The number of people with diabetes mellitus has rapidly increased worldwide. The World Health Organization reported that an estimated 422 million adults worldwide were living with diabetes in 2014 In Japan, the number of patients with diabetes has increased from 2.70 million in 2011 to 3.17 million in 2014, according to a patient survey by the Ministry of Health, Labour and Welfare [2].

Objective: Estimate the effects of electronic health records (EHRs) on physician productivity in day-to-day practice by including the combinations of EHRs with nonelectronic records that typify current practice. Study Design: Cross section of 7,725 physicians representing 70% of physicians who provided patient care in 2012-2014 in Arizona. The sample was divided into office based (OFB) and non-office based (NOFB) physicians. Methods: Information from licensing applications was combined with a survey of the uses of electronic and nonelectronic health records. Productivity was measured as patient visits per hour in a typical work week. The effects of EHRs on productivity were estimated from a regression model that compared users to non-users and an model that included combinations of electronic, paper and scanned records. The results are compared to the physicians’ rankings of the effect of each combination of records on staff and physician productivity. Results: The productivity of OFB physicians is increased by the use of e-prescribing (+17.4%, p<0.001) and intervention reminders (+5.7%, p=0.03). There are no significant effects of the different mixes of health records. Among NOFB physicians, e-prescribing is the only contributor to productivity (+7.7%, p=0.069). Physicians rank EHR-only as more productive than any combinations of EHRs with non-electronic records. Conclusion: The potential productivity of EHRs is severly limited by the typical practice of combining EHRs with non-electronic records. Reducing the number of different types of records used in a practice will increase the positive effects of EHRs on productivity. One requirement for such reductions is an increased availability of health information exchanges.

Background: The prevalence of noncommunicable diseases (NCDs) is increasing throughout the world, including in developing countries. An NCD prevention program using information communication technology was implemented for 2 years in Bangladesh. Health checkup data were collected from 16,741 study subjects. However, the effectiveness of the utilized prevention strategy has not yet been evaluated, and some subjects with a risk of NCD have gone undetected. Objective: This study aimed to improve intervention strategies by analyzing collected data and proposing a costeffective personalized predictive model to identify subjects predicted to be at future risk of NCD. Methods: We selected 2,110 subjects who participated in both years of the program and used a machine learning algorithm, gradient boosting decision tree, to build models that would identify subjects who were at risk of future high blood pressure, blood sugar or body mass index (BMI). We used area under the curve (AUC) of receiver operating characteristic curves and cumulative accuracy profile (CAP) curves to evaluate the performance of our models. Results: Models showed fairly good performance: the BMI model (AUC=0.910) yielded the greatest AUC whereas the BS model (AUC=0.730) yielded the lowest. CAP curves indicated that the BMI model could correctly identify 98.0% of at-risk subjects at only 50% of the total time cost. Conclusions: Our models represent powerful tools with which to improve the effect of health intervention programs and the effectiveness at which they are performed with limited medical resources.

The word information is often used without carefully distinguishing between different meanings it has taken on during its history. Generally, it refers to a finding or findings concerning facts, events, things, people, thoughts or notions, that is, a certain reflection of real or abstract objects or processes. It usually consists of its syntactic (structure), semantic (meaning), and pragmatic (goal) components. Therefore information can be defined as data that has been

Objec ves: Aiming to strengthen EU ci zens' fundamental privacy rights in the digital age the new European General Data Protec on Regula on shall apply from May 25th 2018. It will require companies processing personal data to implement a set of organiza onal and technical controls for ensuring proper handling of these data. Obviously this applies for companies providing eHealth services. As HL7 off ers a lot of material to support security and privacy for handling personal healthcare data, this paper aims at showing which HL7 standards and components can be used to support the implementa on of GDPR related controls.

