Impact of an electronic alert notification system embedded in radiologists' workflow on closed-loop communication of critical results: a time series analysis

Classification and Communication of Critical Findings in Emergency Radiology: A Scoping Review

PURPOSE

To identify the published standards for the classification and communication of critical actionable findings in emergency radiology and the associated facilitators and barriers to communication and message management or dissemination of such findings.

MATERIALS AND METHODS

Search terms for resources pertaining to critical findings (CFs) in emergency radiology were applied to two databases (PubMed, Embase). Screening of hits using the following pre-established inclusion and exclusion criteria were performed by three analysts with subsequent consensus discussion for discrepancies: (1) the resources include any standards for the classification and communication of imaging findings as critical, or (2) the resource discusses any facilitators to the communication of CFs, or (3) the resource discusses any barriers to the communication of CFs. Resources with explicit focus on a pediatric population or predominant focus on artificial intelligence or natural language processing were omitted. Accompanying gray literature search was used to expand included resources. Data extraction included year, country, resource type, scope or purpose, participants, context, standards to identifying or communicating CFs, facilitators and barriers, method type, recommendations, applicability, and disclosures.

RESULTS

Seventy-six resources were included in the final analysis, including 16 societal or commission guidelines. Among the guidelines, no standardized list of CFs was identified, with typical recommendations suggesting application of a local policy. Communication standards included direct closed-loop communication for high acuity findings, with more flexible communication channels for less acute findings. Applied interventions for CFs management most frequently fell into four categories: electronic (n = 10), hybrid (ie, electronic or administrative) (n = 3), feedback or education (n = 5), and administrative (n = 4).

CONCLUSION

There are published standards, policies, and interventions for the management of CFs in emergency radiology. Three-tier stratification (eg, critical, urgent, incidental) based on time sensitivity and severity is most common with most CFs necessitating closed-loop communication. Awareness of systemic facilitators and barriers should inform local policy development. Electronic and administrative communication pathways are useful adjuncts. Further research should offer comparative analyses of different CF interventions with regard to cost-effectiveness, notification time, and user feedback.

Adverse diagnostic events in hospitalised patients: a single-centre, retrospective cohort study

BACKGROUND

Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care.

METHODS

We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 days, complex clinical events, and none of the aforementioned high-risk criteria. Cases in higher-risk subgroups were over-sampled in predefined percentages. Each case was reviewed by two adjudicators trained to judge the likelihood of DE using the Safer Dx instrument; characterise harm, preventability and severity; and identify associated process failures using the Diagnostic Error Evaluation and Research Taxonomy modified for acute care. Cases with discrepancies or uncertainty about DE or impact were reviewed by an expert panel. We used descriptive statistics to report population estimates of harmful, preventable and severely harmful DEs by demographic variables based on the weighted sample, and characteristics of harmful DEs. Multivariable models were used to adjust association of process failures with harmful DEs.

RESULTS

Of 9147 eligible cases, 675 were randomly sampled within each subgroup: 100% of ICU transfers, 38.5% of deaths within 90 days, 7% of cases with complex clinical events and 2.4% of cases without high-risk criteria. Based on the weighted sample, the population estimates of harmful, preventable and severely harmful DEs were 7.2% (95% CI 4.66 to 9.80), 6.1% (95% CI 3.79 to 8.50) and 1.1% (95% CI 0.55 to 1.68), respectively. Harmful DEs were frequently characterised as delays (61.9%). Severely harmful DEs were frequent in high-risk cases (55.1%). In multivariable models, process failures in assessment, diagnostic testing, subspecialty consultation, patient experience, and history were significantly associated with harmful DEs.

CONCLUSIONS

We estimate that a harmful DE occurred in 1 of every 14 patients hospitalised on general medicine, the majority of which were preventable. Our findings underscore the need for novel approaches for adverse DE surveillance.

