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Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method By Dr. Otilia Gowelle, DHR Department of Training and Human Resource Development In collaboration with CUAMM November 2015
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Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Jan 18, 2018

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Mitchell Sutton

Our Big Concern: Is there adequate staffing to offer quality Services in health care facilities to meet the service guarantees under HSSP IV and MMAM?
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Page 1: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities:

A Case Study of Ludewa District in Njombe using WISN MethodBy

Dr. Otilia Gowelle, DHRDepartment of Training and Human Resource Development

In collaboration with CUAMMNovember 2015

Page 2: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Context and Background

HSSP IV has provided certain targets to provide universal health coverage

MMAM promises for a village level to have dispensary, Ward level to have a HC, and District level to have a Hospital

HRH is important for morbidity and mortality reduction

Demand vs. Supply of workforce is not tallying

Page 3: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Our Big Concern:

Is there adequate staffing to offer quality Services in health care facilities to meet the service guarantees under HSSP IV and MMAM?

Page 4: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

About WISN Method

WISN- Workload Indicators of Staffing Need A method of setting the correct Heath Facility staffing

levels. Developed by Shipp (1998) and popularized by WHO Tried in Tanzania, Papua New Guinea, Kenya,

Botswana, Namibia, Zimbabwe, Hong Kong, Turkey and Bangladesh

Page 5: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Advantages Optimal Allocation and deployment of current staff

geographically according to volume of services Optimal Allocation and deployment of current staff functionally

between the different types of health facilities or different health services in district

Staffing patterns and levels (categories and numbers) in individual health facilities according to local conditions (morbidity, access, attitudes) and not based on national averages (population ratios and standard staffing schedules)

Useful for both medical and non-medical administrators at all levels of the health service

Simple to operate and use, technically acceptable, comprehensible and realistic so that results are acceptable by non clinical manager.

Page 6: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

What has been done so far? Training of trainees (TOT) has already been

organized and training in each step of the WISN method. Orientation has been done to Expert working groups

from regions and districts and Workload components and Activity standards have been developed for data

collection WISN study has been piloted in Ludewa, Shinyanga and

Sengerema District

Page 7: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

WISN Steps Chart

X

Time required for procedure

Service guarantees

Proportion of population requiring services

Total deman

d

Time available per worker

Personnel strength

Total supply of staff

time

Surplus/Gap

Total deman

d

Total supply of staff

time

Interview & FGD

IPHS HMIS & Secondary data

Interview & FGD

HMIS/Record review

X X =

=

_ =

Step-I

Step-II

Step-III

Page 8: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.
Page 9: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

FINDINGS

Page 10: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

WISN calculated per Dispensary, ownership and level, for maternity activities-specific cadre related

Page 11: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

WISN Staff Posted

WISN difference

WISN ratio

Public HC

Manda 0.51 1 0.49 2Makonde 0.27 1 0.73 3.7Mlangali 0.19 1 0.81 5.2

Mean 0.32 1 0.68 3.6

PNFP HC

Nindi 0.41 1 0.59 2.4Mavanga 0.63 1 0.37 1.6Madunda 0.37 1 0.63 2.7

Mean 0.41 1 0.53 2.2

WISN calculated per Health Centre, ownership and level, for maternity activities-specific cadre related

Page 12: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Conclusion The WISN difference column gives us a mean of 0.78 and 0.82 for

Public and PNFP Dispensaries and 0.68 versus 0.53 for Public and PNFP HCs respectively. It means the activities performed at martinity level would only need a fraction of the person actually posted for the purpose. In other words the maternities are overstaffed by 20% at Dispensaries and 40% (in mean) at HC level.

Conversely, the WISN ratio column gives us a mean of 6.92 and 6.40 for Public and PNFP Dispensaries and 3.6 versus 2,2 for Public and PNFP HCs respectively. A WISN ratio equal to 1 means the workload is in balance with the staff posted, the greater the WISN ratio(>1) the lower the workload preassure on the staff as what refers to the current service utilisation.

Page 13: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Resuming the assessment results:

The maternity services are overstaffed by 20% at Dispensary and 40% at HC level(mean) or conversely the staff is performing 80% and 60% of the work given the HW’s available annual working time.

The utilisation of service is poor as the staff performs around 80% and 60% (mean) of the work that could be done given the available annual working time

Page 14: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

Recommendations In the presence of government promises to deliver a minimum

package of services, the WISN method should be used as a methodology to calculate the expected demand as well as supply and the gap.

Government health planners should use WISN data to consider the magnitude of staffing increases that would be needed to meet service guarantees.

Our study generated time standards in minutes for each MCH activity developed by experts of the MoHSW. These standards could now be applied to other districts in 16 BRN Regions with slight modification if required.

WISN, then, can provide a useful tool for civil society advocates who seek to hold governments accountable for their health service guarantees.

Page 15: Mapping Adequacy of Staffing to Ensure Service Guarantees for Primary Health Care Facilities: A Case Study of Ludewa District in Njombe using WISN Method.

THANK YOU