Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals

Abstract Background Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of differe...

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Veröffentlicht in:Clinical infectious diseases 2022-09, Vol.75 (7), p.1187-1193
Hauptverfasser: Rock, Clare, Abosi, Oluchi, Bleasdale, Susan, Colligan, Erin, Diekema, Daniel J, Dullabh, Prashila, Gurses, Ayse P, Heaney-Huls, Krysta, Jacob, Jesse T, Kandiah, Sheetal, Lama, Sonam, Leekha, Surbhi, Mayer, Jeanmarie, Mena Lora, Alfredo J, Morgan, Daniel J, Osei, Patience, Pau, Sara, Salinas, Jorge L, Spivak, Emily, Wenzler, Eric, Cosgrove, Sara E
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container_end_page 1193
container_issue 7
container_start_page 1187
container_title Clinical infectious diseases
container_volume 75
creator Rock, Clare
Abosi, Oluchi
Bleasdale, Susan
Colligan, Erin
Diekema, Daniel J
Dullabh, Prashila
Gurses, Ayse P
Heaney-Huls, Krysta
Jacob, Jesse T
Kandiah, Sheetal
Lama, Sonam
Leekha, Surbhi
Mayer, Jeanmarie
Mena Lora, Alfredo J
Morgan, Daniel J
Osei, Patience
Pau, Sara
Salinas, Jorge L
Spivak, Emily
Wenzler, Eric
Cosgrove, Sara E
description Abstract Background Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers’ (HCP) workflow are not well understood. Methods Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre– and post–CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. Results In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%–36%) and 23% (95% CI: 21%–25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%–28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient’s most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. Conclusions CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making. This 15-hospital, 2-year cohort, mixed-methods study found reduced Clostridioides difficiletest incidence rates after computerized clinical decision support (CCDS) implementation. Healthcare providers’ perceptions were positive when CCDS was integrated into their workflow and provided relevant patient-specific information.
doi_str_mv 10.1093/cid/ciac074
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Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers’ (HCP) workflow are not well understood. Methods Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre– and post–CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. Results In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%–36%) and 23% (95% CI: 21%–25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%–28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient’s most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. Conclusions CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making. This 15-hospital, 2-year cohort, mixed-methods study found reduced Clostridioides difficiletest incidence rates after computerized clinical decision support (CCDS) implementation. Healthcare providers’ perceptions were positive when CCDS was integrated into their workflow and provided relevant patient-specific information.</description><identifier>ISSN: 1058-4838</identifier><identifier>EISSN: 1537-6591</identifier><identifier>DOI: 10.1093/cid/ciac074</identifier><identifier>PMID: 35100620</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Clostridioides ; Clostridioides difficile ; Clostridium Infections - diagnosis ; Clostridium Infections - epidemiology ; Cohort Studies ; Decision Support Systems, Clinical ; Hospitals ; Humans ; Laxatives</subject><ispartof>Clinical infectious diseases, 2022-09, Vol.75 (7), p.1187-1193</ispartof><rights>The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com. 2022</rights><rights>The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c320t-cec3f0e3d27f064175f0a515ec1469a95375d725aaa09b08c6fbcd9cd8a091ba3</citedby><cites>FETCH-LOGICAL-c320t-cec3f0e3d27f064175f0a515ec1469a95375d725aaa09b08c6fbcd9cd8a091ba3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,1578,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35100620$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rock, Clare</creatorcontrib><creatorcontrib>Abosi, Oluchi</creatorcontrib><creatorcontrib>Bleasdale, Susan</creatorcontrib><creatorcontrib>Colligan, Erin</creatorcontrib><creatorcontrib>Diekema, Daniel J</creatorcontrib><creatorcontrib>Dullabh, Prashila</creatorcontrib><creatorcontrib>Gurses, Ayse P</creatorcontrib><creatorcontrib>Heaney-Huls, Krysta</creatorcontrib><creatorcontrib>Jacob, Jesse T</creatorcontrib><creatorcontrib>Kandiah, Sheetal</creatorcontrib><creatorcontrib>Lama, Sonam</creatorcontrib><creatorcontrib>Leekha, Surbhi</creatorcontrib><creatorcontrib>Mayer, Jeanmarie</creatorcontrib><creatorcontrib>Mena Lora, Alfredo J</creatorcontrib><creatorcontrib>Morgan, Daniel