Improving acute kidney injury alerts in tertiary care by linking primary care data: An observational cohort using routine care data

Objective

Acute kidney injury (AKI) is easily missed and underdiagnosed in routine clinical care. Timely AKI management is important to decrease morbidity and mortality risks. We recently implemented an AKI e-alert at the University Medical Center Utrecht, comparing plasma creatinine concentrations with historical creatinine baselines, thereby identifying patients with AKI. This alert is limited to data from tertiary care, and primary care data can increase diagnostic accuracy for AKI. We assessed the added value of linking primary care data to tertiary care data, in terms of timely diagnosis or excluding AKI.

Methods

With plasma creatinine tests for 84,984 emergency department (ED) visits, we applied the Kidney Disease Improving Global Outcome guidelines in both tertiary care-only data and linked data and compared AKI cases.

Results

Using linked data, the presence of AKI could be evaluated in an additional 7886 ED visits. Sex- and age-stratified analyses identified the largest added value for women (an increase of 4095 possible diagnoses) and patients ≥60 years (an increase of 5190 possible diagnoses). We observed 398 additional visits where AKI was diagnosed, as well as 185 cases where AKI could be excluded. We observed no overall decrease in time between baseline and AKI diagnosis (28.4 days vs. 28.0 days). For cases where AKI was diagnosed in both data sets, we observed a decrease of 2.8 days after linkage, indicating a timelier diagnosis of AKI.

Conclusions

Combining primary and tertiary care data improves AKI diagnostic accuracy in routine clinical care and enables timelier AKI diagnosis.

Flowing through laboratory clinical data: the role of artificial intelligence and big data

During the last few years, clinical laboratories have faced a sea change, from facilities producing a high volume of low-cost test results, toward a more integrated and patient-centered service. Parallel to this paradigm change, the digitalization of healthcare data has made an enormous quantity of patients' data easily accessible, thus opening new scenarios for the utilization of artificial intelligence (AI) tools. Every day, clinical laboratories produce a huge amount of information, of which patients' results are only a part. The laboratory information system (LIS) may include other "relevant" compounding data, such as internal quality control or external quality assessment (EQA) results, as well as, for example, timing of test requests and of blood collection and exams transmission, these data having peculiar characteristics typical of big data, as volume, velocity, variety, and veracity, potentially being used to generate value in patients' care. Despite the increasing interest expressed in AI and big data in laboratory medicine, these topics are approaching the discipline slowly for several reasons, attributable to lack of knowledge and skills but also to poor or absent standardization, harmonization and problematic regulatory and ethical issues. Finally, it is important to bear in mind that the mathematical postulation of algorithms is not sufficient for obtaining useful clinical tools, especially when biological parameters are not evaluated in the appropriate context. It is therefore necessary to enhance cooperation between laboratory and AI experts, and to coordinate and govern processes, thus favoring the development of valuable clinical tools.

Redundant laboratory testing on referral from general practice to the outpatient clinic: a post-hoc analysis

Background

Inappropriately repeated laboratory testing is a commonly occurring problem. However, this has not been studied extensively in the outpatient clinic after referral by GPs.

Aim

The aim of this study was to investigate how often laboratory tests ordered by the GP were repeated on referral to the outpatient clinic, and how many of the normal test results remained normal on repetition.

Design & setting

This is a post-hoc analysis of a study on laboratory testing strategies in patients newly referred to the outpatient clinic between April 2015 and April 2017.

Method

All patients who had a referral letter including laboratory test results ordered by the GP were included. These results were compared with the laboratory test results ordered in the outpatient clinic.

Results

Data were available for 295 patients, 191 of which had post-visit testing done. In this group, 56% of tests ordered by the GP were repeated. Tests with abnormal results were repeated more frequently than tests with normal results (65% versus 53%; P<0.001). A longer test interval was associated with slightly smaller odds of tests being repeated (odds ratio [OR] 0.97, 95% confidence interval [CI] = 0.95 to 0.99; P = 0.003). Of the tests with normal test results that were repeated, 90% remained normal. This was independent of testing interval or testing strategy.

Conclusion

Laboratory tests ordered by the GP are commonly repeated on referral to the outpatient clinic. The number of test results remaining normal on repetition suggests a high level of redundancy in laboratory test repetition.

Requirements for electronic laboratory reports according to the German guideline Rili-BAEK and ISO 15189

Objectives

Legal regulations and guidelines such as the Guidelines of the German Medical Association for the Quality Assurance of Laboratory Medical Examinations (Rili-BAEK) and ISO 15189 apply to electronic laboratory reports. However, many laboratories struggle with practical implementation of these regulations and guidelines.