Patient-Centered Radiology Communications: Engaging Patients as Partners

Patient-centered care is a model in which, by bringing the patient's perspective to the design and delivery of health care, we can better meet patients' needs, enhancing the quality of care. Patient-centered care requires finding ways to communicate effectively with a diverse patient population that has various levels of health literacy, cultural backgrounds, and unique needs and preferences. Moreover, multimedia resources have the potential to inform and educate patients promoting greater independence. In this review, we discuss the fundamentals of communication with the different modes used in radiology and the key elements of effective communication. Then, we highlight five opportunities along the continuum of care in the radiology practice in which we can improve communications to empower our patients and families and strengthen this partnership. Lastly, we discuss the importance on communication training of the workforce, optimizing and seamlessly integrating technology solutions into our workflows, and the need for patient feedback in the design and delivery of care.

Artificial intelligence in cardiac computed tomography

Artificial Intelligence (AI) is a broad discipline of computer science and engineering. Modern application of AI encompasses intelligent models and algorithms for automated data analysis and processing, data generation, and prediction with applications in visual perception, speech understanding, and language translation. AI in healthcare uses machine learning (ML) and other predictive analytical techniques to help sort through vast amounts of data and generate outputs that aid in diagnosis, clinical decision support, workflow automation, and prognostication. Coronary computed tomography angiography (CCTA) is an ideal union for these applications due to vast amounts of data generation and analysis during cardiac segmentation, coronary calcium scoring, plaque quantification, adipose tissue quantification, peri-operative planning, fractional flow reserve quantification, and cardiac event prediction. In the past 5 years, there has been an exponential increase in the number of studies exploring the use of AI for cardiac computed tomography (CT) image acquisition, de-noising, analysis, and prognosis. Beyond image processing, AI has also been applied to improve the imaging workflow in areas such as patient scheduling, urgent result notification, report generation, and report communication. In this review, we discuss algorithms applicable to AI and radiomic analysis; we then present a summary of current and emerging clinical applications of AI in cardiac CT. We conclude with AI's advantages and limitations in this new field.

Medical imaging call centre: a communication success story

AIM

To evaluate utilisation of a medical imaging call centre (MICC) at a multi-site, academic radiology department, focusing on communication of critical, urgent, or significant unexpected findings.

MATERIALS AND METHODS

Institutional research ethics board approval was obtained. All calls made to MICC from 1 January to 31 December 2019 were reviewed retrospectively. The total number of calls, date, and reason of each call, level of report alert, and turnaround time (TAT) were recorded. Level 1, 2, and 3 alerts were defined as "potentially life-threatening new/unexpected findings", "could result in morbidity/mortality", or "not immediately life-threatening or urgent", respectively. TAT was defined as the time from alert request received by the MICC until acknowledgement of receipt by the referring physician, with a desired TAT of 60 min, 3 h, and 3 days for each level, respectively.

RESULTS

The MICC received 29,799 calls in 2019, on average 2,483 (range 1,989-3,098) calls per month. The most common indications for contacting the MICC were to request imaging reports to be expedited (14,916 calls, 50%) and issuing report alerts to communicate unexpected or urgent findings (7,060 calls, 24%). Average number and range of calls for Level 1, 2, and 3 alerts were 57 (39-80), 345 (307-388), and 187 (127-215) per month, respectively. Average TAT for Level 1, 2, and 3 report alerts were 59 min, 2 h 26 min, and 19 h 39 min, respectively.

CONCLUSION

The MICC received a large volume of calls and was a successful method for timely communication of unexpected or urgent imaging findings using a three-tiered alert system.

Teamwork on Patrol: Investigating Teamwork Processes and Underlaying Coordinating Mechanisms in a Police Training Program

The Big Five theory suggests that five components in teamwork are essential for team effectiveness in stressful environments. Furthermore, three coordinating mechanisms are claimed to be decisive to upholding and informing vital teamwork processes. Although much research has been conducted into the Big Five theory and its components, to the best of our knowledge, no study has yet been made of the relative importance of the three mechanisms and their impact on team effectiveness. Also, only a few studies have tried to investigate whether the components and the coordinating mechanisms are trainable. This study aims to make a theoretical contribution to the part of the theory focusing on the coordinating mechanisms. Secondly, it investigates whether training can improve team performance. Working in teams of two, 166 police officers participated in a simulated operational scenario. Correlational analyses indicated that all Big Five teamwork behaviors and coordinating mechanisms relate to external ratings of team performance. Only the mechanisms of Closed Loop Communication (CLC) and Shared Mental Model (SMM) predicted performance indicators, with SMM predicting above and beyond the effect of CLC. No effect of the training program was found. The study provides new evidence in a police situation that the most important coordinating mechanism of the Big Five theory is that of shared mental models, which in turn has consequences for the type of training needed.

