Impact of Embedding a Venous Thromboembolism Risk Assessment Model in the Electronic Health Record Versus Usual Care: A Cluster-Randomized Trial.

BACKGROUND: There are multiple risk assessment models (RAMs) for venous thromboembolism prophylaxis, but it is unknown whether they increase appropriate prophylaxis. METHODS: To determine the impact of a RAM embedded in the electronic health record, we conducted a stepped-wedge hospital-level cluster-randomized trial conducted from October 1, 2017 to February 28, 2019 at 10 Cleveland Clinic hospitals. We included consecutive general medical patients aged 18 years or older. Patients were excluded if they had a contraindication to prophylaxis, including anticoagulation for another condition, acute bleeding, or comfort-only care. A RAM was embedded in the general admission order set and physicians were encouraged to use it. The decisions to use the RAM and act on the results were reserved to the treating physician. The primary outcome was the percentage of patients receiving appropriate prophylaxis (high-risk patients with pharmacological thromboprophylaxis plus low-risk patients without prophylaxis) within 48 hours of hospitalization. Secondary outcomes included total patients receiving prophylaxis, venous thromboembolism among high-risk patients at 14 and 45 days, major bleeding, heparin-induced thrombocytopenia, and length of stay. Mixed-effects models were used to analyze the study outcomes. RESULTS: A total of 26 506 patients (mean age, 61; 52% female; 73% White) were analyzed, including 11 134 before and 15 406 after implementation of the RAM. After implementation, the RAM was used for 24% of patients, and the percentage of patients receiving appropriate prophylaxis increased from 43.1% to 48.8% (adjusted odds ratio, 1.11 [1.00-1.23]), while overall prophylaxis use decreased from 73.5% to 65.2% (adjusted odds ratio, 0.87 [0.78-0.97]). Rates of venous thromboembolism among high-risk patients (adjusted odds ratio, 0.72 [0.38-1.36]), rates of bleeding and heparin-induced thrombocytopenia (adjusted odds ratio, 0.19 [0.02-1.47]), and length of stay were unchanged. CONCLUSIONS: Implementation of a RAM for venous thromboembolism increased appropriate prophylaxis use, but the RAM was used for a minority of patients. REGISTRATION: URL: https://www.clinicaltrials.gov/study/NCT03243708?term=nct03243708&rank=1; Unique identifier: NCT03243708.

Assisted ambulation to improve health outcomes for older medical inpatients (AMBULATE): study protocol for a randomized controlled trial.

BACKGROUND: Hospitalized older adults spend as much as 95% of their time in bed, which can result in adverse events and delay recovery while increasing costs. Observational studies have shown that general mobility interventions (e.g., ambulation) can mitigate adverse events and improve patients' functional status. Mobility technicians (MTs) may address the need for patients to engage in mobility interventions without overburdening nurses. There is no data, however, on the effect of MT-assisted ambulation on adverse events or functional status, or on the cost tradeoffs if a MT were employed. The AMBULATE study aims to determine whether MT-assisted ambulation improves mobility status and decreases adverse events for older medical inpatients. It will also include analyses to identify the patients that benefit most from MT-assisted mobility and assess the cost-effectiveness of employing a MT. METHODS: The AMBULATE study is a multicenter, single-blind, parallel control design, individual-level randomized trial. It will include patients admitted to a medical service in five hospitals in two regions of the USA. Patients over age 65 with mild functional deficits will be randomized using a block randomization scheme. Those in the intervention group will ambulate with the MT up to three times daily, guided by the Johns Hopkins Mobility Goal Calculator. The intervention will conclude at hospital discharge, or after 10 days if the hospitalization is prolonged. The primary outcome is the Short Physical Performance Battery score at discharge. Secondary outcomes are discharge disposition, length of stay, hospital-acquired complications (falls, venous thromboembolism, pressure ulcers, and hospital-acquired pneumonia), and post-hospital functional status. DISCUSSION: While functional decline in the hospital is multifactorial, ambulation is a modifiable factor for many patients. The AMBULATE study will be the largest randomized controlled trial to test the clinical effects of dedicating a single care team member to facilitating mobility for older hospitalized patients. It will also provide a useful estimation of cost implications to help hospital administrators assess the feasibility and utility of employing MTs. TRIAL REGISTRATION: Registered in the United States National Library of Medicine clinicaltrials.gov (# NCT05725928). February 13, 2023.

