Forced Inefficiencies of the Electronic Health Record

Leveraging multi-source to resolve inconsistency across pharmacogenomic datasets in drug sensitivity prediction

Pharmacogenomics datasets have been generated for various purposes, such as investigating different biomarkers. However, when studying the same cell line with the same drugs, differences in drug responses exist between studies. These variations arise from factors such as inter-tumoral heterogeneity, experimental standardization, and the complexity of cell subtypes. Consequently, drug response prediction suffers from limited generalizability. To address these challenges, we propose a computational model based on Federated Learning (FL) for drug response prediction. By leveraging three pharmacogenomics datasets (CCLE, GDSC2, and gCSI), we evaluate the performance of our model across diverse cell line-based databases. Our results demonstrate superior predictive performance compared to baseline methods and traditional FL approaches through various experimental tests. This study underscores the potential of employing FL to leverage multiple data sources, enabling the development of generalized models that account for inconsistencies among pharmacogenomics datasets. By addressing the limitations of low generalizability, our approach contributes to advancing drug response prediction in precision oncology.

Smart healthcare system using integrated and lightweight ECC with private blockchain for multimedia medical data processing

Cloud-based Healthcare 4.0 systems have research challenges with secure medical data processing, especially biomedical image processing with privacy protection. Medical records are generally text/numerical or multimedia. Multimedia data includes X-ray scans, Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, etc. Transferring biomedical multimedia data to medical authorities raises various security concerns. This paper proposes a one-of-a-kind blockchain-based secure biomedical image processing system that maintains anonymity. The integrated Healthcare 4.0 assisted multimedia image processing architecture includes an edge layer, fog computing layer, cloud storage layer, and blockchain layer. The edge layer collects and sends periodic medical information from the patient to the higher layer. The multimedia data from the edge layer is securely preserved in blockchain-assisted cloud storage through fog nodes using lightweight cryptography. Medical users then safely search such data for medical treatment or monitoring. Lightweight cryptographic procedures are proposed by employing Elliptic Curve Cryptography (ECC) with Elliptic Curve Diffie-Hellman (ECDH) and Elliptic Curve Digital Signature (ECDS) algorithm to secure biomedical image processing while maintaining privacy (ECDSA). The proposed technique is experimented with using publically available chest X-ray and CT images. The experimental results revealed that the proposed model shows higher computational efficiency (encryption and decryption time), Peak to Signal Noise Ratio (PSNR), and Meas Square Error (MSE).

Evaluating Electronic Health Record Limitations and Time Expenditure in a German Medical Center

OBJECTIVES

This study set out to obtain a general profile of physician time expenditure and electronic health record (EHR) limitations in a large university medical center in Germany. We also aim to illustrate the merit of a tool allowing for easier capture and prioritization of specific clinical needs at the point of care for which the current study will inform development in subsequent work.

METHODS

Nineteen physicians across six different departments participated in this study. Direct clinical observations were conducted with 13 out of 19 physicians for a total of 2,205 minutes, and semistructured interviews were conducted with all participants. During observations, time was measured for larger activity categories (searching information, reading information, documenting information, patient interaction, calling, and others). Semistructured interviews focused on perceived limitations, frustrations, and desired improvements regarding the EHR environment.

RESULTS

Of the observed time, 37.1% was spent interacting with the health records (9.0% searching, 7.7% reading, and 20.5% writing), 28.0% was spent interacting with patients corrected for EHR use (26.9% of time in a patient's presence), 6.8% was spent calling, and 28.1% was spent on other activities. Major themes of discontent were a spread of patient information, high and often repeated documentation burden, poor integration of (new) information into workflow, limits in information exchange, and the impact of such problems on patient interaction. Physicians stated limited means to address such issues at the point of care.

CONCLUSION

In the study hospital, over one-third of physicians' time was spent interacting with the EHR, environment, with many aspects of used systems far from optimal and no convenient way for physicians to address issues as they occur at the point of care. A tool facilitating easier identification and registration of issues, as they occur, may aid in generating a more complete overview of limitations in the EHR environment.

