Publications by authors named "Jason S Adelman"

21 Publications

  • Page 1 of 1

COVID-19 and Patient Safety: Time to Tap Into Our Investment in High Reliability.

J Patient Saf 2021 Mar 13. Epub 2021 Mar 13.

From the Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center Department of Quality and Patient Safety, NewYork-Presbyterian, New York, NY Press Ganey Associates LLC, Boston, MA.

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http://dx.doi.org/10.1097/PTS.0000000000000843DOI Listing
March 2021

Incident Reports of Naming Errors among Two Sets of Infant Twins.

Pediatr Qual Saf 2020 Nov-Dec;5(6):e356. Epub 2020 Oct 23.

Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, N.Y.

Newborns are at high risk for identification errors due to their inability to speak and indistinguishable features. To reduce this risk, The Joint Commission requires hospitals to use a distinct identification method for newborns. Most hospitals create medical records for newborns at birth using temporary naming conventions, resulting in patients with similar identifiers. Typically, multiple-birth infants are distinguished from their siblings by a single character (1, 2, or A, B), placing them at higher risk for identification errors, which can delay care and compromise patient safety.

Methods: We present 2 unrelated cases involving naming errors in sets of infant twins receiving care in a healthcare system using Joint Commission compliant distinct temporary naming convention.

Results: In the 2 cases, system failures contributed to naming errors in 2 sets of infant twins, which resulted in delayed care. In the first case, twins were inadvertently assigned the same temporary name. In the second case, an infant's blood specimen label did not include a single character, which distinguishes a multiple-birth infant from their sibling. Further safeguards are needed to reduce this risk. These cases illustrated the potential for misidentification related to newborn naming conventions during the registration process, especially between siblings of multiple-birth infants.

Conclusions: Further research is needed to determine strategies to prevent newborn identification errors. Potential strategies to reduce this risk and protect newborns include improving the design of newborn identifiers, systems-level interventions such as verification alerts, and improved registration processes.
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http://dx.doi.org/10.1097/pq9.0000000000000356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7870170PMC
October 2020

Development and Validation of a Fall Prevention Efficiency Scale.

J Patient Saf 2021 Jan 21. Epub 2021 Jan 21.

From the Partners HealthCare Harvard Medical School, Boston, Massachusetts Montefiore Medical Center Hospitals Columbia University School of Nursing NewYork-Presbyterian Hospital, New York, New York.

Objectives: Fall TIPS (Tailoring Interventions for Patient Safety) is an evidence-based fall prevention program that led to a 25% reduction in falls in hospitalized adults. Because it would be helpful to assess nurses' perceptions of burdens imposed on them by using Fall TIPS or other fall prevention program, we conducted a study to learn benefits and burdens.

Methods: A 3-phase mixed-method study was conducted at 3 hospitals in Massachusetts and 3 in New York: (1) initial qualitative, elicited and categorized nurses' views of time spent implementing Fall TIPS; (2) second qualitative, used nurses' quotes to develop items, research team inputs for refinement and organization, and clinical nurses' evaluation and suggestions to develop the prototype scale; and (3) quantitative, evaluated psychometric properties.

Results: Four "time" themes emerged: (1) efficiency, (2) inefficiency, (3) balances out, and (4) valued. A 20-item prototype Fall Prevention Efficiency Scale was developed, administered to 383 clinical nurses, and reduced to 13 items. Individual items demonstrated robust stability with Pearson correlations of 0.349 to 0.550 and paired t tests of 0.155 to 1.636. Four factors explained 74.3% variance and provided empirical support for the scale's conceptual basis. The scale achieved excellent internal consistency values (0.82-0.92) when examined with the test, validation, and paired (both test and retest) samples.

Conclusions: This new scale assess nurses' perceptions of how a fall prevention program affects their efficiency, which impacts the likelihood of use. Learning nurses' beliefs about time wasted when implementing new programs allows hospitals to correct problems that squander time.
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http://dx.doi.org/10.1097/PTS.0000000000000811DOI Listing
January 2021

Association of Display of Patient Photographs in the Electronic Health Record With Wrong-Patient Order Entry Errors.

