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Can a clinician predict the technical equipment a patient will need during intensive care unit treatment ? An approach to standardize and redesign the intensive care unit workstation
The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm p...
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Published in: | Journal of Clinical Monitoring 1992, Vol.8 (1), p.1-6 |
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description | The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm philosophies, and cannot communicate with each other. By contrast, ICU workstations could be equipped permanently and in a standardized manner with electronically linked modules if the attending physicians could reliably predict, at the time of admission, the patient's equipment needs. Over a period of 3 1/2 months, the doctors working in our 20-bed surgical ICU made 1,000 predictions concerning outcome, equipment need, duration of artificial ventilation, and duration of hospitalization for 300 recently admitted patients. The interviews were made within the first 24 hours after admission. The doctors being interviewed were usually (i.e., in over 90% of cases) unfamiliar with the patient. Information concerning the patient's general state of health, special pre-ICU events, and complications was offered to the interviewed clinician because this information represents standard admission data. It was found that the equipment need (represented by two different setups, "high tech" and "low tech") could be predicted most reliably (96.4% correct predictions) compared with a prediction on outcome of ICU treatment (94.5%), on duration of artificial ventilation (75.4%), and on duration of stay (43.4%). There was no significant (p greater than 0.05) difference in the reliability of predictions between residents and consultants. Factors influencing the postoperative equipment need varied with surgical specialty. |
doi_str_mv | 10.1007/BF01618079 |
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An approach to standardize and redesign the intensive care unit workstation</title><source>Alma/SFX Local Collection</source><creator>HÄHNEL, J ; FRIESDORF, W ; SCHWILK, B ; MARX, T ; BLESSING, S</creator><creatorcontrib>HÄHNEL, J ; FRIESDORF, W ; SCHWILK, B ; MARX, T ; BLESSING, S</creatorcontrib><description>The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm philosophies, and cannot communicate with each other. By contrast, ICU workstations could be equipped permanently and in a standardized manner with electronically linked modules if the attending physicians could reliably predict, at the time of admission, the patient's equipment needs. 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There was no significant (p greater than 0.05) difference in the reliability of predictions between residents and consultants. Factors influencing the postoperative equipment need varied with surgical specialty.</description><identifier>ISSN: 0748-1977</identifier><identifier>EISSN: 2214-7330</identifier><identifier>EISSN: 1573-2614</identifier><identifier>DOI: 10.1007/BF01618079</identifier><identifier>PMID: 1538245</identifier><identifier>CODEN: JCMOEH</identifier><language>eng</language><publisher>Boston, MA: Little</publisher><subject>Anesthesia Department, Hospital ; Anesthesia. Intensive care medicine. Transfusions. 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Emergency, hospital ward ; Intensive Care Units - statistics & numerical data ; Length of Stay ; Male ; Medical Laboratory Science - instrumentation ; Medical sciences ; Middle Aged ; Monitoring, Physiologic - instrumentation ; Outcome Assessment (Health Care) ; Probability ; Respiration, Artificial ; Sepsis ; Survival Rate ; Time Factors</subject><ispartof>Journal of Clinical Monitoring, 1992, Vol.8 (1), p.1-6</ispartof><rights>1992 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-98844eb412ab2d64b56621aaf10be7d176bb668f8deb6a3c23e08c366cc751b73</citedby><cites>FETCH-LOGICAL-c347t-98844eb412ab2d64b56621aaf10be7d176bb668f8deb6a3c23e08c366cc751b73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=5206374$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/1538245$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>HÄHNEL, J</creatorcontrib><creatorcontrib>FRIESDORF, W</creatorcontrib><creatorcontrib>SCHWILK, B</creatorcontrib><creatorcontrib>MARX, T</creatorcontrib><creatorcontrib>BLESSING, S</creatorcontrib><title>Can a clinician predict the technical equipment a patient will need during intensive care unit treatment ? An approach to standardize and