The impact of a computerised decision support system on antibiotic usage in an English hospital
Background Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics. Objective This study aimed to evaluate the impact of computerized decision support...
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| Veröffentlicht in: | International journal of clinical pharmacy 2020-04, Vol.42 (2), p.765-771 |
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| creator | Al Bahar, F. Curtis, C. E. Alhamad, H. Marriott, J. F. |
| description | Background
Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics.
Objective
This study aimed to evaluate the impact of computerized decision support systems on the volume of antibiotics used.
Setting
A very large 1200-bed teaching hospital in Birmingham, England.
Main outcome measure
The primary outcome measure was the defined daily doses/1000 occupied bed-days.
Method
A retrospective longitudinal study was conducted to examine the impact of computerised decision support systems on the volume of antibiotic use. The study compared two periods: one with computerised decision support systems, which lasted for 2 years versus one without which lasted for 2 years after the withdrawal of computerised decision support systems. Antibiotic use data from June 2012 to June 2016 were analysed (comprising 2 years with computerised decision support systems immediately followed by 2 years where computerised decision support systems had been withdrawn). Regression analysis was applied to assess the change in antibiotic consumption through the period of the study.
Result
From June 2012 to June 2016, total antibiotic usage increased by 13.1% from 1436 to 1625 defined daily doses/1000 bed-days: this trend of increased antibiotic prescribing was more pronounced following the withdrawal of structured prescribing (computerised decision support systems). There was a difference of means of − 110.14 defined daily doses/1000 bed days of the total usage of antibiotics in the period with and without structured prescribing, and this was statistically significant (
p
= 0.026). From June 2012 to June 2016, the dominant antibiotic class used was penicillins. The trends for the total consumption of all antibiotics demonstrated an increase of use for all antibiotic classes except for tetracyclines, quinolones, and anti-mycobacterial drugs, whereas aminoglycoside usage remained stable.
Conclusion
The implementation of computerised decision support systems appears to influence the use of antibiotics by reducing their consumption. Further research is required to determine the specific features of computerised decision support systems, which influence increased higher adoption and uptake of this technology. |
| doi_str_mv | 10.1007/s11096-020-01022-3 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2389210405</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2396571370</sourcerecordid><originalsourceid>FETCH-LOGICAL-c375t-4cfb97bf782bf2d42c41d568c017a9e2d0d397aa9d61b5827ac60b2402dc13303</originalsourceid><addsrcrecordid>eNp9kcFu3CAQhlHVqonSvEAPFVIuvTgZBtusj1WUtJEi5ZKeEQa8S2Qbl8GHvH3Y7jaVcggX0PDNB5qfsa8CLgWAuiIhoGsrQKhAAGIlP7BTRAGVUkJ8fD2DPGHnRE9QVt2iaOrP7EQiqg5lc8r0487zMC3GZh4HbriN07JmnwJ5x523gUKcOa3LElPm9EzZT7xUzJxDH2IOlq9ktkWyr_GbeTsG2vFdpCVkM35hnwYzkj8_7mfs9-3N4_Wv6v7h5931j_vKStXkqrZD36l-UBvsB3Q12lq4pt1YEMp0Hh042SljOteKvtmgMraFHmtAZ4WUIM_Y94N3SfHP6inrKZD142hmH1fSKDddGUgNTUEv3qBPcU1z-V2hurZRQqq9EA-UTZEo-UEvKUwmPWsBep-APiSgSwL6bwJalqZvR_XaT969tvybdwHkAaByNW99-v_2O9oX14SQFg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2396571370</pqid></control><display><type>article</type><title>The impact of a computerised decision support system on antibiotic usage in an English hospital</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Al Bahar, F. ; Curtis, C. E. ; Alhamad, H. ; Marriott, J. F.</creator><creatorcontrib>Al Bahar, F. ; Curtis, C. E. ; Alhamad, H. ; Marriott, J. F.</creatorcontrib><description>Background
Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics.
Objective
This study aimed to evaluate the impact of computerized decision support systems on the volume of antibiotics used.
Setting
A very large 1200-bed teaching hospital in Birmingham, England.
Main outcome measure
The primary outcome measure was the defined daily doses/1000 occupied bed-days.
