gms | German Medical Science

10. Deutscher Kongress für Versorgungsforschung, 18. GAA-Jahrestagung

Deutsches Netzwerk Versorgungsforschung e. V.
Gesellschaft für Arzneimittelanwendungsforschung und Arzneimittelepidemiologie e. V.

20.-22.10.2011, Köln

Does health care infrastructure have an impact on time to diagnosis and outcomes?

Meeting Abstract

  • corresponding author presenting/speaker Carl Rudolf Blankart - Hamburg Centre for Health Economics, University of Hamburg, Hamburg, Germany
  • author Tom Stargardt - Hamburg Centre for Health Economics, University of Hamburg, Hamburg, Germany
  • author Linder Roland - WINEG – Scientific Institute of the Techniker Krankenkasse (TK) for Benefit and Efficiency in Health Care, Hamburg, Germany
  • author Frank Verheyen - WINEG – Scientific Institute of the Techniker Krankenkasse (TK) for Benefit and Efficiency in Health Care, Hamburg, Germany
  • author Jonas Schreyögg - Hamburg Centre for Health Economics, University of Hamburg, Hamburg, Germany

10. Deutscher Kongress für Versorgungsforschung. 18. GAA-Jahrestagung. Köln, 20.-22.10.2011. Düsseldorf: German Medical Science GMS Publishing House; 2011. Doc11dkvf063

DOI: 10.3205/11dkvf063, URN: urn:nbn:de:0183-11dkvf0631

Veröffentlicht: 12. Oktober 2011

© 2011 Blankart et al.
Dieser Artikel ist ein Open Access-Artikel und steht unter den Creative Commons Lizenzbedingungen (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.de). Er darf vervielfältigt, verbreitet und öffentlich zugänglich gemacht werden, vorausgesetzt dass Autor und Quelle genannt werden.


Gliederung

Text

Background: Gastric cancer is one of the most incident cancers. However, survival time for this entity is very short. Thus gastric cancer with a prevalence of 20 per 100.000 is considered as rare disease. The disease is difficult to diagnose in its early stages, because it often progresses asymptomatic or causes nonspecific symptoms. Late diagnosis in an advanced stage is one of the main reasons for the disease’s poor prognosis. We therefore aim a) to evaluate whether health infrastructure has an impact on time to diagnosis and b) to determine whether time to diagnosis and quality of health care facilities treating the patient impacts mortality.

Materials and methods: A retrospective analysis with administrative data from 3,004 gastric cancer patients with an incidental ICD-10 diagnosis of C16 between January 2004 and June 2009 was conducted. The dataset was obtained from the Techniker Krankenkasse, a nationwide operating German sickness fund that covers more than seven million insured, i.e. about 9% of Germany’s population. We assumed gastric cancer to have been prevalent but undiagnosed when symptoms such as duodenitis (K29), gastro-oesophageal reflux disease (K21), abdominal and pelvic pain (R10) and other conditions typical for gastric cancer were present before the incidental diagnosis. To evaluate the relationship between in- and outpatient health care infrastructure and time to diagnosis, we employed cox proportional hazard models with time to diagnosis as dependent variable. Outpatient health care infrastructure was conceptualized by including a) the density of general practitioners or b) the density of gastroenterologists at the patient’s residence. Inpatient health care infrastructure was defined by the proximity of patients to specialty treatment centers. In a second model we evaluated the impact of health facilities treating the patient and time to diagnosis on mortality. Again, we applied cox proportional hazard models with mortality as dependent variable. We defined outpatient health care infrastructure as described above. Quality of inpatient health care facilities was defined by the number of gastric cancer cases performed and the nurses per bed at hospital where the patient was treated. In both models, we additionally adjusted for co-morbidities applying the Elixhauser co-morbidity index, age and gender.

Results: While greater availability of inpatient health care infrastructure increases the likelihood of an incidental diagnosis (p=0.0003) and decreases the hazard of dying (p<0.0001), an effect of outpatient health care infrastructure on time to diagnosis (p=0.5731) and mortality (p=0.5491) was not evident. We could not either find an impact of time to diagnosis on mortality (p=0.9767). Thus, living 1 km nearer to a specialist treatment center increases the probability of a diagnosis of gastric cancer by 0.3% whereas living in an area with a higher density of physicians did not have an influence. Treatment in hospital with 100 additional cases of gastric cancer decreased the hazard of dying by 19.6%.

Conclusions: Our results suggest that the quality of inpatient health care infrastructure decreases time to diagnosis of gastric cancer and positively impacts mortality. However, an impact of outpatient health care infrastructure could not be shown. Therefore, it seems advisable to centralize the treatment of gastric cancer in specialist treatment centers while also trying to ensure adequate access to inpatient health care facilities for patients living in remote areas.

This study was supported by a research grant from the Federal Ministry for Research and Education in Germany (grant number: BMBF 01FG09007). The sponsor had no role in the study design, collection and analysis of data, the writing of the report or the submission of the paper for publication.