Notifications received by primary care practitioners in electronic health records: a taxonomy and time analysis

Enhancing communication and care coordination: A scoping review of encounter notification systems between emergency departments and primary care providers

OBJECTIVE

This scoping review aims to explore the current state of encounter notification systems (ENS) between emergency departments (EDs) and primary care providers (PCPs), focusing on their mechanisms, effectiveness, impacts, and challenges in healthcare settings.

METHODS

A systematic search was conducted using PubMed/MEDLINE and Google Scholar to identify relevant literature on ENS between EDs and PCPs. Eligible studies were selected based on predefined criteria, and data were synthesized narratively.

RESULTS

The initial search yielded 1,396 articles, with 29 included in the review. Studies highlighted the significance of encounter notifications in improving communication and care coordination between EDs and PCPs, leading to enhanced patient outcomes. However, challenges such as technological barriers, privacy concerns, and variations in healthcare settings were identified.

CONCLUSION

ENS play a crucial role in enhancing communication and care coordination between EDs and PCPs. Despite challenges, these systems offer substantial benefits and opportunities for improving patient care in the ED-primary care continuum. Future research should focus on addressing implementation barriers and evaluating long-term impacts to optimize the effectiveness of ENS in this context.

Characterizing barriers to closing cross-institutional referral loops: Workflow and information flow analysis

The specialty referral process consists of primary care clinicians referring patients to specialty consultants. This care transition requires effective care coordination and health information exchange between care teams; however, breakdowns in workflow and information flow impede "closing the referral loop" and delay or prevent referrers from receiving the consultant's "visit notes," particularly in cross-institutional referrals. This study aimed to describe and map the referral process as it occurs in clinics and identify and characterize work system barriers affecting its performance. Referrers and consultants were interviewed about their perceived workflows, barriers, and clinical outcomes to inform a workflow analysis.

Continuity of care after attempted suicide: the primary care physicians' role

BACKGROUND

Suicide prevention is an important public health concern, and primary care physicians (PCPs) often serve as the first point of contact for individuals at risk. Few interventions in the primary care setting have been linked to reduced suicide attempt (SA) rates. The Continuity of Care (COC) protocol was developed to improve the primary care treatment of high-risk suicidal patients.

OBJECTIVES

This study examined PCPs' awareness of the COC protocol, its perceived effectiveness, and PCPs' attitudes towards post-SA-discharge visits.

METHODS

A survey was administered to 64 PCPs who had a recent office visit with a patient who had attempted suicide. Data were collected between May and July 2021 and analyzed anonymously.

RESULTS

Thirty of the 64 PCPs answered the questionnaires, giving a response rate of 47%. Most were unaware of the COC protocol. Seventeen physicians (57%) felt that the visit strengthened their physician-patient relationship, and while nearly half of the physicians (47%, n = 14) agreed they had the knowledge and tools to manage a post-SA-discharge visit, 43% of them (n = 13) preferred that the visit would have been handled by a mental health professional rather than a PCP. Analysis of open-ended questions uncovered three themes: knowledge gap, system limitation, and the PCP's role in maintaining the COC.

CONCLUSION

The findings of this study highlighted the important role PCPs can play to prevent future SAs, as well as exposed gaps in the knowledge and system constraints that impede them from carrying out this role as effectively as possible.

Moving Away from Chaos: Intentional and Adaptive Management of the Non-visit Care River

In modern primary care practice, clinicians face increasing volumes of asynchronous, electronic, non-visit care (NVC). Systems for completing this work, however, remain under-developed and often lack definition around patient and practice expectations for work completion and team member contributions. The resulting reactive, unstructured, and unscheduled NVC workflows cause and exacerbate physicians' cognitive overload, distraction, and dissatisfaction. Herein, we propose that primary care practices take an intentional, holistic approach to managing systems of NVC and offer a conceptual model for managing NVC work, analogizing the flow of these tasks to the flow of water through a river system: (1) by carefully controlling the inputs into the NVC system (the tributaries entering the river system); (2) by carefully defining the workflows, roles and responsibilities for completion of common tasks (the direction of river flow); (3) by improving the interface of the electronic health record (obstacles encountered in the river); and (4) by optimizing effectiveness of primary care teams (the contours of the river determining rate of flow). This framework for managing NVC, viewed from a broader system perspective, has the potential to improve productivity, quality of care, and clinician work experience.

Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review

BACKGROUND

Electronic clinical decision support tools (eCDS) are increasingly available to assist General Practitioners (GP) with the diagnosis and management of a range of health conditions. It is unclear whether the use of eCDS tools has an impact on GP workload. This scoping review aimed to identify the available evidence on the use of eCDS tools by health professionals in general practice in relation to their impact on workload and workflow.

METHODS

A scoping review was carried out using the Arksey and O'Malley methodological framework. The search strategy was developed iteratively, with three main aspects: general practice/primary care contexts, risk assessment/decision support tools, and workload-related factors. Three databases were searched in 2019, and updated in 2021, covering articles published since 2009: Medline (Ovid), HMIC (Ovid) and Web of Science (TR). Double screening was completed by two reviewers, and data extracted from included articles were analysed.

RESULTS

The search resulted in 5,594 references, leading to 95 full articles, referring to 87 studies, after screening. Of these, 36 studies were based in the USA, 21 in the UK and 11 in Australia. A further 18 originated from Canada or Europe, with the remaining studies conducted in New Zealand, South Africa and Malaysia. Studies examined the use of eCDS tools and reported some findings related to their impact on workload, including on consultation duration. Most studies were qualitative and exploratory in nature, reporting health professionals' subjective perceptions of consultation duration as opposed to objectively-measured time spent using tools or consultation durations. Other workload-related findings included impacts on cognitive workload, "workflow" and dialogue with patients, and clinicians' experience of "alert fatigue".

CONCLUSIONS

The published literature on the impact of eCDS tools in general practice showed that limited efforts have focused on investigating the impact of such tools on workload and workflow. To gain an understanding of this area, further research, including quantitative measurement of consultation durations, would be useful to inform the future design and implementation of eCDS tools.

Enhancing opportunistic recruitment and retention in primary care trials: lessons learned from a qualitative study embedded in the Cranberry for Urinary Tract Infection (CUTI) feasibility trial

Background

Opportunistic recruitment in primary care is challenging due to the inherent unpredictability of incident conditions, and workload and time pressures. Many clinical trials do not recruit to target, leading to equivocal answers to research questions. Learning from the experiences of patients and recruiters to trials of incident conditions has the potential to improve recruitment and retention to future trials, thereby enhancing the quality and impact of research findings. The aim of this research was to learn from the trial experiences of UTI patients and recruiters to the Cranberry for UTI (CUTI) trial, to help plan an adequately powered trial of similar design.

