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

Medical Home Implementation and Follow-Up of Cancer-Related Abnormal Test Results in the Veterans Health Administration

Importance

Lack of timely follow-up of cancer-related abnormal test results can lead to delayed or missed diagnoses, adverse cancer outcomes, and substantial cost burden for patients. Care delivery models, such as the Veterans Affairs' (VA) Patient-Aligned Care Team (PACT), which aim to improve patient-centered care coordination, could potentially also improve timely follow-up of abnormal test results. PACT was implemented nationally in the VA between 2010 and 2012.

Objective

To evaluate the long-term association between PACT implementation and timely follow-up of abnormal test results related to the diagnosis of 5 different cancers.

Design, Setting, and Participants

This multiyear retrospective cohort study used 14 years of VA data (2006-2019), which were analyzed using panel data-based random-effects linear regressions. The setting included all VA clinics and facilities. The participants were adult patients who underwent diagnostic testing related to 5 different cancers and had abnormal test results. Data extraction and statistical analyses were performed from September 2021 to December 2023.

Exposure

Calendar years denoting preperiods and postperiods of PACT implementation, and the PACT Implementation Progress Index Score denoting the extent of implementation in each VA clinic and facility.

Main Outcome and Measure

Percentage of potentially missed timely follow-ups of abnormal test results.

Results

This study analyzed 6 data sets representing 5 different types of cancers. During the initial years of PACT implementation (2010 to 2013), percentage of potentially missed timely follow-ups decreased between 3 to 7 percentage points for urinalysis suggestive of bladder cancer, 12 to 14 percentage points for mammograms suggestive of breast cancer, 19 to 22 percentage points for fecal tests suggestive of colorectal cancer, and 6 to 13 percentage points for iron deficiency anemia laboratory tests suggestive of colorectal cancer, with no statistically significant changes for α-fetoprotien tests and lung cancer imaging. However, these beneficial reductions were not sustained over time. Better PACT implementation scores were associated with a decrease in potentially missed timely follow-up percentages for urinalysis (0.3-percentage point reduction [95% CI, -0.6 to -0.1] with 1-point increase in the score), and laboratory tests suggestive of iron deficiency anemia (0.5-percentage point reduction [95% CI,-0.8 to -0.2] with 1-point increase in the score).

Conclusions and Relevance

This cohort study found that implementation of PACT in the VA was associated with a potential short-term improvement in the quality of follow-up for certain test results. Additional multifaceted sustained interventions to reduce missed test results are required to prevent care delays.

Developing electronic clinical quality measures to assess the cancer diagnostic process

OBJECTIVE

Measures of diagnostic performance in cancer are underdeveloped. Electronic clinical quality measures (eCQMs) to assess quality of cancer diagnosis could help quantify and improve diagnostic performance.

MATERIALS AND METHODS

We developed 2 eCQMs to assess diagnostic evaluation of red-flag clinical findings for colorectal (CRC; based on abnormal stool-based cancer screening tests or labs suggestive of iron deficiency anemia) and lung (abnormal chest imaging) cancer. The 2 eCQMs quantified rates of red-flag follow-up in CRC and lung cancer using electronic health record data repositories at 2 large healthcare systems. Each measure used clinical data to identify abnormal results, evidence of appropriate follow-up, and exclusions that signified follow-up was unnecessary. Clinicians reviewed 100 positive and 20 negative randomly selected records for each eCQM at each site to validate accuracy and categorized missed opportunities related to system, provider, or patient factors.

RESULTS

We implemented the CRC eCQM at both sites, while the lung cancer eCQM was only implemented at the VA due to lack of structured data indicating level of cancer suspicion on most chest imaging results at Geisinger. For the CRC eCQM, the rate of appropriate follow-up was 36.0% (26 746/74 314 patients) in the VA after removing clinical exclusions and 41.1% at Geisinger (1009/2461 patients; P < .001). Similarly, the rate of appropriate evaluation for lung cancer in the VA was 61.5% (25 166/40 924 patients). Reviewers most frequently attributed missed opportunities at both sites to provider factors (84 of 157).