Workflow Applications of Artificial Intelligence in Radiology and an Overview of Available Tools

In the past decade, there has been tremendous interest in applying artificial intelligence (AI) to improve the field of radiology. Currently, numerous AI applications are in development, with potential benefits spanning all steps of the imaging chain from test ordering to report communication. AI has been proposed as a means to optimize patient scheduling, improve worklist management, enhance image acquisition, and help radiologists interpret diagnostic studies. Although the potential for AI in radiology appears almost endless, the field is still in the early stages, with many uses still theoretical, in development, or limited to single institutions. Moreover, although the current use of AI in radiology has emphasized its clinical applications, some of which are in the distant future, it is increasingly clear that AI algorithms could also be used in the more immediate future for a variety of noninterpretive and quality improvement uses. Such uses include the integration of AI into electronic health record systems to reduce unwarranted variation in radiologists' follow-up recommendations and to improve other dimensions of radiology report quality. In the end, the potential of AI in radiology must be balanced with acknowledgment of its current limitations regarding generalizability and data privacy.

Deep learning-based automated detection of pulmonary embolism on CT pulmonary angiograms: No significant effects on report communication times and patient turnaround in the emergency department nine months after technical implementation

OBJECTIVES

Rapid communication of CT exams positive for pulmonary embolism (PE) is crucial for timely initiation of anticoagulation and patient outcome. It is unknown if deep learning automated detection of PE on CT Pulmonary Angiograms (CTPA) in combination with worklist prioritization and an electronic notification system (ENS) can improve communication times and patient turnaround in the Emergency Department (ED).

METHODS

In 01/2019, an ENS allowing direct communication between radiology and ED was installed. Starting in 10/2019, CTPAs were processed by a deep learning (DL)-powered algorithm for detection of PE. CTPAs acquired between 04/2018 and 06/2020 (n = 1808) were analysed. To assess the impact of the ENS and the DL-algorithm, radiology report reading times (RRT), radiology report communication time (RCT), time to anticoagulation (TTA), and patient turnaround times (TAT) in the ED were compared for three consecutive time periods. Performance measures of the algorithm were calculated on a per exam level (sensitivity, specificity, PPV, NPV, F1-score), with written reports and exam review as ground truth.

RESULTS

Sensitivity of the algorithm was 79.6 % (95 %CI:70.8-87.2%), specificity 95.0 % (95 %CI:92.0-97.1%), PPV 82.2 % (95 %CI:73.9-88.3), and NPV 94.1 % (95 %CI:91.4-96 %). There was no statistically significant reduction of any of the observed times (RRT, RCT, TTA, TAT).

CONCLUSION

DL-assisted detection of PE in CTPAs and ENS-assisted communication of results to referring physicians technically work. However, the mere clinical introduction of these tools, even if they exhibit a good performance, is not sufficient to achieve significant effects on clinical performance measures.

Electronic Health Record Transition and Impact on Screening Test Follow-Up

INTRODUCTION

Nonurgent clinically significant test results (CSTRs) are a common cause of missed and delayed diagnoses. However, little is known about the impact of electronic health record (EHR) transitions on CSTR follow-up. This study examines follow-up rates for three CSTRs (incidental pulmonary nodules [IPNs]), prostate-specific antigen [PSA], and Pap smears) before and after EHR transition.

METHODS

This is a retrospective cohort study at an urban tertiary medical center using an interrupted time series (ITS) design to assess monthly changes in CSTR follow-up-defined as completion of computed tomography chest imaging 5 to 13 months after first mention of an IPN in a radiology report; completion of a follow-up PSA test, urology visit, or prostate biopsy within 6 months of the first reported PSA > 4; or completion of a colposcopy or gynecology visit within 6 months of a first reported abnormal Pap smear. Patients were included with first-onset abnormal CSTRs for IPN, PSAs > 4, or abnormal Pap smears occurring in the 24 months before and after the EHR transition.

