Abstract
Acute post-operative delirium (POD) and long-term post-operative cognitive dysfunction (POCD) are frequent and associated with increased mortality, dependency on care giving and institutionalization rates. The POCD-related cost burden on the German long-term care insurance provides an indication for the savings potential from risk-adapted treatment schemes. Comprehensive estimates have not been assessed or published so far.
A model-based cost-analysis was designed to estimate POCD-related costs in the long-term care insurance. Comprehensive analysis of inpatient operations and procedures (OPS-codes) served as the base for case number calculations, which were then used as input to the actual cost model. POCD-incidence rates were obtained from the BioCog study. Various sensitivity analyses were performed to assess uncertainty of the model results.
Total POCD related annual costs in the German long-term care insurance account for approximately 1.6 billion EUR according to the base case of our analysis. Total annual costs for all POCD cases depend on surgery numbers, incidence rates, other assumptions, and uncertain input parameters.
The financial burden to the long-term care insurance is substantial, even in a conservative scenario of the cost model. Variability of results stems from uncertain assumptions, POCD-incidence rates and from uncertain patient numbers who are undergoing surgery and are therefore at risk to develop POCD.
Author Contributions
Copyright© 2021
A. Weber Simon, et al.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Competing interests The authors have declared that no competing interests exist.
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Introduction
The long-term care insurance (“ Post-operative cognitive dysfunction (POCD) is a frequently occurring complication after surgeries, not only but especially among elderly patients aged 65 years and above It is worth noticing that the existing nomenclature for perioperative cognitive deficits has recently been revised and the Primary aim of the BioCog consortium is the development of a prospective diagnostic tool, capable of reliably predicting POD and POCD risks of patients, in order to either individually adapt and improve post-operative care or to suspend and potentially discard the initially planned surgery. For this purpose, the BioCog consortium conducted an observational study to identify suitable biomarkers by including more than one thousand patients in Berlin, Germany and Utrecht, Netherlands aged 65 years and above, undergoing an inpatient major elective surgery with general anesthesia. Specifics of the BioCog study design are reported elsewhere In anticipation of the prospective diagnostic POCD risk prediction tool we seek to determine parts of the possible market size of such a tool in terms of EUR. To estimate the health-economic value of the proposed pre-operative assessment it is essential to also consider downstream costs associated with POCD, which could potentially be avoided. A major share of these downstream costs is suspected to be incurred by the long-term care insurance in Germany due to sustained POCD of a significant proportion of patients. Health-economic literature on POD - and POCD-related costs is scarce, especially literature on costs borne by long-term care insurances. According to published studies in the field of health-economics, it could be shown that POD significantly contributes to increased inpatient costs Analyses of the financial burden of POCD to the German long-term insurance caused by premature dependency on care giving could not be found in the present literature. There is a lack of published, transparent, and reproducible estimates of the long-term care burden in Germany attributable to POD/POCD, especially within the new framework of “Pflegegrade” – a formal system which assigns a patient to one out of five categories depending on the degree of long-term care intensity. The BioCog group therefore decided to develop a health-economic model estimating the cost-consequences attributable to POCD for the German long-term care insurance, based on the BioCog trial results and other published data.
Results
The results of the base case are displayed in Several deterministic sensitivity analyses were performed, and the results are shown in a tornado diagram ( Regarding the three chosen parameters and assumptions, it becomes obvious that the highest share of uncertainty surrounding the model results stems from the assumption of all POCD cases transitioning from long-term care intensity 0 to 2. Assuming half of the POCD cases transitioning from care intensity 0 to 1 and the other half from 0 to 2 would decrease annual costs to the long-term-care insurance to approximately 796mio EUR. On the other hand, assuming half the POCD cases transitioning from care intensity 0 to 3 and the other half again from 0 to 2 would increase total costs to 2.3 billion EUR. While a 10% in- or decrease in POCD incidence rates directly translates into a 10% in- or decrease in total long-term care costs, a corresponding in- and decrease of the average amount of chapter 5 OPS-codes per patient and inpatient surgery would result in annual costs of either 1.4 billion EUR (10% increase) or 1.7 billion EUR (10% decrease). The diverging effect compared to an alteration of POCD incidences stems from the distribution of cases in respective age-groups and the fact, that OPS numbers are divided by this factor.