redesign the intensive care unit workstation</title><title>Journal of Clinical Monitoring</title><addtitle>J Clin Monit</addtitle><description>The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm philosophies, and cannot communicate with each other. By contrast, ICU workstations could be equipped permanently and in a standardized manner with electronically linked modules if the attending physicians could reliably predict, at the time of admission, the patient's equipment needs. Over a period of 3 1/2 months, the doctors working in our 20-bed surgical ICU made 1,000 predictions concerning outcome, equipment need, duration of artificial ventilation, and duration of hospitalization for 300 recently admitted patients. The interviews were made within the first 24 hours after admission. The doctors being interviewed were usually (i.e., in over 90% of cases) unfamiliar with the patient. Information concerning the patient's general state of health, special pre-ICU events, and complications was offered to the interviewed clinician because this information represents standard admission data. It was found that the equipment need (represented by two different setups, "high tech" and "low tech") could be predicted most reliably (96.4% correct predictions) compared with a prediction on outcome of ICU treatment (94.5%), on duration of artificial ventilation (75.4%), and on duration of stay (43.4%). There was no significant (p greater than 0.05) difference in the reliability of predictions between residents and consultants. Factors influencing the postoperative equipment need varied with surgical specialty.</description><subject>Anesthesia Department, Hospital</subject><subject>Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy</subject><subject>Biological and medical sciences</subject><subject>Cardiac Surgical Procedures - statistics & numerical data</subject><subject>Coronary Artery Bypass - statistics & numerical data</subject><subject>Critical Care - statistics & numerical data</subject><subject>Emergency and intensive care: techniques, logistics</subject><subject>Equipment Design</subject><subject>Female</subject><subject>Heart Valves - surgery</subject><subject>Humans</subject><subject>Intensive care medicine</subject><subject>Intensive care unit. Emergency transport systems. Emergency, hospital ward</subject><subject>Intensive Care Units - statistics & numerical data</subject><subject>Length of Stay</subject><subject>Male</subject><subject>Medical Laboratory Science - instrumentation</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Monitoring, Physiologic - instrumentation</subject><subject>Outcome Assessment (Health Care)</subject><subject>Probability</subject><subject>Respiration, Artificial</subject><subject>Sepsis</subject><subject>Survival Rate</subject><subject>Time Factors</subject><issn>0748-1977</issn><issn>2214-7330</issn><issn>1573-2614</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1992</creationdate><recordtype>article</recordtype><recordid>eNptkc1u1DAUhS0EKkNhwx7JC9RFpVD_xfasUBm1gFSpG1hH185Nx5BxUtuhog_G8-F2RnTDyke-3z3H8iHkLWcfOGPm7NMl45pbZtbPyEoIrhojJXtOVswo2_C1MS_Jq5x_MMaEXYsjcsRbaYVqV-TPBiIF6scQgw9Vzwn74AstW6QF_bZew0jxdgnzDmOp7AwlPKi7MI40Iva0X1KINzTEgjGHX0g9JKRLDNUmIZTHxY_0vCbNc5rAb2mZaC4Qe0h9uEdaFa3BmMNNfIz-n9fdlH7WpRKm-Jq8GGDM-OZwHpPvlxffNl-aq-vPXzfnV42XypRmba1S6BQX4ESvlWu1Fhxg4Myh6bnRzmltB9uj0yC9kMisl1p7b1rujDwmJ3vf-uzbBXPpdiF7HEeIOC25M8IKqVpZwdM96NOUc8Khm1PYQfrdcdY9lNQ9lVThdwfXxe2wf0L3rdT5-8Mccv39IUH0If_DWsG0NEr-BRccnMs</recordid><startdate>1992</startdate><enddate>1992</enddate><creator>HÄHNEL, J</creator><creator>FRIESDORF, W</creator><creator>SCHWILK, B</creator><creator>MARX, T</creator><creator>BLESSING, S</creator><general>Little</general><scope>IQODW</scope><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>1992</creationdate><title>Can a clinician predict the technical equipment a patient will need during intensive care unit treatment ? An approach to standardize and redesign the intensive care unit workstation</title><author>HÄHNEL, J ; FRIESDORF, W ; SCHWILK, B ; MARX, T ; BLESSING, S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-98844eb412ab2d64b56621aaf10be7d176bb668f8deb6a3c23e08c366cc751b73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1992</creationdate><topic>Anesthesia Department, Hospital</topic><topic>Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy</topic><topic>Biological and medical sciences</topic><topic>Cardiac Surgical Procedures - statistics & numerical data</topic><topic>Coronary Artery Bypass - statistics & numerical data</topic><topic>Critical Care - statistics & numerical