Investigating lead time, cost and patient pathways of breast cancer care: a comparative study of four hospitals in Sweden
2016
Introduction:
This paper aims to provide support for quality improvement in breast cancer care in Sweden. Using quality
register data from 2009-2012 with approximately 2630 patients in four hospitals, we would like to answer
three questions: (1) Is there a hospital which has the shortest lead time and/or lowest cost thus serving as a
role model? (2) Is there a typical way of working, in terms of patient pathways, that leads to shorter lead time
and/or lower cost? (3) Does shorter lead time imply lower cost? The results of this research will be useful for
inter-organizational learning among the hospitals for creating better breast cancer care.
Methods:
Descriptive statistics is used to analyze the lead times to surgery and subsequent treatments (radiation and
chemotherapy) and cost per patient for each hospital. Process mining using ProM software is used for
understanding patients’ pathways. For all hospitals, the lead time and cost are categorized into three groups,
namely, short or low, moderate, and long or high. The grouping uses discretization technique in such a way that
the low-cost or short-lead time class corresponds to set goals and the moderate group will be the majority of
the cases. The analysis is carried out within and across hospitals. The relationship between low/high cost care,
short/long lead time and patient pathways are investigated visually and cross-checked with the practitioners.
Results: Results show that lead times often exceed set goals and this is especially true for time between
surgery and radiation. Two hospitals seem to achieve a better result here, and one of these hospital also
appear to stand out positively from the other three hospitals in terms of lead time from diagnosis to surgery.
The two hospitals above also have a larger percentage of low-cost patients than the other two hospitals.
Pathway mapping revealed differences in the use of personnel resources among the hospitals. Generally, there
seems to be a relationship between the unique pathways and the cost. Across hospitals, the low cost group has
a lot less unique pathways. This can imply that the deviation from the common clinical pathway may lead to
higher cost.
Discussion: This work shows how quality register data can provide useful information for improving breast
cancer care. Based on the evidence, areas of improvement can be mapped for each hospital and how they can
learn from each other. This work provides a starting point for a more directed investigation into understanding
patient clinical pathways and towards explaining why some care costs a lot more than the others or why some
patients have to wait for such a long time.
Declaration of competing interests
We gratefully thank Regional Cancer Centre West for the funding of this research.
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