J Am Med Inform Assoc - A multi-layered framework for disseminating knowledge for computer-based decision support.

Tópicos

{ clinic(1479) use(1117) guidelin(835) }
{ concept(1167) ontolog(924) domain(897) }
{ implement(1333) system(1263) develop(1122) }
{ framework(1458) process(801) describ(734) }
{ use(1733) differ(960) four(931) }
{ design(1359) user(1324) use(1319) }
{ data(3963) clinic(1234) research(1004) }
{ ehr(2073) health(1662) electron(1139) }
{ measur(2081) correl(1212) valu(896) }
{ sequenc(1873) structur(1644) protein(1328) }
{ can(981) present(881) function(850) }
{ extract(1171) text(1153) clinic(932) }
{ patient(1821) servic(1111) care(1106) }
{ decis(3086) make(1611) patient(1517) }
{ system(1976) rule(880) can(841) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ control(1307) perform(991) simul(935) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ import(1318) role(1303) understand(862) }
{ health(3367) inform(1360) care(1135) }
{ intervent(3218) particip(2042) group(1664) }
{ health(1844) social(1437) communiti(874) }
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{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
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{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
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{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
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{ care(1570) inform(1187) nurs(1089) }
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{ risk(3053) factor(974) diseas(938) }
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{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: There are several challenges in encoding guideline knowledge in a form that is portable to different clinical sites, including the heterogeneity of clinical decision support (CDS) tools, of patient data representations, and of workflows.METHODS: We have developed a multi-layered knowledge representation framework for structuring guideline recommendations for implementation in a variety of CDS contexts. In this framework, guideline recommendations are increasingly structured through four layers, successively transforming a narrative text recommendation into input for a CDS system. We have used this framework to implement rules for a CDS service based on three guidelines. We also conducted a preliminary evaluation, where we asked CDS experts at four institutions to rate the implementability of six recommendations from the three guidelines.CONCLUSION: The experience in using the framework and the preliminary evaluation indicate that this approach has promise in creating structured knowledge, to implement in CDS systems, that is usable across organizations.

Resumo Limpo

ckground sever challeng encod guidelin knowledg form portabl differ clinic site includ heterogen clinic decis support cds tool patient data represent workflowsmethod develop multilay knowledg represent framework structur guidelin recommend implement varieti cds context framework guidelin recommend increas structur four layer success transform narrat text recommend input cds system use framework implement rule cds servic base three guidelin also conduct preliminari evalu ask cds expert four institut rate implement six recommend three guidelinesconclus experi use framework preliminari evalu indic approach promis creat structur knowledg implement cds system usabl across organ

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