Method
A retrospective longitudinal study was conducted to examine the impact of computerised decision support systems on the volume of antibiotic use. The study compared two periods: one with computerised decision support systems, which lasted for 2 years versus one without which lasted for 2 years after the withdrawal of computerised decision support systems. Antibiotic use data from June 2012 to June 2016 were analysed (comprising 2 years with computerised decision support systems immediately followed by 2 years where computerised decision support systems had been withdrawn). Regression analysis was applied to assess the change in antibiotic consumption through the period of the study.
Result
From June 2012 to June 2016, total antibiotic usage increased by 13.1% from 1436 to 1625 defined daily doses/1000 bed-days: this trend of increased antibiotic prescribing was more pronounced following the withdrawal of structured prescribing (computerised decision support systems). There was a difference of means of − 110.14 defined daily doses/1000 bed days of the total usage of antibiotics in the period with and without structured prescribing, and this was statistically significant (
p
= 0.026). From June 2012 to June 2016, the dominant antibiotic class used was penicillins. The trends for the total consumption of all antibiotics demonstrated an increase of use for all antibiotic classes except for tetracyclines, quinolones, and anti-mycobacterial drugs, whereas aminoglycoside usage remained stable.
Conclusion
The implementation of computerised decision support systems appears to influence the use of antibiotics by reducing their consumption. Further research is required to determine the specific features of computerised decision support systems, which influence increased higher adoption and uptake of this technology.</description><identifier>ISSN: 2210-7703</identifier><identifier>EISSN: 2210-7711</identifier><identifier>DOI: 10.1007/s11096-020-01022-3</identifier><identifier>PMID: 32279235</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Aminoglycoside antibiotics ; Anti-Bacterial Agents - administration & dosage ; Antibiotics ; Antimicrobial agents ; Antimicrobial resistance ; Decision support systems ; Decision Support Systems, Clinical - standards ; Decision Support Systems, Clinical - trends ; Drug Resistance, Multiple, Bacterial - drug effects ; Drug Resistance, Multiple, Bacterial - physiology ; Electronic Prescribing - standards ; England - epidemiology ; Hospitals, Teaching - standards ; Hospitals, Teaching - trends ; Humans ; Internal Medicine ; Longitudinal Studies ; Medicine ; Medicine & Public Health ; Pharmacy ; Quinolones ; Research Article ; Retrospective Studies ; Statistical analysis ; Tetracyclines</subject><ispartof>International journal of clinical pharmacy, 2020-04, Vol.42 (2), p.765-771</ispartof><rights>Springer Nature Switzerland AG 2020</rights><rights>Springer Nature Switzerland AG 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-4cfb97bf782bf2d42c41d568c017a9e2d0d397aa9d61b5827ac60b2402dc13303</citedby><cites>FETCH-LOGICAL-c375t-4cfb97bf782bf2d42c41d568c017a9e2d0d397aa9d61b5827ac60b2402dc13303</cites><orcidid>0000-0002-4302-6636</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11096-020-01022-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11096-020-01022-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32279235$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Al Bahar, F.</creatorcontrib><creatorcontrib>Curtis, C. E.</creatorcontrib><creatorcontrib>Alhamad, H.</creatorcontrib><creatorcontrib>Marriott, J. F.</creatorcontrib><title>The impact of a computerised decision support system on antibiotic usage in an English hospital</title><title>International journal of clinical pharmacy</title><addtitle>Int J Clin Pharm</addtitle><addtitle>Int J Clin Pharm</addtitle><description>Background
Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics.
Objective
This study aimed to evaluate the impact of computerized decision support systems on the volume of antibiotics used.
Setting
A very large 1200-bed teaching hospital in Birmingham, England.
Main outcome measure
The primary outcome measure was the defined daily doses/1000 occupied bed-days.
Method
A retrospective longitudinal study was conducted to examine the impact of computerised decision support systems on the volume of antibiotic use. The study compared two periods: one with computerised decision support systems, which lasted for 2 years versus one without which lasted for 2 years after the withdrawal of computerised decision support systems. Antibiotic use data from June 2012 to June 2016 were analysed (comprising 2 years with computerised decision support systems immediately followed by 2 years where computerised decision support systems had been withdrawn). Regression analysis was applied to assess the change in antibiotic consumption through the period of the study.
