Pharmacist-guided pharmacogenetic service lowered warfarin-related hospitalizations.

Background: The authors aimed to assess outcomes with a pharmacogenetic (PGx)-informed, pharmacist-guided, personalized consult service for warfarin dosing. Methods: This retrospective cohort study included patients admitted with thromboembolic events. Eligible subjects received either PGx-informed (n = 389) or historical non-PGx pharmacist-guided warfarin dosing (Hx; n = 308) before hospital discharge. The composite of admission with bleeding or thromboembolic events over 90 days after the discharge was compared between the PGx and Hx groups. Results: The rate ratio (95% CI) of the composite of bleeding or thromboembolic admissions for PGx versus Hx was 0.32 (0.12-0.82). The estimated hazard ratio was 0.43 (0.16-1.12). Conclusion: A PGx-informed warfarin dosing service was associated with decreased bleeding and thromboembolic encounters.

Changing from mandatory to optional genotyping results in higher acceptance of pharmacist-guided warfarin dosing.

Aim: We evaluated the clinical acceptance and feasibility of a pharmacist-guided personalized consult service following its transition from a mandatory (mPGx) to optional (oPGx) CYP2C9/VKORC1/CYP4F2 genotyping for warfarin. Methods: A total of 1105 patients were included. Clinical acceptance and feasibility outcomes were analyzed using bivariate and multivariable analyses. Results: After transitioning to optional genotyping, genotype testing was still ordered in a large segment of the eligible population (52.1%). Physician acceptance of pharmacist-recommended doses improved from 83.9% (mPGx) to 86.6% (oPGx; OR: 1.3; 95% CI: 1.1-1.5; p = 0.01) with a shorter median genotype result turnaround time (oPGX: 23.6 h vs mPGX: 25.1 h; p < 0.01). Conclusion: Ordering of genotype testing and provider acceptance of dosing recommendations remained high after transitioning to optional genotyping.

Indication alerts to improve problem list documentation.

BACKGROUND: Problem lists represent an integral component of high-quality care. However, they are often inaccurate and incomplete. We studied the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problem list when ordering medications that lacked a corresponding indication. METHODS: We analyzed medication orders from 2 healthcare systems that used an innovative indication alert. We collected data at site 1 between December 2018 and January 2020, and at site 2 between May and June 2021. We reviewed random samples of 100 charts from each site that had problems added in response to the alert. Outcomes were: (1) alert yield, the proportion of triggered alerts that led to a problem added and (2) problem accuracy, the proportion of problems placed that were accurate by chart review. RESULTS: Alerts were triggered 131 134, and 6178 times at sites 1 and 2, respectively, resulting in a yield of 109 055 (83.2%) and 2874 (46.5%), P< .001. Orders were abandoned, for example, not completed, in 11.1% and 9.6% of orders, respectively, P<.001. Of the 100 sample problems, reviewers deemed 88% ± 3% and 91% ± 3% to be accurate, respectively, P = .65, with a mean of 90% ± 2%. CONCLUSIONS: Indication alerts triggered by medication orders initiated in the absence of a justifying diagnosis were useful for populating problem lists, with yields of 83.2% and 46.5% at 2 healthcare systems. Problems were placed with a reasonable level of accuracy, with 90% ± 2% of problems deemed accurate based on chart review.

Improving the In-Hospital Mortality Prediction of Diabetes ICU Patients Using a Process Mining/Deep Learning Architecture.

Diabetes intensive care unit (ICU) patients are at increased risk of complications leading to in-hospital mortality. Assessing the likelihood of death is a challenging and time-consuming task due to a large number of influencing factors. Healthcare providers are interested in the detection of ICU patients at higher risk, such that risk factors can possibly be mitigated. While such severity scoring methods exist, they are commonly based on a snapshot of the health conditions of a patient during the ICU stay and do not specifically consider a patient's prior medical history. In this paper, a process mining/deep learning architecture is proposed to improve established severity scoring methods by incorporating the medical history of diabetes patients. First, health records of past hospital encounters are converted to event logs suitable for process mining. The event logs are then used to discover a process model that describes the past hospital encounters of patients. An adaptation of Decay Replay Mining is proposed to combine medical and demographic information with established severity scores to predict the in-hospital mortality of diabetes ICU patients. Significant performance improvements are demonstrated compared to established risk severity scoring methods and machine learning approaches using the Medical Information Mart for Intensive Care III dataset.

Home Health Care for Patients Without Shelter.

