Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.
There has been a lot of interest over the past several years in improving glucose monitoring. Capillary point of care (POC) blood sugar level measurement has been the default for monitoring and treatment of patients hospitalized with diabetes. POC blood glucose measurement is usually carried out 3-4 times in one day in hospital settings to monitor glycemic levels (Davis et al., 2020). There is, however, the increased importance of more frequent blood glucose (BG) due to the associated problems with intermittent POC testing. This desire for a more frequent BG measurement system led to the investment in the development of continuous glucose monitoring technology in the 1970s, with the first approval of such a system happening in 1999 by the Food and Drug Administration (Davis et al., 2020). CGM enables constant monitoring of BG levels with measurements every 5-15 minutes allowing for monitoring of trends. This is an important feature for both inpatient and outpatient circumstances.
A study seeking to analyze the performance of the Dexcom G6 as a CGM tool in non-critically-ill patients hospitalized with diabetes showed that it was a reliable tool for hospital usage and had the potential to improve BG monitoring for non-ICU diabetic patients (Davis et al., 2021). The research involved 218 patients aged between 48 and 72 years. The research involved comparing retrospective matched pair CGM values with those of the capillary point of care approach. Accuracy metrics analyzed included mean absolute relative difference (MARD), the proportion of CGM values, and mean absolute relative difference (ARD). The proportion of CGM values was within 15%-30% or 15-30 mg/dL for POC values of BG. The results of the experiment showed that the MARD for 4067 glucose pairs was 12.85 (Davis et al., 2020). The median ARD was 10.1 percent, while 68.7, 81.7, and 93.85 readings were meeting 15/15%, 20/20%, and 30/30 criteria, respectively.
Diabetes has been established as a risk factor for COVID-19 mortality and ICU hospitalization. Cardiovascular diseases and other metabolic factors are significant risk factors for the requirement of mechanical ventilators, severe kidney injury, and mortality. Hyperglycemia during hospitalization has also been identified as a poor prognostic sign. It has also been established that individuals with poorly controlled diabetes carried a higher risk factor for morbidity and mortality from COVID. Ehrhardt & Hirsch (2020), report that previous use of insulin, as opposed to HBA, was a mortality predictor. Another report showed that survivors of COVID showed lower mean BG levels during hospitalization than non-survivors. In light of these findings, it is curious if lowering glycemic targets could assist in mitigating the acute above the chronic inflammatory response to improve outcomes.
Another research was conducted to investigate hospital glucose management through POC testing against CGM. The research was carried out using a sample of 110 adults with type 2 diabetes in a non-critical care setting. They had used RT-CGM from Dexcom- the G6- juxtaposed against usual UC care. The results from the G6 had been transmitted wirelessly from the bedside (Fortmann et al., 2020). The CGM results were monitored by the hospital telemetry alerting bedside nurses of glucose results and trends while using standard protocols for interventions (Fortmann et al., 2020). The results showed that the RT-CGM exhibited lower mean BG levels and percentage period in hyperglycemia compared to the UC samples. This led to the conclusion that RT-CGM could be successfully used in non-ICU settings to enhance glucose management.
Electronic health records (EHR) has become an important part of healthcare due to advancement in technology and legislation requiring proper use. Wearables have the potential to augment EHRs through health systems interdependence. Issues arising with wearables include privacy concerns, patient data, and system interoperability (Dinh-Le et al., 2019). In a study to establish the landscape of wearable health technology, Dinh-Le et al. (2019) established that the integration of wearables into patient portals has already commenced. They identified 10 start-up organizations that are developing technology to improve wearable health technology enabling integration into HER systems. These companies include Royal Philips, Overlap, Validic, Vivify Health, Doximity Dialer, Xealth, Redox, Conversa, Glooko, and Human API. The research reported 16 collaborations between these start-ups and health corporations in addressing challenges in the meaningful use of wearable device data and streamlining workflows. It was also found that four insurance companies were encouraging the uptake and incorporation of wearables into health systems.
Although the FDA is yet to allow the use of CGMs in hospital settings, special consideration was allowed during the COVID-19 pandemic. According to Galindo et al. (2020), patients with moderate to severe hyperglycemia could be put on CGM because they require frequent BG monitoring and use complex insulin regimens. CGM was also recommended for patients with comorbidities that raise the risk of hypoglycemia. On which CGM devices are available, they found two classifications: those that are calibrated in the factory (Abbott FreeStyle Libre 14) and those calibrated by the patient (Dexcom G6) (Mhugel, 2021). Others require intermittent calibration, such as the Enlite 2 and the Medtronic Guardian, and the Eversense, which is the only implantable CGM that is FDA-approved.
