Electronic medical record in the intensive care unit

The Evolution and Future of Intensive Care Management in the Era of Telecritical Care and Artificial Intelligence

Critical care practice has been embodied in the healthcare system since the institutionalization of intensive care units (ICUs) in the late '50s. Over time, this sector has experienced many changes and improvements in providing immediate and dedicated healthcare as patients requiring intensive care are often frail and critically ill with high mortality and morbidity rates. These changes were aided by innovations in diagnostic, therapeutic, and monitoring technologies, as well as the implementation of evidence-based guidelines and organizational structures within the ICU. In this review, we examine these changes in intensive care management over the past 40 years and their impact on the quality of care available to patients. Moreover, the current state of intensive care management is characterized by a multidisciplinary approach and the use of innovative technologies and research databases. Advancements such as telecritical care and artificial intelligence are being increasingly explored, especially since the COVID-19 pandemic, to reduce the length of hospitalization and ICU mortality. With these advancements in intensive care and ever-changing patient needs, critical care experts, hospital managers, and policymakers must also explore appropriate organizational structures and future enhancements within the ICU.

Extracting research-quality phenotypes from electronic health records to support precision medicine

The convergence of two rapidly developing technologies - high-throughput genotyping and electronic health records (EHRs) - gives scientists an unprecedented opportunity to utilize routine healthcare data to accelerate genomic discovery. Institutions and healthcare systems have been building EHR-linked DNA biobanks to enable such a vision. However, the precise extraction of detailed disease and drug-response phenotype information hidden in EHRs is not an easy task. EHR-based studies have successfully replicated known associations, made new discoveries for diseases and drug response traits, rapidly contributed cases and controls to large meta-analyses, and demonstrated the potential of EHRs for broad-based phenome-wide association studies. In this review, we summarize the advantages and challenges of repurposing EHR data for genetic research. We also highlight recent notable studies and novel approaches to provide an overview of advanced EHR-based phenotyping.

Information technology in critical care: review of monitoring and data acquisition systems for patient care and research

There is a broad consensus that 21st century health care will require intensive use of information technology to acquire and analyze data and then manage and disseminate information extracted from the data. No area is more data intensive than the intensive care unit. While there have been major improvements in intensive care monitoring, the medical industry, for the most part, has not incorporated many of the advances in computer science, biomedical engineering, signal processing, and mathematics that many other industries have embraced. Acquiring, synchronizing, integrating, and analyzing patient data remain frustratingly difficult because of incompatibilities among monitoring equipment, proprietary limitations from industry, and the absence of standard data formatting. In this paper, we will review the history of computers in the intensive care unit along with commonly used monitoring and data acquisition systems, both those commercially available and those being developed for research purposes.

The impact of a Critical Care Information System (CCIS) on time spent charting and in direct patient care by staff in the ICU: a review of the literature

PURPOSE

The introduction of a Critical Care Information System (CCIS) into an intensive care unit (ICU) is purported to reduce the time health care providers (HCP) spend on documentation and increase the time available for direct patient care. However, there is a paucity of rigorous empirical research that has investigated these assertions. Moreover, those studies that have sought to elucidate the relationship between the introduction of a CCIS and the time spent by staff on in/direct patient care activities have published contradictory findings. The objective of this literature review is to establish the impact of a CCIS on time spent documenting and in direct patient care by staff in the ICU.

METHODS

Five electronic databases were searched including PubMed Central, EMBASE, CINAHL, IEEE Xplore, and the Cochrane Database of Systematic Reviews. Reference lists of all published papers were hand searched, and citations reviewed to identify extra papers. We included studies that were empirical articles, published in English, and provided original data on the impact of a CCIS on time spent documenting and in direct patient care by staff in the ICU.

RESULTS

In total, 12 articles met the inclusion criteria. Workflow analysis (66%) and time-and-motion analysis (25%) were the most common forms of data collection. Three (25%) studies found an increase in time spent charting, five (42%) found no difference, and four (33%) studies reported a decrease. Results on the impact of a CCIS on direct patient care were similarly inconclusive.

