Telemed J E Health - e-Health policy and deployment activities in Europe.

Tópicos

{ health(3367) inform(1360) care(1135) }
{ ehr(2073) health(1662) electron(1139) }
{ model(3404) distribut(989) bayesian(671) }
{ care(1570) inform(1187) nurs(1089) }
{ blood(1257) pressur(1144) flow(957) }
{ implement(1333) system(1263) develop(1122) }
{ use(2086) technolog(871) perceiv(783) }
{ chang(1828) time(1643) increas(1301) }
{ algorithm(1844) comput(1787) effici(935) }
{ health(1844) social(1437) communiti(874) }
{ studi(1119) effect(1106) posit(819) }
{ state(1844) use(1261) util(961) }
{ model(2656) set(1616) predict(1553) }
{ learn(2355) train(1041) set(1003) }
{ clinic(1479) use(1117) guidelin(835) }
{ risk(3053) factor(974) diseas(938) }
{ model(2341) predict(2261) use(1141) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ method(2212) result(1239) propos(1039) }
{ can(774) often(719) complex(702) }
{ inform(2794) health(2639) internet(1427) }
{ sequenc(1873) structur(1644) protein(1328) }
{ imag(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ assess(1506) score(1403) qualiti(1306) }
{ extract(1171) text(1153) clinic(932) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ model(3480) simul(1196) paramet(876) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ first(2504) two(1366) second(1323) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ 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) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ concept(1167) ontolog(924) domain(897) }
{ 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) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ perform(1367) use(1326) method(1137) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ monitor(1329) mobil(1314) devic(1160) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ 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) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ 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

JECTIVE: e-Health has become a major topic in the European Union (EU) Commission due to the assumption that it improves the quality and effectiveness of health services and, at the same time, promotes information and communications technologies in this emerging high-technology area. In 2004, the EU Commission adopted the first e-health Action Plan, which sets targets for member states in the adoption of telematics applications. This article aims at explaining the variance in the application of e-health tools across 24 EU member states.METHODS: The study includes the implementation of 12 e-health policies as of early 2007. Each policy was coded on a binary scale distinguishing between implementation and nonimplementation. The summing up of all binary values created an additive index. We used several multiple linear regression models to estimate the impact of socio-economic, political and healthcare related variables on the scope of implementation.RESULTS: The scope of implementation mostly depends on political factors, whereas economic and health-related variables scarcely account for cross-country variance. Only the scope and importance of the domestic information and communication technology market have a significant effect on the scope of implementation. In contrast, political variables constitute most of the variance in the implementation scope. The strength of left parties in government has a significant effect: an increase of left parties in government increases the total amount of e-health measures implemented.CONCLUSION: Governments that included e-health applications in policy documents rather early have adopted more telematics applications.

Resumo Limpo

jectiv ehealth becom major topic european union eu commiss due assumpt improv qualiti effect health servic time promot inform communic technolog emerg hightechnolog area eu commiss adopt first ehealth action plan set target member state adopt telemat applic articl aim explain varianc applic ehealth tool across eu member statesmethod studi includ implement ehealth polici earli polici code binari scale distinguish implement nonimplement sum binari valu creat addit index use sever multipl linear regress model estim impact socioeconom polit healthcar relat variabl scope implementationresult scope implement most depend polit factor wherea econom healthrel variabl scarc account crosscountri varianc scope import domest inform communic technolog market signific effect scope implement contrast polit variabl constitut varianc implement scope strength left parti govern signific effect increas left parti govern increas total amount ehealth measur implementedconclus govern includ ehealth applic polici document rather earli adopt telemat applic

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