DHB 2006/07 - Health Systems Trust

Section A: Indicator Comparisons by District
3. Process indicators
3.1 Nurse Clinical Workload Jackie Smith
The nurse clinical workload measures the average daily number of patients attended to by a
professional nurse in PHC facilities. This is a measure of efficiency and very low values indicate that
scarce skills (i.e. professional nurse time) are not being optimally utilised. Very high values indicate
that either the data are incorrect or that nurses are seeing too many patients per day resulting in a
compromise in quality of care of the patient or burn-out of the nurse, or both.
There was an improvement in data submission for this indicator during 2006/07 with all districts, including
those in the Western Cape, supplying data. There is a problem that there are various interpretations of
this indicator and a final definition and interpretation needs to be confirmed nationally. Regular data
quality checks will need to be put in place thereafter to assess consistency.
District View
The nurse clinical workload was 26.9 patients a day in South Africa in
2006/07, which was a decrease of 4.6 patients per day from 2005/06.
Figure 27 shows the range of values from a low of 13 patients per day in
Waterberg (LP) to 51 in the City of Cape Town (WC). It is pleasing to see that
the improbable figures found in iLembe (KZN), Pixley ka Seme and Namakwa
(NC) in 2005/06 appeared more realistic in 2006/07. This indicates an
improvement in the quality of the data due to a better understanding of the
indicator.
Capricorn, Greater Sekhukhune and Waterberg districts in Limpopo were
responsible for three of the four lowest workload indicators of 15 or less
patients a day in 2006/07. This, being an average result for the district,
requires investigation as it implies that many professional nurses are seeing
less than 10 patients a day.
In 24 of the districts nurses saw more than the national average of 27
patients per day. In some provinces such as KwaZulu-Natal and Northern
Cape all the districts were closely clustered. This implies equity in the
distribution of staff. However in most of the provinces there was wide intraprovincial
variation, implying that there are very varying workloads being
carried at individual clinics. This is a good example of how information can
inform managerial decision making
Some provinces are using professional nurses and others are using all nurses as the denominator. There are also various
interpretations as to what is a nurse day with e.g. sick leave, study leave being treated differently in different provinces.
THE DHIS INDICATORS PRESENTED HERE ARE AS RECEIVED FROM THE NATIONAL DHIS AND HAVE NOT BEEN ALTERED BY THE AUTHORS OR HST 31