Methods

One-to-one semi-structured interviews were embedded within the CUTI feasibility trial, an open-label, randomised feasibility trial of cranberry extract for symptoms of acute, uncomplicated Urinary Tract Infection (UTI) in primary care. Interviews were conducted with a sample of: CUTI trial participants; non-CUTI trial UTI patients; and, recruiters to the CUTI trial. Verbatim transcripts were analysed thematically.

Results

Twenty-six patients with UTI and eight recruiters (nurses and GPs) to the CUTI trial were interviewed. Three themes were developed around: reasons for participating in research; barriers to opportunistic recruitment; and, UTI patients’ experiences of trial procedures. Recruiters found that targeted electronic prompts directed at healthcare practitioners based in clinics where patients with incident conditions were likely to present (e.g. minor illness clinic) were more effective than generic prompts (e.g. desk prompts) at filtering patients from their usual clinical pathway to research clinics. Using a script to explain the delayed antibiotic trial group to patients was found to be helpful, and may have served to boost recruitment. For UTI patients, using an electronic diary to rate their symptoms was considered an acceptable medium, and often preferable to using a paper diary or mobile phone application.

Conclusions

The use of targeted prompts directed at clinicians, a script to explain trial groups that may be deemed less desirable, and an appropriate diary format for patient-reported outcomes, may help to improve trial recruitment and retention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12875-022-01796-7.

'But there are so many referrals which are totally … only generating work and irritation': a qualitative study of physicians' and nurses' experiences of work tasks in primary care in Sweden

OBJECTIVE

This study explored the perceptions of physicians and nurses in Swedish primary care regarding the legitimacy of their work tasks and the use of their professional competence.

DESIGN AND SETTING

This qualitative study was based on manifest content analysis. Data were collected with individual semi-structured interviews of physicians and nurses at publicly managed primary care centres in the Region Östergötland, Sweden. To include both large and small primary care centres, we applied strategic sampling. Among 15 primary care centres invited, nine agreed to participate, including four urban, two suburban, and three rural centres.

SUBJECTS

The study included 11 physicians and 13 nurses from nine primary care centres.

MAIN OUTCOME MEASURES AND RESULTS

The physicians and nurses perceived several of their work tasks as illegitimate. In addition, they experienced work-related difficulties, due to resource shortages, challenging electronic data systems, work inefficiencies, and that there were insufficient cooperation with, and problems drawing the line between, primary care and hospital care responsibilities. However, most found that their individual expertise was appropriately used, overall.

CONCLUSIONS

Strained work situations and illegitimate work tasks may inflate discontentment and lead to negative work stress. Nevertheless, the staff felt that competence was used appropriately in the tasks considered legitimate.Key PointsPhysicians and nurses in primary care in Sweden described several work tasks as illegitimate.Physicians and nurses described problems with heavy workloads, resource shortages, electronic data-system challenges, inefficiencies and with cooperation and drawing the line between primary care and hospital care.Overall, physicians and nurses believed their individual expertise was used appropriately.To uphold sustainable working conditions and thoughtful use of staff competence, organisational measures, such as redistributing staff from hospital to primary care were proposed.

Reduction in Medication Refill Encounters Through Primary Care Redesign Workflow Changes

With a goal of improving efficiency and reducing workload outside of visits, we sought to examine a primary care redesign process aimed at reducing refill requests made outside of office visits. Data on the number of refill encounters per panel member were collected at 17 clinics before, during, and after the implementation of a redesign process. There was an initial reduction in the number of medication refill encounters, and the rate of refill encounters continued to decline following implementation. Variation across clinic contexts suggests that redesign processes may need to be tailored for different settings to optimize effectiveness.

Building the evidence-base to reduce electronic health record-related clinician burden

Clinicians face competing pressures of being clinically productive while using imperfect electronic health record (EHR) systems and maximizing face-to-face time with patients. EHR use is increasingly associated with clinician burnout and underscores the need for interventions to improve clinicians' experiences. With an aim of addressing this need, we share evidence-based informatics approaches, pragmatic next steps, and future research directions to improve 3 of the highest contributors to EHR burden: (1) documentation, (2) chart review, and (3) inbox tasks. These approaches leverage speech recognition technologies, natural language processing, artificial intelligence, and redesign of EHR workflow and user interfaces. We also offer a perspective on how EHR vendors, healthcare system leaders, and policymakers all play an integral role while sharing responsibility in helping make evidence-based sociotechnical solutions available and easy to use.

A Fact-Finding Procedure Integrating Machine Learning and AHP Technique to Predict Delayed Diagnosis of Bladder Patients with Hematuria

Bladder cancer, the ninth most common cancer worldwide, requires fast diagnosis and treatment to prevent disease progression and improve patient survival. However, patients with bladder cancer often experience considerable delays in diagnosis. One reason for such delays is that hematuria, a major symptom of bladder cancer, has a high probability of also being a warning sign for urinary tract diseases. Another reason is that the sensitivity of the body parts affected by bladder cancer deters patients from undergoing cystoscopy and influences patients' "physician shopping" behavior. In this study, the analytic hierarchy process was used to determine critical variables influencing delayed diagnosis; moreover, the variables were used to construct models for predicting delayed diagnosis in patients with hematuria by using several machine learning techniques. Furthermore, the critical variables associated with delayed diagnosis of bladder cancer in patients with hematuria were evaluated using GainRatio technology. The study sample was selected from a population-based database. The model evaluation results indicated that the prediction model established using decision tree algorithms outperformed the other models. The critical risk factors for delayed diagnosis of bladder cancer were as follows: (1) cystoscopy performed 6 months after hematuria diagnosis and (2) physician shopping.

The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review

A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.

A Convolutional Neural Network-Based Triplet-Mining Metric Learning Schema for Measuring Patient Similarity Addressing Personalized Healthcare

Prediction of the development risk of some diseases is an important area of Health Care Research. When exploring the personalized care of the patients, precise identification and classification of similarity in patients from their past report is an important process. Electronically stored health information EHRs that has been sampled unevenly as well as which has variable appointment durations, is considered to be unsuitable for measuring the similarity among patients directly, as there is no proper representation that are fitting. In addition, a technique is required that is efficient to evaluate similarities in patient. We propose two new similarities learning environments using deep learning that learn simultaneously the representations of the patients as well as measurement of similarity in pairs. A Convolutional Neural Network (CNN) is used to understand EHRs that contains crucial information which are local thereby providing scholastic illumination in the triplet loss otherwise entropy loss. When the training is completed, distances are calculated as well as similarities scores. Using this similarity information, disease predictions along with patient grouping is performed. Experimentally the results gives an idea that CNN can represent the EHR sequences in a better way and the schema offered are more efficient than the modern metric distance learning.