CONCLUSIONS

We implemented 2 eCQMs to evaluate the diagnostic process in cancer at 2 large health systems. Health care organizations can use these eCQMs to monitor diagnostic performance related to cancer.

Improving the diagnostic process for patients with possible bladder and kidney cancer: a mixed-methods study to identify potential missed diagnostic opportunities

BACKGROUND

Patients with bladder and kidney cancer may experience diagnostic delays.

AIM

To identify patterns of suboptimal care and contributors of potential missed diagnostic opportunities (MDOs).

DESIGN AND SETTING

Prospective, mixed-methods study recruiting participants from nine general practices in Eastern England between June 2018 and October 2019.

METHOD

Patients with possible bladder and kidney cancer were identified using eligibility criteria based on National Institute for Health and Care Excellence (NICE) guidelines for suspected cancer. Primary care records were reviewed at recruitment and at 1 year for data on symptoms, tests, referrals, and diagnosis. Referral predictors were examined using logistic regression. Semi-structured interviews were undertaken with 15 patients to explore their experiences of the diagnostic process, and these were analysed thematically.

RESULTS

Participants (n = 940) were mostly female (n = 657, 69.9%), with a median age of 71 years (interquartile range 64-77 years). In total, 268 (28.5%) received a referral and 465 (48.5%) had a final diagnosis of urinary tract infection (UTI). There were 33 (3.5%) patients who were diagnosed with cancer, including prostate (n = 17), bladder (n = 7), and upper urothelial tract (n = 1) cancers. Among referred patients, those who had a final diagnosis of UTI had the longest time to referral (median 81.5 days). Only one-third of patients with recurrent UTIs were referred despite meeting NICE referral guidelines. Qualitative findings revealed barriers during the diagnostic process, including inadequate clinical examination, female patients given repeated antibiotics without clinical reviews, and suboptimal communication of test results to patients.

CONCLUSION

Older females with UTIs might be at increased risk of MDOs for cancer. Targeting barriers during the initial diagnostic assessment and follow-up might improve quality of diagnosis.

Cancer Evaluations During the COVID-19 Pandemic: An Observational Study Using National Veterans Affairs Data

INTRODUCTION

Fewer cancer diagnoses have been made during the COVID-19 pandemic. Pandemic-related delays in cancer diagnosis could occur from limited access to care or patient evaluation delays (e.g., delayed testing after abnormal results). Follow-up of abnormal test results warranting evaluation for cancer was examined before and during the pandemic.

METHODS

Electronic trigger algorithms were applied to the Department of Veterans Affairs electronic health record data to assess follow-up of abnormal test results before (March 10, 2019-March 7, 2020) and during (March 8, 2020-March 6, 2021) the pandemic.

RESULTS

Electronic triggers were applied to 8,021,406 veterans' electronic health records to identify follow-up delays for abnormal results warranting evaluation for 5 cancers: bladder (urinalysis with high-grade hematuria), breast (abnormal mammograms), colorectal (positive fecal occult blood tests/fecal immunochemical tests or results consistent with iron deficiency anemia), liver (elevated alpha-fetoprotein), and lung (chest imaging suggestive of malignancy) cancers. Between prepandemic and pandemic periods, test quantities decreased by 12.6%-27.8%, and proportions of abnormal results lacking follow-up decreased for urinalyses (-0.8%), increased for fecal occult blood tests/fecal immunochemical test (+2.3%) and chest imaging (+1.8%), and remained constant for others. Follow-up times decreased for most tests; however, control charts suggested increased delays at 2 stages: early (pandemic beginning) for urinalyses, mammograms, fecal occult blood tests/fecal immunochemical test, iron deficiency anemia, and chest imaging and late (30-45 weeks into pandemic) for mammograms, fecal occult blood tests/fecal immunochemical test, and iron deficiency anemia.

CONCLUSIONS

Although early pandemic delays in follow-up may have led to reduced cancer rates, the significant decrease in tests performed is likely a large driver of these reductions. Future emergency preparedness efforts should bolster essential follow-up and testing procedures to facilitate timely cancer diagnosis.

