Abstract
Mobile health (mHealth) applications are rapidly becoming increasingly available to patients. These interventions utilize simple mobile messaging (SMS) and software applications on mobile devices for a variety of purposes. In the surgical population mHealth applications have shown promise in increasing medication and protocol adherence, monitoring patients after surgery, and helping modify behaviors associated with poor surgical outcomes. There is a paucity of spine specific applications at this time. Further development and study of efficacy of spine specific mHealth applications is needed.
Keywords: Mobile health (mHealth), telemedicine, spine surgery, texting, mobile messaging, patient communication
Introduction
Mobile phones are nearly ubiquitous in the United States. An estimated 96% of people in the U.S. own a cellular phone, and 81% own a smartphone (1). The number of cell phone owners has almost tripled from 35% in 2011. Orthopaedic patients have a similar cell phone utilization, with 77% of patients in a large urban academic center report owning a smartphone (2). Due to the rapid growth of smartphone use, mobile health (mHealth) applications have become increasingly common; over 165,000 mHealth applications are currently available for purchase (3-5).
The World Health Organization defines mobile health or “mHealth” broadly as “medical and public health practice supported by mobile devices” (6). There are a number of different types of mHealth applications; these include mobile access to clinical records, communication between healthcare team and patients, patient monitoring, telemedicine/remote delivery of care, wearable devices, emergency services, patient education/counseling, appointment reminders, outcomes/surveys collection, and provider decision support. According to the WHO, the most common types of mHealth initiates are health call centers, emergency toll-free telephone services, mobile tools to manage large scale emergencies and disasters, and mobile telemedicine. The great majority of these programs are in the pilot or informal stages.
While the number of mHealth applications is growing, and a few have been studied in surgical patients, there is a limited number of applications that are specific to spine surgery patients. The review below outlines mHealth applications that have been studied in a variety of setting, many of which can be applied to spine surgery patients but have not been formally studied in that population.
Behavioral modification
There has been a ground swell of research into the effectiveness of behavior modification with the use of mHealth applications. The majority of research to date has focused modification of secondary risk factors for cardiovascular disease. Studied risk factors include cigarette use, weight loss, diet modification, and medication compliance (7,8). The success of smoking cessation interventions has been shown to benefit from patient engagement (9-11). A number of mHealth applications have been developed aimed at cigarette smoking cessation (12-14). Heminger et al. reports on an automated text messaging system with messages centered around a user-set quit date. Messages are designed to promote engagement, track cigarette use, and administer timed surveys. The application was shown to be effective in generating user engagement and higher smoking cessation rates compared to controls (15).
Chow et al. performed a large randomized controlled trial (RCT) of patients with coronary heart disease randomized to an SMS cohort receiving 4 texts per week for 6 months versus standard care and found that the intervention group demonstrated increased physical activity, better improvement in low-density lipoprotein (LDL) cholesterol, blood pressure control, and BMI relative to controls (16). Other mHealth initiatives have also demonstrated similar effectiveness in improving physical activity in patients with cardiovascular disease (17-19). A review of mHealth and SMS applications for secondary prevention of cardiovascular disease found that higher frequency of text messages, personalized content, two-way communication, and use of multiple modalities were consistently associated with success of behavior modification (20).
Substance use disorders is another area where mHealth interventions have been studied in their effectiveness to modify behavior. Computer based and computer assisted cognitive behavioral therapy as well as community reinforcement approach (CRA) programs have been shown to lead to similar success in treatment of alcohol, marijuana and cocaine dependence compared to in-person therapist-based approaches (21-23). While the above studies do not directly apply to the spine surgery population, a number of conditions studied such as cigarette use, obesity, substance abuse have been linked to negative outcomes after spine surgery and represent areas where mHealth interventions could optimize outcomes (24,25). There remains a paucity of data on behavior modification and pre-operative patient optimization using mHealth tools in the spine population.