Introduction: In Germany, there is currently no consistent analytic structure within genomic diagnostics in oncological diseases. Within the framework of the project GENeALYSE, a standardized and interoperable specification for associated uses cases shall be developed. Intended Methods: Through process analysis and interface modeling, problems of the actual processes will be depicted between the involved actors. In the next step, the workflows and relevant findings will be displayed and adapted. In particular, the heterogeneous workflows in genome diagnostics will be represented by semantic annotation in an international terminology. The results of the semantic annotation build the basement for the creation of an implementation guide for standardized genome analytics, referring to HL7 Clinical Document Architecture (HL7 CDA). Discussion: The problems of heterogeneous genomic diagnostics as well as unstructured findings in oncology leave the actors face comparable challenges on a regional and supranational level. Interfaces, ambiguous semantics and manual activities inhibit interoperability, promote errors and lead to risks for patients and their sufficient medical treatment. A major challenge will be consistency between the heterogeneous terms to be found in genome analysis. The problem shall be addressed via using international terminologies as well as appropriate mapping techniques. Conclusions: The aim of the project is to create an implementation guide for standardized digital documentation and communication solutions between diagnostics, medical therapy and research in the field of genome analysis. GENeALYSE is intended to optimize the coordination between the diagnostic genome laboratory and the clinical therapy decision in order to increase the safety and success of medical treatment, as well as to improve the health-related quality of life of the affected patients.

Development of HL7 v2 data exchange interface specifi ca ons has long been problema c, plagued with ambiguous and inconsistent requirement specifi ca ons.This situa on leads to poten al misinterpreta on by implementers, thus limi ng the eff ec veness of the specifi ca on and crea ng ar fi cial and unnecessary barriers to interoperability.Likewise, the ability to test implementa ons eff ec vely for conformance to the specifi ca ons is hindered.The current approach of specifi ca on development and test plan crea on relies on word processing tools, meaning implementers and testers must read and interpret the informa on in these documents and then translate it into machine-computable requirements and test asser ons.This approach is error prone-a be er methodology is needed.We present a set of produc vity tools in an integrated pla orm that allow users to defi ne and constrain HL7 v2 specifi ca ons and to develop test plans that result in machine-computable ar facts.A tes ng infrastructure and framework subsequently uses these ar facts to create conformance tes ng tools automa cally.We present and demonstrate the u lity of a pla orm for developing specifi ca ons, wri ng test plans, and crea ng tes ng tools.The value proposi on of this end-to-end methodology is explained for authors wri ng HL7 v2 specifi ca ons, for developers implemen ng interfaces, and for testers crea ng valida on tools.

Background: In a popula on health partnership, shareable clinical decision support (CDS) can reduce service duplica on and promote pa ent wellness by presen ng consistent informa on to all members of a cross-func onal, distributed care team.However, exis ng health IT standards present challenges in the exchange of CDS outputs from mul ple systems.Objec ves: To exchange and reconcile CDS outputs across systems in a partnership between an integrated health system (Deaconess Health System) and a popula on health services organiza on (Evolent Health).Methods: We developed a bi-direc onal HL7-based interface for CDS outputs between Deaconess's Electronic Health Record (EHR) and Evolent's popula on health services pla orm (PHSP).The mapping of CDS logic between systems enabled this interface to automa cally reconcile inconsistent CDS outputs.Fi een quality measure (QM)based CDS rules to iden fy care gaps were selected for this ini a ve.These care gaps remind Deaconess's clinicians to provide care or documenta on necessary for gap closure, and also guide Evolent's care management services.Results: Two months a er launch, Deaconess reconciled 14,040 care gaps from Evolent using data only available in the EHR.Addi onally, 1,047 care gaps were resolved due to pa ent refusal or clinical inappropriateness, and 246 gaps were closed by services or prescrip ons provided during clinical encounters. Conclusions:We implemented an HL7-based interface to exchange and reconcile a large volume of CDS outputs between a health system EHR and a PHSP.Future direc on is to standardize the linkage between a CDS rule and its reference QM by universal iden fi ers and a taxonomy of varia ons.

Numerous tools de ne metamodels to describe the require- ments included in CDA speci cations, the most recent and standardized one is the HL7 Templates Standard. The Templates Design resulting of this standard allow distribut- ing the CDA speci cation in a formal way. One application of this normalization is the validation of CDA documents. IHE-Europe/Gazelle team developed already a methodol- ogy named Gazelle ObjectsChecker in order to generate model-based validation of XML requirements, including HL7 CDA standard. The aim of this paper is to describe the way the re- quirements from HL7 Templates Standard are imported on Gazelle ObjectsChecker, and the bene t of such method- ology for CDA implementation guides and for CDA docu- ments validation.