J Am Med Inform Assoc - Benchmarking health IT among OECD countries: better data for better policy.

Tópicos

{ health(3367) inform(1360) care(1135) }
{ concept(1167) ontolog(924) domain(897) }
{ perform(999) metric(946) measur(919) }
{ record(1888) medic(1808) patient(1693) }
{ perform(1367) use(1326) method(1137) }
{ inform(2794) health(2639) internet(1427) }
{ implement(1333) system(1263) develop(1122) }
{ care(1570) inform(1187) nurs(1089) }
{ data(3008) multipl(1320) sourc(1022) }
{ learn(2355) train(1041) set(1003) }
{ method(1557) propos(1049) approach(1037) }
{ search(2224) databas(1162) retriev(909) }
{ case(1353) use(1143) diagnosi(1136) }
{ studi(1410) differ(1259) use(1210) }
{ ehr(2073) health(1662) electron(1139) }
{ process(1125) use(805) approach(778) }
{ can(774) often(719) complex(702) }
{ sequenc(1873) structur(1644) protein(1328) }
{ treatment(1704) effect(941) patient(846) }
{ howev(809) still(633) remain(590) }
{ import(1318) role(1303) understand(862) }
{ cost(1906) reduc(1198) effect(832) }
{ high(1669) rate(1365) level(1280) }
{ studi(2440) review(1878) systemat(933) }
{ chang(1828) time(1643) increas(1301) }
{ data(1714) softwar(1251) tool(1186) }
{ monitor(1329) mobil(1314) devic(1160) }
{ medic(1828) order(1363) alert(1069) }
{ first(2504) two(1366) second(1323) }
{ health(1844) social(1437) communiti(874) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ method(2212) result(1239) propos(1039) }
{ model(3404) distribut(989) bayesian(671) }
{ 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(2830) propos(1344) filter(1198) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ 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) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ model(3480) simul(1196) paramet(876) }
{ state(1844) use(1261) util(961) }
{ 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) }
{ signal(2180) analysi(812) frequenc(800) }
{ 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) }
{ 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) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ method(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

JECTIVE: To develop benchmark measures of health information and communication technology (ICT) use to facilitate cross-country comparisons and learning.MATERIALS AND METHODS: The effort is led by the Organisation for Economic Co-operation and Development (OECD). Approaches to definition and measurement within four ICT domains were compared across seven OECD countries in order to identify functionalities in each domain. These informed a set of functionality-based benchmark measures, which were refined in collaboration with representatives from more than 20 OECD and non-OECD countries. We report on progress to date and remaining work to enable countries to begin to collect benchmark data.RESULTS: The four benchmarking domains include provider-centric electronic record, patient-centric electronic record, health information exchange, and tele-health. There was broad agreement on functionalities in the provider-centric electronic record domain (eg, entry of core patient data, decision support), and less agreement in the other three domains in which country representatives worked to select benchmark functionalities.DISCUSSION: Many countries are working to implement ICTs to improve healthcare system performance. Although many countries are looking to others as potential models, the lack of consistent terminology and approach has made cross-national comparisons and learning difficult.CONCLUSIONS: As countries develop and implement strategies to increase the use of ICTs to promote health goals, there is a historic opportunity to enable cross-country learning. To facilitate this learning and reduce the chances that individual countries flounder, a common understanding of health ICT adoption and use is needed. The OECD-led benchmarking process is a crucial step towards achieving this.

Resumo Limpo

jectiv develop benchmark measur health inform communic technolog ict use facilit crosscountri comparison learningmateri method effort led organis econom cooper develop oecd approach definit measur within four ict domain compar across seven oecd countri order identifi function domain inform set functionalitybas benchmark measur refin collabor repres oecd nonoecd countri report progress date remain work enabl countri begin collect benchmark dataresult four benchmark domain includ providercentr electron record patientcentr electron record health inform exchang telehealth broad agreement function providercentr electron record domain eg entri core patient data decis support less agreement three domain countri repres work select benchmark functionalitiesdiscuss mani countri work implement ict improv healthcar system perform although mani countri look other potenti model lack consist terminolog approach made crossnat comparison learn difficultconclus countri develop implement strategi increas use ict promot health goal histor opportun enabl crosscountri learn facilit learn reduc chanc individu countri flounder common understand health ict adopt use need oecdl benchmark process crucial step toward achiev

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