Home health care (HHC) is a well-established model of caring for patients in their homes, which has not been robustly applied to benefit patients without regular access to shelter. This article describes Chicago Street Medicine, an organization that implements HHC to improve health outcomes and care continuity for patients experiencing homelessness.

Risk factors associated with medication ordering errors.

OBJECTIVE: We utilized a computerized order entry system-integrated function referred to as "void" to identify erroneous orders (ie, a "void" order). Using voided orders, we aimed to (1) identify the nature and characteristics of medication ordering errors, (2) investigate the risk factors associated with medication ordering errors, and (3) explore potential strategies to mitigate these risk factors. MATERIALS AND METHODS: We collected data on voided orders using clinician interviews and surveys within 24 hours of the voided order and using chart reviews. Interviews were informed by the human factors-based SEIPS (Systems Engineering Initiative for Patient Safety) model to characterize the work systems-based risk factors contributing to ordering errors; chart reviews were used to establish whether a voided order was a true medication ordering error and ascertain its impact on patient safety. RESULTS: During the 16-month study period (August 25, 2017, to December 31, 2018), 1074 medication orders were voided; 842 voided orders were true medication errors (positive predictive value = 78.3 ± 1.2%). A total of 22% (n = 190) of the medication ordering errors reached the patient, with at least a single administration, without causing patient harm. Interviews were conducted on 355 voided orders (33% response). Errors were not uniquely associated with a single risk factor, but the causal contributors of medication ordering errors were multifactorial, arising from a combination of technological-, cognitive-, environmental-, social-, and organizational-level factors. CONCLUSIONS: The void function offers a practical, standardized method to create a rich database of medication ordering errors. We highlight implications for utilizing the void function for future research, practice and learning opportunities.

Impact of traditional risk factors for the outcomes of atrial fibrillation across race and ethnicity and sex groups.

BACKGROUND: Although traditional risk factors for atrial fibrillation (AF) and its outcomes are established in whites, their role in the pathogenesis of AF across race-ethnicity and both sexes remain unclear. Cohort studies have consistently shown worse AF-related outcomes in these groups. The objective of this study was to determine the role played by race- and sex-specific risk factors in AF outcomes in non-Hispanic blacks (NHBs), Hispanics/Latinos (H/Ls), and non-Hispanic whites (NHWs). METHODS: Using electronic health records (EHR), 3607 patients with an ICD-9 code for AF were identified over a 7-year period. Risk factors were identified from ICD to 9 CM claims data: hypertension (HTN), type 2 diabetes mellitus (T2DM), stroke/transient ischemic attack (TIA), smoking, chronic obstructive pulmonary disease (COPD), coronary artery disease (CAD), peripheral arterial disease (PAD) and obstructive sleep apnea (OSA). Multivariate analysis of variance was used to compare the incidence of AF risk factors. RESULTS: NHBs and H/Ls with AF experienced more stroke than NHWs (27% and 24% vs. 19% P < 0.01). Females had less HTN (48.4% vs 51.6% [males], P = 0.0002), CAD (47.4% vs 55.7% [males], P = 0.02), and smoking rates (38.2% vs 61.8% [males], P < 0.0001) but higher stroke rates (25.9% [female] vs 21.8% [males], P < 0.0001). Age-adjusted risk factors for stroke varied markedly across race-ethnicity and sex. CONCLUSIONS: We identified differences in risk factors for AF and stroke across race-ethnicity and sex. The findings of our study are hypothesis generating and should be used to direct future studies.

The Effects of a Multicomponent Colorectal Cancer Screening Intervention on Knowledge, Recommendation, and Screening among Underserved Populations.

This trial tested a multicomponent intervention to increase colorectal cancer (CRC) screening among underserved patients. Participants were randomized to: (1) physician + patient intervention, (2) physician-only intervention, or (3) usual care (UC). Study outcomes included patient knowledge, physician recommendation of CRC screening, and screening completion via colonoscopy or stool tests. Among 538 participants, those exposed to the physician + patient intervention had significantly increased knowledge over patients in physician-only (p=.0008) or UC arms (p=.0003). However, there were no statistically significant differences in completion of CRC screening, with 10%, 20%, and 16% of UC, physician-only, and physician + patient participants screened, respectively. In UC, all completed screenings were colonoscopy, whereas in the physician-only and physician + patient arms, 39% and 46% of completed tests were via stool test, respectively. The multicomponent intervention did not increase overall CRC screening, yet results underscore the need to provide patients options for completing CRC screening.

