Enhancing the Supervision of Community Health Workers With WhatsApp Mobile Messaging: Qualitative Findings From 2 Low-Resource Settings in Kenya.

An estimated half of all mobile phone users in Kenya use WhatsApp, an instant messaging platform that provides users an affordable way to send and receive text messages, photos, and other media at the one-to-one, one-to-many, many-to-one, or many-to-many levels. A mobile learning intervention aimed at strengthening supervisory support for community health workers (CHWs) in Kibera and Makueni, Kenya, created a WhatsApp group for CHWs and their supervisors to support supervision, professional development, and team building. We analyzed 6 months of WhatsApp chat logs (from August 19, 2014, to March 1, 2015) and conducted interviews with CHWs and their supervisors to understand how they used this instant messaging tool. During the study period, 1,830 posts were made by 41participants. Photos were a key component of the communication among CHWs and their supervisors: 430 (23.4%) of all posts contained photos or other media. Of the remaining 1,400 text-based posts, 87.6% (n = 1,227) related to at least 1 of 3 defined supervision objectives: (1) quality assurance, (2) communication and information, or (3) supportive environment. This supervision took place in the context of posts about the roll out of the new mobile learning intervention and the delivery of routine health care services, as well as team-building efforts and community development. Our preliminary investigation demonstrates that with minimal training, CHWs and their supervisors tailored the multi-way communication features of this mobile instant messaging technology to enact virtual one-to-one, group, and peer-to-peer forms of supervision and support, and they switched channels of communication depending on the supervisory objectives. We encourage additional research on how health workers incorporate mobile technologies into their practices to develop and implement effective supervisory systems that will safeguard patient privacy, strengthen the formal health system, and create innovative forms of community-based, digitally supported professional development for CHWs.

Comparison of office visit and nurse advice hotline data for syndromic surveillance--Baltimore-Washington, D.C., metropolitan area, 2002.

INTRODUCTION: Kaiser Permanente of the Mid-Atlantic States (KPMAS) is collaborating with the Electronic Surveillance System for Early Notification of Community-Based Epidemics II (ESSENCE II) program to understand how managed-care data can be effectively used for syndromic surveillance. OBJECTIVES: This study examined whether KPMAS nurse advice hotline data would be able to predict the syndrome diagnoses made during subsequent KPMAS office visits. METHODS: All nurse advice hotline calls during 2002 that were linked to an outpatient office visit were identified. By using International Classification of Diseases, Ninth Revision (ICD-9) codes, outpatient visits were categorized into seven ESSENCE II syndrome groups (coma, gastrointestinal, respiratory, neurologic, hemorrhagic, infectious dermatologic, and fever). Nurse advice hotline calls were categorized into ESSENCE II syndrome groups on the basis of the advice guidelines assigned. For each syndrome group, the sensitivity, specificity, and positive predictive value of hotline calls were calculated by using office visits as a diagnostic standard. For matching syndrome call-visit pairs, the lag (i.e., the number of hours that elapsed between the date and time the patient spoke to an advice nurse and the date and time the patient made an office visit) was calculated. RESULTS: Of all syndrome groups, the sensitivity of hotline calls for respiratory syndrome was highest (74.7%), followed by hotline calls for gastrointestinal syndrome (72.0%). The specificity of all nurse advice syndrome groups ranged from 88.9% to 99.9%. The mean lag between hotline calls and office visits ranged from 8.3 to 50 hours, depending on the syndrome group. CONCLUSIONS: The timeliness of hotline data capture compared with office visit data capture, as well as the sensitivity and specificity of hotline calls for detecting respiratory and gastrointestinal syndromes, indicate that KPMAS nurse advice hotline data can be used to predict KPMAS syndromic outpatient office visits.