BMC Med Inform Decis Mak - Medical record: systematic centralization versus secure on demand aggregation.

Tópicos

{ system(1050) medic(1026) inform(1018) }
{ health(3367) inform(1360) care(1135) }
{ can(774) often(719) complex(702) }
{ data(3008) multipl(1320) sourc(1022) }
{ search(2224) databas(1162) retriev(909) }
{ design(1359) user(1324) use(1319) }
{ general(901) number(790) one(736) }
{ cancer(2502) breast(956) screen(824) }
{ research(1085) discuss(1038) issu(1018) }
{ drug(1928) target(777) effect(648) }
{ ehr(2073) health(1662) electron(1139) }
{ method(2212) result(1239) propos(1039) }
{ measur(2081) correl(1212) valu(896) }
{ featur(1941) imag(1645) propos(1176) }
{ research(1218) medic(880) student(794) }
{ first(2504) two(1366) second(1323) }
{ problem(2511) optim(1539) algorithm(950) }
{ concept(1167) ontolog(924) domain(897) }
{ control(1307) perform(991) simul(935) }
{ risk(3053) factor(974) diseas(938) }
{ age(1611) year(1155) adult(843) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ inform(2794) health(2639) internet(1427) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2675) segment(2577) method(1081) }
{ studi(2440) review(1878) systemat(933) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ method(984) reconstruct(947) comput(926) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ visual(1396) interact(850) tool(830) }
{ blood(1257) pressur(1144) flow(957) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ model(2656) set(1616) predict(1553) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ system(1976) rule(880) can(841) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ 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) }
{ treatment(1704) effect(941) patient(846) }
{ learn(2355) train(1041) set(1003) }
{ 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) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ import(1318) role(1303) understand(862) }
{ 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) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ 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) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: As patients often see the data of their medical histories scattered among various medical records hosted in several health-care establishments, the purpose of our multidisciplinary study was to define a pragmatic and secure on-demand based system able to gather this information, with no risk of breaching confidentiality, and to relay it to a medical professional who asked for the information via a specific search engine.METHODS: Scattered data are often heterogeneous, which makes the task of gathering information very hard. Two methods can be compared: trying to solve the problem by standardizing and centralizing all the information about every patient in a single Medical Record system or trying to use the data "as is" and find a way to obtain the most complete and the most accurate information. Given the failure of the first approach, due to the lack of standardization or privacy and security problems, for example, we propose an alternative that relies on the current state of affairs: an on-demand system, using a specific search engine that is able to retrieve information from the different medical records of a single patient.RESULTS: We describe the function of Medical Record Search Engines (MRSE), which are able to retrieve all the available information regarding a patient who has been hospitalized in different hospitals and to provide this information to health professionals upon request. MRSEs use pseudonymized patient identities and thus never have access to the patient's identity. However, though the system would be easy to implement as it by-passes many of the difficulties associated with a centralized architecture, the health professional would have to validate the information, i.e. read all of the information and create his own synthesis and possibly reject extra data, which could be a drawback. We thus propose various feasible improvements, based on the implementation of several tools in our on-demand based system.CONCLUSIONS: A system that gathers all of the currently available information regarding a patient on the request of health-care professionals could be of great interest. This low-cost pragmatic alternative to centralized medical records could be developed quickly and easily. It could also be designed to include extra features and should thus be considered by health authorities.

Resumo Limpo

ckground patient often see data medic histori scatter among various medic record host sever healthcar establish purpos multidisciplinari studi defin pragmat secur ondemand base system abl gather inform risk breach confidenti relay medic profession ask inform via specif search enginemethod scatter data often heterogen make task gather inform hard two method can compar tri solv problem standard central inform everi patient singl medic record system tri use data find way obtain complet accur inform given failur first approach due lack standard privaci secur problem exampl propos altern reli current state affair ondemand system use specif search engin abl retriev inform differ medic record singl patientresult describ function medic record search engin mrse abl retriev avail inform regard patient hospit differ hospit provid inform health profession upon request mrses use pseudonym patient ident thus never access patient ident howev though system easi implement bypass mani difficulti associ central architectur health profession valid inform ie read inform creat synthesi possibl reject extra data drawback thus propos various feasibl improv base implement sever tool ondemand base systemconclus system gather current avail inform regard patient request healthcar profession great interest lowcost pragmat altern central medic record develop quick easili also design includ extra featur thus consid health author

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