Patient, Operator, and Procedural Characteristics of Guidewire Retention as a Complication of Vascular Catheter Insertion.

Guidewire retention after intravascular catheter insertion is considered a "never event." Prior reports attribute this complication to various characteristics including uncooperative patients, operator inexperience, off-hour or emergent insertion, and underutilization of ultrasound guidance. In this descriptive analysis of consecutive events, we assessed the frequency of patient, operator, and procedural factors in guidewire retention. DESIGN: Pre-specified observational analysis as part of a quality improvement study of consecutive guidewire retention events across a multihospital health system from August 2007 to October 2015. SETTING: Ten hospitals within the Cleveland Clinic Health System in Ohio, United States. PATIENTS: Consecutive all-comers who experienced guidewire retention after vascular catheter insertion. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Data were manually obtained from the electronic medical records and reviewed for potential contributing factors for guidewire retention, stratified into patient, operator, and procedural characteristics. A total of 24 events were identified. Overall, the median age was 74 years, 58% were males, and the median body mass index was 26.5 kg/m2. A total of 12 (50%) individuals were sedated during the procedure. Most incidents (10 [42%]) occurred in internal jugular venous access sites. The majority of cases (13 [54%]) were performed or supervised by an attending. Among all cases, three (12%) were performed by first-year trainees, seven (29%) by residents, three (12%) by fellows, and four (17%) by certified nurse practitioners. Overall, 16 (67%) events occurred during regular working hours (8 amto 5 pm). In total, 22 (92%) guidewires were inserted nonemergently, with two (8%) during a cardiac arrest. Ultrasound guidance was used in all but one case. CONCLUSIONS: Guidewire retention can occur even in the presence of optimal patient, operator, and procedural circumstances, highlighting the need for constant awareness of this risk. Efforts to eliminate this important complication will require attention to issues surrounding the technical performance of the procedure.

Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study.

BACKGROUND: Driven by quality outcomes and economic incentives, predicting 30-day hospital readmissions remains important for healthcare systems. The Cleveland Clinic Health System (CCHS) implemented an internally validated readmission risk score in the electronic medical record (EMR). OBJECTIVE: We evaluated the predictive accuracy of the readmission risk score across CCHS hospitals, across primary discharge diagnosis categories, between surgical/medical specialties, and by race and ethnicity. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult patients discharged from a CCHS hospital April 2017-September 2020. MAIN MEASURES: Data was obtained from the CCHS EMR and billing databases. All patients discharged from a CCHS hospital were included except those from Oncology and Labor/Delivery, patients with hospice orders, or patients who died during admission. Discharges were categorized as surgical if from a surgical department or surgery was performed. Primary discharge diagnoses were classified per Agency for Healthcare Research and Quality Clinical Classifications Software Level 1 categories. Discrimination performance predicting 30-day readmission is reported using the c-statistic. RESULTS: The final cohort included 600,872 discharges from 11 Northeast Ohio and Florida CCHS hospitals. The readmission risk score for the cohort had a c-statistic of 0.6875 with consistent yearly performance. The c-statistic for hospital sites ranged from 0.6762, CI [0.6634, 0.6876], to 0.7023, CI [0.6903, 0.7132]. Medical and surgical discharges showed consistent performance with c-statistics of 0.6923, CI [0.6807, 0.7045], and 0.6802, CI [0.6681, 0.6925], respectively. Primary discharge diagnosis showed variation, with lower performance for congenital anomalies and neoplasms. COVID-19 had a c-statistic of 0.6387. Subgroup analyses showed c-statistics of > 0.65 across race and ethnicity categories. CONCLUSIONS: The CCHS readmission risk score showed good performance across diverse hospitals, across diagnosis categories, between surgical/medical specialties, and by patient race and ethnicity categories for 3 years after implementation, including during COVID-19. Evaluating clinical decision-making tools post-implementation is crucial to determine their continued relevance, identify opportunities to improve performance, and guide their appropriate use.