Protocol/medication adherence
mHealth applications have been studied in the surgical setting for impact on patient adherence to discharge instructions/postoperative protocols as well as improving adherence to medication regimens. Miloh et al. studied medication adherence in pediatric patients with orthotopic liver transplants and demonstrated improved adherence to antirejection medications with automated SMS based reminders sent to primary medication administrator relative to control (26). Improvement in adherence to postoperative protocols and discharge instructions has been shown in patients undergoing endoscopic retrograde cholangiopancreatography (ERCP) (27). Mobile application reminders for preoperative instruction have also shown promise in improving adherence to preoperative instructions leading to decreased day of surgery cancellations in a group of neurosurgery patients (28).
Park et al. studied the impact of post-discharge counseling via phone versus SMS on patient satisfaction, activities of daily living, and knee function in patients that have under gone a total knee arthroplasty (29). The authors found that phone and SMS counseling have the same effect on the studied outcomes. This suggests that automated SMS texts can play a role in optimizing resource utilization of orthopaedic clinic staff. Day et al. found that an automated SMS texts program increased patient satisfaction measures after total joint arthroplasty (TJA) (30). The positive impact of mHealth on medication adherence has been studied in surgical and non-surgical settings (31).
A Cochrane Collaboration review and meta-analysis found that mobile phone text messaging programs were effective in improving medication compliance amongst patients with HIV (32). The review also notes that the frequency of messaging appears to be important, with weekly text messages associated with lower rates of nonadherence compared to daily messages. Multiple other studies have suggested the benefit of mHealth intervention to medication adherence in this population (33-36). Foreman et al. found that SMS medication reminders improved adherence by about 10% in a non-randomized cohort study of patients with a broad range of chronic conditions beyond HIV (37).
Patient monitoring
The average length of stay for various spine surgeries has been gradually decreasing, and outpatient surgeries are becoming more common. As patients leave the hospital earlier, remote patient monitoring has been a growing area of interest to ensure patient safety and well-being after discharge. Debono et al. studied an application based patient monitoring system in patients that underwent ambulatory microdiscectomy (38). Patients were queried daily regarding their symptoms. The system triggered alerts to the neurosurgery treatment team based on symptom severity as well as nonresponse. Thirty-two percent of patients triggered an alarm, with 94% of alarms handled over the phone without the need for in person evaluation (38).
Remote wound monitoring with pictures sent to the surgical team via mobile devices has been studied in plastic surgery, orthopaedic surgery, and general surgery patients (39,40). There is a lack of studies that directly compare postoperative ER visits with versus without remote monitoring. A number of studies using surrogate measures suggest that postoperative ER and clinic visits may be decreased with mHealth interventions (39-41). Martínez-Ramos et al. found that 55% of patients undergoing remote wound monitoring after ambulatory surgery stated that they would have returned to the hospital to seek further care if not for the remote wound monitoring application (39).
Barriers to adoption
The field of mHealth is currently in its early stages. Prior to wide adoption, a number of challenges need to be overcome. The WHO in their analysis of the mHealth global market has highlighted poor evidence, uncertain regulation, and data safety concerns as key barriers to broad adoption (6). While there is a rapidly growing number of new applications being developed, very few have been studied in a rigorous manner. The majority of the research on mHealth interventions is comprised of low quality prospective, nonrandomized studies. Due to the increasing pressures on health systems to deliver efficient, high-quality care, cost-effectiveness of various mobile interventions will have to be studied in a scientifically sound manner.
The regulatory landscape of mHealth is another area of uncertainty. As mHealth applications become more sophisticated, many offer functionality that can aid in the diagnosis of health conditions. In the United States, the practice of medicine is regulated by state law, and the practice of medicine without a license is illegal. Mobile applications that provide medical tools to individuals that can aid in diagnosis fall under a poorly defined category. While providing health related information is not considered medical practice, providing medical advice does fall under the category of medical practice. The definition of medical advice varies from state to state and needs to be considered for future mHealth application development and regulation.
