A prospective observational concordance study to evaluate computational model-driven clinical practice guidelines for Type 2 diabetes mellitus

BACKGROUND

Clinical Practice Guidelines (CPGs) provide healthcare professionals with performance and decision-making support during the treatment of patients. Sometimes, however, they are poorly implemented. The IDE4ICDS platform was developed and validated with CPGs for type 2 diabetes mellitus (T2DM).

OBJECTIVE

The main objective of this paper is to present the results of the clinical validation of the IDE4ICDS platform in a real clinical environment at two health clinics in the Andalusian Public Health System (SSPA) in the southern Spanish region of Andalusia.

METHODS

National and international knowledge sources on T2DM were selected and reviewed and used to define a diabetes CPG model on the IDE4ICDS platform. Once the diabetes CPG was configured and deployed, it was validated. A total of 506 patients were identified as meeting the inclusion criteria, of whom 130 could be recruited and 89 attended the appointment.

RESULTS

A concordance analysis was performed with the kappa value. Overall agreement between the recommendations provided by the system and those recorded in each patient's EHR was good (0.61 - 0.80) with a total kappa index of 0.701, leading to the conclusion that the system provided appropriate recommendations for each patient and was therefore well-functioning.

CONCLUSIONS

A series of possible improvements were identified based on the limitations for the recovery of variables related to the quality of these recolected variables, the detection of duplicate recommendations based on different input variables for the same patient, and clinical usability, such as the capacity to generate reports based on the recommendations generated. Nevertheless, the project resulted in the IDE4ICDS platform: a Clinical Decision Support System (CDSS) capable of providing appropriate recommendations for improving the management and quality of patient care and optimizing health outcomes. The result of this validation is a safe and effective pathway for developing and adopting digital transformation at the regional scale of the use of biomedical knowledge in real healthcare.

Health data hubs: an analysis of existing data governance features for research

BACKGROUND

Digital transformation in healthcare and the growth of health data generation and collection are important challenges for the secondary use of healthcare records in the health research field. Likewise, due to the ethical and legal constraints for using sensitive data, understanding how health data are managed by dedicated infrastructures called data hubs is essential to facilitating data sharing and reuse.

METHODS

To capture the different data governance behind health data hubs across Europe, a survey focused on analysing the feasibility of linking individual-level data between data collections and the generation of health data governance patterns was carried out. The target audience of this study was national, European, and global data hubs. In total, the designed survey was sent to a representative list of 99 health data hubs in January 2022.

RESULTS

In total, 41 survey responses received until June 2022 were analysed. Stratification methods were performed to cover the different levels of granularity identified in some data hubs' characteristics. Firstly, a general pattern of data governance for data hubs was defined. Afterward, specific profiles were defined, generating specific data governance patterns through the stratifications in terms of the kind of organization (centralized versus decentralized) and role (data controller or data processor) of the health data hub respondents.

CONCLUSIONS

The analysis of the responses from health data hub respondents across Europe provided a list of the most frequent aspects, which concluded with a set of specific best practices on data management and governance, taking into account the constraints of sensitive data. In summary, a data hub should work in a centralized way, providing a Data Processing Agreement and a formal procedure to identify data providers, as well as data quality control, data integrity and anonymization methods.

FAIR principles to improve the impact on health research management outcomes

Background

The FAIR principles, under the open science paradigm, aim to improve the Findability, Accessibility, Interoperability and Reusability of digital data. In this sense, the FAIR4Health project aimed to apply the FAIR principles in the health research field. For this purpose, a workflow and a set of tools were developed to apply FAIR principles in health research datasets, and validated through the demonstration of the potential impact that this strategy has on health research management outcomes.

Objective

This paper aims to describe the analysis of the impact on health research management outcomes of the FAIR4Health solution.

Methods

To analyse the impact on health research management outcomes in terms of time and economic savings, a survey was designed and sent to experts on data management with expertise in the use of the FAIR4Health solution. Then, differences between the time and costs needed to perform the techniques with (i) standalone research, and (ii) using the proposed solution, were analyzed.

Results

In the context of the health research management outcomes, the survey analysis concluded that 56.57% of the time and 16800 EUR per month could be saved if the FAIR4Health solution is used.

Conclusions

Adopting principles in health research through the FAIR4Health solution saves time and, consequently, costs in the execution of research involving data management techniques.

Correction: A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study

[This corrects the article DOI: 10.2196/27990.].