Derivation and Validation of a Risk Factor Model to Identify Medical Inpatients at Risk for Venous Thromboembolism.

BACKGROUND: Venous thromboembolism (VTE) prophylaxis is recommended for hospitalized medical patients at high risk for VTE. Multiple risk assessment models exist, but few have been compared in large datasets. METHODS: We constructed a derivation cohort using 6 years of data from 12 hospitals to identify risk factors associated with developing VTE within 14 days of admission. VTE was identified using a complex algorithm combining administrative codes and clinical data. We developed a multivariable prediction model and applied it to three validation cohorts: a temporal cohort, including two additional years, a cross-validation, in which we refit the model excluding one hospital each time, applying the refitted model to the holdout hospital, and an external cohort. Performance was evaluated using the C-statistic. RESULTS: The derivation cohort included 155,026 patients with a 14-day VTE rate of 0.68%. The final multivariable model contained 13 patient risk factors. The model had an optimism corrected C-statistic of 0.79 and good calibration. The temporal validation cohort included 53,210 patients, with a VTE rate of 0.64%; the external cohort had 23,413 patients and a rate of 0.49%. Based on the C-statistic, the Cleveland Clinic Model (CCM) outperformed both the Padua (0.76 vs. 0.72, p = 0.002) and IMPROVE (0.68, p < 0.001) models in the temporal cohort. C-statistics for the CCM at individual hospitals ranged from 0.68 to 0.78. In the external cohort, the CCM C-statistic was similar to Padua (0.70 vs. 0.66, p = 0.17) and outperformed IMPROVE (0.59, p < 0.001). CONCLUSION: A new VTE risk assessment model outperformed recommended models.

Association between limiting the number of open records in a tele-critical care setting and retract-reorder errors.

BACKGROUND: Wrong patient selection errors may be tracked by retract-reorder (RAR) events. The aim of this quality improvement study was to assess the impact of reducing the number of concurrently open electronic health records from 4 to 2 on RAR errors generated by a tele-critical care service. METHODS: The study encompassed 32 months before and 21 months after restriction. Chi-Square test of proportions and T statistical process control chart for rare events were used. RESULTS: There were 156 318 orders with 57 RAR errors (36.5/100 000 orders) before restriction, and 122 587 orders with 34 errors (27.7/100 000 orders) after. Rates were not statistically different (P = .20), but analysis was underpowered. When plotted on a T control chart, random variation was detected between RAR errors. CONCLUSION: We found no significant difference in RAR errors in the tele-critical care setting after open record limitation. Other strategies should be studied to reduce wrong patient selection errors.

Clinical Characteristics and Outcomes of Non-ICU Hospitalization for COVID-19 in a Nonepicenter, Centrally Monitored Healthcare System.

