KnE Life Sciences | The 3rd International Meeting of Public Health and the 1st Young Scholar Symposium on Public Health | pages: 129–139

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1. Introduction

Electronic Patient-Reported Outcomes (e-PROs) have overgrown in clinical research and care. In 1994, Landgraf and Abetz [13] had developed the infant/toddler quality of life questionnaire (ITQOL) as an assessment of child health-related quality of life through parent report for children between 2 months and five years old. The United States Food and Drug Administration (FDA) Guidelines for Industry also developed E-PROs since 2009 to ensure the delivery of quality patient care (FDA in Landgraf et al., 2012). The European Medical Association (EMA) acknowledged the need for e-PROs since October 2010 to increase healthier lifestyles and better decision making for doctor and patient (European Commission in Landgraf et al., 2012). Although there was no universal definition of an e-PROs, Parliari et al. (2012) had defined e-PROs as “an electronic application in which individuals can access and manage their health information in a private, secure and confidential environment."

The adoption of e-PROs has potential advantages to maximize the value of health outcomes research. Patients with long term conditions are the most need to track their illness and real-time decision treatments (Parliari et al., 2012). E-PROs may increase partnership between health professionals and patients through sharing information to ensure the delivery of quality patient care ([26], Wu, AW, 2013). Chang (2007) emphasized that e-PROs may reduce the health care cost by identifying patients' symptoms, guiding health prevention, and providing medical intervention. E-PROs can be a useful tool to reach diverse, geographically dispersed and specifically targeted populations [7].

Research on the use of ePROs to conduct health surveillance faced potential issues and challenges. Those issues and problems are privacy as well security concern, digital divide, technical considerations, lack of comprehensive yet clinical relevant PROs measures, health provider burdens, and lack of clinically meaningful analyses ([12], Pangliari et al., 2007, Ekman and Litton, 2006). Lengthy instruments can frustrate and disinterest patients to respond due to time as well as energy consumed, that may cause missing or inaccurate data (Moris et al. in [17], Miller, D, et al., 2015). PROs instruments which have more than 20 variables lead to overburden patients which cause further content redundancy [27].

In Indonesia, despite substantial growth in internet use, the Association of Indonesian Internet Service Providers has estimated that there 48.2 percent of individuals lacked internet access in 2016 [2]. Internet access varies widely by socioeconomic status which leads to digital exclusion (the so-called `digital divide') [7]. The factors underlying the digital divide may result from socioeconomic barriers to access as well as a lack of desire or ability to use the internet among particular segments of the population (Wagner et al., 2005). Subsequently, the digital divide will be outpaced by those who are ahead in the ability to select and process information (Mason and Hacker, 2003, Wong et al., 2009).

Located in the capital city of West Java Province, Ciparay's Sub-District has recorded as the most populated district in Bandung Region. In 2015, the population reached 148.025 people in which its population density has estimated 19.784 people per km 2 [2]. Ciparay Sub-District has the highest poverty level compared to another district in Bandung area [2]. In 2012, there were one neonatal death (0-6 days) and three infant death in Ciparay's Sub-District [6].

The purpose of this study was to evaluate patients who access the Primary Health Care in Caray's Sub-District to the adoption of Electronic Patient-Reported Outcomes.

Therefore, this study was designed to address the following questions:

  • Are there any significant demographic differences among Ciparay's patients about their adoption of emerging patient-reported outcomes?

  • To what extent are patients in Caray's Sub-District fill in various types of variables in the patient-reported outcomes technology?

  • What barriers to the adoption of patient-reported outcomes in Ciparay's Sub-District? staff

2. Methods

The study design is a cross-section, analyzed by the descriptive way as part of an evaluation of Memobayi.com, an EPROM technology. This study included a convenience sample of patients who have access Ciparay's Primary Health Care during April to July 2016. Participants informed that by filling out the EPROs, they would give informed consent and had agreed to participate in this research voluntarily.

