3. OptiMedis, regionally based integrated care model

This section outlines Germany’s healthcare system, at a high level, followed by a description of the OptiMedis model.

Germany operates a compulsory social health insurance. In the late 19th century, Germany introduced the world’s first social health insurance (SHI) system, built on the foundation of solidarity. Today, the majority of residents within the country are required to obtain SHI from one of the 103 sickness funds. However, those who earn over a certain income (i.e. EUR 62 550) and certain professionals (e.g. self-employed and civil servants) can opt out and purchase health insurance instead. As of 2020, 87% of residents are covered by SHI with the remaining 11% opting for private insurance (the remaining 2% are covered by special programs) (Blümel et al., 2020[1]).

Germany has a world-class healthcare system, but it is expensive. Residents living in Germany have access to universal health insurance, which covers a comprehensive set of benefits with minimal cost-sharing. For this reason, the healthcare system is highly regarded. Nevertheless, it is relatively expensive with health expenditure comprising 11.7%1 of gross domestic product (GDP). Among OECD countries, this figure is only surpassed by the United States (16.8%) (OECD, 2020[2]).

Relatively high healthcare expenditure has not translated into better health outcomes. For example, as of 2019,2 life expectancy in Germany reached 81.4 years, which ranks it 24th among 38 OECD countries. Further, around two-thirds (66%) of the population report being in good health, which is lower than the EU average of 69% (OECD/European Observatory on Health Systems and Policies, 2021[3]).

A lack of co-ordination is considered one of the key reasons Germany’s healthcare system has not performed as well as expected. Germany’s healthcare system is complex with the separation of legislative, planning and regulatory power across different sectors – i.e. ambulatory, inpatient, long-term care, and public health (for full details see (Blümel et al., 2020[1])). For this reason, the healthcare system lacks co-ordination, which negatively affects service delivery and therefore health outcomes. Another factor contributing to Germany’s overall performance is its reliance on secondary care. As an example, hospital admissions for asthma and chronic obstructive pulmonary disease (COPD) are above the EU average in Germany, indicating lack of effective primary care treatment and self-management support, as well as a focus on secondary treatment (OECD/European Observatory on Health Systems and Policies, 2021[3]). Consequently, the estimated cost of avoidable hospital admissions is over eight times higher than the OECD30 average (USD 7.2 million versus USD 0.84 million per year) (OECD, 2020[4]).

Germany introduced various policies to improve care co-ordination in recent years. Given the difficulty in implementing large scale, structural changes to the German healthcare system, policy makers have instead opted to implement a series of reforms that encourage care co-ordination. This includes the 2004 Social Health Insurance Modernisation Act, which “introduced a legal framework for integrated care provision and strengthened primary care” (Amelung et al., 2017[5]). Following this Act, a number of voluntary integrated care contracts emerged, which patients had the option of joining. One of the integrated care models to emerge was the OptiMedis regionally based integrated care model (hereafter, the OptiMedis model), which is the focus of this case study.

The regionally based integrated care model by OptiMedis emerged in 2005. The model is driven by regional networks involving physicians and other stakeholders and aims to bring together healthcare providers at all levels of a determined region into one integrated network, while assuming accountability for the health and healthcare of the region’s population. People can voluntarily enrol with the model who then have access to a wide range of healthcare interventions, ranging from disease management programs to discounts for exercise facilities.

Further information on the model’s objectives, target population, governance and payment system, and interventions provided are summarised below.

The OptiMedis model promotes care co-ordination across all sectors with a focus on prevention and introduces evidence-based interventions to address identified healthcare needs. Through doing so, it aims to achieve the following four objectives (also referred to as the “Quadruple aim approach”):

  • Improve patient experiences of care (quality and satisfaction)

  • Improve the health of the population

  • Reduce the per capita cost of healthcare

  • Improve work/life balance for healthcare providers.

People of all ages, regardless of their disease history, can enrol in the OptiMedis model where it is offered. Given the model’s focus on co-ordination, it is particularly beneficial to individuals living with one or multiple chronic conditions who require care from several health professionals.

The OptiMedis model involves the creation of a regional integrator, an institution in charge of managing the network integration with a physical presence in the region and legally constituted as an enterprise. Healthcare providers in partnership with the network participate in the regional integrator in the capacity of partners, owners or associates (depending on the particular context) together with OptiMedis AG, a German healthcare management company with an expertise in management support, business intelligence and health data analytics.

