Widely Used Sepsis Warning System Missed Two-Thirds of Cases.

Study raises questions about adopting commercial technology without scientific review.

The Use of Primary Care Big Data in Understanding the Pharmacoepidemiology of COVID-19: A Consensus Statement From the COVID-19 Primary Care Database Consortium.

The use of big data containing millions of primary care medical records provides an opportunity for rapid research to help inform patient care and policy decisions during the first and subsequent waves of the coronavirus disease 2019 (COVID-19) pandemic. Routinely collected primary care data have previously been used for national pandemic surveillance, quantifying associations between exposures and outcomes, identifying high risk populations, and examining the effects of interventions at scale, but there is no consensus on how to effectively conduct or report these data for COVID-19 research. A COVID-19 primary care database consortium was established in April 2020 and its researchers have ongoing COVID-19 projects in overlapping data sets with over 40 million primary care records in the United Kingdom that are variously linked to public health, secondary care, and vital status records. This consensus agreement is aimed at facilitating transparency and rigor in methodological approaches, and consistency in defining and reporting cases, exposures, confounders, stratification variables, and outcomes in relation to the pharmacoepidemiology of COVID-19. This will facilitate comparison, validation, and meta-analyses of research during and after the pandemic.

The Role of Dementia as Cause of Death: Certifiers' Opinions versus Automated Coding.

BACKGROUND: Dementia is a major cause of death in many countries today. The way in which countries code causes of death determines the occurrence of dementia in statistics. The change over from manual to automated coding is accompanied by a 7-19% increase in the occurrence of dementia as the underlying cause of death. Because of this sudden change, researchers, physicians, policy makers, and press question the validity of the outcome of automated coding. Therefore, the role of dementia as a cause of death was investigated. METHODS: A questionnaire was sent to a random sample of 700 certifiers who mentioned "dementia" on a death certificate in the second half of 2017. They were asked questions about the role of dementia as a cause of death. For each certificate, the opinion of the certifier was compared with the outcome of automated coding. RESULTS: A response of 65% (n = 446) was obtained. The automated coding system selected dementia as the underlying cause of death 9.5% points (95% CI: 5.8-14.4%) more often than the certifier would do. This finding in the sample corresponded to an overestimation of dementia in the cause-of-death statistics with 22.7% (95% CI: 18-28%). Main reason for this overestimation was the selection of dementia as the underlying cause of death by the automated coding system, while it was noted as the contributory cause of death on part 2 of the death certificate by the certifier. CONCLUSION: For international comparisons of data on dementia as a cause of death, the outcome of automated coding can be used as the system adheres to international (ICD-10) guidelines and reduces coding variations in and between countries. However, for interpreting the local (national) impact of dementia as a cause of death, the opinion of the certifier should be taken into account.

Towards Interoperability in Clinical Research - Enabling FHIR on the Open-Source Research Platform XNAT.

This paper presents an approach to enable interoperability of the research data management system XNAT by the implementation of the HL7 standards framework Fast Healthcare Interoperability Resources (FHIR). The FHIR implementation is realized as an XNAT plugin (Source code: https://github.com/somnonetz/xnat-fhir-plugin ), that allows easy adoption in arbitrary XNAT instances. The approach is demonstrated on patient data exchange between a FHIR reference implementation and XNAT.

Evaluation of the Quality of French Hospital Data for Perinatal Algorithms.

The aim of our validation study was to assess the quality of hospital data for perinatal algorithms on a national level. In each hospital, we selected 150 discharge abstracts of delivery (after 22 weeks of gestation), in 2014, and their corresponding medical records. Overall, 23 hospitals were included and 3,246 discharge abstracts were studied. This first national validation study of several case-funding algorithms using various perinatal variables suggests that the French national hospital discharge abstracts database is an appropriate data source for epidemiological studies.

Feasibility of Using EN 13606 Clinical Archetypes for Defining Computable Phenotypes.

