Assignment on LITERATURE REVIEW of opportunities for leveraging health information technology

This chapter describes the evidence base and components associated with diabetes, DSM approaches, and health IT. It begins with an outline of the approach taken to collate the relevant literature.

2.1. Approach of explore healthcare professionals’ perceptions and experiences about opportunities for leveraging health information technology

Initially, the relevant literature was examined for applicable evidence to the study topic. At first, the search criteria included the online data resources available on MEDLINE and Google Scholar then, they were extended to Embase, Web of Science, and ScienceDirect (23). Only publications in the English language were included and considered.

The research questions were constructed using the Population, Intervention, Comparison, and Outcome (PICO) framework (24), to facilitate specific literature recovery. The keywords used for research were “Diabetes Mellitus”, “Self-Management”, “Health Behaviour Theories”, “Information Technology”, “melt”, “Mobile Health Applications”, and “Health Literacy” concerning DSM and MHAs to ensure coverage of relevant topics concerning the primary research question.

2.2. Diabetes of explore healthcare professionals’ perceptions and experiences about opportunities for leveraging health information technology           

Diabetes can be thought of as a combination of metabolic diseases characterized by high blood sugar levels associated with dysfunction and failure of body organs in the long-term because of hyperglycemia. The long-term complications of diabetes include nephropathies, retinopathy, cardiovascular, and cerebrovascular events (25). Research often finds high blood pressure and high cholesterol levels in patients with diabetes.

Diabetes is a global epidemic and has been spreading in the Middle East region. According to the International Diabetes Federation (IDF), 425 million people have diabetes in the world and over 39 million people in the Middle East and North Africa (MENA) Region; by 2045 this will rise to 84 million (26). In the State of Kuwait, the prevalence is 9.2 percent which is the second-highest of all IDF regions (26, 27). In 2016, the four major non-communicable chronic diseases including cancer, chronic lung disease, cardiovascular, and diabetes contributed to two-thirds of mortality globally (28). The IDF also reports that diabetes was responsible for nearly 373 000 deaths in the MENA Region in 2017 (26). In Kuwait, there were 441,000 cases of diabetes in 2017 (29), with a prevalence of diabetes in adults of 15.1 percent (26), which is an increase from 12.4 percent in 2006  and a reported 7.6 percent in 1996 (30).

With the high prevalence rate and an extensive list of complications, diabetes has created a massive burden on healthcare systems worldwide, especially in developing and under-developed countries. The estimated costs of healthcare worldwide concerning diabetes have accounted for as much as USD 727 billion for the age group 20-79. If the predicted prevalence for 2045 is accurate, this cost could reach as high as USD 958 billion (31). In the MENA region on average, 17 percent of the total healthcare budget was provided to diabetes which is the highest percentage from all the IDF regions (26). Published data regarding the financial impact of diabetes on the MENA area is sparingly available. The individual cost of diabetes treatment in Kuwait is estimated to be $2,000 annually (26).

Diet, lifestyle, and high income are the reasons behind obesity and comorbidities, such as diabetes in the Kuwaiti population (31, 32). Besides this, the eating habits in most Kuwaiti households are characterized by high fat and low fiber foods which have aided in the rise of this phenomenon (32). Thus, Kuwait has the eighth highest incidence of obesity and is the ninth-ranked country for diabetes globally (33, 34), with the prevalence predicted to double by 2030 (35). It is estimated that around 40 percent of Kuwaiti citizens have diabetes or pre-diabetes (36).

Considering the prevalence and the percentages of people with diabetes, the Middle East region stands out as number one. Alarmingly, the prevalence keeps increasing every year. This high prevalence of diabetes puts the burden on the healthcare system thereby needing a more novel approach that relies on empowering patients with DSM skills.

2.3. Diabetes Self-Management of explore healthcare professionals’ perceptions and experiences about opportunities for leveraging health information technology

Diabetes is a chronic disease, which needs life-long medical assistance and Self-Management. DSM has been an important component of managing diabetes since the 1930s (37). Unfortunately, 50-80 percent of individuals lack the essential skill for DSM; the recommended HbA1c (of 6.5 percent) is reached by fewer than half of the patients with type 2 diabetes (38).