A key feature of the OptiMedis model is the payment system, which is based on a “shared savings contract”. The contract is drawn between the integrated network on one side and sickness funds on the other. As part of this contract, positive differences between expected costs3 and the real healthcare costs of the population the network is accountable for are considered “savings” and are shared between the integrated network and sickness funds.

The share of savings received by the integrated network is used to finance integration efforts, including performance bonuses and operations of the regional integrator. Remaining profits are re-invested in the regional healthcare system.

To avoid an under provision of services as a way to generate savings, there are minimum quality standards that need to be complied with. The payment system, therefore, is designed so that there is a financial incentive to invest in delivering high-quality, efficient, preventative care.

There are two types of value-creating interventions within the OptiMedis model: direct interventions for people that are enrolled within the model, and indirect interventions, directed at improving system efficiency through providers at all levels of care (i.e. primary, secondary, tertiary, and long-term care) that are part of the network and public health campaigns Figure 3.1). The latter are available for the entire population accounted for the by the integrated network.

Each of the interventions listed are underlined by a common set of features, namely (The King’s Fund, 2022[6]):

  • Individual treatment plans and goal setting agreements between doctors and patients

  • Enhancing patient self-management and shared decision-making

  • Care planning based on the chronic care model, patient coaching and follow up care

  • Providing the right care at the right time

  • Overarching support through purposely designed system-wide electronic patient records and digital patient empowerment platforms. This is of particular interest given in Germany electronic sharing of patient data is relatively low (see Box 3.1).4

This section analyses the OptiMedis model against the five criteria within OECD’s Best Practice Identification Framework – Effectiveness, Efficiency, Equity, Evidence-base and Extent of coverage (see Box 3.1 for a high-level assessment).

This section on effectiveness presents the long-term health impact of the OptiMedis model in Germany as well as countries that are members of the OECD and EU27. The analysis relied on neural networks and microsimulation modelling by the OECD. Details on the methodology, including modelling assumptions, are in Annex 3.A.

Implementing the OptiMedis integrated care model across Germany is estimated to lead to an additional 146 441 life years (LYs) and 97 558 disability-adjusted life years (DALYs) by 2050.

Transferring OptiMedis to the eligible population across EU27 countries is estimated to result in 9.7 LYs and 6.5 DALYs gained per 100 000 people on average per year between 2022 and 2050 (Figure 3.3). OECD countries such as Portugal and Italy would experience the largest gain, while the effect is estimated to be lowest in Greece and the Slovak Republic.

Like “Effectiveness”, this section presents results for Germany followed by OECD and EU-27 countries.

Over the modelled period, 2022-50, the OECD-SPHeP NCD model estimates that OptiMedis would lead to cumulative health expenditure savings of EUR 3 470 per person (Figure 3.4).

Average annual health expenditure (HE) savings as a proportion of total HE is estimated at 4%, on average, across EU-27 countries. This translates into annual savings of EUR 80.14 for every person aged 20 years and over between 2022 and 2050, with figures ranging from EUR 23 in Romania to EUR 179 in Germany (Figure 3.5).

Health Coaches, Healthcare Navigators, and the Health Kiosk are key interventions within the OptiMedis model, which aim to reduce health inequalities. The Health Kiosk was first introduced in the city of Hamburg, specifically in two boroughs where 70% of the population is comprised of migrants (compared to 13% across the whole country). The Health Kiosk caters to disadvantaged groups, such as migrants, by offering counselling services in a range of languages including Arabic, Farsi, Russian and Polish. At present, seven counsellors work within the Health Kiosk providing healthcare navigation and holistic counselling sessions related to health and social issues (e.g. nutrition, alcohol, smoking, employment and cultural integration). At present, the Health Kiosk only exists within Hamburg, however, a recent initiative aims to establish Health Kiosks in other cities, as well as in rural areas (where health topics are different, but low-threshold health information and navigation is equally important).

Core features of the OptiMedis model help reduce health inequalities. The primary objectives of the OptiMedis model are to improve patient experiences and population health, as well as reduce per capita costs. Features of the model designed to achieve these objectives also play a key role in reducing health inequalities, namely by:

  • Offering care tailored to individual patient needs, including those from disadvantaged backgrounds

  • Standardising care pathways across all patients thereby ensuring everyone receives the same service quality. Although standardised, the pathways can also be personalised to align with the patient’s need (e.g. depending on osteoporosis risk, different physiotherapy sessions or supplements might be recommended).