Impact of a medical scribe on clinical efficiency and quality in an academic general internal medicine practice

Background

Scribes have been proposed as an intervention to decrease physician electronic health record (EHR) workload and improve clinical quality. We aimed to assess the impact of a scribe on clinical efficiency and quality in an academic internal medicine practice.

Methods

Six faculty physicians worked with one scribe at an urban academic general internal medicine clinic April through June 2017. Patient visits during the 3 months prior to intervention (baseline, n = 789), unscribed visits during the intervention (concurrent control, n = 605), and scribed visits (n = 579) were included in the study. Clinical efficiency outcomes included time to close encounter, patient time in clinic, and number of visits per clinic session. Quality outcomes included EHR note quality, rates of medication and immunization review, population of patient instructions, reconciliation of outside information, and completion of preventative health recommendations.

Results

Median time to close encounter (IQR) was lower for scribed visits [0.4 (4.8) days] compared to baseline and unscribed visits [1.2 (5.9) and 2.9 (5.4) days, both p < 0.001]. Scribed notes were more likely to have a clear history of present illness (HPI) [OR = 7.30 (2.35–22.7), p = 0.001] and sufficient HPI information [OR = 2.21 (1.13–4.35), p = 0.02] compared to unscribed notes. Physicians were more likely to review the medication list during scribed vs. baseline visits [OR = 1.70 (1.22–2.35), p = 0.002]. No differences were found in the number of visits per clinic session, patient time in clinic, completion of preventative health recommendations, or other outcomes.

Conclusions

Working with a scribe in an academic internal medicine practice was associated with more timely documentation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06710-y.

Effect of Outpatient Note Templates on Note Quality: NOTE (Notation Optimization through Template Engineering) Randomized Clinical Trial

BACKGROUND

This is the first randomized controlled trial evaluating the impact of note template design on note quality using a simulated patient encounter and a validated assessment tool.

OBJECTIVE

To compare note quality between two different templates using a novel randomized clinical simulation process.

DESIGN

A randomized non-blinded controlled trial of a standard note template versus redesigned template.

PARTICIPANTS

PGY 1-3 IM residents.

INTERVENTIONS

Residents documented the simulated patient encounter using one of two templates. The standard template was modeled after the usual outpatient progress note. The new template placed the assessment and plan section in the beginning, grouped subjective data into the assessment, and deemphasized less useful elements.

MAIN MEASURES

Note length; time to note completion; note template evaluation by resident authors; note evaluation by faculty reviewers.

KEY RESULTS

36 residents participated, 19 randomized to standard template, 17 to new. New template generated shorter notes (103 vs 285 lines, p < 0.001) that took the same time to complete (19.8 vs 21.6 min, p = 0.654). Using a 5-point Likert scale, residents considered new notes to have increased visual appeal (4 vs 3, p = 0.05) and less redundancy and clutter (4 vs 3, p = 0.006). Overall template satisfaction was not statistically different. Faculty reviewers rated the standard note more up-to-date (4.3 vs 2.7, p = 0.001), accurate (3.9 vs 2.6, p = 0.003), and useful (4 vs 2.8, p = 0.002), but less organized (3.3 vs 4.5, p < 0.001). Total quality was not statistically different.

CONCLUSIONS

Residents rated the new note template more visually appealing, shorter, and less cluttered. Faculty reviewers rated both note types equivalent in the overall quality but rated new notes inferior in terms of accuracy and usefulness though better organized. This study demonstrates a novel method of a simulated clinical encounter to evaluate note templates before the introduction into practice.

TRIAL REGISTRATION

ClinicalTrials.gov ID: NCT04333238.