Currently mHealth applications are not regulated by the Food and Drug Administration (FDA). The FDA is responsible for the regulation of, among other things, medical devices (3). According to the FDA, a medical device is “any implement, machine, or apparatus intended for use in the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease” (42). As such, many mHealth applications would qualify as medical devices. The FDA issued a guidance document in 2015 that lists 28 categories of mobile medical applications that may quality as medical devices but the FDA elected to not actively regulate. Broadly, the 28 categories can be grouped into (I) General Health and Wellness applications; (II) illness prevention/management applications; (III) tracking, logging, and trending applications; and (IV) symptom-disease association applications (43).
Conclusions
A growing number of mHealth applications are available to the public. Orthopaedic and spine patients have demonstrated that the great majority own smartphones, have internet access, and are willing to use mobile applications for medical purposes. While the majority of early research has pertained to non-spine patients, early reports are promising in the utility of mHealth applications for behavior modification, patient monitoring, and protocol adherence. Development of spine specific applications and further study of the effectiveness of mHealth applications in spine is needed.
Acknowledgments
None.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Footnotes
Conflicts of Interest: The authors have no conflicts of interest to declare.
References
- 1.Pew Research Center Mobile fact sheet. Pew Research Center: Internet, Science & Tech, 2017. [Google Scholar]
- 2.Dattilo JR, Gittings DJ, Sloan M, et al. “Is there an app for that?” Orthopaedic patient preferences for a smartphone application. Appl Clin Inform 2017;8:832-44. 10.4338/ACI-2017-04-RA-0058 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Lang M, Zawati MH. The app will see you now: mobile health, diagnosis, and the practice of medicine in Quebec and Ontario. J Law Biosci 2018;5:142-73. 10.1093/jlb/lsy004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Baig MM, GholamHosseini H, Connolly MJ. Mobile healthcare applications: system design review, critical issues and challenges. Australas Phys Eng Sci Med 2015;38:23-38. 10.1007/s13246-014-0315-4 [DOI] [PubMed] [Google Scholar]
- 5.Aitken M, Lyle J. Patient adoption of mHealth. IMS Institute for Healthcare Informatics: New York, NY, USA, 2015. [Google Scholar]
- 6.Kay M, Santos J, Takane M. mHealth: New horizons for health through mobile technologies. World Health Organization 2011;64:66-71.
- 7.Morawski K, Ghazinouri R, Krumme A, et al. Association of a smartphone application with medication adherence and blood pressure control: the MedISAFE-BP randomized clinical trial. JAMA Intern Med 2018;178:802-9. 10.1001/jamainternmed.2018.0447 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Cho YM, Lee S, Islam SMS, et al. Theories Applied to m-Health Interventions for Behavior Change in Low- and Middle-Income Countries: A Systematic Review. Telemed J E Health 2018;24:727-41. 10.1089/tmj.2017.0249 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Miller LC, Appleby PR, Christensen JL, et al. Virtual interactive interventions for reducing risky sex: adaptations, integrations, and innovations. EHealth Applications: Promising Strategies for Behavior Change. Taylor and Francis, 2012:79-95. [Google Scholar]
- 10.Doak CC, Doak LG, Root JH. Teaching patients with low literacy skills. 1985.
