Implementation of a Web-Based Communication System for Primary Care Providers and Cancer Specialists

Healthcare providers have reported challenges with coordinating care for patients with cancer. Digital technology tools have brought new possibilities for improving care coordination. A web- and text-based asynchronous system (eOncoNote) was implemented in Ottawa, Canada for cancer specialists and primary care providers (PCPs). This study aimed to examine PCPs' experiences of implementing eOncoNote and how access to the system influenced communication between PCPs and cancer specialists. As part of a larger study, we collected and analyzed system usage data and administered an end-of-discussion survey to understand the perceived value of using eOncoNote. eOncoNote data were analyzed for 76 shared patients (33 patients receiving treatment and 43 patients in the survivorship phase). Thirty-nine percent of the PCPs responded to the cancer specialist's initial eOncoNote message and nearly all of those sent only one message. Forty-five percent of the PCPs completed the survey. Most PCPs reported no additional benefits of using eOncoNote and emphasized the need for electronic medical record (EMR) integration. Over half of the PCPs indicated that eOncoNote could be a helpful service if they had questions about a patient. Future research should examine opportunities for EMR integration and whether additional interventions could support communication between PCPs and cancer specialists.

A Trend-Based Early Warning Score Can Be Implemented in a Hospital Electronic Medical Record to Effectively Predict Inpatient Deterioration

OBJECTIVES

To determine whether a statistically derived, trend-based, deterioration index is superior to other early warning scores at predicting adverse events and whether it can be integrated into an electronic medical record to enable real-time alerts.

DESIGN

Forty-three variables and their trends from cases and controls were used to develop a logistic model and deterioration index to predict patient deterioration greater than or equal to 1 hour prior to an adverse event.

SETTING

Two large Australian teaching hospitals.

PATIENTS

Cases were considered as patients who suffered adverse events (unexpected death, unplanned ICU transfer, urgent surgery, and rapid-response alert) between August 1, 2016, and April 1, 2019.

INTERVENTIONS

The logistic model and deterioration index were tested on historical data and then integrated into an electronic medical record for a 6-month prospective "silent" validation.

MEASUREMENTS AND MAIN RESULTS

Data were acquired from 258,732 admissions. There were 8,002 adverse events. The addition of vital sign and laboratory trend values to the logistic model increased the area under the curve from 0.84 to 0.89 and the sensitivity to predict an adverse event 1-48 hours prior from 0.35 to 0.41. A 48-hour simulation showed that the logistic model had a higher area under the curve than the Modified Early Warning Score and National Early Warning Score (0.87 vs 0.74 vs 0.71). During the silently run prospective trial, the sensitivity of the deterioration index to detect adverse event any time prior to the adverse event was 0.474, 0.369 1 hour prior, and 0.327 4 hours prior, with a specificity of 0.972.

CONCLUSIONS

A deterioration prediction model was developed using patient demographics, ward-based observations, laboratory values, and their trends. The model's outputs were converted to a deterioration index that was successfully integrated into a live hospital electronic medical record. The sensitivity and specificity of the tool to detect inpatient deterioration were superior to traditional early warning scores.

Differences in Clinician Electronic Health Record Use Across Adult and Pediatric Primary Care Specialties

This cross-sectional study examines differences in electronic health record use across adult and pediatric primary care specialties.

Length and Redundancy of Outpatient Progress Notes Across a Decade at an Academic Medical Center

IMPORTANCE

There is widespread concern that clinical notes have grown longer and less informative over the past decade. Addressing these concerns requires a better understanding of the magnitude, scope, and potential causes of increased note length and redundancy.

OBJECTIVE

To measure changes between 2009 and 2018 in the length and redundancy of outpatient progress notes across multiple medical specialties and investigate how these measures associate with author experience and method of note entry.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study was conducted at Oregon Health & Science University, a large academic medical center. Participants included clinicians and staff who wrote outpatient progress notes between 2009 and 2018 for a random sample of 200 000 patients. Statistical analysis was performed from March to August 2020.

EXPOSURES

Use of a comprehensive electronic health record to document patient care.

MAIN OUTCOMES AND MEASURES

Note length, note redundancy (ie, the proportion of text identical to the patient's last note), and percentage of templated, copied, or directly typed note text.