The Impact of Clinical Decision Support Alerts on Clostridioides difficile Testing: A Systematic Review

BACKGROUND

Several studies have investigated the utility of electronic decision support alerts in diagnostic stewardship for Clostridioides difficile infection (CDI). However, it is unclear if alerts are effective in reducing inappropriate CDI testing and/or CDI rates. The aim of this systematic review was to determine if alerts related to CDI diagnostic stewardship are effective at reducing inappropriate CDI testing volume and CDI rates among hospitalized adult patients.

METHODS

We searched Ovid Medline and 5 other databases for original studies evaluating the association between alerts for CDI diagnosis and CDI testing volume and/or CDI rate. Two investigators independently extracted data on study characteristics, study design, alert triggers, cointerventions, and study outcomes.

RESULTS

Eleven studies met criteria for inclusion. Studies varied significantly in alert triggers and in study outcomes. Six of 11 studies demonstrated a statistically significant decrease in CDI testing volume, 6 of 6 studies evaluating appropriateness of CDI testing found a significant reduction in the proportion of inappropriate testing, and 4 of 7 studies measuring CDI rate demonstrated a significant decrease in the CDI rate in the postintervention vs preintervention period. The magnitude of the increase in appropriate CDI testing varied, with some studies reporting an increase with minimal clinical significance.

CONCLUSIONS

The use of electronic alerts for diagnostic stewardship for C. difficile was associated with reductions in CDI testing, the proportion of inappropriate CDI testing, and rates of CDI in most studies. However, broader concerns related to alerts remain understudied, including unintended adverse consequences and alert fatigue.

Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

Background

Increased work through electronic health record (EHR) messaging is frequently cited as a factor of physician burnout. However, studies to date have relied on anecdotal or self-reported measures, which limit the ability to match EHR use patterns with continuous stress patterns throughout the day.

Objective

The aim of this study is to collect EHR use and physiologic stress data through unobtrusive means that provide objective and continuous measures, cluster distinct patterns of EHR inbox work, identify physicians’ daily physiologic stress patterns, and evaluate the association between EHR inbox work patterns and physician physiologic stress.

Methods

Physicians were recruited from 5 medical centers. Participants (N=47) were given wrist-worn devices (Garmin Vivosmart 3) with heart rate sensors to wear for 7 days. The devices measured physiological stress throughout the day based on heart rate variability (HRV). Perceived stress was also measured with self-reports through experience sampling and a one-time survey. From the EHR system logs, the time attributed to different activities was quantified. By using a clustering algorithm, distinct inbox work patterns were identified and their associated stress measures were compared. The effects of EHR use on physician stress were examined using a generalized linear mixed effects model.

Results

Physicians spent an average of 1.08 hours doing EHR inbox work out of an average total EHR time of 3.5 hours. Patient messages accounted for most of the inbox work time (mean 37%, SD 11%). A total of 3 patterns of inbox work emerged: inbox work mostly outside work hours, inbox work mostly during work hours, and inbox work extending after hours that were mostly contiguous to work hours. Across these 3 groups, physiologic stress patterns showed 3 periods in which stress increased: in the first hour of work, early in the afternoon, and in the evening. Physicians in group 1 had the longest average stress duration during work hours (80 out of 243 min of valid HRV data; P=.02), as measured by physiological sensors. Inbox work duration, the rate of EHR window switching (moving from one screen to another), the proportion of inbox work done outside of work hours, inbox work batching, and the day of the week were each independently associated with daily stress duration (marginal R²=15%). Individual-level random effects were significant and explained most of the variation in stress (conditional R²=98%).

Conclusions

This study is among the first to demonstrate associations between electronic inbox work and physiological stress. We identified 3 potentially modifiable factors associated with stress: EHR window switching, inbox work duration, and inbox work outside work hours. Organizations seeking to reduce physician stress may consider system-based changes to reduce EHR window switching or inbox work duration or the incorporation of inbox management time into work hours.

The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour & improve safety

BACKGROUND

Prescribing alerts of an electronic health record are meant to be protective, but often are disruptive to providers. Our goal was to assess the effectiveness of interruptive medication-prescriber alerts in changing prescriber behaviour and improving patient outcomes in ambulatory care settings via computerised provider order entry (CPOE) systems.

METHODS

A standardised search strategy was developed and applied to the following key bibliographical databases: PubMed, Embase, CINAHL and The Cochrane Library. Non-comparison studies and studies on non-interrupted alerts were eliminated. We developed a standardised data collection form and abstracted data that included setting, study design, category of intervention alert and outcomes measured. The search was completed in August 2018 and repeated in November of 2019 and of 2020 to identify any new publications during the time lapse.

RESULTS

Ultimately, nine comparison studies of triggered alerts were identified. Each studied at least one outcome measure illustrating how the alert affected prescriber decision-making. Provider behaviour was influenced in the majority, with most noting a positive change. Alerts decreased pharmaceutical costs, moved medications toward preferred medications tiers and steered treatments toward evidence-based choices. They also decreased prescribing errors. Clinician feedback, rarely solicited, expressed frustration with alerts creating a time delay.

CONCLUSION

The current evidence shows a clear indication that many categories of alerts are effective in changing prescriber behaviour. However, it is unclear whether these behavioural changes lead to improved patient outcomes. Despite the rapid transition to CPOE use for patient care, there are few rigorous studies of triggered alerts and how workflow interruptions impact patient outcomes and provider acceptance.

Are specific elements of electronic health record use associated with clinician burnout more than others?

OBJECTIVE

The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data.

MATERIALS AND METHODS

We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics.

RESULTS

Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039).

DISCUSSION

High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, "patient calls" encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being.

CONCLUSIONS

Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.

Electronic Health Record Reminders for Chlamydia Screening in an American Indian Population

OBJECTIVES

Indian Health Service (IHS) screening rates for Chlamydia trachomatis are lower than national rates of chlamydia screening in the Southwest. We describe and evaluate the effect of a public health intervention consisting of electronic health record (EHR) reminders to alert health care providers to screen for chlamydia at an IHS facility. We also conducted an awareness presentation among health care providers on chlamydia screening.

METHODS

We conducted our intervention from November 1, 2013, through October 31, 2015, at an IHS facility in the Southwest. We implemented algorithms that queried database values to assess chlamydia screening performance in 6 clinical departments. We presented data on the screening performance of clinical departments and health care providers (de-identified) in the awareness presentations. We re-queried database values 1 and 2 years after implementation of the EHR reminder intervention to evaluate before-and-after screening rates, comparing data among all patients and among female patients only.

RESULTS

We found small, sustained relative increases in chlamydia screening rates during the 2012-2015 evaluation period: 20.8% pre-intervention to 24.9% and 24.2% one and two years postintervention, respectively, across all patients; 32.3% preintervention to 36.6% and 35.6% one and two years postintervention, respectively, among female patients. Increases in clinical department-specific screening rates varied and were most prominent in internal medicine (35.8% preintervention to peak 65.8% postintervention). The 1 clinic (obstetrics-gynecology) that did not receive an awareness presentation showed a consistent downward trend in screening rates, although absolute rates were consistently higher in that clinic than in other clinics.

