Laboratory Information Systems

The integration of information systems in a hospital is accomplished by the introduction of a number of specialised and interconnected information systems. At the General Hospital of Athens G. Gennimatas, a clinical information system (CIS) is installed and running. Shortly after the operation of the clinical information system, the need to couple the CIS with a laboratory information system (LIS) became apparent. The LIS had to be interconnected with the existing clinical information system and the information system for the hospital administration. The difficulties encountered along the progress of this project and the decisions taken in order to obtain the determined goals are presented in this paper. The project management team designed a master plan for the entire duration of the works. Along the course of the project's development, many decisions had to be reconsidered, altered or postponed and many arguments had to be discussed leading to a number of compromises.

Despite its many advantages, using a computerized patient record is still considered as a time consuming activity for care providers. In numerous situations, time is wasted because of the lack of interoperability between systems. In this study, we aim to assess the time gains that nursing teams could achieve with a tightly integrated computerized order entry system. Using a time-motion method, we compared expected versus effective time spent managing laboratory orders for two different computerized systems: one integrated, the other not integrated. Our results tend to show that nurses will complete their task an average of five times faster than their expected performance (p<0.001). We also showed that a tightly integrated system provides a threefold speed gain for nurses compared to a non-integrated CPOE with the laboratory information system (p<0.001). We evaluated the economic benefit of this gain, therefore arguing for a strong interoperability of systems, in addition to patient safety benefits.