Defining Diagnostic Error: A Scoping Review to Assess the Impact of the National Academies' Report Improving Diagnosis in Health Care

BACKGROUND

Standards for accurate and timely diagnosis are ill-defined. In 2015, the National Academies of Science, Engineering, and Medicine (NASEM) committee published a landmark report, Improving Diagnosis in Health Care , and proposed a new definition of diagnostic error, "the failure to ( a ) establish an accurate and timely explanation of the patient's health problem(s) or ( b ) communicate that explanation to the patient."

OBJECTIVE

This study aimed to explore how researchers operationalize the NASEM's definition of diagnostic error with relevance to accuracy, timeliness, and/or communication in peer-reviewed published literature.

METHODS

Using the Arskey and O'Malley's framework framework, we identified published literature from October 2015 to February 2021 using Medline and Google Scholar. We also conducted subject matter expert interviews with researchers.

RESULTS

Of 34 studies identified, 16 were analyzed and abstracted to determine how diagnostic error was operationalized and measured. Studies were grouped by theme: epidemiology, patient focus, measurement/surveillance, and clinician focus. Nine studies indicated using the NASEM definition. Of those, 5 studies also operationalized with existing definitions proposed before the NASEM report. Four studies operationalized the components of the NASEM definition and did not cite existing definitions. Three studies operationalized error using existing definitions only. Subject matter experts indicated that the NASEM definition functions as foundation for researchers to conceptualize diagnostic error.

CONCLUSIONS

The NASEM report produced a common understanding of diagnostic error that includes accuracy, timeliness, and communication. In recent peer-reviewed literature, most researchers continue to use pre-NASEM report definitions to operationalize accuracy and timeliness. The report catalyzed the use of patient-centered concepts in the definition, resulting in emerging studies focused on examining errors related to communicating diagnosis to patients.

Issues with the Swedish e-prescribing system - An analysis of health information technology-related incident reports using an existing classification system

Objective

To identify issues with the Swedish e-prescribing system and devise a set of recommendations to overcome the identified challenges.

Methods

A number of health information technology-related incidents were collected retrospectively from various sources using purposive and snowball sampling. A search term containing five keywords was used to identify the electronic prescription-related incidents. The identified incidents (n = 24) were subjected to an existing framework, i.e., the Health Information Technology Classification System. Special attention was paid to the software-related issues, which were analysed using thematic analysis.

Results

Several types of software-related issues (n = 22) were identified: system configuration, interface with other software systems or components, software functionality, data storage and backup, record migration, software not accessible, and network/server down or slow. Both human and technical factors contributed to these incidents, including prescriptions not cancelled actively, drug handling errors, software programming errors, and system updates/upgrades. These software problems led to various consequences, such as incidents affecting multiple patients’ care management, delays in patient care, and risks of serious deterioration of health. Several temporary initiatives or administrative adjustments, for instance, cover letters to patients and local strategies, were used to overcome some of these challenges.

Conclusions

This study provides insights into the challenges related to the e-prescribing system, contributing factors, consequences, and actions taken to mitigate those risks. Therefore, healthcare organisations using the e-prescribing system should adopt the provided recommendations to minimise the risks of design and developmental challenges, implementation and use-related issues, and the problems related to monitoring, evaluation, and optimisation.

Understanding barriers to diagnosis in a rare, genetic disease: Delays and errors in diagnosing schwannomatosis

Diagnosis of rare, genetic diseases is challenging, but conceptual frameworks of the diagnostic process can guide quality improvement initiatives. Using the National Academy of Medicine diagnostic framework, we assessed the extent of, and reasons for diagnostic delays and diagnostic errors in schwannomatosis, a neurogenetic syndrome characterized by nerve sheath tumors and chronic pain. We reviewed the medical records of 97 people with confirmed or probable schwannomatosis seen in two US tertiary care clinics. Time-to-event analysis revealed a median time from first symptom to diagnosis of 16.7 years (95% CI, 7.5-26.0 years) and median time from first medical consultation to diagnosis of 9.8 years (95% CI, 3.5-16.2 years). Factors associated with longer times to diagnosis included initial signs/symptoms that were intermittent, non-specific, or occurred at younger ages (p < 0.05). Thirty-six percent of patients were misdiagnosed; misdiagnoses were of underlying genetic condition (18.6%), pain etiology (16.5%), and nerve sheath tumor presence/pathology (11.3%) (non-mutually exclusive categories). One-fifth (19.6%) of patients had a clear missed opportunity for genetics workup that could have led to an earlier schwannomatosis diagnosis. These results suggest that interventions in clinician education, genetic testing availability, expert review of pathology findings, and automatic triggers for genetics referrals may improve diagnosis of schwannomatosis.