  • Offering all residents in the region access to the model, including all the interventions within it.

The OptiMedis model may disproportionally benefit patients with a lower socio-economic status given rates of morbidity are higher in this group. Socio-economic status is a key predictor of health status, including in Germany. Drawing upon OECD analyses, in Germany, those in the lowest income quintile are 1.3 times more likely to have multiple chronic conditions compared to those in the highest income quintile (OECD, 2019[9]). These results are supported by patient feedback, which found self-reported health was markedly lower for poorer populations (OECD/European Observatory on Health Systems and Policies, 2021[3]). Integrated care models that take into account individual patient needs and promote care co-ordination may therefore be particularly beneficial to multimorbid patients who are typically poorer. However, to benefit from OptiMedis services, vulnerable populations may be less likely to voluntarily enrol in this model of care due to, for example, lower levels of health literacy making it difficult to access and navigate the healthcare system. For example, in Germany, differences in screening rates between the highest and lowest income quintile for cervical, breast and colorectal cancer are 13, 2 and 6 percentage points, respectively (with rates higher for those in the top income quintile) (OECD, 2019[9]). Therefore, outreach models, such as Health Coaches, Healthcare Navigators or the Health Kiosk are of importance.

Estimates regarding the effectiveness and efficiency of OptiMedis were calculated using neural networks and OECD’s SPHeP-NCD microsimulation model. In-depth details of the microsimulation model are explained elsewhere: http://oecdpublichealthexplorer.org/ncd-doc/.

To estimate the health and economic gains from OptiMedis, OECD models relied on inputs from (Schubert et al., 2016[8]), which estimated the impact of OptiMedis on the mortality rate. This section assesses the quality of this study using the Quality Assessment Tool for Quantitative Studies developed by the Effective Public Health Practice Project (Effective Public Health Practice Project, 1998[10]) (Table 3.1). The assessment shows that the study by (Schubert et al., 2016[8]) used strong data collection methods and adequately controlled for confounding factors.

According to data form the region of Kinzigtal, approximately one-third of eligible residents are enrolled in the OptiMedis model. As outlined under the “Intervention description”, around 50% of all residents living with the region of Kinzigtal receive health insurance through one of the two sickness funds that have contracts with GK Limited (i.e. approx. 35 000 people). Of these eligible residents, around one-third (i.e. 10 500) voluntarily enrolled in the OptiMedis integrated care model.

Data is not available to assess what proportion of eligible health professionals and providers enrol in the OptiMedis integrated care model. However, the gross number of professionals enrolled in the programme as of 2022 in the region of Kinzigtal are as follows:5

  • 52 physicians and psychotherapists

  • 20 clinics and nursing care centres

  • 30 providers of nursing care and physiotherapy

  • 50 associations

  • 20 pharmacies

  • 23 businesses participating in workplace health promotion programs.

This section outlines policy options to enhance the performance of the OptiMedis model against each of the five best practice criteria. Policies target either OptiMedis administrators or higher level policy makers within the German healthcare system.

Proactively identify high-risk patients who stand to benefit most from integrated care. Patients who are at high risk of developing complex health needs stand to benefit most from accessing preventative care offered as part of OptiMedis. Policy makers should therefore consider ways to proactively identify at-risk patients and direct them to OptiMedis prevention services. This will not only improve population health outcomes, but also economic outcomes by reducing demand for healthcare services and increasing productivity.

The shared savings contract is a key feature of the OptiMedis model (see “Intervention description”). For this reason, no recommendations on how to enhance efficiency are included in this report. However, it is acknowledged that any future expansion of the model may lead to efficiency savings, particularly in regard to “back of office” activities, such as data management, data analytics, development of care programmes, dashboard development, digital transformation projects, IT support and general administrative support (controlling). Further, as outlined under “Enhancing effectiveness”, proactively identifying patients who would benefit from OptiMedis prevention programs will reduce costs and boost productivity.

Expand the Health Kiosk to other eligible regions. As outlined under “Equity”, one of the key interventions to promote health equity under the OptiMedis integrated care model is the Health Kiosk. At present, the Health Kiosk only exists within the city of Hamburg, however, there are plans to expand it to other regions in the country. This proposal is highly recommended given disadvantaged groups, such as those with a migrant background, are at greater risk of developing complex health needs. Any transfers of the Health Kiosk, however, should be adapted to the needs of the local population. This requires a contextual analysis of the region covering factors such as population health needs, race/ethnicity structure, health literacy levels, utilisation patterns, structure and coverage of health services, and workforce skills. For further details on the types of contextual factors to consider before transferring an intervention, see OECD’s Guidebook on Best Practices in Public Health (OECD, 2022[12]).

