Performance comparison of 6 in-hospital patient monitoring systems in the detection and alarm of ventricular cardiac arrhythmias.

Background: Patient monitoring devices are critical for alerting of potential cardiac arrhythmias during hospitalization; however, there are concerns of alarm fatigue due to high false alarm rates. Objective: The purpose of this study was to evaluate the sensitivity and false alarm rate of hospital-based continuous electrocardiographic (ECG) monitoring technologies. Methods: Six commonly used multiparameter bedside monitoring systems available in the United States were evaluated: B125M (GE HealthCare), ePM10 and iPM12 (Mindray), Efficia and IntelliVue (Philips), and Life Scope (Nihon Kohden). Sensitivity was tested using ECG recordings containing 57 true ventricular tachycardia (VT) events. False-positive rate testing used 205 patient-hours of ECG recordings containing no cardiac arrhythmias. Signals from ECG recordings were fed to devices simultaneously; high-severity arrhythmia alarms were tracked. Sensitivity to true VT events and false-positive rates were determined. Differences were assessed using Fisher exact tests (sensitivity) and Z-tests (false-positive rates). Results: B125M raised 56 total alarms for 57 annotated VT events and had the highest sensitivity (98%; P <.05), followed by iPM12 (84%), Life Scope (81%), Efficia (79%), ePM10 (77%), and IntelliVue (75%). B125M raised 20 false alarms, which was significantly lower (P <.0001) than iPM12 (284), Life Scope (292), IntelliVue (304), ePM10 (324), and Efficia (493). The most common false alarm was VT, followed by nonsustained VT. Conclusion: We found significant performance differences among multiparameter bedside ECG monitoring systems using previously collected recordings. B125M had the highest sensitivity in detecting true VT events and lowest false alarm rate. These results can assist in minimizing alarm fatigue and optimizing patient safety by careful selection of in-hospital continuous monitoring technology.

Predictors of ECG Interpretation Proficiency in Healthcare Professionals.

Accurate ECG interpretation is vital, but variations in skills exist among healthcare professionals. This study aims to identify factors contributing to ECG interpretation proficiency. Survey data and ECG interpretation test scores from participants in the EDUCATE Trial were analyzed to identify predictors of performance for 30 sequential 12-lead ECGs. Nonmodifiable factors (being a physician, clinical experience, patient care impact) and modifiable factors (weekly interpretation volume, training hours, expert supervision frequency) were analyzed. Bivariate and multivariate analyses were used to generate a Comprehensive Model (incorporating all factors) and Actionable Model (incorporating modifiable factors only). Among 1206 participants analyzed, there were 72 (6.0%) primary care physicians, 146 (12.1%) cardiology fellows-in-training, 353 (29.3%) resident physicians, 182 (15.1%) medical students, 84 (7.0%) advanced practice providers, 120 (9.9%) nurses, and 249 (20.7%) allied health professionals. Among them, 571 (47.3%) were physicians and 453 (37.6%) were nonphysicians. The average test score was 56.4% ± 17.2%. Bivariate analysis demonstrated significant associations between test scores and >10 weekly ECG interpretations, being a physician, >5 training hours, patient care impact, and expert supervision but not clinical experience. In the Comprehensive Model, independent associations were found with weekly interpretation volume (9.9 score increase; 95% CI, 7.9-11.8; P < 0.001), being a physician (9.0 score increase; 95% CI, 7.2-10.8; P < 0.001), and training hours (5.7 score increase; 95% CI, 3.7-7.6; P < 0.001). In the Actionable Model, scores were independently associated with weekly interpretation volume (12.0 score increase; 95% CI, 10.0-14.0; P < 0.001) and training hours (4.7 score increase; 95% CI, 2.6-6.7; P < 0.001). The Comprehensive and Actionable Models explained 18.7% and 12.3% of the variance in test scores, respectively. Predictors of ECG interpretation proficiency include nonmodifiable factors like physician status and modifiable factors such as training hours and weekly ECG interpretation volume.

Impact of Computer-Interpreted ECGs on the Accuracy of Healthcare Professionals.

