Methods Inf Med - Piloting the EHR4CR feasibility platform across Europe.

Tópicos

{ data(1714) softwar(1251) tool(1186) }
{ ehr(2073) health(1662) electron(1139) }
{ model(2656) set(1616) predict(1553) }
{ spatial(1525) area(1432) region(1030) }
{ survey(1388) particip(1329) question(1065) }
{ use(976) code(926) identifi(902) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ research(1218) medic(880) student(794) }
{ studi(2440) review(1878) systemat(933) }
{ clinic(1479) use(1117) guidelin(835) }
{ control(1307) perform(991) simul(935) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ analysi(2126) use(1163) compon(1037) }
{ search(2224) databas(1162) retriev(909) }
{ patient(2837) hospit(1953) medic(668) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ data(3008) multipl(1320) sourc(1022) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(2830) propos(1344) filter(1198) }
{ take(945) account(800) differ(722) }
{ design(1359) user(1324) use(1319) }
{ general(901) number(790) one(736) }
{ signal(2180) analysi(812) frequenc(800) }
{ implement(1333) system(1263) develop(1122) }
{ model(3404) distribut(989) bayesian(671) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ method(1219) similar(1157) match(930) }
{ network(2748) neural(1063) input(814) }
{ assess(1506) score(1403) qualiti(1306) }
{ model(2220) cell(1177) simul(1124) }
{ import(1318) role(1303) understand(862) }
{ health(3367) inform(1360) care(1135) }
{ state(1844) use(1261) util(961) }
{ data(2317) use(1299) case(1017) }
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{ can(774) often(719) complex(702) }
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{ imag(2675) segment(2577) method(1081) }
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{ treatment(1704) effect(941) patient(846) }
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{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ 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) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ 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) }
{ result(1111) use(1088) new(759) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: Pharmaceutical clinical trials are primarily conducted across many countries, yet recruitment numbers are frequently not met in time. Electronic health records store large amounts of potentially useful data that could aid in this process. The EHR4CR project aims at re-using EHR data for clinical research purposes.OBJECTIVE: To evaluate whether the protocol feasibility platform produced by the Electronic Health Records for Clinical Research (EHR4CR) project can be installed and set up in accordance with local technical and governance requirements to execute protocol feasibility queries uniformly across national borders.METHODS: We installed specifically engineered software and warehouses at local sites. Approvals for data access and usage of the platform were acquired and terminology mapping of local site codes to central platform codes were performed. A test data set, or real EHR data where approvals were in place, were loaded into data warehouses. Test feasibility queries were created on a central component of the platform and sent to the local components at eleven university hospitals.RESULTS: To use real, de-identified EHR data we obtained permissions and approvals from 'data controllers' and ethics committees. Through the platform we were able to create feasibility queries, distribute them to eleven university hospitals and retrieve aggregated patient counts of both test data and de-identified EHR data.CONCLUSION: It is possible to install a uniform piece of software in different university hospitals in five European countries and configure it to the requirements of the local networks, while complying with local data protection regulations. We were also able set up ETL processes and data warehouses, to re-use EHR data for feasibility queries distributed over the EHR4CR platform.

Resumo Limpo

ckground pharmaceut clinic trial primarili conduct across mani countri yet recruit number frequent met time electron health record store larg amount potenti use data aid process ehrcr project aim reus ehr data clinic research purposesobject evalu whether protocol feasibl platform produc electron health record clinic research ehrcr project can instal set accord local technic govern requir execut protocol feasibl queri uniform across nation bordersmethod instal specif engin softwar warehous local site approv data access usag platform acquir terminolog map local site code central platform code perform test data set real ehr data approv place load data warehous test feasibl queri creat central compon platform sent local compon eleven univers hospitalsresult use real deidentifi ehr data obtain permiss approv data control ethic committe platform abl creat feasibl queri distribut eleven univers hospit retriev aggreg patient count test data deidentifi ehr dataconclus possibl instal uniform piec softwar differ univers hospit five european countri configur requir local network compli local data protect regul also abl set etl process data warehous reus ehr data feasibl queri distribut ehrcr platform

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