- 11.Devries KM, Kenward MG, Free CJ. Preventing smoking relapse using text messages: analysis of data from the txt2stop trial. Nicotine Tob Res 2013;15:77-82. 10.1093/ntr/nts086 [DOI] [PubMed] [Google Scholar]
- 12.Heminger CL, Boal AL, Zumer M, et al. Text2Quit: an analysis of participant engagement in the mobile smoking cessation program. Am J Drug Alcohol Abuse 2016;42:450-8. 10.3109/00952990.2016.1149591 [DOI] [PubMed] [Google Scholar]
- 13.Riley W, Obermayer J, Jean-Mary J. Internet and mobile phone text messaging intervention for college smokers. J Am Coll Health 2008;57:245-8. 10.3200/JACH.57.2.245-248 [DOI] [PubMed] [Google Scholar]
- 14.Rodgers A, Corbett T, Bramley D, et al. Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging. Tob Control 2005;14:255-61. 10.1136/tc.2005.011577 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Abroms LC, Boal AL, Simmens SJ, et al. A randomized trial of Text2Quit: a text messaging program for smoking cessation. Am J Prev Med 2014;47:242-50. 10.1016/j.amepre.2014.04.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Chow CK, Redfern J, Hillis GS, et al. Effect of lifestyle-focused text messaging on risk factor modification in patients with coronary heart disease: a randomized clinical trial. JAMA 2015;314:1255-63. 10.1001/jama.2015.10945 [DOI] [PubMed] [Google Scholar]
- 17.Antypas K, Wangberg SC. An Internet-and mobile-based tailored intervention to enhance maintenance of physical activity after cardiac rehabilitation: short-term results of a randomized controlled trial. J Med Internet Res 2014;16:e77. 10.2196/jmir.3132 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Frederix I, Hansen D, Coninx K, et al. Medium-term effectiveness of a comprehensive internet-based and patient-specific telerehabilitation program with text messaging support for cardiac patients: randomized controlled trial. J Med Internet Res 2015;17:e185. 10.2196/jmir.4799 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Maddison R, Pfaeffli L, Whittaker R, et al. A mobile phone intervention increases physical activity in people with cardiovascular disease: Results from the HEART randomized controlled trial. Eur J Prev Cardiol 2015;22:701-9. 10.1177/2047487314535076 [DOI] [PubMed] [Google Scholar]
- 20.Park LG, Beatty A, Stafford Z, et al. Mobile phone interventions for the secondary prevention of cardiovascular disease. Prog Cardiovasc Dis 2016;58:639-50. 10.1016/j.pcad.2016.03.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Tofighi B, Abrantes A, Stein MD. The role of technology-based interventions for substance use disorders in primary care: A review of the literature. Med Clin North Am 2018;102:715-31. 10.1016/j.mcna.2018.02.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Bickel WK, Marsch LA, Buchhalter AR, et al. Computerized behavior therapy for opioid-dependent outpatients: a randomized controlled trial. Exp Clin Psychopharmacol 2008;16:132-43. 10.1037/1064-1297.16.2.132 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Roozen HG, Boulogne JJ, van Tulder MW, et al. A systematic review of the effectiveness of the community reinforcement approach in alcohol, cocaine and opioid addiction. Drug Alcohol Depend 2004;74:1-13. 10.1016/j.drugalcdep.2003.12.006 [DOI] [PubMed] [Google Scholar]
- 24.Patel N, Bagan B, Vadera S, et al. Obesity and spine surgery: relation to perioperative complications. J Neurosurg Spine 2007;6:291-7. 10.3171/spi.2007.6.4.1 [DOI] [PubMed] [Google Scholar]
- 25.Glassman SD, Anagnost SC, Parker A, et al. The effect of cigarette smoking and smoking cessation on spinal fusion. Spine 2000;25:2608-15. 10.1097/00007632-200010150-00011 [DOI] [PubMed] [Google Scholar]
- 26.Miloh T, Annunziato R, Arnon R, et al. Improved adherence and outcomes for pediatric liver transplant recipients by using text messaging. Pediatrics 2009;124:e844-50. 10.1542/peds.2009-0415 [DOI] [PubMed] [Google Scholar]