Result
From June 2012 to June 2016, total antibiotic usage increased by 13.1% from 1436 to 1625 defined daily doses/1000 bed-days: this trend of increased antibiotic prescribing was more pronounced following the withdrawal of structured prescribing (computerised decision support systems). There was a difference of means of − 110.14 defined daily doses/1000 bed days of the total usage of antibiotics in the period with and without structured prescribing, and this was statistically significant (
p
= 0.026). From June 2012 to June 2016, the dominant antibiotic class used was penicillins. The trends for the total consumption of all antibiotics demonstrated an increase of use for all antibiotic classes except for tetracyclines, quinolones, and anti-mycobacterial drugs, whereas aminoglycoside usage remained stable.
Conclusion
The implementation of computerised decision support systems appears to influence the use of antibiotics by reducing their consumption. Further research is required to determine the specific features of computerised decision support systems, which influence increased higher adoption and uptake of this technology.</description><subject>Aminoglycoside antibiotics</subject><subject>Anti-Bacterial Agents - administration & dosage</subject><subject>Antibiotics</subject><subject>Antimicrobial agents</subject><subject>Antimicrobial resistance</subject><subject>Decision support systems</subject><subject>Decision Support Systems, Clinical - standards</subject><subject>Decision Support Systems, Clinical - trends</subject><subject>Drug Resistance, Multiple, Bacterial - drug effects</subject><subject>Drug Resistance, Multiple, Bacterial - physiology</subject><subject>Electronic Prescribing - standards</subject><subject>England - epidemiology</subject><subject>Hospitals, Teaching - standards</subject><subject>Hospitals, Teaching - trends</subject><subject>Humans</subject><subject>Internal Medicine</subject><subject>Longitudinal Studies</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Pharmacy</subject><subject>Quinolones</subject><subject>Research Article</subject><subject>Retrospective Studies</subject><subject>Statistical analysis</subject><subject>Tetracyclines</subject><issn>2210-7703</issn><issn>2210-7711</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><recordid>eNp9kcFu3CAQhlHVqonSvEAPFVIuvTgZBtusj1WUtJEi5ZKeEQa8S2Qbl8GHvH3Y7jaVcggX0PDNB5qfsa8CLgWAuiIhoGsrQKhAAGIlP7BTRAGVUkJ8fD2DPGHnRE9QVt2iaOrP7EQiqg5lc8r0487zMC3GZh4HbriN07JmnwJ5x523gUKcOa3LElPm9EzZT7xUzJxDH2IOlq9ktkWyr_GbeTsG2vFdpCVkM35hnwYzkj8_7mfs9-3N4_Wv6v7h5931j_vKStXkqrZD36l-UBvsB3Q12lq4pt1YEMp0Hh042SljOteKvtmgMraFHmtAZ4WUIM_Y94N3SfHP6inrKZD142hmH1fSKDddGUgNTUEv3qBPcU1z-V2hurZRQqq9EA-UTZEo-UEvKUwmPWsBep-APiSgSwL6bwJalqZvR_XaT969tvybdwHkAaByNW99-v_2O9oX14SQFg</recordid><startdate>20200401</startdate><enddate>20200401</enddate><creator>Al Bahar, F.</creator><creator>Curtis, C. E.</creator><creator>Alhamad, H.</creator><creator>Marriott, J. F.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</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>3V.</scope><scope>7RV</scope><scope>7T5</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-4302-6636</orcidid></search><sort><creationdate>20200401</creationdate><title>The impact of a computerised decision support system on antibiotic usage in an English hospital</title><author>Al Bahar, F. ; Curtis, C. E. ; Alhamad, H. ; Marriott, J. F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-4cfb97bf782bf2d42c41d568c017a9e2d0d397aa9d61b5827ac60b2402dc13303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aminoglycoside antibiotics</topic><topic>Anti-Bacterial Agents - administration & dosage</topic><topic>Antibiotics</topic><topic>Antimicrobial agents</topic><topic>Antimicrobial resistance</topic><topic>Decision support systems</topic><topic>Decision Support Systems, Clinical - standards</topic><topic>Decision Support Systems, Clinical - trends</topic><topic>Drug Resistance, Multiple, Bacterial - drug effects</topic><topic>Drug Resistance, Multiple, Bacterial - physiology</topic><topic>Electronic Prescribing - standards</topic><topic>England - epidemiology</topic><topic>Hospitals, Teaching - standards</topic><topic>Hospitals, Teaching - trends</topic><topic>Humans</topic><topic>Internal Medicine</topic><topic>Longitudinal Studies</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Pharmacy</topic><topic>Quinolones</topic><topic>Research Article</topic><topic>Retrospective Studies</topic><topic>Statistical analysis</topic><topic>Tetracyclines</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Al Bahar, F.