gms | German Medical Science

Background: In recent years outpatient treatment has, due to specific patient groups with related cost effects, gained more and more attention of health policy makers. Several works had the focus on the analysis of medical diagnoses in outpatient treatment [7]. In particular, diagnostic diversity has been the reserch subject of several studies [1]. Jutel (2009) [7] found that sociodemographic parameters including social class, age and gender might be regarded as influencing factors for diagnostic diversity. Thus there is an urgent need to analyze medical diagnoses in this context. One possible way is to use secondary data i.e. from large patient registers or insurance data.

The fraction of people covered by statutory health insurance changes with age and one can suspect that on average they have a lower morbidity. Due to reimbursements not all treatments of patients with private insurance are reported to those insurances. There are no valid morbidity data for the comparison of private and statutory healthcare. This complicates or prevents population based considerations. In contrast to inpatient treatment there are no main diagnoses defined by the statutory physicians.

The main objective of this paper is to analyze whether there is an influence of gender and age with respect to diagnostic diversity. This allows for development of interdisciplinary treatment concepts for patient subgroups focussing on multimorbidity.

Materials and Methods: This article considers all diagnoses for all patients of statutory health insurance in Schleswig-Holstein in quarter 2/2016. We analyze all diseases diagnosed and coded (International Statistical Classification of Diseases and Related Health Problems in its 10th Revision (ICD-10)) by physicians treating the patient. Thus this article takes a patient centered point of view. The first descriptive part analyzes, if the resolution level of chapters (e.g. Chapter IX, Diseases of the circulatory system, I00-I99), ICD-Blocks (e.g. Ischaemic heart diseases, I20-I25) or first three digits of the ICD (e.g. Angina pectoris, I20) influence the results. It also determines which ICD-10 chapter is most central for the treatment of patients with respect to age and gender.

Due to multimorbidity patients can have diseases of different chapers. This is also considered as an influencing factor. To detect diagnostic diversity, we applied Shannon‘s entropy [9]. Shannon’s entropy is based on a system of mutually exclusive and exhaustive events. The largest value of the entropy is given for the uniform distribution. A comparison of Shannon’s entropy, Lorentz curves with Gini coefficients and deviations from the mean value [10] showed similar results with respect to a naturally ordered set (weekdays), here we haven’t an ordered structure with respect to ICD Chapters and prefer Shannon‘s entropy which is robust against scaling effects and is also used in physics.

Results: For male and female patients under the age of one year only the chapter XVIII (Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified) is central. Between one and 31 years diseases of the respiratory system (chapter X, J00-J99,) are most dominant for patients with the exception of boys between 6 and 8 years, for which mental and behavioral disorders (chapter V, F00-F99,) are most relevant. For females aged 32 mental and behavioral disorders are at the top. For men between 32 and 53 and woman between 33 and 59 diseases of the musculoskeletal system and connective tissue (Chapter XII, M00-M99) are in the focus. Above that age diseases of the circulatory system (Chapter IX, I00-I99) are most common. Regarding Chapter X (there is a decreasing importance in childhood with a new peak around the age of 17. There are slightly increased values for men until around 40 years, above that age the situation reverses. Above 70 years there are surging values for males. Until the age of 15 years there is a male dominance in mental and behavioral disorders (most relevant between 6 and 15 years), after the age of 17 years there is a stable and relevant female dominance. The part of patients with diseases of the musculoskeletal system and connective tissue shows only minor differences untill an age of around 45 years. Afterwards it increases to an upper limit value of 60 % for men and 70 % for women. The part of patients with diseases of the circulatory system is monotonically increasing up to a limit value of 90 % both for men and women with up to 5 % higher values for men between 45 and 75 years.

Conclusion: The analysis of secondary data is a promising approach for health care policy makers and stakeholders. This article describes a straight forward pragmatic way to analyse diagnostic diversity using Shannon’s Entropy from a sample of patients covered by statutory health insurance in Schleswig-Holstein in quarter 2/2016.

This approach has already been used in the inpatient field [6], [9]. This article applies this approach to outpatient data. The limiting factor might be, that many outpatient procedures lack a final and secured diagnosis and thus unspecified diagnoses could be overrepresented (Siegel 2017).

From a methodological point of view, Shannon‘s entropy is sensitive to rare events, which makes it one of the most reliable diversity indicator (Leinster & Cobbold (2012). Another study found similarities to Gini‘s coefficient of inequality [10]. In conclusion the use of Shannon’s entropy as a measure of diversity should gain the researchers‘ attention and health services research should learn more about this measure or rather rediscover it.