INTRODUCTION: Computable phenotypes are gaining importance as structured and reproducible method of using electronic health data to identify people with certain clinical conditions. A formal standard is not available for defining and formally representing phenotyping algorithms. In this paper, we have tried to build a formal representation of such phenotyping algorithm. METHODS: We built EN 13606 EHR standard for building clinical archetypes to represent the computable phenotyping algorithm for 'diagnosis of cardiac failure'. As part of this work, we created a set of new clinical archetypes for defining 'cardiac failure diagnosis'. The EN13606 editor called Object Dictionary Client was used which was in-house developed by University College London. We evaluated the ability of EN 13606 to provide clinical archetypes to define EHR phenotyping algorithms using the predefined desiderata for the purpose [Mo et al]. RESULTS: EN 13606 archetypes could represent phenotype components grouped and nested based on their logical meaning. It was possible to build the EHR phenotyping algorithm with the clinical elements and their interrelationships along with hierarchical structure and temporal criteria. But the specific mathematical calculation and temporal relations involved in the algorithm was difficult to incorporate. These will need to be coded and integrated within the clinical information system. These archetypes can be mapped for comparison with the openEHR models. Binding to external clinical terminology is fully supported. However, it does not satisfy all the desiderata defined by Mo et al. A possible way could be an approach using phenotype ontologies and its architectural representation integrated with ISO interoperability. CONCLUSION: The EN13606 archetypes can be used to define the phenotype algorithm that basically identifies patients by a set of clinical characteristics in their records. Phenotype representations defined in EN 13606 do not satisfy all the desiderata proposed by Mo et al. and thus currently has a limited ability to define the computable phenotyping algorithms. Further work is required to make the EN13606 standard to fully support the objective.

The Electronic Medical Record and Nephrology Fellowship Education in the United States: An Opinion Survey.

BACKGROUND AND OBJECTIVES: An unintended consequence of electronic medical record use in the United States is the potential effect on graduate physician training. We assessed educational burdens and benefits of electronic medical record use on United States nephrology fellows by means of a survey. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We used an anonymous online opinion survey of all United States nephrology program directors (n=148), their faculty, and fellows. Program directors forwarded survey links to fellows and clinical faculty, indicating to how many they forwarded the link. The three surveys had parallel questions to permit comparisons. RESULTS: Twenty-two percent of program directors (n=33) forwarded surveys to faculty (n=387) and fellows (n=216; 26% of United States nephrology fellows). Faculty and fellow response rates were 25% and 33%, respectively; 51% of fellows agreed/strongly agreed that the electronic medical record contributed positively to their education. Perceived positive effects included access flexibility and ease of obtaining laboratory/radiology results. Negative effects included copy-forward errors and excessive, irrelevant documentation. Electronic medical record function was reported to be slow, disrupted, or completely lost monthly or more by >40%, and these were significantly less likely to agree that the electronic medical record contributed positively to their education. Electronic medical record completion time demands contributed to fellow reluctance to do procedures (52%), participate in conferences (57%), prolong patient interactions (74%), and do patient-directed reading (55%). Sixty-five percent of fellows reported often/sometimes exceeding work-hours limits due to documentation time demands; 85% of faculty reported often/sometimes observing copy-forward errors. Limitations include potential nonresponse and social desirability bias. CONCLUSIONS: Respondents reported that the electronic medical record enhances fellow education with efficient and geographically flexible patient data access, but the time demands of data and order entry reduce engagement in educational activities, contribute to work-hours violations, and diminish direct patient interactions.

Ethical Use of Electronic Health Record Data and Artificial Intelligence: Recommendations of the Primary Care Informatics Working Group of the International Medical Informatics Association.

OBJECTIVE: To create practical recommendations for the curation of routinely collected health data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use. METHODS: We defined data curation as the process of management of data throughout its lifecycle to ensure it can be used into the future. We used a literature review and Delphi exercises to capture insights from the Primary Care Informatics Working Group (PCIWG) of the International Medical Informatics Association (IMIA). RESULTS: We created six recommendations: (1) Ensure consent and formal process to govern access and sharing throughout the data life cycle; (2) Sustainable data creation/collection requires trust and permission; (3) Pay attention to Extract-Transform-Load (ETL) processes as they may have unrecognised risks; (4) Integrate data governance and data quality management to support clinical practice in integrated care systems; (5) Recognise the need for new processes to address the ethical issues arising from AI in primary care; (6) Apply an ethical framework mapped to the data life cycle, including an assessment of data quality to achieve effective data curation. CONCLUSIONS: The ethical use of data needs to be integrated within the curation process, hence running throughout the data lifecycle. Current information systems may not fully detect the risks associated with ETL and AI; they need careful scrutiny. With distributed integrated care systems where data are often used remote from documentation, harmonised data quality assessment, management, and governance is important. These recommendations should help maintain trust and connectedness in contemporary information systems and planned developments.