Patients were approached during their consultation in the Ciparay's Primary Health Care and were asked to complete the patient-reported outcomes. They are given a written statement regarding the research goal and objectives, which stated that by filling the Memobayi.com. Those patients had consented to take part in the research project. It also said that if they decided not to take part in not complete the survey, it would not affect their right or benefits in any way. Initially, those patients had assisted in filling in the Memobayi.com. Afterward, the patients had to fill in the Memobayi.com itself. A year after the research has conducted in Ciparay, several patients had been re-contacted by email and phone on August 2017 to have feedback on Memobayi.com.

Theoretical concepts from Roger's Diffusion of Innovations Theory guided the development of patient-reported outcomes [21]. Roger describes five characteristics of an innovation namely, relative advantage, compatibility, complexity, trialability and observability. The theory has also suggested that the users' perception of the attributes of change determines the extents of uptake of new technology [21].

The project team developed a Memobayi.com, an EPROM which included 114-variables to assess the health status of children. Demographic information in the Memobayi included age, educational background, marital status, parent's height, parent's weight, and occupation. Data on infants included name, gender, date of birth, place of birth, parity, birth history, perinatal history, parenting history, disease history, neonatal screening, and obstetric history.

3. Results

A total of 112 patients in Ciparay's Primary Health Care has filled Memobayi.com. Only 6 percent of the patients have a private email. Therefore, those patients have been assisted in creating their email since private email is mandatory to register into Memobayi.com.

All patients have fully responders to fill in selected variables e.g. name of the user, user's email, date of birth, marital status, user's address, phone number, medical personnel handling, place of health service, sex of their infants, activation date, birth weight, birth length of their infants, Apgar value and birth condition of their infants. Nearly 95 percent of the responders have registered into Memobayi.com for one month after their babies are born. The majority of those infants have normal birth weight (more than 2.500 gram) whereas only 6 percent of the infants have low birth weight (less than 2.500 gram).

Attachement NO. 1

Completion Rate of Memobayi.com, Ciparay's Sub-District, 2016.