RESULTS

There were no significant differences in follow-up in the IPN or the Pap smear ITS models. In the PSA ITS model, follow-up was significantly decreasing (p = 0.0133) in the preintervention period, and there was a significant change in trend from intervention to postintervention (p = 0.0279).

CONCLUSION

EHR transition reversed a decreasing trend over time for PSA test follow-up, while IPN and Pap smear follow-up trends did not change significantly. Effects of EHR transition may differ by test studied.

Building an Ambulatory Safety Program at an Academic Health System

BACKGROUND

Patient safety has traditionally focused on the inpatient setting; however, there is an increased awareness of ambulatory safety risk. However, successful strategies and programs to mitigate risk in the ambulatory setting are lacking.

PROGRAM

In 2012, we started building a multidisciplinary ambulatory safety program at an academic health system. Our team was composed of clinical, administrative, and patient safety membership. Based on organizational needs, our program initially focused on the following: (1) safety reporting, (2) safety culture measurement, (3) medication safety, and (4) test result management.

WHAT WE DID

We were able to develop initiatives around safety reporting, safety culture survey administration, and medication safety and begin to work on test result management. Internal metrics were developed to measure performance and to drive improvement.

SAFETY REPORTING

When evaluating our ambulatory safety reports, we discovered that less than one-third of staff filing safety reports requested feedback. From 2013 to 2018, we tested various strategies to increase the rates of feedback to staff and ultimately found that a decentralized process that was supported by the ambulatory safety program could achieve rates of feedback of 90%.

SAFETY CULTURE MEASUREMENT

We administered the Agency for Healthcare Research and Quality Medical Office Survey in 2012, 2014, and 2016, achieving a more than 70% response rate across 70 unique ambulatory areas. Data from these surveys were shared with senior hospital leadership, local departmental directors, and managers and ultimately with frontline staff focusing on two key survey areas: communication openness and communication about error.

MEDICATION SAFETY

From 2012 to 2014, our rates of ambulatory medication reconciliation increased to more than 90% in both primary care and specialty practices in our homegrown electronic medical record system. From 2015 to 2016, rates of ambulatory medication reconciliation in our new vendor-based electronic medical record were 73% as of August 2017.

CONCLUSIONS

We were able to build an infrastructure to focus and support ambulatory safety efforts on safety reporting, safety culture change, and medication reconciliation with a team dedicated to ambulatory-focused safety risks and encountered many challenges along the way. Currently, we are expanding our program to concentrate on test result follow-up to prevent missed and delayed diagnosis and medication error reduction.

An International Survey of Quality and Safety Programs in Radiology

PURPOSE

The aim of this study was to determine the status of radiology quality improvement programs in a variety of selected nations worldwide.

METHODS

A survey was developed by select members of the International Economics Committee of the American College of Radiology on quality programs and was distributed to committee members. Members responded on behalf of their country. The 51-question survey asked about 12 different quality initiatives which were grouped into 4 themes: departments, users, equipment, and outcomes. Respondents reported whether a designated type of quality initiative was used in their country and answered subsequent questions further characterizing it.

RESULTS

The response rate was 100% and represented Australia, Canada, China, England, France, Germany, India, Israel, Japan, the Netherlands, Russia, and the United States. The most frequently reported quality initiatives were imaging appropriateness (91.7%) and disease registries (91.7%), followed by key performance indicators (83.3%) and morbidity and mortality rounds (83.3%). Peer review, equipment accreditation, radiation dose monitoring, and structured reporting were reported by 75.0% of respondents, followed by 58.3% of respondents for quality audits and critical incident reporting. The least frequently reported initiatives included Lean/Kaizen exercises and physician performance assessments, implemented by 25.0% of respondents.

CONCLUSION

There is considerable diversity in the quality programs used throughout the world, despite some influence by national and international organizations, from whom further guidance could increase uniformity and optimize patient care in radiology.

