Inform Health Soc Care - A web-based intensive care clinical decision support system: from design to evaluation.

Tópicos

{ survey(1388) particip(1329) question(1065) }
{ clinic(1479) use(1117) guidelin(835) }
{ decis(3086) make(1611) patient(1517) }
{ design(1359) user(1324) use(1319) }
{ method(1969) cluster(1462) data(1082) }
{ measur(2081) correl(1212) valu(896) }
{ health(3367) inform(1360) care(1135) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ medic(1828) order(1363) alert(1069) }
{ inform(2794) health(2639) internet(1427) }
{ spatial(1525) area(1432) region(1030) }
{ first(2504) two(1366) second(1323) }
{ activ(1452) weight(1219) physic(1104) }
{ studi(1410) differ(1259) use(1210) }
{ data(3008) multipl(1320) sourc(1022) }
{ model(3404) distribut(989) bayesian(671) }
{ bind(1733) structur(1185) ligand(1036) }
{ patient(2315) diseas(1263) diabet(1191) }
{ assess(1506) score(1403) qualiti(1306) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ control(1307) perform(991) simul(935) }
{ general(901) number(790) one(736) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1119) effect(1106) posit(819) }
{ group(2977) signific(1463) compar(1072) }
{ patient(1821) servic(1111) care(1106) }
{ analysi(2126) use(1163) compon(1037) }
{ use(976) code(926) identifi(902) }
{ method(2212) result(1239) propos(1039) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ system(1976) rule(880) can(841) }
{ imag(1057) registr(996) error(939) }
{ sequenc(1873) structur(1644) protein(1328) }
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{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The aim of this study is to develop and evaluate a web-based clinical decision support system (CDSS) containing clinical guidelines and protocols that will support intensive care unit (ICU) providers in making decisions more effectively and quickly. First, a survey was carried out with 38 physicians in order to determine their preferences, needs and concerns regarding decision support tools. After the survey, guidelines were prepared by a group of specialists in ICU, and a medical informatician converted the guidelines into algorithm forms. Ten CDSS were developed using the algorithms, and placed onto the Intensive Care Decision Support Website (ICDSW). In order to evaluation of the website, 15 physicians were asked to answer 10 questions in 10 different scenarios first using a paper-based approach, then with ICDSW. When the answers were analyzed, it was found that the answers given by using ICDSW were significantly better than the paper-based approach (p < 0.001). However, there was no significant difference in terms of the time needed to answer the questions (p = 0.138). The usability score of the website was 85.6 ? 8.89. The study demonstrated the successful implementation of an ICDSW within intensive care units.

Resumo Limpo

aim studi develop evalu webbas clinic decis support system cdss contain clinic guidelin protocol will support intens care unit icu provid make decis effect quick first survey carri physician order determin prefer need concern regard decis support tool survey guidelin prepar group specialist icu medic informatician convert guidelin algorithm form ten cdss develop use algorithm place onto intens care decis support websit icdsw order evalu websit physician ask answer question differ scenario first use paperbas approach icdsw answer analyz found answer given use icdsw signific better paperbas approach p howev signific differ term time need answer question p usabl score websit studi demonstr success implement icdsw within intens care unit

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