RESULTS

A total of 2 704 800 notes written by 6228 primary authors across 46 specialties were included in this study. Median note length increased 60.1% (99% CI, 46.7%-75.2%) from a median of 401 words (interquartile range [IQR], 225-660 words) in 2009 to 642 words (IQR, 399-1007 words) in 2018. Median note redundancy increased 10.9 percentage points (99% CI, 7.5-14.3 percentage points) from 47.9% in 2009 to 58.8% in 2018. Notes written in 2018 had a mean value of just 29.4% (99% CI, 28.2%-30.7%) directly typed text with the remaining 70.6% of text being templated or copied. Mixed-effect linear models found that notes with higher proportions of templated or copied text were significantly longer and more redundant (eg, in the 2-year model, each 1% increase in the proportion of copied or templated note text was associated with 1.5% [95% CI, 1.5%-1.5%] and 1.6% [95% CI, 1.6%-1.6%] increases in note length, respectively). Residents and fellows also wrote significantly (26.3% [95% CI, 25.8%-26.7%]) longer notes than more senior authors, as did more recent hires (1.8% for each year later [95% CI, 1.3%-2.4%]).

CONCLUSIONS AND RELEVANCE

In this study, outpatient progress notes grew longer and more redundant over time, potentially limiting their use in patient care. Interventions aimed at reducing outpatient progress note length and redundancy may need to simultaneously address multiple factors such as note template design and training for both new and established clinicians.

Harnessing the electronic health record to advance integrated care

INTRODUCTION

Integrated health care is utilized in primary care clinics to meet patients' physical, behavioral, and social needs. Current methods to collect and evaluate the effectiveness of integrated care require refinement. Using informatics and electronic health records (EHR) to distill large amounts of clinical data may help researchers measure the impact of integrated care more efficiently. This exploratory pilot study aimed to (a) determine the feasibility of using EHR documentation to identify behavioral health and social care components of integrated care, using social work as a use case, and (b) develop a lexicon to inform future research using natural language processing.

METHOD

Study steps included development of a preliminary lexicon of behavioral health and social care interventions to address basic needs, creation of an abstraction guide, identification of appropriate EHR notes, manual chart abstraction, revision of the lexicon, and synthesis of findings.

RESULTS

Notes (N = 647) were analyzed from a random sample of 60 patients. Notes documented behavioral health and social care components of care but were difficult to identify due to inconsistencies in note location and titling. Although the interventions were not described in detail, the outcomes of screening, referral, and brief treatment were included. The integrated care team frequently used EHR to share information and communicate.

DISCUSSION

Opportunities and challenges to using EHR data were identified and need to be addressed to better understand the behavioral health and social care interventions in integrated care. To best leverage EHR data, future research must determine how to document and extract pertinent information about integrated team-based interventions. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Four Years Later: Examining Nurse Perceptions of Electronic Documentation Over Time

OBJECTIVE

To examine changes in registered nurse (RN) perceptions of electronic documentation over a 4-year period.

BACKGROUND

The investigators previously reported differences in RN perceptions prior to and 1 year after adoption of a comprehensive electronic health record (EHR).

METHODS

Investigators repeated the study 4 years after adoption, using the Nurses' Perceptions of Electronic Documentation tool and interviews with a subset of RNs.

RESULTS

Nurses scored higher on ease of use domain and lower on concern about the EHR domain and showed no difference on the impacts of the EHR domain. Interviews revealed that 4 years later, some aspects of documentation were easier; the tool was comprehensive, but not without risk, and nurses remained ambivalent about the EHR.

CONCLUSIONS

Use of EHR technology impacts nursing work. It is important to understand how nurses' perceptions change over time. This study gives nursing leaders insight into adoption and acceptance of an EHR.

Antimicrobial Stewardship by Leveraging Electronic Medical Records

This paper describes how an antimicrobial stewardship program was successfully developed and integrated into a university medical center's electronic healthcare records and improved antibiotic selection.