Contextual Structured Reporting in Radiology: Implementation and Long-Term Evaluation in Improving the Communication of Critical Findings

Structured reporting contributes to the completeness of radiology reports and improves quality. Both the content and the structure are essential for successful implementation of structured reporting. Contextual structured reporting is tailored to a specific scenario and can contain information retrieved from the context. Critical findings detected by imaging need urgent communication to the referring physician. According to guidelines, the occurrence of this communication should be documented in the radiology reports and should contain when, to whom and how was communicated. In free-text reporting, one or more of these required items might be omitted. We developed a contextual structured reporting template to ensure complete documentation of the communication of critical findings. The WHEN and HOW items were included automatically, and the insertion of the WHO-item was facilitated by the template. A pre- and post-implementation study demonstrated a substantial improvement in guideline adherence. The template usage improved in the long-term post-implementation study compared with the short-term results. The two most often occurring categories of critical findings are “infection / inflammation” and “oncology”, corresponding to the a large part of urgency level 2 (to be reported within 6 h) and level 3 (to be reported within 6 days), respectively. We conclude that contextual structured reporting is feasible for required elements in radiology reporting and for automated insertion of context-dependent data. Contextual structured reporting improves guideline adherence for communication of critical findings.

Assessment of actionable findings in radiology reports

PURPOSE

The American College of Radiology (ACR) Actionable Reporting Work Group defined three categories of imaging findings that require additional, nonroutine communication with the referring physician because of their urgency or unexpectedness. The objective of this study was to determine the prevalence of actionable findings in radiology reports, and to assess how well radiologists agree on the categorisation of actionable findings.

METHOD

From 124,909 consecutive radiology reports stored in the electronic health record system of a large university hospital, 1000 reports were randomly selected. Two radiologists independently annotated all actionable findings according to the three categories of urgency defined by the ACR Work Group. Annotation differences were resolved in a consensus meeting and a final category was established for each report. Interannotator agreement was measured by accuracy and the kappa coefficient.

RESULTS

The prevalence of the three categories of actionable findings together was 32.5 %. Of all reports, 10.9 % were from patients seen in the emergency department. Prevalence of actionable findings for these patients (45.9 %) was considerably higher than for patients in routine clinical care (30.9 %). Interannotator agreement scores on the categorisation of actionable findings were 0.812 for accuracy and 0.616 for kappa coefficient.

CONCLUSIONS

The prevalence of actionable findings in radiology reports is high. The interannotator agreement scores are moderate, indicating that categorisation of actionable findings is a difficult task. To avoid unneeded increase in the workload of radiologists, in particular in routine practice, clinical context may need to be considered in deciding whether a finding is actionable.

Assessing information sources to elucidate diagnostic process errors in radiologic imaging - a human factors framework

Objective

To assess information sources that may elucidate errors related to radiologic diagnostic imaging, quantify the incidence of potential safety events from each source, and quantify the number of steps involved from diagnostic imaging chain and socio-technical factors.

Materials and Methods

This retrospective, Institutional Review Board-approved study was conducted at the ambulatory healthcare facilities associated with a large academic hospital. Five information sources were evaluated: an electronic safety reporting system (ESRS), alert notification for critical result (ANCR) system, picture archive and communication system (PACS)-based quality assurance (QA) tool, imaging peer-review system, and an imaging computerized physician order entry (CPOE) and scheduling system. Data from these sources (January-December 2015 for ESRS, ANCR, QA tool, and the peer-review system; January-October 2016 for the imaging ordering system) were collected to quantify the incidence of potential safety events. Reviewers classified events by the step(s) in the diagnostic process they could elucidate, and their socio-technical factors contributors per the Systems Engineering Initiative for Patient Safety (SEIPS) framework.

Results

Potential safety events ranged from 0.5% to 62.1% of events collected from each source. Each of the information sources contributed to elucidating diagnostic process errors in various steps of the diagnostic imaging chain and contributing socio-technical factors, primarily Person, Tasks, and Tools and Technology.

Discussion

Various information sources can differentially inform understanding diagnostic process errors related to radiologic diagnostic imaging.

Conclusion

Information sources elucidate errors in various steps within the diagnostic imaging workflow and can provide insight into socio-technical factors that impact patient safety in the diagnostic process.