Although diabetes care has dramatically improved in recent years (e.g., continuous blood glucose monitoring devices), the outcomes for many patients are still not satisfactory. Patients with diabetes must play a vital role in self-managing their health conditions. Evidence shows that chronic disease patients such as patients with diabetes when empowered with DSME are more likely to show adherence to their treatment regimens (39-41). DSME is also associated with better blood sugar levels and positive clinical outcomes.

Many technologies have appeared to provide DSME to patients as an alternative to traditional care (45). Interactive software can provide a tailored and self-paced education (46), that is enhanced with automated telephone calls, which has been shown to improve SM and adherence (47). When used as a tool, the internet has the potential to reach a large population and internet novices are happy to be part of an internet-based SM plan (48, 49). One study on the internet model of SM has correctly shown a noteworthy behavioural change linked to improved physical activity (50).

Although DSM has proven to be one of the more difficult chronic conditions to encourage DSM, its importance rests in improved outcomes; evidence shows that using modern-day tools like enhanced communication technologies has a positive impact on results. Studies show that telephone calls regarding SM support can improve the health of patients with chronic diseases and can even serve as a replacement for a visit to their medical caregiver (42). In brief, DSM is a multi-faceted process involving a multi-directional approach. DSM can only be successful when a broad and coordinated diabetes care approach is implemented (43).

One further example of DSM in coordinating patient care, tracking personal health variables, plays a vital role; for example, monitoring blood sugar levels more frequently is linked to long term improvements in HbA1c levels (44). When considering DSM, one cannot complete the debate without considering the theory of health behaviour change intervention (45). This technique suggests that SM, in applying feedback on the collated data, can be a crucial component of behaviour modification (46). This also holds true for other chronic diseases regarding technology-based interventions that are in-line with health behaviour change models (47).

2.4. Theoretical Building Blocks for Self-Management Informatics

For DSM to be effective, it is essential that the tools supporting it consider cognitive and behavioural theories. A systematic review of informatics-based interventions concluded that theories such as self-determination, planned behaviour, social cognitive, and the transtheoretical model of behaviour change are the most popular and influential theories for designing DSM interventions (48). Given that health informatics is a vast field established over many years, it is not surprising to find that there are many theories on health behaviour change that involve interventions for health (49). In the following subsections, there is an exploration of some of the most salient theories relevant to this research.

2.4.1. Social Cognitive Theory (SCT)

Social Cognitive Theory (SCT) is linked to the work of Bandura (50) in association with social learning theory, particularly related to various motivating behaviours of humans and the social factors influencing human actions. Bandura states:

“People gain an understanding of causal relationships and expand their knowledge by operating symbolically on the wealth of information derived from personal and vicarious experiences. They generate solutions to problems, evaluate their likely outcomes, and pick suitable options without having to go through a difficult behavioural search” (50).

In recent works, SCT has served as the basis for interventions focused on weight-loss (51) and the cessation of smoking behaviour (52). DSME programs usually include behaviour change theories like SCT as they can predict adherence to diabetes-related interventions such as DSM and lifestyle changes.

2.4.2. Self-Determination Theory (SDT) of explore healthcare professionals’ perceptions and experiences about opportunities for leveraging health information technology

Self-Determination Theory (SDT) emerged from the work of Ryan and Deci (53) which differs from SCT, in that SDT is associated with human behaviour regulated by inner resources. SDT proposes continuity in the autonomy of human behaviour regulation and the extent to which a person’s actions are internally motivated. More of this motivation leads to better performance and a more positive coping style (53).

Informatics applications based on SDT appear to depend on a human's internal motivation, e.g. adherence to medicine and monitoring blood pressure (54). Furthermore, it depends on humans' sense of autonomy by making them focused on their logic of more exercise and activities (55). SDT supplies a framework or platform, so that integrating behaviour science theory may enhance the efficiency of MHAs aimed at changing behaviour.

2.4.3. Theory of Planned Behaviour (TPB)

The Theory of Planned Behaviour (TPB) revolves around intention and action; it addresses voluntary behaviours. In this approach, it relates to humans having a choice to engage or not in a specific behaviour (56). According to Ajzen (56), an individual’s past behaviour has an indirect influence on their future behaviour and thus, contributes to the formation of habits.