CONCLUSIONS

Due to the discrepant findings and several key methodological issues, the impact of a CCIS on time spent charting and in direct patient care remains unclear. This review highlights the need for an increase in rigorous empirical research in this area and provides recommendations for the design and implementation of future studies.

Implementing an electronic medical record

We consider the practical aspects of justifying, planning, implementing, and budgeting for an electronic medical record. Examples include the decision about integrating versus replacing old systems, the timing of implementation for each clinical area, preparation for installing computerized order entry, a discussion about how to implement physician progress notes, and a discussion about how electronic nursing systems interact with the EMR. Integration of other systems such as PACS and EKGs are discussed. Wireless integration and telemedicine also are addressed, as well as backup, redundant systems and budgeting. The reader will gain a full understanding of the scope of the problems involved in implementing an EMR, and will have a step-by-step description of how to approach the task.

Care pathways for acute stroke care and stroke rehabilitation: from theory to evidence

Care pathways aim to promote evidence- and guideline-based care, improve the organisation and efficiency of care, and reduce cost. In the past decade, care pathways have been increasingly implemented as a tool in acute stroke care and stroke rehabilitation. In the most recent Cochrane systematic review, which included three randomised and 12 non-randomised studies, patient management with stroke care pathways was found to have no significant benefit on functional outcome, and patient satisfaction and quality of life might actually be worse. On the other hand, it was associated with a higher proportion of patients receiving investigations and a lower risk of developing certain complications such as infections and readmissions. Overall, the evidence supports the use of care pathways in acute stroke but not stroke rehabilitation. Future developments, including electronic care pathways, patient pathways, and pre-hospital care pathways for hyperacute stroke, will be discussed.

Barriers to Glucose Control in the Intensive Care Unit

Despite published evidence supporting glycemic control in critically ill patients, achieving euglycemia remains a problem in the intensive care units (ICUs) of many institutions. Clinicians seeking to implement the findings of published evidence in their practice face many potential barriers that make euglycemia difficult to achieve in patients in the ICU. Developing a comprehensive understanding of the many barriers to ICU glucose control can aide clinicians in attempting to change practice and improve patient outcomes. Barriers to ICU glucose control include the role of different health professionals in glucose management, communication among health care professionals, guidelines, protocols, ICU culture, fear of hypoglycemia, glucose monitoring, education, systems analysis, health care resources, nutritional needs, and drug utilization. By ensuring compliance, changing ICU culture, developing guidelines and protocols, and incorporating a multidisciplinary approach, clinicians can achieve glycemic control in the critically ill population and improve patient outcomes.

The accuracy of clinical information systems

The clinical information system (CIS) is becoming more common in intensive care units. These systems have the ability to record, store, and retrieve large amounts of clinical patient data with great ease. This should greatly facilitate outcomes research and quality assurance. Unfortunately, there is not much information available about the accuracy of the data coming from these systems. True accuracy of a patient record requires both completeness of data and correctness of data as well as legibility. Automated systems are clearly superior to human entered data in terms of completeness and legibility but the correctness of entered data remains unclear. There are aspects of automated data entry that facilitate erroneous data entry. This article reviews the existing literature on accuracy of CISs with special attention to the qualities of automated data entry that can lead to false data. Additionally, data are presented from a newly published study by the author evaluating the validity of data from a commercially available CIS.