JAMA Netw Open 2020 11 2;3(11):e2019652. Epub 2020 Nov 2.

Department of Emergency Medicine, Brigham and Women's Hospital, Boston, Massachusetts.

Importance: Wrong-patient order entry (WPOE) errors have a high potential for harm; these errors are particularly frequent wherever workflows are complex and multitasking and interruptions are common, such as in the emergency department (ED). Previous research shows that interruptive solutions, such as electronic patient verification forms or alerts, can reduce these types of errors but may be time-consuming and cause alert fatigue.

Objective: To evaluate whether the use of noninterruptive display of patient photographs in the banner of the electronic health record (EHR) is associated with a decreased rate of WPOE errors.

Design, Setting, And Participants: In this cohort study, data collected as part of care for patients visiting the ED of a large tertiary academic urban hospital in Boston, Massachusetts, between July 1, 2017, and June 31, 2019, were analyzed.

Exposures: In a quality improvement initiative, the ED staff encouraged patients to have their photographs taken by informing them of the intended safety impact.

Main Outcomes And Measures: The rate of WPOE errors (measured using the retract-and-reorder method) for orders placed when the patient's photograph was displayed in the banner of the EHR vs the rate for patients without a photograph displayed. The primary analysis focused on orders placed in the ED; a secondary analysis included orders placed in any care setting.

Results: A total of 2 558 746 orders were placed for 71 851 unique patients (mean [SD] age, 49.2 [19.1] years; 42 677 (59.4%) female; 55 109 (76.7%) non-Hispanic). The risk of WPOE errors was significantly lower when the patient's photograph was displayed in the EHR (odds ratio, 0.72; 95% CI, 0.57-0.89). After this risk was adjusted for potential confounders using multivariable logistic regression, the effect size remained essentially the same (odds ratio, 0.57; 95% CI, 0.52-0.61). Risk of error was significantly lower in patients with higher acuity levels and among patients whose race was documented as White.

Conclusions And Relevance: This cohort study suggests that displaying patient photographs in the EHR provides decision support functionality for enhancing patient identification and reducing WPOE errors while being noninterruptive with minimal risk of alert fatigue. Successful implementation of such a program in an ED setting involves a modest financial investment and requires appropriate engagement of patients and staff.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.19652DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7658731PMC
November 2020

Impact of Hearing Loss on Patient Falls in the Inpatient Setting.

Am J Prev Med 2020 06;58(6):839-844

Department of Otolaryngology-Head and Neck Surgery, Columbia University College of Physicians and Surgeons, New York, New York. Electronic address:

Introduction: The objectives of this study were to investigate an association between the risk of patient falls and self-reported hearing loss and to examine whether self-reported hearing loss with versus without hearing aids predicts patient falls in an inpatient setting.

Methods: This retrospective cohort analysis was conducted in 2018 in a large, urban, academic medical center. Participants included unique inpatients (N=52,805) of adults aged >18 years between February 1, 2017, and February 1, 2018. Outcome measures were falls in the inpatient setting and hearing loss with versus without hearing aids as predictors for patient falls.

Results: Self-reported hearing loss was associated with falls in the inpatient setting (OR=1.74, 95% CI=1.46, 2.07, p<1.43 × 10). Among patients with hearing impairment, a lack of hearing aids increased the risk for falls in the inpatient setting (OR=2.70, 95% CI=1.64, 4.69, p<1.41 × 10). After accounting for the risk of fall using the Morse Fall Scale (which does not include hearing impairment) and controlling for age and sex, patients with hearing loss and no hearing aids were significantly more likely to fall (OR=2.44, 95% CI=1.002, 5.654, p<0.042), but patients with hearing loss who did have hearing aids were not significantly more likely to fall (p<0.889). Hearing loss together with the Morse Fall Scale better predicted falls than the Morse Fall Scale alone (p<0.017).