CONCLUSIONS

Awareness presentations that offer feedback to health care providers on screening performance, heighten provider awareness of the importance of chlamydia screening, and promote development of novel provider-initiated screening protocols may help to increase screening rates when combined with EHR reminders.

Incorporating the Voice of Community Based Pediatricians to Improve Discharge Communication

Supplemental Digital Content is available in the text.

Introduction:

Communication between pediatric hospitalists and primary care physicians (PCPs) at discharge is an essential part of a successful transition to home. While many hospitals require communicating with PCPs for all admitted patients, it is unknown if PCPs find such communication valuable or if it improves outcomes. Our global aim was to improve discharge communication for patients that pediatric hospitalists and PCPs deemed appropriate.

Methods:

We sent surveys to 422 outpatient pediatricians in our care network to understand their communication preferences. Survey results informed local guidelines for when hospitalists should directly contact PCPs. We determined the proportion of inpatient discharges meeting those guidelines and set a target for our primary process metric: the proportion of discharges with attempted direct PCP contact. We engaged in Plan-Do-Study-Act cycles, including a discharge documentation tool in the electronic health record, education of inpatient teams, email reminders including group performance data, asynchronous Health Insurance Portability and Accountability Act-compliant messaging application, and competitions that shared blinded individual data.

Results:

We increased the percentage of documented direct communication with the PCPs from 2% to 33% and from 4% to 65% for those who met guidelines for direct communication.

Conclusions:

PCPs only want direct communication on a subset of discharges. Interventions focused on high-yield populations improved discharge communication in our institution.

Development and validation of prediction rules to target care intensification in veteran patients with diabetes

Background

Diabetes affects 30.3 million people in the USA. Among these people, a major risk factor for microvascular complications is having a glycated haemoglobin (HbA1c) value of ≥75 mmol/mol; therefore, it would be helpful to identify patients who will obtain future HbA1c values of <75 mmol/mol.

Objectives

To develop and validate two prediction rules among patients with diabetes having a baseline HbA1c value of ≥75 mmol/mol: (1) HbA1c measurement ever <75 mmol/mol and (2) final HbA1c measurement of <75 mmol/mol.

Methods

Retrospective cohort study using a registry extracting data from the Department of Veterans Affairs’s (VA’s) electronic health records system. Baseline was 1 Jul 2013–30 June 2014; patients were followed up until 31 July 2016.

Results

Our population consisted of 145 659 patients. Across models, predictors were age, sex, minority status, baseline HbA1c value, time, HbA1c≥75 mmol/mol, receiving insulin treatment and consecutive number of HbA1c values of 75 mmol/mol. The overall likelihood of a patient ever having an HbA1c<75 mmol/mol was 73.65%; with the rule, predicted probabilities were 38.94%, 50.75% and 78.88%. The overall likelihood of patients having a final HbA1c measurement of <75 mmol/mol was 55.35%; the rule provided predicted probabilities of 29.93%, 50.17% and 68.58%.

Conclusions

Within each rule, there were similar observed and predicted tertile probabilities; maintaining HbA1c values of <75 mmol/mol resulted in probability shifts in the majority of patients. We recommend psychosocial screening for 15% of patients for whom there is less than one-third chance of maintaining HbA1c<75 mmol/mol. We plan to conduct additional research to see whether this approach helps.

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.

A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice

OBJECTIVES

Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.

DESIGN

Retrospective cohort for algorithm derivation and validation, pre-post impact evaluation.

SETTING

Tertiary teaching hospital system in Philadelphia, PA.

PATIENTS

All non-ICU admissions; algorithm derivation July 2011 to June 2014 (n = 162,212); algorithm validation October to December 2015 (n = 10,448); silent versus alert comparison January 2016 to February 2017 (silent n = 22,280; alert n = 32,184).

INTERVENTIONS

A random-forest classifier, derived and validated using electronic health record data, was deployed both silently and later with an alert to notify clinical teams of sepsis prediction.

MEASUREMENT AND MAIN RESULT

Patients identified for training the algorithm were required to have International Classification of Diseases, 9th Edition codes for severe sepsis or septic shock and a positive blood culture during their hospital encounter with either a lactate greater than 2.2 mmol/L or a systolic blood pressure less than 90 mm Hg. The algorithm demonstrated a sensitivity of 26% and specificity of 98%, with a positive predictive value of 29% and positive likelihood ratio of 13. The alert resulted in a small statistically significant increase in lactate testing and IV fluid administration. There was no significant difference in mortality, discharge disposition, or transfer to ICU, although there was a reduction in time-to-ICU transfer.

CONCLUSIONS

Our machine learning algorithm can predict, with low sensitivity but high specificity, the impending occurrence of severe sepsis and septic shock. Algorithm-generated predictive alerts modestly impacted clinical measures. Next steps include describing clinical perception of this tool and optimizing algorithm design and delivery.

Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow

The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.

The Development and Evaluation of an Electronic Health Record Efficiency Workshop for Providers

BACKGROUND

The electronic health record (EHR) has historically been known to be a source of stress and dissatisfaction, leading to reduced efficiency and productivity for providers. This issue is complicated by constant changes in EHRs that are necessary to keep systems current with evolving functionality. Knowing the existence of this problem, an evidenced-based solution, known as an efficiency workshop, was developed by our information technology training and optimization team for providers as a means of ongoing professional development.

OBJECTIVES

The objectives of this project were to identify EHR optimization needs for providers in various clinical departments and improve their EHR satisfaction. The development of a program focused on provider efficiency tools and personalization was key and, once piloted, how to measure program success.

METHODS

Efficiency workshops comprised members of the IT training team who set up on site training sessions during reserved time with providers during departmental meetings. Sessions focused on reviewing EHR efficiency tools using demonstration of existing system functionality. Participating providers were given continuing medical education (CME) credits upon completion of evaluations used as a quality improvement tool for the program.

RESULTS

Descriptive results showed that providers were satisfied with this method of EHR instruction. Subjective feedback yielded positive themes such as informative, well done, organized, and helpful.

CONCLUSION

This initiative began as a pilot program and successfully expanded across clinical departments at our academic medical center. Future plans are to sustain and further invest in this program by using EHR reporting features to further customize these sessions and evaluate impact on system use.

