Improving Documentation Timeliness: A "Brighter Future" for the Electronic Medical Record in Resident Clinics

Scoping review: Positive and negative impact of technology on clinicians

BACKGROUND

Unnecessary electronic health record (EHRs) documentation burden and usability issues have negatively impacted clinician well-being (e.g., burnout and moral distress).

PURPOSE

This scoping review was conducted by members from three expert panels of the American Academy of Nurses to generate consensus on the evidence of both positive and negative impact of EHRs on clinicians.

METHODS

The scoping review was conducted based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews guidelines.

RESULTS

The scoping review captured 1,886 publications screened against title and abstract 1,431 excluded, examined 448 in a full-text review, excluded 347 with 101 studies informing the final review.

DISCUSSION

Findings suggest few studies that have explored the positive impact of EHRs and more studies that have explored the clinician's satisfaction and work burden. Significant gaps were identified in associating distress to use of EHRs and minimal studies on EHRs' impact on nurses.

CONCLUSION

Examined the evidence of HIT's positive and negative impacts on clinician's practice, clinicians work environment, and if psychological impact differed among clinicians.

Perspectives of undergraduate and graduate medical trainees on documenting clinical notes: Implications for medical education and informatics

Ensuring the accuracy of unstructured clinical notes is critical for patient care, research, and quality improvement. Understanding how trainees learn to document these notes and the challenges they encounter are important steps to developing educational and informatics solutions.Authors conducted focus groups to gather the perspectives of 40 medical students (MS) and family and emergency medicine (EM) residents on recording clinical notes in the electronic medical record (EMR). Focus groups were audio recorded, transcribed, and thematically analyzed.Thematic analysis with a deductive approach revealed: a lack of formal education, a shift from information gathering to documenting clinical reasoning with seniority, and barriers to charting development, including variable preceptor expectations and EMR design constraints.Participating trainees report gaps in education around the documentation of notes in the EMR. Future work should explore opportunities to reduce gaps, including more formal education, the creation of specific competencies, and improvements to the EMR.

Completion of electronic nursing documentation of inpatient admission assessment: Insights from Australian metropolitan hospitals

INTRODUCTION

Electronic nursing documentation is an essential aspect of inpatient care and multidisciplinary communication. Analysing data in electronic medical record (eMR) systems can assist in understanding clinical workflows, improving care quality, and promoting efficiency in the healthcare system. This study aims to assess timeliness of completion of an electronic nursing admission assessment form and identify patient and facility factors associated with form completion in three metropolitan hospitals.

MATERIALS AND METHODS

Records of 37,512 adult inpatient admissions (November 2018-November 2019) were extracted from the hospitals' eMR system. A dichotomous variable descriptive of completion of the nursing assessment form (Yes/No) was created. Timeliness of form completion was calculated as the interval between date and time of admission and form completion. Univariate and multivariate multilevel logistic regression were used to identify factors associated with form completion.

RESULTS

An admission assessment form was completed for 78.4% (n = 29,421) of inpatient admissions. Of those, 78% (n = 22,953) were completed within the first 24 h of admission, 13.3% (n = 3,910) between 24 and 72 h from admission, and 8.7% (n = 2,558) beyond 72 h from admission. Patient length of hospital stay, admission time, and admitting unit's nursing hours per patient day were associated with form completion. Patient gender, age, and admitting unit type were not associated with form completion.

DISCUSSION

Form completion rate was high, though more emphasis needs to be placed on the importance of timely completion to allow for adequate patient care planning. Staff education, qualitative understanding of delayed form completion, and streamlined guidelines on nursing admission and eMR use are recommended.

Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review

BACKGROUND

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OBJECTIVE

Electronic health records (EHRs) are linked with documentation burden resulting in clinician burnout. While clear classifications and validated measures of burnout exist, documentation burden remains ill-defined and inconsistently measured. We aim to conduct a scoping review focused on identifying approaches to documentation burden measurement and their characteristics.

MATERIALS AND METHODS

Based on Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Extension for Scoping Reviews (ScR) guidelines, we conducted a scoping review assessing MEDLINE, Embase, Web of Science, and CINAHL from inception to April 2020 for studies investigating documentation burden among physicians and nurses in ambulatory or inpatient settings. Two reviewers evaluated each potentially relevant study for inclusion/exclusion criteria.

RESULTS

Of the 3482 articles retrieved, 35 studies met inclusion criteria. We identified 15 measurement characteristics, including 7 effort constructs: EHR usage and workload, clinical documentation/review, EHR work after hours and remotely, administrative tasks, cognitively cumbersome work, fragmentation of workflow, and patient interaction. We uncovered 4 time constructs: average time, proportion of time, timeliness of completion, activity rate, and 11 units of analysis. Only 45.0% of studies assessed the impact of EHRs on clinicians and/or patients and 40.0% mentioned clinician burnout.

DISCUSSION

Standard and validated measures of documentation burden are lacking. While time and effort were the core concepts measured, there appears to be no consensus on the best approach nor degree of rigor to study documentation burden.

CONCLUSION

Further research is needed to reliably operationalize the concept of documentation burden, explore best practices for measurement, and standardize its use.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment

BACKGROUND

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU).

OBJECTIVE

To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS).

METHODS

The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors.

RESULTS

Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS.

CONCLUSIONS

Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors.