Background: To make the best use of health resources, it is crucial to understand the healthcare needs
of a population – including how needs will evolve and respond to changing epidemiological context
and patient behaviour – and how this compares to the capabilities to deliver healthcare with the
existing workforce. Existing approaches to planning either rely on using observed healthcare demand
from a fixed historical period or using models to estimate healthcare needs within a narrow domain
(e.g., a specific diease area or health programme). A new data-grounded modelling method is
proposed by which healthcare needs and the capabilities of the healthcare workforce can be
compared and analysed under a range of scenarios: in particular, when there is much greater
propensity for healthcare seeking.
Methods: A model representation of the healthcare workforce, one that formalises how the time of
the different cadres is drawn into the provision of units of healthcare, was integrated with an
individual-based epidemiological model - the Thanzi La Onse Model - that represents mechanistically
the development of disease and ill-health and patients’ healthcare seeking behaviour. The model was
applied in Malawi using routinely available data and the estimates of the volume of health service
delivered were tested against officially recorded data. Model estimates of the “time needed” and
“time available” for each cadre were compared under different assumptions for whether vacant (or
established) posts are filled and healthcare seeking behaviour.
Results: The model estimates of volume of each type of service delivered were in good agreement
with the available data. The “time needed” for the healthcare workforce greatly exceeded the “time
available” (overall by 1.82-fold), especially for pharmacists (6.37-fold) and clinicians (2.83-fold). This
discrepancy would be largely mitigated if all vacant posts were filled, but the large discrepancy would
remain for pharmacists (2.49-fold). However, if all of those becoming ill did seek care immediately,
the “time needed” would increase dramatically and exceed “time supply” (2.11-fold for nurses and
midwives, 5.60-fold for clinicians, 9.98-fold for pharmacists) even when there were no vacant
positions.
Conclusions: The results suggest that services are being delivered in less time on average than they
should be, or that healthcare workers are working more time than contracted, or a combination of
the two. Moreover, the analysis shows that the healthcare system could become overwhelmed if
patients were more likely to seek care. It is not yet known what the health consequences of such
changes would be but this new model provides – for the first time – a means to examine such
questions.