Computers in the ICU: where we started and where we are now

The first use of computers in critical care units were described in the mid 1960s. They reported the use of very large mainframe computers that filled entire rooms yet had very limited memory and processing capacities by today's standards. These were limited to only a few institutions until microprocessors were developed increasing computation speed and expanding memory capacity by many magnitudes. This allowed smaller more affordable stand alone systems to be developed and the inclusion of microprocessors into bedside devices. As the capacity expanded uses broadened. Simple results review developed into a more complete electronic medical record. Databases were created allowing population analysis for research and systems quality improvement activities. Decision support started as simple alerting of potential errors and dangers and expanded into more sophisticated clinical decision-making support. With this came problems that needed solutions. As the amount of information became overwhelming to the bedside clinician, methods to filter and display data made it more useful. Security and confidentiality became major concerns. Data input solutions had to be found including interfaces between computers, bedside devices and instruments designed to automate data input like scanners, bar coders, and other devices. The biggest issue of all however, was developing acceptance among clinicians and creating the cultural change required for successful implementation of electronic medical records. This paper will explore these issues.

Changes in intensive care unit nurse task activity after installation of a third-generation intensive care unit information system

OBJECTIVE To determine the percentage of time that intensive care unit (ICU) nurses spend on documentation and other nursing activities before and after installation of a third-generation ICU information system.

DESIGN

Prospective data collection using real-time time-motion analysis, before and after installation of the ICU information system.

SETTING

A ten-bed surgical ICU at a Veterans Affairs medical center.

SUBJECTS

ICU nurses.

INTERVENTIONS

Installation of a third-generation ICU information system.

MEASUREMENTS AND MAIN RESULTS

Ten ICU nurses were studied before and after installation of the ICU information system. Each ICU nurse's activities and tasks, during 4-hr observation periods, were categorized in real-time by a nurse observer and recorded in a laptop computer. Each recorded task was automatically time-stamped and logged into a data file. The percentage of time spent on documentation decreased from 35.1 +/- 8.3% to 24.2 +/- 7.6% (p =.025) after the ICU information system was installed. The percentage of time providing direct patient care increased from 31.3 +/- 9.2% to 40.1 +/- 11.7% (p =.085). The percentage of time doing patient assessment, a direct patient care task, increased from 4.0 +/- 4.7% to 9.4 +/- 4.4% (p =.001).

CONCLUSIONS

Installation of a third-generation ICU information system decreased the percentage of time ICU nurses spent on documentation by >30%. Almost half of the time saved on documentation was spent on patient assessment, a direct patient care task.

Handheld computers in critical care

BACKGROUND

Computing technology has the potential to improve health care management but is often underutilized. Handheld computers are versatile and relatively inexpensive, bringing the benefits of computers to the bedside. We evaluated the role of this technology for managing patient data and accessing medical reference information, in an academic intensive-care unit (ICU).

METHODS

Palm III series handheld devices were given to the ICU team, each installed with medical reference information, schedules, and contact numbers. Users underwent a 1-hour training session introducing the hardware and software. Various patient data management applications were assessed during the study period. Qualitative assessment of the benefits, drawbacks, and suggestions was performed by an independent company, using focus groups. An objective comparison between a paper and electronic handheld textbook was achieved using clinical scenario tests.

RESULTS

During the 6-month study period, the 20 physicians and 6 paramedical staff who used the handheld devices found them convenient and functional but suggested more comprehensive training and improved search facilities. Comparison of the handheld computer with the conventional paper text revealed equivalence. Access to computerized patient information improved communication, particularly with regard to long-stay patients, but changes to the software and the process were suggested.

CONCLUSIONS

The introduction of this technology was well received despite differences in users' familiarity with the devices. Handheld computers have potential in the ICU, but systems need to be developed specifically for the critical-care environment.

Critical care computing. Past, present, and future

With rapidly increasing processing power, networks, and bandwidth, we have ever more powerful tools for ICU computing. The challenge is to use these tools to build on the work of the Innovators and Early Adopters, who pioneered the first three generations of systems, and extend computing to the Majority, who still rely on paper. What is needed is compelling evidence that these systems reduce cost and improve quality. The experience of other industries suggests that we need to address fundamental issues, such as clinical organization, roles, behavior, and incentives, before we will be able to prove the benefits of computing technology. When these preconditions are met, the promise of computing will be realized, perhaps with the upcoming fourth-generation systems. ICU computing can then finally cross the chasm and become the standard of care.