The use of electronic health records to inform cancer surveillance efforts: a scoping review and test of indicators for public health surveillance of cancer prevention and control

INTRODUCTION

State cancer prevention and control programs rely on public health surveillance data to set objectives to improve cancer prevention and control, plan interventions, and evaluate state-level progress towards achieving those objectives. The goal of this project was to evaluate the validity of using electronic health records (EHRs) based on common data model variables to generate indicators for surveillance of cancer prevention and control for these public health programs.

METHODS

Following the methodological guidance from the PRISMA Extension for Scoping Reviews, we conducted a literature scoping review to assess how EHRs are used to inform cancer surveillance. We then developed 26 indicators along the continuum of the cascade of care, including cancer risk factors, immunizations to prevent cancer, cancer screenings, quality of initial care after abnormal screening results, and cancer burden. Indicators were calculated within a sample of patients from the New York City (NYC) INSIGHT Clinical Research Network using common data model EHR data and were weighted to the NYC population using post-stratification. We used prevalence ratios to compare these estimates to estimates from the raw EHR of NYU Langone Health to assess quality of information within INSIGHT, and we compared estimates to results from existing surveillance sources to assess validity.

RESULTS

Of the 401 identified articles, 15% had a study purpose related to surveillance. Our indicator comparisons found that INSIGHT EHR-based measures for risk factor indicators were similar to estimates from external sources. In contrast, cancer screening and vaccination indicators were substantially underestimated as compared to estimates from external sources. Cancer screenings and vaccinations were often recorded in sections of the EHR that were not captured by the common data model. INSIGHT estimates for many quality-of-care indicators were higher than those calculated using a raw EHR.

CONCLUSION

Common data model EHR data can provide rich information for certain indicators related to the cascade of care but may have substantial biases for others that limit their use in informing surveillance efforts for cancer prevention and control programs.

Why Test Results Are Still Getting "Lost" to Follow-up: a Qualitative Study of Implementation Gaps

BACKGROUND

Lack of timely follow-up of abnormal test results is common and has been implicated in missed or delayed diagnosis, resulting in potential for patient harm.

OBJECTIVE

As part of a larger project to implement change strategies to improve follow-up of diagnostic test results, this study sought to identify specifically where implementation gaps exist, as well as possible solutions identified by front-line staff.

DESIGN

We used a semi-structured interview guide to collect qualitative data from Veterans Affairs (VA) facility staff who had experience with test results management and patient safety.

SETTING

Twelve VA facilities across the USA.

PARTICIPANTS

Facility staff members (n = 27), including clinicians, lab and imaging professionals, nursing staff, patient safety professionals, and leadership.

APPROACH

We conducted a content analysis of interview transcripts to identify perceived barriers and high-risk areas for effective test result management, as well as recommendations for improvement.

RESULTS

We identified seven themes to guide further development of interventions to improve test result follow-up. Themes related to trainees, incidental findings, tracking systems for electronic health record notifications, outdated contact information, referrals, backup or covering providers, and responsibility for test results pending at discharge. Participants provided recommendations for improvement within each theme.

CONCLUSIONS

Perceived barriers and recommendations for improving test result follow-up often reflected previously known problems and their corresponding solutions, which have not been consistently implemented in practice. Better policy solutions and improvement methods, such as quality improvement collaboratives, may bridge the implementation gaps between knowledge and practice.

Validation of an electronic trigger to measure missed diagnosis of stroke in emergency departments

OBJECTIVE

Diagnostic errors are major contributors to preventable patient harm. We validated the use of an electronic health record (EHR)-based trigger (e-trigger) to measure missed opportunities in stroke diagnosis in emergency departments (EDs).

