Comprehensive Life Cycle Support for Access Rules in Information Systems: The CEOSIS Project

The definition and management of access rules (e.g., to control access to business documents and business functions) is a fundamental task in any enterprise information system (EIS). While there exists considerable work on how to specify and represent access rules, only little research has been spent on access rule changes. Examples include the evolution of organizational models with need for subsequent adaptation of related access rules as well as direct access rule modifications (e.g., to state a previously defined rule more precisely). This paper presents a comprehensive change framework for the controlled evolution of role-based access rules in EIS. First, we consider changes of organizational models and elaborate how they affect existing access rules. Second, we define change operations which enable direct adaptations of access rules. In the latter context, we define the formal semantics of access rule changes based on operator trees. Particularly, this enables their unambiguous application; i.e., we can precisely determine which effects are caused by respective rule changes. This is important, for example, to be able to efficiently and correctly adapt user worklists in process-aware information systems. Altogether this paper contributes to comprehensive life cycle support for access rules in (adaptive) EIS

Routinedaten aus notaufnahmen: unterschiedliche dokumentationsanforderungen, abrechnungsmodalitäten und datenhalter bei identischem ort der leistungserbringung / Routine data from emergency departments: varying documentation standards, billing modalities and data custodians at an identical unit of care

[German abstract] Hintergrund Nicht nur im Kontext der Neuordnung der Notfallversorgung in Deutschland besteht derzeit ein hoher Bedarf an Daten aus Notaufnahmen. Für die Versorgungsforschung bieten sich Daten an, welche auf gesetzlicher Grundlage generiert werden. Unterschiedliche Kostenträger und Abrechnungsmodi stellen eigene Anforderungen an die Dokumentation dieser Routinedaten. Methodische Herausforderungen Aufgrund der sektoralen Trennung gibt es keinen Datensatz oder Datenhalter, der Auskunft über alle Notaufnahmebehandlungen geben kann. Aus administrativer Sicht gilt die gesamte Notaufnahmebehandlung als ambulant oder stationär, tatsächlich wird die Entscheidung darüber erst während der Versorgung getroffen. Für die stationäre Versorgung existiert ein administratives Notfallkennzeichen, allerdings kein direktes Merkmal für Notaufnahmebehandlungen. Bei Abrechnung ambulanter Fälle über die kassenärztlichen Vereinigungen ist mindestens eine Diagnose (ICD-10-Kode) zu erfassen, versehen mit einem Kennzeichen zur Diagnosesicherheit. Es können mehrere ICD-10-Kodes ohne Hierarchie angegeben werden. Bei stationär behandelten Patienten ist eine Aufnahmediagnose und nach Behandlungsende die Hauptdiagnose und ggf. Nebendiagose(n) an die zuständige Krankenkasse zu übermitteln. Die gesetzliche Unfallversicherung hat eigene Dokumentationsanforderungen. Lösungsansätze Je nach Forschungsfrage und Studiendesign sind unterschiedliche Vorgehensweisen erforderlich. Stammen die Daten unmittelbar aus Notaufnahmen bzw. Kliniken ist eine Information über den Kostenträger und den Abrechnungsmodus hilfreich. Bei Nutzung von Krankenkassendaten muss die Identifikation von stationär behandelten Patienten in einer Notaufnahme aktuell indirekt erfolgen. Dazu können unter anderem die Parameter Aufnahmegrund und definierte „eindeutige“ Notfall-Diagnosen herangezogen werden. Die fallpauschalenbezogene Krankenhausstatistik hat eigene Limitationen, enthält dafür aber die stationären Fälle aller Kostenträger. Diskussion Die divergierenden Anforderungen an die administrative Dokumentation verursachen einen hohen Aufwand in den Kliniken. Perspektivisch ist eine Vereinheitlichung der Leistungserfassung und Dokumentation von Notfallbehandlungen aller Kostenarten auch zur Generierung von validen, vergleichbaren und repräsentativen Daten für die Versorgungsforschung erstrebenswert. Die Einführung eines eigenen Fachabteilungsschlüssels würde zur Identifikation von Notaufnahmebehandlungen beitragen. [English abstract] Background Currently, there is a big need for data on emergency department (ED) utilization in Germany. One reason is the ongoing reorganisation of emergency care. Possible sources are routine data that are being collected based on legal regulations. Different payers and compensation systems have their own requirements for data collection. Methodological challenges Due to the sectoral separation of health care services, there is no dataset or data holder to provide information on all ED treatments in Germany. From an administrative point of view, emergency care in Germany is considered ambulatory outpatient or inpatient care from the time point of admission to the ED. In contrast, clinical decision about inpatient admission can sometimes only be made towards the end of emergency care. EDs themselves cannot be identified in claims data; only the medical discipline (e. g. surgery) is classified. In the case of outpatient treatment, reimbursed by the Association of Statutory Health Insurance Physicians, at least one coded diagnosis (ICD) has to be recorded, accompanied by an additional code for the likelihood of this diagnosis. In case of multiple ICDs, a primary diagnosis cannot be specified. In the case of in-hospital treatment, an admission diagnosis must be recorded. After completion of hospital treatment, the main diagnosis and possibly secondary diagnoses are transferred to the respective health insurance fund. The statutory occupational accident insurance has its own requirements. Solutions Depending on the research question and study design, different approaches are required. If data are queried directly in emergency departments or hospitals, additional information on the designated data holder and billing mode is crucial. When using health insurance data from inpatient care, the identification of emergency departments can be estimated on the basis of the reason for hospital admission and defined "unique" emergency ICDs. The case-related hospital statistics has its own limitations, but includes inpatients of all payers. Discussion Differing requirements for the administrative documentation cause a high workload in emergency departments. A standardised data collection system for all payers for inpatient and outpatient emergency care is recommended. This would contribute to the creation of valid and comparable datasets. The introduction of a particular identifier for EDs in claims data would enhance health services research

