Carrie Freed, Cynthia King, Brandon Soltesz, M David Gothard, Bushra Altabbaa, Aleksandra Majstorovic
{"title":"药剂师专业知识对大型学术医疗系统综合电子咨询项目接受率的影响。","authors":"Carrie Freed, Cynthia King, Brandon Soltesz, M David Gothard, Bushra Altabbaa, Aleksandra Majstorovic","doi":"10.24926/iip.v15i3.6278","DOIUrl":null,"url":null,"abstract":"<p><p><i>Background:</i> Although electronic consults (e-consults) are utilized in healthcare systems by medical professionals, use of e-consults by pharmacy remains novel outside of niche disease states. Additional research is required to fill literature gaps to assist in optimizing the pharmacist's role in e-consult programs. <i>Objective:</i> This study aimed to assess the impact of pharmacist expertise on e-consult outcomes. <i>Methods:</i> This study was a retrospective review of all pharmacy e-consults completed by pharmacists at a large academic health system between March 1st, 2020, and August 31st, 2022. This was deemed quality improvement and did not require Institutional Review Board approval. E-consults were identified using a report. Key data collection points included e-consult disease state, ordering provider, pharmacists' specialty, and recommendation result. The primary outcome was the difference in acceptance rates of expert versus non-expert pharmacist recommendations. Secondary outcomes included the overall implementation rate, implementation rate over time, acceptance rate between provider types, time to implementation, and pharmacist response time. Acceptance rates were compared between expert/non-expert dichotomy via Pearson chi-square test. <i>Results:</i> A total of 375 e-consults met inclusion criteria and spanned 19 unique disease states. The three most common included diabetes mellitus (27.0%), pain management (13.1%), and mental health (11.0%). Nearly 60% of e-consults were in a disease with an expert. The provider acceptance rate was higher when e-consults were completed by an expert versus non-expert (62.6% versus 39.6% respectively, p = 0.002). The overall implementation rate was 51.8%. Physicians (MD/DOs) accepted the pharmacist's recommendations 55.6% of the time, advanced practice registered nurses (APRNs) 64.7%, physician assistants (PAs) 100.0%, and other professionals 25.0% (p = 0.033). Mean time to recommendation implementation was 16.5 days (SD = 29.4 days). Mean time to pharmacist response was 1.1 days (SD = 1.4 days). <i>Conclusions:</i> Comprehensive e-consult programs are more successful when integrating expert pharmacists.</p>","PeriodicalId":501014,"journal":{"name":"Innovations in pharmacy","volume":"15 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11524217/pdf/","citationCount":"0","resultStr":"{\"title\":\"Impact of Pharmacist Expertise on Acceptance Rates in a Comprehensive E-Consult Program within a Large Academic Health System.\",\"authors\":\"Carrie Freed, Cynthia King, Brandon Soltesz, M David Gothard, Bushra Altabbaa, Aleksandra Majstorovic\",\"doi\":\"10.24926/iip.v15i3.6278\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>Background:</i> Although electronic consults (e-consults) are utilized in healthcare systems by medical professionals, use of e-consults by pharmacy remains novel outside of niche disease states. Additional research is required to fill literature gaps to assist in optimizing the pharmacist's role in e-consult programs. <i>Objective:</i> This study aimed to assess the impact of pharmacist expertise on e-consult outcomes. <i>Methods:</i> This study was a retrospective review of all pharmacy e-consults completed by pharmacists at a large academic health system between March 1st, 2020, and August 31st, 2022. This was deemed quality improvement and did not require Institutional Review Board approval. E-consults were identified using a report. Key data collection points included e-consult disease state, ordering provider, pharmacists' specialty, and recommendation result. The primary outcome was the difference in acceptance rates of expert versus non-expert pharmacist recommendations. Secondary outcomes included the overall implementation rate, implementation rate over time, acceptance rate between provider types, time to implementation, and pharmacist response time. Acceptance rates were compared between expert/non-expert dichotomy via Pearson chi-square test. <i>Results:</i> A total of 375 e-consults met inclusion criteria and spanned 19 unique disease states. The three most common included diabetes mellitus (27.0%), pain management (13.1%), and mental health (11.0%). Nearly 60% of e-consults were in a disease with an expert. The provider acceptance rate was higher when e-consults were completed by an expert versus non-expert (62.6% versus 39.6% respectively, p = 0.002). The overall implementation rate was 51.8%. Physicians (MD/DOs) accepted the pharmacist's recommendations 55.6% of the time, advanced practice registered nurses (APRNs) 64.7%, physician assistants (PAs) 100.0%, and other professionals 25.0% (p = 0.033). Mean time to recommendation implementation was 16.5 days (SD = 29.4 days). Mean time to pharmacist response was 1.1 days (SD = 1.4 days). <i>Conclusions:</i> Comprehensive e-consult programs are more successful when integrating expert pharmacists.</p>\",\"PeriodicalId\":501014,\"journal\":{\"name\":\"Innovations in pharmacy\",\"volume\":\"15 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11524217/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Innovations in pharmacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24926/iip.v15i3.6278\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innovations in pharmacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24926/iip.v15i3.6278","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
Impact of Pharmacist Expertise on Acceptance Rates in a Comprehensive E-Consult Program within a Large Academic Health System.
Background: Although electronic consults (e-consults) are utilized in healthcare systems by medical professionals, use of e-consults by pharmacy remains novel outside of niche disease states. Additional research is required to fill literature gaps to assist in optimizing the pharmacist's role in e-consult programs. Objective: This study aimed to assess the impact of pharmacist expertise on e-consult outcomes. Methods: This study was a retrospective review of all pharmacy e-consults completed by pharmacists at a large academic health system between March 1st, 2020, and August 31st, 2022. This was deemed quality improvement and did not require Institutional Review Board approval. E-consults were identified using a report. Key data collection points included e-consult disease state, ordering provider, pharmacists' specialty, and recommendation result. The primary outcome was the difference in acceptance rates of expert versus non-expert pharmacist recommendations. Secondary outcomes included the overall implementation rate, implementation rate over time, acceptance rate between provider types, time to implementation, and pharmacist response time. Acceptance rates were compared between expert/non-expert dichotomy via Pearson chi-square test. Results: A total of 375 e-consults met inclusion criteria and spanned 19 unique disease states. The three most common included diabetes mellitus (27.0%), pain management (13.1%), and mental health (11.0%). Nearly 60% of e-consults were in a disease with an expert. The provider acceptance rate was higher when e-consults were completed by an expert versus non-expert (62.6% versus 39.6% respectively, p = 0.002). The overall implementation rate was 51.8%. Physicians (MD/DOs) accepted the pharmacist's recommendations 55.6% of the time, advanced practice registered nurses (APRNs) 64.7%, physician assistants (PAs) 100.0%, and other professionals 25.0% (p = 0.033). Mean time to recommendation implementation was 16.5 days (SD = 29.4 days). Mean time to pharmacist response was 1.1 days (SD = 1.4 days). Conclusions: Comprehensive e-consult programs are more successful when integrating expert pharmacists.