Applied Clinical Informatics最新文献

Background:  Multitasking, defined as performing two or more interventions simultaneously, increases the cognitive burden of clinicians. This may, in turn, lead to higher risk of medication and procedural errors. Time motion study (TMS) data for nurses in nursing homes revealed an extensive amount of multitasking while managing medications. Further investigation of multitasked nursing interventions will provide a foundation for optimizing medication management workflows.

Objectives:  Using a continuous observational TMS method, this study aimed to describe pairs of multitasked nursing interventions associated with medication management interventions, including preparing and administering medications, assessing medication effects, instructing on medications, and documenting medication administration.

Methods:  An external nurse observer used 57 predefined Omaha System nursing interventions embedded within TimeCaT (version 3.9), TMS data recording software to collect observation data in a single nursing home. A total of 120 hours of time-stamped observation data from nine nurses were downloaded from TimeCaT and analyzed using descriptive and inferential statistics.

Results:  The majority (74%) of medication management interventions were multitasked, resulting in 2,003 pairs of multitasked interventions. Of the 57 Omaha System nursing interventions, 35 were involved in these multitasking pairs. When nurses multitasked, the average duration of medication preparation was longer (non-multitasked: 81 seconds; multitasked: 162 seconds, p < 0.05), while the average duration of medication administration record documentation was shorter (non-multitasked: 93 seconds; multitasked: 66 seconds, p < 0.05).

Conclusion:  The findings reveal the complexity of medication management in nursing homes with numerous and diverse multitasking pairs. Findings provide a platform for in-depth study of medication management multitasking in the clinical context, and inform future efforts to create clinical and informatics solutions to optimize medication management workflow. This method may be also applied to examine medication management and multitasking in other clinical settings.

Background:  Hospital settings provide a unique opportunity to screen for intimate partner violence (IPV) and sexual assault (SA) yet often lack health information technology (IT) solutions for generating reliable and valid medicolegal documentation via forensic reports.

Objectives:  The objective of the project was to evaluate a pilot, technology "tool" for documenting cases of IPV and SA that could support forensic nurse examiners and related stakeholders in generating high-quality documentation and coordinating victim support services.

Methods:  The tool was a digital health intervention implemented for use among forensic nurse examiners, law enforcement, victim support organizations, and more within four counties of California. We conducted a mixed-methods pilot study that captured data around the adoption, use, and impact of having access to the newly implemented tool.

Results:  The tool successfully went live in all four pilot counties at different time points with different proportions of use by county and form type: exams, referrals, addenda, risk assessments, and other. Participants were motivated to use the tool out of a perceived need for data handling functionalities that went beyond traditional manual (paper) means. Key functionalities included body mapping, data quality controls within validated forms, attaching addenda to already existing case reports, and the means to distribute data to external recipients. Further study and development are needed on functions to incorporate into body maps and forms and understanding the information needs of law enforcement and victim support organizations.

Conclusion:  Our evaluation demonstrated the feasibility and acceptability of a health IT tool to support forensic nurse documentation of IPV and SA and direct information to multiple legal and support-related stakeholders. Areas of future development include integrating IPV- and SA-related data standards for digitized forms, enhancements to the body mapping feature, and understanding the needs of those who receive digital data from forensic nurse examiners within the tool.

Background:  The electronic health record (EHR) has been associated with provider burnout, exacerbated by increasing In-Basket burden.

Objectives:  We sought to study the impact of implementing a team-based approach to In-Basket management on a series of primary care ambulatory sites.

Methods:  We performed a workflow analysis of the transition to the Advanced In-Basket Management (AIM) nurse team triage for six family medicine clinic locations in a large health system. We abstracted and analyzed associated provider workflow metrics from our EHR. We conducted a postintervention provider survey on satisfaction with the AIM project and provider burnout.

Results:  The AIM project was implemented in six family medicine clinics after provider townhalls and workgroup development. A nurse team curriculum was created using the principles of "maturing the message" before sending it to a provider and "only handle it once" to improve response efficiency. Provider workload metrics abstracted from the EHR demonstrated 12.2 fewer In-Basket messages per provider per day (p < 0.05), 6.3 fewer minutes per provider per day worked outside scheduled hours (p < 0.05), 3.5 fewer minutes spent in the In-Basket per provider per day (p < 0.05), but 13.7 more seconds spent per completed message per provider (p = 0.017), likely attributable to increased message complexity. Sixty-four percent of providers reported no burnout symptoms in a postintervention survey, 56% agreed that the AIM project reduced their burnout, and approximately 70% of providers agreed that the AIM project was acceptable and appropriate for their clinic.