The Development of Medical Markup Language Version 4 as a Clinical Document Exchange Format for Nationwide EHR Systems.

Medical Markup Language (MML) is a standard format for exchange of healthcare data among healthcare providers. Following the last major update (version 3), we developed new modules and discussed the requirements for the next major updates. Subsequently, in 2016 we released MML version 4 and used it to obtain clinical data from healthcare providers for a nationwide electronic health records (EHR) system. In this article we provide an overview of this major update of MML version 4 and discuss its interoperability for clinical data.

[Document standards for pathology reports in digital medicine]. / Dokumentenstandards für Pathologiebefundberichte in einer digitalisierten Medizin.

Pathology reports are important clinical documents for the diagnosis, treatment, and follow-up of often severe diseases. They are subject to a series of formal and substantive requirements that are anchored in several jurisdictions, which also apply to the digital form of these records. Only a few of the currently used digital document formats meet these requirements and are at the same time interoperable, regardless of the computer platforms used. Practically, they are only partially used in pathology laboratories, practice management, and hospital information systems. The consistent use of these standard formats for pathological findings reports provided a clear digital added value for both pathologists and clinicians as well as their patients.

Completeness of operative reports for rectal cancer surgery.

INTRODUCTION: Synoptic operative reporting has been shown to improve completeness and consistency in surgical documentation. We sought to determine whether operative reports contain the key elements recommended by the National Accreditation Program for Rectal Cancer. METHODS: Rectal cancer operative reports from June-December 2018 were submitted from ten hospitals in Michigan. These reports were analyzed to identify key elements in the synoptic operative template and assessed for completeness. RESULTS: In total, 110 operative reports were reviewed. Thirty-one (28%) reports contained all 24 elements; all of these reports used a synoptic template. Overall, 62 (56%) reports used a synoptic template and 48 (44%) did not. Using a synoptic template significantly improved documentation, as these reports contained 92% of required elements, compared to 39% for narrative reports (p < 0.001). CONCLUSIONS/DISCUSSION: Narrative operative reports inconsistently document rectal cancer resection. This study provides evidence that synoptic reporting will improve quality of documentation for rectal cancer surgery.

Postoperative respiratory failure: An update on the validity of the Agency for Healthcare Research and Quality Patient Safety Indicator 11 in an era of clinical documentation improvement programs.

BACKGROUND: Administrative data can be used to identify cases of postoperative respiratory failure (PRF). We aimed to determine if recent changes to the Agency for Healthcare Research and Quality Patient Safety Indicator 11 (PSI 11) and adoption of clinical documentation improvement programs have improved the validity of PSI 11. We also analyzed reasons why PSI 11 was falsely triggered. STUDY DESIGN: Cross-sectional study of all eligible discharges using health record data from five academic medical centers between October 1, 2012 and September 30, 2015. RESULTS: Of 437 flagged records, 434 (99.3%) were accurately coded and 414 (94.7%) represented true clinical PRF. None of the false positive records involved respiratory failure present on admission. Most (78.3%) false positive records required airway protection but did not have respiratory failure. CONCLUSION: The validity of PSI 11 has improved with recent changes to the code criterion and adoption of clinical documentation improvement programs.

Recording problems and diagnoses in clinical care: developing guidance for healthcare professionals and system designers.

BACKGROUND: Accurate recording of problems and diagnoses in health records is key to safe and effective patient care, yet it is often done poorly. Electronic health record systems vary in their functionality and ease of use, and are not optimally designed for easy recording and sharing of clinical information. There is a lack of professional consensus and guidance on how problems and diagnoses should be recorded. METHODS: The Professional Record Standards Body commissioned work led by the Royal College of Physicians Health Informatics Unit to carry out a literature review, draft guidance, carry out an online consultation and round table discussion, and produce a report including recommendations for systems. A patient workshop was held to explore patient preferences for mechanisms for sharing diagnosis information between primary and secondary care. RESULTS: Consensus was reached among medical specialties on key elements of diagnosis recording, and draft guidance was produced ready for piloting in a variety of care settings. Patients were keen for better ways for diagnosis information to be shared. DISCUSSION: Improving the recording of diagnoses and problems will require a major effort of which the new guidance is only a part. The guidance needs to be embedded in training, and clinical systems need to have improved, standardised functionality. Front-line clinicians, specialist societies, clinical informaticians and patients need to be engaged in developing information models for diagnoses to support care and research, accessible via user-friendly interfaces.

