Clinical Surveillance

The Actionable Benefits of Objective Medical Device Data for Critical Decision-Making

John Zaleski

• Publisher: Productivity Press
• Year: 2020
• ISBN:
  9781000196115
• Edition: 1
• Topic: Commerce
• Subtopic: Gestion de l'information

For more than a decade, the focus of information technology has been on capturing and sharing data from a patient within an all-encompassing record (a.k.a. the electronic health record, EHR), to promote improved longitudinal oversight in the care of the patient. There are both those who agree and those who disagree as to whether this goal has been met, but it is certainly evolving. A key element to improved patient care has been the automated capture of data from durable medical devices that are the source of (mostly) objective data, from imagery to time-series histories of vital signs and spot-assessments of patients.

The capture and use of these data to support clinical workflows have been written about and thoroughly debated. Yet, the use of these data for clinical guidance has been the subject of various papers published in respected medical journals, but without a coherent focus on the general subject of the clinically actionable benefits of objective medical device data for clinical decision-making purposes. Hence, the uniqueness of this book is in providing a single point-of-capture for the targeted clinical benefits of medical device data--both electronic- health-record-based and real-time--for improved clinical decision-making at the point of care, and for the use of these data to address and assess specific types of clinical surveillance.

Clinical Surveillance: The Actionable Benefits of Objective Medical Device Data for Crucial Decision-Making focuses on the use of objective, continuously collected medical device data for the purpose of identifying patient deterioration, with a primary focus on those data normally obtained from both the higher-acuity care settings in intensive care units and the lower-acuity settings of general care wards. It includes examples of conditions that demonstrate earlier signs of deterioration including systemic inflammatory response syndrome, opioid-induced respiratory depression, shock induced by systemic failure, and more. The book provides education on how to use these data, such as for clinical interventions, in order to identify examples of how to guide care using automated durable medical device data from higher- and lower-acuity care settings. The book also includes real-world examples of applications that are of high value to clinical end-users and health systems.

Chapter 1

Introduction to Clinical Surveillance

Clinical Surveillance. What does it mean and why dedicate an entire book to the subject?

Clinical is defined by Merriam-Webster as “of, relating to, or conducted in or as if in a clinic: such as (a) involving direct observation of the patient clinical diagnosis; (b) based on or characterized by observable and diagnosable symptoms” [9].

Surveillance is defined by the same source as “close watch kept over someone or something (as by a detective)” [10].

The compound term Clinical Surveillance is self-evident by the combination of the terms: the intent is to provide a close and continuous watch over a patient in a clinical setting. The terms together imply a close watch—a continuous watch—over all aspects of the subject patient. The term surveillance has been applied in other domains to imply the same close watch, based on the available information on the subject and the environment in which the subject is active. By analogy, in the context of surveillance as might be considered from a law enforcement or military perspective, the implication is the close observation and oversight of a subject (target) in all its aspects. A key point is that close observation implies continuous—that is, uninterrupted observation and monitoring so that the subject of the surveillance is always under scrutiny for changes that may be of interest or import. In a sense, continuous monitoring can seem foreboding—both for the individual performing the surveillance and for the subject of the surveillance—in terms of the energy required to surveil and for possible concerns regarding the “privacy” of the individual being surveilled. Personal privacy implications and continuous surveillance are potentially competing interests that need to be balanced to meet the best interests of both the subject (patient) and the observer (clinician). Yet, in the application of clinical surveillance, the subject or the “target” of the surveillance is the individual patient, and the object is to detect changes in patient “state” or condition that would be deemed untoward or adverse—changes or trends toward the undesirable. Continuous oversight of patients can consume a great deal of energy and time. In certain locations within the healthcare setting (e.g., intensive care units, operating rooms, telemetry units, emergency departments) the effort to oversee patients continuously requires dedicated personnel and equipment that can monitor patient cardiac and respiratory function. In such cases, alarms and notifications surrounding untoward deviations in patient state are transmitted in real-time to inform clinical personnel of adverse events so that rapid intervention can be initiated as required. The annunciation of alarms and alarm signals is a subject of a later chapter relating to detecting and differentiating true alarms from false alarms. Because alarms can become overwhelming in environments such as cardiac telemetry units and intensive care units (ICUs), other aids need to be brought to bear to assist the clinician in the continuous surveillance of patients to help identify when an alarm truly requires immediate action. The physiological monitoring and other equipment employed in these environments enable the setting of alarms or limit settings that identify when undesirable changes happen to a patient, and the changes in patient “state” as measured through physiological parameters provide insight into how patients evolve (or devolve) over time.

Yet, patients are not robots and do not obey absolute guidelines or behaviors in terms of their physiological responses. Those individuals reading this who are licensed clinicians may understand this and also recognize that while patients can present with gross symptoms that are consistent with known diagnoses, variations can exist that either make such diagnoses difficult at first, or make the diagnoses obvious, again, depending on patient presentation. Thus, the key message is that viewing “the numbers” alone—vital signs, for example—is necessary but insufficient in terms of diagnosing a patient. Direct observation combined with other sources of information, including comprehensive metabolic panels, imaging, and direct observation, combined with palpation and auscultation, are necessary and expected as part of clinical practice. The numbers obtained from vital signs measurement, however, can provide an important adjunct for early notification as to a change of state in the patient that could predate adverse events. The identification of these early warning signs is the subject of this text, together with example techniques that can be used to assist in the identification of such events.

1.1 Patient Safety and Clinical Surveillance

It has been estimated that half of reported adverse events, or events leading to decompensation, and upwards of 60% of general care unit patients, experience “at least one or aberrant vital signs measurements up to six hours prior to a cardiac arrest” [11].

In the context of clinical surveillance, a key reason for observing changes in patient state is to identify adverse events early enough so as to be able to ward off or lessen the impact on the patient. In other words, the objective is to promote a safer outcome for the patient by detecting changes early enough so that an intervention can prevent worsening of the symptoms that could lead to catastrophic outcomes. Hence, patient safety is a key motivation behind clinical surveillance of the patient in the inpatient and even the outpatient, or ambulatory, care setting.

In ECRI’s Top 10 Patient Safety Concerns for 2019, several entries bear mentioning as concerns the understanding of how knowledge of a patient’s condition can translate into early indications of patient safety. Several of the items highlighted in the table below, and their importance relative to surveillance are paraphrased from the original source [12]:

Item number	Patient safety concern
6	“Failure to detect changes in a patient’s condition …across the continuum of care” in which “inadequately trained staff” can fail to respond or rescue a patient in sufficient time.
8	Early detection of sepsis in order to “facilitate timely diagnosis and management” of these patients for the reason of identifying adverse events early and providing the means to treat a patient as soon as possible.
10	Systemic improvements and standardization of patient safety in large and diverse healthcare systems “…to institute structures that effectively allow patient safety priorities … help the organization reduce inconsistencies and embed a strong focus o...

Table of contents

• Cover
• Half-Title
• Title
• Copyright
• Dedication
• Contents
• List of Figures
• List of Tables
• Preface
• Acronyms
• 1 Introduction to Clinical Surveillance
• 2 Use of Patient Care Device Data for Clinical Surveillance
• 3 Alarms and Clinical Surveillance
• 4 Mathematical Techniques Applied to Clinical Surveillance
• 5 Clinical Workflows Supported by Patient Care Device Data
• Epilogue: Lessons Learned from Continuous Monitoring
• Bibliography
• Index