Conclusions: In the inpatient setting, there was a positive association between hearing loss and falls. However, among patients with hearing loss, only those without hearing aids were significantly more likely to fall, accounting for the Morse Fall Scale score and demographics characteristics. These findings support adding hearing loss as a modifiable risk factor in risk assessment tools for falls and exploring the use of amplification devices as an intervention.
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http://dx.doi.org/10.1016/j.amepre.2020.01.019DOI Listing
June 2020

A National Survey on the Use of Temporary Naming Conventions for Newborns: 5-Year Follow-up.

Clin Pediatr (Phila) 2020 09 19;59(9-10):925-928. Epub 2020 May 19.

Columbia University Irving Medical Center, New York, NY, USA.

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http://dx.doi.org/10.1177/0009922820922534DOI Listing
September 2020

EHR audit logs: A new goldmine for health services research?

J Biomed Inform 2020 01 7;101:103343. Epub 2019 Dec 7.

Agency for Healthcare Research and Quality, 5600 Fishers Lane, Rockville, MD 20857, USA. Electronic address:

A byproduct of the transition to electronic health records (EHRs) is the associated observational data that capture EHR users' granular interactions with the medical record. Often referred to as audit log data or event log data, these datasets capture and timestamp user activity while they are logged in to the EHR. These data - alone and in combination with other datasets - offer a new source of insights, which cannot be gleaned from claims data or clinical data, to support health services research and those studying healthcare processes and outcomes. In this commentary, we seek to promote broader awareness of EHR audit log data and to stimulate their use in many contexts. We do so by describing EHR audit log data and offering a framework for their potential uses in quality domains (as defined by the National Academy of Medicine). The framework is illustrated with select examples in the safety and efficiency domains, along with their accompanying methodologies, which serve as a proof of concept. This article also discusses insights and challenges from working with EHR audit log data. Ensuring that researchers are aware of such data, and the new opportunities they offer, is one way to assure that our healthcare system benefits from the digital revolution.
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http://dx.doi.org/10.1016/j.jbi.2019.103343DOI Listing
January 2020

Project RedDE: Cluster Randomized Trial to Reduce Missed or Delayed Abnormal Laboratory Value Actions.

Pediatr Qual Saf 2019 Sep-Oct;4(5):e218. Epub 2019 Sep 30.

Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center, Department of Medicine, Baylor College of Medicine, Center of Innovation, Houston, Tex.

Failure of timely abnormal laboratory result follow-up is relatively common and may lead to harm. This study hypothesized that a quality improvement collaborative (QIC) could reduce the frequency of missed or delayed action on abnormal laboratory values.

Methods: A national cohort of pediatric practices was cluster-randomized to sequentially receive a QIC intervention: video conferences, transparent data sharing, a "focus on failures," QI coaching, and tools to help reduce missed or delayed action on abnormal laboratory values. Practices recorded the percentage of patients with 5 specific abnormal laboratory values who received an appropriate provider action (control), and then, during an 8-month intervention phase, implemented QI strategies to reduce errors (intervention). Subsequently, practices collected data on laboratory errors while working to reduce unrelated second (sustain phase), and third (maintenance phase) errors. Generalized mixed-effects regression models compared the mean percentage of patients with appropriate actions.

Results: We randomized 43 practices, of which 31 were included in analyses. Control and intervention phases included 1,357 and 1,426 patients with abnormal laboratory values, respectively. The mean percentage of patients who received appropriate actions did not change comparing control and intervention phases [risk difference (RD) 1%; 95% CI -1%, 3%]. In analyses, practices significantly improved comparing control to sustain (RD 3%; 95% CI 0.3%, 6%) and maintenance phases (RD 6%; 95% CI 3%, 9%).

Conclusion: Implementation of a QIC did not reduce the frequency of abnormal laboratory errors in the initial 8-month intervention phase. A significant reduction was appreciated comparing sustain and maintenance phases (months 9-24) to the control phase.
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http://dx.doi.org/10.1097/pq9.0000000000000218DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805103PMC
September 2019

Limiting the Number of Open Records in an Electronic Health Record-Reply.

JAMA 2019 10;322(13):1314-1315

Division of Hospital Medicine, Albert Einstein College of Medicine, Bronx, New York.