Number of responders Completion Rate (in %)
Demographic characteristics of the parents
User's Name 112 100
Email's Address 112 100
User's Date of Birth 112 100
User's Educational Background 112 100
Marital status 112 100
Address 112 100
User's occupation 112 100
Phone number 112 100
Health provider 112 100
Institution 112 100
Registration Date 112 100
The blood type of user 95 84.82
User's Height 0 0
User's Weight 0 0
Infant's Data
Infant's name 112 100
A medical record number of the infant 112 100
Infant's sex 112 100
Activation Date 112 100
Birth History
Place of birth 112 100
Infant's Date of Birth 112 100
Delivery Process 112 100
Birth Weight of Infant 112 100
Birth Length 112 100
Apgar Value 112 100
Birth Attendant 109 97.32
Initial Breastfeeding 108 96.43
Birth Complication 107 95.54
Head Circumference 106 94.64
Babies cry directly 105 93.75
Injection of Vitamin K 105 93.75
Infant Bluish 104 92.86
The blood type of infant 13 11.61
Perinatal History
Weight at returning home 98 87.50
Congenital abnormalities 95 84.82
Room in between mother and newborn 83 74.11
Prematurity status 83 74.11
When the baby has a yellow appearance 38 33.93
Light therapy 30 26.79
Bilirubin level 1 0.89
Parenting history
Parenting history 81 72.32
Number of older sister/brother 51 45.54
Breastfeed history 48 42.86
Solid food consumed 46 41.07
Formula milk history 44 39.29
Number of younger sister/brother 1 0.89
Disease History Among Parents
Disease history of the parents: Asthma 83 74.11
Disease history of the parents: Allergy to food 83 74.11
Disease history of the parents: Allergy to Medicine 83 74.11
Disease history of the parents: Obesity 83 74.11
Disease history of the parents: Diabetes Mellitus 82 73.21
Disease history of the parents: Hypertension 82 73.21
Disease history of the parents: Tuberculosis 81 72.32
Disease history of the parents: Thalassemia 78 69.64
Disease history of the parents: Other 0 0
Disease History of the Child
Disease history of the child: Congenital Abnormalities 97 86.61
Disease history of the child: Convulsions 97 86.61
Disease history of the child: Allergy on Medicine 97 86.61
Disease history of the child: Asthma 97 86.61
Disease history of the child: Tuberculosis 95 84.82
Disease history of the child: allergy to food 83 74.11
Disease history of the child: dermatitis/eczema 82 73.21
Disease History of the Child: Measles 79 70.54
Disease History of the Child: Hepatitis B 79 70.54
Disease History of the Child: Malaria 79 70.54
Disease History of the Child: Typhoid 77 68.75
Disease history of the Child: chicken pox 76 67.86
Convulsions 75 66.96
Tuberculosis history of the child: Doctor 3 2.68
Tuberculosis history: duration 2 1.79
Disease History of the Child: Other 1 0.89
Tuberculosis history of the child: age 1 0.89
Chickenpox history of the child: Age 0 0
Neonatus Screening
Neonatus: Other Screening 81 72.32
G6PD enzyme's deficiency 80 71.43
Congenital Hypothyroidism 80 71.43
Neonatus - Hb 75 66.96
Laboratorium - Blood sugar 75 66.96
Left Congenital Deafness 0 0
Right Congenital Deafness 0 0
Obstetric History
Obstetrik - Hb 82 73.21
Complication During Pregnancy 80 71.43
Duration of pregnancy 80 71.43
HIV 80 71.43
Hypertention & preeclamsia 79 70.54
Premature Rupture of Membranes 79 70.54
Examination on K1 79 70.54
Examination on K4 77 68.75
Bleeding 77 68.75
Infection 77 68.75
Upper Arm Circumference 46 41.07
Lactation Visit 41 36.61
Weight Gain 32 28.57
Rubella 7 6.25
pre-screening development questionnaires - 15 months 2 1.79
pre-screening development questionnaires-3 months 1 0.89
pre-screening development questionnaires- 6 months 1 0.89
pre-screening development questionnaires - 9 months 1 0.89
pre-screening development questionnaires- 12 months 1 0.89
pre-screening development questionnaires - 18 months 1 0.89
pre-screening development questionnaires - 21 months 1 0.89
pre-screening development questionnaires - 24 months 1 0.89
pre-screening development questionnaires - 30 months 1 0.89
pre-screening development questionnaires - 36 months 0 0
pre-screening development questionnaires - 42 months 0 0
pre-screening development questionnaires - 48 months 0 0
pre-screening development questionnaires - 54 months 0 0
pre-screening development questionnaires - 60 months 0 0
pre-screening development questionnaires - 66 months 0 0
pre-screening development questionnaires - 72 months 0 0
Toxoplasma 0 0
Syphilis 0 0
Cytomegalovirus 0 0
Herpes simplex 0 0
Source. Data recorded by ePROs Memobayi.com, 2016.

However, none of those patients have to fill in several variables such as parent's height, parent's weight, child's disease history on chicken pox, toxoplasma's status, syphilis's status, herpes simplex's status, congenital deaf's status, and pre-screening development questionnaires (refer to attachment no. 1). These conditions lead to missing data and bias for the research's analysis [18].

Table 1 reveals the demographic characteristics of the responders in Ciparay's Sub-District in 2016. The responders were predominantly housewives (89.3%) with 6.25% responders working informal sector and 4.5% responders working in the intimate area. Half (51.8%) of the participants had senior high school graduated whereas only 6.2 percent indicating they had a graduate degree, 27.72 percent patients had junior high school graduated, and 14.29 percent patients had elementary school graduated. Almost half of the responders at the age of 31-40 years old (45.54%), 21-30 years old (34.82%), less than 20 years old (11.61%) and more than 41 years old (8.04%).

