DL Seminar | Privacy and Equity in Developing Countries
Updated: Jan 8, 2019
By Natalie Friedman & Julia Narakornpichit | MA Students | Cornell Tech
On Thursday, November 8th, we had the pleasure of listening to Fabian Okeke’s talk entitled “Privacy and Equity in Developing Countries.” Okeke (pictured above) is an Information Science PHD candidate and a DLI Doctoral Fellow. He focuses on healthcare in underserved settings and tries to understand how we can design technology to improve healthcare opportunities.
Okeke began the talk with a story about a serious pain in his left leg. He explained that he used Uber to go to the hospital, saw the reviews of his Uber driver in advance, then chose a doctor based on reviews as well. He was able to look at reviews of various institutions in order to make an informed decision. This he explained, is a luxury, as the reviewers have the freedom and incentive to be honest via this platform while he has the freedom to make decisions based upon these reviews. He explains that people in Kenya do not have this freedom to give reviews nor the proper platform to access this.
Okeke studied the feedback practices within villages in Kenya for three weeks, where he spoke with community health workers, their supervisors, and care recipients. He determined how feedback from care recipients were being collected, used the challenges that arose when collecting feedback. From his time in Kenya, he learned that feedback was collected by community health workers and the methods of collection prevented honest feedback. Feedback was collected through three methods: 1) phone calls, 2) informal reports, and 3) chance encounters. Phone calls were a formal method of feedback collection and were made directly to the care recipients asking about the services they received and how they could be improved. This method proved to be problematic as it lacked equity; Not all care recipients have mobile phones and the feedback collected was mostly a check that the health workers were doing their jobs. This was instead of understanding the care recipient’s experience with the caretakers.
Informal reports were also used to collect feedback. These were directly communicated to a care provider. This method was also problematic due to lots of biases and a lack of privacy. If care recipients found the care to be bad, they may not give candid feedback out of politeness. However, if they were candid and provided negative feedback, the care worker may not give the feedback to their supervisor, leading to no improvements.
Lastly, a somewhat successful form of feedback were chance encounters. This meant that when a citizen ran into a health worker wearing a community shirt, the supervisor could collect verbal feedback. A potential problem with this form of feedback was recall bias, as the supervisor’s selection from his memory may be skewed. In addition, it is based on chance and therefore difficult to depend upon.
All feedback collected could potentially be used to motivate other health workers through praise and positive stories to improve training programs. From his research, Okeke came to the conclusion that the feedback being collected is not systematic, not equitable, and lacks privacy. In order to resolve these challenges, feedback collection should be phone agnostic, anonymous, and formalized. Some solutions he recommended were an Interactive Voice Response system (IVR) for those who are illiterate and a Unstructured Supplementary Service Data (USSD) which allows citizens to use a phone to access a feedback center without having a smartphone. Okeke ended the talk with acceptance that there is much more to be done and hope for the community’s healthcare.