Perspect Health Inf Manag - Hospital characteristics related to the intention to apply for meaningful use incentive payments.

Tópicos

{ ehr(2073) health(1662) electron(1139) }
{ high(1669) rate(1365) level(1280) }
{ inform(2794) health(2639) internet(1427) }
{ cost(1906) reduc(1198) effect(832) }
{ use(2086) technolog(871) perceiv(783) }
{ drug(1928) target(777) effect(648) }
{ howev(809) still(633) remain(590) }
{ monitor(1329) mobil(1314) devic(1160) }
{ can(774) often(719) complex(702) }
{ general(901) number(790) one(736) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ sampl(1606) size(1419) use(1276) }
{ implement(1333) system(1263) develop(1122) }
{ problem(2511) optim(1539) algorithm(950) }
{ extract(1171) text(1153) clinic(932) }
{ visual(1396) interact(850) tool(830) }
{ research(1218) medic(880) student(794) }
{ data(2317) use(1299) case(1017) }
{ first(2504) two(1366) second(1323) }
{ cancer(2502) breast(956) screen(824) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ 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) }
{ sequenc(1873) structur(1644) protein(1328) }
{ 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) }
{ 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) }
{ learn(2355) train(1041) set(1003) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ 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) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ 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) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ state(1844) use(1261) util(961) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ 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) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 provides incentives for hospitals to fully adopt and use electronic health records (EHRs). We used data from the 2009 American Hospital Association (AHA) Annual Survey Information Technology Supplement and the Centers for Medicare and Medicaid Services (CMS) 2008 Hospital Cost Reports to examine how various hospital characteristics are associated with the intention to pursue meaningful use incentives. Overall, 86 percent of hospitals indicated an intent to pursue HITECH incentives. However, hospitals that already have an EHR system, are larger, and are located in urban areas are more likely to indicate an intention to pursue incentives. Despite a high interest in HITECH incentives, certain hospital characteristics, including current EHR use, increase the proclivity for some hospitals to pursue meaningful use. Given these differences, there is the potential for the HITECH Act to inadvertently increase the digital divide between hospitals with certain characteristics and their counterparts without those characteristics. Policy makers should consider ways to alleviate barriers, especially for nonusers of EHRs, to realize the maximum benefits of the HITECH Act.

Resumo Limpo

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