Another classification of CGM devices available is either personal or professional. Professional devices use office-provided equipment to investigate patients’ BG. The patient is supposed to wear the device for roughly two weeks, after which the provider downloads the data (Laprezez & Woods, 2020). The professional can then draw BG patterns of the patients such as hypo or hyperglycemia, therapeutic range periods, and glucose variabilities, and can then use professional tools to treat the patients. These devices are recommended for patients that do not qualify for personal CGMs.
Intravascular CGM devices have been used with potentially acceptable precision but are not as widely adopted as the Dexcom G6 (Galindo et al., 2020a). The benefit of ICU usage of CGM has been inconsistent, while the use of CGMs for ambulatory services is limited despite documented benefits. For which patients CGM is recommended, patients in the 140-180 mg/dL range were favored. It was also recommended to continue using a hybrid system for hospital settings as more data is gathered on CGMs.
Despite the improvement of CGMs and the improved diabetes treatment systems, these devices come at an extra effort on the part of the patient. Besides CGM, there is the technology for the automation of insulin administration, also called closed-loop (CL) (Kropff & DeVries, 2016). CL technology relies on CGM data. Commercial CL products have used an insulin delivery shutoff system and have been successful in reducing hypoglycemia (Kropff & DeVries, 2016). Insulin-only devices have shown an increase in euglycemia and reduced hypo/hyperglycemia. There is also testing of dual-hormone CL artificial pancreas systems, which have also shown promise (Rodbard, 2017). These developments have been greatly improved by improved glucose monitoring technology, the development of algorithms, and the miniaturization of electronic devices (Kropff & DeVries, 2016). Challenges to the adoption of CL devices include the usability of the devices and reimbursement (Rodbard, 2016). According to Faulds et al. (2021), other challenges include lack of FDA approval, need for recalibration, need for regular replacement of sensors, lack of standardized software, and time and implicit costs spent in handling data.
CGM technology has pervaded the outpatient industry. In the hospital setting, the use of CGM is investigational and has been used specifically in non-ICU settings. CGM and closed-loop technologies have a lot of potential in improving glycemic control, reducing adverse events, reducing the length of stay, and lowering the risk of adverse events associated with hypo/hyperglycemia (Wang et al., 2019). Significant investment will be necessary, especially for hospital staff training together with infrastructural development. CL systems have limitations such as potential inaccuracies, interstitial BG measurements because of interference from medication, sensor lag, sensor drift, and the need for routine monitoring of sites to ensure enough insulin in the reservoir (Wang et al., 2019). Hospital staff must be familiar with troubleshooting and alternative methods of delivering insulin (Yeh et al., 2021). The CL systems may also require endocrinology teams because of these complexities, which may hamper adoption.
A panel of experts was convened by the Diabetes Technology Society in 2016. The goal was to study the situation of CGM use in the hospital. The panel conducted a literature review on CGM use in the ICU, non-ICU, and for transitioning outpatient CGM into inpatient. The panel concluded that CGM had the potential to improve patient outcomes, particularly in the reduction of hypoglycemia. According to Wallia et al. (2017), the use of CGM in the ICU setting may not be feasible, but some populations could benefit from further research, such as patients in the following settings: those receiving insulin particularly intravenously, postcardiac surgery, neonatal ICU, posttransplant patients, and those receiving glucocorticoids (Wallia et al., 2017). Additionally, those with end-stage renal/live disease, vascular or traumatic brain injury and patients with hypoglycemia unawareness fell into the category.
The Diabetes Technology Society organized a virtual seminar in 2020 where they made recommendations on CGMs and automated insulin dosing systems (Galindo, et al., 2020b). According to a review of literature carried out by the panelists, they provided three recommendations regarding the continuation of CGM usage after hospitalization, initiation of CGM usage in hospitals, and continuation of AID technology in hospitals (Galindo, et al., 2020b). They also made recommendations on CGMs and AID systems hands-on care and logistics and finally on CGM and AID systems data management systems.
For the continuation of home CGMs, it was recommended that HCPs consult inpatient diabetes teams and not rely heavily on CGM data for patients with severe hyper/hyperglycemia (Galindo, et al., 2020b). HCPs were also to avoid the continuation of CGM usage in case of skin infection on the site of the sensor. They were also to use a CGM checklist during elective procedures and advise pregnant women to continue using CGMs during hospitalization. Moreover, they were supposed to ask patients to bring with them supplies to the hospital (Galindo, et al., 2020b). Further, HCPs are to check BG measurements after procedures for non-ICU patients and venous blood for ICU patients to ensure the proper functioning of CGMs. HCPs were also to use trend arrows to curtail extreme glycemic events to help establish when a BG test is necessary. HCPs were also to set glycemic targets’ alarm thresholds for both hypo/hyperglycemia, and finally, HCPs are to document CSII and CGM system information into the HER for admissions and elective procedures.