Follow-up of incidental pulmonary nodules and association with mortality in a safety-net cohort

Background Though incidental pulmonary nodules are common, rates of guideline-recommended surveillance and associations between surveillance and mortality are unclear. In this study, we describe adherence (categorized as complete, partial, late and none) to guideline-recommended surveillance among patients with incidental 5-8 mm pulmonary nodules and assess associations between adherence and mortality. Methods This was a retrospective cohort study of 551 patients (≥35 years) with incidental pulmonary nodules conducted from September 1, 2008 to December 31, 2016, in an integrated safety-net health network. Results Of the 551 patients, 156 (28%) had complete, 87 (16%) had partial, 93 (17%) had late and 215 (39%) had no documented surveillance. Patients were followed for a median of 5.2 years [interquartile range (IQR), 3.6-6.7 years] and 82 (15%) died during follow-up. Adjusted all-cause mortality rates ranged from 2.24 [95% confidence interval (CI), 1.24-3.25] deaths per 100 person-years for complete follow-up to 3.30 (95% CI, 2.36-4.23) for no follow-up. In multivariable models, there were no statistically significant associations between the levels of surveillance and mortality (p > 0.16 for each comparison with complete surveillance). Compared with complete surveillance, adjusted mortality rates were non-significantly increased by 0.45 deaths per 100 person-years (95% CI, -1.10 to 2.01) for partial, 0.55 (95% CI, -1.08 to 2.17) for late and 1.05 (95% CI, -0.35 to 2.45) for no surveillance. Conclusions Although guideline-recommended surveillance of small incidental pulmonary nodules was incomplete or absent in most patients, gaps in surveillance were not associated with statistically significant increases in mortality in a safety-net population.

From Genetics to Genomics: Facing the Liability Implications in Clinical Care

Health care is transitioning from genetics to genomics, in which single-gene testing for diagnosis is being replaced by multi-gene panels, genome-wide sequencing, and other multi-genic tests for disease diagnosis, prediction, prognosis, and treatment. This health care transition is spurring a new set of increased or novel liability risks for health care providers and test laboratories. This article describes this transition in both medical care and liability, and addresses 11 areas of potential increased or novel liability risk, offering recommendations to both health care and legal actors to address and manage those liability risks.

Impacts of Operational Failures on Primary Care Physicians' Work: A Critical Interpretive Synthesis of the Literature

PURPOSE

Operational failures are system-level errors in the supply of information, equipment, and materials to health care personnel. We aimed to review and synthesize the research literature to determine how operational failures in primary care affect the work of primary care physicians.

METHODS

We conducted a critical interpretive synthesis. We searched 7 databases for papers published in English from database inception until October 2017 for primary research of any design that addressed problems interfering with primary care physicians' work. All potentially eligible titles/abstracts were screened by 1 reviewer; 30% were subject to second screening. We conducted an iterative critique, analysis, and synthesis of included studies.

RESULTS

Our search retrieved 8,544 unique citations. Though no paper explicitly referred to "operational failures," we identified 95 papers that conformed to our general definition. The included studies show a gap between what physicians perceived they should be doing and what they were doing, which was strongly linked to operational failures-including those relating to technology, information, and coordination-over which physicians often had limited control. Operational failures actively configured physicians' work by requiring significant compensatory labor to deliver the goals of care. This labor was typically unaccounted for in scheduling or reward systems and had adverse consequences for physician and patient experience.

CONCLUSIONS

Primary care physicians' efforts to compensate for suboptimal work systems are often concealed, risking an incomplete picture of the work they do and problems they routinely face. Future research must identify which operational failures are highest impact and tractable to improvement.

Reducing Alert Burden in Electronic Health Records: State of the Art Recommendations from Four Health Systems

BACKGROUND

Electronic health record (EHR) alert fatigue, while widely recognized as a concern nationally, lacks a corresponding comprehensive mitigation plan.

OBJECTIVES

The goal of this manuscript is to provide practical guidance to clinical informaticists and other health care leaders who are considering creating a program to manage EHR alerts.

METHODS

This manuscript synthesizes several approaches and recommendations for better alert management derived from four U.S. health care institutions that presented their experiences and recommendations at the American Medical Informatics Association 2019 Clinical Informatics Conference in Atlanta, Georgia, United States. The assembled health care institution leaders represent academic, pediatric, community, and specialized care domains. We describe governance and management, structural concepts and components, and human-computer interactions with alerts, and make recommendations regarding these domains based on our experience supplemented with literature review. This paper focuses on alerts that impact bedside clinicians.

RESULTS

The manuscript addresses the range of considerations relevant to alert management including a summary of the background literature about alerts, alert governance, alert metrics, starting an alert management program, approaches to evaluating alerts prior to deployment, and optimization of existing alerts. The manuscript includes examples of alert optimization successes at two of the represented institutions. In addition, we review limitations on the ability to evaluate alerts in the current state and identify opportunities for further scholarship.

CONCLUSION

Ultimately, alert management programs must strive to meet common goals of improving patient care, while at the same time decreasing the alert burden on clinicians. In so doing, organizations have an opportunity to promote the wellness of patients, clinicians, and EHRs themselves.

The Effect of Eliminating Intermediate Severity Drug-Drug Interaction Alerts on Overall Medication Alert Burden and Acceptance Rate

OBJECTIVE

This study aimed to determine the effects of reducing the number of drug-drug interaction (DDI) alerts in an order entry system.

METHODS

Retrospective pre-post analysis at an urban medical center of the rates of medication alerts and alert acceptance during a 5-month period before and 5-month period after the threshold for firing DDI alerts was changed from "intermediate" to "severe." To ensure that we could determine varying response to each alert type, we took an in-depth look at orders generating single alerts.

RESULTS

Before the intervention, 241,915 medication orders were placed, of which 25.6% generated one or more medication alerts; 5.3% of the alerts were accepted. During the postintervention period, 245,757 medication orders were placed of which 16.0% generated one or more medication alerts, a 37.5% relative decrease in alert rate (95% confidence interval [CI]: -38.4 to -36.8%), but only a 9.6% absolute decrease (95% CI: -9.4 to -9.9%). 7.4% of orders generating alerts were accepted postintervention, a 39.6% relative increase in acceptance rate (95% CI: 33.2-47.2%), but only a 2.1% absolute increase (95% CI: 1.8-2.4%). When only orders generating a single medication alert were considered, there was a 69.1% relative decrease in the number of orders generating DDI alerts, and an 85.7% relative increase in the acceptance rate (95% CI: 58.6-126.2%), though only a 1.8% absolute increase (95% CI: 1.3-2.3%).

CONCLUSION

Eliminating intermediate severity DDI alerts resulted in a statistically significant decrease in alert burden and increase in the rate of medication alert acceptance, but alert acceptance remained low overall.

Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support

Objective

Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care.

Material and Methods

A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems.

Results

Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features.

Discussion

Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS.

Conclusion

This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.

An Exploration of Barriers, Facilitators, and Suggestions for Improving Electronic Health Record Inbox-Related Usability: A Qualitative Analysis

IMPORTANCE

Managing messages in the electronic health record (EHR) inbox consumes substantial amounts of physician time. Certain factors associated with inbox management, such as poor usability and excessive and unnecessary inbox messages, have been associated with physician burnout. Additionally, inbox design, usability, and workflows are associated with physicians' situational awareness (ie, perception, comprehension, and projection of clinical status) and efficiency of processing EHR inbox messages. Understanding factors associated with inbox usability could improve future EHR inbox designs and workflows, thus reducing risk of burnout while improving patient safety.