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http://dx.doi.org/10.1001/jama.2019.11501DOI Listing
October 2019

Risk of Wrong-Patient Orders Among Multiple vs Singleton Births in the Neonatal Intensive Care Units of 2 Integrated Health Care Systems.

JAMA Pediatr 2019 Aug 26. Epub 2019 Aug 26.

Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Importance: Multiple-birth infants in neonatal intensive care units (NICUs) have nearly identical patient identifiers and may be at greater risk of wrong-patient order errors compared with singleton-birth infants.

Objectives: To assess the risk of wrong-patient orders among multiple-birth infants and singletons receiving care in the NICU and to examine the proportion of wrong-patient orders between multiple-birth infants and siblings (intrafamilial errors) and between multiple-birth infants and nonsiblings (extrafamilial errors).

Design, Setting, And Participants: A retrospective cohort study was conducted in 6 NICUs of 2 large, integrated health care systems in New York City that used distinct temporary names for newborns per the requirements of The Joint Commission. Data were collected from 4 NICUs at New York-Presbyterian Hospital from January 1, 2012, to December 31, 2015, and 2 NICUs at Montefiore Health System from July 1, 2013, to June 30, 2015. Data were analyzed from May 1, 2017, to December 31, 2017. All infants in the 6 NICUs for whom electronic orders were placed during the study periods were included.

Main Outcomes And Measures: Wrong-patient electronic orders were identified using the Wrong-Patient Retract-and-Reorder (RAR) Measure. This measure was used to detect RAR events, which are defined as 1 or more orders placed for a patient that are retracted (ie, canceled) by the same clinician within 10 minutes, then reordered by the same clinician for a different patient within the next 10 minutes.

Results: A total of 10 819 infants were included: 85.5% were singleton-birth infants and 14.5% were multiple-birth infants (male, 55.8%; female, 44.2%). The overall wrong-patient order rate was significantly higher among multiple-birth infants than among singleton-birth infants (66.0 vs 41.7 RAR events per 100 000 orders, respectively; adjusted odds ratio, 1.75; 95% CI, 1.39-2.20; P < .001). The rate of extrafamilial RAR events among multiple-birth infants (36.1 per 100 000 orders) was similar to that of singleton-birth infants (41.7 per 100 000 orders). The excess risk among multiple-birth infants (29.9 per 100 000 orders) appears to be owing to intrafamilial RAR events. The risk increased as the number of siblings receiving care in the NICU increased; a wrong-patient order error occurred in 1 in 7 sets of twin births and in 1 in 3 sets of higher-order multiple births.

Conclusions And Relevance: This study suggests that multiple-birth status in the NICU is associated with significantly increased risk of wrong-patient orders compared with singleton-birth status. This excess risk appears to be owing to misidentification between siblings. These results suggest that a distinct naming convention as required by The Joint Commission may provide insufficient protection against identification errors among multiple-birth infants. Strategies to reduce this risk include using given names at birth, changing from temporary to given names when available, and encouraging parents to select names for multiple births before they are born when acceptable to families.
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http://dx.doi.org/10.1001/jamapediatrics.2019.2733DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6714004PMC
August 2019

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

JAMA 2019 05;321(18):1780-1787

Division of Hospital Medicine, Department of Medicine, Albert Einstein College of Medicine, Montefiore Health System, Bronx, New York.

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.
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http://dx.doi.org/10.1001/jama.2019.3698DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518341PMC
May 2019

Development and Validation of a Fall Prevention Knowledge Test.

J Am Geriatr Soc 2019 01 9;67(1):133-138. Epub 2018 Oct 9.

New York-Presbyterian Hospital, New York, New York.