Paper-and-pencil versus computerized administration mode: Comparison of data quality and risk behavior prevalence estimates in the European school Survey Project on Alcohol and other Drugs (ESPAD).

PURPOSE: The aim of this experimental study was to investigate whether paper-and-pencil and computerized surveys administered in the school setting yield equivalent data quality indicators and risk behavior prevalence estimates. METHODS: Data were drawn from the European School Survey Project on Alcohol and Other Drugs (ESPAD®) carried out in Italy to monitor drug, alcohol, tobacco use and other risk-behaviors among Italian high school students aged 15-19 years. A sub-sample of schools was recruited for the study (1673 pupils). For each school, two entire randomly selected courses (from the first to the fifth grade) participated and were assigned randomly to the self-administered paper-and-pencil (N = 811) or computerized survey (N = 862). Differences in data quality were assessed using the following indicators: questionnaire completeness (missing gender and/or 50% of missing answers) and internal consistency (repetitive extreme response patterns). Separate logistic regression models were used to estimate the mode effect on the reporting of each risk behavior, controlling for gender and age. Finally, the prevalence estimates of the experimental study were compared to the results of the national ESPAD® study. RESULTS: The computerized administration mode produced a higher proportion of invalid questionnaires, but the prevalence estimates generated from responses to the paper-and-pencil and computerized surveys were generally equivalent. Nevertheless, comparing these results with those of the national ESPAD® study, some differences in the prevalence rates were found. CONCLUSIONS: The findings suggest that in a proctored school setting, the computerized survey mode yields almost the same results as the paper-and-pencil mode. However, because of the reliance on existing informatics facilities until when all schools in the country will be sufficiently equipped for the computerized data collection, they should be given the opportunity to choose between paper-and-pencil and computerized survey modes, in order to avoid a possible selection bias.

Oncology Information System: A Qualitative Study of Users' Requirements.

BACKGROUND: Cancer care is a complex care process and is associated with generating a variety of data during the care process. Therefore, it seems that designing and using information systems is necessary to enhance the accessibility, organization and management of cancer-related data. The aim of this study was to identify users' requirements of an oncology information system (OIS). METHODS: This was a qualitative study conducted in 2018. In depth semi-structured interviews were performed with clinicians and non-clinicians in five teaching hospitals to identify users' requirements. Data were analyzed by using framework analysis. RESULTS: The four themes emerged from data analysis included: a) methods of recording cancer data in the hospitals, b) required cancer data in different departments, c) comprehensive cancer care documentation, and d) required functions of an oncology information system. CONCLUSION: According to the results, currently, electronic documentation is less frequently used for cancer patients. Therefore, an extensive effort is needed to identify users' requirements before designing and implementing an oncology information system. As multidisciplinary teams are involved in cancer care, all potential users and their requirements should be taken into account. Such a system can help to collect and use cancer data effectively.

Methodological description of clinical research data collection through electronic medical records in a center participating in an international multicenter study.

Data collection for clinical research can be difficult, and electronic health record systems can facilitate this process. The aim of this study was to describe and evaluate the secondary use of electronic health records in data collection for an observational clinical study. We used Cerner Millennium®, an electronic health record software, following these steps: (1) data crossing between the study's case report forms and the electronic health record; (2) development of a manual collection method for data not recorded in Cerner Millennium®; (3) development of a study interface for automatic data collection in the electronic health records; (4) employee training; (5) data quality assessment; and (6) filling out the electronic case report form at the end of the study. Three case report forms were consolidated into the electronic case report form at the end of the study. Researchers performed daily qualitative and quantitative analyses of the data. Data were collected from 94 patients. In the first case report form, 76.5% of variables were obtained electronically, in the second, 95.5%, and in the third, 100%. The daily quality assessment of the whole process showed complete and correct data, widespread employee compliance and minimal interference in their practice. The secondary use of electronic health records is safe and effective, reduces manual labor, and provides data reliability. Anesthetic care and data collection may be done by the same professional.