Mobile health: Difference between revisions
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{{CMG}} {{AE}} [[User:Peters|Stephanie Peters]]; [[User:Foster|Sierra Foster]]; [[User:Mkhurana1|Monica Khurana]]; [[User:RMiller|Ross Miller]]; Matt Greenstein; Lauren Schuessler | |||
==Overview== | |||
'''Mobile health''', also called '''mHealth''', is a component of eHealth. “To date, no standardized definition of mHealth has been established...the [http://www.who.int/goe/en/ Global Observatory for eHealth (GOe)] defined mHealth or mobile health as medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices. mHealth involves the use and capitalization on a mobile phone’s core utility of voice and short messaging service (SMS) as well as more complex functionalities and applications including general packet radio service (GPRS), third and fourth generation mobile telecommunications (3G and 4G systems), global positioning system (GPS), and Bluetooth technology”<ref>World Health Organization (2011). [http://www.who.int/goe/publications/goe_mhealth_web.pdf mHealth New horizons for health through mobile technologies] {{ISBN|9789241564250}}</ref>. | |||
In an age where technology plays a significant role in all aspects of our lives, it seems reasonable to believe that mHealth will become an integral part of our healthcare. | |||
One [[observational study]] showed that the vast majority of the patients have a smartphone and have an interest in utilizing it to improve their health, even in a population with lower socioeconomic status where access may be of concern<ref name="pmid27095507">{{cite journal| author=Ramirez V, Johnson E, Gonzalez C, Ramirez V, Rubino B, Rossetti G| title=Assessing the Use of Mobile Health Technology by Patients: An Observational Study in Primary Care Clinics. | journal=JMIR Mhealth Uhealth | year= 2016 | volume= 4 | issue= 2 | pages= e41 | pmid=27095507 | doi=10.2196/mhealth.4928 | pmc=4858592 | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=27095507 }} </ref>. | |||
==Effectiveness== | ==Effectiveness== | ||
Mobile phone text messaging approximately doubles the odds of medication adherence. A [[meta analysis]] was conducted of 16 [[randomized control trial]]s to assess the effect of mobile phone text messaging on medication adherence in the setting chronic disease. Study concluded that this intervention improved adherence rates from 50% to 67.8% or an absolute increase of 17.8% | mHealth may increase [[patient engagement]]. One prospective [[randomized control trial]] found that the participants utilizing a mobile application to track their chronic disease had improvement in health self-management as compared to the the control participants who were not utilizing a mobile application<ref name="pmid26788432">{{cite journal| author=Bloss CS, Wineinger NE, Peters M, Boeldt DL, Ariniello L, Kim JY et al.| title=A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors. | journal=PeerJ | year= 2016 | volume= 4 | issue= | pages= e1554 | pmid=26788432 | doi=10.7717/peerj.1554 | pmc=4715435 | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=26788432 }} </ref>. | ||
Being that mHealth is a novel concept, there are a limited number of randomized control trials and systematic reviews evaluating the effectiveness of mobile interventions on disease management. At this point in time the exact role mHealth will play in patient care remains unclear. Some studies focused on mHealth interventions show promising results with improved health outcomes in chronic disease management, while others have found no difference in health outcomes when a mHealth intervention is used in comparison to current standard health practices. | |||
There is not yet strong evidence that mobile phone messaging interventions improve health outcomes, but they may improve a patient’s ability to self-manage their disease. A Cochrane Review of four studies that utilized mobile phone messaging interventions in the management of chronic diseases ([[diabetes mellitus]], [[hypertension]], and [[asthma]]) demonstrated that there was no significant difference in glycemic control, blood pressure control or [[FVC]]/[[FEV1]] values between intervention and control groups. The reviewed study that focused on asthma did however find that there was a significant difference in the pooled asthma symptom score, favoring the text messaging intervention over usual care. All four reviewed studies showed evidence of either improved disease self-monitoring or better medication adherence with the utilization of mobile phone messaging interventions<ref name="pmid23235644">{{cite journal| author=de Jongh T, Gurol-Urganci I, Vodopivec-Jamsek V, Car J, Atun R| title=Mobile phone messaging for facilitating self-management of long-term illnesses. | journal=Cochrane Database Syst Rev | year= 2012 | volume= 12 | issue= | pages= CD007459 | pmid=23235644 | doi=10.1002/14651858.CD007459.pub2 | pmc= | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=23235644 }} </ref>. | |||