METHODS

Using two frameworks, the Safer Dx Trigger Tools Framework and the Symptom-disease Pair Analysis of Diagnostic Error Framework, we applied a symptom-disease pair-based e-trigger to identify patients hospitalized for stroke who, in the preceding 30 days, were discharged from the ED with benign headache or dizziness diagnoses. The algorithm was applied to Veteran Affairs National Corporate Data Warehouse on patients seen between 1/1/2016 and 12/31/2017. Trained reviewers evaluated medical records for presence/absence of missed opportunities in stroke diagnosis and stroke-related red-flags, risk factors, neurological examination, and clinical interventions. Reviewers also estimated quality of clinical documentation at the index ED visit.

RESULTS

We applied the e-trigger to 7,752,326 unique patients and identified 46,931 stroke-related admissions, of which 398 records were flagged as trigger-positive and reviewed. Of these, 124 had missed opportunities (positive predictive value for "missed" = 31.2%), 93 (23.4%) had no missed opportunity (non-missed), 162 (40.7%) were miscoded, and 19 (4.7%) were inconclusive. Reviewer agreement was high (87.3%, Cohen's kappa = 0.81). Compared to the non-missed group, the missed group had more stroke risk factors (mean 3.2 vs 2.6), red flags (mean 0.5 vs 0.2), and a higher rate of inadequate documentation (66.9% vs 28.0%).

CONCLUSION

In a large national EHR repository, a symptom-disease pair-based e-trigger identified missed diagnoses of stroke with a modest positive predictive value, underscoring the need for chart review validation procedures to identify diagnostic errors in large data sets.

Factors Associated With Delay of Diagnosis of Hepatocellular Carcinoma in Patients With Cirrhosis

BACKGROUND & AIMS

We examined the frequency of and factors associated with delays in diagnosis of hepatocellular carcinoma (HCC) in a cohort of patients with cirrhosis in the Veterans Health Administration.

METHODS

In a retrospective study, we collected and analyzed data from the Veterans Health Administration's electronic health records. We used a multivariate logistic regression model to identify factors associated with a delay in diagnosis of HCC of more than 60 days following a red flag (defined as the earliest date at which a diagnosis of HCC could have been made, based on American Association for the Study of Liver Disease 2005 guidelines). We used multivariate Cox proportional hazards model to evaluate the effects of delayed diagnosis on survival, adjusting for patient and provider characteristics.

RESULTS

Among 655 patients with cirrhosis and a diagnosis of HCC from 2006 through 2011, 46.9% had a delay in diagnosis of more than 60 days following a red flag for HCC. Delays in diagnosis for more than 60 days were significantly associated with lack of provider adherence to the guidelines (adjusted odds ratio [OR], 4.82; 95% CI, 3.12-7.45), a diagnostic imaging evaluation instead of only measurement of alfa fetoprotein (adjusted OR, 2.63; 95% CI, 1.09-6.24), and diagnosis as an incidental finding during examination for an unrelated medical problem (compared with an HCC-related assessment) (adjusted OR, 2.26; 95% CI, 1.09-4.67). Diagnostic delays of 60 days or more were associated with lower mortality compared to patients without a delay in diagnosis (unadjusted hazard ratio, 0.57; 95% CI, 0.47-0.68 and adjusted hazard ratio, 0.63; 95% CI, 0.50-0.78).

CONCLUSIONS

Nearly half of veterans with cirrhosis have delays in diagnosis of HCC of 60 days or more after a red flag, defined by guidelines. Interventions are needed to improve timely follow-up of red flags for HCC and adherence to guidelines, to increase early detection of HCC.

Evaluation and recommendations for effective data visualization for seizure forecasting algorithms

Objective

Seizure forecasting algorithms have become increasingly accurate and may reduce the morbidity and mortality caused by seizure unpredictability. Translating these benefits into meaningful health outcomes for people with epilepsy requires effective data visualization of algorithm outputs. To date, no studies have investigated patient and physician perspectives on effective translation of algorithm outputs into data visualizations through health information technology.

Materials and Methods

We developed front-end data visualizations as part of a Seizure Forecast Visualization Toolkit. We surveyed 627 people living with epilepsy and caregivers, and 28 epilepsy healthcare providers. Respondents scored each visualization in terms of international standardized software quality criteria for functionality, appropriateness, and usability.

