The Integration of Technology and Innovation in the Development of Patient-Centered Medicine in the Intensive Care Unit: A Literature Review

The Integration of Technology and Innovation in the Development of Patient-Centered Medicine in the Intensive Care Unit: A Literature Review

Introduction

(Article introduction authored by ICU Editorial Team)

Since the advent of intensive care units in the twentieth century, several advances have been developed in relation to diagnosis, organ support, and treatment modalities.

However, the environment for professionals, patients and their families continues to be stressful and uncomfortable. Optimizing the working conditions and processes of intensive care units is of great significance for improving efficiency and minimizing human errors.

Innovations and technological advances can also bring higher quality and safer medicine, as well as greater personalization and a better experience for critically ill patients. This article reviews the progress in the related fields that could be the trend in the coming years for the formation of intelligent intensive care units.

It is discussed how thinking about design, structure, equipment, less invasive monitoring, expansion of digital transformation, incorporation of artificial intelligence, in addition to the perspectives of these changes on the multidisciplinary team, can be important in the search for patient-centered care in the future of the intensive care units.

Challenges and Opportunities in critical care

Design and structure of the ICU

It has been shown that the physical environment impacts the physiology, psychology, and social behaviors of ICU patients and staff. Transforming the ICU from a hostile to a “home-like” environment through architectural and design changes can improve care and patient well-being.

Rethinking ICU layout and services for patients and families helps minimize stressors by controlling factors like light, sound, and room arrangement. Single rooms enhance comfort, privacy, and infection
control.

Organizing patient equipment efficiently and utilizing remote control technologies can reduce unnecessary interventions and PPE usage. Future ICU designs should facilitate patient-centered care, with features like smart glass walls, nearby nursing stations, and home-like elements to prevent delirium.

Individualized alarm settings and central monitoring systems can minimize noise. The ICU should accommodate family presence, treating them as part of the care process and allowing extended visiting hours.

Patient safety remains crucial, with camera monitoring to prevent accidents and quick access for emergencies. Family areas should be comfortable and supportive, guided by the ICU team on contributing to patient care.

ICU monitoring

Historically, ICU professional practices have been shaped by the equipment used to support patients’ failing organs. Technical innovations have revolutionized critical care equipment. New bedside monitors and wearable devices offer wireless information, improving safety and comfort by reducing invasive procedures.

Non-invasive technologies for hemodynamic monitoring, like continuous blood pressure measurement and cardiac output assessment, have advanced rapidly, minimizing complications of invasive methods. Techniques using thoracic electrical bioimpedance and plethysmography are effective and cost-efficient.

Future hemodynamic monitoring aims to optimize organ perfusion and oxygenation at the tissue level using technologies like NIRS and video-microscopy, enhanced by AI for precise, real-time treatment.

Economic constraints highlight the need for accessible monitoring solutions. Simplified devices, like hand-held echocardiography, are becoming more common. Smart systems will further facilitate measurements, improving outcomes.

Technological advancements in mechanical ventilators will monitor critical parameters to prevent ventilator-induced lung injury.

Biochemical tests in ICUs may soon be replaced by specific molecular biomarkers for personalized treatments. Point-of-care tests for inflammation, nutrition, coagulation, and renal function will enhance treatment agility.

Microfluidic devices for continuous drug monitoring will ensure therapeutic doses and reduce risks of kidney and liver damage.

2.4 ICU support and personalized treatments

A challenge in personalizing therapy in critically ill patients is their inherent heterogeneity, however, with the advance of technologies, new devices for organ support will emerge in the next years.

Regarding respiratory support, 2 subtypes of acute respiratory distress syndrome (ARDS) have been identified in large observational cohorts. These biologic phenotypes appear to respond differently to standard supportive therapies, and the mechanical ventilation

Personalization of ICU nutrition is also essential in the future smart ICUs Ideally, nutrition should be individualized, with accurate markers indicating when energy intake is adequate, minimizing over-and underfeeding. Thus, it is necessary to develop future devices for measurement of energy and protein needs to meet specific targets.