BACKGROUND: The clinical characteristics and outcomes associated with non-intensive care unit (non-ICU) hospitalizations for coronavirus disease 2019 (COVID-19) outside disease epicenters remain poorly characterized. METHODS: Systematic analysis of all non-ICU patient hospitalizations for COVID-19 completing discharge between March 13 and May 1, 2020, in a large US health care system utilizing off-site central monitoring. Variables of interest were examined in relation to a composite event rate of death, ICU transfer, or increased oxygen requirement to high-flow nasal cannula, noninvasive ventilation, or mechanical ventilation. RESULTS: Among 350 patients (age, 64 ± 16 years; 55% male), most (73%) required 3 L/min or less of supplemental oxygen during admission. Telemetry was widely utilized (79%) yet arrhythmias were uncommon (14%) and were predominantly (90%) among patients with abnormal troponin levels or known cardiovascular disease. Ventricular tachycardia was rare (5%), nonsustained, and not associated with hydroxychloroquine/azithromycin treatment. Adverse events occurred in 62 patients (18%), including 22 deaths (6%), 48 ICU transfers (14%), and 49 patients with increased oxygen requirement (14%) and were independently associated with elevated C-reactive protein (odds ratio, 1.09 per 1 mg/dL; 95% CI, 1.01-1.18; P = .04) and lactate dehydrogenase (OR, 1.006 per 1U/L; 95% CI, 1.001-1.012; P = .03) in multivariable analysis. CONCLUSION: Among non-critically ill patients hospitalized within a nonepicenter health care system, overall survival was 94% with the development of more severe illness or death independently associated with higher levels of C-reactive protein and lactate dehydrogenase on admission. Clinical decompensation was largely respiratory-related, while serious cardiac arrhythmias were rare, which suggests that telemetry can be prioritized for high-risk patients.

Limiting the number of open charts does not impact wrong patient order entry in the emergency department.

OBJECTIVE: We sought to examine the impact of limiting the number of open active charts on wrong patient order entry events among 13 emergency departments (EDs) in a large integrated health system. METHODS: A retrospective chart review of all orders placed between September 2017 and September 2019 was conducted. The rate of retract and reorder events was analyzed with no overlap in both the period pre- and post-intervention period. Secondary analysis of error rate by clinician type, clinician patient load, and time of day was performed. RESULTS: The order retraction rate was not improved pre- and post-intervention. Retraction rates varied by clinician type with residents retracting more often than physicians (odds ratio [OR] = 1.443 [1.349, 1.545]). Advanced practice providers also showed a slightly higher rate than physicians (OR = 1.114 [1.071, 1.160]). Pharmacists showed very low rates compared to physicians (OR = 0.191 [0.048, 0.764]). Time of day and staffing ratios appear to be a factor with wrong patient order entry rates slightly lower during the night (1900-0700) than the day (OR 0.958 [0.923, 0.995]), and increasing slightly with every additional patient per provider (OR 1.019 [1.005, 1.032]). The Academic Medical Center had more retractions that the other EDs. OR for the various ED types compared to the Academic Medical Center included Community (OR 0.908 [0.859, 0.959]), Teaching Hospitals (OR 0.850 [0.802, 0.900]), and Freestanding (OR 0.932 [0.864, 1.006]). CONCLUSIONS: Limiting the number of open active charts from 4 to 2 did not significantly reduce the incidence of wrong patient order entry. Further investigation into other factors contributing to order entry errors is warranted.

Indication-specific event rates among hospitalized patients undergoing continuous cardiac monitoring.

BACKGROUND: Cardiac telemetry monitoring is widely utilized for a variety of clinical indications, yet indication-specific event rates for monitored patients are seldomly reported. HYPOTHESIS: High-risk hospitalized patients for clinical deterioration can be identified using standardized telemetry monitoring indications. METHODS: Adjudicated data from events triggering emergency response team (ERT) activation were systematically characterized at the Cleveland Clinic from among standardized telemetry indications ordered over a 13-month period. RESULTS: Among 72 199 orders created for telemetry monitored patients, ERT activation occurred in 2677 patients (3.7%), of which 1326 (49.5%) were cardiac-related. Patients with deep venous thrombosis or pulmonary embolism (DVT/PE) demonstrated the highest overall event rate (ERT: n = 41 of 593 pts [6.9%]; 25/41 cardiac related [61%]). Cardiac-related events were proportionally highest among patients with coronary disease awaiting revascularization (ERT: n = 19 of 847 patients [2.2%]; 13/19 cardiac-related [68.4%]). Arrhythmia-specific events were highest among patients who underwent cardiac surgery (n = 78 of 193 cardiac-related ERT [40.4%]), and patients with known or suspected tachyarrhythmias (n = 318 of 788 cardiac-related ERT [40.4%]). Bubble plot analysis identified patients hospitalized with DVT/PE, drug or alcohol exposures, and acute coronary syndrome as among the highest overall and cardiac-related events while identifying patients with respiratory disorder monitoring indications as carrying the highest noncardiac event rate. CONCLUSION: High-risk hospitalized patients can be identified by telemetry indication and prioritized according to concerns for cardiac, arrhythmia-specific and noncardiac clinical deterioration. This is particularly useful when monitored bed resources are constrained.