Effect of Restriction of the Number of Concurrently Open Records in an Electronic Health Record on Wrong-Patient Order Errors: A Randomized Clinical Trial.

Importance: Recommendations in the United States suggest limiting the number of patient records displayed in an electronic health record (EHR) to 1 at a time, although little evidence supports this recommendation. Objective: To assess the risk of wrong-patient orders in an EHR configuration limiting clinicians to 1 record vs allowing up to 4 records opened concurrently. Design, Setting, and Participants: This randomized clinical trial included 3356 clinicians at a large health system in New York and was conducted from October 2015 to April 2017 in emergency department, inpatient, and outpatient settings. Interventions: Clinicians were randomly assigned in a 1:1 ratio to an EHR configuration limiting to 1 patient record open at a time (restricted; n = 1669) or allowing up to 4 records open concurrently (unrestricted; n = 1687). Main Outcomes and Measures: The unit of analysis was the order session, a series of orders placed by a clinician for a single patient. The primary outcome was order sessions that included 1 or more wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder measure (an electronic query that identifies orders placed for a patient, retracted, and then reordered shortly thereafter by the same clinician for a different patient). Results: Among the 3356 clinicians who were randomized (mean [SD] age, 43.1 [12.5] years; mean [SD] experience at study site, 6.5 [6.0] years; 1894 females [56.4%]), all provided order data and were included in the analysis. The study included 12 140 298 orders, in 4 486 631 order sessions, placed for 543 490 patients. There was no significant difference in wrong-patient order sessions per 100 000 in the restricted vs unrestricted group, respectively, overall (90.7 vs 88.0; odds ratio [OR], 1.03 [95% CI, 0.90-1.20]; P = .60) or in any setting (ED: 157.8 vs 161.3, OR, 1.00 [95% CI, 0.83-1.20], P = .96; inpatient: 185.6 vs 185.1, OR, 0.99 [95% CI, 0.89-1.11]; P = .86; or outpatient: 7.9 vs 8.2, OR, 0.94 [95% CI, 0.70-1.28], P = .71). The effect did not differ among settings (P for interaction = .99). In the unrestricted group overall, 66.2% of the order sessions were completed with 1 record open, including 34.5% of ED, 53.7% of inpatient, and 83.4% of outpatient order sessions. Conclusions and Relevance: A strategy that limited clinicians to 1 EHR patient record open compared with a strategy that allowed up to 4 records open concurrently did not reduce the proportion of wrong-patient order errors. However, clinicians in the unrestricted group placed most orders with a single record open, limiting the power of the study to determine whether reducing the number of records open when placing orders reduces the risk of wrong-patient order errors. Trial Registration: clinicaltrials.gov Identifier: NCT02876588.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems.

Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.

Similar burden of type 2 diabetes among adult patients with sickle cell disease relative to African Americans in the U.S. population: a six-year population-based cohort analysis.

Conflicting evidence exists on the epidemiology of type 2 diabetes mellitus (T2DM) among patients with sickle cell disease (SCD). This study measured the prevalence, incidence and clinical outcomes associated with T2DM in a large US population of commercially-insured adults aged ≥20 years with SCD between 2009 and 2014. Among 7070 patients with SCD, the mean age (median) was 39 (37) years and 60·8% were female. The standardized prevalence of T2DM among patients with SCD showed a modest increase, from 15·7% to 16·5% (P trend = 0·026), and was comparable to African-American respondents to the National Health and Nutrition Examination Survey (18·2%). Over 17 024 person-years, the crude incidence rate for T2DM was 25·4 per 1000 person-years. Incident T2DM was associated with comorbid hypertension (hazard ratio [HR] = 1·45, 95% confidence interval [CI] 1·14-1·83), and dyslipidaemia (HR = 1·43, 95%CI 1·04-1·96). Compared to SCD patients without T2DM, more SCD patients with T2DM had diagnoses of nephropathy (28·0% vs. 9·5%; P < 0·001), neuropathy (17·7% vs. 5·2%; P < 0·001) and stroke (24·1% vs. 9·2%; P < 0·001). Prevalence of T2DM in SCD patients is similar to the general African American population with an increasing trend in recent years. These trends support routine screening for T2DM in aging patients with SCD, especially those with comorbid hypertension and/or dyslipidaemia.

A Prescription For Enhancing Electronic Prescribing Safety.