data</topic><topic>Emergency and intensive care: techniques, logistics</topic><topic>Equipment Design</topic><topic>Female</topic><topic>Heart Valves - surgery</topic><topic>Humans</topic><topic>Intensive care medicine</topic><topic>Intensive care unit. Emergency transport systems. Emergency, hospital ward</topic><topic>Intensive Care Units - statistics & numerical data</topic><topic>Length of Stay</topic><topic>Male</topic><topic>Medical Laboratory Science - instrumentation</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Monitoring, Physiologic - instrumentation</topic><topic>Outcome Assessment (Health Care)</topic><topic>Probability</topic><topic>Respiration, Artificial</topic><topic>Sepsis</topic><topic>Survival Rate</topic><topic>Time Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>HÄHNEL, J</creatorcontrib><creatorcontrib>FRIESDORF, W</creatorcontrib><creatorcontrib>SCHWILK, B</creatorcontrib><creatorcontrib>MARX, T</creatorcontrib><creatorcontrib>BLESSING, S</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of Clinical Monitoring</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>HÄHNEL, J</au><au>FRIESDORF, W</au><au>SCHWILK, B</au><au>MARX, T</au><au>BLESSING, S</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Can a clinician predict the technical equipment a patient will need during intensive care unit treatment ? An approach to standardize and redesign the intensive care unit workstation</atitle><jtitle>Journal of Clinical Monitoring</jtitle><addtitle>J Clin Monit</addtitle><date>1992</date><risdate>1992</risdate><volume>8</volume><issue>1</issue><spage>1</spage><epage>6</epage><pages>1-6</pages><issn>0748-1977</issn><eissn>2214-7330</eissn><eissn>1573-2614</eissn><coden>JCMOEH</coden><abstract>The technical equipment of today's intensive care unit (ICU) workstation has been characterized by a gradual, incremental accumulation of individual devices, whose presence is dictated by patient needs. These devices usually present differently designed controls, operate under different alarm philosophies, and cannot communicate with each other. By contrast, ICU workstations could be equipped permanently and in a standardized manner with electronically linked modules if the attending physicians could reliably predict, at the time of admission, the patient's equipment needs. Over a period of 3 1/2 months, the doctors working in our 20-bed surgical ICU made 1,000 predictions concerning outcome, equipment need, duration of artificial ventilation, and duration of hospitalization for 300 recently admitted patients. The interviews were made within the first 24 hours after admission. The doctors being interviewed were usually (i.e., in over 90% of cases) unfamiliar with the patient. Information concerning the patient's general state of health, special pre-ICU events, and complications was offered to the interviewed clinician because this information represents standard admission data. It was found that the equipment need (represented by two different setups, "high tech" and "low tech") could be predicted most reliably (96.4% correct predictions) compared with a prediction on outcome of ICU treatment (94.5%), on duration of artificial ventilation (75.4%), and on duration of stay (43.4%). There was no significant (p greater than 0.05) difference in the reliability of predictions between residents and consultants. Factors influencing the postoperative equipment need varied with surgical specialty.</abstract><cop>Boston, MA</cop><pub>Little</pub><pmid>1538245</pmid><doi>10.1007/BF01618079</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Anesthesia Department, Hospital Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy Biological and medical sciences Cardiac Surgical Procedures - statistics & numerical data Coronary Artery Bypass - statistics & numerical data Critical Care - statistics & numerical data Emergency and intensive care: techniques, logistics Equipment Design Female Heart Valves - surgery Humans Intensive care medicine Intensive care unit. Emergency transport systems. Emergency, hospital ward Intensive Care Units - statistics & numerical data Length of Stay Male Medical Laboratory Science - instrumentation Medical sciences Middle Aged Monitoring, Physiologic - instrumentation Outcome Assessment (Health Care) Probability Respiration, Artificial Sepsis Survival Rate Time Factors |
title | Can a clinician predict the technical equipment a patient will need during intensive care unit treatment ? An approach to standardize and redesign the intensive care unit workstation |
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