Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study
Background: The refeeding syndrome (RFS) is an oftentimes-unrecognized complication of reintroducing nutrition in malnourished patients that can lead to fatal cardiovascular failure. We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: W...
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| Veröffentlicht in: | Nutrients 2023-08, Vol.15 (17), p.3712 |
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| creator | Heuft, Lara Voigt, Jenny Selig, Lars Schmidt, Maria Eckelt, Felix Steinbach, Daniel Federbusch, Martin Stumvoll, Michael Schlögl, Haiko Isermann, Berend Kaiser, Thorsten |
| description | Background: The refeeding syndrome (RFS) is an oftentimes-unrecognized complication of reintroducing nutrition in malnourished patients that can lead to fatal cardiovascular failure. We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: We developed an algorithm from current diagnostic criteria for RFS detection, tested the algorithm on a retrospective dataset and combined the final algorithm with therapy and referral recommendations in a knowledge-based CDSS. The CDSS integration into clinical practice was prospectively investigated for six months. Results: The utilization of the RFS-CDSS lead to RFS diagnosis in 13 out of 21 detected cases (62%). It improved patient-related care and documentation, e.g., RFS-specific coding (E87.7), increased from once coded in 30 month in the retrospective cohort to four times in six months in the prospective cohort and doubled the rate of nutrition referrals in true positive patients (retrospective referrals in true positive patients 33% vs. prospective referrals in true positive patients 71%). Conclusion: CDSS-facilitated RFS diagnosis is possible and improves RFS recognition. This effect and its impact on patient-related outcomes needs to be further investigated in a large randomized-controlled trial. |
| doi_str_mv | 10.3390/nu15173712 |
| format | Article |
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We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: We developed an algorithm from current diagnostic criteria for RFS detection, tested the algorithm on a retrospective dataset and combined the final algorithm with therapy and referral recommendations in a knowledge-based CDSS. The CDSS integration into clinical practice was prospectively investigated for six months. Results: The utilization of the RFS-CDSS lead to RFS diagnosis in 13 out of 21 detected cases (62%). It improved patient-related care and documentation, e.g., RFS-specific coding (E87.7), increased from once coded in 30 month in the retrospective cohort to four times in six months in the prospective cohort and doubled the rate of nutrition referrals in true positive patients (retrospective referrals in true positive patients 33% vs. prospective referrals in true positive patients 71%). Conclusion: CDSS-facilitated RFS diagnosis is possible and improves RFS recognition. This effect and its impact on patient-related outcomes needs to be further investigated in a large randomized-controlled trial.</description><identifier>ISSN: 2072-6643</identifier><identifier>EISSN: 2072-6643</identifier><identifier>DOI: 10.3390/nu15173712</identifier><identifier>PMID: 37686744</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Algorithms ; Analgesics ; Clinical decision making ; Datasets ; Decision support systems ; Electrolytes ; Electronic health records ; Feasibility studies ; Gastrointestinal surgery ; Information systems ; Laboratories ; Malnutrition ; Medical referrals ; Metabolism ; Nutrition ; Nutritionists ; Parenteral nutrition ; Patients ; Potassium ; Renal replacement therapy</subject><ispartof>Nutrients, 2023-08, Vol.15 (17), p.3712</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c382t-55b44743b10d60fb87e60c3a6b245957631ca9892e2da3f107fdf3cbbae7db883</cites><orcidid>0000-0002-9470-1910 ; 0000-0003-0714-6160 ; 0000-0003-2364-598X ; 0000-0002-9479-3659 ; 0000-0003-0523-3113 ; 