AMIA Annu Symp Proc - Using language models to identify relevant new information in inpatient clinical notes.

Tópicos

{ extract(1171) text(1153) clinic(932) }
{ record(1888) medic(1808) patient(1693) }
{ search(2224) databas(1162) retriev(909) }
{ analysi(2126) use(1163) compon(1037) }
{ research(1085) discuss(1038) issu(1018) }
{ can(981) present(881) function(850) }
{ high(1669) rate(1365) level(1280) }
{ result(1111) use(1088) new(759) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ monitor(1329) mobil(1314) devic(1160) }
{ patient(2837) hospit(1953) medic(668) }
{ group(2977) signific(1463) compar(1072) }
{ use(976) code(926) identifi(902) }
{ detect(2391) sensit(1101) algorithm(908) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1057) registr(996) error(939) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
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{ visual(1396) interact(850) tool(830) }
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{ health(3367) inform(1360) care(1135) }
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{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
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{ control(1307) perform(991) simul(935) }
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{ howev(809) still(633) remain(590) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ patient(1821) servic(1111) care(1106) }
{ 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) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

Redundant information in clinical notes within electronic health record (EHR) systems is ubiquitous and may negatively impact the use of these notes by clinicians, and, potentially, the efficiency of patient care delivery. Automated methods to identify redundant versus relevant new information may provide a valuable tool for clinicians to better synthesize patient information and navigate to clinically important details. In this study, we investigated the use of language models for identification of new information in inpatient notes, and evaluated our methods using expert-derived reference standards. The best method achieved precision of 0.743, recall of 0.832 and F1-measure of 0.784. The average proportion of redundant information was similar between inpatient and outpatient progress notes (76.6% (SD=17.3%) and 76.7% (SD=14.0%), respectively). Advanced practice providers tended to have higher rates of redundancy in their notes compared to physicians. Future investigation includes the addition of semantic components and visualization of new information.

Resumo Limpo

redund inform clinic note within electron health record ehr system ubiquit may negat impact use note clinician potenti effici patient care deliveri autom method identifi redund versus relev new inform may provid valuabl tool clinician better synthes patient inform navig clinic import detail studi investig use languag model identif new inform inpati note evalu method use expertderiv refer standard best method achiev precis recal fmeasur averag proport redund inform similar inpati outpati progress note sd sd respect advanc practic provid tend higher rate redund note compar physician futur investig includ addit semant compon visual new inform

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