Barriers and facilitators impacting reliability of the electronic health record-facilitated total testing process

OBJECTIVE

Despite ongoing efforts to improve reliability of the total testing process (TTP), breakdowns continue to occur resulting in diagnostic delays and suboptimal patient outcomes. We performed an exploratory study to identify factors that impact TTP reliability in electronic health record (EHR)-enabled care.

MATERIALS AND METHODS

We interviewed experts at three large EHR-enabled health care organizations and identified all TTP steps performed from clinician test ordering to result communication to patients. Findings from all sites were combined to develop a detailed process map of known TTP activities. We additionally asked experts about factors that positively or negatively impacted TTP reliability at each step. We describe the specific TTP steps identified and associated barriers and facilitators to TTP reliability.

RESULTS

We interviewed 39 experts involved in or overseeing the TTP. Most TTP activities identified were similar across sites, but we found significant differences with test order transmission to diagnostic services and relay of results back to clinicians and patients. Twenty-five unique barriers were identified related to technology and EHR usability issues, time and resource constraints, suboptimal clinic workflows, patient-related factors, information access limitations, and insufficient clinician training. Twenty-four unique facilitators were identified related to personnel training, workflow optimization and standardization, helpful EHR features, and improved electronic communication between clinics and diagnostic services.

DISCUSSION

Barriers related to EHR usability and with communication between clinicians and diagnostic services increase TTP vulnerability and should be targeted by future efforts to improve process reliability. Several facilitators identified in the study could inform future strategies and solutions to improve TTP reliability.

Classifying Safety Events Related to Diagnostic Imaging From a Safety Reporting System Using a Human Factors Framework

Purpose:

To measure diagnostic imaging safety events reported to an electronic safety reporting system (ESRS) and assess steps where they occurred within the diagnostic imaging workflow and contributing socio-technical factors.

Methods:

We evaluated all ESRS safety reports related to diagnostic imaging during calendar 2015 at an academic medical center with 50,000 admissions, 950,000 ambulatory visits, and performing 680,000 diagnostic imaging studies annually. Each report was assigned a 0-4 harm score by the reporter; we classified scores of 2 (minor harm) to 4 (death) as “potential harm”. Two reviewers manually classified reports into steps involved in the diagnostic imaging chain and socio-technical factors per the Systems Engineering Initiative for Patient Safety (SEIPS) framework. Kappa measured inter-reviewer agreement on 10% of reports. The percentage of reports that could cause “potential harm” was compared for each step and socio-technical factor using chi-square analysis.

Results:

Of 11,570 safety reports submitted in 2015, 854 (7%) were related to diagnostic imaging. Although the most common step was Imaging Procedure (54% of reports), potential harm occurred more in Report Communication (Odds Ratio=2.36, p=0.05). Person factors most commonly contributed to safety reports (71%). Potential harm occurred more in safety reports that were related to Task compared to Person factors (OR=5.03, p<0.0001). Kappa was 0.79.

Conclusion:

Safety events were related to diagnostic imaging in 7% of reports and potential harm occurred primarily during Imaging Procedure and Report Communication. Safety events were attributed to multifactorial socio-technical factors. Further work is necessary to decrease safety events related to diagnostic imaging.

Assessing Documentation of Critical Imaging Result Follow-up Recommendations in Emergency Department Discharge Instructions

To facilitate follow-up of critical test results across transitions in patient care settings, we implemented an electronic discharge module that enabled care providers to include follow-up recommendations in the discharge instructions. We assessed the impact of this module on documentation of follow-up recommendations for critical imaging findings in Emergency Department (ED) discharge instructions. We studied 240 patients with critical imaging findings discharged from the ED before (n = 80) and after (n = 160) implementation of the module. We manually reviewed hand-written forms and electronic discharge instructions to determine if follow-up recommendations were documented. Follow-up recommendations in ED discharge instructions increased from 60.0% (48/80) to 73.8% (118/160) post-module implementation (p = 0.03), a relative increase of 23%. There was no significant change in the rate of documented critical imaging findings in the discharge instructions (77.5% [62/80] before the intervention and 76.9% [123/160] after the intervention; p = 0.91). Implementation of a discharge module was associated with increased documentation of critical imaging finding follow-up recommendations in ED discharge instructions. However, one in four patients still did not receive adequate follow-up recommendations, suggesting further opportunities for performance improvement exist.