J</creatorcontrib><creatorcontrib>Osei, Patience</creatorcontrib><creatorcontrib>Pau, Sara</creatorcontrib><creatorcontrib>Salinas, Jorge L</creatorcontrib><creatorcontrib>Spivak, Emily</creatorcontrib><creatorcontrib>Wenzler, Eric</creatorcontrib><creatorcontrib>Cosgrove, Sara E</creatorcontrib><title>Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals</title><title>Clinical infectious diseases</title><addtitle>Clin Infect Dis</addtitle><description>Abstract Background Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers’ (HCP) workflow are not well understood. Methods Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre– and post–CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. Results In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%–36%) and 23% (95% CI: 21%–25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%–28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient’s most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. Conclusions CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making. This 15-hospital, 2-year cohort, mixed-methods study found reduced Clostridioides difficiletest incidence rates after computerized clinical decision support (CCDS) implementation. Healthcare providers’ perceptions were positive when CCDS was integrated into their workflow and provided relevant patient-specific information.</description><subject>Clostridioides</subject><subject>Clostridioides difficile</subject><subject>Clostridium Infections - diagnosis</subject><subject>Clostridium Infections - epidemiology</subject><subject>Cohort Studies</subject><subject>Decision Support Systems, Clinical</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Laxatives</subject><issn>1058-4838</issn><issn>1537-6591</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kEtLxDAUhYMozji6ci9ZiSDVm7bpYznUJ4wIzsy6pMmNRDpNTdrF_HujM7p0cbkPPg7nHkLOGdwwKJNbaVQoISFPD8iU8SSPMl6ywzADL6K0SIoJOfH-A4CxAvgxmSScAWQxTImrWtMZKVp6h9J4Yzu6HPveuoEut37AjaeDpW-oRol03XUo0XvhtrRqrR-cUcYahZ4qo7WRpkW6Qj-Y7p3OpbPe05exHUwf7k_W92YQrT8lRzo0PNv3GVk_3K-qp2jx-vhczReRTGIYIoky0YCJinMNWcpyrkFwxlGyNCtFGf7kKo-5EALKBgqZ6UaqUqoi7KwRyYxc7XR7Zz_H4KreGC-xbUWHdvR1nMVplrE0TgN6vUN_PDvUde_MJrxZM6i_Q65DyPU-5EBf7IXHZoPqj_1NNQCXO8CO_b9KX0FPiCY</recordid><startdate>20220930</startdate><enddate>20220930</enddate><creator>Rock, Clare</creator><creator>Abosi, Oluchi</creator><creator>Bleasdale, Susan</creator><creator>Colligan, Erin</creator><creator>Diekema, Daniel J</creator><creator>Dullabh, Prashila</creator><creator>Gurses, Ayse P</creator><creator>Heaney-Huls, Krysta</creator><creator>Jacob, Jesse T</creator><creator>Kandiah, Sheetal</creator><creator>Lama, Sonam</creator><creator>Leekha, Surbhi</creator><creator>Mayer, Jeanmarie</creator><creator>Mena Lora, Alfredo J</creator><creator>Morgan, Daniel J</creator><creator>Osei, Patience</creator><creator>Pau, Sara</creator><creator>Salinas, Jorge L</creator><creator>Spivak, Emily</creator><creator>Wenzler, Eric</creator><creator>Cosgrove, Sara E</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20220930</creationdate><title>Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals</title><author>Rock, Clare ; 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Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers’ (HCP) workflow are not well understood. Methods Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre– and post–CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. Results In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%–36%) and 23% (95% CI: 21%–25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%–28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient’s most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. Conclusions CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making. This 15-hospital, 2-year cohort, mixed-methods study found reduced Clostridioides difficiletest incidence rates after computerized clinical decision support (CCDS) implementation. Healthcare providers’ perceptions were positive when CCDS was integrated into their workflow and provided relevant patient-specific information.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>35100620</pmid><doi>10.1093/cid/ciac074</doi><tpages>7</tpages></addata></record>
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source Oxford University Press Journals All Titles (1996-Current); MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection
subjects Clostridioides
Clostridioides difficile
Clostridium Infections - diagnosis
Clostridium Infections - epidemiology
Cohort Studies
Decision Support Systems, Clinical
Hospitals
Humans
Laxatives
title Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals
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