Introduction
(To comply with my non-disclosure agreement, confidential information has been omitted/obfuscated. The information here is my own and does not necessarily reflect the views of Philips.)
Primary care in Kenya poses several challenges; some of which is less access to care in remote areas, under-use of primary care facilities due to late diagnosis, leading to crowded secondary and tertiary care facilities, and hence sub-optimal care to people who need it the most in crucial times. To help optimize the use of primary care, there are programs in place where an appointed member of a community volunteers to go door-to-door and screen people for pre-diagnosis, leading to early referrals for those who seem to be at risk of a condition.
Philips was developing a new technology that monitors vital signs in an easier way, and can be embodied in devices that might improve quality of screenings, reduce effort of community health volunteers, and support them in decision-making.
For my Master graduation project, I did an early stage research to understand how Philips should the design the devices and service around it. I combined my field research with another student's graduation project (on sustainable business model), and we both participated in executing each other's study in Kenya (Nairobi).
Keywords:
Screening devices, Decision support, Accessible health, Primary care, Low-resource setting, Field research, Mixed method approach, Sustainable business
[The above image was given to me as introduction to project, and is not my work. Credits remain with the illustrator].
Research questions
This work consisted of several goals, all contributing to development of these smart devices.
Primary research question: How can we design these devices such that the new technology is accepted and adopted by the community health volunteers, and other stakeholders?
Secondary research question: What are the opportunities of building a (sustainable) business around these devices? What value can connected devices bring to the ecosystem of primary-secondary healthcare in Kenya?
Project outcome
Key outcomes of my thesis project were:
- Product design guidelines for the devices
- Technical guidelines for decision-support feature
- Understanding of user and product aspects that might influence the acceptance of a new over existing technology
Other outcomes from field research (combined with colleague's thesis):
- Service design guidelines for the smart screening devices when used in professional healthcare and community settings
- Uncovering the pains of stakeholders involved in the business model of such a device, and their motivations
- Understanding the challenges posed by existing referral system (structurally and in practice), by the difference in context of use (environment, facility infrastructure), and culturally (interpersonal trust)
Research methods and process
I used a mixed-method approach; quantitative research to extract key predictors of technology acceptance in this context, and qualitative research to extract design and service requirements.
Highlights of the process:
- Identified main factors that might influence technology acceptance: From literature research and existing know-how of the topic within the company, I found key interpersonal factors like trust and privacy important when a healthcare professional or voluneteer interact with a person. Other factors key in determining how a technology might be perceived was individual's background (like, education, medical expertise), and technology factors (like, usability, accuracy in measurement).
- Mock-up of a measurement device, and questionnaire design: To prepare for the field research, we 3D printed a non-functional mock-up (this was NOT a clinical study). And we designed a questionnaire keeping in mind that our participants were probably not exposed to filling such a questionnaire before.
Used 7-point Likert scale with clear labels. Language was English (populary spoken in Kenya), checked for understandability by double translation (English to Swahili by one native, and back to English from another one).
- Semi-structured qualitative research setup: Designed the setup to accommodate the uncertainty related to access to participants (which could include patients, community health volunteers, professional nurses and doctors). For confirmed participants, we covered the most important research questions. The questions which were of secondary importance and those that arose in the field, we answered them by adapting our study setup on-the-go.
- Conducted interviews and questionnaire study: Over a course of 2 weeks, we received answers from almost 70 participants to our questionnaires, and we interviewed approximately 20 nurses and community volunteers. For my colleague's study, we conducted a workshop with stakeholders and prior to that, interviewed them. Stakeholders included healthcare facility owners, device distributors, eRecycling company, mHealth entrepreneurs, and policy makers. Depending on the setup and comfort levels of our participants, we interviewed either in groups or one-on-one.
- Quantitative and qualitative analyses: To model indicators of technology acceptance, I used the tool MPlus to do a Structural Modelling Equation analysis for data acquired by questionnaires. This analysis resulted in a model that suggests which device and personal attributes might determine whether a technology will be accepted or not.
Device characteristics: efficiency in measurement seems to positively affect perceived usage and (indirectly trust), impact on patients' feeling of nervousness (due to placement of the device on chest) seems to negatively affect trust, and other external factors (unexplained variance) have positive affect on trust.
Health-worker characteristics: General trust in technology leads to high perceived trust (not surprising), and if the health-worker feels intimidated by technology, they tend to perceive it less easy to use and useful. Community health workers were more intimidated by technology than professional nurses.
The qualitative analyses of interview data gave design and service requirements for design of such devices, and the service around it.
What I learnt:
I've been fortunate enough to conduct field research in a variety of settings with different types of people. In Kenya, cultural differences and a flexible working approach posed special challenges for me.
Highlights of my learnings from this project:
- Learnt a great deal on how to be sensitive to the cultural nuances (e.g., body postures).
- Due to the project collaboration, got a taste of sustainable business modelling.
- I valued how our team worked hard to make the most of the time we had there, grabbing every opportunity to win interviews with local stakeholders.
- Experienced on-the-go adapting and extending the research setup, and recruiting in a 'street smart' way.
- Got some insights on what might or might not work in mixed-method approach in such a setting.