Early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma is most frequently detected at an advanced stage. Such late detection restricts treatment options and contributes to a dismal 5-year survival rate of 3-15%. Pancreatic ductal adenocarcinoma is relatively uncommon and screening of the asymptomatic adult population is not feasible or recommended with current modalities. However, screening of individuals in high-risk groups is recommended. Here, we review groups at high risk for pancreatic ductal adenocarcinoma, including individuals with inherited predisposition and patients with pancreatic cystic lesions. We discuss studies aimed at finding ways of identifying pancreatic ductal adenocarcinoma in high-risk groups, such as among individuals with new-onset diabetes mellitus and people attending primary and secondary care practices with symptoms that suggest this cancer. We review early detection biomarkers, explore the potential of using social media for detection, appraise prediction models developed using electronic health records and research data, and examine the application of artificial intelligence to medical imaging for the purposes of early detection.

Toward the Design of an Engagement Tool for Effective Electronic Health Record Adoption

As healthcare systems continue to expand their use of electronic health records (EHRs), barriers to robust and successful engagement with such systems by stakeholders remain tenacious. To this effect, this research presents the results of a survey tool utilizing both original and modified constructs from the Consolidated Framework for Implementation Research to assess key points of engagement barriers and potential points of intervention for stakeholders of EHRs in a large-scale healthcare organization (500-bed level II regional trauma center). Based on the extensive assessment, the paper presents recommendations for the utility of engagement process modeling and discusses how intervention opportunities can be used to mitigate engagement barriers.

A Pilot Study of Use of a Software Platform for the Collection, Integration, and Visualization of Diabetes Device Data by Health Care Providers in a Multidisciplinary Pediatric Setting

BACKGROUND

Diabetes devices provide data for health care providers (HCPs) and people with type 1 diabetes to make management decisions. Extracting and viewing the data require separate, proprietary software applications for each device. In this pilot study, we examined the feasibility of using a single software platform (Tidepool) that integrates data from multiple devices.

MATERIALS AND METHODS

Participating HCPs (n = 15) used the software with compatible devices in all patient visits for 6 months. Samples of registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups.

RESULTS

The time required to upload data and the length of the office visit did not change. However, the number of times the HCP referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per visit (P = 0.0002). A significantly larger proportion of children looked at the device data with the new application (baseline: 61% vs. study end: 94%, P = 0.015). HCPs liked the web-based user interface, integration of the data from multiple devices, the ability to remotely access data, and use of the application to initiate patient education. Challenges included the need for automated data upload and integration with electronic medical records.

CONCLUSIONS

The software did not add to the time needed to upload data or the length of clinic visits and promoted discussions with patients about data. Future studies of HCP use of the application will evaluate clinical outcomes and effects on patient engagement and self-management.

A pilot study: a teaching electronic medical record for educating and assessing residents in the care of patients

OBJECTIVE

We tested a novel, web-based teaching electronic medical record to teach and assess residents' ability to enter appropriate admission orders for patients admitted to the intensive care unit. The primary objective was to determine if this tool could improve the learners' ability to enter an evidence-based, comprehensive initial care plan for critically ill patients.

METHODS

The authors created three modules using de-identifed real patient data from selected patients that were admitted to the intensive care unit. All senior residents (113 total) were invited to participate in a dedicated two-hour educational session to complete the modules. Learner performance was graded against gold standard admission order sets created by study investigators based on the latest evidence-based medicine and guidelines.

RESULTS

The session was attended by 39 residents (34.5% of invitees). There was an average improvement of at least 20% in users' scores across the three modules (Module 3-Module 1 mean difference 22.5%; p = 0.001 and Module 3-Module 2 mean difference 20.3%; p = 0.001). Diagnostic acumen improved in successive modules. Almost 90% of the residents reported the technology was an effective form of teaching and would use it autonomously if more modules were provided.

CONCLUSIONS

In this pilot project, using a novel educational tool, users' patient care performance scores improved with a high level of user satisfaction. These results identify a realistic and well-received way to supplement residents' training and assessment on core clinical care and patient management in the face of duty hour restrictions.

Sometimes determination and compromise thwart success: lessons learned from an effort to study copying and pasting in the electronic medical record

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An Overview of the Application of Wearable Technology to Nursing Practice

PROBLEM

Wearable technology is here and nurses are going to be increasingly responsible for patients who use it. Most research in this area has been done in other fields and now is the time for nurses to be more involved in this promising technology to improve patient lives.