Falls are a serious, persistent problem in hospitals. Ensuring that all hospital staff have adequate knowledge of how to prevent falls is the first step in prevention. We identified validated fall prevention knowledge tests (FPKTs) and planned to conduct a systematic literature review. When the review identified a lack of FPKTs, we developed and evaluated a FPKT, confirmed its conceptual framework, identified the content domain, drafted test items, devised the format, selected items for empirical examination, and conducted a psychometric evaluation. We randomly divided a 209-subject data set into test and validation samples to make item reduction decisions and examine reliability and validity. The typical respondent was a white, 42-year old female nurse with a bachelor's degree and 7 years' experience. Subjects were confident in their ability to prevent falls, rating themselves an 8 on a self-efficacy scale of 1 (not at all) to 10 (very). The 11-item FPKT scale (range 0-11) attained a tetrachoric coefficient of 0.73, confirming initial reliability. FPKT mean scores obtained before and after fall prevention education improved from 5.1 ± 1.8 to 6.6 ± 1.7. Statistically significant differences (paired t-test = 12.4, p < .001) confirmed validity. A robust way to assess nurses' knowledge of fall prevention is needed to inform effective educational programs. Addressing gaps in validated FPKTs provides an opportunity to inform and evaluate effective fall prevention programs. J Am Geriatr Soc 67:133-138, 2019.
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http://dx.doi.org/10.1111/jgs.15563DOI Listing
January 2019

Diagnostic Errors in Primary Care Pediatrics: Project RedDE.

Acad Pediatr 2018 03 10;18(2):220-227. Epub 2017 Aug 10.

Medical University of South Carolina, Charleston, SC.

Objective: Diagnostic errors (DEs), which encompass failures of accuracy, timeliness, or patient communication, cause appreciable morbidity but are understudied in pediatrics. Pediatricians have expressed interest in reducing high-frequency/subacute DEs, but their epidemiology remains unknown. The objective of this study was to investigate the frequency of two high-frequency/subacute DEs and one missed opportunity for diagnosis (MOD) in primary care pediatrics.

Methods: As part of a national quality improvement collaborative, 25 primary care pediatric practices were randomized to collect 5 months of retrospective data on one DE or MOD: elevated blood pressure (BP) and abnormal laboratory values (DEs), or adolescent depression evaluation (MOD). Relationships between DE or MOD proportions and patient age, gender, and insurance status were explored with mixed-effects logistic regression models.

Results: DE or MOD rates in pediatric primary care were found to be 54% for patients with elevated BP (n = 389), 11% for patients with abnormal laboratory values (n = 381), and 62% for adolescents with an opportunity to evaluate for depression (n = 400). When examining the number of times a pediatrician may have recognized an abnormal condition but either knowingly or unknowingly did not act according to recommended guidelines, providers did not document recognition of an elevated BP in 51% of patients with elevated BP, and they did not document recognition of an abnormal laboratory value without a delay in 9% of patients with abnormal laboratory values.

Conclusions: DEs and MODs occur at an appreciable frequency in pediatric primary care. These errors may contribute to care delays and patient harm.
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http://dx.doi.org/10.1016/j.acap.2017.08.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809238PMC
March 2018

Evaluating Serial Strategies for Preventing Wrong-Patient Orders in the NICU.

Pediatrics 2017 May;139(5)

Division of Hospital Medicine.

Background: NICU patients have characteristics believed to increase their risk for wrong-patient errors; however, little is known about the frequency of wrong-patient errors in the NICU or about effective interventions for preventing these errors. We conducted a quality improvement study to evaluate the frequency of wrong-patient orders in the NICU and to assess the effectiveness of an ID reentry intervention and a distinct naming convention (eg, "Wendysgirl") for reducing these errors, using non-NICU pediatric units as a comparator.

Methods: Using a validated measure, we examined the rate of wrong-patient orders in NICU and non-NICU pediatric units during 3 periods: baseline (before implementing interventions), ID reentry intervention (reentry of patient identifiers before placing orders), and combined intervention (addition of a distinct naming convention for newborns).

Results: We reviewed >850 000 NICU orders and >3.5 million non-NICU pediatric orders during the 7-year study period. At baseline, wrong-patient orders were more frequent in NICU than in non-NICU pediatric units (117.2 vs 74.9 per 100 000 orders, respectively; odds ratio 1.56; 95% confidence interval, 1.34-1.82). The ID reentry intervention reduced the frequency of errors in the NICU to 60.2 per 100 000 (48.7% reduction; < .001). The combined ID reentry and distinct naming interventions yielded an additional decrease to 45.6 per 100 000 (61.1% reduction from baseline; < .001).

