AMIA Annu Symp Proc - Demonstrating collect once, use many--assimilating public health secondary data use requirements into an existing Domain Analysis Model.

Tópicos

{ data(3963) clinic(1234) research(1004) }
{ ehr(2073) health(1662) electron(1139) }
{ data(1737) use(1416) pattern(1282) }
{ research(1218) medic(880) student(794) }
{ model(3404) distribut(989) bayesian(671) }
{ patient(2315) diseas(1263) diabet(1191) }
{ health(1844) social(1437) communiti(874) }
{ sequenc(1873) structur(1644) protein(1328) }
{ imag(2830) propos(1344) filter(1198) }
{ learn(2355) train(1041) set(1003) }
{ model(2220) cell(1177) simul(1124) }
{ search(2224) databas(1162) retriev(909) }
{ risk(3053) factor(974) diseas(938) }
{ data(2317) use(1299) case(1017) }
{ implement(1333) system(1263) develop(1122) }
{ can(774) often(719) complex(702) }
{ method(1219) similar(1157) match(930) }
{ take(945) account(800) differ(722) }
{ problem(2511) optim(1539) algorithm(950) }
{ design(1359) user(1324) use(1319) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ perform(1367) use(1326) method(1137) }
{ spatial(1525) area(1432) region(1030) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ activ(1138) subject(705) human(624) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ method(2212) result(1239) propos(1039) }
{ 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) }
{ bind(1733) structur(1185) ligand(1036) }
{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ 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) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ care(1570) inform(1187) nurs(1089) }
{ 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) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ 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) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(1733) differ(960) four(931) }
{ survey(1388) particip(1329) question(1065) }
{ 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) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The healthcare industry has an increasing need for clinical data content standards to support patient care and data re-use in areas such as research, quality and public health. The Diabetes Data Strategy (Diabe-DS) project was formed in 2009 by the HL7 EHR Working Group to demonstrate a repeatable process that identifies disease-specific Common Data Elements (CDEs) for clinical care and secondary use. The Diabe-DS project previously developed a set of important CDEs and supporting data models for clinical care, quality and research uses of diabetes data. This paper will describe the process for identifying the data elements and activities required for public health use of clinical data, and mapping them to Diabe-DS CDEs, use case and data models. The result is a model for consideration which provides data needed in the immediate clinical environment of care, and supports the use of data for multiple uses.

Resumo Limpo

healthcar industri increas need clinic data content standard support patient care data reus area research qualiti public health diabet data strategi diab project form hl ehr work group demonstr repeat process identifi diseasespecif common data element cdes clinic care secondari use diab project previous develop set import cdes support data model clinic care qualiti research use diabet data paper will describ process identifi data element activ requir public health use clinic data map diab cdes use case data model result model consider provid data need immedi clinic environ care support use data multipl use

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