The American scholar Warren G. Bennis once said that “[e]xcellence is a better teacher than mediocrity. The lessons of the ordinary are everywhere. Truly profound and original insights are to be found only in studying the exemplary.” 1 In efforts to enable current and future generations of anatomic pathologists to excel in their careers, we need to learn and teach what we can from the truly exceptional examples of those who we can designate as “master diagnosticians.” A recent viewpoint article2 in the Journal of the American Medical Association explored the same concepts in the field of clinical medicine and arrived at 4 principles of operation. We found the article insightful and provocative. In this article, we aim to do the same as our clinical medicine colleagues: examine characterizations of master diagnosticians of anatomic pathology from the past and present, and the future, distilling similar/adapted principles that may help guide us toward our goals of present and future excellence in the art and science of anatomic diagnosis.Our exemplary anatomic pathologist of the past has practiced in a large academic institution for decades. He is a generalist and completed a residency in anatomic pathology. He is an astute observer, classifying and subclassifying entities according to morphology. His pattern recognition is incredibly strong, his intuition for the significance of what he sees is remarkable, and his eye for nuance is sought after. He has contributed to the field by describing and characterizing entities in his field of interest, being a veritable encyclopedia of published and unpublished observations, which include patient outcome. He helped develop some of the initial immunohistochemical stains and studies, but does not rely on them as a primary resource for diagnosis. He has a strong rapport with his clinical colleagues and receives his clinical information directly from them. This pathologist has seen a very high volume of cases and has followed a large portion of them from receipt from the surgeon, through the gross bench, to the microscope, with anecdotal clinical follow-up.Today's master diagnostician has been practicing at an academic institution or large pathology group for at least 15 years. She completed a residency in anatomic pathology and a fellowship in a surgical pathology subspecialty. She has excellent communication skills, is respected by her clinical colleagues, and sits on multiple interdisciplinary medical groups. She has seen a high volume of cases in her career so far and has contributed to the current literature by characterizing molecular findings in established entities and has participated as an investigator in numerous clinical trials. She is partially or wholly subspecialized in her practice. When a colleague's family member has had a biopsy or new diagnosis, this colleague asks for her opinion or understanding of prognosis. She can quote prognosis, associated conditions, and clinical actions for numerous findings and diagnoses. She relies on an evidence-based morphologic checklist and has an extensive differential diagnosis from which she can narrow down her possible “ancillary studies” according to tissue site, age, presentation, operative findings, and gross appearance. She is skilled at navigating the electronic health record for most of this information, but makes frequent phone calls to clinicians to verify information. She has an enviable library of print resources to check and add to her knowledge base, and she is not overly fond of Internet resources. She is cost conscious and pragmatic in her diagnoses, but does not actively monitor her case turnaround time or codify her cases. She also has certain immunohistochemical panels that she trusts through personal experience, and doesn't rely on the occasional literature concerning cost-effectiveness or suggested panels. She signs out a surgical pathology report, and allows the molecular oncology group to issue their own report. Sometimes, she is made aware by her clinicians that the molecular report does not seem to correlate well with her diagnosis and she issues an addendum. She keeps up on the current literature and is on the editorial board for a few journals. Because of her diagnostic competence and clinical respect, she is offered and accepts administrative roles, which broaden her horizons concerning clinical medicine but limit the amount of time that she can spend as a diagnostician.The master diagnostician of the future practices for a large, nonacademic, centralized pathology group and has changed employers twice so far. She is a general surgical pathologist and completed a combined anatomic pathology and clinical pathology residency and fellowships in both surgical pathology and gastrointestinal pathology. She handles most of the liver and gastrointestinal neoplastic cases for her practice. She has seen a very high volume of cases and has developed, through extensive experience, attuned morphologic pattern recognition. Her strong morphologic skills have been adapted to allow her to expand her practice through providing consultation for in vivo microscopy imaging. This pathologist does not gross her own specimens, but relies on the pathologists' assistant's description and available digital gross pictures to aid in her assessment. She is facile with digital pathology and new technologies, and her group uses a completely digital workflow system that enables her to sign out more cases in a shorter amount of time. Owing to the digital nature of the workflow system, the patient's clinical information is viewed through the pathologist's laboratory information system (LIS), which facilitates the pathologist's clinical review of a case.This anatomic pathologist frequently consults her electronic decision support resources when ordering immunohistochemical stains and molecular testing, as these resources take into account the patient's demographic and epidemiologic circumstances, clinical information, morphometric analysis, and cost to the patient. She frequently monitors her turnaround time, relative value unit generation, quality assurance diagnostic reports, and measures of efficiency and effectiveness through a digital dashboard with real-time updates. She receives updated synthesized reports on patient outcomes weekly, allowing her to monitor her diagnostic and prognostic accuracy. She is well versed in statistical analysis and molecular oncology, to the point of being capable of interpreting molecular data results. As far as some of the common entities are concerned, she can spout off probabilistic data, but relies on accurate and frequently updated electronic