The Kenya Health Workforce

Project

Dr. Martha Rogers

Project Principal Investigator

Emory University

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.

Problem for Health Managers

• Need to manage workers efficiently

• Which requires data for planning and making decisions

BUT

• Lack informatics systems to generate data

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

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

Situation in Kenya

Many different

qualifications exist for

nurses

+

Many nurses have

multiple qualifications

Difficulty tracking nurses

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

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

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

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

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

Phase I: Supply Side

Convert hard copy data at the regulatory agency (e.g., NCK) to electronic data

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

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

Roll-Out to Provinces

Coast

Rift

Valley

Nyanza

Eastern

Nairobi

North

Eastern

Central

Western

CNO

NCK

Kenyan Nurses Age <55 by Cadre

1%

64%

35%

Enrolled

RN

BSN

Newly Trained Nurses: 2005-2007

90%

5%5%

Enrolled

RN

BSN

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

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.

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

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

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

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

Thanks !

Asante Sana!