The Impact of Automated Notification on Follow-up of Actionable Tests Pending at Discharge: a Cluster-Randomized Controlled Trial

BACKGROUND

Follow-up of tests pending at discharge (TPADs) is poor. We previously demonstrated a twofold increase in awareness of any TPAD by attendings and primary care physicians (PCPs) using an automated email intervention OBJECTIVE: To determine whether automated notification improves documented follow-up for actionable TPADs DESIGN: Cluster-randomized controlled trial SUBJECTS: Attendings and PCPs caring for adult patients discharged from general medicine and cardiology services with at least one actionable TPAD between June 2011 and May 2012 INTERVENTION: An automated system that notifies discharging attendings and network PCPs of finalized TPADs by email MAIN MEASURES: The primary outcome was the proportion of actionable TPADs with documented action determined by independent physician review of the electronic health record (EHR). Secondary outcomes included documented acknowledgment, 30-day readmissions, and adjusted median days to documented follow-up.

KEY RESULTS

Of the 3378 TPADs sampled, 253 (7.5%) were determined to be actionable by physician review. Of these, 150 (123 patients discharged by 53 attendings) and 103 (90 patients discharged by 44 attendings) were assigned to intervention and usual care groups, respectively, and underwent chart review. The proportion of actionable TPADs with documented action was 60.7 vs. 56.3% (p = 0.82) in the intervention vs. usual care groups, similar for documented acknowledgment. The proportion of patients with actionable TPADs readmitted within 30 days was 22.8 vs. 31.1% in the intervention vs. usual care groups (p = 0.24). The adjusted median days [95% CI] to documented action was 9 [6.2, 11.8] vs. 14 [10.2, 17.8] (p = 0.04) in the intervention vs. usual care groups, similar for documented acknowledgment. In sub-group analysis, the intervention had greater impact on documented action for patients with network PCPs compared with usual care (70 vs. 50%, p = 0.03).

CONCLUSIONS

Automated notification of actionable TPADs shortened time to action but did not significantly improve documented follow-up, except for network-affiliated patients. The high proportion of actionable TPADs without any documented follow-up (~ 40%) represents an ongoing safety concern.

CLINICAL TRIALS IDENTIFIER

NCT01153451.

Semiautomated System for Nonurgent, Clinically Significant Pathology Results

BACKGROUND

Failure of timely test result follow-up has consequences including delayed diagnosis and treatment, added costs, and potential patient harm. Closed-loop communication is key to ensure clinically significant test results (CSTRs) are acknowledged and acted upon appropriately. A previous implementation of the Alert Notification of Critical Results (ANCR) system to facilitate closed-loop communication of imaging CSTRs yielded improved communication of critical radiology results and enhanced adherence to institutional CSTR policies.

OBJECTIVE

This article extends the ANCR application to pathology and evaluates its impact on closed-loop communication of new malignancies, a common and important type of pathology CSTR.

MATERIALS AND METHODS

This Institutional Review Board-approved study was performed at a 150-bed community, academically affiliated hospital. ANCR was adapted for pathology CSTRs. Natural language processing was used on 30,774 pathology reports 13 months pre- and 13 months postintervention, identifying 5,595 reports with malignancies. Electronic health records were reviewed for documented acknowledgment for a random sample of reports. Percent of reports with documented acknowledgment within 15 days assessed institutional policy adherence. Time to acknowledgment was compared pre- versus postintervention and postintervention with and without ANCR alerts. Pathologists were surveyed regarding ANCR use and satisfaction.

RESULTS

Acknowledgment within 15 days was documented for 98 of 107 (91.6%) pre- and 89 of 103 (86.4%) postintervention reports (p = 0.2294). Median time to acknowledgment was 7 days (interquartile range [IQR], 3, 11) preintervention and 6 days (IQR, 2, 10) postintervention (p = 0.5083). Postintervention, median time to acknowledgment was 2 days (IQR, 1, 6) for reports with ANCR alerts versus 6 days (IQR, 2.75, 9) for reports without alerts (p = 0.0351). ANCR alerts were sent on 15 of 103 (15%) postintervention reports. All pathologists reported that the ANCR system positively impacted their workflow; 75% (three-fourths) felt that the ANCR system improved efficiency of communicating CSTRs.