Improve access to healthcare services for disadvantaged groups by promoting health literacy. Disadvantaged groups, such as those with a lower socio-economic status, are less likely to access necessary healthcare services (OECD, 2019[9]). For example, across the OECD, 74% of people in the highest income quintile have been screened for breast cancer compared to 63% among those in the lowest income quintile (OECD, 2019[9]). Although disadvantaged groups stand to benefit most the OptiMedis model, which incentivises high-quality, preventative care, they may be less likely to voluntarily enrol (however, it is noted that many people enrolled in the model of care after having visited a Health Kiosk). Programs that promote health literacy among disadvantaged groups may increase voluntarily enrolment rates (see Box 3.3 for further details).

Listed below are recommendations to enhance the data collected as part of the OptiMedis programme. These suggestions are based on a review of current data collection protocols.

  • Collect data from two identical treatment groups, i.e. control and experimental groups, up to a small statistical error (e.g. data on health status and utilisation). Ideally this would be achieved through a randomised control trial (RCT) given such studies are considered the “gold standard” for assessing the impact of an intervention. However, RCTs are not always plausible, for example due to high costs or difficulty achieving randomised participation. In that regard, OptiMedis has co-published a qualitative comparison of several economic evaluation methods for integrated care systems, which aims to find a balance between statistical power and practical feasibility (Pimperl et al., 2014[14]);

  • Collect data simultaneously in several regions in order to improve data representativeness;

  • Collect information about how the intervention is implemented (for example, what are the inclusion criteria; action plan for each health profile) to improve modelling capabilities;

  • Elicit the theory of change underlying the interventions, ideally at the start of the initiative.

Consider setting targets on the proportion of patients who have enrolled in an integrated care programme. Providing integrated care centred on patient needs is widely recognised as best practice for treating patients with complex health needs. Despite this, population based integrated care models are not common across OECD countries, including Germany. To boost uptake in voluntary integrated care models, such as the OptiMedis model, policy makers could consider setting a target – i.e. the proportion of the population enrolled in an integrated care model.

Develop a multi-pronged recruitment strategy covering a range of different places, such as those outlined in Box 3.4.

This section explores the transferability of the OptiMedis model and is broken into three components: 1) an examination of previous transfers; 2) a transferability assessment using publicly available data; and 3) additional considerations for policy makers interested in transferring this intervention.

At present, the OptiMedis model has been implemented in three different regions, however, long-term experience and evaluations only exist for the Kinzigtal region of south-west Germany. There are active discussions to expand the model of care to other regions in the country.

In an integrated care handbook outlining the OptiMedis model, it was noted “that the results from the [model] can be successfully transferred and achieved elsewhere, including in regions that are different in population structure and health service organisation” (Amelung et al., 2021[16]). The report also outlined several core features of the OptiMedis model that should be replicated in future implementations, as well as implementation facilitators – see Box 3.5.

Finally, although regions outside Germany have not implemented the OptiMedis model, it should be noted that the underlying features that support the model exist across most OECD countries (e.g. the chronic care model, preventative care, case management, multidisciplinary care teams, electronic patient data sharing, and personalised care plans). Further, there are active discussions in regions of France (Strasbourg) and Belgium (Germany speaking community) to transfer this model of care as part of the EU Joint Action on implementation of digitally enabled person-centred care (JADECARE).

The following section outlines the methodological framework to assess transferability and results from the assessment.

A few indicators to assess the transferability of the OptiMedis model were identified (see Table 14.4). Indicators were drawn from international databases and surveys to maximise coverage across OECD and non-OECD European countries. Please note, the assessment is intentionally high level given the availability of public data covering OECD and non-OECD European countries.

Results from the analysis are outlined in Table 3.3 with a summary provided below:

  • The proportion of countries whose GPs work in single-handed practices is lower among OECD and EU27 countries when compared to Germany – i.e. the proportion in Germany is “high” (>50%) compared to two-thirds of remaining countries with available data where the proportion is either “low” (<27%) or “medium” (28-50%). Similarly, levels of task-shifting between doctors and nurses is non-existent in Germany. Both results indicate relative to Germany, GPs in remaining OECD and EU27 countries are more likely to undertaken their work as part of a multidisciplinary team.