Mobile phone text messaging approximately doubles the odds of medication adherence. A [[meta analysis]] was conducted of 16 [[randomized control trial]]s to assess the effect of mobile phone text messaging on medication adherence in the setting chronic disease. Study concluded that this intervention improved adherence rates from 50% to 67.8% or an absolute increase of 17.8%<ref name="pmid26831740">{{cite journal| author=Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A et al.| title=Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis. | journal=JAMA Intern Med | year= 2016 | volume= | issue= | pages= | pmid=26831740 | doi=10.1001/jamainternmed.2015.7667 | pmc= | url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=26831740 }} </ref>. | |||
A smartphone app may improve adherence and total weight loss after 6 months when compared to a website monitoring group | A smartphone app may improve adherence and total weight loss after 6 months when compared to a website monitoring group<ref name="pmid3636323">{{cite journal| author=Rahal JJ, Simberkoff MS| title=Comparative bactericidal activity of penicillin-netilmicin and penicillin-gentamicin against enterococci. | journal=J Antimicrob Chemother | year= 1986 | volume= 17 | issue= 5 | pages= 585-91 | pmid=3636323 | doi= | pmc= | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=3636323 }} </ref>. In a pilot study done in the UK, a sample of 128 overweight individuals were randomized to receive a weight management intervention delivered by smartphone app, website, or paper diary. The smartphone app intervention, My Meal Mate (MMM), was developed by the research team using an evidence-based behavioral approach. <ref name="pmid3636323"/> | ||
* Trial retention was 93% in the smartphone group, 55% in the website group, and 53% in the paper diary group at 6 months. | * Trial retention was 93% in the smartphone group, 55% in the website group, and 53% in the paper diary group at 6 months. | ||
* Adherence means were 92 days in the smartphone group, 35 days in the website group, and 29 days in the paper diary group. | * Adherence means were 92 days in the smartphone group, 35 days in the website group, and 29 days in the paper diary group. | ||
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Regarding care of [[diabetes mellitus]]: | Regarding care of [[diabetes mellitus]]: | ||
A meta-analysis and more recent trial have found that mobile health technology has a greater reduction in [[hemoglobin A1c]] | A meta-analysis and more recent trial have found that mobile health technology has a greater reduction in [[hemoglobin A1c]]<ref name="pmid27926892">{{cite journal| author=Hou C, Carter B, Hewitt J, Francisa T, Mayor S| title=Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials. | journal=Diabetes Care | year= 2016 | volume= 39 | issue= 11 | pages= 2089-2095 | pmid=27926892 | doi=10.2337/dc16-0346 | pmc= | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=27926892 }} </ref><ref name="pmid26645932">{{cite journal| author=Hsu WC, Lau KH, Huang R, Ghiloni S, Le H, Gilroy S et al.| title=Utilization of a Cloud-Based Diabetes Management Program for Insulin Initiation and Titration Enables Collaborative Decision Making Between Healthcare Providers and Patients. | journal=Diabetes Technol Ther | year= 2016 | volume= 18 | issue= 2 | pages= 59-67 | pmid=26645932 | doi=10.1089/dia.2015.0160 | pmc= | url=http://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=26645932 }} </ref>. | ||
Regarding [[coronary artery disease]], a [[randomized controlled trial]] found reduction of risk factors associated with using mobile health | Regarding [[coronary artery disease]], a [[randomized controlled trial]] found reduction of risk factors associated with using mobile health<ref name="pmid26393848">{{cite journal| author=Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML et al.| title=Effect of Lifestyle-Focused Text Messaging on Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial. | journal=JAMA | year= 2015 | volume= 314 | issue= 12 | pages= 1255-63 | pmid=26393848 | doi=10.1001/jama.2015.10945 | pmc= | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=26393848 }} [https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=26784497 Review in: Ann Intern Med. 2016 Jan 19;164(2):JC7] </ref>. | ||
Regarding [[physical activity]], text messaging may give short term improvement | Regarding [[physical activity]], text messaging may give short term improvement<ref>{{Cite journal| doi = 10.2196/jmir.6439| issn = 1438-8871| volume = 18| issue = 11| pages = –307| last1 = Agboola| first1 = Stephen| last2 = Jethwani| first2 = Kamal| last3 = Lopez| first3 = Lenny| last4 = Searl| first4 = Meghan| last5 = O’Keefe| first5 = Sandra| last6 = Kvedar| first6 = Joseph| title = Text to Move: A Randomized Controlled Trial of a Text-Messaging Program to Improve Physical Activity Behaviors in Patients With Type 2 Diabetes Mellitus| journal = Journal of Medical Internet Research| accessdate = 2016-11-18| date = 2016-11-18| url = http://www.jmir.org/2016/11/e307/}}</ref>. | ||
