Until recently, continuous glucose monitoring (CGM) systems were reserved for use in the outpatient setting or for investigational purposes in hospitalized patients. However, during the coronavirus disease 2019 pandemic, use of CGM in the inpatient setting has grown rapidly. This review outlines important details related to the accuracy, limitations, and implementation of, as well as necessary staff education for, inpatient CGM use and offers a glimpse into the future of CGM in the inpatient setting.

Inpatient glucose management is challenging given the complexities of care for hospitalized patients with diabetes, including changes in diet status, medications, glucose metabolism, and schedules. Glucose variability and hypoglycemia have been associated with worse outcomes in hospitalized patients (13). In addition, diabetes and hyperglycemia are associated with worse coronavirus disease 2019 (COVID-19) outcomes (4,5).

Until recently, blood glucose measurements using point-of-care (POC) and whole-blood laboratory testing were the only means of assessing glycemia in the hospital setting. In contrast, the advent of continuous glucose monitoring (CGM) revolutionized diabetes care in outpatient settings. CGM measures interstitial fluid glucose levels via a subcutaneous sensor that transmits data to an insulin pump, smartphone, or stand-alone receiver or reader, either in real-time when using a real-time CGM (rtCGM) system or when a user scans the sensor with the receiver when using an intermittently scanned CGM (isCGM) system (Table 1) (69). Before the COVID-19 pandemic, inpatient CGM was limited to use for research purposes, in which it demonstrated a reduction in inpatient hypoglycemia (10,11) and hyperglycemia (12). However, in April 2020, the U.S. Food and Drug Administration (FDA) expanded the availability and implementation of noninvasive patient monitoring devices during the pandemic by exercising enforcement discretion so that CGM could be used temporarily in the inpatient setting (13). CGM was well suited to address some challenges of the COVID-19 pandemic by reducing nursing exposure, preserving personal protective equipment (PPE), and providing additional glucose data including trends (14). However, there are many important considerations for its continued inpatient use.

Inpatient CGM may be a promising alternative to periodic POC glucose measurement and offers advantages that include automatic measurement of glucose values displayed at intervals of 1–5 minutes, automatic transmission of glucose values to physically distant display devices, and programmable alerts and alarms to warn the inpatient care team of existing or impending dysglycemia. However, it is important to understand that CGM measures interstitial glucose rather than blood glucose, as is measured with capillary POC or laboratory glucose testing. Intestinal glucose can lag behind blood glucose by up to 40 minutes, with an average delay of ∼9 minutes (15). The delay is noted to be more prolonged and clinically significant in the setting of rapidly changing glucose levels such as after meals (15,16). Few studies of interstitial glucose have been conducted in settings such as hypotension, hypoperfusion, hypoxia, or other states common in hospitalized patients. Nevertheless, since April 2020, because of the need to adapt inpatient workflows in response to the COVID-19 pandemic, inpatient use of CGM has expanded significantly.

Patients admitted to the hospital may wish to continue using their own personal CGM system during their hospital stay. Published guidelines overwhelmingly support this option (1719) and call for policy development, patient and staff education, and appropriate electronic health record (EHR) documentation to foster its safe and successful use. In this review, we discuss current guidelines, measures of accuracy, steps for successful implementation, current data, and future research recommendations for use of CGM in the adult inpatient population.

Several consensus guidelines have been published (1719), including the Diabetes Technology Society’s (DTS’s) statement titled “Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline” (19). The DTS statement was published in September 2020, which was early in the period immediately following the FDA’s announcement of its intended enforcement discretion (13) and before inpatient CGM was adopted more widely and research articles on its expanding use were published. The DTS’s consensus guideline writing group emphasized the need for hospitals to develop policies, processes, and staff education programs and provided basic recommendations for initiating CGM in the hospital. The statement called on hospitals to:

  • Consider the use of inpatient CGM “to reduce the need for frequent nurse contact for POC glucose testing and the use of PPE for patients in isolation with highly contagious infectious diseases (e.g., COVID-19)”

  • Avoid initiating CGM “in patients with severe hypoglycemia or hyperglycemia (i.e., blood glucose levels <40 or >500 mg/dL) or during periods of rapid glucose fluctuations”

Key DTS recommendations are outlined below for hospitals with patients who want to continue using their own CGM system while hospitalized (19).

