Comput. Biol. Med. - Clinicians' evaluation of computer-assisted medication summarization of electronic medical records.

Tópicos

{ record(1888) medic(1808) patient(1693) }
{ studi(2440) review(1878) systemat(933) }
{ medic(1828) order(1363) alert(1069) }
{ method(2212) result(1239) propos(1039) }
{ error(1145) method(1030) estim(1020) }
{ perform(999) metric(946) measur(919) }
{ concept(1167) ontolog(924) domain(897) }
{ care(1570) inform(1187) nurs(1089) }
{ design(1359) user(1324) use(1319) }
{ analysi(2126) use(1163) compon(1037) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ method(1557) propos(1049) approach(1037) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ research(1085) discuss(1038) issu(1018) }
{ health(3367) inform(1360) care(1135) }
{ cost(1906) reduc(1198) effect(832) }
{ intervent(3218) particip(2042) group(1664) }
{ result(1111) use(1088) new(759) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
{ assess(1506) score(1403) qualiti(1306) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
{ spatial(1525) area(1432) region(1030) }
{ ehr(2073) health(1662) electron(1139) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ activ(1138) subject(705) human(624) }
{ can(981) present(881) function(850) }
{ process(1125) use(805) approach(778) }
{ model(3404) distribut(989) bayesian(671) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
{ sequenc(1873) structur(1644) protein(1328) }
{ 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) }
{ treatment(1704) effect(941) patient(846) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ risk(3053) factor(974) diseas(938) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ 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

Each year thousands of patients die of avoidable medication errors. When a patient is admitted to, transferred within, or discharged from a clinical facility, clinicians should review previous medication orders, current orders and future plans for care, and reconcile differences if there are any. If medication reconciliation is not accurate and systematic, medication errors such as omissions, duplications, dosing errors, or drug interactions may occur and cause harm. Computer-assisted medication applications showed promise as an intervention to reduce medication summarization inaccuracies and thus avoidable medication errors. In this study, a computer-assisted medication summarization application, designed to abstract and represent multi-source time-oriented medication data, was introduced to assist clinicians with their medication reconciliation processes. An evaluation study was carried out to assess clinical usefulness and analyze potential impact of such application. Both quantitative and qualitative methods were applied to measure clinicians' performance efficiency and inaccuracy in medication summarization process with and without the intervention of computer-assisted medication application. Clinicians' feedback indicated the feasibility of integrating such a medication summarization tool into clinical practice workflow as a complementary addition to existing electronic health record systems. The result of the study showed potential to improve efficiency and reduce inaccuracy in clinician performance of medication summarization, which could in turn improve care efficiency, quality of care, and patient safety.

Resumo Limpo

year thousand patient die avoid medic error patient admit transfer within discharg clinic facil clinician review previous medic order current order futur plan care reconcil differ medic reconcili accur systemat medic error omiss duplic dose error drug interact may occur caus harm computerassist medic applic show promis intervent reduc medic summar inaccuraci thus avoid medic error studi computerassist medic summar applic design abstract repres multisourc timeori medic data introduc assist clinician medic reconcili process evalu studi carri assess clinic use analyz potenti impact applic quantit qualit method appli measur clinician perform effici inaccuraci medic summar process without intervent computerassist medic applic clinician feedback indic feasibl integr medic summar tool clinic practic workflow complementari addit exist electron health record system result studi show potenti improv effici reduc inaccuraci clinician perform medic summar turn improv care effici qualiti care patient safeti

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