This review found that 4 benchmark institutions have done most of the published research on the effects of the electronic health record on medical care. The research shows that electronic health re...

Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

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Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

OBJECTIVE — The A1C assay, expressed as the percent of hemoglobin that is glycated, measures chronic glycemia and is widely used to judge the adequacy of diabetes treatment and adjust therapy. Day-to-day management is guided by self-monitoring of capillary glucose concentrations (milligrams per deciliter or millimoles per liter). We sought to define the mathematical relationship between A1C and average glucose (AG) levels and determine whether A1C could be expressed and reported as AG in the same units as used in self-monitoring. RESEARCH DESIGN AND METHODS — A total of 507 subjects, including 268 patients with type 1 diabetes, 159 with type 2 diabetes, and 80 nondiabetic subjects from 10 international centers, was included in the analyses. A1C levels obtained at the end of 3 months and measured in a central laboratory were compared with the AG levels during the previous 3 months. AG was calculated by combining weighted results from at least 2 days of continuous glucose monitoring performed four times, with seven-point daily self-monitoring of capillary (fingerstick) glucose performed at least 3 days per week. RESULTS — Approximately 2,700 glucose values were obtained by each subject during 3 months. Linear regression analysis between the A1C and AG values provided the tightest correlations (AGmg/dl 28.7 A1C 46.7, R 2 0.84, P 0.0001), allowing calculation of an estimated average glucose (eAG) for A1C values. The linear regression equations did not differ significantly across subgroups based on age, sex, diabetes type, race/ethnicity, or smoking status. CONCLUSIONS — A1C levels can be expressed as eAG for most patients with type 1 and type 2 diabetes. Diabetes Care 31:1473–1478, 2008

/pdf/translating-the-a1c-assay-into-estimated-average-glucose-1cqhxxjqjk.pdf

Translating the A1C Assay Into Estimated Average Glucose Values

Measurement of glycated hemoglobin (HbA1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.

/pdf/international-consensus-on-use-of-continuous-glucose-cnnnkmnod1.pdf

International Consensus on Use of Continuous Glucose Monitoring

Therapeutic drug monitoring (TDM) is the quantification and interpretation of drug concentrations in blood to optimize pharmacotherapy. It considers the interindividual variability of pharmacokinetics and thus enables personalized pharmacotherapy. In psychiatry and neurology, patient populations that may particularly benefit from TDM are children and adolescents, pregnant women, elderly patients, individuals with intellectual disabilities, patients with substance abuse disorders, forensic psychiatric patients or patients with known or suspected pharmacokinetic abnormalities. Non-response at therapeutic doses, uncertain drug adherence, suboptimal tolerability, or pharmacokinetic drug-drug interactions are typical indications for TDM. However, the potential benefits of TDM to optimize pharmacotherapy can only be obtained if the method is adequately integrated in the clinical treatment process. To supply treating physicians and laboratories with valid information on TDM, the TDM task force of the Arbeitsgemeinschaft fur Neuropsychopharmakologie und Pharmakopsychiatrie (AGNP) issued their first guidelines for TDM in psychiatry in 2004. After an update in 2011, it was time for the next update. Following the new guidelines holds the potential to improve neuropsychopharmacotherapy, accelerate the recovery of many patients, and reduce health care costs.

/pdf/consensus-guidelines-for-therapeutic-drug-monitoring-in-18b8y5mu39.pdf

Consensus Guidelines for Therapeutic Drug Monitoring in Neuropsychopharmacology: Update 2017.

Background: Glycohemoglobin (gHb), measured as hemoglobin (Hb) A1c or as total gHb, provides a common means for assessing long-term glycemic control in individuals with diabetes mellitus. Genetic variants and chemically modified derivatives of Hb can profoundly affect the accuracy of these measurements, although effects vary considerably among commercially available methods. The prevalence of genetic variants such as HbS, HbC, and HbE, and chemically modified derivatives such as carbamyl-Hb among patient populations undergoing testing is not insignificant. Clinical laboratories and sites responsible for point-of-care testing of gHb need to be aware of the interferences produced in assays by these Hbs.

