National Survey of Patient Safety Experiences in Hospital Medicine During the COVID-19 Pandemic.

BACKGROUND: During the COVID-19 pandemic, hospitals were caring for increasing numbers of patients with a novel and highly contagious respiratory illness, forcing adaptations in care delivery. The objective of this study was to understand the impact of these adaptations on patient safety in hospital medicine. METHODS: The authors conducted a nationwide survey to understand patient safety challenges experienced by hospital medicine clinicians during the COVID-19 pandemic. The survey was distributed to members of the Society of Hospital Medicine via an e-mail listserv. It consisted of closed- and open-ended questions to elicit respondents' experience in five domains: error reporting and communication, staffing, equipment, personal protective equipment (PPE) and isolation practices, and infrastructure. Quantitative questions were reported as counts and percentages; qualitative responses were coded and analyzed for relevant themes. RESULTS: Of 196 total responses, 167 respondents (85.2%) were attending physicians and 85 (43.8%) practiced at teaching hospitals. Safety concerns commonly identified included nursing shortages (71.0%), limiting patient interactions to conserve PPE (61.9%), and feeling that one was practicing in a more hazardous environment (61.4%). In free-text responses, clinicians described poor outcomes and patient decompensation due to provider and equipment shortages, as well as communication lapses and diagnostic errors resulting from decreased patient contact and the need to follow isolation protocols. CONCLUSION: Efforts made to accommodate shortages in staff and equipment, adapt to limited PPE, and enforce isolation policies had unintended consequences that affected patient safety and created a more hazardous environment characterized by less efficient care, respiratory decompensations, diagnostic errors, and poor communication with patients.

Retrospective cohort study of wrong-patient imaging order errors: how many reach the patient?

Studying near-miss errors is essential to preventing errors from reaching patients. When an error is committed, it may be intercepted (near-miss) or it will reach the patient; estimates of the proportion that reach the patient vary widely. To better understand this relationship, we conducted a retrospective cohort study using two objective measures to identify wrong-patient imaging order errors involving radiation, estimating the proportion of errors that are intercepted and those that reach the patient. This study was conducted at a large integrated healthcare system using data from 1 January to 31 December 2019. The study used two outcome measures of wrong-patient orders: (1) wrong-patient orders that led to misadministration of radiation reported to the New York Patient Occurrence Reporting and Tracking System (NYPORTS) (misadministration events); and (2) wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder (RAR) measure, a measure identifying orders placed for a patient, retracted and rapidly reordered by the same clinician on a different patient (near-miss events). All imaging orders that involved radiation were extracted retrospectively from the healthcare system data warehouse. Among 293 039 total eligible orders, 151 were wrong-patient orders (3 misadministration events, 148 near-miss events), for an overall rate of 51.5 per 100 000 imaging orders involving radiation placed on the wrong patient. Of all wrong-patient imaging order errors, 2% reached the patient, translating to 50 near-miss events for every 1 error that reached the patient. This proportion provides a more accurate and reliable estimate and reinforces the utility of systematic measure of near-miss errors as an outcome for preventative interventions.

Effect of restricting electronic health records on clinician efficiency: substudy of a randomized clinical trial.

A prior randomized controlled trial (RCT) showed no significant difference in wrong-patient errors between clinicians assigned to a restricted electronic health record (EHR) configuration (limiting to 1 record open at a time) versus an unrestricted EHR configuration (allowing up to 4 records open concurrently). However, it is unknown whether an unrestricted EHR configuration is more efficient. This substudy of the RCT compared clinician efficiency between EHR configurations using objective measures. All clinicians who logged onto the EHR during the substudy period were included. The primary outcome measure of efficiency was total active minutes per day. Counts were extracted from audit log data, and mixed-effects negative binomial regression was performed to determine differences between randomized groups. Incidence rate ratios (IRRs) were calculated with 95% confidence intervals (CIs). Among a total of 2556 clinicians, there was no significant difference between unrestricted and restricted groups in total active minutes per day (115.1 vs 113.3 min, respectively; IRR, 0.99; 95% CI, 0.93-1.06), overall or by clinician type and practice area.

Examining medication ordering errors using AHRQ network of patient safety databases.