For researchers, it was recommended that they provide additional data to support recommendations on improved outcomes (Galindo, et al., 2020a). Researchers are also to conduct studies that indicate optimum telemetry alert levels for nurse action. Researchers were also to conduct further research on the accuracy of CGMs during pregnancy, labor, delivery, and peripartum periods. Finally, researchers were supposed to study the lag time effect on BG measurements in the hospital. For hospital recommendations, there were recommendations for the development of standard CGM reports and workflows (Galindo, et al., 2020a). Secondly, they were to develop procedures for testing and calibrating equipment and develop CGM notification systems. Finally, hospitals are to develop guidelines for CGM usage for their staff.
In the case study of a 33-year-old man with type 1 diabetes, the patient had been admitted with onset seizures. Due to mental status, swallowing difficulty, and hypoglycemia unawareness, their Omnipod insulin pump had been disconnected with tube feeding initiated (Levitt et al., 2017a). On the fourth day after his tube feeding was disconnected and on days 5, 6, and 7, he experienced low POC glucose levels of 26 and <55 mg/dL, at which point CGM was initiated with the consent of the concerned parties (Levitt et al., 2017a). The family was instructed on how to calibrate the Dexcom G4 device and the threshold set to 80 and 250 mg/dL for hypo/hyperglycemia. No acetaminophen was administered during CGM, nor was MRI/CT scan imaging obtained that would have hindered the DexCom device use. After CGM initiation and 1071 measurements, the mean value was 222 mg/dL, and not once did the values go below 70 mg. The study showed that CGM could be used in an inpatient hospital setting.
With CGM, it becomes possible to obtain real-time BG level trends and prevent hypo and hyperglycemia before clinical symptoms. By 2011, the Endocrine Society had provided guidelines that did not recommend CGM for inpatient hospital settings because of unproven reliability and accuracy (Levitt et al., 2017b). Still, many studies on accuracy and reliability have not been published (Migdal et al., 2020). Providers and patients have been commonly blinded by investigational CGM research in the non-critically ill setting. When retrospectively reviewed, data shows improved hypoglycemia detection in the non-ICU setting, but in the ICU setting, data shows inconsistent results if CGM can enhance glycemic outcomes (Levitt et al., 2017b). The population most likely to benefit from CGM is type 1 diabetes which research has not focused more on.
Longo et al. (2021) carried out a study to investigate the accuracy of CGM in an inpatient setting after the FDA allowed limited use due to COVID-19. They used results from general care units and ICUs. They obtained 808 paired samples from 28 patients, of whom 10 were in the ICU and 28 from the general floor. They determined that CGM can be used in an inpatient hospital setting as an alternative under proper protocols and safeguards.
A study was carried out to investigate the accuracy of CGM in hospitalized patients under radiology. Current standards recommend that CGM devices be removed during radiology as it could potentially interfere with the functioning of the devices. The results showed radiology did not significantly affect the functioning of the CGM devices. Longo et al. (2021) recommend that the removal of devices during radiology could drive up healthcare costs and may be unnecessary.
Scripps Health’s mission is to provide quality and affordable healthcare. They intend to provide superior services in a caring environment while making positive, measurable differences (Scripps Health, 2020). Diabetes is a costly disease that affects every community. As a hospital that prioritizes primary care, diabetes care is of importance. The adoption of better technologies to counter the disease will go a long way in fulfilling its mission and vision.
References
Davis, G. M., Galindo, R. J., Migdal, A. L., & Umpierrez, G. E. (2020). Diabetes Technology in the Inpatient Setting for Management of Hyperglycemia. Endocrinology and metabolism clinics of North America. Web.
Davis, G. M., Spanakis, E. K., Migdal, A. L., Singh, L. G., Albury, B., Urrutia, M. A., Zamudio-Coronado, K. W., Scott, W. H., Doerfler, R., Lizama, S., Satyarengga, M., Munir, K., Galindo, R. J., Vellanki, P., Cardona, S., Pasquel, F. J., Peng, L., & Umpierrez, G. E. (2021). Accuracy of Dexcom G6 Continuous Glucose Monitoring in Non–Critically Ill Hospitalized Patients With Diabetes. Diabetes Care. Web.
Dinh-Le, C., Chuang, R., Chokshi, S., & Mann, D. (2019). Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions. JMIR mHealth and uHealth. Web.
Ehrhardt, N., & Hirsch, I. B. (2020). The Impact of COVID-19 on CGM Use in the Hospital. Diabetes Care. Web.