Discussion
A strength of the present analysis lies in its transparency and the utilization of publicly available data, together with recently established POCD incidence rates in Germany and reasonable assumptions. However, the results of the sensitivity analyses vary - in one case even significantly - indicating the degree of uncertainty of assumptions and inputs that were used. The reported results of our model-based calculations depend on the applied incidence rates of POCD. Therefore, significant effort was made to obtain reliable estimates of age-specific incidence rates across surgery types from the BioCog study. The fact that we applied incidence rates across surgery types introduces uncertainty of the modelled results, because the data base used for estimating POCD patient numbers (OPS 2019 statistic) reflects slightly different shares of operations with regards to the surgery site compared to the BioCog sample from which POCD incidence was inferred. This is important to note, since most publications on POCD incidences focus on specific types of surgeries and report highly heterogeneous numbers For the base case, we used a controlled definition of POCD based on a reliable change index as suggested by Rasmussen et al., 2001. This definition results in lower POCD incidence compared to more liberal definitions. To give an example: A recent publication on recommendations for the nomenclature of cognitive change associated with anesthesia and surgery suggests to report postoperative cognitive dysfunction more in line with the DSM-5 diagnosis of Neurocognitive disorder (mild/major NCD) and use the former POCD as a specifier to indicate its coincidence with surgery for up to one year postoperatively It should also be noted, that the BioCog sample - from which we drew the applied POCD incidence rates - represents a younger cohort than the chapter 5 OPS utilization sample that was used to estimate the number of patients undergoing surgery in Germany in 2019. Since POCD-incidence is highly dependent on patient age, the model rather underestimates the true number of POCD cases. In addition to that, POCD incidence rates obtained from the BioCog study might be influenced by the trial`s drop-out rate: POCD data at 3 months is available for 641 out of 933 patients. Low follow-up rates (69% for cognitive testing in BioCog) are common in POCD trials, e.g. the ISPOCD study reported a similar low POCD prevalence (10%) with a comparable follow-up rate of 78% A limitation of the present study involves the fact, that cost consequences of transitions from long-term care intensity 0 to 2 (Pflegegrad 2) were modelled. We investigate the effect of exemplary alternative transition distributions in corresponding sensitivity analyses, but in fact there are many other possible transitions (e.g. from care intensity 1 to 4, from 2 to 5 etc. and even switches between long-term care types) that were not modelled but each triggering different cost consequences depending on the shares of patients in each segment of inpatient or outpatient long-term care. These aspects were not modelled, because there is a lack of evidence that could serve as a base for reasonable assumptions and guide our calculations. The fact that we only modelled one possible switch from long-term care intensity 0 to 2 - but in fact there many more - indicates that the long-term care costs attributable to POCD are likely to be even higher than we report. Future analyses should focus on determining the exact amounts and shares of patients transitioning from one care segment to another. In light of our conservatively chosen incidence rates, the analyzed chapter 5 OPS utilization numbers as a representative base for POCD case number calculations, actually reflect performed operations and not cases or patients. We sought to control for that aspect by excluding supplemental OPS-codes not reflecting separate surgeries, and by dividing the resulting number of chapter 5 OPS-codes by the average number of chapter 5 OPS-codes per patient observed in a sub-sample of the BioCog study. Dividing chapter 5 OPS utilization by the average number of chapter 5 codes per patient introduces additional uncertainty, because it is unclear whether this factor is the same in all German patients undergoing surgery captured in the OPS data. Therefore, we investigated the effect of varying average numbers of chapter 5 OPS-codes per patient in corresponding sensitivity analyses. Currently, a large multicenter clinical trial is recruiting patients in Germany who will undergo a multimodal and multidisciplinary intervention after surgery with the aim to reduce POD rates by at least 40% and to reduce POCD rates by at least 20% cancellation of surgery, if justifiable from a medical perspective suspension of surgery, if improvement of test-outcome at a later point of time is likely modification of treatment path, e.g. application of multimodal and multidisciplinary interventions, modified anesthesia or other measures These consequences would need to be precisely investigated with regards to costs and effectiveness for an exact estimation of the health- and socio-economic value of a prognostic POCD detection tool.
Conclusion
A first and transparent model-based analysis of POCD associated costs in the German social long-term care insurance could be developed and evaluated. The analysis reveals significant long-term care costs associated with POCD of approximately 1.6 billion EUR annually. Several assumptions and features of the cost-model ensure conservative estimates of the results, suggesting that the actual financial burden of POCD to the long-term care insurance is even higher. For a precise determination of POCD related long-term care costs more research needs to be devoted to aspects surrounding the consequences of POCD with respect to the long-term care insurance. These aspects include age-specific POCD incidence rates, numbers and shares of patients transitioning from no dependency on long-term care to other segments of long-term care intensity and type. Additional studies should further reveal whether shares of patients are altered between different long-term care schemes due to the development of POCD, and consider effects on expenses for technical long-term care aids (Pflegehilfsmittel), support for improvements in home environments (Wohnumfeld-Verbesserungsmaßnahmen), transfer payments to pension funds, unemployment insurance, statutory health insurances and other legal financial support of the long-term care insurance.