Improving clinic attendance through text message reminders to homeless patients with chronic health conditions


Background: Homeless people with chronic disorders need routine follow up to control chronic diseases and prevent exacerbations. Follow-ups without a reminder is challenging giving other competing needs. An intervention involving text message reminders was shown to increase clinic attendance. Routine clinic follow-ups improve chronic diseases management and reduce delay in presenting symptoms that may improve health

Objective: The objective of this study was to determine the effectiveness of short message service (SMS) for healthcare appointments to increase clinic follow-up attendance of homeless people in two Los Angeles clinics.

Methods: By using a quasi-experiment designed to measure clinic attendance, SMS text reminders were sent out to homeless patients attending the two clinics in a 3-month time period. An intervention process enabled from the electronic health record (EHR) was used to send out two text message reminders. The study compared homeless patients’ clinic attendance after the implementation of text message reminders for patients seen in 2018 compared to those seen in 2019.

Results: Of the 128 homeless people in the sample, 75% were males and 25% females with 52.3% whites, 18% blacks, Asians and Native Americans 2% each. The results showed a reduction of no-shows by 6% and an increase in attendance by up to 46% (n=128).

Conclusion: Implementing such a reminder could increase communication and reduce missed visits and emergency room use. Improved clinic attendance following text message reminders may not only improve health outcomes but eventually lower the cost of healthcare.

Improving clinic attendance through text message reminders to homeless patients with chronic health conditions.


Delivery of healthcare is significantly affected when patients miss clinic appointments. In out-patient clinic settings, this phenomenon of non-attendance in which a scheduled appointment is not kept is commonly called “no-show”. Several patient-related factors (personal/clinical) and health system-related factors (nature and clinic operations) influence clinic non-attendance (Paterson, Charlton & Richard, 2010). In an extensive literature study, Rafii, Fatemi, Danielson, Johansson, & Modanloo (2014) devised a working definition of compliance to include clinical attributes like patient obedience, ability to implement medical advice, flexibility, responsibility, collaboration, participation, and persistence to increase compliance. 

Homeless people with chronic diseases who do not follow up care often end up in the hospital due to the severity of symptoms. In one study about 679854 emergency room visits were made by homeless people from 2010-2015 (Lin, Bharel, Zhang, O’Connell, & Clark (2015) while another estimated the cost of no-shows and economic losses estimated to be $14.58 million (Kheirkhah, Feng, Q., Travis, L. Tavakoli- Sharafkhaneh, (2016). When a reminder letter system was applied to these 10 Virginia systems, the no show rate cost decreased from 18.17 % to 16.96 % (Kheirkha et al. 2016).

This project involved homeless persons who frequent the LACHC out-patient clinics in Los Angeles. All persons deemed homeless according to section 330(h)(5)(A) definition of homelessness – lack a night residence including staying in public or private supervised facility like shelters (National healthcare for the Homeless council, 2018) are eligible for care at these federally approved clinics including those of LACHC where this research was conducted.

Missed clinic appointments is a challenge in the primary care setting made worse by homelessness. Salameh, Olsen, & Howard (2012) examined patients with diabetes in an ambulatory clinic and showed that missed appointments resulted in inconsistency and ineffective care that may raise health care costs. One study showed that forgetfulness, schedule conflicts, long wait times, transportation, and medical provider-patient trust issues presented barriers to clinic attendance (Lacy, Paulman, Reuter, & Lovejoy, 2004). However, there is limited literature on the challenges of clinic attendance amongst the homeless population. By researching databases from Healthcare for the Homeless (HCH) services, Zlotnick, Zerger, & Wolfe (2013) found that by June 1986, 19 HCH grantees had provided healthcare to 30,000 homeless persons including 2,000 aged 15 years or younger. Timely and quality access to healthcare by homeless individuals remain a challenge.