Conclusions: The risk of wrong-patient orders in the NICU was significantly higher than in non-NICU pediatric units. Implementation of a combined ID reentry intervention and distinct naming convention greatly reduced this risk.
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http://dx.doi.org/10.1542/peds.2016-2863DOI Listing
May 2017

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

J Am Med Inform Assoc 2017 Sep;24(5):992-995

Department of Medicine, Division of Hospital Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA.

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.
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http://dx.doi.org/10.1093/jamia/ocx034DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7651980PMC
September 2017

Ordering Interruptions in a Tertiary Care Center: A Prospective Observational Study.

Hosp Pediatr 2017 03 1;7(3):134-139. Epub 2017 Feb 1.

The Children's Hospital at Montefiore, Bronx, New York.

Objectives: By self-report, interruptions may contribute to up to 80% of ordering errors. A greater understanding of the frequency and context of interruptions during ordering is needed to identify targets for intervention. We sought to characterize the epidemiology of interruptions during order placement in the pediatric inpatient setting.

Methods: This prospective observational study conducted 1-hour-long structured observations on morning rounds and afternoons and evenings in the resident workroom. The primary outcome was the number of interruptions per 100 orders placed by residents and physician assistants. We assessed the role of ordering provider, number, type and urgency of interruptions and person initiating interruption. Descriptive statistics, χ, and run charts were used.

Results: Sixty-nine structured observations were conducted with a total of 414 orders included. The interruption rate was 65 interruptions per 100 orders during rounds, 55 per 100 orders in the afternoons and 56 per 100 orders in the evenings. The majority of interruptions were in-person ( = 144, 61%). Interruptions from overhead announcements occurred most often in the mornings, and phone interruptions occurred most often in the evenings ( = .002). Nurses initiated interruptions most frequently. Attending physicians and fellows were more likely to interrupt during rounds, and coresidents were more likely to interrupt in the evenings ( = .002).

Conclusions: Residents and physician assistants are interrupted at a rate of 57 interruptions per 100 orders placed. This may contribute to ordering errors and worsen patient safety. Efforts should be made to decrease interruptions during the ordering process and track their effects on medication errors.
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http://dx.doi.org/10.1542/hpeds.2016-0127DOI Listing
March 2017

Improving hospital venous thromboembolism prophylaxis with electronic decision support.

J Hosp Med 2013 Mar 26;8(3):115-20. Epub 2012 Nov 26.

Department of Medicine, Montefiore Medical Center, Bronx, NY, USA.

Background: Venous thromboembolism (VTE) disease prophylaxis rates among medical inpatients have been noted to be <50%.

Objective: Our objective was to evaluate the effectiveness and safety of a computerized decision support application to improve VTE prophylaxis.

Design: Observational cohort study.

Setting: Academic medical center.

Patients: Adult inpatients on hospital medicine and nonmedicine services.

Intervention: A decision support application designed by a quality improvement team was implemented on medicine services in September 2009.

Measurements: Effectiveness and safety parameters were compared on medicine services and nonmedicine (nonimplementation) services for 6-month periods before and after implementation. Effectiveness was evaluated by retrospective information system queries for rates of any VTE prophylaxis, pharmacologic VTE prophylaxis, and hospital-acquired VTE incidence. Safety was evaluated by queries for bleeding and thrombocytopenia rates.

Results: Medicine service overall VTE prophylaxis increased from 61.9% to 82.1% (P < 0.001), and pharmacologic VTE prophylaxis increased from 59.0% to 74.5% (P < 0.001). Smaller but significant increases were observed on nonmedicine services. Hospital-acquired VTE incidence on medicine services decreased significantly from 0.65% to 0.42% (P = 0.008) and nonsignificantly on nonmedicine services. Bleeding rates increased from 2.9% to 4.0% (P < 0.001) on medicine services and from 7.7% to 8.6% (P = 0.043) on nonmedicine services, with nonsignificant changes in thrombocytopenia rates observed on both services.

