AMIA Annu Symp Proc - Metadata extraction routines for improving infobutton performance.

Tópicos

{ inform(2794) health(2639) internet(1427) }
{ care(1570) inform(1187) nurs(1089) }
{ extract(1171) text(1153) clinic(932) }
{ implement(1333) system(1263) develop(1122) }
{ data(2317) use(1299) case(1017) }
{ use(1733) differ(960) four(931) }
{ sampl(1606) size(1419) use(1276) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ assess(1506) score(1403) qualiti(1306) }
{ data(3963) clinic(1234) research(1004) }
{ research(1085) discuss(1038) issu(1018) }
{ health(3367) inform(1360) care(1135) }
{ signal(2180) analysi(812) frequenc(800) }
{ patient(1821) servic(1111) care(1106) }
{ process(1125) use(805) approach(778) }
{ imag(1057) registr(996) error(939) }
{ studi(2440) review(1878) systemat(933) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ method(1557) propos(1049) approach(1037) }
{ search(2224) databas(1162) retriev(909) }
{ howev(809) still(633) remain(590) }
{ perform(999) metric(946) measur(919) }
{ import(1318) role(1303) understand(862) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(2656) set(1616) predict(1553) }
{ gene(2352) biolog(1181) express(1162) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ use(976) code(926) identifi(902) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ system(1976) rule(880) can(841) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ 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) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ 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) }
{ analysi(2126) use(1163) compon(1037) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ drug(1928) target(777) effect(648) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

Infobuttons have been proven as an effective means for providing quick, context-specific links to pertinent information resources at the point of care. Current infobutton manager implementations, however, lack the ability to exchange metadata, are limited to a relatively small set of information providers, and are targeted primarily for a clinician audience. As part of a local effort to implement infobuttons for patient use via a tethered personal health record, we present a series of metadata extraction routines. These routines were constructed to extract key pieces of information from health information providers on the Internet, including content coverage, language availability, and readability scores. The extraction routines were tested using thirty different disease conditions against eight different providers. The routines yielded 183 potential infobutton targets and associated metadata for each. The capabilities of the extraction routines will be expanded to cover new types of metadata in the future.

Resumo Limpo

infobutton proven effect mean provid quick contextspecif link pertin inform resourc point care current infobutton manag implement howev lack abil exchang metadata limit relat small set inform provid target primarili clinician audienc part local effort implement infobutton patient use via tether person health record present seri metadata extract routin routin construct extract key piec inform health inform provid internet includ content coverag languag avail readabl score extract routin test use thirti differ diseas condit eight differ provid routin yield potenti infobutton target associ metadata capabl extract routin will expand cover new type metadata futur

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