</creatorcontrib><creatorcontrib>Curtis, C. E.</creatorcontrib><creatorcontrib>Alhamad, H.</creatorcontrib><creatorcontrib>Marriott, J. F.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Immunology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>International journal of clinical pharmacy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Al Bahar, F.</au><au>Curtis, C. E.</au><au>Alhamad, H.</au><au>Marriott, J. F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of a computerised decision support system on antibiotic usage in an English hospital</atitle><jtitle>International journal of clinical pharmacy</jtitle><stitle>Int J Clin Pharm</stitle><addtitle>Int J Clin Pharm</addtitle><date>2020-04-01</date><risdate>2020</risdate><volume>42</volume><issue>2</issue><spage>765</spage><epage>771</epage><pages>765-771</pages><issn>2210-7703</issn><eissn>2210-7711</eissn><abstract>Background
Antimicrobial resistance is correlated with the inappropriate use of antibiotics. Computerised decision support systems may help practitioners to make evidence-based decisions when prescribing antibiotics.
Objective
This study aimed to evaluate the impact of computerized decision support systems on the volume of antibiotics used.
Setting
A very large 1200-bed teaching hospital in Birmingham, England.
Main outcome measure
The primary outcome measure was the defined daily doses/1000 occupied bed-days.
Method
A retrospective longitudinal study was conducted to examine the impact of computerised decision support systems on the volume of antibiotic use. The study compared two periods: one with computerised decision support systems, which lasted for 2 years versus one without which lasted for 2 years after the withdrawal of computerised decision support systems. Antibiotic use data from June 2012 to June 2016 were analysed (comprising 2 years with computerised decision support systems immediately followed by 2 years where computerised decision support systems had been withdrawn). Regression analysis was applied to assess the change in antibiotic consumption through the period of the study.
Result
From June 2012 to June 2016, total antibiotic usage increased by 13.1% from 1436 to 1625 defined daily doses/1000 bed-days: this trend of increased antibiotic prescribing was more pronounced following the withdrawal of structured prescribing (computerised decision support systems). There was a difference of means of − 110.14 defined daily doses/1000 bed days of the total usage of antibiotics in the period with and without structured prescribing, and this was statistically significant (
p
= 0.026). From June 2012 to June 2016, the dominant antibiotic class used was penicillins. The trends for the total consumption of all antibiotics demonstrated an increase of use for all antibiotic classes except for tetracyclines, quinolones, and anti-mycobacterial drugs, whereas aminoglycoside usage remained stable.
Conclusion
The implementation of computerised decision support systems appears to influence the use of antibiotics by reducing their consumption. Further research is required to determine the specific features of computerised decision support systems, which influence increased higher adoption and uptake of this technology.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>32279235</pmid><doi>10.1007/s11096-020-01022-3</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-4302-6636</orcidid></addata></record> |
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| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Aminoglycoside antibiotics Anti-Bacterial Agents - administration & dosage Antibiotics Antimicrobial agents Antimicrobial resistance Decision support systems Decision Support Systems, Clinical - standards Decision Support Systems, Clinical - trends Drug Resistance, Multiple, Bacterial - drug effects Drug Resistance, Multiple, Bacterial - physiology Electronic Prescribing - standards England - epidemiology Hospitals, Teaching - standards Hospitals, Teaching - trends Humans Internal Medicine Longitudinal Studies Medicine Medicine & Public Health Pharmacy Quinolones Research Article Retrospective Studies Statistical analysis Tetracyclines |
| title | The impact of a computerised decision support system on antibiotic usage in an English hospital |
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