Approach: We conducted a review of the literature describing the effects of variant Hbs on gHb assay methods commonly used in clinical laboratories.

Content: This review summarizes the documented effects of both common and uncommon Hb variants and derivatives on the measurement of gHb. Where known, we discuss mechanisms of interference on specific assays and methodologies. We specifically address effects of commonly encountered Hbs, such as carbamyl-Hb, HbS, HbC, HbE, and HbF, on assays that use cation-exchange chromatography, immunoassays, or boronate affinity methods for measuring gHb.

Summary: A variety of patient- and laboratory-related factors can adversely affect the measurement of gHb in patients harboring Hb variants or derivatives. Identification of the variant or derivative Hb before or during testing may allow accurate measurement of gHb by the selection of a method unaffected by the given variant or derivative. However, laboratories should make available alternative, non-Hb-based methods for assessing long-term glycemic control in individuals with HbCC, HbSS, or HbSC disease, or with other underlying disorders where the concentration of gHb does not accurately reflect long-term glycemic control.

/pdf/effects-of-hemoglobin-variants-and-chemically-modified-31f6k684bx.pdf

Effects of Hemoglobin Variants and Chemically Modified Derivatives on Assays for Glycohemoglobin

We established criteria for appropriate use of the prostate-specific antigen (PSA) assay and used them to evaluate PSA test utilization at 1 tertiary care institution. During a 6-month period, 2,330 PSA results were reported for outpatients and 95 for inpatients. We reviewed medical records for a random sample of 338 outpatient results (14.51%) and all 95 inpatient results, of which 21% (71/338) of outpatient and 17% (16/95) of inpatient results were inappropriate according to our test utilization criteria. Among outpatients, 52% of tests were done for screening and 19% for monitoring for cancer recurrence. For inpatients, workup for cancer (53/95 [56%]) was the most frequent indication for testing and screening the second (24/95 [25%]). Of tests failing the criteria, 66 (76%) of 87 resulted from excessively frequent and age-inappropriate screening. We assessed the potential effect on clinical outcome if these tests were not performed. Of the 87 tests considered inappropriate, only 1 test result influenced clinical management for patients younger than 75 years. By instituting simple limits on age and frequency, we estimate that 74% (64/87) of the inappropriate tests could have been eliminated.

Appropriateness of prostate-specific antigen testing.

Use of Serum Cardiac Troponin-I Levels in Dialysis Patients

Development of specific monoclonal antibodies and a sensitive discriminatory immunoassay for the circulating tumor markers SCCA1 and SCCA2.

We designed and implemented 2 automated, computerized screens for use at the time of antiepileptic drug (AED) test order entry to improve appropriateness by reminding physicians when a potentially redundant test was ordered and providing common indications for monitoring and pharmacokinetics of the specific AED. All computerized orders for inpatient serum AED levels during two 3-month periods were included in the study. During the 3-month period after implementation of the automated intervention, 13% of all AED tests ordered were canceled following computerized reminders. For orders appearing redundant, the cancellation rate was 27%. For nonredundant orders, 4% were canceled when information on specific AED monitoring and pharmacokinetics was provided. The cancellation rate was sustained after 4 years. There has been a 19.5% decrease in total AED testing volume since implementation of this intervention, despite a 19.3% increase in overall chemistry test volume. Inappropriateness owing to repeated testing before pharmacologic steady state was reached decreased from 54% of all AED orders to 14.6%. A simple, automated, activity-based intervention targeting a specific test-ordering behavior effectively reduced inappropriate laboratory testing. The sustained benefit supports the idea that computerized interventions may durably affect physician behavior. Computerized delivery of such evidence-based boundary guidelines can help narrow the gap between evidence and practice.

A computer-based intervention for improving the appropriateness of antiepileptic drug level monitoring

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