Barriers to homeless people receiving healthcare

Competing priorities is a major barrier to health care among the homeless because they face several daily life’s demands like food and shelter which prevents them from making medical care a necessity. Some barriers are actual while others are perceived. For example, lack of public transportation, low health literacy, language barriers, and lack of healthcare insurance are actual (Salameh et al. 2012) and lack of safe places to discharge patients or patient’s fear as perceived barriers (Hunter, Getty, Kemsley, & Skelly, 1991). Communication with the homeless is challenging given that they have no physical address. To determine how homeless people get information and stay connected, Stennet et al (2012) conducted a survey and noted that they spend more time in food pantries, own a cell phone and frequent libraries. Therefore, to find an efficient method of contacting them would include visiting the meal places they frequent or communicate with them through cell phones.

Salameh et al (2012) showed that text message and phone call reminders to diabetic patients in an outpatient clinic resulted in a decrease in non-attendance rate from 25.5% (baseline) to 18.2% during the first visit and further dropped to 6.8% at the second visit. The non-attendance rate was suggested to be related to the complexity of the medical condition, stating that the more complex the less likely the patient would comply with clinic attendance. Likewise, the presence of comorbidities with diabetic patients played a relevant part in non-attendance. Therefore, to enhance communication between the homeless and the medical providers, mobile phones could potentially be used by health and public care providers to disseminate information to the homeless population (McInnes, Petrakis, Gifford, Rao, Houston, Asch, & O’Toole, 2014).  

To support quality healthcare and better clinical outcomes, an SMS text-based intervention that involves frequent interactions and specific reminders could increase clinic attendance, reduce missed appointments, and promote patient involvement in their care. Coomes et al (2012), reviewed several interventions that used SMS to support healthcare quality and improve health outcomes to propose a conceptual model. The model describes how SMS could be useful for other aspects of self-management, social support, patient involvement in self-care and providing information to enhance health and well-being or decrease health risks.

The purpose of this study is to reduce clinic no-shows by sending SMS text reminders for upcoming clinic visits to improve clinic attendance. With increased clinic attendance, homeless patients will miss fewer clinic appointments, abnormal lab/imaging results will be addressed before the onset of exacerbation resulting in improved health.

Literature review

There is evidence to support the use of short message services (SMS) through mobile phones to improve clinic attendance. However, there is little evidence that this text message reminder system would work for homeless patients. Evidence-based literature in this review show the effect of attendance reminders and missed appointments or “no shows” on clinic attendance rates and specifically regarding the homeless.

Mobile Technology amongst the homeless

The use of mobile phones by the homeless population poses less hassle since it does not involve physical constraints such as landlines. Eyrich-Garg (2010) carried out an exploratory study on mobile phone possession and use by the homeless and showed almost half (44%) of the participants had mobile phones, 100% of mobile phone owners either placed or received a call, while over half (61%) sent or received a text message, and one fifth (20%) accessed the Internet through their mobile phones. McInnes, Petrakis, Gifford, Rao, Houston, Asch, & O’Toole (2014) examined the feasibility of using SMS to cut down on missed medical appointments or no-shows and their results revealed that canceled appointments were reduced from 53 to 37 while the number of no-shows reduced from 31 to 25.  According to the study by Asgary, Sckell, Alcabes, Naderi, Adongo, & Ogedegbe, 2016), homeless people welcomed and supported the use of text messaging to address healthcare issues, appointment reminders, health education, and disease management.

The importance of healthcare coordination and its effects on the homeless

Care coordination is essential in healthcare so there is a collaboration between different teams for a continuum of care. Quality improvement strategies to coordinate care has been shown to reduce hospital admissions among patients with chronic conditions and fewer emergency visits amongst older patients (Tricco, Antony, Ivers, Ashoor, Khan, Blondal, & … Straus, 2014). Having noted that a small group of patients frequently use the health care system, Tricco et al (2014) reviewed 663 full-text articles, 36 RCTs including 7,494 patients, and 14 companion reports and found that significantly fewer patients in the intervention group than in the control group were admitted to the hospital. Other studies have supported care coordination quality improvement strategies like the use of patient navigators who connect patients with the right doctors and ensure that they have access to the necessary therapies and resources (Walkinshaw, 2011). Bringing homeless patients more often to the clinic will provide increased opportunities to apply these improvement strategies.