Results

People with epilepsy and caregivers ranked hourly radar charts highest for protecting against errors in interpreting forecasts, reducing anxiety from seizure unpredictability, and understanding seizure patterns. Accuracy in interpreting visuals, such as a risk gauge, was dependent on seizure frequency. Visuals showing hourly/daily forecasts were more useful for patients who experienced seizure cycling than those who did not. Hourly line graphs and monthly heat maps were rated highest among clinicians for ease of understanding, anticipated integration into clinical practice, and the likelihood of clinical usage. Epilepsy providers indicated that daily heat maps, daily line graphs, and hourly line graphs were most useful for interpreting seizure diary patterns, assessing therapy impact, and counseling on seizure safety.

Discussion

The choice of data visualization impacts the effective translation of seizure forecast algorithms into meaningful health outcomes.

Conclusion

This effort underlines the importance of incorporating standardized, quantitative methods for assessing the effectiveness of data visualization to translate seizure forecast algorithms into clinical practice.

Assessment of Health Information Technology-Related Outpatient Diagnostic Delays in the US Veterans Affairs Health Care System: A Qualitative Study of Aggregated Root Cause Analysis Data

IMPORTANCE

Diagnostic delay in the outpatient setting is an emerging safety priority that health information technology (HIT) should help address. However, diagnostic delays have persisted, and new safety concerns associated with the use of HIT have emerged.

OBJECTIVE

To analyze HIT-related outpatient diagnostic delays within a large, integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study involved qualitative content analysis of safety concerns identified in aggregated root cause analysis (RCA) data related to HIT and outpatient diagnostic delays. The setting was the US Department of Veterans Affairs using all RCAs submitted to the Veterans Affairs (VA) National Center for Patient Safety from January 1, 2013, to July 31, 2018.

MAIN OUTCOMES AND MEASURES

Common themes associated with the role of HIT-related safety concerns were identified and categorized according to the Health IT Safety framework for measuring, monitoring, and improving HIT safety. This framework includes 3 related domains (ie, safe HIT, safe use of HIT, and using HIT to improve safety) situated within an 8-dimensional sociotechnical model accounting for interacting technical and nontechnical variables associated with safety. Hence, themes identified enhanced understanding of the sociotechnical context and domain of HIT safety involved.

RESULTS

Of 214 RCAs categorized by the terms delay and outpatient submitted during the study period, 88 were identified as involving diagnostic delays and HIT, from which 172 unique HIT-related safety concerns were extracted (mean [SD], 1.97 [1.53] per RCA). Most safety concerns (82.6% [142 of 172]) involved problems with safe use of HIT, predominantly sociotechnical factors associated with people, workflow and communication, and a poorly designed human-computer interface. Fewer safety concerns involved problems with safe HIT (14.5% [25 of 172]) or using HIT to improve safety (0.3% [5 of 172]). The following 5 key high-risk areas for diagnostic delays emerged: managing electronic health record inbox notifications and communication, clinicians gathering key diagnostic information, technical problems, data entry problems, and failure of a system to track test results.

CONCLUSIONS AND RELEVANCE

This qualitative study of a national RCA data set suggests that interventions to reduce outpatient diagnostic delays could aim to improve test result management, interoperability, data visualization, and order entry, as well as to decrease information overload.

Imaging activity possibly signalling missed diagnostic opportunities in bladder and kidney cancer: A longitudinal data-linkage study using primary care electronic health records

INTRODUCTION

Sub-optimal use or interpretation of imaging investigations prior to diagnosis of certain cancers may be associated with less timely diagnosis, but pre-diagnostic imaging activity for urological cancer is unknown.

METHOD

We analysed linked data derived from primary and secondary care records and cancer registration to evaluate the use of clinically relevant imaging tests pre-diagnosis, in patients with bladder and kidney cancer diagnosed in 2012-15 in England. As pre-diagnostic imaging activity increased from background rate 8 months pre-diagnosis, we used logistic regression to determine factors associated with first imaging test occurring 4-8 months pre-diagnosis, considering that such instances may reflect possible missed opportunities for expediting the diagnosis.