OBJECTIVE

To determine barriers, facilitators, and suggestions associated with EHR inbox-related usability.

DESIGN, SETTING, AND PARTICIPANTS

This qualitative study included cognitive walkthroughs of EHR inbox management with 25 physicians (17 primary care physicians and 8 specialists) at 6 large health care organizations using 4 different EHR systems between May 6, 2015, and September 19, 2016. While processing EHR inbox messages, participants identified facilitators and barriers associated with EHR inbox situational awareness and processing efficiency and potential interventions to address such barriers. A qualitative analysis was performed on transcribed recordings using an inductive thematic approach with an 8-dimension sociotechnical model as a theoretical lens from May 6, 2015, to August 15, 2019.

RESULTS

The cognitive walkthroughs identified 60 barriers, 32 facilitators, and 28 suggestions for improving the EHR inbox. Emergent data fit within 5 major themes: message processing complexity, inbox interface design, cognitive load, team communication, and inbox message content. Within these themes, similar barriers were identified across sites, such as poor usability due the high numbers of clicks needed to accomplish actions. In certain instances, an identified facilitator at one site provided the exact solution needed to address a barrier identified at another site.

CONCLUSIONS AND RELEVANCE

This qualitative study found that usability of the EHR inbox is often suboptimal and variable across sites, suggesting lack of shared best practices related to information management. Implementation of optimized design features and workflows will require EHR developers and health care organizations to collectively share this responsibility. Development of regional or national consortia to support collaborative sharing and implementation of EHR system best practices across EHR developers and health care organizations could also improve safety and efficiency and reduce physician burnout.

Practicing Clinicians' Recommendations to Reduce Burden from the Electronic Health Record Inbox: a Mixed-Methods Study

BACKGROUND

Workload from electronic health record (EHR) inbox notifications leads to information overload and contributes to job dissatisfaction and physician burnout. Better understanding of physicians' inbox requirements and workflows could optimize inbox designs, enhance efficiency, and reduce safety risks from information overload.

DESIGN

We conducted a mixed-methods study to identify strategies to enhance EHR inbox design and workflow. First, we performed a secondary analysis of national survey data of all Department of Veterans Affairs (VA) primary care practitioners (PCP) to identify major themes in responses to a free-text question soliciting suggestions to improve EHR inbox design and workflows. We then conducted expert interviews of clinicians at five health care systems (1 VA and 4 non-VA settings using 4 different EHRs) to understand existing optimal strategies to improve efficiency and situational awareness related to EHR inbox use. Themes from survey data were cross-validated with interview findings.

RESULTS

We analyzed responses from 2104 PCPs who completed the free-text inbox question (of 5001 PCPs who responded to survey) and used an inductive approach to identify five themes: (1) Inbox notification content should be actionable for patient care and relevant to recipient clinician, (2) Inboxes should reduce risk of losing messages, (3) Inbox functionality should be optimized to improve efficiency of processing notifications, (4) Team support should be leveraged to help with EHR inbox notification burden, (5) Sufficient time should be provided to all clinicians to process EHR inbox notifications. We subsequently interviewed 15 VA and non-VA clinicians and identified 11 unique strategies, each corresponding directly with one of these five themes.

CONCLUSION

Feedback from practicing end-user clinicians provides robust evidence to improve content and design of the EHR inbox and related clinical workflows and organizational policies. Several strategies we identified could improve clinicians' EHR efficiency and satisfaction as well as empower them to work with their local administrators, health IT personnel, and EHR developers to improve these systems.

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.

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study

Background

Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR–based clinical decision support (CDS), shedding light on whether and why CDS is effective.

Objective

This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians’ (PCPs’) opening of and response to noninterruptive alerts delivered to EHR InBaskets.

Methods

We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs’ InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients’ posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs’ follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use.

Results

We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation.

Conclusions

EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR–based study.

Impact of a national QI programme on reducing electronic health record notifications to clinicians

BACKGROUND

Emerging evidence suggests electronic health record (EHR)-related information overload is a risk to patient safety. In the US Department of Veterans Affairs (VA), EHR-based 'inbox' notifications originally intended for communicating important clinical information are now cited by 70% of primary care practitioners (PCPs) to be of unmanageable volume. We evaluated the impact of a national, multicomponent, quality improvement (QI) programme to reduce low-value EHR notifications.

METHODS

The programme involved three steps: (1) accessing daily PCP notification load data at all 148 facilities operated nationally by the VA; (2) standardising and restricting mandatory notification types at all facilities to a recommended list; and (3) hands-on training for all PCPs on customising and processing notifications more effectively. Designated leaders at each of VA's 18 regional networks led programme implementation using a nationally developed toolkit. Each network supervised technical requirements and data collection, ensuring consistency. Coaching calls and emails allowed the national team to address implementation challenges and monitor effects. We analysed notification load and mandatory notifications preintervention (March 2017) and immediately postintervention (June-July 2017) to assess programme impact.

RESULTS

Median number of mandatory notification types at each facility decreased significantly from 15 (IQR: 13-19) to 10 (IQR: 10-11) preintervention to postintervention, respectively (P<0.001). Mean daily notifications per PCP decreased significantly from 128 (SEM=4) to 116 (SEM=4; P<0.001). Heterogeneity in implementation across sites led to differences in observed programme impact, including potentially beneficial carryover effects.

CONCLUSIONS

Based on prior estimates on time to process notifications, a national QI programme potentially saved 1.5 hours per week per PCP to enable higher value work. The number of daily notifications remained high, suggesting the need for additional multifaceted interventions and protected clinical time to help manage them. Nevertheless, our project suggests feasibility of using large-scale 'de-implementation' interventions to reduce unintended safety or efficiency consequences of well-intended electronic communication systems.

Data-driven approach to Early Warning Score-based alert management

Background

Increasing adoption of electronic health records (EHRs) with integrated alerting systems is a key initiative for improving patient safety. Considering the variety of dynamically changing clinical information, it remains a challenge to design EHR-driven alerting systems that notify the right providers for the right patient at the right time while managing alert burden. The objective of this study is to proactively develop and evaluate a systematic alert-generating approach as part of the implementation of an Early Warning Score (EWS) at the study hospitals.

Methods

We quantified the impact of an EWS-based clinical alert system on quantity and frequency of alerts using three different alert algorithms consisting of a set of criteria for triggering and muting alerts when certain criteria are satisfied. We used retrospectively collected EHRs data from December 2015 to July 2016 in three units at the study hospitals including general medical, acute care for the elderly and patients with heart failure.

Results

We compared the alert-generating algorithms by opportunity of early recognition of clinical deterioration while proactively estimating alert burden at a unit and patient level. Results highlighted the dependency of the number and frequency of alerts generated on the care location severity and patient characteristics.