Gute Praxis Datenlinkage (GPD) : Good Practice Data Linkage

Das personenbezogene Verknüpfen verschiedener Datenquellen (Datenlinkage) für Forschungszwecke findet in den letzten Jahren in Deutschland zunehmend Anwendung. Jedoch fehlen hierfür konsentierte methodische Standards. Ziel dieses Beitrages ist es, solche Standards für Forschungsvorhaben zu definieren. Eine weitere Intention ist es, dem Lesenden eine Checkliste zur Bewertung geplanter Forschungsvorhaben und Artikel bereitzustellen. Zu diesem Zweck hat eine aus Mitgliedern verschiedener Fachgesellschaften zusammengesetzte Expertengruppe seit 2016 insgesamt 7 Leitlinien mit 27 konkreten Empfehlungen erstellt. Die Gute Praxis Datenlinkage beinhaltet die folgenden Leitlinien: (1) Forschungsziele, Fragestellung, Datenquellen und Ressourcen, (2) Dateninfrastruktur und Datenfluss, (3) Datenschutz, (4) Ethik, (5) Schlüsselvariablen und Linkageverfahren, (6) Datenprüfung/Qualitätssicherung sowie (7) Langfristige Datennutzung für noch festzulegende Fragestellungen. Jede Leitlinie wird ausführlich diskutiert. Zukünftige Aktualisierungen werden wissenschaftliche und datenschutzrechtliche Entwicklungen berücksichtigen

Health service utilization patterns of primary care patients with osteoarthritis

Contains fulltext : 53455.pdf ( ) (Open Access)BACKGROUND: To assess factors associated with visits to GPs, orthopaedists, and non-physician practitioners of complementary medicine (alternative practitioners) by primary care patients with osteoarthritis (OA). METHODS: Cross-sectional survey among 1250 consecutively addressed patients from 75 primary care practices in Germany. All patients suffered from OA of the knee or hip according to ACR criteria. They received questionnaires collecting sociodemographic data, data about health service utilisation, prescriptions, comorbidities. They also included established instruments as the Arthritis Impact Measurement Scale (AIMS2-SF) to assess disease-specific quality of life and the Patient Health Questionnaire (PHQ-9) to assess depression. Hierarchical stepwise multiple linear regression models were used to reveal significant factors influencing health service utilization. RESULTS: 1021 of 1250 (81.6%) questionnaires were returned. Nonrespondents did not differ from participants. Factors associated with health service use (HSU) varied between providers of care. Not being in a partnership, achieving a high score on the PHQ-9, increased pain severity reflected in the "symptom" scale of the AIMS2-SF, and an increased number of drug prescriptions predicted a high frequency of GP visits. The PHQ-9 score was also a predictor for visits to orthopaedists, as were previous GP contacts, a high score in the "symptom" scale as well as a high score in the "lower limb scale" of the AIMS2-SF. Regarding visits to alternative practitioners, a high score in the AIMS -"social" scale was a positive predictor as older people were less likely to visit them. CONCLUSION: Our results emphasize the need for awareness of psychological factors contributing to the use of health care providers. Addressing the revealed factors associated with HSU appropriately may lead to decreased health care utilization. But further research is needed to assess how this can be done successfully

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

A study of CP violation in B-+/- -> DK +/- and B-+/- -> D pi(+/-) decays with D -> (KSK +/-)-K-0 pi(-/+) final states

A first study of CP violation in the decay modes $B^\pm\to [K^0_{\rm S} K^\pm \pi^\mp]_D h^\pm$ and $B^\pm\to [K^0_{\rm S} K^\mp \pi^\pm]_D h^\pm$, where $h$ labels a $K$ or $\pi$ meson and $D$ labels a $D^0$ or $\overline{D}^0$ meson, is performed. The analysis uses the LHCb data set collected in $pp$ collisions, corresponding to an integrated luminosity of 3 fb$^{-1}$. The analysis is sensitive to the CP-violating CKM phase $\gamma$ through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of $\gamma$ using other decay modes

