AMIA Annu Symp Proc - Cross-mapping clinical notes between hospitals: an application of the LOINC Document Ontology.

Tópicos

{ ehr(2073) health(1662) electron(1139) }
{ concept(1167) ontolog(924) domain(897) }
{ method(1219) similar(1157) match(930) }
{ case(1353) use(1143) diagnosi(1136) }
{ extract(1171) text(1153) clinic(932) }
{ implement(1333) system(1263) develop(1122) }
{ bind(1733) structur(1185) ligand(1036) }
{ control(1307) perform(991) simul(935) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ use(976) code(926) identifi(902) }
{ survey(1388) particip(1329) question(1065) }
{ detect(2391) sensit(1101) algorithm(908) }
{ data(1737) use(1416) pattern(1282) }
{ framework(1458) process(801) describ(734) }
{ design(1359) user(1324) use(1319) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
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{ health(3367) inform(1360) care(1135) }
{ 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) }
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{ data(3008) multipl(1320) sourc(1022) }
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{ time(1939) patient(1703) rate(768) }
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{ analysi(2126) use(1163) compon(1037) }
{ 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) }
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{ estim(2440) model(1874) function(577) }
{ 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) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ sequenc(1873) structur(1644) protein(1328) }
{ 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) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ 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) }
{ data(1714) softwar(1251) tool(1186) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ 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) }

Resumo

Standardization of document titles is essential for management as the volume of electronic clinical notes increases. The two campuses of the New York Presbyterian Hospital have over 2,700 distinct document titles. The LOINC Document Ontology (DO) provides a standard for the naming of clinical documents in a multi-axis structure. We have represented the latest LOINC DO structure in the MED, and developed an automated process mapping the clinical documents from both the West (Columbia) and East (Cornell) campuses to the LOINC DO. We find that the LOINC DO can represent the majority of our documents, and about half of the documents map between campuses using the LOINC DO as a reference. We evaluated the possibility of using current LOINC codes in document exchange between different institutions. While there is clear success in the ability of the LOINC DO to represent documents and facilitate exchange we find there are granularity issues.

Resumo Limpo

standard document titl essenti manag volum electron clinic note increas two campus new york presbyterian hospit distinct document titl loinc document ontolog provid standard name clinic document multiaxi structur repres latest loinc structur med develop autom process map clinic document west columbia east cornel campus loinc find loinc can repres major document half document map campus use loinc refer evalu possibl use current loinc code document exchang differ institut clear success abil loinc repres document facilit exchang find granular issu

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