1. Louis Fazen Benjamin Chemwolo Astrid C Deb

2. Background  The Academc Model providing access to health care (AMPATH) was established by a partnership of Moi University, MTRH and consortium of NA Universities led by Indiana Universty for HIV care initially.  Now involved in Primary Care using governent KEPH stragegy in North Rift Westerb abd Nyanza prvinces

3. Rationale Community Health Workers (CHWs) are vital to the health of their communities. We wanted to strengthen their ability to make health decisions and link women and infants to care through the use of clinical decision-support on mobile phones. By extending our electronic medical record system to CHWs, we wished to show how quality of care can be improved.

4. Objective Addressing maternal and newborn health is complex in the setting of poverty and weak health systems Seek to capitalize on existing mobile phone literacy and network connectivity in Kenya to support CHWs in clinical decision-making, referrals and the follow- up of patients. By integrating clinical decision-support (CDS) with an electronic medical record of >20 million encounters, we will extend centralized health information systems into the community. This new model of health care delivery is timely given Kenya's expansion of CHWs.

5. Justification The scope of maternal and newborn health is broad and encompasses such services as birth planning, PMTCT, malaria prevention, labour accompaniment, newborn care, referrals, breastfeeding and safe water promotion. Completing these tasks is challenging. Paper-based algorithms and data collection may not be effective when the environmental costs and time necessary to analyze the data are considered.

6. Justification CHW tasked with completing 150 questions, assessing 9 diagnoses, counseling on family planning and nutrition and ensuring follow-up to high-risk clients across 50-100 households. USAID evaluations in Rwanda have demonstrated CHW performance declines with number and complexity of tasks. CDS software may help CHWs to prioritize workflow, simplify form entry, and decrease the questions required per household. CDS has been shown to reduce medical errors as well as improve documentation, information retrieval, guideline adherence, disease management, and health outcomes (Tomasi 2004, Garg 2005).

7. Scientific basis The most effective components of CDS— system-initiated information, actionable recommendations, and point-of-care support —can be designed to support CHWs using a mobile device. By running simple logic rules on longitudinal patient records, a CDS system can structure static guidelines into dynamically-generated, patient-specific ‘smart forms’ on mobile phones.

8. AccessMRS: Overview  Developed new software application to allow CHWs to access clinical data on mobile phones  Focus on security of all patient data  Full encryption of all patient data on the phones  Encryption of all data transmitted to and from phones  Ability to manipulate phones remotely in case of lost or stolen phone  Ability to transmit forms from mobile phones directly into the patient’s record in the AMRS Medical Record System

9. AccessMRS: Clinical Dashboard  4 Client Lists  Organization of Clients into lists with incomplete, complete, or suggested forms  Reminder to refresh patient data  Ability to add new patients in the field

10. Example: List of All Available Clients  Basic Demographic Data  Search by Patient Id or Name  May always add a new client if not found in database  Clearly Display Saved and Suggested Forms

11. Patient Dashboard  Demographic Data For Patient Identification  Access to Clinical Forms and ability to fill them out on device  Access to Clinical Data from AMRS EMR  Authorization process for viewing clinical data  Access to all Previous Form Encounters

12. Pre-populated Patient Forms  Launch Form Entry from within the patient dashboard  Forms are pre-populated with patient data:  Demographic details  Pertinent Past Medical History  Allows for Faster Form Entry

13. Results Currently 97 android phones have been provided to community health volunteers in Kosirai Division Programming and training of CHVs already done. Data collection using the electronic clinical encounter forms has begun with linkage to AMPATH Medical Records System. The pilot is currently on-going with planned scale-up to a new site in Bunyala District

15. Lessons learnt  There is evidence that it is cheaper than paper based so it makes sense to take to scale  We plan to role out a phone based emergency alert system, with CHVs connected to community taxis and health facilities: the Mother Baby Health Network.

16. AMPATH-Plus mHealth-Use of mobile technology to improve health in the community by CHVs

17. It takes a village...

18. Acknowledgements  The Grand Challenges Canada  The ministries of health Kenya and the DHMT, and community units in Kosirai Division  Staff of the mHealth project  AMPATH staff