resources when she signs out her cases. She is an excellent communicator and makes her reports clear and understandable. She also sits on the utilization committee at the main hospital affiliated with her group.Like all clinicians, exemplary diagnosticians in anatomic pathology succeed owing to a combination of their personal traits, training, and environment. They are most likely an incredibly diverse group, but their habits and skills can be seen to adhere to a few basic principles. As the field of pathology strives to transform residency and fellow training, adherence and indoctrination to the following principles of operation may enable those who strive for excellence in their efforts.A saying mentioned frequently in anatomic pathology training is, “you can't see what you don't know.” Each of our master diagnosticians demonstrated a broad and deep knowledge base that was created though study and extensive personal experience, although the content central to that base of knowledge may differ slightly. The pathologist of the past had an expertly attuned eye for morphologic patterns and matching them with a clinical scenario, which was learned primarily through study and his extensive work experience. Our expert pathologist of today also has attuned morphologic pattern recognition, but has a studied knowledge base of corresponding immunophenotype and probabilistic data that is gleaned from textbooks and journal articles. While the pathologist of today contributes to the academic literature in her area of expertise, most of her base of knowledge comes from her studies and not from her patient care experiences. The exemplary diagnostic pathologist of the future has a solid and broad knowledge of surgical pathology learned through formal studies. She also has a strong foundation in molecular oncology, statistics, and test methodology. This allows her to adapt by properly assimilating and questioning new data and new types of data, which are necessary to provide optimal diagnostic and personalized care.At this point, it is not possible to recall (or even have read) the entire body of knowledge of our specialty. However, expert diagnostic skills have their basis in a strong and broad foundation of morphologic pattern recognition. Nearly every pathologist completes at least 1 fellowship in order to gain a greater foundation of that knowledge. This is a foundation that cannot be replaced by an electronic alternative, and anatomic pathologists will drown in their casework if they think they can “always look it up.” As excellence in diagnostic pathology expands further past morphologic analysis, our basic foundation of knowledge should also include statistical analysis, immunophenotypic profiles, molecular oncology pathways, and facility with new methodologies because these allow the pathologist to make a well-informed interpretation of the data.Isaac Asimov once bemoaned “the saddest aspect of life right now [being] that science gathers knowledge faster than society gathers wisdom.” 3 While we focus a lot of effort on accumulating scientific knowledge in order to make diagnoses, we don't spend a lot of time studying or paying attention to how we make decisions. Ideas such as immediate pattern recognition, implicit knowledge, and gut feeling are not viable or reliable measures of decision making. To achieve the status of a master diagnostician, we need to be self-aware and recognize our limits in our decision-making processes and biases.Feedback is critical to performance improvement, yet formal external feedback is received infrequently and sporadically. We receive small amounts of intermediate feedback on our morphologic analyses as we review immunophenotypic stains on our specimens or from cases that have been reviewed at other institutions, but ultimate feedback requires searching the LIS and electronic health record for clinical outcomes. Sometimes, current or recent cases are discussed at tumor board conferences, but further follow-up is rare. The LIS of the future should be able to notify the anatomic pathologist of any subsequent or concurrent testing performed on a selected patient's material, should allow for patient-specific communication for a real-time clinical-radiologic-pathologic consensus, and should also provide a window into the patient's treatment and outcome by monitoring for radiologic and follow-up testing. The sooner we receive clinicopathologic follow-up data, the sooner we can implement changes in behavior and judgment, which will allow us to become more skilled and to excel in our diagnostic endeavors.One of the largest differences between the pathologist of the past and the future is that the expert pathologist of the future relies on accessing external facts that are not a fundamental part of her core knowledge. Not only is there vastly more scientific information now, but the rate at which the information changes has increased. Diagnostic excellence also requires more in-depth and complex analyses than were previously necessary. The expert pathologist of today relies heavily on internal checklists or diagnostic criteria with a few written guidelines to help her keep up. In the future, computer-aided diagnostic tools that are built into our workflow will be crucial to enabling us in our diagnostic excellence: much the same way that a pilot's cockpit is different today than the platform (there was no cockpit) of the Wright Flyer, the pathologist's toolkit and resources will be greatly expanded and computerized. With a strong foundation of knowledge that will guide her judgment, the pathologist of the future can analyze and synthesize vast amounts of disparate information to achieve a personalized, accurate diagnosis.During the last 100 years, the field of pathology has greatly expanded and the practice of anatomic pathology has changed dramatically. We have many excellent examples of master diagnosticians from which we can learn and after which we can model ourselves. We believe that awareness and adaptation around the principles of “Centrality of Knowledge,” “Knowing Your Limits,” “Feedback,” and “Offloading” will aid us in our efforts to be the master diagnosticians of today and tomorrow. Implicit in this transformation of practice will be a revision of the training of the future master anatomic pathologist, with a special emphasis on so-called genomics and information technology, and a mechanism to help trainees transition from a supervised setting to one that is unsupervised but clearly not autonomous. We hope these thoughts will spur a discussion in our chosen field to help maintain a vibrant discipline that is clinically relevant.

