Med Decis Making - Better medicine by default.

Tópicos

{ medic(1828) order(1363) alert(1069) }
{ decis(3086) make(1611) patient(1517) }
{ howev(809) still(633) remain(590) }
{ treatment(1704) effect(941) patient(846) }
{ high(1669) rate(1365) level(1280) }
{ method(984) reconstruct(947) comput(926) }
{ take(945) account(800) differ(722) }
{ design(1359) user(1324) use(1319) }
{ health(3367) inform(1360) care(1135) }
{ use(2086) technolog(871) perceiv(783) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ survey(1388) particip(1329) question(1065) }
{ imag(1057) registr(996) error(939) }
{ method(1219) similar(1157) match(930) }
{ assess(1506) score(1403) qualiti(1306) }
{ general(901) number(790) one(736) }
{ visual(1396) interact(850) tool(830) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ group(2977) signific(1463) compar(1072) }
{ can(774) often(719) complex(702) }
{ measur(2081) correl(1212) valu(896) }
{ network(2748) neural(1063) input(814) }
{ studi(2440) review(1878) systemat(933) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ data(3963) clinic(1234) research(1004) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ activ(1138) subject(705) human(624) }
{ patient(1821) servic(1111) care(1106) }
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{ sequenc(1873) structur(1644) protein(1328) }
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{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ motion(1329) object(1292) video(1091) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ 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) }
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{ care(1570) inform(1187) nurs(1089) }
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{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ 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) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ signal(2180) analysi(812) frequenc(800) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ 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(1969) cluster(1462) data(1082) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: American health care is transitioning to electronic physician ordering. These computerized systems are unique because they allow custom order interfaces. Although these systems provide great benefits, there are also potential pitfalls, as the behavioral sciences have shown that the very format of electronic interfaces can influence decision making. The current research specifically examines how defaults in electronic order templates affect physicians' treatment decisions and medical errors.METHODS: Forty-five medical residents completed order sets for 3 medical case studies. Participants were randomly assigned to receive order sets with either "opt-in" defaults (options visible but unselected) or "opt-out" defaults (options visible and preselected).RESULTS: compare error rates between conditions and examine the type and severity of errors most often made with opt-in versus opt-out defaults. Results. Opt-out defaults resulted in a greater number of items ordered and specifically increased commission errors (overordering) compared with opt-in defaults. However, while opt-in defaults resulted in fewer orders, they also increased omission errors. When the severity of the errors is taken into account, the default effects seem limited to less severe errors.CONCLUSION: The defaults used in electronic order sets influence medical treatment decisions when the consequences to a patient's health are low. This pattern suggests that physicians cognitively override incorrect default choices but only to a point, and it implies tradeoffs that maximize accuracy and minimize cognitive effort. Results indicate that defaults for low-impact items on electronic templates warrant careful attention because physicians are unlikely to override them.

Resumo Limpo

ckground american health care transit electron physician order computer system uniqu allow custom order interfac although system provid great benefit also potenti pitfal behavior scienc shown format electron interfac can influenc decis make current research specif examin default electron order templat affect physician treatment decis medic errorsmethod fortyf medic resid complet order set medic case studi particip random assign receiv order set either optin default option visibl unselect optout default option visibl preselectedresult compar error rate condit examin type sever error often made optin versus optout default result optout default result greater number item order specif increas commiss error overord compar optin default howev optin default result fewer order also increas omiss error sever error taken account default effect seem limit less sever errorsconclus default use electron order set influenc medic treatment decis consequ patient health low pattern suggest physician cognit overrid incorrect default choic point impli tradeoff maxim accuraci minim cognit effort result indic default lowimpact item electron templat warrant care attent physician unlik overrid

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