Conclusion:  The AIM project demonstrates team-based nurse In-Basket triage is possible to implement across multiple primary care sites, is an acceptable intervention for providers, can reduce provider workload burden and self-reported provider burnout.

Background:  Leaders in Informatics, Quality, and Systems (LInQS) is a non-ACGME (Accreditation Council for Graduate Medical Education)-accredited 2-year training program developed to enhance training in the fields of health care delivery, quality improvement (QI), clinical informatics, and leadership.

Methods:  This single-institution 2-year longitudinal training program grounded in QI and informed by leadership and clinical informatics includes didactics, coaching, and mentorship, all centered around individualized QI projects. The program has been available to sub-specialty fellows, advanced practice providers, and physicians.

Results:  From 2019 to 2023, 32 fellows have been accepted into the program with 13 graduates and 16 currently enrolled. Fellows have been predominately female, physicians, and from multiple specialties but predominantly hospital medicine. Fellows' evaluations of the fellowship are highly positive, rating the didactics and mentorship aspects of the curriculum most favorably. Most fellows' projects utilized informatics solutions including clinical decision support tools to increase quality of care, improve patient outcomes, and reduce costs of care resulting in manuscript publications, national presentations, and a national specialty society award. Since matriculation, 50% of fellows received certification as Epic Physician Builders and 34% received leadership positions in clinical informatics, quality, and education.

Conclusion:  Our experience supports the need to provide health care providers more expansive training in the areas of QI, clinical informatics, and leadership for improving health care delivery. Additional in-depth knowledge and experience in these fields may produce and benefit leaders in these fields.

Background As teleconsultations continue to rise in popularity due to their convenience and accessibility, it's crucial to identify and address the challenges they present in order to improve the patient experience, enhance outcomes, and ensure the quality of care. To identify communication challenges that clinicians and patients experience during teleconsultation, a scoping review was conducted. Methods Studies were obtained from four databases (Ovid [MEDLINE], Ovid [Embase], CINAHL and Scopus). Gray literatures were not included. Studies focused on communication challenges between clinicians and their patients during teleconsultation in the context of COVID-19 and published from January 2000 to December 2022 were collected. Screening process was conducted by 2 independent reviewers. Data extraction was performed using a standardized form to capture study characteristics and communication challenges. Extracted data were analyzed to identify the communication challenges during teleconsultation, adherent to PRISMA-ScR. Results A total of 893 studies were collected from 4 databases and 26 studies were selected based on inclusion/exclusion criteria. Of these 26 eligible studies, 12 (46%) were from the US, 3 studies (12%) were from Australia, 2 (8%) were from the UK and Canada. These studies included 12 (46%) qualitative studies, 6 (23%) quantitative studies, 6 (23%) review articles, and 2 (8%) case reports. Eight factors contributing to communication challenges between clinicians and patients during teleconsultations were identified: technical issues, difficulties in developing rapport, lack of non-verbal communication, lack of physical examination, language barrier, spatial issues, clinician preparation, and difficulties in assessing patients' health literacy. Conclusion Eight factors were identified contributing to communication challenges during teleconsultation in the context of COVID-19. These findings highlight the need for addressing communication challenges to ensure effective teleconsultations. With the rise of teleconsultation in routine healthcare delivery, further research is warranted to confirm these findings, and to explore ways to overcome communication challenges during teleconsultation.

Background Ensuring the security of nursing information holds substantial importance. The awareness of information security among nurses in China is generally inadequate, and there is a lack of standardized evaluation tools for nurse information security in nursing practice. The nursing sector necessitates the establishment of a robust culture surrounding information security. Objective The aim of this study was to construct a self-reporting instrument for evaluating nursing information security. Methods The research team utilized literature analysis and group discussions to draft the item pool. After two rounds of Delphi consultation by 15 experts and pilot testing, the initial questionnaire was formed. Item analysis was carried out on the questionnaire, and the validity and reliability of the instrument were statistically tested by computing the Keiser-Meier-Olkin (KMO) and Bartlett tests, an exploratory factor analysis, a confirmatory factor analysis, convergent and discriminative validity, descriptive statistics, Cronbach's α and test-retest reliability. Results A total of 501 nurses participated in the study, supplemented by the inclusion of five experts who were invited to contribute to the assessment of content validity. Four factors were formed using exploratory factor analysis (n=250), and the cumulative variance contribution rate was found to be 60.10%. The confirmatory factor analysis (n=251) showed the model fit was good. The overall Cronbach's α coefficient of the questionnaire was 0.948, and the test-retest reliability was 0.837. Conclusion Finally, the NIS-Q with 38 items and three dimensions of knowledge, attitude and practice were formed. A promising assessment instrument for gauging the degree of nursing information security was introduced. Further, a foundational platform was established for implementing specific enhancement strategies aimed at advancing nursing information security.

