Abstract
Background Certification programs seek to improve the quality of complex
interdisciplinary models of care such as cancer treatment through structuring
the process of care in accordance with evidence-based guidelines. In Germany,
the German Cancer Society (Deutsche Krebsgesellschaft, DKG) provides a
certification programme for cancer care that covers more than one thousand
centers. In a recent retrospective cohort study, it has been shown on a large,
nationwide data set based on data from a statutory health insurance and selected
clinical cancer registries, that there is a benefit in survival for cancer
patients who have received initial treatment in hospitals certified by the DKG.
Here, we deduce two absolute measures from the relative benefit in survival with
the aim to quantify this benefit if all patients had been treated in a certified
center.
Methods The WiZen study analysed survival of adult patients insured by
the AOK with a cancer diagnosis between 2009 and 2017 in certified hospitals vs.
non-certified hospitals. Besides Kaplan-Meier-estimators, Cox regression with
shared frailty was used for 11 types of cancer in total, adjusting for
patient-specific information such as demographic characteristics and
comorbidities as well as hospital characteristics and temporal trend. Based on
this regression, we predict adjusted survival curves that directly address the
certification effect. From the adjusted survivals, we calculated years of life
lost (YLL) and number needed to treat (NNT), along with a difference in deaths 5
years after diagnosis.
Results Based on our estimate for the 537,396 patients that were treated
in a non-certified hospital included in the WiZen study, corresponding to
68,7% of the study population, we find a potential of 33,243 YLL per
year in Germany based on the size of the German population as of 2017. The
potential to avoid death cases 5 years from diagnosis totals 4,729 per year in
Germany.
Conclusion While Cox regression is an important tool to evaluate the
benefit that arises from variables with a potential impact on survival such as
certification, its direct results are not well suited to quantify this benefit
for decision makers in health care. The estimated years of life lost and the
number of deaths that could have been avoided 5 years from diagnosis avoid
mis-interpretation of the hazard ratios commonly used in survival analysis and
should help to inform key stakeholders in health care without specialist
background knowledge in statistics. Our measures, directly adressing the effect
of certification, can furthermore be used as a starting point for
health-economic calculations. Steering the care of cancer patients primarily to
certified hospitals would have a high potential to improve outcomes.
Key words
cancer - certification - survival analysis