RESULTS

1963 patients with bladder or kidney cancer had at least one imaging test in the 8 months pre-diagnosis. 420 (21%) of patients had their first imaging test 4-8 months pre-diagnosis, that being ultrasound, CT and X-ray in 48%, 43% and 9% of those cases, respectively. Factors associated with greater risk of a first imaging test 4-8 months pre-diagnosis were kidney cancer, diagnosis at stages other than stage IV, first imaging having been an X-ray, test requested by GP and absence of haematuria before the imaging request.

CONCLUSION

About 1 in 5 patients with urological cancers receive relevant first imaging investigations 4-8 months prior to diagnosis, which may represent potential missed diagnostic opportunities for earlier diagnosis.

A comparative study of the utilisation of an electronic test-result management system in emergency and intensive care settings

The purpose of this qualitative study was to identify differences in the utilisation of an electronic medical record test-result management system between two acute care departments. Field observations (130 min) and semi-structured interviews (n = 24) were conducted in the Intensive Care Unit and Emergency Department of an Australian hospital. Work processes identified from audio transcripts were modelled using business process modelling. Comparison of the Emergency Department and Intensive Care Unit identified the following: (1) test ordering variations according to clinical roles, (2) differences in the use of electronic medical record functionality according to specific demands of the clinical environment and (3) the non-linear components of the test-result management process. Variations were identified in the number of process decisions, external collaborations and temporal process workflows. Modelling the business processes, collaboration and communication needs of individual clinical environments can aid in enhancing the quality and appositeness of health information technology interventions and thus contribute to improving patient safety. Future health information technology interventions/evaluations aimed at improving the safety of test-result management processes need to address both the nuances of the clinical environment and accommodate the individual work practices of clinicians within that environment.

Cancer screening in the United States, 2019: A review of current American Cancer Society guidelines and current issues in cancer screening

Each year, the American Cancer Society publishes a summary of its guidelines for early cancer detection, data and trends in cancer screening rates, and select issues related to cancer screening. In this issue of the journal, the current American Cancer Society cancer screening guidelines are summarized, and the most current data from the National Health Interview Survey are provided on the utilization of cancer screening for men and women and on the adherence of men and women to multiple recommended screening tests.

Association of the Usability of Electronic Health Records With Cognitive Workload and Performance Levels Among Physicians

IMPORTANCE

Current electronic health record (EHR) user interfaces are suboptimally designed and may be associated with excess cognitive workload and poor performance.

OBJECTIVE

To assess the association between the usability of an EHR system for the management of abnormal test results and physicians' cognitive workload and performance levels.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study was conducted in a simulated EHR environment. From April 1, 2016, to December 23, 2016, residents and fellows from a large academic institution were enrolled and allocated to use either a baseline EHR (n = 20) or an enhanced EHR (n = 18). Data analyses were conducted from January 9, 2017, to March 30, 2018.

INTERVENTIONS

The EHR with enhanced usability segregated in a dedicated folder previously identified critical test results for patients who did not appear for a scheduled follow-up evaluation and provided policy-based decision support instructions for next steps. The baseline EHR displayed all patients with abnormal or critical test results in a general folder and provided no decision support instructions for next steps.

MAIN OUTCOMES AND MEASURES

Cognitive workload was quantified subjectively using NASA-Task Load Index and physiologically using blink rates. Performance was quantified according to the percentage of appropriately managed abnormal test results.

RESULTS

Of the 38 participants, 25 (66%) were female. The 20 participants allocated to the baseline EHR compared with the 18 allocated to the enhanced EHR demonstrated statistically significantly higher cognitive workload as quantified by blink rate (mean [SD] blinks per minute, 16 [9] vs 24 [7]; blink rate, -8 [95% CI, -13 to -2]; P = .01). The baseline group showed statistically significantly poorer performance compared with the enhanced group who appropriately managed 16% more abnormal test results (mean [SD] performance, 68% [19%] vs 98% [18%]; performance rate, -30% [95% CI, -40% to -20%]; P < .001).

CONCLUSIONS AND RELEVANCE

Relatively basic usability enhancements to the EHR system appear to be associated with better physician cognitive workload and performance; this finding suggests that next-generation systems should strip away non-value-added EHR interactions, which may help physicians eliminate the need to develop their own suboptimal workflows.