Faulds, E. R., Jones, L., McNett, M., Smetana, K. S., May, C. C., Sumner, L., Buschur, E., Exline, M., Ringel, M. D., & Dungan, K. (2021, April 27). Facilitators and Barriers to Nursing Implementation of Continuous Glucose Monitoring (CGM) in Critically Ill Patients With COVID-19. Endocrine practice: official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists. Web.
Fortmann, A. L., Bagsic, S. R. S., Talavera, L., Garcia, I. M., Sandoval, H., Hottinger, A., & Philis-Tsimikas, A. (2020). Glucose as the Fifth Vital Sign: A Randomized Controlled Trial of Continuous Glucose Monitoring in a Non-ICU Hospital Setting. Diabetes Care. Web.
Galindo, R. J., Aleppo, G., Klonoff, D. C., Spanakis, E. K., Agarwal, S., Vellanki, P., Olson, D. E., Umpierrez, G. E., Davis, G. M., & Pasquel, F. J. (2020a). Implementation of Continuous Glucose Monitoring in the Hospital: Emergent Considerations for Remote Glucose Monitoring During the COVID-19 Pandemic – Rodolfo J. Galindo, Grazia Aleppo, David C. Klonoff, Elias K. Spanakis, Shivani Agarwal, Priya Vellanki, Darin E. Olson, Guillermo E. Umpierrez, Georgia M. Davis, Francisco J. Pasquel, 2020. SAGE Journals. Web.
Galindo, R. J., Umpierrez, G. E., Rushakoff, R. J., Basu, A., Lohnes, S., Nichols, J. H., Spanakis, E. K., Espinoza, J., Palermo, N. E., Awadjie, D. G., Bak, L., Buckingham, B., Cook, C. B., Freckmann, G., Heinemann, L., Hovorka, R., Mathioudakis, N., Newman, T., O’Neal, D. N., … Klonoff, D. C. (2020b). Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline . SAGE Journals. Web.
Kropff, J., & DeVries, J. H. (2016, February 1). Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects. Diabetes technology & therapeutics. Web.
Laprezez, J., & Woods, A. (2020). Implementing Inpatient Continuous Glucose Monitor Use During COVID-19. U.S. Pharmacist – The Leading Journal in Pharmacy. Web.
Levitt, D. L., Silver, K. D., & Spanakis, E. K. (2017a). Mitigating Severe Hypoglycemia by Initiating Inpatient Continuous Glucose Monitoring for Type 1 Diabetes Mellitus. Journal of diabetes science and technology. Web.
Levitt, D. L., Silver, K. D., & Spanakis, E. K. (2017b). Inpatient Continuous Glucose Monitoring and Glycemic Outcomes. Journal of diabetes science and technology. Web.
Longo, R. R., Elias, H., Khan, M., & Seley, J. J. (2021, May 10). Use and Accuracy of Inpatient CGM During the COVID-19 Pandemic: An Observational Study of General Medicine and ICU Patients . SAGE Journals. Web.
Mhugel. (2021). Dexcom CGM & COVID-19: Information for Hospital Use. Dexcom. Web.
Migdal, A. L., Spanakis, E. K., Galindo, R. J., Davis, G., Singh, L. G., Satyarengga, M., Scott, W. H., Fayfman, M., Pasquel, F. J., Albury, B., Urrutia, M., Zamudio Coronado, K. W., Cardona, S., Peng, L., & Umpierrez, G. E. (2020, November 14). Accuracy and Precision of Continuous Glucose Monitoring in Hospitalized Patients Undergoing Radiology Procedures. Journal of diabetes science and technology. Web.
Rodbard, D. (2016). Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities. Diabetes technology & therapeutics. Web.
Rodbard, D. (2017). Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes. Diabetes technology & therapeutics. Web.
Scripps Health Mission and Values. Scripps Health. (2020). Web.
Wallia, A., Umpierrez, G. E., Rushakoff, R. J., Klonoff, D. C., Rubin, D. J., Hill Golden, S., Cook, C. B., Thompson, B., & DTS Continuous Glucose Monitoring in the Hospital Panel. (2017). Consensus Statement on Inpatient Use of Continuous Glucose Monitoring. Journal of diabetes science and technology. Web.
Wang, M., Singh, L. G., & Spanakis, E. K. (2019). Advancing the Use of CGM Devices in a Non-ICU Setting. Journal of diabetes science and technology. Web.
Yeh, T., Yeung, M., & Mendelsohn Curanaj, F. A. (2021). Managing Patients with Insulin Pumps and Continuous Glucose Monitors in the Hospital: to Wear or Not to Wear. Current diabetes reports. Web.
Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.