AMIA Annu Symp Proc - Query log analysis of an electronic health record search engine.

Tópicos

{ search(2224) databas(1162) retriev(909) }
{ ehr(2073) health(1662) electron(1139) }
{ data(1737) use(1416) pattern(1282) }
{ implement(1333) system(1263) develop(1122) }
{ design(1359) user(1324) use(1319) }
{ care(1570) inform(1187) nurs(1089) }
{ group(2977) signific(1463) compar(1072) }
{ result(1111) use(1088) new(759) }
{ activ(1452) weight(1219) physic(1104) }
{ concept(1167) ontolog(924) domain(897) }
{ system(1050) medic(1026) inform(1018) }
{ health(3367) inform(1360) care(1135) }
{ analysi(2126) use(1163) compon(1037) }
{ use(976) code(926) identifi(902) }
{ decis(3086) make(1611) patient(1517) }
{ imag(1947) propos(1133) code(1026) }
{ system(1976) rule(880) can(841) }
{ studi(2440) review(1878) systemat(933) }
{ extract(1171) text(1153) clinic(932) }
{ data(1714) softwar(1251) tool(1186) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ research(1218) medic(880) student(794) }
{ sampl(1606) size(1419) use(1276) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ high(1669) rate(1365) level(1280) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ 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) }
{ assess(1506) score(1403) qualiti(1306) }
{ 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) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(1557) propos(1049) approach(1037) }
{ 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) }
{ howev(809) still(633) remain(590) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(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) }
{ 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) }
{ 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) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ survey(1388) particip(1329) question(1065) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

We analyzed a longitudinal collection of query logs of a full-text search engine designed to facilitate information retrieval in electronic health records (EHR). The collection, 202,905 queries and 35,928 user sessions recorded over a course of 4 years, represents the information-seeking behavior of 533 medical professionals, including frontline practitioners, coding personnel, patient safety officers, and biomedical researchers for patient data stored in EHR systems. In this paper, we present descriptive statistics of the queries, a categorization of information needs manifested through the queries, as well as temporal patterns of the users' information-seeking behavior. The results suggest that information needs in medical domain are substantially more sophisticated than those that general-purpose web search engines need to accommodate. Therefore, we envision there exists a significant challenge, along with significant opportunities, to provide intelligent query recommendations to facilitate information retrieval in EHR.

Resumo Limpo

analyz longitudin collect queri log fulltext search engin design facilit inform retriev electron health record ehr collect queri user session record cours year repres informationseek behavior medic profession includ frontlin practition code personnel patient safeti offic biomed research patient data store ehr system paper present descript statist queri categor inform need manifest queri well tempor pattern user informationseek behavior result suggest inform need medic domain substanti sophist generalpurpos web search engin need accommod therefor envis exist signific challeng along signific opportun provid intellig queri recommend facilit inform retriev ehr

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