Objective: Duplicate patient records can increase cost and medical errors. We assessed the association between demographic factors, comorbidities, healthcare usage and duplicate electronic health records.

Materials and methods: We analyzed the association between duplicate patient records and multiple demographic variables (race, Hispanic ethnicity, sex and age) as well as Charlson comorbidity index (CCI), number of diagnoses, and number of healthcare encounters. The study population included 3,018,413 patients seen at a large urban academic medical center with at least one recorded diagnosis. Duplication of patient medical records was determined by using a previously validated enterprise Master Person Index.

Results: Unknown or missing demographic data, Black race when compared to White Race (OR 1.35, p < 0.001), Hispanic compared to non-Hispanic ethnicity (OR 1.48, p < 0.001), older age (OR 1.01, p < 0.001), and "Other" sex compared to female sex (OR 4.71, p < 0.001) were associated with higher odds of having a duplicate record. Comorbidities (CCI, OR 1.10, p < 0.001) and more encounters with the health care system (OR 1.01, p < 0.001) were also associated with higher odds of having a duplicate record. In contrast, male sex compared to female sex was associated with lower odds of having a duplicate record (OR 0.88, p < 0.001).

Discussion: The odds of duplications in medical records were higher in Black, Hispanic, older, non-male patients with more healthcare encounters, more comorbidities, and unknown demographic data. Understanding the epidemiology of duplicate records can help guide prevention and mitigation efforts for high-risk populations.

Conclusion: Duplicate records can contribute to disparities in health care outcomes in minority populations.

Objectives: This research study aims to advance the staging of Parkinson's disease (PD) by incorporating machine learning to assess and include a broader multi-functional spectrum of neurocognitive symptoms in the staging schemes beyond motor-centric assessments. Specifically, we provide a novel framework to modernize and personalize PD staging more objectively by proposing a hybrid feature scoring approach.

Methods: We recruited thirty-seven individuals diagnosed with PD, each of whom completed a series of tablet-based neurocognitive tests assessing motor, memory, speech, executive functions, and tasks ranging in complexity from single to multi-functional. Then, the collected data was used to develop a hybrid feature scoring system to calculate a weighted vector for each function. We evaluated current PD staging schemes and developed a new approach based on the features selected and extracted using Random Forest and Principal Component Analysis.

Results: Our findings indicate a substantial bias in current PD staging systems toward fine-motor skills, i.e., other neurological functions (memory, speech, executive function, etc.) do not map into current PD stages as well as fine-motor skills do. The results demonstrate that a more accurate and personalized assessment of PD severity could be achieved by including a more exhaustive range of neurocognitive functions in the staging systems either by involving multiple functions in a unified staging score or by designing a function-specific staging system.

Conclusions: The proposed hybrid feature score approach provides a comprehensive understanding of PD by highlighting the need for a staging system that covers various neurocognitive functions. This approach could potentially lead to more effective, objective, and personalized treatment strategies. Further, this proposed methodology could be adapted to other neurodegenerative conditions such as Alzheimer's disease or ALS.

Objectives This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician.

Methods Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization either independently or with assistance. Demographic data, the hospital principal problem upon admission, and International Classification of Diseases 10th Revision (ICD-10) codes were retrieved from the electronic health record (EHR). Two physicians independently rated concordance between patient-reported diagnosis and clinician-entered principal problem as full, partial, or no. Discrepancies were resolved by consensus. Descriptive statistics were used to report demographics for concordant (full) and nonconcordant (partial or no) outcome groups. Multivariable logistic regressions of PDQ questions and a priori selected EHR data as independent variables were conducted to predict nonconcordance.

Results A total of 157 (77.7%) questionnaires were completed by 202 participants; 77 (49.0%), 46 (29.3%), and 34 (21.7%) were rated fully concordant, partially concordant, and not concordant, respectively. Cohen's kappa for agreement on preconsensus ratings by independent reviewers was 0.81 (0.74, 0.88). In multivariable analyses, patient-reported lack of confidence and undifferentiated symptoms (ICD-10 “R-code”) for the principal problem were significantly associated with nonconcordance (partial or no concordance ratings) after adjusting for other PDQ questions (3.43 [1.30, 10.39], p = 0.02) and in a model using selected variables (4.02 [1.80, 9.55], p < 0.01), respectively.

Conclusion About one-half of patient-reported diagnoses were concordant with the clinician-entered diagnosis on admission. An ICD-10 “R-code” entered as the principal problem and patient-reported lack of confidence may predict patient–clinician nonconcordance early during hospitalization via this approach.