While electronic prescribing has been shown to reduce medication errors and improve prescribing safety, it is vulnerable to error-prone processes. We review six intersecting areas in which changes to electronic prescribing systems, particularly in the outpatient setting, could transform medication ordering quality and safety. We recommend incorporating medication indications into electronic prescribing, establishing a single shared online medication list, implementing the transmission of electronic cancellation orders to pharmacies (CancelRx) to ensure that drugs are safely and reliably discontinued, implementing standardized structured and codified prescription instructions, reengineering clinical decision support, and redesigning electronic prescribing to facilitate the ordering of nondrug alternatives.

A New Approach towards Minimizing the Risk of Misdosing Warfarin Initiation Doses.

It is a challenge to be able to prescribe the optimal initial dose of warfarin. There have been many studies focused on an efficient strategy to determine the optimal initial dose. Numerous clinical, genetic, and environmental factors affect the warfarin dose response. In practice, it is common that the initial warfarin dose is substantially different from the stable maintenance dose, which may increase the risk of bleeding or thrombosis prior to achieving the stable maintenance dose. In order to minimize the risk of misdosing, despite popular warfarin dose prediction models in the literature which create dose predictions solely based on patients' attributes, we have taken physicians' opinions towards the initial dose into consideration. The initial doses selected by clinicians, along with other standard clinical factors, are used to determine an estimate of the difference between the initial dose and estimated maintenance dose using shrinkage methods. The selected shrinkage method was LASSO (Least Absolute Shrinkage and Selection Operator). The estimated maintenance dose was more accurate than the original initial dose, the dose predicted by a linear model without involving the clinicians initial dose, and the values predicted by the most commonly used model in the literature, the Gage clinical model.

Learning optimal opioid prescribing and monitoring: a simulation study of medical residents.

OBJECTIVE: Hospitalized patients often receive opioids. There is a lack of consensus regarding evidence-based guidelines or training programs for effective management of pain in the hospital. We investigated the viability of using an Internet-based opioid dosing simulator to teach residents appropriate use of opioids to treat and manage acute pain. MATERIALS AND METHODS: We used a prospective, longitudinal design to evaluate the effects of simulator training. In face-to-face didactic sessions, we taught 120 (108 internal medicine and 12 family medicine) residents principles of pain management and how to use the simulator. Each trainee completed 10 training and, subsequently, 5 testing trials on the simulator. For each trial, we collected medications, doses, routes and times of administration, pain scores, and a summary score. We used mixed-effects regression models to assess the impact of simulation training on simulation performance scores, variability in pain score trajectories, appropriate use of short- and long-acting opioids, and use of naloxone. RESULTS: Trainees completed 1582 simulation trials (M = 13.2, SD = 6.8), with sustained improvements in their simulated pain management practices. Over time, trainees improved their overall simulated pain management scores (b = 0.05, P < .01), generated lower pain score trajectories with less variability (b = -0.02, P < .01), switched more rapidly from short-acting to long-acting agents (b = -0.50, P < .01), and used naloxone less often (b = -0.10, P < .01). DISCUSSION AND CONCLUSIONS: Trainees translated their understanding of didactically presented principles of pain management to their performance on simulated patient cases. Simulation-based training presents an opportunity for improving opioid-based inpatient acute pain management.

Effect of number of open charts on intercepted wrong-patient medication orders in an emergency department.

To reduce the risk of wrong-patient errors, safety experts recommend allowing only one patient chart to be open at a time. Due to the lack of empirical evidence, the number of allowable open charts is often based on anecdotal evidence or institutional preference, and hence varies across institutions. Using an interrupted time series analysis of intercepted wrong-patient medication orders in an emergency department during 2010-2016 (83.6 intercepted wrong-patient events per 100 000 orders), we found no significant decrease in the number of intercepted wrong-patient medication orders during the transition from a maximum of 4 open charts to a maximum of 2 (b = -0.19, P = .33) and no significant increase during the transition from a maximum of 2 open charts to a maximum of 4 (b = 0.08, P = .67). These results have implications regarding decisions about allowable open charts in the emergency department in relation to the impact on workflow and efficiency.

High number of newly initiated direct oral anticoagulant users switch to alternate anticoagulant therapy.