  • Rates of electronic healthcare record (EHR) use, both in primary and secondary care, is similar in Germany when compared to the OECD and EU27 average. This result masks differences at the individual country level, for example, in Nordic countries such as Denmark, Iceland and Finland, EHR use is at 100% across the healthcare system compared to around a third or less in countries such as Japan and Poland. Countries where EHR use is relatively low may experience barriers to providing integrated care across given difficulties in sharing patient data.

  • Financially, as a proportion of total health expenditure, Germany spends more on primary care and prevention than the average OECD/EU27 country. Germany also has financial incentives for delivering co-ordinated care, while many OECD/EUR27 countries do not.

To help consolidate findings from the transferability assessment above, countries have been clustered into one of three groups, based on indicators reported in Table 14.4. Countries in clusters with more positive values have the greatest transfer potential. For further details on the methodological approach used, please refer to Annex A.

Key findings from each of the clusters are below with further details in Figure 3.6 and Table 3.4:

  • Countries in cluster one typically have healthcare systems that promote integrated care. Further, these countries spend relatively high amounts on primary care and prevention. This cluster includes Germany, where OptiMedis currently operates in certain regions.

  • Countries in cluster two also have healthcare systems that promote integrated care. However, they spend relatively less on primary care and prevention, which may hinder long-term sustainability of integrated care models focused on avoiding or delaying complex health needs.

  • Countries in cluster three should consider whether their healthcare systems are ready to implement population based integrated care models, and also whether such a model is affordable in the long-term.

Data from publicly available datasets alone is not ideal to assess the transferability of public health interventions. Box 3.6 outlines several new indicators, or factors, policy makers could consider before transferring the OptiMedis integrated care model.

Policy changes in Germany to promote care co-ordination led to the implementation of the OptiMedis model. Germany’s healthcare system is complex due to the separation of legislative, planning and regulatory power across different sectors. In an effort to improve care co-ordination, the government implemented several policies including the 2004 Social Health Insurance Modernisation Act. Following on from this Act, OptiMedis implemented its regionally based population integrated care model in certain regions in Germany.

The OptiMedis model offers patients co-ordinated care across all health sectors with a focus on prevention. Insurees of any sickness fund that has a contract with OptiMedis can voluntarily enrol in the integrated care model. Those who enrol have access to all healthcare services plus additional interventions that promote care co-ordination and prevention. There is a shared savings contract exists between sickness funds and OptiMedis in order to incentivise high quality care. The difference is calculated by subtracting the money spent on patients from the amount sickness funds receive from the central payment authority.

OptiMedis leads to an improvement in health outcomes as well as cost savings based on modelling estimates. For example, OECD countries, on average, could expect to gain 9.7 LY and 6.5 DALYs per 100 000 people per year between years 2022 and 2050 by operating the OptiMedis model of care. From an efficiency point of view, OptiMedis has the potential to reduce health expenditure by an amount equivalent to 4% of their total spending on health.

To successfully transfer this model of care, OptiMedis administrators have outlined several core features and implementation facilitators. These include, but are not limited to, ensuring the population size is no longer than 100 000, fostering a culture of both co-operation and competition, and developing a comprehensive information-technology package that has the capability of undertaking advanced data analytics.

Box 3.7 outlines next steps for policy makers and funding agencies in regard to the OptiMedis model.


[5] Amelung, V. et al. (2017), Handbook Integrated Care, Springer International Publishing, Cham, Swizerland.

[16] Amelung, V. et al. (eds.) (2021), Handbook Integrated Care, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-69262-9.

[1] Blümel, M. et al. (2020), Germany: Health system review, European Observatory of Health Systems and Polciies, https://eurohealthobservatory.who.int/publications/i/germany-health-system-review-2020.

[15] Center for Consumer Engagement in Health Innovation (2021), Person-Centered Enrollment Strategies for Integrated Care Toolkit, https://www.healthinnovation.org/resources/toolkits/person-centered-enrollment-strategies-for-integrated-care-toolkit.

[10] Effective Public Health Practice Project (1998), Quality Assessment Tool for Quantitative Studies, https://www.ephpp.ca/quality-assessment-tool-for-quantitative-studies/ (accessed on 28 July 2021).