- 27.Gu Y, Wang L, Zhao L, et al. Effect of mobile phone reminder messages on adherence of stent removal or exchange in patients with benign pancreaticobiliary diseases: a prospectively randomized, controlled study. BMC Gastroenterol 2016;16:105. 10.1186/s12876-016-0522-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Stewart JJ, Fayed I, Henault S, et al. Use of a Smartphone Application for Spine Surgery Improves Patient Adherence with Preoperative Instructions and Decreases Last-minute Surgery Cancellations. Cureus 2019;11:e4192. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Park KH, Song MR. The effects of postdischarge telephone counseling and short message Service on the knee function, activities of daily living, and life satisfaction of patients undergoing total knee replacement. Orthop Nurs 2017;36:229-36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Day MA, Anthony CA, Bedard NA, et al. Increasing perioperative communication with automated mobile phone messaging in total joint arthroplasty. J Arthroplasty 2018;33:19-24. 10.1016/j.arth.2017.08.046 [DOI] [PubMed] [Google Scholar]
- 31.Lu K, Marino NE, Russell D, et al. Use of short message service and smartphone applications in the management of surgical patients: a systematic review. Telemed J E Health 2018;24:406-14. 10.1089/tmj.2017.0123 [DOI] [PubMed] [Google Scholar]
- 32.Horvath T, Azman H, Kennedy GE, et al. Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection. Cochrane Database Syst Rev 2012;(3):CD009756. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Anglada‐Martinez H, Riu‐Viladoms G, Martin‐Conde M, et al. Does mHealth increase adherence to medication? Results of a systematic review. Int J Clin Pract 2015;69:9-32. 10.1111/ijcp.12582 [DOI] [PubMed] [Google Scholar]
- 34.Pop-Eleches C, Thirumurthy H, Habyarimana JP, et al. Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders. AIDS 2011;25:825-34. 10.1097/QAD.0b013e32834380c1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Lewis MA, Uhrig JD, Bann CM, et al. Tailored text messaging intervention for HIV adherence: A proof-of-concept study. Health Psychol 2013;32:248-53. 10.1037/a0028109 [DOI] [PubMed] [Google Scholar]
- 36.Petrie KJ, Perry K, Broadbent E, et al. A text message programme designed to modify patients’ illness and treatment beliefs improves self‐reported adherence to asthma preventer medication. Br J Health Psychol 2012;17:74-84. 10.1111/j.2044-8287.2011.02033.x [DOI] [PubMed] [Google Scholar]
- 37.Foreman KF, Stockl KM, Le LB, et al. Impact of a text messaging pilot program on patient medication adherence. Clin Ther 2012;34:1084-91. 10.1016/j.clinthera.2012.04.007 [DOI] [PubMed] [Google Scholar]
- 38.Debono B, Bousquet P, Sabatier P, et al. Postoperative monitoring with a mobile application after ambulatory lumbar discectomy: an effective tool for spine surgeons. Eur Spine J 2016;25:3536-42. 10.1007/s00586-016-4680-4 [DOI] [PubMed] [Google Scholar]
- 39.Martínez-Ramos C, Cerdán MT, López RS. Mobile phone–based telemedicine system for the home follow-up of patients undergoing ambulatory surgery. Telemed J E Health 2009;15:531-7. 10.1089/tmj.2009.0003 [DOI] [PubMed] [Google Scholar]
- 40.Semple JL, Sharpe S, Murnaghan ML, et al. Using a mobile app for monitoring post-operative quality of recovery of patients at home: a feasibility study. JMIR Mhealth Uhealth 2015;3:e18. 10.2196/mhealth.3929 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Carrier G, Cotte E, Beyer-Berjot L, et al. Post-discharge follow-up using text messaging within an enhanced recovery program after colorectal surgery. J Visc Surg 2016;153:249-52. 10.1016/j.jviscsurg.2016.05.016 [DOI] [PubMed] [Google Scholar]
- 42.Pilot LR, Waldmann DR. Food and Drug Administration Modernization Act of 1997: medical device provisions. Food Drug Law J 1998;53:267-95. [PubMed] [Google Scholar]
- 43.Food and Drug Administration. Mobile medical applications: guidance for industry and Food and Drug Administration staff. Retrieved on February 2015;1:2016.