Currently, indirect calorimetry (IC) measurement of energy expenditure (EE) is recommended after stabilization in the ICU admission. In the future, we expect to see different techniques for monitoring muscle, such as ultrasound, to assess nutrition risk and monitor response to nutrition.

The use of specialized anabolic nutrients such as hydroxymethylbutyrate (HMB), leucine and creatine to improve strength muscle mass is promising in specific populations and deserves future studies.

Another major future challenge is the emergence of antimicrobial resistance (AMR) to most available antibiotics, especially the emergence of multidrug-resistant (MDR) bacteria.

For successful treatment of infectious diseases, a prior knowledge of the in-vitro bacteria susceptibility to antimicrobial agents is crucial Scientists are working on the development of novel and faster methods of antimicrobial susceptibility testing to be applicable in the microbiological laboratory practice.

To meet these requirements, there especially important in ICUs, where patients present complex unpredictable ways and a timely intervention is important to improve outcomes.

Thus, predicting disease progression can be crucial for critical patients. For clinicians manage this complexity, a careful consideration of underlying etiologies and clinical conditions is necessary.

In the past, prognostic models focused on mortality using simple ordinal disease severity rating scores, which had to be tabulated manually by a human. Nowadays, Al can recognize patterns leading to more personalized treatment plans.

This is a current trend in research to explore automation, genotypic and micro/nano technology-based innovations. Automation in detection systems and computer technology for online data analysis and sharing are giant advances toward automated methods.

With the evolution of methods in antimicrobial susceptibility testing, we will have faster results and the implementation of more specific treatments in a more agile way.

Systems that underlie ICU care and applications of artificial intelligence (AI)

Currently, health information technology is widely available even in developing countries. Electronic medical record (EMR) systems can minimize costs and time spent by ICU staff on documentation by focusing on essential data fields and enabling automatic data capture.

Furthermore, medical device integration can synchronize data from medical equipment and monitors to the EMRs, generating an efficient and accurate data transfer. Integration of data enables the conversion of the traditional ICU into a leaming healthcare system that analyzes and interprets data from various sources to favorably change clinical practice.

Moreover, quick data analysis from EMRS for research, benchmarking, and safe and quality institutional improvement programs can contribute to the education of ICU workers and the implementation of processes and protocols capable of improving cost-effectiveness.

The creation of learning healthcare systems sets the foundation for personalized medicine as a medical model that individualizes the care of patients according to risk of disease or the predicted response to an intervention.

This feature is Dynamic random forest model (RF) is al type of a computer-driven machine learning technique that can predict outcomes in the ICU. A study by Yoon et al, showed that a dynamic model using random forest classification could predict cardiorespiratory instability hours before these events occurred.

In other words, the use of a variety of machine leaming tools can lead to the identification of alert artifacts and filtering of bedside alarms, displaying real-time stratification to assist clinical decision-making at the bedside.

Another area in which machine learning can be important is to predict symptoms. A recent study, focused on pain experienced by critically ill patients, demonstrated that vital signs, continuously measured in the ICU, can be used to predict pain with high accuracy using a RF model as well. These results show that machine learning can be used to continuously evaluate pain and recommend starting analgesic medications earlier.

This algorithm may be even more relevant in patients who cannot communicate, which could improve their ICU experience. All these examples show how Al can serve as an aid to more personalized medicine in the coming decades.

Conclusion

Despite recent advances in intensive care over the years, the substantial heterogeneity of illnesses in critically ill patients and the psychological stress that involves ICU workers make this an extremely challenging environment for sufficient progress regarding therapies and outcomes. To continue progressing, critical care infrastructure needs to be transformed and the focus must be on personalized and patient-centered medicine.

Technology will continue to provide tools to redesign processes, improve efficiency and minimize human errors in intensive care. However, it is imperative that the focus on developing non-technical skills must be prioritized, with an emphasis on communication, empathy, and engagement of the ICU staff.

Sources: Citation: Filho, R., R., and Corrêa, T., D., 2024. The Integration of Technology and Innovation in the Development of Patient-Centered Medicine in the Intensive Care Unit: A Literature Review. Medical Research Archives, [online] 12(1). https://doi.org/10.18103/mra.