Application of electronic trigger tools to identify targets for improving diagnostic safety

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals indicative of a likely error or adverse event, offer a promising method to efficiently identify errors. The increasing amounts of longitudinal electronic data and maturing data warehousing techniques and infrastructure offer an unprecedented opportunity to implement new types of e-trigger tools that use algorithms to identify risks and events related to the diagnostic process. We present a knowledge discovery framework, the Safer Dx Trigger Tools Framework, that enables health systems to develop and implement e-trigger tools to identify and measure diagnostic errors using comprehensive electronic health record (EHR) data. Safer Dx e-trigger tools detect potential diagnostic events, allowing health systems to monitor event rates, study contributory factors and identify targets for improving diagnostic safety. In addition to promoting organisational learning, some e-triggers can monitor data prospectively and help identify patients at high-risk for a future adverse event, enabling clinicians, patients or safety personnel to take preventive actions proactively. Successful application of electronic algorithms requires health systems to invest in clinical informaticists, information technology professionals, patient safety professionals and clinicians, all of who work closely together to overcome development and implementation challenges. We outline key future research, including advances in natural language processing and machine learning, needed to improve effectiveness of e-triggers. Integrating diagnostic safety e-triggers in institutional patient safety strategies can accelerate progress in reducing preventable harm from diagnostic errors.

Current challenges in health information technology-related patient safety

We identify and describe nine key, short-term, challenges to help healthcare organizations, health information technology developers, researchers, policymakers, and funders focus their efforts on health information technology-related patient safety. Categorized according to the stage of the health information technology lifecycle where they appear, these challenges relate to (1) developing models, methods, and tools to enable risk assessment; (2) developing standard user interface design features and functions; (3) ensuring the safety of software in an interfaced, network-enabled clinical environment; (4) implementing a method for unambiguous patient identification (1-4 Design and Development stage); (5) developing and implementing decision support which improves safety; (6) identifying practices to safely manage information technology system transitions (5 and 6 Implementation and Use stage); (7) developing real-time methods to enable automated surveillance and monitoring of system performance and safety; (8) establishing the cultural and legal framework/safe harbor to allow sharing information about hazards and adverse events; and (9) developing models and methods for consumers/patients to improve health information technology safety (7-9 Monitoring, Evaluation, and Optimization stage). These challenges represent key "to-do's" that must be completed before we can expect to have safe, reliable, and efficient health information technology-based systems required to care for patients.

Medical Records Flag for Suicide Risk: Predictors and Subsequent Use of Care Among Veterans With Substance Use Disorders

OBJECTIVE

The U.S. Department of Veterans Affairs (VA) health care system established policies to include patient record flags (PRFs) for high suicide risk in the electronic medical record to alert providers and to increase health care contacts. This study identified predictors of new PRFs and described health care utilization before and after PRF initiation among VA patients with substance use disorders.

METHODS

The sample included patients ages ≥18 who received a substance use disorder diagnosis in 2012 (N=474,946). Demographic, clinical, and utilization predictors of PRFs were identified by multivariable logistic regression. Changes in short-term (three months) and longer-term (12 months) health care utilization before and after PRF initiation were compared by negative binomial regression.

RESULTS

A total of 8,913 patients received PRFs. Demographic predictors of PRF initiation included being younger than 35, white, and homeless. Clinical predictors were cocaine, opioid, and sedative use disorders; posttraumatic stress, psychotic, bipolar, and depressive disorders; and diagnosis of a suicide attempt. Patients with PRFs averaged 1.33 (95% confidence interval [CI]=1.29-1.38) times more primary care visits, 2.29 (CI=2.24-2.34) times more mental health visits, 4.10 (CI=3.80-4.42) times more substance use visits, and fewer (incidence rate ratio=.55, CI=.53-.58) emergency department visits in the three months following compared with the three months before PRF initiation. Modest increases in mental health- and substance use--related days hospitalized were observed.

CONCLUSIONS

Veterans received significantly more health care services after PRF initiation. Further research is warranted on the effects of PRFs on clinical outcomes, such as suicide behaviors.