Methods

Laboratory and legal experts analyse the relevant guidelines and provide checklists and practical recommendations for implementation.

Results

Laboratories have less control over the display of electronic laboratory reports than over paper documents. However, an electronic report alone is legally sufficient and need not be accompanied by a paper copy. Rili-BAEK and ISO 15189 stipulate a set of minimum information in every report. The laboratory must verify that reports are transmitted and displayed correctly. To help laboratories do so, agreements between laboratories and the report recipients can clarify responsibilities.

Conclusions

Electronic laboratory reports can improve patient care, but laboratories need to verify their quality. Towards this end, Rili-BAEK and ISO 15189 set out helpful provisions.

Erstellung zuverlässiger Erythrozytenkonzentrat-Bedarfslisten für Operationen und Interventionen aus Data-Warehouse-Daten und der patientenbezogenen Chargendokumentation von Blutkomponenten

Das Versäumnis, transfusionsvorbereitende Diagnostik durchzuführen und eine ausreichende Anzahl von Blutkomponenten vor der Operation zu bestellen, führt zunehmend zu klinischen Notfällen und vermeidbaren Risiken für die Patienten. Die eigentlich obligatorische Erstellung von Blutbedarfslisten scheitert oft an der Verfügbarkeit geeigneter Daten. Das Universitätsklinikum Erlangen ist ein Krankenhaus der Tertiärversorgung mit 1400 Betten. Hier werden seit 2010 kontinuierlich alle relevanten Daten zur Interpretation von Mustern bei der Verwendung von Blutbestandteilen erhoben. Wir sind in der Lage, die klinischen Data-Warehouse-Komponenten der persönlichen Daten der Empfänger von Erythrozytenkonzentraten (EK), die Codes der stationären Patienten im G-DRG-System (G-DRG: German Diagnosis Related Group), ICD-Codes, OPS-Codes und die Daten der EK-Komponenten aus dem IT-System der Blutbank zu integrieren. Die erhaltenen DRGs, ICD-Codes und OPS-Codes werden mit den Daten des Blutkomponentenverbrauchs auf individueller Basis verknüpft. Analysen können sowohl im gesamten Krankenhaus als auch in Bezug auf bestimmte Abteilungen durchgeführt werden. Die laufende Verfeinerung der Datenbankabfragen verbessert die Fähigkeit, den Blutbedarf für Standardoperationen und Interventionen korrekt abzuschätzen. Die Ergebnisse weichen zum Teil erheblich von den Schätzungen der Operateure hinsichtlich der Wahrscheinlichkeit einer Transfusion ab, oftmals wird die Wahrscheinlichkeit einer Transfusion unterschätzt. Die korrekte Einhaltung der 10-prozentigen Transfusionswahrscheinlichkeitsgrenze für die Frage der frühen präoperativen Bereitstellung von Kreuzblut kann durch solche Abfragen verbessert werden. Dem Phänomen der „verzögerten Transfusion“ entgegenzuwirken, wird zu einer immer wichtigeren Aufgabe für den klinisch tätigen transfusionsmedizinischen Arzt. Die Erstellung von Statistiken über die Transfusionswahrscheinlichkeit durch die Verknüpfung von Data-Warehouse-Daten und Chargendokumentationsdaten aus Blutbanken kann die notwendigen Werkzeuge bereitstellen.

LOINC: Origin, development of and perspectives for medical research and biobanking – 20 years on the way to implementation in Germany

Twenty-five years of LOINC (LogicalObservationIdentifierNames andCodes) and almost 20 years of experience with the implementation of LOINC in Germany – without having so far achieved a binding national definition of or a relevant routine use of LOINC in laboratory data communication. This article sketches the development of LOINC use in Germany since the year 2000 on the basis of grey literature. For the first time, the use of LOINC in Germany is experiencing a significant impetus at the national level: On the one hand, the current health legislation with its stipulations for a legally defined electronic patient record provides the necessary framework for nationwide stipulations; on the other hand, there is a significant impulse from the German Medical Informatics Initiative (MII) out of the medical research field for implementing a uniform LOINC subset. In recognition of the 25thanniversary of the LOINC nomenclature (1995–2019), the article traces the emergence of LOINC – which is characterized by interactions between European (EUCLIDES, READ, NPU) and US (HL7, LOINC, SNOMED CT) developments and the interplay of various standardization initiatives. Different national definitions and e-health strategies resulting from this history will be a challenge for the future e-health harmonization in the EU. The concerns of medical research and biobanking must be taken into account here, since the standardization of lab data according to international nomenclatures is of utmost importance for them.