The impact of automating laboratory request forms on the quality of healthcare services.

Laboratory Information System, integrated with the Hospital Information System, has been developed at the G.Pasquinucci Hospital, section of Institute of Clinical Physiology of National Research Council (CNR), specialized in adult and paediatric cardiac surgery. The aim was to automate the testing process from clinical departments to laboratory and back into medical record. Laboratory workflow consists of three parts: (a) test ordering by clinical staff, printing bar-coded ID labels and transmitting orders by network to laboratory; (b) processing test requests and controlling identified specimens by laboratory staff, providing work orders to analytical instruments and validation of results authorizing delivery into the hospital clinical repository; (c) consulting test results in clinical departments by referring physicians through the electronic medical record. This year the system has been used on adult patients processing 135000 laboratory tests concerning chemistry, haematology, coagulation and immunology

Editorial

BackgroundReducing laboratory errors presents a significant opportunity for both cost reduction and healthcare quality improvement. This is particularly true in low-resource settings where laboratory errors are further exacerbated by poor infrastructure and shortages in a trained workforce. Informatics interventions can be used to address some of the sources of laboratory errors.ObjectivesThis article describes the development process for a clinical laboratory information system (LIS) that leverages informatics interventions to address problems in the laboratory testing process at a hospital in a low-resource setting.MethodsWe designed interventions using informatics methods for previously identified problems in the laboratory testing process at a clinical laboratory in a low-resource setting. First, we reviewed a pre-existing LIS functionality assessment toolkit and consulted with laboratory personnel. This provided requirements that were developed into a LIS with interventions designed to address the problems that had been identified. We piloted the LIS at the Kamuzu Central Hospital in Lilongwe, Malawi.ResultsWe implemented a series of informatics interventions in the form of a LIS to address sources of laboratory errors and support the entire laboratory testing process. Custom hardware was built to support the ordering of laboratory tests and review of laboratory test results.ConclusionOur experience highlights the potential of using informatics interventions to address systemic problems in the laboratory testing process in low-resource settings. Implementing these interventions may require innovation of new hardware to address various contextual issues. We strongly encourage thorough testing of such innovations to reduce the risk of failure when implemented.

The clinical laboratory (LAB) was an early adopter of computer technology, beginning with the chemistry and hematology laboratories, which had similar information processing requirements. LAB systems in the early 1960s were primarily offline, batch-oriented systems that used punched cards for data transfer to the hospital mainframe. The advent of minicomputers in the 1970s caused a rapid surge in the development of LAB systems that supported online processing of data from automated laboratory instruments. In the 1980s, LAB systems increasingly employed minicomputers to integrate data into a common database and satisfy functional requirements, including programs for quality control, reference values, trend analyses, graphical presentation, online test interpretations, and clinical guidelines. By 1987 about 20 % of US hospitals had computer links between their LAB systems and their hospital information systems and affiliated outpatient information systems. In the 1990s, LAB systems began using client-server architecture with networked workstations, and most hospitals had a variety of specialized clinical support information systems interconnected to form a medical information system with a distributed database of clinical data that constituted the electronic patient record. By the 2000s, several hundred different clinical tests were routinely available (there had been only a few dozen in the 1950s). The need for more sophisticated and powerful LAB systems has largely been met by commercially available standalone laboratory information systems (LIS); however, there is now increasing pressure to replace these products with the lab-system functionality of the enterprise-wide integrated electronic health record system, for which there is little reported experience.Keywords Clinical laboratory system s Laboratory information system s Chemistry laboratory system s Hematology laboratory system s Networked system s Automated laboratory equipment Minicomputer-based laboratory system s Workstations Clinical support information system s

Artificial Intelligence and the Pathologist: Future Frenemies?

The Electronic Medical Record (EMR) incorporates computerised provider order entry systems which allow clinicians to order diagnostic tests electronically, thus eliminating the need for cumbersome handwritten orders. In many situations the EMR relies on a manual transition of information across systems (e.g., integration with the Laboratory Information System). This study, based in a laboratory setting requiring such a transition across systems, aimed to compare the data entry time (from when a specimen arrives in the Central Specimen Reception [CSR] area of the laboratory, to when it is forwarded on for processing), along with a laboratory turnaround time (TAT) (from the time a specimen is received to the time a verified result is issued) for paper and EMR orders, for two high volume tests, across six hospitals. Results showed that the median data entry time for all hospitals combined, was three minutes shorter for EMR entered orders than paper orders. This difference was consistent and significant for Electrolytes, Urea, Creatinine (EUC) and Automated Differential (including full blood count) tests in 2010 and 2011. These decreases contributed to significantly lower median Laboratory TATs for EMR orders (for EUC tests the difference in medians was 12 minutes in 2010 and six minutes in 2011; for Automated Differential tests, the difference was four minutes in 2010 and two minutes in 2011).