  • If available, consult with an inpatient diabetes team when continuing or initiating CGM in the inpatient setting.

  • Avoid using CGM for management decisions in the following settings:

    • Severe hypoglycemia or hyperglycemia (i.e., blood glucose levels <40 or >500 mg/dL)

    • Diabetic ketoacidosis (DKA) until glucose is in the CGM measurement range, and then for adjunctive use

    • Rapidly changing glucose levels and fluid/electrolyte shifts

    • Skin infections near the sensor site (or placing sensors in areas with significant edema)

    • Use of vasoactive agents or with poor tissue perfusion

  • Use a CGM checklist for elective procedures during preoperative visits to ensure proper documentation of devices and real-time data reporting.

  • Check the correlation between capillary or venous blood values and CGM values after procedures for noncritically ill patients and between venous/arterial blood glucose and CGM values for critically ill patients to ensure that the patient’s CGM system is functioning well.

  • Use glycemic trend arrows and rates of change to help prevent extreme glycemic excursions, and set alarm thresholds for inpatient glycemic targets to predict hypoglycemia and hyperglycemia.

  • Develop hospital policies to ensure documentation of CGM in the EHR with standard CGM data reports and workflows and that capillary glucose is tested to calibrate CGM systems that require calibration.

Additionally, guidelines recommend that pregnant women continue using CGM during hospitalization (19). It should be noted that, although CGM is not FDA-approved for use in pregnancy, clinical benefits of such use have been demonstrated, including the use of glycemic trend arrows to prevent impending hypoglycemia or hyperglycemia (20). The American Diabetes Association’s 2022 Standards of Medical Care in Diabetes (17) acknowledge the lack of FDA approval and thus do not offer recommendations for use in hospitalized pregnant women until further data on improved glycemic and hospital outcomes are available (17).

The accuracy of CGM is of the utmost importance. It is especially important for clinicians to understand and interpret measures of CGM given the current lack of regulation or standardization of CGM in the inpatient setting.

Several standards exist for determining the accuracy of traditional blood glucose meters, as summarized in Table 2 (2123). The FDA has published standards for the use of prescription POC glucose meters in U.S. hospitals (24). This guidance is similar to that of the International Organization for Standardization (ISO) standard ISO 15197:2013 (21), which is widely used outside of the United States. In addition, the Clinical and Laboratory Standards Institute has published consensus guidelines for hospital POC glucose monitoring (25). These guidelines are specific to glucose meters but do provide a frame of reference for current meter accuracy standards when interpreting CGM accuracy data. Included in Table 2 are the FDA’s recommendations for systems it calls “integrated CGM,” including advanced hybrid closed-loop insulin pump systems that use CGM data to calculate and deliver insulin dose adjustments in real time.

One frequently reported analytic statistical metric for CGM is the mean absolute relative difference (MARD). Error grid analysis results are also frequently reported to describe CGM accuracy.

MARD Values

The MARD is the percentage difference in either direction between the reference method (e.g., Yellow Springs Instrument method) and the sensor value (26). Most current glucose sensors have MARDs ranging from 8.5 to 13.6% over the entire range of glucose levels for outpatient use (69,27) (Table 1).

MARD values can vary based on glucose level, rate of change, sensor wear time, and need for calibration, as well as differences between individuals (26,28,29). The MARD is also dependent on the accuracy of the comparator glucose measurement, which is often a blood glucose meter that carries its own variation in accuracy from its reference instrument (26,30), particularly POC blood glucose measurements in the setting of hypotension (31).

In general, the lower a system’s MARD value is, the greater its accuracy is. As discussed above, there are currently no guidelines or cut-off values for CGM MARD values (32) in the outpatient setting, much less in the inpatient setting. MARD values have also been demonstrated to vary within a day (33) and should not be used as the sole criterion to assess CGM system accuracy (26).

Error Grid Analysis

Error grids are useful to help define how clinically accurate a glucose monitoring device is compared with a gold standard glucose measurement. The Clarke error grid (CEG), Parkes consensus error grid, and surveillance error grid are commonly used error grids (3436). Error grid results are presented both visually and as a percentage of data points falling within grid zones (36). Readings falling into zone A on the CEG are considered clinically accurate; those falling into zone B are less accurate but are considered benign errors. Readings from both zones A and B are considered acceptable for making clinical decisions (Figure 1) (37).