A Personalized Ontology-Based Decision Support System for Complex Chronic Patients: Retrospective Observational Study

BACKGROUND

Due to an increase in life expectancy, the prevalence of chronic diseases is also on the rise. Clinical practice guidelines (CPGs) provide recommendations for suitable interventions regarding different chronic diseases, but a deficiency in the implementation of these CPGs has been identified. The PITeS-TiiSS (Telemedicine and eHealth Innovation Platform: Information Communications Technology for Research and Information Challenges in Health Services) tool, a personalized ontology-based clinical decision support system (CDSS), aims to reduce variability, prevent errors, and consider interactions between different CPG recommendations, among other benefits.

OBJECTIVE

The aim of this study is to design, develop, and validate an ontology-based CDSS that provides personalized recommendations related to drug prescription. The target population is older adult patients with chronic diseases and polypharmacy, and the goal is to reduce complications related to these types of conditions while offering integrated care.

METHODS

A study scenario about atrial fibrillation and treatment with anticoagulants was selected to validate the tool. After this, a series of knowledge sources were identified, including CPGs, PROFUND index, LESS/CHRON criteria, and STOPP/START criteria, to extract the information. Modeling was carried out using an ontology, and mapping was done with Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) and Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT; International Health Terminology Standards Development Organisation). Once the CDSS was developed, validation was carried out by using a retrospective case study.

RESULTS

This project was funded in January 2015 and approved by the Virgen del Rocio University Hospital ethics committee on November 24, 2015. Two different tasks were carried out to test the functioning of the tool. First, retrospective data from a real patient who met the inclusion criteria were used. Second, the analysis of an adoption model was performed through the study of the requirements and characteristics that a CDSS must meet in order to be well accepted and used by health professionals. The results are favorable and allow the proposed research to continue to the next phase.

CONCLUSIONS

An ontology-based CDSS was successfully designed, developed, and validated. However, in future work, validation in a real environment should be performed to ensure the tool is usable and reliable.

FAIRness for FHIR: Towards Making Health Datasets FAIR Using HL7 FHIR

Medical data science aims to facilitate knowledge discovery assisting in data, algorithms, and results analysis. The FAIR principles aim to guide scientific data management and stewardship, and are relevant to all digital health ecosystem stakeholders. The FAIR4Health project aims to facilitate and encourage the health research community to reuse datasets derived from publicly funded research initiatives using the FAIR principles. The 'FAIRness for FHIR' project aims to provide guidance on how HL7 FHIR could be utilized as a common data model to support the health datasets FAIRification process. This first expected result is an HL7 FHIR Implementation Guide (IG) called FHIR4FAIR, covering how FHIR can be used to cover FAIRification in different scenarios. This IG aims to provide practical underpinnings for the FAIR4Health FAIRification workflow as a domain-specific extension of the GoFAIR process, while simplifying curation, advancing interoperability, and providing insights into a roadmap for health datasets FAIR certification.

FAIR4Health: Findable, Accessible, Interoperable and Reusable data to foster Health Research

Due to the nature of health data, its sharing and reuse for research are limited by ethical, legal and technical barriers. The FAIR4Health project facilitated and promoted the application of FAIR principles in health research data, derived from the publicly funded health research initiatives to make them Findable, Accessible, Interoperable, and Reusable (FAIR). To confirm the feasibility of the FAIR4Health solution, we performed two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations. The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Finally, we promoted the FAIRified data to share and reuse in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR principles in health research and preparing the ground for a roadmap for health research institutions. This scientific report presents a general overview of the FAIR4Health solution: from the FAIRification workflow design to translate raw data/metadata to FAIR data/metadata in the health research domain to the FAIR4Health demonstrators' performance.

Distinct nitrogen isotopic compositions of healthy and cancerous tissue in mice brain and head&neck micro-biopsies

BACKGROUND

Cancerous cells can recycle metabolic ammonium for their growth. As this ammonium has a low nitrogen isotope ratio (15N/14N), its recycling may cause cancer tissue to have lower 15N/14N than surrounding healthy tissue. We investigated whether, within a given tissue type in individual mice, tumoral and healthy tissues could be distinguished based on their 15N/14N.

METHODS

Micro-biopsies of murine tumors and adjacent tissues were analyzed for 15N/14N using novel high-sensitivity methods. Isotopic analysis was pursued in Nude and C57BL/6 mice models with mature orthotopic brain and head&neck tumors generated by implantation of H454 and MEERL95 murine cells, respectively.