According to the Pew Research Center on Internet and Technology, 95% of Americans own mobile phones (Pew Research Center, 2018). With mobile phones that ubiquitous, healthcare workers could use them to disseminate information. Establishing an effective way to communicate with the homeless population has been a difficult task. In a study by Stennett, Weissenborn, Fisher, & Cook (2012), homeless people were shown to prefer communication through mobile phone rather than email due to low literacy levels. The lack of email use was supported by another study in which 32,036 records (including RCTs, quasi-randomized trials, controlled before and after studies) used emails compared to other forms of coordinating appointments and reminders found no occurrence (Atherton, 2012). It is therefore important to choose a reliable communication method that would reach the homeless who may be at risk of missing clinic appointments.

To identify patients at risk for missing appointments Goffman, Monte, Myaskovsky, Rodriguez, Harris, May, & … Vargas (2017) developed and tested a predictive model that identifies patients at high probability of missing their outpatient appointments. They showed that patient’s no-show probability was related to a past attendance behavior, the age of the appointment, and having multiple appointments scheduled on same day (Goffman et al., 2017). Another study targeting patients at high risk of missing appointments revealed the no-show rate of those who received reminder phone calls (22.8 %) was significantly lower than those in the control arm (29.2 %) (Shah, Cronin, Hong, Hwang, Ashburner, Bearnot, & … Kimball, 2016).  

Bridging the literature gap – Text message reminders for clinic attendance to the homeless

There is limited literature on the use of mobile technology to improve clinic attendance amongst the homeless. The current project used support for text message to improve attendance rates among other vulnerable populations and evaluated the effect on the homeless population. Despite numerous barriers to technologies, homeless people show high access to technologies and use them for about the same reasons as the general population but in addition for reasons associated to their homelessness (Jennings, Lee, Shore, Strohminger, Allison, Conserve, & Cheskin, 2016).

A similar study on use of information technologies by homeless persons showed that among the homeless, mobile phone ownership ranged from 44% to 62%; computer ownership, from 24% to 40%; computer access and use, from 47% to 55%; and Internet use, from 19% to 84% (McInnes, Li, & Hogan, 2013). Though there is limited research on homeless and mobile health there is even less research on how SMS text reminders can improve clinic attendance in a homeless community. Although these studies do not directly look at the effect of mobile phones on clinic attendance, exploring the cell phone use by the homeless for medical and health reasons other than homeless related activities will further improve health outcomes of this vulnerable population.


This research was designed to measure clinic attendance after the initiation of Short Message Service (SMS) reminders for clinic visits. The SMS reminder intervention was assessed for compliance improvement of clinic attendance. The medical record was not accessed for this project therefore no consent form or questionnaire was required. The independent variable was sending text message reminders while the dependent variable was compliance with clinic attendance measured as percent of clinic no-shows and overall attendance.

Research design

This quasi-experimental study evaluated the impact of text message reminders to homeless patients on clinic attendance. The percent no-show rate (dependent variable) for text message recipient was measured. The project was carried out at two Los Angeles Christian Health Centers (LACHC) clinics.

Population, Sampling, and Location

Participants were selected from a study sample that included homeless adults 18 years or older who attend the two LACHC clinics. The LACHC clinic is a federally approved clinic for the homeless in the city of Los Angeles. The clinic serves chronically homeless individuals who live either on the streets, in emergency shelters, transitional housing or in a community of low-income families. There are many definitions for homelessness often based on the types of services being requested at state or federal level. The Health and Human Services definition of homelessness used in this study states: According to 330(h)(5)(A), a homeless person is defined as “an individual who lacks housing (without regard to whether the individual is a member of a family), including an individual whose primary residence during the night is a supervised public or private facility (e.g., shelters) that provides temporary living accommodations, and an individual who is a resident in transitional housing.”  