Conclusions: An electronic decision support application on inpatient medicine services can significantly improve VTE prophylaxis and hospital-acquired VTE rates with a reasonable safety profile.
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http://dx.doi.org/10.1002/jhm.1993DOI Listing
March 2013

Understanding and preventing wrong-patient electronic orders: a randomized controlled trial.

J Am Med Inform Assoc 2013 Mar-Apr;20(2):305-10. Epub 2012 Jun 29.

Departments of Medicine, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, NY 10467, USA.

Objective: To evaluate systems for estimating and preventing wrong-patient electronic orders in computerized physician order entry systems with a two-phase study.

Materials And Methods: In phase 1, from May to August 2010, the effectiveness of a 'retract-and-reorder' measurement tool was assessed that identified orders placed on a patient, promptly retracted, and then reordered by the same provider on a different patient as a marker for wrong-patient electronic orders. This tool was then used to estimate the frequency of wrong-patient electronic orders in four hospitals in 2009. In phase 2, from December 2010 to June 2011, a three-armed randomized controlled trial was conducted to evaluate the efficacy of two distinct interventions aimed at preventing these errors by reverifying patient identification: an 'ID-verify alert', and an 'ID-reentry function'.

Results: The retract-and-reorder measurement tool effectively identified 170 of 223 events as wrong-patient electronic orders, resulting in a positive predictive value of 76.2% (95% CI 70.6% to 81.9%). Using this tool it was estimated that 5246 electronic orders were placed on wrong patients in 2009. In phase 2, 901 776 ordering sessions among 4028 providers were examined. Compared with control, the ID-verify alert reduced the odds of a retract-and-reorder event (OR 0.84, 95% CI 0.72 to 0.98), but the ID-reentry function reduced the odds by a larger magnitude (OR 0.60, 95% CI 0.50 to 0.71).

Discussion And Conclusion: Wrong-patient electronic orders occur frequently with computerized provider order entry systems, and electronic interventions can reduce the risk of these errors occurring.
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http://dx.doi.org/10.1136/amiajnl-2012-001055DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3638184PMC
August 2013

The impact of the heparin-induced thrombocytopenia (HIT) computerized alert on provider behaviors and patient outcomes.

J Am Med Inform Assoc 2011 Nov-Dec;18(6):783-8. Epub 2011 Jun 28.

Department of Medicine, NYU Langone Medical Center, New York 10010, USA.

Objective: The aim of this study was to measure the effect of an electronic heparin-induced thrombocytopenia (HIT) alert on provider ordering behaviors and on patient outcomes.

Materials And Methods: A pop-up alert was created for providers when an individual's platelet values had decreased by 50% or to <100,000/mm(3) in the setting of recent heparin exposure. The authors retrospectively compared inpatients admitted between January 24, 2008 and August 24, 2008 to a control group admitted 1 year prior to the HIT alert. The primary outcome was a change in HIT antibody testing. Secondary outcomes included an assessment of incidence of HIT antibody positivity, percentage of patients started on a direct thrombin inhibitor (DTI), length of stay and overall mortality.

Results: There were 1006 and 1081 patients in the control and intervention groups, respectively. There was a 33% relative increase in HIT antibody test orders (p=0.01), and 33% more of these tests were ordered the first day after the criteria were met when a pop-up alert was given (p=0.03). Heparin was discontinued in 25% more patients in the alerted group (p=0.01), and more direct thrombin inhibitors were ordered for them (p=0.03). The number who tested HIT antibody-positive did not differ, however, between the two groups (p=0.99). The length of stay and mortality were similar in both groups.

Conclusions: The HIT alert significantly impacted provider behaviors. However, the alert did not result in more cases of HIT being detected or an improvement in overall mortality. Our findings do not support implementation of a computerized HIT alert.
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Source
http://dx.doi.org/10.1136/amiajnl-2011-000138DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3197994PMC
February 2012