Business Intelligence in the Context of Integrated Care Systems (ICS): Experiences from the ICS “Gesundes Kinzigtal” in Germany

Pimperl, Alexander; Schulte, Timo; Hildebrandt, Helmut

doi:10.1007/978-3-319-25226-1_2

Cited by 4 publications

(5 citation statements)

References 20 publications

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“…The database used for this study is deidentified insured-level claims data ( n = 69,392) from two regional integrated care networks of OptiMedis AG, an integrated care management organization [ 26 ]. The regions are set as one rural and one urban area, each accounting for nearly half of the population size.…”

Section: Methodsmentioning

confidence: 99%

Big Data Analytics to Reduce Preventable Hospitalizations—Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions

Schulte

Wurz

Groene

et al. 2023

IJERPH

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The purpose of this study was to develop a prediction model to identify individuals and populations with a high risk of being hospitalized due to an ambulatory care-sensitive condition who might benefit from preventative actions or tailored treatment options to avoid subsequent hospital admission. A rate of 4.8% of all individuals observed had an ambulatory care-sensitive hospitalization in 2019 and 6389.3 hospital cases per 100,000 individuals could be observed. Based on real-world claims data, the predictive performance was compared between a machine learning model (Random Forest) and a statistical logistic regression model. One result was that both models achieve a generally comparable performance with c-values above 0.75, whereas the Random Forest model reached slightly higher c-values. The prediction models developed in this study reached c-values comparable to existing study results of prediction models for (avoidable) hospitalization from the literature. The prediction models were designed in such a way that they can support integrated care or public and population health interventions with little effort with an additional risk assessment tool in the case of availability of claims data. For the regions analyzed, the logistic regression revealed that switching to a higher age class or to a higher level of long-term care and unit from prior hospitalizations (all-cause and due to an ambulatory care-sensitive condition) increases the odds of having an ambulatory care-sensitive hospitalization in the upcoming year. This is also true for patients with prior diagnoses from the diagnosis groups of maternal disorders related to pregnancy, mental disorders due to alcohol/opioids, alcoholic liver disease and certain diseases of the circulatory system. Further model refinement activities and the integration of additional data, such as behavioral, social or environmental data would improve both model performance and the individual risk scores. The implementation of risk scores identifying populations potentially benefitting from public health and population health activities would be the next step to enable an evaluation of whether ambulatory care-sensitive hospitalizations can be prevented.

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Section: Methodsmentioning

confidence: 99%

Big Data Analytics to Reduce Preventable Hospitalizations—Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions

Schulte

Wurz

Groene

et al. 2023

IJERPH

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“…Chaudhry and Dhingra [45], who performed qualitative research with 11 NI-based SMEs, offered several suggestions for facilitating the implementation of BI&BA. While Pimperl, Schulte, and Hildebrandt in [46] conducted an exploratory investigation of BI&BA application in German SMEs in order to identify underlying elements linked to the ideology of BI&BA's organizational determinants, obstacles, and advantages, their research did not find any significant differences between the two groups. Gauzelin and Bentz in [47] found seven NACs of a BI&BA frameworks through empirical research with twenty French firms.…”

Section: Biandba Adoptionmentioning

confidence: 98%

A Review of Business Intelligence and Analytics in Small and Mediumsized Enterprises

Ericsson

Persson

2022

JEBI

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This paper provides a critical review of the adoption of Business Intelligence and Business Analytics (BI&BA) in SMEs. Business Intelligence (BI), Business Analytics (BA), Small and Medium-sized Enterprises (SMEs), and their respective combinations were among the keywords searched to find as many relevant articles as possible for this review. Business Analytics (BA) relies heavily on predictive and explanatory modeling, fact-based management, numerical analytic and analytical modeling to guide decision-making. Business intelligence (BI), on the other hand, help entrepreneurs manage their budgets and allocate resources more effectively. In this paper, BI&BA (Business Intelligence and Business Analytics) has been utilized to cover these data-centric criteria to enhancing corporate decision-making process within SMEs. BI&BA seems to be a top technical option for enhancing competitive advantage in SMEs, which have not embraced the BI&BA technology in their business activities. This paper further reviews the assumptions from various aspects such as BI&BA elements, BI&BA solution, BI&BA implementation, BI&BA benefits, BI&BA applications, BI&BA adoption, cloud BI&BA, and mobile BI&BA.

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“…Gesundes Kinzigtal GmbH has built a health network of numerous local partners and is able to invest about 3 million € each year into the health of the insured through a variety of health care management services as well as health and prevention programs because of its share of the savings that are produced by these activities [37].…”

Section: Pharmacists' Involvement In a Pilot Of Integratedmentioning

confidence: 99%

“…Traditionally, cooperation between physicians and pharmacists in Germany has been limited to positive individual cases, whereas at the association level it has been burdened with mutual reservations and demarcations (according to the motto "Schuster bleib bei deinem Leisten", "Cobblers stick to your last" or "This is our turf"). Insofar even the somehow limited integration of pharmacists in Kinzigtal was far ahead of normal cooperation between pharmacists and physicians (Table 3) [37][38].…”

Section: Pharmacists' Involvement In a Pilot Of Integratedmentioning

confidence: 99%

“…A new law from the ministry of health was just processed that proposes experiments in these forms of pharmaceutical care and models for remuneration [Gesetz zur Stärkung der Vor-Ort-Apotheken, 2019]. The professional associations of physicians disagreed but the head of the organization of pharmacists in Germany ABDA made a press release urging for new pharmaceutical care to be remunerated and detailing the possible interventions [37][38][39].…”

Section: New Federal Law On Remuneration Of Pharmaceutical Carementioning

confidence: 99%

See 1 more Smart Citation

Population Health Management Approach: Integration of Community-Based Pharmacists into Integrated Care Systems: Reflections from the U.S., Achievements in Scotland and Discussions in Germany

Lyles¹,

Hildebrandt²,

Mair

2020

International Journal of Integrated Care

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Business Intelligence in the Context of Integrated Care Systems (ICS): Experiences from the ICS “Gesundes Kinzigtal” in Germany

Cited by 4 publications

References 20 publications

Big Data Analytics to Reduce Preventable Hospitalizations—Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions

Big Data Analytics to Reduce Preventable Hospitalizations—Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions

A Review of Business Intelligence and Analytics in Small and Mediumsized Enterprises

Population Health Management Approach: Integration of Community-Based Pharmacists into Integrated Care Systems: Reflections from the U.S., Achievements in Scotland and Discussions in Germany

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