Time-motion examination of electronic health record utilization and clinician workflows indicate frequent task switching and documentation burden

Clinical documentation burden has been broadly acknowledged, yet few interprofessional measures of burden exist. Using interprofessional time-motion study (TMS) data, we evaluated clinical workflows with a focus on electronic health record (EHR) utilization and fragmentation among 47 clinicians: 34 advanced practice providers (APPs) and 13 registered nurses (RNs) from: an acute care unit (n=15 observations [obs]), intensive care unit (nobs=14), ambulatory clinic (nobs=3), and emergency department (nobs=15). We examined workflow fragmentation, task-switch type, and task involvement. In our study, clinicians on average exhibited 1.4±0.6 switches per minute in their workflow. Eighty-four (19.6%) of the 429 task-switch types presented in the data accounted for 80.1% of all switches. Among those, data viewing- and data entry-related tasks were involved in 48.2% of all switches, indicating documentation burden may play a critical role in workflow disruptions. Therefore, interruption rate evaluated through task switches may serve as a proxy for measuring burden.

Human-Computer Interaction, Ethics, and Biomedical Informatics

Objectives : To provide an overview of recent work at the intersection of Biomedical Informatics, Human-Computer Interaction, and Ethics.

Methods : Search terms for Human-Computer Interaction, Biomedical Informatics, and Ethics were used to identify relevant papers published between 2017 and 2019.Relevant papers were identified through multiple methods, including database searches, manual reviews of citations, recent publications, and special collections, as well as through peer recommendations. Identified articles were reviewed and organized into broad themes.

Results : We identified relevant papers at the intersection of Biomedical Informatics, Human-Computer Interactions, and Ethics in over a dozen journals. The content of these papers was organized into three broad themes: ethical issues associated with systems in use, systems design, and responsible conduct of research.

Conclusions : The results of this overview demonstrate an active interest in exploring the ethical implications of Human-Computer Interaction concerns in Biomedical Informatics. Papers emphasizing ethical concerns associated with patient-facing tools, mobile devices, social media, privacy, inclusivity, and e-consent reflect the growing prominence of these topics in biomedical informatics research. New questions in these areas will likely continue to arise with the growth of precision medicine and citizen science.

Assessment of Electronic Health Record Search Patterns and Practices by Practitioners in a Large Integrated Health Care System

IMPORTANCE

The electronic health record (EHR) is a source of practitioner dissatisfaction in part because of challenges with information retrieval. To improve data accessibility, a better understanding of practitioners' information needs within individual patient records is needed.

OBJECTIVE

To assess EHR users' searches using data from a large integrated health care system.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cross-sectional analysis used EHR search data from Kaiser Permanente Northern California, an integrated health care delivery system with more than 4.4 million members. Users' EHR search activity data were obtained from April 1, 2018, to May 15, 2019.

MAIN OUTCOMES AND MEASURES

Search term frequency was grouped by user and practitioner types. Network analyses were performed of co-occurring search terms within a single search episode, and centrality measures for search terms (degree and betweenness centrality) were calculated.

RESULTS

A total of 12 313 047 search activities (including 4 328 330 searches and 7 984 717 result views) conducted by 34 735 unique users within 977 160 unique patient EHRs were identified. In aggregate, users searched for 208 374 unique search terms and conducted a median of 4 searches (interquartile range, 1-28 searches). Of all 97 367 active EHR users, 34 735 (35.7%) conducted at least 1 search. However, of all 12 968 active EHR physician users, 9801 (75.6%) conducted at least 1 search, and of all 1908 active pharmacist users, 1402 (73.5%) conducted at least 1 search. The top 3 most commonly searched terms were statin (75 017 searches [1.7%]), colonoscopy (73 545 [1.7%]), and pft (54 990 [1.3%]). However, wide variation in top searches were noted across practitioner groups. Terms searched most often with another term in a single linked search episode included statin, lisinopril, colonoscopy, gabapentin, and aspirin.

CONCLUSIONS AND RELEVANCE

Although physicians and pharmacists were the most active users of EHR searches, search volume and frequently searched terms varied considerably by and within user role. Further customization of the EHR interface may help leverage users' search content and patterns to improve targeted information retrieval.