scholarly journals Efficiency of Emergency Physicians: Insights from an Observational Study using EHR Log Files

2018 ◽  
Vol 09 (01) ◽  
pp. 099-104 ◽  
Author(s):  
Thomas Kannampallil ◽  
Courtney Denton ◽  
Jason Shapiro ◽  
Vimla Patel
Keyword(s):  
Performance Metrics ◽  
Clinical Care ◽  
Emergency Physicians ◽  
Federal Mandates ◽  
Health Records ◽  
Physician Review ◽  
Log Files ◽  
Positive Correlations ◽  
Attending Physicians ◽  
Disposition Time

Objective With federal mandates and incentives since the turn of this decade, electronic health records (EHR) have been widely adopted and used for clinical care. Over the last several years, we have seen both positive and negative perspectives on its use. Using an analysis of log files of EHR use, we investigated the nature of EHR use and their effect on an emergency department's (ED) throughput and efficiency. Methods EHR logs of time spent by attending physicians on EHR-based activities over a 6-week period (n = 2,304 patients) were collected. For each patient encounter, physician activities in the EHR were categorized into four activities: documentation, review, orders, and navigation. Four ED-based performance metrics were also captured: door-to-provider time, door-to-doctor time, door-to-disposition time, and length of stay (LOS). Association between the four EHR-based activities and corresponding ED performance metrics were evaluated. Results We found positive correlations between physician review of patient charts, and door-to-disposition time (r = 0.43, p < 0.05), and with LOS (r = 0.48, p < 0.05). There were no statistically significant associations between any of the other performance metrics and EHR activities. Conclusion The results highlight that longer time spent on reviewing information on the EHR is potentially associated with decreased ED throughput efficiency. Balancing these competing goals is often a challenge of physicians, and its implications for patient safety is discussed.

scholarly journals Determinants and extent of weight recording in UK primary care: an analysis of 5 million adults’ electronic health records from 2000 to 2017

BMC Medicine ◽  
2019 ◽  
Vol 17 (1) ◽  
Author(s):  
B. D. Nicholson ◽  
P. Aveyard ◽  
C. R. Bankhead ◽  
W. Hamilton ◽  
F. D. R. Hobbs ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Negative Binomial ◽  
Cox Regression ◽  
Clinical Care ◽  
Negative Binomial Regression ◽  
Routine Activity ◽  
Health Records ◽  
Clinical Events ◽  
Electronic Health

Abstract Background Excess weight and unexpected weight loss are associated with multiple disease states and increased morbidity and mortality, but weight measurement is not routine in many primary care settings. The aim of this study was to characterise who has had their weight recorded in UK primary care, how frequently, by whom and in relation to which clinical events, symptoms and diagnoses. Methods A longitudinal analysis of UK primary care electronic health records (EHR) data from 2000 to 2017. Descriptive statistics were used to summarise weight recording in terms of patient sociodemographic characteristics, health professional encounters, clinical events, symptoms and diagnoses. Negative binomial regression was used to model the likelihood of having a weight record each year, and Cox regression to the likelihood of repeated weight recording. Results A total of 14,049,871 weight records were identified in the EHR of 4,918,746 patients during the study period, representing 26,998,591 person-years of observation. Around a third of patients had a weight record each year. Forty-nine percent of weight records were repeated within a year with an average time to a repeat weight record of 1.92 years. Weight records were most often taken by nursing staff (38–42%) and GPs (37–39%) as part of a routine clinical care, such as chronic disease reviews (16%), medication reviews (6–8%) and health checks (6–7%), or were associated with consultations for contraception (5–8%), respiratory disease (5%) and obesity (1%). Patient characteristics independently associated with an increased likelihood of weight recording were as follows: female sex, younger and older adults, non-drinkers, ex-smokers, low or high BMI, being more deprived, diagnosed with a greater number of comorbidities and consulting more frequently. The effect of policy-level incentives to record weight did not appear to be sustained after they were removed. Conclusion Weight recording is not a routine activity in UK primary care. It is recorded for around a third of patients each year and is repeated on average every 2 years for these patients. It is more common in females with higher BMI and in those with comorbidity. Incentive payments and their removal appear to be associated with increases and decreases in weight recording.