RESULTS

In the 7 mice analyzed, the brain tumors had distinctly lower 15N/14N than healthy neural tissue. In the 5 mice with head&neck tumors, the difference was smaller and more variable. This was at least partly due to infiltration of healthy head&neck tissue by tumor cells. However, it may also indicate that the 15N/14N difference between tumoral and healthy tissue depends on the nitrogen metabolism of the healthy organ in question.

CONCLUSIONS

The findings, coupled with the high sensitivity of the 15N/14N measurement method used here, suggest a new approach for micro-biopsy-based diagnosis of malignancy as well as an avenue for investigation of cancer metabolism.

Testosterone use in postmenopausal women

The physiological, clinical and therapeutic aspects of testosterone in women's health are still a matter of controversy and debate. Quality evidence data of clinical trials favors the use of transdermal testosterone in postmenopausal women with female sexual dysfunction causing distress. Doses of testosterone should approximate physiological testosterone levels found in premenopausal women, avoiding supraphysiological concentrations that expose women to adverse events. Short-term treatment periods have been shown to be effective and safe in postmenopausal women with hypoactive sexual desire disorder/dysfunction. However, long-term safety of testosterone use must be determined.

Facilitating the design of HL7 domain models through a model-driven solution

Background and goal

Health information systems are increasingly sophisticated and developing them is a challenge for software developers. Software engineers usually make use of UML as a standard model language that allows defining health information system entities and their relations. However, working with health system requires learning HL7 standards, that defines and manages standards related to health information systems. HL7 standards are varied, however this work focusses on v2 and v3 since these are the most used one on the area that this work is being conducted. This works aims to allow modeling HL7 standard by using UML.

Methods

Several techniques based on the MDE (Model-Driven Engineering) paradigm have been used to cope with it.

Results

A useful reference framework, reducing final users learning curve and allowing modeling maintainable and easy-going health information systems.

Conclusions

By using this approach, a software engineer without any previous knowledge about HL7 would be able to solve the problem of modeling HL7-based health information systems. Reducing the learning curve when working in projects that need HL7 standards.

Validation of large-volume batch solar reactors for the treatment of rainwater in field trials in sub-Saharan Africa

The efficiency of two large-volume batch solar reactors [Prototype I (140 L) and II (88 L)] in treating rainwater on-site in a local informal settlement and farming community was assessed. Untreated [Tank 1 and Tank 2-(First-flush)] and treated (Prototype I and II) tank water samples were routinely collected from each site and all the measured physico-chemical parameters (e.g. pH and turbidity, amongst others), anions (e.g. sulphate and chloride, amongst others) and cations (e.g. iron and lead, amongst others) were within national and international drinking water guidelines limits. Culture-based analysis indicated that Escherichia coli, total and faecal coliforms, enterococci and heterotrophic bacteria counts exceeded drinking water guideline limits in 61%, 100%, 45%, 24% and 100% of the untreated tank water samples collected from both sites. However, an 8 hour solar exposure treatment for both solar reactors was sufficient to reduce these indicator organisms to within national and international drinking water standards, with the exception of the heterotrophic bacteria which exceeded the drinking water standard limit in 43% of the samples treated with the Prototype I reactor (1 log reduction). Molecular viability analysis subsequently indicated that mean overall reductions of 75% and 74% were obtained for the analysed indicator organisms (E. coli and enterococci spp.) and opportunistic pathogens (Klebsiella spp., Legionella spp., Pseudomonas spp., Salmonella spp. and Cryptosporidium spp. oocysts) in the Prototype I and II solar reactors, respectively. The large-volume batch solar reactor prototypes could thus effectively provide four (88 L Prototype II) to seven (144 L Prototype I) people on a daily basis with the basic water requirement for human activities (20 L). Additionally, a generic Water Safety Plan was developed to aid practitioners in identifying risks and implement remedial actions in this type of installation in order to ensure the safety of the treated water.

[Hallux metatarsophalangeal arthrodesis: retrospective comparison between blocked plate and cannulated screws]

INTRODUCTION

There are multiple methods and implants used for the metatarsophalangeal arthrodesis of hallux without evidence in favor of one or the other in the bibliography. The goal was to compare the clinical and radiological results of 2 methods and implants used in our center.

MATERIAL AND METHODS

Retrospective review of 37 feet between 2013 and 2017 (22 feet by plate and 15 by cannulated screws). Clinical and radiological variables were collected and the AOFAS and Manchester-Oxford scales were applied. Variables were studied descriptively and analytically through the SPSSv15 program.