Regarding [[weight loss]], a [[randomized control trial]] of 212 patients with a [[body mass index]] >25 kg/m^2 aimed at evaluating the efficacy of the application MyFitnessPal for weight loss in the primary care setting demonstrated that the application did not result in increased weight loss compared to usual care. Although it must be noted that most participants didn’t use the application after the first month of the study; 94 participants logged on in the first month compared to only 34 in the sixth month<ref name="pmid25402403">{{cite journal| author=Laing BY, Mangione CM, Tseng CH, Leng M, Vaisberg E, Mahida M et al.| title=Effectiveness of a smartphone application for weight loss compared with usual care in overweight primary care patients: a randomized, controlled trial. | journal=Ann Intern Med | year= 2014 | volume= 161 | issue= 10 Suppl | pages= S5-12 | pmid=25402403 | doi=10.7326/M13-3005 | pmc=4422872 | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=25402403 }} </ref>. | |||
==References== | ==References== | ||
{{Reflist|2}} | {{Reflist|2}} | ||
Revision as of 15:27, 19 October 2017
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Editor-In-Chief: C. Michael Gibson, M.S., M.D. [1] Associate Editor(s)-in-Chief: Stephanie Peters; Sierra Foster; Monica Khurana; Ross Miller; Matt Greenstein; Lauren Schuessler
Overview
Mobile health, also called mHealth, is a component of eHealth. “To date, no standardized definition of mHealth has been established...the Global Observatory for eHealth (GOe) defined mHealth or mobile health as medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants (PDAs), and other wireless devices. mHealth involves the use and capitalization on a mobile phone’s core utility of voice and short messaging service (SMS) as well as more complex functionalities and applications including general packet radio service (GPRS), third and fourth generation mobile telecommunications (3G and 4G systems), global positioning system (GPS), and Bluetooth technology”[1].
In an age where technology plays a significant role in all aspects of our lives, it seems reasonable to believe that mHealth will become an integral part of our healthcare.
One observational study showed that the vast majority of the patients have a smartphone and have an interest in utilizing it to improve their health, even in a population with lower socioeconomic status where access may be of concern[2].
Effectiveness
mHealth may increase patient engagement. One prospective randomized control trial found that the participants utilizing a mobile application to track their chronic disease had improvement in health self-management as compared to the the control participants who were not utilizing a mobile application[3].
Being that mHealth is a novel concept, there are a limited number of randomized control trials and systematic reviews evaluating the effectiveness of mobile interventions on disease management. At this point in time the exact role mHealth will play in patient care remains unclear. Some studies focused on mHealth interventions show promising results with improved health outcomes in chronic disease management, while others have found no difference in health outcomes when a mHealth intervention is used in comparison to current standard health practices.
There is not yet strong evidence that mobile phone messaging interventions improve health outcomes, but they may improve a patient’s ability to self-manage their disease. A Cochrane Review of four studies that utilized mobile phone messaging interventions in the management of chronic diseases (diabetes mellitus, hypertension, and asthma) demonstrated that there was no significant difference in glycemic control, blood pressure control or FVC/FEV1 values between intervention and control groups. The reviewed study that focused on asthma did however find that there was a significant difference in the pooled asthma symptom score, favoring the text messaging intervention over usual care. All four reviewed studies showed evidence of either improved disease self-monitoring or better medication adherence with the utilization of mobile phone messaging interventions[4].
Mobile phone text messaging approximately doubles the odds of medication adherence. A meta analysis was conducted of 16 randomized control trials to assess the effect of mobile phone text messaging on medication adherence in the setting chronic disease. Study concluded that this intervention improved adherence rates from 50% to 67.8% or an absolute increase of 17.8%[5].
A smartphone app may improve adherence and total weight loss after 6 months when compared to a website monitoring group[6]. In a pilot study done in the UK, a sample of 128 overweight individuals were randomized to receive a weight management intervention delivered by smartphone app, website, or paper diary. The smartphone app intervention, My Meal Mate (MMM), was developed by the research team using an evidence-based behavioral approach. [6]
- Trial retention was 93% in the smartphone group, 55% in the website group, and 53% in the paper diary group at 6 months.