Anatomic pathology quality assurance: Developing an LIS based tracking and documentation module for intradepartmental consultations

The 11th Antwerp conference welcomed 109 delegates from 22 different countries. Many lectures of these conferences are published in this journal [1–8]. The conference in 2006 focused especially on automation and quality. Fundamental questions were: Can automation improve quality of results and also of laboratory information? What can the diagnostic industry guarantee with regard to the quality of the medical laboratory’s performance? Can automation of pre-analytical processes reduce labor and errors? Which practical quality indicators can be used in medical laboratories? During this conference it was the intention to bring together three giants: James Westgard, Martin Hinckley, and Robin Felder. Unfortunately James Westgard could not attend the conference, but his lecture was presented by a colleague. In the introduction lecture, Jean-Claude Libeer gave an overview of how external quality assurance (EQA) programs can contribute to quality monitoring of medical laboratories. In the years to come, virtual microscopy [9] will play an important role in EQA programs, allowing new applications that were not possible until now. He also expressed his concerns about the seriousness of incidents reported in the EU of in vitro medical devices with software errors. According to in-vitro diagnostic directive EC 98/79 these incidents are defined as causing serious harm to the patient. Twenty percent of all incidents reported in 2005 can be summarized as being a software problem with the consequence that a laboratory result is not linked to the right patient identity during the production process. The error can occur in the measurement equipment, during transfer from the measurement equipment to the laboratory information system (LIS), during transfer to the hospital information system (HIS), or even during transfer to an electronic medical patient file. In a near future it will absolutely be necessary to define the responsibilities of all parties involved in the process. A solution must also be found enabling laboratories can detect such errors, and which validation procedures must be used in order to detect them. This year the James Westgard award was given to Martin Hinckley (Fig. 1), who introduced an understanding of the various types of error in laboratory medicine. The best approaches for controlling variation, mistakes and complexity are each a form of mistake proofing. Especially with automated equipment there is a danger of large amounts of non-conformance when a failure occurs. Consequently, achieving the best results with automated equipment requires extensive use of mistake proofing. This approach has been successful in the Japanese automotive industry and can also be applied in the design of laboratory medicine equipment. His contribution has already been published in this journal [10]. The next Antwerp conference (March 22nd and 23rd, 2007) had the theme auditing and quality. The 12th Antwerp conference welcomed 115 delegates from 24 countries. This year’s conference had a somewhat different focus from the previous ones. The practical implementation and use of ISO norm 15189 (Medical laboratories—particular requirements for quality and competence) in various types of laboratory (general, specialized, point of care, etc.), in different scientific fields (microbiology testing, hematology, genetic testing, and others), and in different European countries, was the framework. The lead motif of the conference was ‘‘Audit to improve’’. All of this was J. C. Libeer H. M. J. Goldschmidt (&) Regional Diagnostic Services (DCT), Hoefstraat 258, 5014 NR Tilburg, The Netherlands e-mail: henk@goldschmidt.ws

The objective of this study was to evaluate the impact of online access to the state Immunization Information Systems (IIS) on the immunization practices of emergency department (ED) providers in a pediatric academic tertiary care center. Interoperability between Health Information Systems (HIS) such as Electronic Health Records (EHRs), Laboratory Information Systems (LIS), and health registries, maintained by various care providers (e.g., primary/specialty care, ED, inpatient hospital systems) and public health departments (e.g., IIS, formerly referred to as immunization registries) are required for full realization of healthcare reform, set forth by the Affordable Care Act [1], [2]. Pediatric immunization is mainly covered by the primary care providers, supplemented in certain circumstances by alternative settings such as the ED and hospitals. It is critical that updated immunization records of individual patients are available at the Point-Of-Care (POC), to help decide the need for an immunization, such as tetanus vaccination in trauma patients, and prevent over or under immunization. To provide up-to-date information about immunization administered to individual patients by all care providers, with a view to improve immunization coverage and reduce unnecessary and duplicate immunization, the Georgia Department of Public Health (DPH) created a population based IIS (Georgia Registry of Immunization Transactions and Services or GRITS) [3]. Children's Healthcare of Atlanta worked with the DPH to establish an interface between their EHR system and GRITS so that the updated immunization records could be accessed online within the EHR at POC. This online access could also be viewed as a golden opportunity to improve the Center for Disease Control (CDC) recommended Tetanus, Diphtheria and Pertussis (Tdap) coverage for the 11 to 19 year-old children, known to be difficult population to reach out to, to improve Tdap coverage targets. We compared the immunization coverage practices, based on CDC recommendations, in patients 10 to 20 years of age, presenting with trauma where tetanus immunization was indicated, pre-post availability of GRITS via EHR. At implementation onset, there was a significant increase in vaccination rates (2.3%, p=0.01), but, the increase was not sustained and the pre-implementation downward trend continued (p=0.91). There were only 4 patients who were seen more than once for trauma and ordered tetanus immunization (combined) twice; 2 patients before and 2 after the implementation. Both the pre-implementation patients were vaccinated twice, whereas only 1 patient was vaccinated twice in the post-implementation phase and the other patient's order was discontinued. While showing a short-term increase in ED based immunization post-implementation of GRITS, real time access to updated immunization records did not impact the overall long- term rates of updating Tdap immunization in the ED. As with many Quality Initiative (QI) efforts, improvements may be transient and further evaluation of GRITS and strategies to maintain the QI impact of this and other EHR systems are important. As suggested by some experts, providing appropriate interactive reminders and alerts at POC to reduce "missed opportunities" to vaccinate during all patient encounters are needed to reach the 90% target of Tdap coverage by 2020 set forth by the government [4].