RESULTS

The group intervened by plate was composed of 77% of women, with an average age of 65 years and a distribution by diagnosis of severe hallux valgus (HV) (36%), hallux valgus relapse (HVR) (36%) and hallux rigidus (HR) (28%), compared to 80% of women, 68 years old and HV (34%), HVR (46%) HR (20%) in the group of cannulated screws. No significant differences were found in the correction of angles for HV or HVR. The rate of painful pseudoarthrosis was 13% in both and the re-intervention was 18% in the plate group and 26% in the screw group. Both the AOFAS and M-O scales were better in the plate group 63.8 vs 52.6 (p = 0.07); 30.1 vs 41.0 (p = 0.10); as well as patient satisfaction 86% vs 66% (p 0.05) and postoperative pain 3.68 vs 5.58 (p 0.05).

CONCLUSION

Small study groups, not implant randomization, both options are functional without being able to find a preferred one.

An Innovative Platform to Analyze Heart Failure Biomarkers in Saliva

This paper explains a methodology to improve patient safety through early detecting of HF complications and analyzing HF biomarkers in saliva obtained using a biosensor developed in HEARTEN project. A pilot study was performed in two hospitals in Spain and Italy respectively. A direct correlation was identified between TNF-alpha levels in saliva and weight. The weight gain in HF patients could predict a HF decompensation, consequently TNF-alpha could be a new biomarker of these decompensations.

An Ontology-Based Personalized Decision Support System for Use in the Complex Chronically Ill Patient

Management of the complex chronically ill patient is highly problematic. This is due to the need to complement recommendations in clinical guidelines with recommendations based on treatments performed on a representative set of patients. It is necessary to identify conflicts between the recommendations of different guidelines designed for handling specific chronic diseases. The PITeS-TIiSS project (code PI15/01213) aims to overcome this problem by designing and deploying an ontology-based personalized clinical decision support tool. This helps to improve personalized decisions and reduces variability in clinical practice in an integrated care environment. This paper describes the methodology followed in developing the ontology used to infer clinical knowledge and to develop and implement the support tool. The tool will access the information provided by the Electronic Health Record of Andalusian Health Public Service, the main healthcare provider in a region in Spain with more than eight million inhabitants.

Learning Healthcare System for the Prescription of Genetic Testing in the Gynecological Cancer Risk

Clinical evidence demonstrates that BRCA 1 and BRCA2 mutations can develop a gynecological cancer but genetic testing has a high cost to the healthcare system. Besides, several studies in the literature indicate that performing these genetic tests to the population is not cost-efficient. Currently, our physicians do not have a system to provide them the support for prescribing genetic tests. A Decision Support System for prescribing these genetic tests in BRCA1 and BRCA2 and preventing gynecological cancer risks has been designed, developed and deployed in the Virgen del Rocío University Hospital (VRUH). The technological architecture integrates a set of open source tools like Mirth Connect, OpenClinica, OpenCDS, and tranSMART in addition to several interoperability standards. The system allows general practitioners and gynecologists to classify patients as low risk (they do not require a specific treatment) or high risk (they should be attended by the Genetic Council). On the other hand, by means of this system we are also able to standardize criteria among professionals to prescribe these genetic tests. Finally, this system will also contribute to improve the assistance for this kind of patients.

Clinical Decision Support using a Terminology Server to improve Patient Safety

Clinical Decision Support Systems (CDSS) are software applications that support clinicians in making healthcare decisions providing relevant information for individual patients about their specific conditions. The lack of integration between CDSS and Electronic Health Record (EHR) has been identified as a significant barrier to CDSS development and adoption. Andalusia Healthcare Public System (AHPS) provides an interoperable health information infrastructure based on a Service Oriented Architecture (SOA) that eases CDSS implementation. This paper details the deployment of a CDSS jointly with the deployment of a Terminology Server (TS) within the AHPS infrastructure. It also explains a case study about the application of decision support to thromboembolism patients and its potential impact on improving patient safety. We will apply the inSPECt tool proposal to evaluate the appropriateness of alerts in this scenario.