[11] Effective Public Health Pratice Project (1998), Quality assessment tool for quantitative studies, https://www.nccmt.ca/knowledge-repositories/search/14.

[22] European Observatory on Health Systems and Policies (2021), The Health Systems and Policy Monitor, https://eurohealthobservatory.who.int/countries/overview (accessed on 9 June 2021).

[20] Maier, C. and L. Aiken (2016), “Task shifting from physicians to nurses in primary care in 39 countries: a cross-country comparative study”, The European Journal of Public Health, Vol. 26/6, pp. 927-934, https://doi.org/10.1093/eurpub/ckw098.

[18] Oderkirk, J. (2017), “Readiness of electronic health record systems to contribute to national health information and research”, OECD Health Working Papers, No. 99, OECD Publishing, Paris, https://doi.org/10.1787/9e296bf3-en.

[12] OECD (2022), Guidebook on Best Practices in Public Health, OECD Publishing, Paris, https://doi.org/10.1787/4f4913dd-en.

[23] OECD (2021), Health for the People, by the People: Building People-centred Health Systems, OECD Health Policy Studies, OECD Publishing, Paris, https://doi.org/10.1787/c259e79a-en.

[2] OECD (2020), Current expenditure on health (all functions and providers) as a % of GDP.

[4] OECD (2020), Realising the Potential of Primary Health Care, OECD Health Policy Studies, OECD Publishing, Paris, https://doi.org/10.1787/a92adee4-en.

[9] OECD (2019), Health for Everyone?: Social Inequalities in Health and Health Systems, OECD Health Policy Studies, OECD Publishing, Paris, https://doi.org/10.1787/3c8385d0-en.

[13] OECD (2018), “Health literacy for people-centred care: Where do OECD countries stand?”, OECD Health Working Papers, No. 107, OECD Publishing, Paris, https://doi.org/10.1787/d8494d3a-en.

[21] OECD (2016), Health Systems Characteristics Survey 2016, https://qdd.oecd.org/subject.aspx?Subject=hsc.

[3] OECD/European Observatory on Health Systems and Policies (2021), Germany: Country Health Profile 2021, OECD Publishing, Paris, https://doi.org/10.1787/e4c56532-en.

[14] Pimperl, A. et al. (2014), “Ökonomische Erfolgsmessung von integrierten Versorgungsnetzen – Gütekriterien, Herausforderungen, Best-Practice-Modell”, Das Gesundheitswesen, Vol. 77/12, pp. e184-e193, https://doi.org/10.1055/s-0034-1381988.

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[8] Schubert, I. et al. (2016), “Evaluation der populationsbezogenen ‚Integrierten Versorgung Gesundes Kinzigtal‘ (IVGK). Ergebnisse zur Versorgungsqualität auf der Basis von Routinedaten”, Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen, Vol. 117, pp. 27-37, https://doi.org/10.1016/j.zefq.2016.06.003.

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The table below outlines the assumptions and methodology used to model the effectiveness and efficiency of the OptiMedis integrated care model. The assumptions are broken down as follows: target group, exposure among the target group, effectiveness, timeframe, and costs.

The methodology can be split into two logical and chronological parts. First, by means of a machine learning tool provided by the OECD Secretariat, OptiMedis has trained a neural network from its own real patient-level data and sent back the output file to the OECD Secretariat. This neural network has been designed to estimate the health expenditure from patients’ characteristics (age, sex, diagnoses). Then, for each target country, the OECD Secretariat has simulated a set of 20 random synthetic patient-level data and computed the related health expenditure (HE), LYs and DALYs by means of the neural network and its own microsimulation model. The resulting HE, LYs and DALYs have been averaged over the 20 samples in order to get an accurate an estimate of these quantities.


← 1. Figures are from 2019 to avoid increases in spending due to COVID-19.

← 2. As above.

← 3. Expected costs are calculated according to the risk-adjusted funds received by the sickness funds to care for their contracted insurees from the central authority (Gesundheitsfonds).

← 4. In the German region of Kinzigtal, Gesundes Kinzigtal (of which OptiMedis is a 33% shareholder) invested EUR 1 million to design an e-patient record. The record is compatible with IT systems in each practice, further patient data can be shared across practices. In GWMK, OptiMedis are in the process of implementing a large digital toolbox capable of sharing data between providers, patients and caregivers (i.e. ADLIFE Project).

← 5. Note, figures frequently change.


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