METHODS

This paper synthesizes the current state of wearable technology, a brief history of nurse satisfaction with technology, current research about wearable technology, and implications for its future use in nursing.

FINDINGS

Other areas in health care are already employing wearable technology to improve gait in people with Parkinson's disease, provide automatic defibrillation in cardiac patients, and monitor poststroke rehabilitation. Nurses can be on the front lines of designing and patenting new ideas to improve the lives of their patients.

CONCLUSIONS

Nurses have always adopted the newest technologies such as electronic health records, electronic medication administration records, and simulation experiences in education. Wearable technology is the next step in this journey and the possible uses are endless. Involving patients in their own care is a major goal of nursing and more research is needed to connect patients and their caregivers to the benefits of wearable technology.

Identifying Barriers in the Use of Electronic Health Records in Hawai'i

Hawai'i faces unique challenges to Electronic Health Record (EHR) adoption due to physician shortages, a widespread distribution of Medically Underserved Areas and Populations (MUA/P), and a higher percentage of small independent practices. However, research on EHR adoption in Hawai'i is limited. To address this gap, this article examines the current state of EHR in Hawai'i, the barriers to adoption, and the future of Health Information Technology (HIT) initiatives to improve the health of Hawai'i's people. Eight focus groups were conducted on Lana'i, Maui, Hawai'i Island, Kaua'i, Moloka'i, and O'ahu. In these groups, a total of 51 diverse health professionals were asked about the functionality of EHR systems, barriers to use, facilitators of use, and what EHRs would look like in a perfect world. Responses were summarized and analyzed based on constant comparative analysis techniques. Responses were then clustered into thirteen themes: system compatibility, loss of productivity, poor interface, IT support, hardware/software, patient factors, education/training, noise in the system, safety, data quality concerns, quality metrics, workflow, and malpractice concerns. Results show that every group mentioned system compatibility. In response to these findings, the Health eNet Community Health Record initiative - which allows providers web-based access to patient health information from the patient's provider network- was developed as a step toward alleviating some of the barriers to sharing information between different EHRs. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) legislation will introduce a new payment model in 2017 that is partially based on EHR utilization. Therefore, more research should be done to understand EHR adoption and how this ruling will affect providers in Hawai'i.

Exploring family and social context through the electronic health record: Physicians' experiences

INTRODUCTION

There is ample evidence that social and familial context significantly impacts health. However, family and social history templates typically used in clinical practice exclude prompts to explore important contextual information, such as family dynamics, health beliefs, housing, and neighborhood environment.

METHOD

At the Residency Program in Social Medicine at Montefiore Medical Center/Albert Einstein College of Medicine in Bronx, NY, we developed and piloted an expanded family and social information (FSI) template in our electronic health record (EHR) system. After 10 physicians used the FSI template during routine clinical practice, we conducted and qualitatively analyzed transcripts of semistructured interviews to assess their experiences.

RESULTS

The major themes of physician's experiences using the FSI template included: expanded thinking (promoted thinking and discussion about contextual information), relevancy to care (highlighted important life events, helpful resource for future care or for team-based care), fragmentation (patient narrative difficult to categorize into discrete sections), and abstract phrasing (prompts too abstract and/or too complex to explore well). Some minor themes (themes that were repeated often, but not consistent in all interviews) were also noted: practice demands, educational purpose, and wish list.

DISCUSSION

Within our small sample, we found that an expanded family and social information template broadened physicians' clinical thinking during routine visits. We also found that the structure of the EHR and practice demands create significant barriers to exploring a patient's narrative effectively. Themes identified in this research will inform national efforts to prioritize a contextual and biopsychosocial perspective in EHR systems. (PsycINFO Database Record

Bedside patient data viewer using RFID and e-Ink technology

In the daily routine of hospitals, which work with paper based medical records, the staff has to find the appropriate patient file if it needs information about the patient. With the introduction of ELGA the Austrian hospitals have to use specific standards for their clinical documentation. These structured documents can be used to feed an e-Ink reader with information about every patient in a hospital. Combined with RFID and security measures, the clinical staff is supported during the patient file searching process. The developed experimental setup of the Bedside Patient Data Viewer demonstrates a prototype of such a system. An Amazon Kindle Paperwhite is used to display processed data, supplied by a Raspberry Pi with an attached RFID module for identification purposes. Results show that such a system can be implemented, however a lot of organizational and technical issues remain to be solved.