TPB has contributed towards many human behaviour interventions, such as improving health behaviour, increasing awareness about social norms, and helping humans gain a higher behavioural control (57). Regarding the use of TPB as an informatics intervention, we may use it as a basis for compiling messages conveyed by text messaging (SMS) or emails (58). One example of this is Kothe et al. (59) who used TPB to help students take part in a nutritional program. TBP might be most often used for persuasion and information with repeating skills, which are often used less, and for setting goals. Thus, the researcher concludes that by using MHAs, patients with diabetes could be informed and persuaded to practice DSM.

2.4.4. Transtheoretical Model (TTM)

In consideration of the concept of persuasion, the Transtheoretical Model (TTM) describes behaviour changes as stages of change (60). These stages are shown in Figure 1 below:

      I.        Pre-contemplation, where individuals do not feel the need to change and have no thoughts of changing.

     II.        Contemplation, where individuals recognize the possibility for change and consider the outcomes if actions were undertaken.

   III.        Preparation where the individual plans to take any action and may take a few steps towards it.

   IV.        Action, where the individual implements processes that might start a change.

    V.        Maintenance, where individuals endeavour to persist with new behaviours and/or take steps to prevent a relapse into the earlier behaviour.

   VI.        Relapse, where one falls back into old patterns of behaviour.

Regarding informatics interventions, one way to apply TTM for chronic disease SM would be to assess the patient's willingness to change, asses the stage, and tailor the message to the appropriate stage needs and challenges (62). The “stage of change” refers to the stage in the cycle when the person adopts at positive change. Interventions based on the TTM have been effective in promoting and supporting physical activity in several populations, including people with type 2 diabetes and chronic heart disease. TTM based interventions tailored to individual needs have been shown to facilitate positive outcomes like cessation of smoking, an increase in physical exercise and even recovery from drug addiction (63).

2.4.5. Problem Solving Model (PSM)

Finally, Hill-Briggs (64) adopted a Problem-Solving Model (PSM) to explain how an individual sees and overrides an external hurdle to achieving a needed self-management behaviour. PSM appears to be a growing area of interest in chronic disease self-management, especially in diabetes. While all the previous theories are relatively generalised in their application, PSM might appear to be the most effective framework for diabetes self-management (65, 66). The American Association of Diabetes includes PSM as an essential part of DSM (67). Evidence suggests that informatics interventions have shown improvement in a patient's psychosocial outcome and blood sugar level concerning DSM (67-70). To summarise, training patients to manage their chronic disease is a challenge for healthcare professionals. Furthermore, patients with diabetes require a higher level of DSM. One way of achieving this level of DSM may be through MHAs (71).

2.5. Mobile Health Apps (MHAs)

Technology has advanced, and now there are many innovations to help SM (72). In the developed world, the demand for innovation and creativity has increased in the last decade. Because of high financial costs, the developed world is facing a crisis concerning paying for healthcare (73). These high costs are due to several factors including an ageing population, the increase in chronic diseases, and fewer medical staff (73, 74). It is important to note that the data from the Arab world related to the financial burden on healthcare is not much available. In this respect, it is worth mentioning the Arab Human Development Report devoted to ‘knowledge acquisition deficit’ and in 2009, another series of papers released under the heading ‘health in a troubled region’ devoted to the Arab region. However, the researchers did not highlight the burden of diabetes in the region. (75)

Diabetes does not only pose a burden on healthcare but additionally can impact both the patients and their families not only because of treatment costs but also because of fewer working hours and concurrent social implications (76). This considerable cost and its related social implications highlight the significance of the issue. Thus, healthcare in the MENA region should work on early diagnosis and DSM due to the alarmingly high prevalence of diabetes (76). With the noted high cost and its significant increase in per capita costs, the disease has become a significant challenge for healthcare systems and a clear obstacle to sustainable economic development in the region.

Although the health sector is known for its innovations in improving quality of life, diagnostic, and treatment options (77), it must think outside of the box to be cost-effective.  Information Technology (IT) may be one of the saviours to help with these burdensome costs. Buntin (78) demonstrated that 92 percent of recent health IT articles demonstrated positive outcomes; eHealth has become the new terminology for the use of health IT (79). Furthermore, with the growing use of smartphones, a new horizon of eHealth has emerged: mHealth (80, 81).