The interpretation of electrocardiograms (ECGs) involves a dynamic interplay between computerized ECG interpretation (CEI) software and human overread. However, the impact of computer ECG interpretation on the performance of healthcare professionals remains largely unexplored. The aim of this study was to evaluate the interpretation proficiency of various medical professional groups, with and without access to the CEI report. Healthcare professionals from diverse disciplines, training levels, and countries sequentially interpreted 60 standard 12-lead ECGs, demonstrating both urgent and nonurgent findings. The interpretation process consisted of 2 phases. In the first phase, participants interpreted 30 ECGs with clinical statements. In the second phase, the same 30 ECGs and clinical statements were randomized and accompanied by a CEI report. Diagnostic performance was evaluated based on interpretation accuracy, time per ECG (in seconds [s]), and self-reported confidence (rated 0 [not confident], 1 [somewhat confident], or 2 [confident]). A total of 892 participants from various medical professional groups participated in the study. This cohort included 44 (4.9%) primary care physicians, 123 (13.8%) cardiology fellows-in-training, 259 (29.0%) resident physicians, 137 (15.4%) medical students, 56 (6.3%) advanced practice providers, 82 (9.2%) nurses, and 191 (21.4%) allied health professionals. The inclusion of the CEI was associated with a significant improvement in interpretation accuracy by 15.1% (95% confidence interval, 14.3-16.0; P < 0.001), decrease in interpretation time by 52 s (-56 to -48; P < 0.001), and increase in confidence by 0.06 (0.03-0.09; P = 0.003). Improvement in interpretation accuracy was seen across all professional subgroups, including primary care physicians by 12.9% (9.4-16.3; P = 0.003), cardiology fellows-in-training by 10.9% (9.1-12.7; P < 0.001), resident physicians by 14.4% (13.0-15.8; P < 0.001), medical students by 19.9% (16.8-23.0; P < 0.001), advanced practice providers by 17.1% (13.3-21.0; P < 0.001), nurses by 16.2% (13.4-18.9; P < 0.001), allied health professionals by 15% (13.4-16.6; P < 0.001), physicians by 13.2% (12.2-14.3; P < 0.001), and nonphysicians by 15.6% (14.3-17.0; P < 0.001).CEI integration improves ECG interpretation accuracy, efficiency, and confidence among healthcare professionals.

Exploring Factors Influencing ECG Interpretation Proficiency of Medical Professionals.

The electrocardiogram (ECG) is a crucial diagnostic tool in medicine with concerns about its interpretation proficiency across various medical disciplines. Our study aimed to explore potential causes of these issues and identify areas requiring improvement. A survey was conducted among medical professionals to understand their experiences with ECG interpretation and education. A total of 2515 participants from diverse medical backgrounds were surveyed. A total of 1989 (79%) participants reported ECG interpretation as part of their practice. However, 45% expressed discomfort with independent interpretation. A significant 73% received less than 5 hours of ECG-specific education, with 45% reporting no education at all. Also, 87% reported limited or no expert supervision. Nearly all medical professionals (2461, 98%) expressed a desire for more ECG education. These findings were consistent across all groups and did not vary between primary care physicians, cardiology FIT, resident physicians, medical students, APPs, nurses, physicians, and nonphysicians. This study reveals substantial deficiencies in ECG interpretation training, supervision, and confidence among medical professionals, despite a strong interest in increased ECG education.

Cost savings through continuous vital sign monitoring in the medical-surgical unit.

OBJECTIVE: This study aimed to determine the potential cost-savings for implementing continuous vital sign monitoring in a hospital's medical-surgical units. METHODS: A cost-savings analysis was designed to calculate potential cost-savings for an average-sized U.S. community hospital (153 total beds) over a 1-year time horizon. Analysis parameters were extracted from national databases and previous studies that compared outcomes for patients receiving continuous vital sign monitoring (SpO2, HR, and RR) or standard of care (intermittent vital sign measurements) in medical-surgical units based on a targeted literature review. Clinical parameters and associated costs served as analysis inputs. The analysis outputs were costs and potential cost-savings using a 50% and 100% adoption rate of continuous monitoring technologies across the medical-surgical unit. RESULTS: Potential annual cost-savings for in-hospital medical-surgical stays were estimated at $3,414,709 (2022 USD) and $6,829,418 for a 50% and 100% adoption rate, respectively. The cost-savings for an adoption rate of 100% equated to a ∼14% reduction in the overall annual cost of medical-surgical unit stays for an average-sized hospital. The largest contribution to potential cost-savings came from patients that avoided serious adverse events that require transfer to the intensive care unit; this resulted in annual cost-savings from reduced average length of stay between $1,756,613 and $3,513,226 (50% and 100% adoption rate, respectively). Additional cost-savings can be attained from reductions in in-hospital cardiac arrest-associated hospitalizations and decreased rapid response team activation. CONCLUSIONS: Our findings demonstrate that there is the potential for cost-savings of over $6.8 million dollars per year in an average-sized US community hospital by improving patient outcomes through implementation of continuous monitoring technologies in medical-surgical units. Continuous vital sign monitoring technologies that increase patient mobility and facilitate recovery may further contribute to cost-savings and should be considered for economic analyses. Future research is needed to explore these health-related outcomes.