Conclusion

EWS-based alert algorithms have the potential to facilitate appropriate alert management prior to integration into clinical practice. By comparing different algorithms with regard to the alert frequency and potential early detection of physiological deterioration as key patient safety opportunities, findings from this study highlight the need for alert systems tailored to patient and care location needs, and inform alternative EWS-based alert deployment strategies to enhance patient safety.

Test results management and distributed cognition in electronic health record-enabled primary care

Managing abnormal test results in primary care involves coordination across various settings. This study identifies how primary care teams manage test results in a large, computerized healthcare system in order to inform health information technology requirements for test results management and other distributed healthcare services. At five US Veterans Health Administration facilities, we interviewed 37 primary care team members, including 16 primary care providers, 12 registered nurses, and 9 licensed practical nurses. We performed content analysis using a distributed cognition approach, identifying patterns of information transmission across people and artifacts (e.g. electronic health records). Results illustrate challenges (e.g. information overload) as well as strategies used to overcome challenges. Various communication paths were used. Some team members served as intermediaries, processing information before relaying it. Artifacts were used as memory aids. Health information technology should address the risks of distributed work by supporting awareness of team and task status for reliable management of results.

Challenges in Communication from Referring Clinicians to Pathologists in the Electronic Health Record Era

We report on the role played by electronic health record inbox messages (EHRmsg) in a safety event involving pathology. Evolving socio-cultural norms led to the coopting of EHRmsg for alternate use and oversight of a clinician to pathologist request. We retrospectively examined EHR inbox messages to pathologists over a 3 month block. 36 messages from 22 pathologists were assessed. 26 pertained to patient care including requests for report corrections and additional testing. 88% of requests had gone unaddressed. Clinicians assumed that pathologists used EHRmsg as clinical care team members, however, pathologists rarely did. Communication gaps exist between primary clinicians and pathologists in the EHR era and they have potential to result in patient harm. Different sociocultural norms and practice patterns between specialties underlie some of the breakdowns. Health information technology implementation needs to proactively look for new sociotechnical failure modes to avoid patient harm from communication lapses.

Time utilization and perceived psychosocial work environment among staff in Swedish primary care settings

Background

Over the past decades, reorganizations and structural changes in Swedish primary care have affected time utilization among health care professionals. Consequently, increases in administrative tasks have substantially reduced the time available for face-to-face consultations. This study examined how work-time was utilized and the association between work time utilization and the perceived psychosocial work environment in Swedish primary care settings.

Methods

This descriptive, multicentre, cross-sectional study was performed in 2014–2015. Data collection began with questionnaire. In the first section, respondents were asked to estimate how their workload was distributed between patients (direct and indirect patient work) and other work tasks. The questionnaire also comprised the Copenhagen Psychosocial Questionnaire, which assessed the psychosocial work environment. Next a time study was conducted where the participants reported their work-time based on three main categories: direct patient-related work, indirect patient-related work, and other work tasks. Each main category had a number of subcategories. The participants recorded the time spent (minutes) on each work task per hour, every day, for two separate weeks. Eleven primary care centres located in southeast Sweden participated. All professionals were asked to participate (n = 441), including registered nurses, primary care physicians, care administrators, nurse assistants, and allied professionals. Response rates were 75% and 79% for the questionnaires and the time study, respectively.

Results

All health professionals allocated between 30.9% - 37.2% of their work-time to each main category: direct patient work, indirect patient work, and other work. All professionals estimated a higher proportion of time spent in direct patient work than they reported in the time study. Physicians scored highest on the psychosocial scales of quantitative demands, stress, and role conflicts. Among allied professionals, the proportion of work-time spent on administrative tasks was associated with more role conflicts. Younger staff perceived more adverse working conditions than older staff.

Conclusions

This study indicated that Swedish primary care staff spent a limited proportion of their work time directly with patients. PCPs seemed to perceive their work environment in negative terms to a greater extent than other staff members. This study showed that work task allocations influenced the perceived psychosocial work environment.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-2948-6) contains supplementary material, which is available to authorized users.

Assessing the Burden of Abnormal LFTs and the Role of the Electronic Health Record: A Retrospective Study

BACKGROUND

Primary care clinicians encounter abnormal liver function tests (LFTs) frequently. This study assesses the prevalence of abnormal LFTs and patient follow-up patterns in response.

METHODS

This is a retrospective study from 2007-2016 of adult patients with abnormal LFTs seen in an internal medicine clinic. The proportion of patients with follow-up testing and the time (in days) to repeat LFTs were the primary outcomes measured. Results were evaluated before and after the implementation of the institution's electronic health record (EHR).

RESULTS

This study identified a period prevalence for abnormal LFTs of 39%. Of these, 9,545 unique patients met inclusion criteria, with 8,415 patients (88.2%) possessing follow-up LFTs and no significant difference in the proportion of patients receiving follow-up by degree of initial abnormality. Median time to follow-up in mild abnormalities (1-2 times normal) was 138 days, compared to 21 days for severe abnormalities (>4 times normal, P < 0.0001). Reduced time to repeat testing across all spectrums of abnormality was observed following EHR implementation, but proportions of missing follow-up did not improve. A multivariable logistic regression model identified younger age, poverty, living over 50 miles from clinic, recent cohort entry and a lower magnitude of abnormality as predictors for missing repeat LFT testing (area under the curve = 0.838 [95% CI: 0.827-0.849]).

CONCLUSIONS

Abnormal LFTs were detected in 39% of all patients seen. The degree of LFT abnormality did not influence rates of follow-up testing, but does appear to play a role in the timing of repeat testing, when obtained. Follow-up rates did not improve with EHR implementation.

Educational Technologies for Physician Continuous Professional Development: A National Survey

PURPOSE

To determine the past experiences with, current use of, and anticipated use of online learning and simulation-based education among practicing U.S. physicians, and how findings vary by age.

METHOD

The authors surveyed 4,648 randomly sampled board-certified U.S. physicians, September 2015 to April 2016, using Internet-based and paper questionnaires. Survey items (some optional) addressed past and current technology usage, perceived technology effectiveness, and anticipated future use of specific technology innovations.

RESULTS

Of 988 respondents, 444 completed optional items. Of these, 429/442 (97.1%) had used online learning and 372/442 (84.2%) had used simulation-based education in the past five years. Desire for more online learning was modest (mean [standard deviation], 4.6 [1.5]; 1 = strongly disagree, 7 = strongly agree), as was desire for more simulation-based education (4.2 [1.7]). Both online learning and simulation-based education were perceived as effective (5.2 [1.4]; 5.0 [1.4]). Physicians believed they possess adequate skills for online learning (5.8 [1.2]) and that point-of-care learning is vital to effective patient care (5.3 [1.3]). Only 39.0% used objective performance data to guide their learning choices, although 64.6% agreed that such information would be useful. The highest-rated innovations included a central repository for listing educational opportunities and tracking continuing education credits, an app to award credit for answering patient-focused questions, 5-minute and 20-minute clinical updates, and an e-mailed "question of the week." Responses to most survey items were similar across age groups.