Identification and recruitment of potential participants

All patients visiting the two LACHC clinics, during a 3-month time period were eligible to be part of the study.  The usual procedure during a visit are

  • Patient meets with a Patient Registration Specialist (PRS) who confirms the information in the Electronic Health Record (EHR).
  • The PRS asks if the patient would like to receive a text message reminder for the follow-up appointment.
  • If the patient agrees, the prompt will be entered in the EHR.
  • This was done for all patients visiting the clinic

Intervention, data collection and measurement

A text-messaging intervention process enabled from the EHR software call eClicincalWorks (eCW) was used to send out text messages. The goal of the study was to compare homeless patients’ clinic attendance before and after the implementation of text message reminders for a follow-up appointment. The intervention was a change in office procedure at two LACHC clinics and one medical provider. All patients scheduled for appointments after the implementation of the text message reminder received a text 6 days before and another 1 day before the appointment. The text message read “{Your name}: {Site} appt on date @ time. If you cannot make it, please call [site] to reschedule” in English or in Spanish (figure 1). Data was gathered from the EHR for the 3-month period of text messaging and compared to a similar 3-month period in the previous year. This report generated from the EHR does not include any patient identifiers but contains demographic data such as age, gender, race, homelessness, text message reminders and follow-up appointments.

The participant’s medical record was not accessed. However, the population health department produced the reports representing the pre-study period without text message the year before and was compared to current attendance after the study.


Given the definition of homelessness in this project, doubling up, transitional housing was included as homeless. All patients with status “Other” were eliminated from the sample size. The total number of patients seen in both 2018 and 2019 included in the sample size for analysis was 128, multiple visits were grouped in 2-weeks increment for analysis in SPSS. A paired t-test was used to analyze the same population comparing periods 2018 and 2019

Ethical Considerations

This project was approved by The University IRB at Edinboro University of Pennsylvania. Homeless people are considered a vulnerable population due to increased risk for adverse health-related outcomes (Strehlow & Amos-Jones, 1999), lack of permanent dwelling, low socioeconomic status even when dying they are “unbefriended” (Ashpole, 2017). These participants did not need to complete an informed consent as consent was considered by accepting to receive text message reminders.

Figure 1: SMS scheduling settings in the EHR


The analyses of the data displayed a total of 128 homeless people from Los Angeles County. The results showed that the average age of the total sample was 47.01 years, SD= 11.86. Among them, the minimum age was 21 years and the maximum age reached 71 years old (Table 1). Based on gender, 25% (n=32) of homeless were female compared to 75% (n=96) who were male. In terms of race, majority of the homeless people in the sample size were White (52%) compared to 26% who refused to state or were unreported; 18% were Black/African Americans; 2% were Asian and American Indian/Alaska respectively (Table 1).

Answering research question one related to effectiveness of SMS on attendance: The practical significance of the effectiveness of SMS on follow-up attendance was calculated as 46%. That means the SMS text reminders significantly increased the follow-up attendance of homeless patients in the out-patient clinic by 46%, p< .000. Answering research question two on attendance amongst males and females: The result indicated that the test was not significant, t(128) = -1.11, p= .26. The female homeless patients’ follow-up attendance through SMS reminder (M=7.81, SD= 1.14) on the average had the same rate of attendance as that of male homeless (M= 8.10, SD= 1.60). The 95% confidence interval for the difference in means (MD = -.29) (Table 2).