Table 1

Sociodemographic characteristics of the parents.


N %
Demographic characteristics
Education
Graduate degree 6 6.3
Senior High School Graduated 58 51.8
Junior High School Graduated 31 27.72
Elementary School Graduated 6 14.29
Profession
Working in the formal sector 7 6.25
Working in the informal sector 5 4.5
Stay at home 100 89.3
Age group (years)
20 13 11.61
21-40 90 80.36
41 8 8.04
Source. Data recorded by ePROs Memobayi.com, 2016

There were notable differences among age groups about complete ePROs (indicated by fill in more than 50% of its variables). The result of chi-square analyses showed that there were statistically significant relationships between age group and completion more than 50% variables of Memobayi.com (X 2 = 7.99, p = 0.018) (table 2).

Table 2

Differences among age groups for completing 50% of Memobayi's variables.


Completion (%)* Chi-square p-value
Yes No
Age group (years)
20 81.2 18.8 7.990 0.018
21-40 69.4 30.6
41 100.0 0.0
*Responders completed in more than 50% of Memobayi.com's variables.
Source. Data recorded by ePROs Memobayi.com, 2016.

After a year, those patients have been re-contacted by phone to identify their willingness to fill in all variables in Memobayi.com. Several feedbacks have occurred such as the font in the application is too small, unfamiliar with medical terms, variables that have to fill are too much, and too busy (RY, 30; T,19).

4. Discussion

This study assessed the extent to which parents were ready to implement emerging electronic technology to monitor their infant's health status. The findings indicated that most respondents had less access personally to the internet thus they were not comfortable to fill in Memobayi. The key to success to increase the completion rate of a survey that is an adequate number of questions, respondent-friendly questionnaire design, and occupant-addressed correspondence (Fung & Hays, 2008).

Furthermore, technology adoption suggested that in some health settings, a variety of training programs have been initiated both for health providers and patients. Some studies revealed that the passage of ePROs needs more than five times training programs to be accepted among the patients [1]. If the basic approaches to such initiatives are slow to be taken, more creative practices are reluctant to be attempted.

Promoting ePROs by health providers may increase the completeness of ePROs. Doctors need to encourage the ePROs data into the health consultation by conducting reference to the fact that the patient had completed the ePROs' questionnaire, either through stating the patient had completed the questionnaire, thanking the patient for completing the questionnaire or asking how the patient had 'got on with' or 'found' completing the questions [10].

A review of the demographic profiles of patients in this study may suggest some possible reasons for non-utilization of web-based communications. Over 50 percent of the patients were staying at home while highly educated (50 percent had earned a graduate degree). This accomplishment did not translate to advanced internet proficiency. The findings point out the importance of acknowledging the digital divide among generations when new Electronic Patient-Reported Outcomes technologies introduced.

5. Conclusion

The study reveals that there still challenges for responders in Ciparay's Sub-District in adopting an ePROs, Memobayi.com. Not all patients are comfortable or knowledgeable with even the underlying technology. Although the intervention strategy has conducted group and one-on-one training to facilitate the adoption of technology in the health domain, these strategies still not entirely successful in promoting the adoption of electronic medical records filled by the patients. Active communication pathways to encourage disease prevention for the children need to be adopted both by health-care providers and their patients to increase the completeness of the pros. Furthermore, given the potential role of health-care provider in providing an ePROs technology to attract and influence patients' awareness. It would be essential to continue this line of electronic communication and outreach by engaging a broader population, particularly the digital divide.

Acknowledgment

We express our gratitude for the hard work of PT. Perina Medika Utama especially Mr. Meifi and Mrs. Fanny with constructing the patient-reported outcome, hosting the web-servers and their expertise in corporate web-based studies. Our gratitude has also delivered for all health providers and patients in Primary Health Care in Ciparay's Sub-District.

Conflict of Interest Statement

All authors have no potential conflicts of interest to report.

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