According to the Global Observatory for eHealth, mHealth is defined as “medical practice with the help of mobile gadgets for healthcare” (72, 82). In the implementation, the broad idea of eHealth and mHealth cannot be segregated (83), with nearly 4.7 billion people using mobile phones and an estimated 1.08 billion people now own smartphones (84). An estimated population of 500 million uses MHAs (a component of mHealth) for chronic disease management, diet, and sporting activities (85). The uses of MHAs to help with DSM in patients are unprecedented. Currently, 100 000 MHAs exist in Google and Apple app stores (84). Amongst all health conditions, the most targeted condition by these MHAs is diabetes, followed by depression and asthma (84).

Thus, these MHAs can provide a valuable medium for promoting health and can be viewed as potential steps towards global wellness. According to the mHealth Alliance:

“Mobile devices everywhere in the developed or developing countries provide the opportunity to improve health outcomes by providing innovation in healthcare and healthcare services to remote areas of the world”(86).

Started during the 20th century, mobile devices have improved communication. Perhaps the most crucial benefit to MHAs is that it could link patients and healthcare professionals more readily and easily and from any distance (86). Accordingly, there are high hopes for MHAs and these may indeed be viewed as a game-changer for healthcare by shifting the overall paradigm from emergency intervention to health promotion and SM (87).

As a game-changer, it has been quoted as “the biggest technology breakthrough of our times” by the US Secretary of Health and Human Services, Kathleen Sebelius (88). However, the adoption of mHealth has been slower than expected (89, 90) because of multiple factors such as barriers at the policymaker level or the individual nature of medical professionals (90). Wu (89) has emphasized the need for further studies to explore the adoption, demand, and the promotion of MHAs in healthcare. Text messaging has resulted in improved diabetes management and is acceptable to many patients (91). Additionally, it has demonstrated a positive diabetes self-efficacy and also treatment adherence (92). A meta-analysis of mobile phone interventions in patients with diabetes found a reduction in HbA1c of 0.3 percent for those in those studies, including patients only with Type 1 Diabetes (93). Likewise, a reinforcing meta-analysis found a reduction in HbA1c of 0.5 percent by using MHAs for DSM (94) and showed that 7.8 percent of people with diabetes having a smartphone is currently using MHAs for DSM (94).

Given the increasing prevalence of diabetes in Kuwait, it is vital to challenge the traditional approaches towards DSM. The use of novel self-care tools like MHAs may aid and help turn the tide for healthcare problems. Technology that aims to involve patients in DSM and optimize the role of healthcare professionals, may ease a more robust, scalable and practical approach to the management of diabetes. In today's developing world, modernism to cope with challenges of healthcare through IT such as MHAs is a continuing need. However, to date, the adoption of this innovation appears slow. Information on barriers and enablers for this is minimal (90). According to a report by Marrero et al., they highlight the significance of applying multiple strategies and systems to promote behaviour change in patients with diabetes (95). Evidence indeed suggests that MHAs can deliver health services and SM tools, and overcome several key barriers that prevent ongoing access (96).

MHAs might even become a replacement for face-to-face diabetes intervention delivery and support. These MHAs offer patients the freedom to process and communicate data in real-time (97). A meta-analysis of 22 intervention studies concluded that MHAs interventions delivered a significant improvement in sugar levels and patient DSM (94). Additionally, a Cochrane review of computer-based DSM interventions found a small but beneficial effect on blood sugar levels in contrast to the more substantial impact noted for MHAs interventions. Reviewers concluded that mobile phone interventions might be more likely to show short-term health benefits, but this can go off by time, still, a technology-based intervention can reinforce the benefits of SM (98). Keeping in mind the literature's emphasis on the advantages of technology breakthroughs, the researcher argues for more effectiveness due to convenience and greater cost-effectiveness of these interventions, to reduce and contain the current load on healthcare (99).

In summary, the evidence from the literature suggests that it is worth exploring the challenges and opportunities of MHAs to engage healthcare professionals in treating patients with diabetes.