Perspect Health Inf Manag - Factors influencing students to enroll in health information management programs.

Tópicos

{ research(1218) medic(880) student(794) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ inform(2794) health(2639) internet(1427) }
{ survey(1388) particip(1329) question(1065) }
{ implement(1333) system(1263) develop(1122) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ design(1359) user(1324) use(1319) }
{ use(976) code(926) identifi(902) }
{ decis(3086) make(1611) patient(1517) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ search(2224) databas(1162) retriev(909) }
{ studi(1410) differ(1259) use(1210) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ perform(1367) use(1326) method(1137) }
{ model(3480) simul(1196) paramet(876) }
{ state(1844) use(1261) util(961) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ use(1733) differ(960) four(931) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ 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) }
{ 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) }
{ 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) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ 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) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ 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) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ 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) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

This nonexperimental quantitative descriptive-correlative research study was performed to describe the sources with the greatest influence on the participants' decision to enroll in a postsecondary educational program with the intent of working toward a career in health information management. Participants were asked, "Which sources have the greatest influence on an individual's decision to enroll in a postsecondary educational program with the intent of working toward a career in health information management (HIM)?" The study population was composed of matriculated students enrolled in accredited postsecondary schools offering an undergraduate medical billing and coding program at a brick-and-mortar campus in a two-county area of a South Atlantic state. The study found that an environmental source, specifically career job opportunities, was statistically significant as the greatest source of influence for these participants. This research aims to support efforts to provide the health information management subsector of the healthcare industry with a sufficient number of trained professionals to fill the identified need for trained HIM professionals, particularly medical coding specialists.

Resumo Limpo

nonexperiment quantit descriptivecorrel research studi perform describ sourc greatest influenc particip decis enrol postsecondari educ program intent work toward career health inform manag particip ask sourc greatest influenc individu decis enrol postsecondari educ program intent work toward career health inform manag studi popul compos matricul student enrol accredit postsecondari school offer undergradu medic bill code program brickandmortar campus twocounti area south atlant state studi found environment sourc specif career job opportun statist signific greatest sourc influenc particip research aim support effort provid health inform manag subsector healthcar industri suffici number train profession fill identifi need train profession particular medic code specialist

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