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(1)

Productivity of health workers:

the case of Tanzania

Global Forum on HRH Bangkok, January 2011

Ottar Mæstad (CMI, Norway) Aziza Mwisongo (NIMR, Tanzania)

(2)

What is productivity analysis?

• Measurement of outputs relative to inputs

• Outputs: Number of patients

• Inputs: Finances (or health workers, equipment etc.)

Inputs

Outputs

(3)

Why productivity analysis?

• Identify and learn from most productive units

• Allocate resources efficiently and equitably

– Ex: Personell from low to high productive units

Higher output?

More equal workload

(4)

Methods for benchmarking productivity

• Total Factor Productivity analysis (TFP)

Compare each facility to the best performing facility

• Data Envelopment Analysis (DEA)

Compare to high performing – but ”similar” – facilities

Similar size, similar input mix

• Stochastic Frontier Analysis (SFA)

Take into account possible measurement errors in your peers’

productivity levels

(5)

MAP project, Tanzania (2006-10):

Health worker Motivation, Availability and Performance

• 9 rural districts

• 126 health facilities

– 99 with data on number of

patients over time

(6)

Simple productivity analysis

• Input:

– Number of health workers in the OPD

• Output:

– Number of patients treated in the OPD

⇒ Productivity:

– Patients pr health worker

(7)

Patients per health worker (per day)

0510152025Percent

0 20 40 60 80

Number of patients per health worker

(8)

Productivity levels – by health facility

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

TFP analysis DEA analysis SFA analysis

(9)

Average productivity (and variation)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

TFP DEA SFA

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Variation: 5 - 95 percentile

(10)

Conclusions

• Low average productivity

– A few facilities do much better than most of the others

• Large variation in

productivity

(11)

What to do?

• Learn from high performers

• Allocate additional health workers to high productive units

• Fewer health workers at low productive units?

Not necessarily. Could imply close-down. Equity?

(12)

Recommendations

• Don’t do productivity analysis without good data!!

• Include all outputs

Delivery, vaccinations, OPD, etc.

• Use the DEA approach

More sensible than TFP analysis

Accounts for differences in the size of health facilities

Easier and more intuitive than SFA analysis

Easily deals with multiple inputs/outputs

Software freely available (e.g., DEAP)

Referanser

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