A vital signs telemonitoring system - interoperability supported by a personal health record systema and a cloud service

This article presents the development process of an acquisition and data storage system managing clinical variables through a cloud storage service and a Personal Health Record (PHR) System. First, the paper explains how a Wireless Body Area Network (WBAN) that captures data from two sensors corresponding to arterial pressure and heart rate is designed. Second, this paper illustrates how data collected by the WBAN are transmitted to a cloud storage service. It is worth mentioning that this cloud service allows the data to be stored in a persistent way on an online database system. Finally, the paper describes, how the data stored in the cloud service are sent to the Indivo PHR System, where they are registered and charted for future revision by health professionals. The research demonstrated the feasibility of implementing WBAN networks for the acquisition of clinical data, and particularly for the use of Web technologies and standards to provide interoperability with PHR Systems at technical and syntactic levels.

Automatic prediction of rheumatoid arthritis disease activity from the electronic medical records

OBJECTIVE

We aimed to mine the data in the Electronic Medical Record to automatically discover patients' Rheumatoid Arthritis disease activity at discrete rheumatology clinic visits. We cast the problem as a document classification task where the feature space includes concepts from the clinical narrative and lab values as stored in the Electronic Medical Record.

MATERIALS AND METHODS

The Training Set consisted of 2792 clinical notes and associated lab values. Test Set 1 included 1749 clinical notes and associated lab values. Test Set 2 included 344 clinical notes for which there were no associated lab values. The Apache clinical Text Analysis and Knowledge Extraction System was used to analyze the text and transform it into informative features to be combined with relevant lab values.

RESULTS

Experiments over a range of machine learning algorithms and features were conducted. The best performing combination was linear kernel Support Vector Machines with Unified Medical Language System Concept Unique Identifier features with feature selection and lab values. The Area Under the Receiver Operating Characteristic Curve (AUC) is 0.831 (σ = 0.0317), statistically significant as compared to two baselines (AUC = 0.758, σ = 0.0291). Algorithms demonstrated superior performance on cases clinically defined as extreme categories of disease activity (Remission and High) compared to those defined as intermediate categories (Moderate and Low) and included laboratory data on inflammatory markers.

CONCLUSION

Automatic Rheumatoid Arthritis disease activity discovery from Electronic Medical Record data is a learnable task approximating human performance. As a result, this approach might have several research applications, such as the identification of patients for genome-wide pharmacogenetic studies that require large sample sizes with precise definitions of disease activity and response to therapies.

Harnessing clinical psychiatric data with an electronic assessment tool (OPCRIT+): the utility of symptom dimensions

Progress in personalised psychiatry is dependent on researchers having access to systematic and accurately acquired symptom data across clinical diagnoses. We have developed a structured psychiatric assessment tool, OPCRIT+, that is being introduced into the electronic medical records system of the South London and Maudsley NHS Foundation Trust which can help to achieve this. In this report we examine the utility of the symptom data being collected with the tool. Cross-sectional mental state data from a mixed-diagnostic cohort of 876 inpatients was subjected to a principal components analysis (PCA). Six components, explaining 46% of the variance in recorded symptoms, were extracted. The components represented dimensions of mania, depression, positive symptoms, anxiety, negative symptoms and disorganization. As indicated by component scores, different clinical diagnoses demonstrated distinct symptom profiles characterized by wide-ranging levels of severity. When comparing the predictive value of symptoms against diagnosis for a variety of clinical outcome measures (e.g. ‘Overactive, aggressive behaviour’), symptoms proved superior in five instances (R² range: 0.06–0.28) whereas diagnosis was best just once (R²∶0.25). This report demonstrates that symptom data being routinely gathered in an NHS trust, when documented on the appropriate tool, have considerable potential for onward use in a variety of clinical and research applications via representation as dimensions of psychopathology.