Increasing Mobility via In-hospital Ambulation Protocol Delivered by Mobility Technicians: A Pilot Randomized Controlled Trial.

BACKGROUND: Ambulating medical inpatients may improve outcomes, but this practice is often overlooked by nurses who have competing clinical duties. OBJECTIVE: This study aimed to assess the feasibility and effectiveness of dedicated mobility technician-assisted ambulation in older inpatients. DESIGN: This study was a single-blind randomized controlled trial. SETTING: Patients aged ≥60 years and admitted as medical inpatients to a tertiary care center were recruited. INTERVENTION: Patients were randomized into two groups to participate in the ambulation protocol administered by a dedicated mobility technician. Usual care patients were not seen by the mobility technician but were not otherwise restricted in their opportunity to ambulate. MEASUREMENTS: Primary outcomes were length of stay and discharge disposition. Secondary outcomes included change in mobility measured by six-clicks score, daily steps measured by Fitbit, and 30-day readmission. RESULTS: Control (n = 52) and intervention (n = 50) groups were not significantly different at baseline. Of patients randomized to the intervention group, 74% participated at least once. Although the intervention did not affect the primary outcomes, the intervention group took nearly 50% more steps than the control group (P = .04). In the per protocol analysis, the six-clicks score significantly increased (P = .04). Patients achieving ≥400 steps were more likely to go home (71% vs 46%, P = .01). CONCLUSIONS: Attempted ambulation three times daily overseen by a dedicated mobility technician was feasible and increased the number of steps taken. A threshold of 400 steps was predictive of home discharge. Further studies are needed to establish the appropriate step goal and the effect of assisted ambulation on hospital outcomes.

Feasibility and Usability of Patch-based Continuous Cardiac Rhythm Monitoring in Comparison with Traditional Telemetry in Noncritically Ill Hospitalized Patients.

Research on traditional cardiac telemetry demonstrates that excessive alarms are related to lead failures and noise-related interruptions. Patch-based continuous cardiac rhythm monitoring (CCRM) has emerged in outpatient ambulatory monitoring situations as a means to improve recording fidelity. In this study, patients hospitalized but not in the intensive care unit were simultaneously monitored via telemetry in parallel with the use of the Vital Signs Patch™ (VSP) CCRM system (LifeWatch Services, Rosemont, IL, USA), applying standardized monitoring and notifications provided by an off-site central monitoring unit (CMU). Among 11 patients (55% male; age: 66.8 ± 12.5 years), there were 42 CMU detections and 98 VSP detections. The VSP device was successfully applied by nursing with connectivity established in all 11 patients (100%). There were no VSP device-related adverse events or skin eruptions during the study. The CMU agreed with 59 (60%) of 98 VSP detections. Among those detections marked by disagreement 30 (77%) of 39 VSP detections were related to clinically meaningful arrhythmias (atrial: n = 9; ventricular: n = 7; brady-: n = 14) undetected by VSP due to noise. In two patients (18%), there were four clinically meaningful atrial fibrillation detections not recorded by the CMU. In conclusion, patch-based CCRM requires further development and review to replace traditional cardiac telemetry monitoring but could evolve into an appropriate method to detect clinically meaningful events missed by traditional methods if noise issues can be mitigated.

Quantifying the defensive medicine contribution to primary care costs.

