AMIA Annu Symp Proc - Methods to identify standard data elements in clinical and public health forms.

Tópicos

{ data(3008) multipl(1320) sourc(1022) }
{ data(3963) clinic(1234) research(1004) }
{ ehr(2073) health(1662) electron(1139) }
{ visual(1396) interact(850) tool(830) }
{ record(1888) medic(1808) patient(1693) }
{ activ(1138) subject(705) human(624) }
{ health(1844) social(1437) communiti(874) }
{ studi(1410) differ(1259) use(1210) }
{ import(1318) role(1303) understand(862) }
{ blood(1257) pressur(1144) flow(957) }
{ state(1844) use(1261) util(961) }
{ measur(2081) correl(1212) valu(896) }
{ sequenc(1873) structur(1644) protein(1328) }
{ studi(2440) review(1878) systemat(933) }
{ treatment(1704) effect(941) patient(846) }
{ perform(999) metric(946) measur(919) }
{ health(3367) inform(1360) care(1135) }
{ group(2977) signific(1463) compar(1072) }
{ use(1733) differ(960) four(931) }
{ method(2212) result(1239) propos(1039) }
{ data(1737) use(1416) pattern(1282) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(2675) segment(2577) method(1081) }
{ framework(1458) process(801) describ(734) }
{ extract(1171) text(1153) clinic(932) }
{ general(901) number(790) one(736) }
{ risk(3053) factor(974) diseas(938) }
{ monitor(1329) mobil(1314) devic(1160) }
{ intervent(3218) particip(2042) group(1664) }
{ analysi(2126) use(1163) compon(1037) }
{ drug(1928) target(777) effect(648) }
{ survey(1388) particip(1329) question(1065) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }
{ 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) }
{ imag(1057) registr(996) error(939) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ 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) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ model(3480) simul(1196) paramet(876) }
{ 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) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }

Resumo

The fragmentation of clinical and public health systems results in divergent information collection practices, presenting challenges to standardization and EHR certification efforts. Data forms employed in public health jurisdictions nationwide reflect these differences in patient treatment, monitoring and evaluation, and follow-up, presenting challenges for data integration. To study these variations, we surveyed tuberculosis contact investigation forms from all fifty states, three municipalities and two countries. We apply statistics and cluster analysis to analyze the divergent content of contact investigation forms with the goal of characterizing normative practices and identifying a common core of data fields. We found widespread variation in data elements between states in the study, with the "Name" field being the only ubiquitous data element. Our method reveals distinct groupings of data fields employed in certain regions, allowing the simultaneous identification of core standard data fields as well as variations in practice.

Resumo Limpo

fragment clinic public health system result diverg inform collect practic present challeng standard ehr certif effort data form employ public health jurisdict nationwid reflect differ patient treatment monitor evalu followup present challeng data integr studi variat survey tuberculosi contact investig form fifti state three municip two countri appli statist cluster analysi analyz diverg content contact investig form goal character normat practic identifi common core data field found widespread variat data element state studi name field ubiquit data element method reveal distinct group data field employ certain region allow simultan identif core standard data field well variat practic

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