz; Terri L Warholak Journal: Res Social Adm Pharm Date: 2012-01-20
Authors: Emily M Campbell; Kenneth P Guappone; Dean F Sittig; Richard H Dykstra; Joan S Ash Journal: J Gen Intern Med Date: 2008-11-20 Impact factor: 5.128
Authors: Karen C Nanji; Jeffrey M Rothschild; Claudia Salzberg; Carol A Keohane; Katherine Zigmont; Jim Devita; Tejal K Gandhi; Anuj K Dalal; David W Bates; Eric G Poon Journal: J Am Med Inform Assoc Date: 2011-06-29 Impact factor: 4.497
Authors: Rollin J Fairbanks; Stanley H Caplan; Paul A Bishop; Aaron M Marks; Manish N Shah Journal: Ann Emerg Med Date: 2007-05-11 Impact factor: 5.721
Authors: Clare L Brown; Helen L Mulcaster; Katherine L Triffitt; Dean F Sittig; Joan S Ash; Katie Reygate; Andrew K Husband; David W Bates; Sarah P Slight Journal: J Am Med Inform Assoc Date: 2017-03-01 Impact factor: 4.497
Authors: Robert J Romanelli; Naomi R M Schwartz; William G Dixon; Carla Rodriguez-Watson; Brian C Sauer; Dawn Albright; Zachary A Marcum Journal: Pharmacoepidemiol Drug Saf Date: 2021-07-28 Impact factor: 2.732