- Adherence means were 92 days in the smartphone group, 35 days in the website group, and 29 days in the paper diary group.
- Mean weight loss and BMI reduction, respectively, at 6 months were -4.6 kg and -1.6 kg/m2 in the smartphone group, -2.9 kg and -1.0 kg/m2 in the paper diary group, and -1.3 kg and -0.5 kg/m2 in the website group.
Regarding care of diabetes mellitus: A meta-analysis and more recent trial have found that mobile health technology has a greater reduction in hemoglobin A1c[7][8].
Regarding coronary artery disease, a randomized controlled trial found reduction of risk factors associated with using mobile health[9].
Regarding physical activity, text messaging may give short term improvement[10].
Regarding weight loss, a randomized control trial of 212 patients with a body mass index >25 kg/m^2 aimed at evaluating the efficacy of the application MyFitnessPal for weight loss in the primary care setting demonstrated that the application did not result in increased weight loss compared to usual care. Although it must be noted that most participants didn’t use the application after the first month of the study; 94 participants logged on in the first month compared to only 34 in the sixth month[11].
References
- ↑ World Health Organization (2011). mHealth New horizons for health through mobile technologies ISBN 9789241564250
- ↑ Ramirez V, Johnson E, Gonzalez C, Ramirez V, Rubino B, Rossetti G (2016). "Assessing the Use of Mobile Health Technology by Patients: An Observational Study in Primary Care Clinics". JMIR Mhealth Uhealth. 4 (2): e41. doi:10.2196/mhealth.4928. PMC 4858592. PMID 27095507.
- ↑ Bloss CS, Wineinger NE, Peters M, Boeldt DL, Ariniello L, Kim JY; et al. (2016). "A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors". PeerJ. 4: e1554. doi:10.7717/peerj.1554. PMC 4715435. PMID 26788432.
- ↑ de Jongh T, Gurol-Urganci I, Vodopivec-Jamsek V, Car J, Atun R (2012). "Mobile phone messaging for facilitating self-management of long-term illnesses". Cochrane Database Syst Rev. 12: CD007459. doi:10.1002/14651858.CD007459.pub2. PMID 23235644.
- ↑ Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A; et al. (2016). "Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis". JAMA Intern Med. doi:10.1001/jamainternmed.2015.7667. PMID 26831740.
- ↑ 6.0 6.1 Rahal JJ, Simberkoff MS (1986). "Comparative bactericidal activity of penicillin-netilmicin and penicillin-gentamicin against enterococci". J Antimicrob Chemother. 17 (5): 585–91. PMID 3636323.
- ↑ Hou C, Carter B, Hewitt J, Francisa T, Mayor S (2016). "Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials". Diabetes Care. 39 (11): 2089–2095. doi:10.2337/dc16-0346. PMID 27926892.
- ↑ Hsu WC, Lau KH, Huang R, Ghiloni S, Le H, Gilroy S; et al. (2016). "Utilization of a Cloud-Based Diabetes Management Program for Insulin Initiation and Titration Enables Collaborative Decision Making Between Healthcare Providers and Patients". Diabetes Technol Ther. 18 (2): 59–67. doi:10.1089/dia.2015.0160. PMID 26645932.
- ↑ Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML; et al. (2015). "Effect of Lifestyle-Focused Text Messaging on Risk Factor Modification in Patients With Coronary Heart Disease: A Randomized Clinical Trial". JAMA. 314 (12): 1255–63. doi:10.1001/jama.2015.10945. PMID 26393848. Review in: Ann Intern Med. 2016 Jan 19;164(2):JC7
- ↑ Agboola, Stephen; Jethwani, Kamal; Lopez, Lenny; Searl, Meghan; O’Keefe, Sandra; Kvedar, Joseph (2016-11-18). "Text to Move: A Randomized Controlled Trial of a Text-Messaging Program to Improve Physical Activity Behaviors in Patients With Type 2 Diabetes Mellitus". Journal of Medical Internet Research. 18 (11): –307. doi:10.2196/jmir.6439. ISSN 1438-8871. Retrieved 2016-11-18.
- ↑ Laing BY, Mangione CM, Tseng CH, Leng M, Vaisberg E, Mahida M; et al. (2014). "Effectiveness of a smartphone application for weight loss compared with usual care in overweight primary care patients: a randomized, controlled trial". Ann Intern Med. 161 (10 Suppl): S5–12. doi:10.7326/M13-3005. PMC 4422872. PMID 25402403.