Impact of Patient-Controlled Analgesia (PCA) Smart Pump-Electronic Health Record (EHR) Interoperability with Auto-Documentation on Chart Completion in a Community Hospital Setting.

INTRODUCTION: Complete and accurate documentation of opioids administered by patient-controlled analgesia (PCA) pumps is critical for ensuring a high-quality medication record and an accurate conversion of the intravenous (IV) regimen to oral therapy. Incomplete charting of PCA usage through a manual process may be associated with fragmented documentation of delivered therapy affecting the completeness of the medical record and the IV to oral dose conversion. This study is the first to evaluate the association between auto-documentation of opioid administration provided by PCA smart pump-electronic health record (EHR) interoperability and the completion of PCA opioid administration charting tasks. METHODS: This retrospective cohort study was conducted at Lancaster General Hospital, Lancaster, Pennsylvania. Patients were assigned to pre-auto-documentation (n = 55) or post-auto-documentation groups (n = 58) based on whether they received PCA therapy prior to or after PCA-EHR interoperability was implemented. Charting of PCA therapy included documentation of the number of patient attempts, number of doses given, and total volume infused for both pre- and post-auto-documentation groups. In addition, total dose delivered was documented for the post-auto-documentation group. The overall chart-field completion rate was evaluated as the primary outcome. Individual chart completion percentages were assessed by stratified groups as secondary outcomes. RESULTS: PCA smart pump-EHR interoperability with auto-documentation was associated with an increase in overall chart-field completion rate from 69.9 to 97.0% (p < 0.001). Auto-documentation was also associated with an increase in fully completed charts from 38 to 91% (139.3% increase, p < 0.001) and reductions of incomplete records in each stratified group (p < 0.001). CONCLUSIONS: PCA smart pump-EHR interoperability with auto-documentation is associated with significant improvements in the completion of opioid administration chart-fields. Improved documentation of PCA administered opioids may have implications for the safety of opioid administration. Additional studies will be needed to assess the potential clinical impact of these results. FUNDING: ICU Medical, Inc.

Smart Pump-Electronic Health Record (EHR) Interoperability with Auto-Documentation is Associated with Increased Submission of Infusion-Therapy Billing Claims at a Community Hospital.

BACKGROUND: Smart pump-electronic health record (EHR) interoperability has been demonstrated to reduce adverse events and increase documentation and billing accuracy. However, relatively little is known about the impact of interoperability on infusion therapy billing claims and hospital finances. OBJECTIVE: Our objective was to evaluate the association between smart pump-EHR interoperability with auto-documentation and current procedural terminology (CPT®)-coded infusion-therapy billing claims submissions. METHODS: At Penn Medicine Lancaster General Health (Lancaster, PA, USA), infusion-therapy billing data were collected for 158,379 patient days (a visit to the emergency department [ED] or 24 h admission to a non-ED unit) and divided into two groups: 78,241 pre- and 80,138 post-auto-documentation. The count and types of submitted CPT-coded claims were analyzed for ED/non-ED groups, inpatient/outpatient status and non-ED unit where the infusion was administered. Dollar amounts for CPT codes were calculated using Medicare Addendum B 2017. Patient day and CPT code counts were converted to annualized values to facilitate analysis. RESULTS: Patient days did not increase significantly from pre- to post-auto-documentation, whereas annualized submitted CPT-coded claims increased significantly by 14.5% (p < 0.001). The corresponding billing claim dollar value increased by $US1,147,652 (13.5%). ED patient days increased by 2.0% (p = 0.44), whereas submitted CPT-coded claims increased significantly by 4.0% (p < 0.001) and $US478,980 (7.4%). Non-ED patient days increased by 2.8% (p = 0.2), whereas CPT-coded claims increased significantly by 31.7% (p < 0.001) and $US668,672 (34.0%). The total number of submitted CPT-coded claims increased by 13.4% for inpatients and 12.3% for outpatients. CONCLUSION: Our findings suggest that auto-documentation of infusion-therapy services may have a positive impact on hospital financial performance, which could help drive adoption of this technology.