Table 1: Demographic Data

Descriptive Statistics (N=128)
Characteristics Frequency Percent
Age (years):
     Average = 47
     Minimum = 21
     Maximum = 71
           Female 32 25.0
           Male 96 75.0
American Indian/Alas 3 2.3
Asian 2 1.6
Black/African American 23 18.0
Unreported/Refused to state 33 25.8
White 67 52.3


Table 2: The effects of SMS text message reminders on clinic attendance (SPSS Analysis)
Intervention (Year) Mean N Std. Deviation
Total weeks (2018) 7.22 128 1.345
Total weeks (2019)                               Females (2018)

Males (2018)

Females (2019)

Males (2019
















  1. Using paired t-testing, t(128) = -10.385, p< 0.000 is significant: increased attendance with SMS texts. The calculated practical significance of effectiveness was calculated as 46%.
  2. Using Levene’s testing, t(128) = -1.118, p=.26, 95% Confidence Interval. Not significant: No difference in attendance between male and female.

Table 3: Overall no-show rate from 2 clinics through eCW (all patients: homeless and housed

LACHC Clinics 2018 No-show rate (%) 2018 No-show rate (%) Reduced by (%)
P4 31.6% 21.6% 10%
CLA 10.8% 22.8% -12%
TOTAL 22.8% 16.5% 6.3%


This study was undertaken in order to improve clinic attendance in two LACHC clinics for homeless patients through SMS reminder text intervention. Prior to this study only phone calls were routinely made to remind patients of their upcoming appointments. In order to reduce missed appointments (no-show), we implemented a seldom-used feature of the current EHR, eCW. We used eCW to generate automatic text message reminders to patients who had been scheduled for follow up clinic visits. The goal was to decrease no-show rates by 10 percent in 3 months compared to a similar period in the prior year, and to determine whether the resulting increase in attendance was significant.

This project resulted in the reduction of no-shows by 6% (Table 3) and an increase in attendance by up to 46% (n=128). Our findings suggest that the reduction in clinic no-shows and increased attendance may possibly be due to the text message reminders since all other variables remained the same. Other studies have shown the impact of text message reminder in improving clinic attendance (Boksmati, et al, 2016) but only a few studies amongst homeless patients. In one of the first studies on improving outpatient attendance with text messages, Guy et al (2012) demonstrated that a 50 % increase in clinic attendance was attributed to text message reminders compared to those with no reminders.

Random responses from the patients in our study indicated patients preferred the text reminders because they could refer to the messages later. In addition, it is easier and cheaper to own a mobile phone than a landline while homeless (Sasso, 2013; Moczygemba, Cox, Marks, Robinson, Goode, & Jafari, 2017). When patients come to the clinic, they are more likely to continue treatment and get appropriate and timely intervention. Therefore, it is critical to use relevant strategies that increase appointment attendance to benefit both patients and services.

Our study revealed 75% males and 25% females consistent with reports of the 2016 Annual Homeless Assessment Report (AHAR) which indicated a prevalence of homeless men (71.6%) over females (27.9%) with the remaining 0.5% being transgendered (HUD, 2016). Our findings on race distribution showed 52.3% of the homeless population were white followed by blacks at 18%, while the HUD report confirms that over 50% of homeless individuals are white, 35% blacks, 1.1 % Asians, and Pacific Islander at 1.2% (HUD, 2016). A substantial percent of homeless people in our findings refused to state their race (25.8%). Anti-homelessness sentiments may be responsible for refusal to state for fear of prejudice (De Las Nueces, 2016). There is limited research on racial distribution in homeless people and even fewer studies separating these racial differences in homeless men and women. However, there is a huge gap when considering the lifetime incidence of homelessness by racial subgroups. Fusaro, Levy, and Shaefer (2018) demonstrated the rates of homelessness were higher for non-Hispanic blacks (16.8%) than non-Hispanic whites (4.8%).

Improved clinic attendance with text messaging may be due to an increased use of mobile phones by homeless people and possibly improved SMS technology. Therefore more healthcare organizations will be able to use SMS reminders. Increased healthcare access to the homeless and underserved communities will bring much-needed preventive care services to this community. The benefit provided by frequent clinic attendance may result in better self-care and management of chronic conditions.


