Laboratory Information Systems

Laboratory Informatics Approaches to Improving Care for Gender- Diverse Patients

Improving care for gender-diverse (GD) patients necessitates developing informatics tools and approaches to support optimal laboratory testing. This requires increased functionality and standardization of laboratory information system/electronic health record and data collection processes. Data tailored to accommodate immediate clinical care and clinical decision support (CDS) also have an impact on interoperability and downstream data needs for patients. Informatics tools can shape the clinical care experience for GD patients by careful design of laboratory-patient interactions.

Laboratory Information Management Systems in Oral Pathology: A Comprehensive Review

Efficiency in oral pathological laboratory processes is paramount for timely and accurate diagnosis. This review explores various strategies and methodologies that help streamline oral pathological laboratory workflows to enhance productivity and reduce turnaround times. Key focus areas include specimen collection, handling, processing, and analysis. Optimization techniques such as automation, digitalization, and standardization are discussed in detail, emphasizing their role in minimizing errors and maximizing throughput. Additionally, the integration of advanced technologies such as artificial intelligence and machine learning is examined for their potential to improve laboratory operations. Moreover, the importance of quality control measures and compliance with regulatory standards is underscored as essential components of any successful laboratory streamlining initiative. By implementing a comprehensive approach that addresses the entire diagnostic pathway, oral pathological laboratories can achieve significant efficiency, ultimately leading to better patient care and outcomes.

SHOT UK Collaborative Reviewing and Reforming IT Processes in Transfusion (SCRIPT) survey: Laboratory information management systems: Are we ready for digital transformation?

OBJECTIVES

To understand the use, functionality and interoperability of laboratory information management systems (LIMS) in UK transfusion laboratories.

BACKGROUND

LIMS are widely used to support safe transfusion practice. LIMS have the potential to reduce the risk of laboratory error using algorithms, flags and alerts that support compliance with best practice guidelines and regulatory standards. Reporting to Serious Hazards of Transfusion (SHOT), the United Kingdom (UK) haemovigilance scheme, has identified cases where the LIMS could have prevented errors but did not. Shared care of patients across different organisations and the development of pathology networks has raised challenges relating to interoperability of IT systems both within, and between, organisations.

METHODS AND MATERIALS

A survey was distributed to all SHOT-reporting organisations to understand the current state of LIMS in the UK, prevalence of expertise in transfusion IT, and barriers to progress. Survey questions covered LIMS interoperability with other IT systems used in the healthcare setting.

RESULTS

A variety of LIMS and version numbers are in use in transfusion laboratories, LIMS are not always updated due to resource constraints. Respondents identified interoperability and improved functionality as the main requirements for transfusion safety.

CONCLUSION

A nationally agreed set of minimum standards for transfusion LIMS is required for safe practice. Adequate resources, training and expertise should be provided to support the effective use and timely updates of LIMS. A single LIMS solution should be in place for transfusion laboratories working within a network and interoperability with other systems should be explored to further improve practice.

Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control

Background

"Artificial intelligence" and "big data" increasingly take the step from just being interesting concepts to being relevant or even part of our lives. This general statement holds also true for transfusion medicine. Besides all advancements in transfusion medicine, there is not yet an established red blood cell quality measure, which is generally applied.

Summary

We highlight the usefulness of big data in transfusion medicine. Furthermore, we emphasize in the example of quality control of red blood cell units the application of artificial intelligence.

Key Messages

A variety of concepts making use of big data and artificial intelligence are readily available but still await to be implemented into any clinical routine. For the quality control of red blood cell units, clinical validation is still required.

Computable Guidelines and Clinical Decision Support for Cervical Cancer Screening and Management to Improve Outcomes and Health Equity

Cervical cancer is highly preventable when precancerous lesions are detected early and appropriately managed. However, the complexity of and frequent updates to existing evidence-based clinical guidelines make it challenging for clinicians to stay abreast of the latest recommendations. In addition, limited availability and accessibility to information technology (IT) decision supports make it difficult for groups who are medically underserved to receive screening or receive the appropriate follow-up care. The Centers for Disease Control and Prevention (CDC), Division of Cancer Prevention and Control (DCPC), is leading a multiyear initiative to develop computer-interpretable ("computable") version of already existing evidence-based guidelines to support clinician awareness and adoption of the most up-to-date cervical cancer screening and management guidelines. DCPC is collaborating with the MITRE Corporation, leading scientists from the National Cancer Institute, and other CDC subject matter experts to translate existing narrative guidelines into computable format and develop clinical decision support tools for integration into health IT systems such as electronic health records with the ultimate goal of improving patient outcomes and decreasing disparities in cervical cancer outcomes among populations that are medically underserved. This initiative meets the challenges and opportunities highlighted by the President's Cancer Panel and the President's Cancer Moonshot 2.0 to nearly eliminate cervical cancer.

Analysis and evaluation of the external quality assessment results of quality indicators in laboratory medicine all over China from 2015 to 2018

Background This study aimed to comprehensively evaluate laboratory quality in China and explore factors affecting laboratory errors through analyzing the external quality assessment (EQA) results of quality indicators (QIs). Methods According to model 3 (interpretive) of the proficiency testing scheme, the National Center for Clinical Laboratories of China (CNCCL) developed a questionnaire for 15 QIs. Clinical laboratories from different provinces of China participated in the EQA program of QIs annually and submitted data via an online reporting system named Clinet-EQA. The results of QIs were expressed in percentage and sigma value or minute. Three levels of quality specifications (QSs) were defined based on percentile values. Furthermore, the QIs were analyzed by disciplines, hospital scales and information construction levels of participant laboratories. Results A total of 3450 laboratories nationwide continuously attended the EQA program and submitted complete data from 2015 to 2018. The performance of most QIs has improved year by year. QIs in post-analytical gained the best performance with sigma values that varied from 5.3σ to 6.0σ. The comparison of results among different disciplines showed significant differences for five QIs. More than half of QIs had statistical differences among different hospital scales measured by hospital grades and number of hospital beds. The performance of nine QIs were influenced by information construction levels of participant laboratories. Conclusions The overall laboratory quality in China has improved since the initiation of EQA program for QIs, but the performance of some QIs was still unsatisfactory. Therefore, laboratories should make efforts for continuous quality improvement based on information provided by QSs.

The ins and outs of molecular pathology reporting

The raid evolution in molecular pathology resulting in an increasing complexity requires careful reporting. The need for standardisation is clearer than ever. While synoptic reporting was first used for reporting hereditary genetic diseases, it is becoming more frequent in pathology, especially molecular pathology reports too. The narrative approach is no longer feasible with the growing amount of essential data present on the report, although narrative components are still necessary for interpretation in molecular pathology. On the way towards standardisation of reports, guidelines can be a helpful tool. There are several guidelines that focus on reporting in the field of hereditary diseases, but it is not always feasible to extrapolate these to the reporting of somatic variants in molecular pathology. The rise of multi-gene testing causes challenges for the laboratories. In order to provide a continuous optimisation of the laboratory testing process, including reporting, external quality assessment is essential and has already proven to improve the quality of reports. In general, a clear and concise report for molecular pathology can be created by including elements deemed important by different guidelines, adapting the report to the process flows of the laboratory and integrating the report with the laboratory information management system and the patient record.