CONCLUSION

ANCR expansion to facilitate closed-loop communication of pathology CSTRs was favorably perceived and associated with significant improved time to documented acknowledgment for new malignancies. The rate of adherence to institutional policy did not improve.

Critical Test Result Notification via Mobile Phone-Based Automated Text Message System in the Radiologic Field: Single Institutional Experience

PURPOSE

To investigate the feasibility of sharing critical test result (CTR) notifications (CTRNs) via automated text messaging.

MATERIALS AND METHODS

CTRNs via automated text messaging was used to notify physicians of CTRs in a tertiary hospital with 1,786 beds. From June 2016 to September 2016, notifications for 545 CTRs were given via a CTRN system. Among them, 490 CTRs (292 male and 198 female patients; mean age, 53.6 years old [range, 1-88]) were included in analysis. CTR levels (CTRLs) were assigned to four categories (CTRL1 to CTRL3 and unclassified) when reported, and reclassified into three CTRLs according to their clinical relevance and urgency. Response time was defined as time lapse between CTR reporting and documentation by physicians. Analysis of variance was performed to compare response times according to CTRLs and patients' location.

RESULTS

Corresponding actions were taken in 404 of 490 cases (82.4%) without any delayed CTRN-related morbidity. There were 15 CTRL1 (3.1%), 50 CTRL2 (10.2%), 112 CTRL3 (22.9%) cases, and the remaining 313 CTRL cases were unclassified. After reclassification, CTRL1, CTRL2, and CTRL3 were 81 (16.5%), 177 (36.1%), and 232 cases (47.3%), respectively. Response time of reclassified CTRL3 was significantly longer than that of reclassified CTRL1 (median 23.0, [interquartile range 2.0-133.5] hours versus 4.0 [0.0-22.0] hours; P < .001). Response time of outpatient cases (80.0 [6.0 to 157.0] hours) was significantly longer (P < .001) than those of inpatient (3.0 [0.0-16.0]) and emergency department cases (5.0 [1.0-21.0]).

CONCLUSION

Automated text messaging could be a feasible option for CTRNs in the radiologic field. Further large-scale investigations regarding efficiency of this system are warranted.

Electronic Triggers to Identify Delays in Follow-Up of Mammography: Harnessing the Power of Big Data in Health Care

PURPOSE

We previously developed electronic triggers to automatically flag records for patients experiencing potential delays in diagnostic evaluation for certain cancers. Because of the unique clinical, logistic, and legal aspects of mammography, this study was conducted to evaluate the effectiveness of a trigger to flag delayed follow-up on mammography.

METHODS

An algorithm was developed to detect delays in follow-up of abnormal mammographic results (>60 days for BI-RADS® 0, 4, and 5 and >7 months for BI-RADS 3) using clinical data in the electronic health record. Flagged records were then manually reviewed to determine the trigger's performance characteristics (positive and negative predictive value, sensitivity, and specificity). The frequency of delays and patient communication related to abnormal results, reasons for lack of follow-up, and whether patients were subsequently diagnosed with breast cancer were also assessed.

RESULTS

Of 365,686 patients seen between January 1, 2010, and May 31, 2015, the trigger identified 2,129 patients with abnormal findings on mammography, of whom it flagged 552 as having delays in follow-up. From these, review of 400 randomly selected records revealed 283 true delays (positive predictive value, 71%; 95% confidence interval, 66%-75%), including 280 records without any documented plan and three patients with plans that were not adhered to. Transcription and reporting inconsistencies were identified in 27% of externally performed mammographic reports. Only 335 records (84%) contained specific documentation that the patient was informed of the abnormal result.

CONCLUSIONS

Care delays appear to continue despite federal laws requiring patient notification of mammographic results within 30 days. Clinical application of mammography-related triggers could help detect these delays.