If patients had both a landline phone number and a mobile number, the text message will fail. The EHR used to send out text message was not previously tested for validity and reliability. Some patients’ phone numbers changed, lost, stolen, or were uncharged giving room for lost text messages. Furthermore, when patients moved (hospitalized, found housing, displaced from street corner near clinic, incarcerated or other legal problems) they would not to return to the clinic even if they received the text message. Despite these limitations our results add to the feasibility of using text message reminders in health-related communications to homeless people.

Implications for future research

Including other clinics in the organization and recruit participants that will be followed specifically to obtain primary data instead of secondary data from EHR. Also exploring the possibility of using a stand-alone text message automated software to send out text message reminders will better control the messaging and receipt confirmation. A future study should also address the time and rate of text message delivery and relate it to the time between reminder and appointment time, the type of clinic, and the setting.


To specifically attribute this improvement or change in office process to the text message reminder intervention, additional assessment is required to show both statistical and clinical significance and greater confidence. Based on the outcome of this study, better communication methods with the homeless may lead to improved health care services and perhaps other services for homeless populations such as housing and employment.


Asgary, R., Sckell, B., Alcabes, A., Naderi, R., Schoenthaler, A., & Ogedegbe, G. (2016). Rates and Predictors of Uncontrolled Hypertension Among Hypertensive Homeless Adults Using New York City Shelter-Based Clinics. Annals Of Family Medicine, 14(1), 41-46. doi:10.1370/afm.1882

Ashpole, B. (2017). Vulnerable populations: from the homeless to the unbefriended. European Journal of Palliative Care, 24(6), 266.

Atherton H, Sawmynaden P, Meyer B, & Car J. (2012). Email for the coordination of healthcare

appointments and attendance reminders. Cochrane Database of Systematic Reviews, (8), N.PAG.

Boksmati, N., Butler-Henderson, K., Anderson, K., & Sahama, T. (2016). The Effectiveness of SMS Reminders on Appointment Attendance: a Meta-Analysis. Journal Of Medical Systems, 40(4), 1- 10. doi:10.1007/s10916-016-0452-2

Booth, S.  (1999). Researching health and homelessness: methodological challenges for researchers working with a vulnerable, hard to reach, transient population. Aust J Prim Health Interchange 5,76–80.

Clark, R. E., Weinreb, L., Flahive, J. M., & Seifert, R. W. (2018). Health Care Utilization and Expenditures of Homeless Family Members Before and After Emergency Housing. American Journal of Public Health, 108(6), 808-814. doi: 10.2105/AJPH.2018.304370

Coomes, C. M., Lewis, M. A., Uhrig, J. D., Furberg, R. D., Harris, J. L., & Bann, C. M. (2012). Beyond reminders: a conceptual framework for using short message service to promote prevention and improve healthcare quality and clinical outcomes for people living with HIV. AIDS Care, 24(3), 348-357. doi:10.1080/09540121.2011.608421

Eyrich-Garg, K. (2010). Mobile phone technology: a new paradigm for the prevention, treatment and research of the non-sheltered ‘Street’ homeless? J Urban Health, 87, 365–380.

Goffman, R. M., Monte, R. J., Myaskovsky, L., Rodriguez, K. L., Harris, S. L., May, J. H., & …

Vargas, D. L. (2017). Modeling Patient No-Show History and Predicting Future Outpatient Appointment Behavior in the Veterans Health Administration. Military Medicine, 182(5), e1708-e1714.  doi:10.7205/MILMED-D-16-00345Promoting Excellence in Healthcare, 32(6), 27–32.

Guy R, Hocking J, Wand H, Stott S, Ali H, & Kaldor J. (2012). How effective are short message

service reminders at increasing clinic attendance? A meta-analysis and systematic review. Health Services Research, 47(2), 614–632.

