The Kenya Health Workforce Project
Transcript of The Kenya Health Workforce Project
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The Kenya Health Workforce
Project
Dr. Martha Rogers
Project Principal Investigator
Emory University
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Situation in Sub-Saharan Africa
• The demand for health workers is increasing
• While supply is decreasing
Many countries are facing a shortage of healthcare manpower.
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Problem for Health Managers
• Need to manage workers efficiently
• Which requires data for planning and making decisions
BUT
• Lack informatics systems to generate data
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Project Objectives:
• Establish an electronic health workforce informatics system that could be used to analyze workforce capacity at MOH and regulatory agencies
• Assist Kenyan leaders in HRH management, research and policy development
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Why was the project needed?
• Kenya healthcare workforce data existed in paper forms only
• MOH lacked accurate data on the number of health workers by position, cadre/ qualification, region or rate of attrition
• Checking reliability of data was labor and time consuming
• Kenyan training institutions lacked data on the training and staffing needs of health professionals
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Situation in Kenya
Many different
qualifications exist for
nurses
+
Many nurses have
multiple qualifications
Difficulty tracking nurses
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Workforce Dynamics
Supply: the available number of healthcare workers (e.g., nurses)
– Those in training
– Those trained outside Kenya migrating in
– Those lost through attrition (death, retirement)
– Those migrating out of the country
Demand: deployment, worksite requirements for HRH, provider:population
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Who has this information?
Supply: Data kept by regulatory agencies (e.g., Nursing Council of Kenya)
– Indexing, licensure, registration, and retention
– Application to work in Kenya or to verify
license to work outside Kenya
Demand: Staff returns from MOH facilities and private and mission healthcare sector
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The Process• First Step: form a steering committee
with representatives of key stakeholders for input– Inform stakeholders of the need
– Gather input, needs, and ideas
– Use as ongoing network for dissemination
• Day-to-day decisions made by smaller groups– Policy sub committee
– Technical subcommittee
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The Process
• Hardware needs were assessed
– Computer workstations including computer,
printer, power back-ups were installed
– Satellite dish was placed on the roof for
sending signals through the Internet
• Data user needs assessed for development of software program
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The Process
Software program was developed with the following database system features:
�Flexible to expansion and revision
�Information can be used to produce a wide variety of reports
�Can be decentralized in different regions/countries
�Different people can use the system simultaneously
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Phase I: Supply Side
Convert hard copy data at the regulatory agency (e.g., NCK) to electronic data
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Network MOH to the regulatory agency via satellite equipment
Phase II: Link with MOH
NCK CNO
NCK=Nursing Council of Kenya
CNO=Chief Nursing Office, MOH
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Phase III: Deployment Side
Design system for capturing data from health facilities
– Assessment of hardware and data user needs
– Development of software program for data
capture and analysis
Roll-out to provincial level
– Sensitization of health managers necessary
– Training of data entry staff
– Workshop for district-level managers
emphasizing role in data collection
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Roll-Out to Provinces
Coast
Rift
Valley
Nyanza
Eastern
Nairobi
North
Eastern
Central
Western
CNO
NCK
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Kenyan Nurses Age <55 by Cadre
1%
64%
35%
Enrolled
RN
BSN
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Newly Trained Nurses: 2005-2007
90%
5%5%
Enrolled
RN
BSN
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Ratio of RNs to Population
9773287Western
11162891Rift Valley
9182783Nyanza
29937754N Eastern
7172394Eastern
14584054Coast
5211441Central
9752097Nairobi
No. People per
Any Nurse
No. People
per RN
Province
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Use of Provincial Data for Planning
of HIV Care
Nyanza Province has the highest prevalence of HIV (15%) and lowest prevalence of circumcision (46%).
– Population age 15-49 2.6 million
– Estimated no. needing HIV Rx 35,000+
– No. needing circumcision 600,000
Task shifting is being proposed to allow for more HIV+ people to received ARVs.
Male RNs could be trained to do circs.
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RNs in Health Facilities
Nyanza Province
855 RNs in Nyanza Province
– 63 hospitals 74%
– 141 health centers 11%
– 332 dispensaries 4%
193 (23%) RNs are male
– 3000+ uncircumcised men per male RN
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In-Country Coordinator
Ms. Agnes Waudo
District Health
Offices
Programmer
Mr. Andrew Kamenju
Hardware-IT
Mr. Japheth Ngoya
Program Analyst
Mr. John Arudo
Organizational Structure
Dr. Martha Rogers, PI
Provincial
Health Offices
Health Facilities
US Federal
Funding
Agency
US University
Provides Oversight
of the Project
Kenya
Ministry of
Health
Kenya Professional
Regulatory Agencies
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Future Plans
• Create informatics systems for other health cadres
• Build capacity for healthcare managers to be able to fully utilize the data to better manage their human resources
• Publish annual reports for all cadres that can be widely distributed
• Disseminate to other countries
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Kenya Project TeamAgnes Waudo Japheth Ngoya
In-Country Director Project NetworkerEunice Masamo Andrew Kamenju
MOH Coordinator Project Programmer
John Arudo
Program Analyst
CDC Technical AdvisorsRebecca Bunnell, Director Tom Oluoch
CDC-GAP-Kenya CDC-GAP-KenyaPatricia RileyCDC-GAP-Atlanta
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Thanks !
Asante Sana!