0000-0002-1126-5763</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490138/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490138/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids></links><search><creatorcontrib>Heuft, Lara</creatorcontrib><creatorcontrib>Voigt, Jenny</creatorcontrib><creatorcontrib>Selig, Lars</creatorcontrib><creatorcontrib>Schmidt, Maria</creatorcontrib><creatorcontrib>Eckelt, Felix</creatorcontrib><creatorcontrib>Steinbach, Daniel</creatorcontrib><creatorcontrib>Federbusch, Martin</creatorcontrib><creatorcontrib>Stumvoll, Michael</creatorcontrib><creatorcontrib>Schlögl, Haiko</creatorcontrib><creatorcontrib>Isermann, Berend</creatorcontrib><creatorcontrib>Kaiser, Thorsten</creatorcontrib><title>Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study</title><title>Nutrients</title><description>Background: The refeeding syndrome (RFS) is an oftentimes-unrecognized complication of reintroducing nutrition in malnourished patients that can lead to fatal cardiovascular failure. We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: We developed an algorithm from current diagnostic criteria for RFS detection, tested the algorithm on a retrospective dataset and combined the final algorithm with therapy and referral recommendations in a knowledge-based CDSS. The CDSS integration into clinical practice was prospectively investigated for six months. Results: The utilization of the RFS-CDSS lead to RFS diagnosis in 13 out of 21 detected cases (62%). It improved patient-related care and documentation, e.g., RFS-specific coding (E87.7), increased from once coded in 30 month in the retrospective cohort to four times in six months in the prospective cohort and doubled the rate of nutrition referrals in true positive patients (retrospective referrals in true positive patients 33% vs. prospective referrals in true positive patients 71%). Conclusion: CDSS-facilitated RFS diagnosis is possible and improves RFS recognition. This effect and its impact on patient-related outcomes needs to be further investigated in a large randomized-controlled trial.</description><subject>Algorithms</subject><subject>Analgesics</subject><subject>Clinical decision making</subject><subject>Datasets</subject><subject>Decision support systems</subject><subject>Electrolytes</subject><subject>Electronic health records</subject><subject>Feasibility studies</subject><subject>Gastrointestinal surgery</subject><subject>Information systems</subject><subject>Laboratories</subject><subject>Malnutrition</subject><subject>Medical referrals</subject><subject>Metabolism</subject><subject>Nutrition</subject><subject>Nutritionists</subject><subject>Parenteral nutrition</subject><subject>Patients</subject><subject>Potassium</subject><subject>Renal replacement therapy</subject><issn>2072-6643</issn><issn>2072-6643</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpdks2KFDEQx4Mo7rLuxScIeBFx1nx0J-mTDDOuLgwIjnsO6U5lzNKdjEn3wHjyIfYJ90lMM4tfqUNC1f__SxUUQi8pueK8Ie_CRGsquaTsCTpnRLKFEBV_-tf7DF3mfEfmI4kU_Dk641IoIavqHB3WcIA-7gcI41u8hux3AZtg8e3oe__DjD4GHB02eLXebrGLCX8BB2B92OHtMdgUB8A-lKzp8cY7wDdhX2yFh1cmwcPP-yW-BpN9W4DjEW_HyR5foGfO9BkuH-8LdHv94evq02Lz-ePNarlZdFyxcVHXbVXJireUWEFcqyQI0nEjWlbVTV2GoZ1pVMOAWcMdJdJZx7u2NSBtqxS_QO9P3P3UDmC70lUyvd4nP5h01NF4_W8l-G96Fw-akqohlM-E14-EFL9PkEc9-NxB35sAccqaKcFZw5ViRfrqP-ldnFIo880qJpqGyhl4dVLtTA_aBxfLx10JC4PvYgDnS34pRcWEVIIWw5uToUsx5wTud_uU6HkH9J8d4L8ALE2i1Q</recordid><startdate>20230824</startdate><enddate>20230824</enddate><creator>Heuft, Lara</creator><creator>Voigt, Jenny</creator><creator>Selig, Lars</creator><creator>Schmidt, Maria</creator><creator>Eckelt, Felix</creator><creator>Steinbach, Daniel</creator><creator>Federbusch, Martin</creator><creator>Stumvoll, Michael</creator><creator>Schlögl, Haiko</creator><creator>Isermann, Berend</creator><creator>Kaiser, Thorsten</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9470-1910</orcidid><orcidid>https://orcid.org/0000-0003-0714-6160</orcidid><orcidid>https://orcid.org/0000-0003-2364-598X</orcidid><orcidid>https://orcid.org/0000-0002-9479-3659</orcidid><orcidid>https://orcid.org/0000-0003-0523-3113</orcidid><orcidid>https://orcid.org/0000-0002-1126-5763</orcidid></search><sort><creationdate>20230824</creationdate><title>Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study</title><author>Heuft, Lara ; Voigt, Jenny ; Selig, Lars ; Schmidt, Maria ; Eckelt, Felix ; Steinbach, Daniel ; Federbusch, Martin ; Stumvoll, Michael ; Schlögl, Haiko ; Isermann, Berend ; Kaiser, Thorsten</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-55b44743b10d60fb87e60c3a6b245957631ca9892e2da3f107fdf3cbbae7db883</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Analgesics</topic><topic>Clinical decision making</topic><topic>Datasets</topic><topic>Decision support systems</topic><topic>Electrolytes</topic><topic>Electronic health records</topic><topic>Feasibility studies</topic><topic>Gastrointestinal surgery</topic><topic>Information systems</topic><topic>Laboratories</topic><topic>Malnutrition</topic><topic>Medical referrals</topic><topic>Metabolism</topic><topic>Nutrition</topic><topic>Nutritionists</topic><topic>Parenteral nutrition</topic><topic>Patients</topic><topic>Potassium</topic><topic>Renal replacement therapy</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Heuft, Lara</creatorcontrib><creatorcontrib>Voigt, Jenny</creatorcontrib><creatorcontrib>Selig, Lars</creatorcontrib><creatorcontrib>Schmidt, Maria</creatorcontrib><creatorcontrib>Eckelt, Felix</creatorcontrib><creatorcontrib>Steinbach, Daniel</creatorcontrib><creatorcontrib>Federbusch, Martin</creatorcontrib><creatorcontrib>Stumvoll, Michael</creatorcontrib><creatorcontrib>Schlögl, Haiko</creatorcontrib><creatorcontrib>Isermann, Berend</creatorcontrib><creatorcontrib>Kaiser, Thorsten</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</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 Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nutrients</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Heuft, Lara</au><au>Voigt, Jenny</au><au>Selig, Lars</au><au>Schmidt, Maria</au><au>Eckelt, Felix</au><au>Steinbach, Daniel</au><au>Federbusch, Martin</au><au>Stumvoll, Michael</au><au>Schlögl, Haiko</au><au>Isermann, Berend</au><au>Kaiser, Thorsten</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study</atitle><jtitle>Nutrients</jtitle><date>2023-08-24</date><risdate>2023</risdate><volume>15</volume><issue>17</issue><spage>3712</spage><pages>3712-</pages><issn>2072-6643</issn><eissn>2072-6643</eissn><abstract>Background: The refeeding syndrome (RFS) is an oftentimes-unrecognized complication of reintroducing nutrition in malnourished patients that can lead to fatal cardiovascular failure. We hypothesized that a clinical decision support system (CDSS) can improve RFS recognition and management. Methods: We developed an algorithm from current diagnostic criteria for RFS detection, tested the algorithm on a retrospective dataset and combined the final algorithm with therapy and referral recommendations in a knowledge-based CDSS. The CDSS integration into clinical practice was prospectively investigated for six months. Results: The utilization of the RFS-CDSS lead to RFS diagnosis in 13 out of 21 detected cases (62%). It improved patient-related care and documentation, e.g., RFS-specific coding (E87.7), increased from once coded in 30 month in the retrospective cohort to four times in six months in the prospective cohort and doubled the rate of nutrition referrals in true positive patients (retrospective referrals in true positive patients 33% vs. prospective referrals in true positive patients 71%). 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| subjects | Algorithms Analgesics Clinical decision making Datasets Decision support systems Electrolytes Electronic health records Feasibility studies Gastrointestinal surgery Information systems Laboratories Malnutrition Medical referrals Metabolism Nutrition Nutritionists Parenteral nutrition Patients Potassium Renal replacement therapy |
| title | Development, Design and Utilization of a CDSS for Refeeding Syndrome in Real Life Inpatient Care—A Feasibility Study |
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