J. Med. Internet Res. - Issues in mHealth: findings from key informant interviews.

Tópicos

{ research(1085) discuss(1038) issu(1018) }
{ state(1844) use(1261) util(961) }
{ clinic(1479) use(1117) guidelin(835) }
{ health(3367) inform(1360) care(1135) }
{ care(1570) inform(1187) nurs(1089) }
{ decis(3086) make(1611) patient(1517) }
{ spatial(1525) area(1432) region(1030) }
{ cost(1906) reduc(1198) effect(832) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ system(1050) medic(1026) inform(1018) }
{ blood(1257) pressur(1144) flow(957) }
{ drug(1928) target(777) effect(648) }
{ method(2212) result(1239) propos(1039) }
{ control(1307) perform(991) simul(935) }
{ monitor(1329) mobil(1314) devic(1160) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ data(1737) use(1416) pattern(1282) }
{ take(945) account(800) differ(722) }
{ chang(1828) time(1643) increas(1301) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ data(3963) clinic(1234) research(1004) }
{ studi(1119) effect(1106) posit(819) }
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{ gene(2352) biolog(1181) express(1162) }
{ intervent(3218) particip(2042) group(1664) }
{ use(2086) technolog(871) perceiv(783) }
{ high(1669) rate(1365) level(1280) }
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{ implement(1333) system(1263) develop(1122) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
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{ sequenc(1873) structur(1644) protein(1328) }
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{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
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{ design(1359) user(1324) use(1319) }
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{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
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{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ 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) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ data(3008) multipl(1320) sourc(1022) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ 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) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: mHealth is enjoying considerable interest and private investment in the United States. A small but growing body of evidence indicates some promise in supporting healthy behavior change and self-management of long-term conditions. The unique benefits mobile phones bring to health initiatives, such as direct access to health information regardless of time or location, may create specific issues for the implementation of such initiatives. Other issues may be shared with general health information technology developments.OBJECTIVE: To determine the important issues facing the implementation of mHealth from the perspective of those within the US health system and those working in mHealth in the United States.METHODS: Semistructured interviews were conducted with 27 key informants from across the health and mHealth sectors in the United States. Interviewees were approached directly following an environmental scan of mHealth in the United States or recommendation by those working in mHealth.RESULTS: The most common issues were privacy and data security, funding, a lack of good examples of the efficacy and cost effectiveness of mHealth in practice, and the need for more high-quality research. The issues are outlined and categorized according to the environment within which they predominantly occur: policy and regulatory environments; the wireless industry; the health system; existing mHealth practice; and research.CONCLUSIONS: Many of these issues could be addressed by making the most of the current US health reform environment, developing a strategic and coordinated approach, and seeking to improve mHealth practice.

Resumo Limpo

ckground mhealth enjoy consider interest privat invest unit state small grow bodi evid indic promis support healthi behavior chang selfmanag longterm condit uniqu benefit mobil phone bring health initi direct access health inform regardless time locat may creat specif issu implement initi issu may share general health inform technolog developmentsobject determin import issu face implement mhealth perspect within us health system work mhealth unit statesmethod semistructur interview conduct key inform across health mhealth sector unit state interviewe approach direct follow environment scan mhealth unit state recommend work mhealthresult common issu privaci data secur fund lack good exampl efficaci cost effect mhealth practic need highqual research issu outlin categor accord environ within predomin occur polici regulatori environ wireless industri health system exist mhealth practic researchconclus mani issu address make current us health reform environ develop strateg coordin approach seek improv mhealth practic

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