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Establishing risk-adjusted quality indicators in surgery using administrative data—an example from neurosurgery

  • Original Article - Neurosurgery general
  • Published:
Acta Neurochirurgica Aims and scope Submit manuscript

Abstract

Background

The current draft of the German Hospital Structure Law requires remuneration to incorporate quality indicators. For neurosurgery, several quality indicators have been discussed, such as 30-day readmission, reoperation, or mortality rates; the rates of infections; or the length of stay. When comparing neurosurgical departments regarding these indicators, very heterogeneous patient spectrums complicate benchmarking due to the lack of risk adjustment.

Objective

In this study, we performed an analysis of quality indicators and possible risk adjustment, based only on administrative data.

Methods

All adult patients that were treated as inpatients for a brain or spinal tumour at our neurosurgical department between 2013 and 2017 were assessed for the abovementioned quality indicators. DRG-related data such as relative weight, PCCL (patient clinical complexity level), ICD-10 major diagnosis category, secondary diagnoses, age and sex were obtained. The age-adjusted Charlson Comorbidity Index (CCI) was calculated. Logistic regression analyses were performed in order to correlate quality indicators with administrative data.

Results

Overall, 2623 cases were enrolled into the study. Most patients were treated for glioma (n = 1055, 40.2%). The CCI did not correlate with the quality indicators, whereas PCCL showed a positive correlation with 30-day readmission and reoperation, SSI and nosocomial infection rates.

Conclusion

All previously discussed quality indicators are easily derived from administrative data. Administrative data alone might not be sufficient for adequate risk adjustment as they do not reflect the endogenous risk of the patient and are influenced by certain complications during inpatient stay. Appropriate concepts for risk adjustment should be compiled on the basis of prospectively designed registry studies.

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Author information

Authors and Affiliations

  1. Department of Neurosurgery, University Hospital Münster, Albert-Schweitzer-Campus 1, 48149, Münster, Germany

    Stephanie Schipmann, Michael Schwake, Dennis Keurhorst, Sebastian Lohmann, Eric Suero Molina, Nils Warneke & Walter Stummer

  2. Institute of Medical Informatics, University Hospital Münster, Münster, Germany

    Julian Varghese, Tobias Brix & Martin Dugas

  3. Department of Neurosurgery, German Armed Forces Hospital Ulm, Ulm, Germany

    Uwe Max Mauer

Authors
  1. Stephanie Schipmann
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  2. Julian Varghese
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  4. Michael Schwake
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Corresponding author

Correspondence to Stephanie Schipmann.

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Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the local ethic committee. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all participants included in the study.

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Comments:

In a reasonably large sample of neurosurgical tumour cases, the authors calculated outcome parameters commonly regarded by politicians as indicators of quality of surgical care. In regression models, those outcome data were adjusted to individual risk factors, both endogenous in patients and including some complications during in-hospital stay. All parameters were retrieved from administrative data primarily collected for billing purposes. They found mainly a dependence of outcome on patient-clinical-complexity-level (PCCL), comorbidities, and male gender in pre-hospital data. As quality measures are increasingly discussed in many health systems (this data was obtained from Germany) and thus also may affect neurosurgical care, this is an important contribution, which approaches the very complex question of how to measure surgical quality with the data most easily accessible to date. As the authors point out, the approaches from different other countries such as the UK and the US cannot be directly transferred to the situation in Germany, e.g. due to a lack of patient registries. Obviously, for serious quality assessment and benchmarking, there is a need for nationwide patient registries. Thus, this notion and also the limitations have impact on neurosurgical practice and political attitudes despite different systems in different countries. Another important issue is that for example in gliomas, the extent of the surgical approach must be determined in individual cases in a complex trade-off between short-term outcome and long-term benefit. Therefore, "outcome Parameters" such as duration of hospital stay may not easily tell the whole truth. This paper is a valuable contribution to illustrate potential, but also limitations of such administrative data based approaches.

Georg Neuloh

Hans Clusmann

Aachen, Germany

This article is part of the Topical Collection on Neurosurgery general

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Schipmann, S., Varghese, J., Brix, T. et al. Establishing risk-adjusted quality indicators in surgery using administrative data—an example from neurosurgery. Acta Neurochir 161, 1057–1065 (2019). https://doi.org/10.1007/s00701-018-03792-2

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  • DOI: https://doi.org/10.1007/s00701-018-03792-2

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