CONCLUSIONS

Practicing physicians generally seem receptive and prepared to use a variety of educational technologies, regardless of age.

Development and Validation of Trigger Algorithms to Identify Delays in Diagnostic Evaluation of Gastroenterological Cancer

BACKGROUND & AIMS

Colorectal cancer (CRC) and hepatocellular cancer (HCC) are common causes of death and morbidity, and patients benefit from early detection. However, delays in follow-up of suspicious findings are common, and methods to efficiently detect such delays are needed. We developed, refined, and tested trigger algorithms that identify patients with delayed follow-up evaluation of findings suspicious of CRC or HCC.

METHODS

We developed and validated two trigger algorithms that detect delays in diagnostic evaluation of CRC and HCC using laboratory, diagnosis, procedure, and referral codes from the Department of Veteran Affairs National Corporate Data Warehouse. The algorithm initially identified patients with positive test results for iron deficiency anemia or fecal immunochemical test (for CRC) and elevated α-fetoprotein results (for HCC). Our algorithm then excluded patients for whom follow-up evaluation was unnecessary, such as patients with a terminal illness or those who had already completed a follow-up evaluation within 60 days. Clinicians reviewed samples of both delayed and nondelayed records, and review data were used to calculate trigger performance.

RESULTS

We applied the algorithm for CRC to 245,158 patients seen from January 1, 2013, through December 31, 2013 and identified 1073 patients with delayed follow up. In a review of 400 randomly selected records, we found that our algorithm identified patients with delayed follow-up with a positive predictive value of 56.0% (95% CI, 51.0%-61.0%). We applied the algorithm for HCC to 333,828 patients seen from January 1, 2011 through December 31, 2014, and identified 130 patients with delayed follow-up. During manual review of all 130 records, we found that our algorithm identified patients with delayed follow-up with a positive predictive value of 82.3% (95% CI, 74.4%-88.2%). When we extrapolated the findings to all patients with abnormal results, the algorithm identified patients with delayed follow-up evaluation for CRC with 68.6% sensitivity (95% CI, 65.4%-71.6%) and 81.1% specificity (95% CI, 79.5%-82.6%); it identified patients with delayed follow-up evaluation for HCC with 89.1% sensitivity (95% CI, 81.8%-93.8%) and 96.5% specificity (95% CI, 94.8%-97.7%). Compared to nonselective methods, use of the algorithm reduced the number of records required for review to identify a delay by more than 99%.

CONCLUSIONS

Using data from the Veterans Affairs electronic health record database, we developed an algorithm that greatly reduces the number of record reviews necessary to identify delays in follow-up evaluations for patients with suspected CRC or HCC. This approach offers a more efficient method to identify delayed diagnostic evaluation of gastroenterological cancers.

Primary Care Providers' Opening of Time-Sensitive Alerts Sent to Commercial Electronic Health Record InBaskets

BACKGROUND

Time-sensitive alerts are among the many types of clinical notifications delivered to physicians' secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care.

OBJECTIVE

To characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets.

DESIGN AND PARTICIPANTS

We analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010-2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications.

MAIN MEASURES

Using EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h.

KEY RESULTS

At the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00-2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18-0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08-0.39]).

CONCLUSIONS

The number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.

Evaluating e-consultation implementations based on use and time-line across various specialties

BACKGROUND

Electronic Consultation (e-consults) can provide improved access, enhance patient and provider satisfaction, and reduce beneficiary travel expenses. We explored how e-consults were implemented across three specialty areas, diabetes (Diab), gastroenterology (GI), and neurosurgery (Neuro), at two Veterans Affairs hospitals in terms of strategies for use and time-lines.

METHODS

We conducted observations and electronically shadowed patient e-consultations submitted to a specialty care service by primary care provider(s) at the two sites during a thirteen-month period. We divided the e-consult process in each specialty into three broad milestones; Request (from primary to specialty), Response (from specialty back to primary), and Follow up (from primary to patient), and recorded the flow and time in each category. An overall hierarchy of e-consults was developed to illustrate the many ways an e-consult was used. The Kolmogorov-Smirnov test was used to compare the distribution of time across specialties.

RESULTS

A total of 394 consults submitted between April 14, 2012 and May 2, 2013 were reviewed (Diab=152, GI=169, Neuro=73). Of the 152 diabetes specialty clinic e-consults, 35% required some sort of direct contact with the patient by the specialty clinic before a recommendation was provided. Overall, 58% of the e-consults were completed within 20days, while 68% were completed within 30days. The Response times between Diab and GI were significantly different (median=0 vs. 3days; p<0.0001) and so were Follow up times (median=0 vs. 4days; p<0.0001). All three stages were statistically different between Diab and Neuro; however, there was not enough evidence to suggest any differences between GI and Neuro.

CONCLUSIONS

The use of an e-consult is likely to vary based on the specialty, but the often significant variations in time may continue to hinder prompt access to care. E-consult design, implementation, documentation, training, self-learning, and monitoring should be tailored to get the most benefit out of this system.

Patient, Provider, and System Factors Associated With Failure to Follow-Up Elevated Glucose Results in Patients Without Diagnosed Diabetes

Background:

Although elevated glucose values are strongly associated with undiagnosed diabetes, they are frequently overlooked. Patient, provider, and system factors associated with failure to follow-up elevated glucose values in electronic medical records (EMRs) are not well described.

Methods:

We conducted a chart review in a comprehensive EMR with a patient portal and results management features. Established primary care patients with no known diagnosis of diabetes and ≥ 1 glucose value >125 mg/dL were included. Follow-up failure was defined as (1) no documented comment on the glucose value or result communication to the patient within 30 days or (2) no hemoglobin A_1c (HbA_1c) ordered within 30 days or resulted within 12 months. Associations were examined using Wilcoxon and χ² tests.

Results:

Of 150 charts reviewed, 97 met inclusion criteria. The median glucose was 133 mg/dL, and 20% of patients had multiple values >125 mg/dL. Only 36% of elevated glucose values were followed up. No associations were observed between patient characteristics, diabetes risk factors, or provider characteristics and follow-up failures. Automated flagging of glucose values ≥140 mg/dL by highlighting them red in the EMR was not associated with improved follow-up (46% vs 32%; P = .19). Even when follow-up occurred (n = 35), only 31% completed gold standard diabetes testing (HbA_1c) within 12 months. Of the resulted HbA_1c tests (n = 11), 55% were in the prediabetes range (5.7%-6.4%).

Conclusions:

Two-thirds of elevated glucose values were not followed up, despite EMR features facilitating results management. Greater understanding of the results management process and improved EMR functionalities to support results management are needed.