Real-world evidence focusing on medication switching patterns amongst direct oral anticoagulant (DOACs) has not been well studied. The objective of this study is to evaluate patterns of prescription switching in non-valvular atrial fibrillation (NVAF) patients initiated on a DOAC and previously naïve to anticoagulation (AC) therapy. Data was obtained from Truven Health MarketScan® Commercial and Medicare Supplemental database (2009-2013). AC naïve (those without prior anticoagulant use) NVAF patients initiated on a DOAC, with 6 months of continuous health plan enrollment before and after treatment initiation and maintained on continuous therapy for a minimum of 6 months were included. Of 34,022 AC naïve NVAF patients initiating a DOAC, 6613 (19.4%) patients switched from an index DOAC prescription to an alternate anticoagulant and 27,409 (80.6%) remained on the DOAC [age: 68.5 ± 11.7 vs. 67.1 ± 12.7 years, p < 0.001; males: 3781 (57.2%) vs. 17,160 (62.6%), p < 0.001]. Amongst those that switched medication, 3196 (48.3%) did so within the first 6 months of therapy. Overall, 2945 (44.5%) patients switched to warfarin, 2912 (44.0%) switched to another DOAC and 756 (11.4%) switched to an injectable anticoagulant. The highest proportion of patients switched from dabigatran to warfarin (N = 2320; 42.5%) or rivaroxaban (N = 2252; 41.3%). The median time to switch from the index DOAC to another DOAC was 309.5 days versus 118.0 days (p < 0.001) to switch to warfarin. In NVAF patients newly initiated on DOAC therapy, one in five patients switch to an alternate anticoagulant and one of every two patients do so within the first 6 months of therapy. Switching from an initial DOAC prescription to traditional anticoagulants occurs as frequently as switching to an alternate DOAC.

Real-World Adherence and Persistence with Direct Oral Anticoagulants in Adults with Atrial Fibrillation.

BACKGROUND: Evidence of adherence and persistence patterns in anticoagulation (AC) therapy comparing treatment-naïve and non-naïve patients is lacking. The objective of this study was to evaluate patterns of medication adherence and persistence in a real-world setting among AC-naïve and AC-experienced patients with atrial fibrillation (AF) who were treated with direct oral anticoagulants (DOACs). METHODS: AF patients newly initiating a DOAC with a minimum of 6 months of continuous health plan enrollment pre and postindex date (first DOAC prescription) were identified from the Truven Health MarketScan Commercial and Medicare Supplemental databases (2009-2013). DOAC adherence (proportion of days covered [PDC]), persistence, and predictors of adherence were assessed at 6 and 12 months postindex. RESULTS: Of 66,090 AF patients included, 46.6% (n=30,826) were AC naïve and 53.4% (n=35,264) were AC experienced (age: 66.9 ± 12.7 vs 70.4 ± 11.4 yrs, p<0.001; male: n=19,132 [62.1%] vs n=21,691 [61.5%], p=0.14, respectively). A majority of patients received dabigatran as their index DOAC (n=49,210; 74.5%). The mean PDC in AC-naïve versus AC-experienced patients at 6 and 12 months of follow-up was 72.3% versus 83.3% (p<0.001) and 63.7% versus 79.9% (p<0.001), respectively. Persistence with DOAC therapy in AC-naïve and AC-experienced patients at 6 and 12 months ranged from 59.3% and 76.3% (p<0.0001) to 31.6% and 50.2% (p<0.0001), respectively. Predictors of higher DOAC adherence were older age and higher number of concomitant medications. Predictors of lower adherence were higher number of comorbidities and AC-naïve user status. CONCLUSION: Medication adherence and persistence with DOACs declined over time and both were suboptimal and lower (at 6 and 12 mo postindex) in AC-naïve compared to AC-experienced patients. These findings can help target future strategies or interventions for patient education and long-term AC management especially in those patients naïve to DOAC therapy. Future investigation should examine potential reasons for differences in DOAC adherence and persistence between AC-experienced versus AC-naïve patients and the implications for patient outcomes.

A national survey assessing the number of records allowed open in electronic health records at hospitals and ambulatory sites.

To reduce the risk of wrong-patient errors, safety experts recommend limiting the number of patient records providers can open at once in electronic health records (EHRs). However, it is unknown whether health care organizations follow this recommendation or what rationales drive their decisions. To address this gap, we conducted an electronic survey via 2 national listservs. Among 167 inpatient and outpatient study facilities using EHR systems designed to open multiple records at once, 44.3% were configured to allow ≥3 records open at once (unrestricted), 38.3% allowed only 1 record open (restricted), and 17.4% allowed 2 records open (hedged). Decision-making centered on efforts to balance safety and efficiency, but there was disagreement among organizations about how to achieve that balance. Results demonstrate no consensus on the number of records to be allowed open at once in EHRs. Rigorous studies are needed to determine the optimal number of records that balances safety and efficiency.