Towards an evaluation framework for Laboratory Information Systems.

Background The National Kidney Foundation estimates that 37 million people in the United States are affected by kidney disease, although 90% of them are unaware of it. While kidney disease is less common in children and adolescents, early diagnosis and treatment is important due to the significant long-term impact it can have on growth, cognitive development, and cardiovascular disease. Unlike adults, the estimated glomerular filtration rate (eGFR) for pediatric patients is not routinely reported by clinical laboratories. The process of estimating GFR is cumbersome and time-consuming for clinicians, requiring data extraction to use estimating equations with variable accuracy. The Chronic Kidney Disease in Children (CKiD) Study has developed and published new, more precise, estimating equations for use in children and young adults that utilize a sex- and age-dependent constant (k) in conjunction with height and serum creatinine and/or serum cystatin-C. In collaboration with Nephrology and Laboratory Information Technology, we implemented three eGFR equations into our laboratory information system (LIS) and currently report the results in the patient's electronic medical record (EMR). Methods The three equations that were implemented were named eGFR-creatinine (eGFR = k x (height/sCr) with height in m and serum creatinine in mg/dL), eGFR-cystatin (eGFR = k×(1/cysC) with serum cystatin-C in mg/L), and eGFR-average, which reports the average of the creatinine and cystatin-C estimating equations when both are ordered. The k constant is dependent on the patient's age and sex. An eGFR value of >90 mL/min|1.73m2 is considered normal. When an eGFR is ordered, the system identifies the most recent creatinine or cystatin-C result. If one has not been resulted in the last 2 hours, the system reflexes an order for a basic metabolic panel or a cystatin-C. For the eGFR-creatinine equation, the system looks back up to 3 months for a height and uses the most current value. Concordance and discordance were determined in patients who had all three equations ordered and compared as to whether all three values gave a result above or below 90 mL/min|1.73 m2. Results The eGFR-creatinine equation went live in June 2022. As of January 2023, 287 eGFR-creatinine values have been resulted. The cystatin-C assay, eGFR-cystatin equation, and e-GFR average equations went live in November 2022. As of January 2023, 114 eGFR-averages and 167 eGFR-cystatins have been resulted. When both equations were ordered and the eGFR-average was calculated, all three values were concordant 69 times (61%) and discordant 45 times (39%). In 26 instances, the eGFR-creatine value was discrepant compared with the other two equations and in 19 instances, the eGFR-cystatin value was discrepant. The differences between the eGFR equations ranged from 1.1–41.9%, however 65% of the values varied by less than 10% and 88% varied by less than 20%. Conclusion Implementation of pediatric eGFR equations into the LIS and reporting of eGFR in the EMR will allow more accurate assessment of pediatric patients’ kidney function and improved clinician and patient awareness of impaired kidney function. Availability of this information will allow an earlier diagnosis and treatment of chronic kidney disease.