BACKGROUND: Defensive medicine represents one cause of economic losses in healthcare. Studies that measured its cost have produced conflicting results. OBJECTIVE: To directly measure the proportion of primary care costs attributable to defensive medicine. RESEARCH DESIGN AND METHODS: Six-week prospective study of primary care physicians from four outpatient practices. On 3 distinct days, participants were asked to rate each order placed the day before on the extent to which it represented defensive medicine, using a 5-point scale from 0 (not at all defensive) to 4 (entirely defensive). MAIN OUTCOME MEASURES: This study calculated the order defensiveness score for each order (the defensiveness/4) and the physician defensive score (the mean of all orders defensiveness scores). Each order was assigned a weighted cost by multiplying the total cost of that order (based on Medicare reimbursement rates) by the order defensiveness score. The proportion of total cost attributable to defensive medicine was calculated by dividing the weighted cost of defensive orders by the total cost of all orders. RESULTS: Of 50 eligible physicians, 23 agreed to participate; 21 returned the surveys and rated 1234 individual orders on 347 patients. Physicians wrote an average of 3.6 ± 1.0 orders/visit with an associated total cost of $72.60 ± 18.5 per order. Across physicians, the median physician defensive score was 0.018 (IQR = [0.008, 0.049]) and the proportion of costs attributable to defensive medicine was 3.1% (IQR = [0.5%, 7.2%]). Physicians with defensive scores above vs below the median had a similar number of orders and total costs per visit. Physicians were more likely to place defensive orders if trained in community hospitals vs academic centers (OR = 4.29; 95% CI = 1.55-11.86; p = 0.01). CONCLUSIONS: This study describes a new method to directly quantify the cost of defensive medicine. Defensive medicine appears to have minimal impact on primary care costs.

A PDZ domain-based assay for measuring HIV protease activity: assay design considerations.

We have recently described a biochemical detection method for peptide products of enzymatic reactions based on the formation of PDZ domain*peptide ligand complexes. The product sensor is based on using masked or cryptic PDZ domain peptide ligands as enzyme substrates. Upon enzymatic processing, a PDZ-binding motif is exposed, and the product sequence bound specifically by a Eu(3+)chelate-labeled GST-PDZ ([Eu(3+)]GST-PDZ). The practical applicability of this PDZ-based detection method is determined by the affinity of the PDZ domain*peptide ligand interaction, and the efficiency of the enzyme to process the masked peptide ligand. To expand the use of this PDZ-based detection strategy to a broader range of enzymatic assays, we have taken advantage of the plasticity in ligand recognition by the variety of PDZ domains found in nature. In the original work, the PDZ3 of PSD-95 was used, which preferentially recognizes the consensus sequence Ser-X-Val-COOH. Here, we show that NHERF PDZ1, which binds to the consensus sequence Thr/Ser-X-Leu-COOH, can be used to extend the flexibility in the recognition of the carboxy-terminal amino acid of the ligand, and monitor the enzymatic activity of HIV protease. The choices of detection format, for example, TRET or ALPHA, were also investigated and influenced assay design.

A PDZ domain-based detection system for enzymatic assays.

A time-resolved fluorescence resonance energy transfer (TR-FRET) detection method based on the formation of a PDZ domain.peptide ligand complex has been developed for enzymatic assays as an alternative to immuno-based detection strategies. The enzyme substrate is a "masked" biotinylated PDZ domain peptide ligand containing the consensus sequence Ser-X-Val-COOH. The critical residues in the binding consensus sequence of the ligand have been modified, for example, by phosphorylation of Ser or C-terminal extensions, providing binding-incompetent PDZ domain peptides. On processing by the corresponding enzyme, the binding epitope is exposed, and the product sequence is recognized specifically by Eu(3+) chelate-labeled GST-PDZ ([Eu(3+)]GST-PDZ) (GST-PDZ-glutathione S-transferase fused to PDZ domain). A ternary complex is subsequently formed by addition of allophycocyanin-labeled streptavidin ([XL665]SA), which binds to the biotinylated N terminus of the peptide, and detected by TR-FRET. Reported here are examples of the applicability of this detection strategy to three enzymatic systems, an endoprotease, an exoprotease, and a Ser/Thr phosphatase.