BACKGROUND: Studies examining the effects of computerized order entry (CPOE) on medication ordering errors demonstrate that CPOE does not consistently prevent these errors as intended. We used the Agency for Healthcare Research and Quality (AHRQ) Network of Patient Safety Databases (NPSD) to investigate the frequency and degree of harm of reported events that occurred at the ordering stage, characterized by error type. MATERIALS AND METHODS: This was a retrospective observational study of safety events reported by healthcare systems in participating patient safety organizations from 6/2010 through 12/2020. All medication and other substance ordering errors reported to NPSD via common format v1.2 between 6/2010 through 12/2020 were analyzed. We aggregated and categorized the frequency of reported medication ordering errors by error type, degree of harm, and demographic characteristics. RESULTS: A total of 12 830 errors were reported during the study period. Incorrect dose accounted for 3812 errors (29.7%), followed by incorrect medication 2086 (16.3%), and incorrect duration 765 (6.0%). Of 5282 events that reached the patient and had a known level of severity, 12 resulted in death, 4 resulted in severe harm, 45 resulted in moderate harm, 341 resulted in mild harm, and 4880 resulted in no harm. CONCLUSION: Incorrect dose and incorrect drug orders were the most commonly reported and harmful types of medication ordering errors. Future studies should aim to develop and test interventions focused on CPOE to prevent medication ordering errors, prioritizing wrong-dose and wrong-drug errors.

Observation and Patients' Perceptions of Incorporating Their Photograph Into the Electronic Health Record.

OBJECTIVES: Wrong-patient errors are common and have the potential to cause serious harm. The Office of the National Coordinator for Health Information Technology Patient Identification SAFER Guide recommends displaying patient photographs in electronic health record (EHR) systems to facilitate patient identification and reduce wrong-patient errors. A potential barrier to implementation is patient refusal; however, patients' perceptions about having their photograph captured during registration and integrated into the EHR are unknown. METHODS: The study was conducted in an emergency department (ED) and primary care outpatient clinic within a large integrated health system in New York City. The study consisted of 2 components: (1) direct observation of the registration process to quantify the frequency of patient refusals and (2) semistructured interviews to elicit patients' feedback on perceived benefits and barriers to integrating their photograph into the EHR. RESULTS: Of 172 registrations where patients were asked to take a photograph for patient identification, 0 refusals were observed (ED, 0 of 87; primary care outpatient clinic, 0 of 85). A convenience sample of 30 patients were interviewed (female, 70%; age ≥55 years, 43%; Hispanic/Latino, 67%; Black, 23%). Perceived benefits of integrating patient photographs into the EHR included improved security (40%), improved patient identification (23%), and ease of registration (17%). A small proportion of patients raised privacy concerns. CONCLUSIONS: Patient refusal was not found to be a barrier to implementation of patient photographs in the EHR. Efforts to identify and address other potential barriers would help ensure that the highest proportion of patients has photographs in their medical record.

Critical Care Clinicians' Experiences of Patient Safety During the COVID-19 Pandemic.

OBJECTIVE: It is unknown how hospital- and systems-level factors have impacted patient safety in the intensive care unit (ICU) during the COVID-19 pandemic. We sought to understand how the pandemic has exacerbated preexisting patient safety issues and created novel patient safety challenges in ICUs in the United States. METHODS: We performed a national, multi-institutional, mixed-methods survey of critical care clinicians to elicit experiences related to patient safety during the pandemic. The survey was disseminated via email through the Society of Critical Care Medicine listserv. Data were reported as valid percentages, compared by COVID caseload and peak of the pandemic; free-text responses were analyzed and coded for themes. RESULTS: We received 335 survey responses. On general patient safety, 61% felt that conditions were more hazardous when compared with the prepandemic period. Those who took care of mostly COVID-19 patients were more likely to perceive that care was more hazardous (odds ratio, 4.89; 95% CI, 2.49-9.59) compared with those who took care of mostly non-COVID-19 or no COVID-19 patients. In free-text responses, providers identified patient safety risks related to pandemic adaptations, such as ventilator-related lung injury, medication and diagnostic errors, oversedation, oxygen device removal, and falls. CONCLUSIONS: Increased COVID-19 case burden was significantly associated with perceptions of a less safe patient care environment by frontline ICU clinicians. Results of the qualitative analysis identified specific patient safety hazards in ICUs across the United States as downstream consequences of hospital and provider strain during periods of the COVID-19 pandemic.

"What's in a name?" Identification of newborn infants at birth using their given names.

OBJECTIVE: To determine the proportion of pregnant women who selected names for their babies to be born and were willing to disclose them for use in hospital systems, thereby potentially reducing infant identification errors. STUDY DESIGN: Survey of pregnant women admitted to postpartum or antepartum units at a large academic hospital. Descriptive analyses were conducted to determine the proportion who had chosen names prior to delivery. Chi-square tests and calculated odds ratios assessed the association with demographic and pregnancy factors. RESULTS: Of postpartum participants, 79.0% had names for their newborns at birth. This proportion was significantly lower in self-identified non-Hispanic, white, and married women. Of antepartum participants, 65.7% had selected a name at the time of survey. CONCLUSION: Most participants had names chosen for use at birth. This finding was consistent across demographic and pregnancy characteristics, supporting the feasibility of using given names for newborns in hospital systems at birth.

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.

Wrong-Patient Orders in Obstetrics.

