AMIA Annu Symp Proc - Place matters: the problems and possibilities of spatial data in electronic health records.

Tópicos

{ health(1844) social(1437) communiti(874) }
{ data(3008) multipl(1320) sourc(1022) }
{ spatial(1525) area(1432) region(1030) }
{ patient(2315) diseas(1263) diabet(1191) }
{ research(1085) discuss(1038) issu(1018) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ take(945) account(800) differ(722) }
{ can(981) present(881) function(850) }
{ decis(3086) make(1611) patient(1517) }
{ system(1976) rule(880) can(841) }
{ care(1570) inform(1187) nurs(1089) }
{ search(2224) databas(1162) retriev(909) }
{ data(3963) clinic(1234) research(1004) }
{ ehr(2073) health(1662) electron(1139) }
{ analysi(2126) use(1163) compon(1037) }
{ implement(1333) system(1263) develop(1122) }
{ imag(1947) propos(1133) code(1026) }
{ framework(1458) process(801) describ(734) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ extract(1171) text(1153) clinic(932) }
{ control(1307) perform(991) simul(935) }
{ howev(809) still(633) remain(590) }
{ model(3480) simul(1196) paramet(876) }
{ intervent(3218) particip(2042) group(1664) }
{ use(2086) technolog(871) perceiv(783) }
{ activ(1452) weight(1219) physic(1104) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ 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) }
{ 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) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ learn(2355) train(1041) set(1003) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ 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) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ 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) }
{ monitor(1329) mobil(1314) devic(1160) }
{ 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) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ 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) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ 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

Research has shown that "place matters" in health and illness. Climate, pollution and crime are examples of geographically specific social and environmental factors that can substantially impact health. However, health care decision-making and practice do not currently include spatial data on specific patients. Opportunities to incorporate clinically relevant data from the environment into health care practice are numerous, and the implementation issues are virtually unexplored. We use a qualitative study from a natural disaster, the Middle Tennessee Flood of 2010, to examine the possibilities presented by community-sourced spatial data. In our case, linking EHR data with data from rasterized photos of inundated areas could have enabled providers to identify at-risk populations of patients after the flood and conduct supportive outreach for patients with chronic illness. We explore the potential benefits for patients, policy issues and implications for biomedical informatics of expanding the health record to incorporate or link to community-sourced data.

Resumo Limpo

research shown place matter health ill climat pollut crime exampl geograph specif social environment factor can substanti impact health howev health care decisionmak practic current includ spatial data specif patient opportun incorpor clinic relev data environ health care practic numer implement issu virtual unexplor use qualit studi natur disast middl tennesse flood examin possibl present communitysourc spatial data case link ehr data data raster photo inund area enabl provid identifi atrisk popul patient flood conduct support outreach patient chronic ill explor potenti benefit patient polici issu implic biomed informat expand health record incorpor link communitysourc data

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