Improving integrated care in chronic kidney failure patients with a standard-based interoperability framework

This paper introduces the evaluation report after fostering a Standard-based Interoperability Framework (SIF) between the Virgen del Rocío University Hospital (VRUH) Haemodialysis (HD) Unit and 5 outsourced HD centres in order to improve integrated care by automatically sharing patients' Electronic Health Record (EHR) and lab test reports. A pre-post study was conducted during fourteen months. The number of lab test reports of both emergency and routine nature regarding to 379 outpatients was computed before and after the integration of the SIF. Before fostering SIF, 19.38 lab tests per patient were shared between VRUH and HD centres, 5.52 of them were of emergency nature while 13.85 were routine. After integrating SIF, 17.98 lab tests per patient were shared, 3.82 of them were of emergency nature while 14.16 were routine. The inclusion of a SIF in the HD Integrated Care Process has led to an average reduction of 1.39 (p=0.775) lab test requests per patient, including a reduction of 1.70 (p=0.084) in those of emergency nature, whereas an increase of 0.31 (p=0.062) was observed in routine lab tests. Fostering this strategy has led to the reduction in emergency lab test requests, which implies a potential improvement of the integrated care.

Deglacial pulses of deep-ocean silicate into the subtropical North Atlantic Ocean

Growing evidence suggests that the low atmospheric CO2 concentration of the ice ages resulted from enhanced storage of CO2 in the ocean interior, largely as a result of changes in the Southern Ocean. Early in the most recent deglaciation, a reduction in North Atlantic overturning circulation seems to have driven CO2 release from the Southern Ocean, but the mechanism connecting the North Atlantic and the Southern Ocean remains unclear. Biogenic opal export in the low-latitude ocean relies on silicate from the underlying thermocline, the concentration of which is affected by the circulation of the ocean interior. Here we report a record of biogenic opal export from a coastal upwelling system off the coast of northwest Africa that shows pronounced opal maxima during each glacial termination over the past 550,000 years. These opal peaks are consistent with a strong deglacial reduction in the formation of silicate-poor glacial North Atlantic intermediate water (GNAIW). The loss of GNAIW allowed mixing with underlying silicate-rich deep water to increase the silicate supply to the surface ocean. An increase in westerly-wind-driven upwelling in the Southern Ocean in response to the North Atlantic change has been proposed to drive the deglacial rise in atmospheric CO2 (refs 3, 4). However, such a circulation change would have accelerated the formation of Antarctic intermediate water and sub-Antarctic mode water, which today have as little silicate as North Atlantic Deep Water and would have thus maintained low silicate concentrations in the Atlantic thermocline. The deglacial opal maxima reported here suggest an alternative mechanism for the deglacial CO2 release. Just as the reduction in GNAIW led to upward silicate transport, it should also have allowed the downward mixing of warm, low-density surface water to reach into the deep ocean. The resulting decrease in the density of the deep Atlantic relative to the Southern Ocean surface promoted Antarctic overturning, which released CO2 to the atmosphere.

Two modes of change in Southern Ocean productivity over the past million years

Export of organic carbon from surface waters of the Antarctic Zone of the Southern Ocean decreased during the last ice age, coinciding with declining atmospheric carbon dioxide (CO(2)) concentrations, signaling reduced exchange of CO(2) between the ocean interior and the atmosphere. In contrast, in the Subantarctic Zone, export production increased into ice ages coinciding with rising dust fluxes, thus suggesting iron fertilization of subantarctic phytoplankton. Here, a new high-resolution productivity record from the Antarctic Zone is compiled with parallel subantarctic data over the past million years. Together, they fit the view that the combination of these two modes of Southern Ocean change determines the temporal structure of the glacial-interglacial atmospheric CO(2) record, including during the interval of "lukewarm" interglacials between 450 and 800 thousand years ago.

SNP genotyping with FRET probes. Optimizing the resolution of heterozygotes

Analysis of single nucleotide polymorphisms by PCR with fluorescence resonance energy transfer (FRET) probes often can produce a result where the melting peak corresponding to perfectly matched sequence (A allele) has a smaller area than the peak corresponding to the allele with a mismatch (B allele). This imbalance can make it difficult to distinguish heterozygous individuals from BB homozygotes. These results suggested that the higher strength in the binding of the perfect match probe to the A allele could cause the selective amplification of the B allele, possibly by interfering with the elongation of the PCR product. In order to optimize the detection of heterozygotes in allelic discrimination assays with FRET probes, we tested several modifications aimed at minimizing the apparent interference of the probes with the amplification process. We observed, in agreement with our hypothesis, that lowering the probe concentration or adding the probes after the amplification step more accurately resolved heterozygotes.