OBJECTIVE: To compare rates of wrong-patient orders among patients on obstetric units compared with reproductive-aged women admitted to medical-surgical units. METHODS: This was an observational study conducted in a large health system in New York between January 1, 2016, and December 31, 2018. The primary outcome was near-miss wrong-patient orders identified using the National Quality Forum-endorsed Wrong-Patient Retract-and-Reorder measure. All electronic orders placed for eligible patients during the study period were extracted retrospectively from the health system data warehouse, and the unit of analysis was the order session (consecutive orders placed by a single clinician for a patient within 60 minutes). Multilevel logistic regression models were used to estimate odds ratios (ORs) and 95% CIs comparing the probability of retract-and-reorder events in obstetric and medical-surgical units, overall, and in subgroups defined by clinician type and order timing. RESULTS: Overall, 1,329,463 order sessions were placed during the study period, including 676,643 obstetric order sessions (from 45,436 patients) and 652,820 medical-surgical order sessions (from 12,915 patients). The rate of 79.5 retract-and-reorder events per 100,000 order sessions in obstetric units was significantly higher than the rate in the general medical-surgical population of 42.3 per 100,000 order sessions (OR 1.98, 95% CI 1.64-2.39). The obstetric retract-and-reorder event rate was significantly higher for attending physicians and house staff compared with advanced practice clinicians. There were no significant differences in error rates between day and night shifts. CONCLUSION: Order errors occurred more frequently on obstetric units compared with medical-surgical units. Systems strategies shown to decrease these events in other high-risk specialties should be explored in obstetrics to render safer maternity care.

Contributing Factors for Pediatric Ambulatory Diagnostic Process Errors: Project RedDE.

BACKGROUND: Pediatric ambulatory diagnostic errors (DEs) occur frequently. We used root cause analyses (RCAs) to identify their failure points and contributing factors. METHODS: Thirty-one practices were enrolled in a national QI collaborative to reduce 3 DEs occurring at different stages of the diagnostic process: missed adolescent depression, missed elevated blood pressure (BP), and missed actionable laboratory values. Practices were encouraged to perform monthly "mini-RCAs" to identify failure points and prioritize interventions. Information related to process steps involved, specific contributing factors, and recommended interventions were reported monthly. Data were analyzed using descriptive statistics and Pareto charts. RESULTS: Twenty-eight (90%) practices submitted 184 mini-RCAs. The median number of mini-RCAs submitted was 6 (interquartile range, 2-9). For missed adolescent depression, the process step most commonly identified was the failure to screen (68%). For missed elevated BP, it was the failure to recognize (36%) and act on (28%) abnormal BP. For missed actionable laboratories, failure to notify families (23%) and document actions on (19%) abnormal results were the process steps most commonly identified. Top contributing factors to missed adolescent depression included patient volume (16%) and inadequate staffing (13%). Top contributing factors to missed elevated BP included patient volume (12%), clinic milieu (9%), and electronic health records (EHRs) (8%). Top contributing factors to missed actionable laboratories included written communication (13%), EHR (9%), and provider knowledge (8%). Recommended interventions were similar across errors. CONCLUSIONS: EHR-based interventions, standardization of processes, and cross-training may help decrease DEs in the pediatric ambulatory setting. Mini-RCAs are useful tools to identify their contributing factors and interventions.

Wrong-Patient Ordering Errors in Peripartum Mother-Newborn Pairs: A Unique Patient-Safety Challenge in Obstetrics.

Because maternal morbidity and mortality remain persistent challenges to the U.S. health care system, efforts to improve inpatient patient safety are critical. One important aspect of ensuring patient safety is reducing medical errors. However, obstetrics presents a uniquely challenging environment for safe ordering practices. When mother-newborn pairs are admitted in the postpartum setting with nearly identical names in the medical record (for example, Jane Doe and Janegirl Doe), there is a potential for wrong-patient medication ordering errors. This can lead to harm from the wrong patient receiving a medication or diagnostic test, especially a newborn receiving an adult dose of medication, as well as delaying treatment for the appropriate patient. We describe two clinical scenarios of wrong-patient ordering errors between mother-newborn pairs. The first involves an intravenous labetalol order that was placed for a postpartum patient but was released from the automated dispensing cabinet under the newborn's name. The medication was administered correctly, but an automatic order for labetalol was generated in the neonate's chart. Another scenario involves a woman presenting in labor with acute psychotic symptoms. The psychiatry service placed a note and orders for antipsychotic medications in the neonate's chart. These orders were cancelled shortly thereafter and replaced for the mother. These scenarios illustrate this specific patient-safety concern inherent in the treatment of mother-newborn pairs and highlight that perinatal units should evaluate threats to patient safety embedded in the unique mother-newborn relationship and develop strategies to reduce risk.

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

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 × 10-9). 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 × 10-5). 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.

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

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.

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

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.

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.