Planning for CGM Use

Key stakeholders should be involved before implementing CGM in the hospital setting. This effort should include the development of a policy, which should reflect input from hospital leadership, diabetes specialists, prescribers, nursing leadership, nurse educators, bedside nurses, pharmacists, laboratory specialists, information technologists, the risk management team, quality champions, and other stakeholders. The policy should encompass information regarding definitions, purpose, scope, exclusion and inclusion criteria, details of procedure, and documentation. Medical leadership and legal and other appropriate institutional departments and committees should review the policy before it is implemented.

Patient Selection and Exclusion

CGM has been used primarily in two types of inpatients: those receiving intravenous (IV) insulin infusions in the intensive care unit (ICU) and step-down units and those on subcutaneous (SQ) insulin protocols in non-ICU settings. In addition, CGM has been used in the surgical setting. During the COVID-19 pandemic, CGM has been used in patients both with and without COVID-19 infection. The literature on these inpatient CGM experiences is summarized in Table 3 (11,12,14,3858).

It is important for hospitals to review the most current published data and consensus guidelines to determine the most appropriate patients for CGM because the field is rapidly evolving. Current guidelines for patient selection and some exclusions to CGM use in the hospital are summarized above. With regard to exclusions, DTS guidelines recommend avoiding the use of inpatient CGM in patients with blood glucose levels <40 or >500 mg/dL and those with DKA, in the setting of rapidly changing glucose levels and fluid and electrolyte shifts, and in those with significant edema requiring vasoactive agents or with poor perfusion (15) until more research is available. Several small studies have reported on the feasibility of CGM use in the critical care setting during the COVID-19 pandemic (Table 3).

Interfering Substances

Various interfering substances can affect the accuracy of each CGM system (Table 1). It is important to be aware of these substances and refer to the user guides of each CGM system for more information. None of the current CGM systems, with the exception of an implantable CGM sensor (27), are labeled for use in the setting of X-rays, computed tomography (CT) scans, MRI, diathermy, or radiation therapy (19). Guidelines recommend removing CGM sensors before CT scans and MRI (19); however, some small studies did not show any effect of CT scan or even simulated MRI radiation on the accuracy of the Dexcom G6 (53,59) or the FreeStyle Libre Pro (60) CGM systems.

Education on Placement of CGM Sensors

Detailed education on CGM sensor insertion and setup procedures is essential for successful inpatient CGM implementation. This education can be provided through in-person training, videos, or tip sheets. Bedside nurses, or preferentially, if resources allow, specially trained CGM champions can be educated on CGM sensor insertion (10,14,48,53). Recommended sensor placement depends on the specifications of the specific CGM system being used. However, the Dexcom system, which is approved for use on the abdomen, was successfully worn with alternative arm placement (because of issues of prone positioning of COVID-19 patients) (44,53).

Protocols for CGM Use and POC Blood Glucose Correlation

For institutions already using CGM for glucose monitoring and insulin dosing, there is significant variability in protocols with regard to the frequency (if any) of confirmatory glucose testing (12,53). Both venous/arterial and POC capillary glucose monitoring have been used for correlation measurements (44,53). Laboratory glucose testing has demonstrated better correlation to CGM than POC capillary glucose testing (53). Although limited in volume and quality, data thus far have indicated the feasibility of CGM compared with POC testing in general ward settings (48) and in the ICU (14).

In most studies, acceptable correlation has been defined as a difference of <20% or <20 mg/dL between POC and CGM values if glucose is <100 mg/dL (14). At one institution, nursing education deemed the 20% calculation too difficult for nurses to calculate in the setting of the COVID-19 pandemic; therefore, an arbitrary difference of >35 mg/dL between POC and CGM was used for glucose levels >100 mg/dL (representing 20% variation from a glucose level of 175 mg/dL) (53).

