AMIA Annu Symp Proc - Syndromic surveillance in an ICD-10 world.

Tópicos

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{ extract(1171) text(1153) clinic(932) }
{ imag(1947) propos(1133) code(1026) }
{ concept(1167) ontolog(924) domain(897) }
{ ehr(2073) health(1662) electron(1139) }
{ system(1976) rule(880) can(841) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
{ import(1318) role(1303) understand(862) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ research(1218) medic(880) student(794) }
{ can(981) present(881) function(850) }
{ cancer(2502) breast(956) screen(824) }
{ result(1111) use(1088) new(759) }
{ inform(2794) health(2639) internet(1427) }
{ imag(1057) registr(996) error(939) }
{ featur(3375) classif(2383) classifi(1994) }
{ assess(1506) score(1403) qualiti(1306) }
{ clinic(1479) use(1117) guidelin(835) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ method(984) reconstruct(947) comput(926) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ state(1844) use(1261) util(961) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ patient(1821) servic(1111) care(1106) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ activ(1452) weight(1219) physic(1104) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ sequenc(1873) structur(1644) protein(1328) }
{ 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) }
{ 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) }
{ chang(1828) time(1643) increas(1301) }
{ method(1557) propos(1049) approach(1037) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ research(1085) discuss(1038) issu(1018) }
{ model(2341) predict(2261) use(1141) }
{ 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) }
{ spatial(1525) area(1432) region(1030) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ 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) }
{ process(1125) use(805) approach(778) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The Centers for Disease Control and Prevention's BioSense program is an integrated national public health surveillance system that uses electronic medical record (EMR) data to provide situational awareness for all-hazard health-related events. Because the system leverages International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coded data from EMRs for syndromic surveillance, the upcoming Health and Human Services-mandated transition from ICD-9-CM to ICD-10-CM will have a significant impact. To translate across the two encoding systems, we developed a Mapping Reference Table (MRT) for the ICD-9/10 transition. We extracted ICD-9-CM codes binned to predefined syndromes and mapped each to its corresponding ICD-10-CM code(s). Then, we translated the output ICD-10-CM codes back to ICD-9-CM through a reverse translation validation process. Throughout the translation process, we examined outputs manually and incorporated annotated results into the MRT. The resulting MRT can be used to refine and update each existing syndromic surveillance definition in BioSense to be compatible with ICD-10-CM and consistently classify or bin any given emergency department visit into the correct syndrome regardless of coding system.

Resumo Limpo

center diseas control prevent biosens program integr nation public health surveil system use electron medic record emr data provid situat awar allhazard healthrel event system leverag intern classif diseas ninth revis clinic modif icdcm code data emr syndrom surveil upcom health human servicesmand transit icdcm icdcm will signific impact translat across two encod system develop map refer tabl mrt icd transit extract icdcm code bin predefin syndrom map correspond icdcm code translat output icdcm code back icdcm revers translat valid process throughout translat process examin output manual incorpor annot result mrt result mrt can use refin updat exist syndrom surveil definit biosens compat icdcm consist classifi bin given emerg depart visit correct syndrom regardless code system

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