Effects of multiple chronic conditions on health care costs: an analysis based on an advanced tree-based regression model

Hans-Helmut König, Hanna Leicht, Horst Bickel, Angela Fuchs, Jochen Gensichen, Wolfgang Maier, Karola Mergenthal, Steffi Riedel-Heller, Ingmar Schäfer, Gerhard Schön, Siegfried Weyerer, Birgitt Wiese, Hendrik van den Bussche, Martin Scherer, Matthias Eckardt, MultiCare study group, Attila Altiner, Horst Bickel, Wolfgang Blank, Monika Bullinger, Hendrik van den Bussche, Anne Dahlhaus, Lena Ehreke, Michael Freitag, Angela Fuchs, Jochen Gensichen, Ferdinand Gerlach, Heike Hansen, Sven Heinrich, Susanne Höfels, Olaf von dem Knesebeck, Hans-Helmut König, Norbert Krause, Hanna Leicht, Melanie Luppa, Wolfgang Maier, Manfred Mayer, Christine Mellert, Anna Nützel, Thomas Paschke, Juliana Petersen, Jana Prokein, Steffi Riedel- Heller, Heinz-Peter Romberg, Ingmar Schäfer, Martin Scherer, Gerhard Schön, Susanne Steinmann, Sven Schulz, Karl Wegscheider, Klaus Weckbecker, Jochen Werle, Siegfried Weyerer, Birgitt Wiese, Margrit Zieger, Hans-Helmut König, Hanna Leicht, Horst Bickel, Angela Fuchs, Jochen Gensichen, Wolfgang Maier, Karola Mergenthal, Steffi Riedel-Heller, Ingmar Schäfer, Gerhard Schön, Siegfried Weyerer, Birgitt Wiese, Hendrik van den Bussche, Martin Scherer, Matthias Eckardt, MultiCare study group, Attila Altiner, Horst Bickel, Wolfgang Blank, Monika Bullinger, Hendrik van den Bussche, Anne Dahlhaus, Lena Ehreke, Michael Freitag, Angela Fuchs, Jochen Gensichen, Ferdinand Gerlach, Heike Hansen, Sven Heinrich, Susanne Höfels, Olaf von dem Knesebeck, Hans-Helmut König, Norbert Krause, Hanna Leicht, Melanie Luppa, Wolfgang Maier, Manfred Mayer, Christine Mellert, Anna Nützel, Thomas Paschke, Juliana Petersen, Jana Prokein, Steffi Riedel- Heller, Heinz-Peter Romberg, Ingmar Schäfer, Martin Scherer, Gerhard Schön, Susanne Steinmann, Sven Schulz, Karl Wegscheider, Klaus Weckbecker, Jochen Werle, Siegfried Weyerer, Birgitt Wiese, Margrit Zieger

Abstract

Background: To analyze the impact of multimorbidity (MM) on health care costs taking into account data heterogeneity.

Methods: Data come from a multicenter prospective cohort study of 1,050 randomly selected primary care patients aged 65 to 85 years suffering from MM in Germany. MM was defined as co-occurrence of ≥3 conditions from a list of 29 chronic diseases. A conditional inference tree (CTREE) algorithm was used to detect the underlying structure and most influential variables on costs of inpatient care, outpatient care, medications as well as formal and informal nursing care.

Results: Irrespective of the number and combination of co-morbidities, a limited number of factors influential on costs were detected. Parkinson's disease (PD) and cardiac insufficiency (CI) were the most influential variables for total costs. Compared to patients not suffering from any of the two conditions, PD increases predicted mean total costs 3.5-fold to approximately € 11,000 per 6 months, and CI two-fold to approximately € 6,100. The high total costs of PD are largely due to costs of nursing care. Costs of inpatient care were significantly influenced by cerebral ischemia/chronic stroke, whereas medication costs were associated with COPD, insomnia, PD and Diabetes. Except for costs of nursing care, socio-demographic variables did not significantly influence costs.

Conclusions: Irrespective of any combination and number of co-occurring diseases, PD and CI appear to be most influential on total health care costs in elderly patients with MM, and only a limited number of factors significantly influenced cost.

Trial registration: Current Controlled Trials ISRCTN89818205.

Figures

Figure 1
Figure 1
Conditional independence tree for total costs. PD = Parkinson’s disease; CCI = cardiac insufficiency; mean costs = predicted mean total costs in € in 6-month period.
Figure 2
Figure 2
Conditional independence tree for inpatient costs. CICS = cerebral ischemia and/or chronic stroke, mean costs = predicted mean inpatient costs in € in 6-month period.
Figure 3
Figure 3
Conditional independence tree for medication costs. COPD = chronic obstructive pulmonary disease; PD = Parkinson’s disease; INS = insomnia; DM = Diabetes mellitus, mean costs = predicted mean medication costs in € in 6-month period.
Figure 4
Figure 4
Conditional independence tree for costs of nursing care. PD = Parkinson’s disease; rd age = rounded age; logincome = natural logarithm of income, mean costs = predicted mean costs of nursing care in € in 6-month period.

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