Modeling patient response to acute myocardial infarction : implications for a tailored technology-based program to reduce patient delay

We are examining ways in which a clinical information system can favorably influence the appropriateness and rapidity of decision-making in patients suffering from symptoms of acute myocardial infarction. In order to do so, we have developed a theoretically based cognitive model for patient decision...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:Proceedings. AMIA Symposium. - 1998. - (1999) vom: 23., Seite 570-4
1. Verfasser: Kukafka, R (VerfasserIn)
Weitere Verfasser: Lussier, Y A, Patel, V L, Cimino, J J
Format: Aufsatz
Sprache:English
Veröffentlicht: 1999
Zugriff auf das übergeordnete Werk:Proceedings. AMIA Symposium
Schlagworte:Journal Article
LEADER 01000naa a22002652 4500
001 NLM104964154
003 DE-627
005 20231222133639.0
007 tu
008 231222s1999 xx ||||| 00| ||eng c
028 5 2 |a pubmed24n0350.xml 
035 |a (DE-627)NLM104964154 
035 |a (NLM)10566423 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Kukafka, R  |e verfasserin  |4 aut 
245 1 0 |a Modeling patient response to acute myocardial infarction  |b implications for a tailored technology-based program to reduce patient delay 
264 1 |c 1999 
336 |a Text  |b txt  |2 rdacontent 
337 |a ohne Hilfsmittel zu benutzen  |b n  |2 rdamedia 
338 |a Band  |b nc  |2 rdacarrier 
500 |a Date Completed 01.02.2000 
500 |a Date Revised 13.11.2018 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a We are examining ways in which a clinical information system can favorably influence the appropriateness and rapidity of decision-making in patients suffering from symptoms of acute myocardial infarction. In order to do so, we have developed a theoretically based cognitive model for patient decision making. Our model includes somatic and emotional awareness, perceived threat (vulnerability and susceptibility), expectations of symptoms, self-efficacy and response efficacy to explain the response of an individual their symptoms. Variables are explained within a framework that details how they are interrelated in the context of other moderating variables. With an understanding of the decision process, we are able to collect, maintain and access patient specific data to tailor technology-based interventions unique to the requirements of each individual at various phases of the decision process. Existing clinical information systems at Columbia-Presbyterian Medical Center already address issues related to patient relevant on-line data. Other patient specific information will be collected through on-line questionnaires. By basing our approach on the use of a cognitive model, we can assess the capacity of our interventions to modify variables important to the decision-making process, allowing us to pinpoint which interventions are effective and the reasons why they are ineffective 
650 4 |a Journal Article 
700 1 |a Lussier, Y A  |e verfasserin  |4 aut 
700 1 |a Patel, V L  |e verfasserin  |4 aut 
700 1 |a Cimino, J J  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Proceedings. AMIA Symposium  |d 1998  |g (1999) vom: 23., Seite 570-4  |w (DE-627)NLM098642928  |x 1531-605X  |7 nnns 
773 1 8 |g year:1999  |g day:23  |g pages:570-4 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |j 1999  |b 23  |h 570-4