Recommendations for when to use POC blood glucose testing to determine a patient’s current glucose level are similar to those reported in a 2021 review by Perez-Guzman et al. (57). These included instances in which:

  • Glucose values are <85 or >300 mg/dL

  • Hypoglycemia symptoms occur

  • Glucose values and/or glycemic trend arrows are not present on the monitor

  • A blood drop symbol appears on the monitor (7)

  • Hemodynamic instability occurs

  • A patient is in the immediate postoperative period (57)

Several different protocols for use of CGM in the settings of IV insulin infusion and SQ insulin dosing have been reported. The most frequently reported protocols are as follows (12,38,40,41,44,45):

  • Initial start-up (after the warm-up period is complete)

    • Patients must have two consecutive sensor-meter pairs ∼1 hour apart in which CGM and POC values differ by <20% or <20 mg/dL if glucose is <100 mg/dL, or

    • CGM data are not used for the first 24 hours and then must meet acceptable correlation criteria, as described above.

  • Maintenance

    • POC blood glucose and CGM glucose values must meet the above criteria every 2–6 hours for continued use in the setting of IV insulin infusion.

    • POC blood glucose and CGM glucose values must meet above criteria every 6–12 hours in the setting of SQ insulin dosing.

CGM System Setup

Hospitals using inpatient CGM must adapt the existing technology, which was designed for outpatient use, to the inpatient setting. Setup procedures depend on the type of CGM system used (rtCGM vs. isCGM), as well as the layout of the nursing unit and choice of devices to receive CGM data.

For rtCGM, some institutions have kept the receiver, smartphone, or reader outside of the patient’s room to prevent nursing exposure and have reported good connection (38,53). Many institutions choose to use smartphones and also to set up smartphones or tablets at the nurses station equipped with real-time “following” applications (e.g., the Dexcom Follow app) to provide real-time alerts at a distanced location (53). For isCGM, nurses or patients have been directed to scan with a stand-alone reader or smartphone at the bedside.

If smartphones are used as receivers, de-identified dummy accounts must be created to provide delayed remote monitoring from Cloud-based reporting software. If a stand-alone receiver is used, data stored in the Cloud-based data-reporting software must be manually downloaded for review.

EHR Integration

Integration of CGM data into EHR systems to allow for remote and immediate access to CGM data are integral to the development of future inpatient CGM programs. Currently, CGM data can reside on a Cloud-based website, which increases concern regarding the safety of these data and the need for protection from cybersecurity breaches (57). Because CGM systems sample glucose values every 1–5 minutes, the amount of storage space needed to save every data point is extraordinarily large. CGM manufacturers need to work with diabetes care teams in conjunction with EHR and middle-ware software vendors to integrate the most useful CGM data into existing EHR platforms.

In some EHR systems, CGM has been manually documented in the glucose flow sheet with a separate column for POC entry and correlation between the two devices. Separate EHR reports that include a patient’s demographics, diagnosis, length of stay, disposition, medications, average placement time for CGM, and data on vasopressors and continuous renal replacement therapy (CRRT) have also been created (38).

Espinoza et al. (61) proposed the development of a consortium of key stakeholders known as the Integration of Continuous Glucose Monitoring Data into the Electronic Health Record (iCoDE) Project, in collaboration with the DTS. The intention of this group would be to 1) develop standards for the exchange, classification, and mapping of CGM data and 2) develop policies to guide the integration of CGM data into EHR systems.

Using Trend Arrows

For outpatients using CGM, several tools have been developed to integrate trend arrows into insulin dosing algorithms (6264). Very few studies using trend arrows in the inpatient setting have been published. Scripps Hospital reported on a remote telemetry service that monitors CGM data, including trend arrows, and reports significant trends to nursing staff. This study demonstrated lower average glucose, improved time in range, and rare hypoglycemia (12).

CGM in Critical Care

Multiple studies have been conducted in ICU patients. Most of these were small and focused on feasibility and accuracy (Table 3). The MARDs reported in these studies ranged from 11.1 to 14%. The use of POC blood glucose measurements was reported to be reduced by 60–71% (44). Many of these studies demonstrated the feasibility of CGM use during the critical time of the COVID-19 pandemic, but more robust studies are clearly needed in this complex patient population.

Davis et al. (44) performed a proof-of-concept study using CGM and a computerized decision-support tool for IV insulin infusions in ICU patients. Negative sensor bias was noted during periods of hypoperfusion (i.e., with pulseless electrical activity or shock), therapeutic hypothermia, and position changes resulting in sensor compression, with a sharp decline in values and loss of signal during cardiac arrest and defibrillation (44).