Measurement of the (eta c)(1S) production cross-section in proton-proton collisions via the decay (eta c)(1S) -> p(p)over-bar

The production of the $\eta_c (1S)$ state in proton-proton collisions is probed via its decay to the $p \bar{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5$ GeV/c. The cross-section for prompt production of $\eta_c (1S)$ mesons relative to the prompt $J/\psi$ cross-section is measured, for the first time, to be $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.74 \pm 0.29 \pm 0.28 \pm 0.18 _{B}$ at a centre-of-mass energy $\sqrt{s} = 7$ TeV using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$, and $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{B}$ at $\sqrt{s} = 8$ TeV using 2.0 fb$^{-1}$. The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta_c (1S)$ and $J/\psi$ decays to the $p \bar{p}$ final state. In addition, the inclusive branching fraction of $b$-hadron decays into $\eta_c (1S)$ mesons is measured, for the first time, to be $B ( b \rightarrow \eta_c X ) = (4.88 \pm 0.64 \pm 0.25 \pm 0.67 _{B}) \times 10^{-3}$, where the third uncertainty includes also the uncertainty on the $J/\psi$ inclusive branching fraction from $b$-hadron decays. The difference between the $J/\psi$ and $\eta_c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1$ MeV/c$^2$.The production of the $\eta _c (1S)$ state in proton-proton collisions is probed via its decay to the $p\overline{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5 \mathrm{{\,GeV/}{ c}}$ . The cross-section for prompt production of $\eta _c (1S)$ mesons relative to the prompt ${{ J}}/{\psi }$ cross-section is measured, for the first time, to be $\sigma _{\eta _c (1S)}/\sigma _{{{{ J}}/{\psi }}} = 1.74\, \pm \,0.29\, \pm \, 0.28\, \pm \,0.18 _{{\mathcal{B}}}$ at a centre-of-mass energy ${\sqrt{s}} = 7 {~\mathrm{TeV}}$ using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$ , and $\sigma _{\eta _c (1S)}/\sigma _{{{{ J}}/{\psi }}} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{{\mathcal{B}}}$ at ${\sqrt{s}} = 8 {~\mathrm{TeV}}$ using 2.0 fb$^{-1}$ . The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta _c (1S)$ and ${{ J}}/{\psi }$ decays to the $p\overline{p}$ final state. In addition, the inclusive branching fraction of ${b}$ -hadron decays into $\eta _c (1S)$ mesons is measured, for the first time, to be ${\mathcal{B}}( b {\rightarrow } \eta _c X ) = (4.88\, \pm \,0.64\, \pm \,0.29\, \pm \, 0.67 _{{\mathcal{B}}}) \times 10^{-3}$ , where the third uncertainty includes also the uncertainty on the ${{ J}}/{\psi }$ inclusive branching fraction from ${b}$ -hadron decays. The difference between the ${{ J}}/{\psi }$ and $\eta _c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1 {\mathrm {\,MeV\!/}c^2}$ .The production of the $\eta_c (1S)$ state in proton-proton collisions is probed via its decay to the $p \bar{p}$ final state with the LHCb detector, in the rapidity range $2.0 6.5$ GeV/c. The cross-section for prompt production of $\eta_c (1S)$ mesons relative to the prompt $J/\psi$ cross-section is measured, for the first time, to be $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.74 \pm 0.29 \pm 0.28 \pm 0.18 _{B}$ at a centre-of-mass energy $\sqrt{s} = 7$ TeV using data corresponding to an integrated luminosity of 0.7 fb$^{-1}$, and $\sigma_{\eta_c (1S)}/\sigma_{J/\psi} = 1.60 \pm 0.29 \pm 0.25 \pm 0.17 _{B}$ at $\sqrt{s} = 8$ TeV using 2.0 fb$^{-1}$. The uncertainties quoted are, in order, statistical, systematic, and that on the ratio of branching fractions of the $\eta_c (1S)$ and $J/\psi$ decays to the $p \bar{p}$ final state. In addition, the inclusive branching fraction of $b$-hadron decays into $\eta_c (1S)$ mesons is measured, for the first time, to be $B ( b \rightarrow \eta_c X ) = (4.88 \pm 0.64 \pm 0.29 \pm 0.67 _{B}) \times 10^{-3}$, where the third uncertainty includes also the uncertainty on the $J/\psi$ inclusive branching fraction from $b$-hadron decays. The difference between the $J/\psi$ and $\eta_c (1S)$ meson masses is determined to be $114.7 \pm 1.5 \pm 0.1$ MeV/c$^2$