Hunter, J. K., Getty, C., Kemsley, M., & Skelly, A. H. (1991). Barriers to providing health care to homeless persons: a survey of providers’ perceptions. Health Values: The Journal of Health Behavior, Education & Promotion, 15(5), 3–11. Retrieved from:

Jennings, L., Lee, N., Shore, D., Strohminger, N., Allison, B., Conserve, D. F., & Cheskin, L. J. (2016). U.S. Minority Homeless Youth’s Access to and Use of Mobile Phones: Implications for mHealth Intervention Design. Journal of Health Communication, 21(7), 725–733

Kheirkhah, P., Feng, Q., Travis, L. M., Tavakoli-Tabasi, S., & Sharafkhaneh, A. (2016). Prevalence, predictors and economic consequences of no-shows. BMC Health Services Research, 16, 13.

Lin, W. C., Bharel, M., Zhang, J., O’Connell, E., & Clark, R. E. (2015). Frequent Emergency Department Visits and Hospitalizations Among Homeless People With Medicaid: Implications for Medicaid Expansion. Am J Public Health, 105 Suppl 5, S716-722. doi: 10.2105/ajph.2015.302693

Lacy, N. L., Paulman, A., Reuter, M. D., & Lovejoy, B. (2004). Why we don’t come: patient perceptions on no-shows. Annals Of Family Medicine, 2(6), 541-545.

McInnes, D. K., Li, A. E., & Hogan, T. P. (2013). Opportunities for Engaging Low-Income, Vulnerable Populations in Health Care: A Systematic Review of Homeless Persons’ Access to and Use of Information Technologies. American Journal Of Public Health, 103(S2), e11-24. doi:10.2105/ AJPH.2013.301623

McInnes, D. K., Petrakis, B. N., Gifford, A. L., Rao, S. R., Houston, T. K., Asch, S. M. &  

O’Toole, T. P. (2014). Retaining Homeless Veterans in Outpatient Care: A Pilot Study of Mobile Phone Text Message Appointment Reminders. American Journal of Public Health,104 (S4): s589-594

Moczygemba, L. R., Cox, L. S., Marks, S. A., Robinson, M. A., Goode, J. R., & Jafari, N. (2017). Homeless patients’ perceptions about using cell phones to manage medications and attend appointments. International Journal Of Pharmacy Practice, 25(3), 220-230. doi:10.1111/ijpp.12321

National Health care for the Homeless council. (2018). What is the official definition of

homelessness? Retrieved from:

Paterson, B. L.l, Charlton P., & Richard, S. (2010). Non‐attendance in chronic disease clinics: a matter of non‐compliance? Journal of Nursing and Healthcare of Chronic Illness 2, 63–74

Pew Research Center. (2018). Mobile fact sheet. Retrieved from:

Salameh, E., Olsen, S., & Howard, D. (2012). Nonattendance with clinic follow-up appointments: Diabetes as exemplar. The Journal for Nurse Practitioners, 8(10), 797-803.

Sasso, B. (2013). FCC Chief: Reagan Could be Proud of ‘Obamaphone’ Program, THE HILL. Retrieved from  

Shah, S., Cronin, P., Hong, C., Hwang, A., Ashburner, J., Bearnot, B., & … Kimball, A. B. (2016). Targeted Reminder Phone Calls to Patients at High Risk of No-Show for Primary Care Appointment: A Randomized Trial. JGIM: Journal Of General Internal Medicine, 31(12), 1460-1466. doi:10.1007/s11606-016-3813-0

Statista. (2018). Number of mobile phone users worldwide from 2013 to 2019 (in billions). Retrieved from:  

Stennett, C., Weissenborn, M., Fisher, G., & Cook, R. (2012). Identifying an effective way to communicate with homeless populations. Public Health (Elsevier), 126(1), 54-56.

Strehlow AJ, & Amos-Jones T. (1999). The homeless as a vulnerable population. Nursing Clinics of North America34(2), 261–274

Walkinshaw, E. (2011). Patient navigators becoming the norm in Canada. CMAJ, 183, E1109–10

Zlotnick, C., Zerger, S., & Wolfe, P. B. (2013). Health Care for the Homeless: What We Have Learned in the Past 30 Years and What’s Next. American Journal Of Public Health, 103(S2), S199-205. doi:10. 2105/AJPH.2013.301586

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