Joshi et al. (38) reported on a retrospective study of 165 patients in the ICU, including patients on vasopressors and CRRT, with an overall MARD of 14% (POC blood glucose vs. CGM) and a Pearson correlation coefficient of R = 0.89 (in patients requiring CRRT/hemodialysis, R = 0.798, and for patients using vasopressors, R = 0.798).

There are more studies in non-ICU settings, many of which are case studies and pooled analyses. These studies reported wide variations in MARD ranging from 9.77 to 28% (Table 3). There was also significant variation in study design and patient selection criteria. Singh et al. (11) published data from a randomized controlled trial involving 72 patients using a glucose telemetry system (GTS) that integrated CGM with the EHR and demonstrated fewer hypoglycemic episodes per patient using GTS (GTS 0.67 [95% CI 0.34–1.3] vs. usual care 1.69 [95% CI 1.11–2.58], P = 0.024). Assessment of the quality of comparator glucose measures was also identified as important in a study by Longo et al. (53), with an overall MARD of 13.9% when using POC blood glucose measurement as a comparator versus 10.9% when CGM was measured against laboratory-measured glucose values.

There have been very few studies assessing CGM in the setting of surgical and radiological procedures. Although an earlier study did not show a good correlation during cardiac surgery (55), a recent study by Perez-Guzman et al. (57) involving 15 patients undergoing coronary artery bypass graft documented a MARD of 12.7%. There was some loss of sensor activity during surgery, but six sensors recovered completely after surgery and maintained accuracy despite vasopressor use.

CGM Satisfaction

CGM has been shown to save nurses time (17 vs. 36 minutes per day spent on glucose management, P <0.001) (65). In addition, in a survey of 112 medical staff using inpatient CGM, 92% reported that they felt CGM reduced their own exposure to COVID-19 (38). Dillman et al. (66) reported that 95% of nurses found CGM to be “useful,” specifically by anticipating hyperglycemia and hypoglycemia, and 64% reported CGM to be time-saving. Faulds et al. (67) also reported positive experiences from nursing staff, including the ability to continuously monitor glucose levels. However, they did find some aspects of the protocol, such as setting up smartphones to receive data, to be lengthy.

As Winston Churchill famously said, “Never let a good crisis go to waste.” The COVID-19 pandemic has allowed for the rapid expansion of inpatient CGM use. Although there is now a growing number of reports of successful integration of CGM in the inpatient setting with reasonable accuracy data, the need for further research focused on safety, accuracy, and outcomes is clear. Moving forward, it will be important to consider the limitations of CGM such as the lag time between interstitial fluid and blood glucose levels, which can vary, particularly in settings of rapidly changing glucose levels (16). Appropriate patient selection is key, and subgroup analyses of accuracy and outcomes data are also important, particularly in critically ill patients requiring vasopressors and CRRT and in states of hypoperfusion. As the DTS guidelines note, studies of the impact of lag time should be done, and standardized protocols for when confirmatory POC blood glucose testing is needed should be created (14,15).

Cost-benefit outcomes data analyses will be crucial for adoption of CGM technology by hospitals and payers. As discussed above, successful implementation of any inpatient CGM program requires extensive staff training in the placement, maintenance, and troubleshooting of CGM systems, as well as clear understanding and interpretation of CGM data.

Future protocols that integrate glycemic trend arrows into insulin dosing decisions may provide opportunity for improvement in inpatient glycemic management. In addition, education of nurses, nurse practitioners, physician associates, pharmacists, and physicians is crucial not only for the successful implementation of inpatient CGM, but also to foster its optimal use and actionable interpretation of the data it provides.

Many institutions have successfully integrated CGM into inpatient glucose management to save PPE, limit nursing exposure, and possibly improve glycemic outcomes during the COVID-19 pandemic. More expansive adoption of CGM may be a much-needed paradigm shift in inpatient glycemic management compared with occasional POC blood glucose checks. Further careful study of the accuracy and outcomes of CGM use in the hospital will be crucial to facilitate its widespread adoption and regulatory approval.

Acknowledgment

The authors thank Laurie Schwing of University of Pittsburgh Medical Assistance for her editorial assistance.

Duality of Interest

R.J. is a speaker for Medscape. No other potential conflicts of interest relevant to this article were reported.

Author Contributions

Both authors researched data and wrote and edited the manuscript. Both authors are the guarantors of this work and, as such, take responsibility for the integrity of the data presentation and accuracy of the review.

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