scholarly journals Clinical Course of Nonfunctional Pituitary Microadenoma in Children: A Single-Center Experience

2019 ◽  
Vol 104 (12) ◽  
pp. 5906-5912 ◽  
Author(s):  
Vidhu V Thaker ◽  
Adrianne E Lage ◽  
Garima Kumari ◽  
V Michelle Silvera ◽  
Laurie E Cohen
Keyword(s):  
Clinical Course ◽  
Clinical Care ◽  
Tertiary Care ◽  
Drug Induced ◽  
Health Records ◽  
Clinical Data Warehouse ◽  
Pituitary Microadenoma ◽  
Single Center Experience

Abstract Context Pituitary lesions consistent with microadenomas are increasingly discovered by MRI. Sparse data are available on the long-term clinical and imaging course of such lesions in children. Objective The aim of this study was to define the clinical and imaging course of pituitary lesions representing or possibly representing nonfunctioning microadenomas in children to guide clinical management. Design Retrospective observational study. Methods The clinical data warehouse at a tertiary care academic children’s hospital was queried with the terms “pituitary” AND “microadenoma” and “pituitary” AND “incidentaloma.” The electronic health records of the identified subjects were reviewed to extract data on the clinical and imaging course. Results A total of 78 children had nonfunctioning pituitary lesions incidentally discovered during clinical care, of which 44 (56%) were reported as presumed or possible microadenomas. In the children with microadenoma (median age 15 years, interquartile range 2), a majority (70%) underwent imaging for nonendocrine symptoms, the most common being headache (n = 16, 36%). No significant increase in the size of the microadenoma or cysts or worsening of pituitary function was seen over the average clinical follow-up of 4.5 ± 2.6 years. Four cases of drug-induced hyperprolactinemia resolved with discontinuation of the offending medication. Conclusions Asymptomatic pituitary lesions representing cysts, microadenomas, or possible microadenomas follow a benign course in children. In the absence of new endocrine or visual symptoms, repeat MRI may not be needed, and if performed, should be done in no less than a year. When possible, it is prudent to discontinue hyperprolactinemia-inducing medications before imaging.

Application of process mining to assess the data quality of routinely collected time-based performance data sourced from electronic health records by validating process conformance

2016 ◽  
Vol 22 (4) ◽  
pp. 1017-1029 ◽  
Author(s):  
Lua Perimal-Lewis ◽  
David Teubner ◽  
Paul Hakendorf ◽  
Chris Horwood
Keyword(s):  
Electronic Health Records ◽  
Data Quality ◽  
Performance Metrics ◽  
Process Mining ◽  
Hospital Performance ◽  
Process Models ◽  
Patient Journey ◽  
Health Records ◽  
Electronic Health

Effective and accurate use of routinely collected health data to produce Key Performance Indicator reporting is dependent on the underlying data quality. In this research, Process Mining methodology and tools were leveraged to assess the data quality of time-based Emergency Department data sourced from electronic health records. This research was done working closely with the domain experts to validate the process models. The hospital patient journey model was used to assess flow abnormalities which resulted from incorrect timestamp data used in time-based performance metrics. The research demonstrated process mining as a feasible methodology to assess data quality of time-based hospital performance metrics. The insight gained from this research enabled appropriate corrective actions to be put in place to address the data quality issues.

scholarly journals Recommended Scoring Approach for the Pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events

2021 ◽  
Author(s):  
Pamela Hinds ◽  
Laura Pinheiro ◽  
Molly McFatrich ◽  
Mia Waldron ◽  
Justin Baker ◽  
...  
Keyword(s):  
Adverse Events ◽  
Pediatric Patient ◽  
Patient Reported Outcomes ◽  
Clinical Care ◽  
Reference Population ◽  
Item Score ◽  
Information Display ◽  
Patient Reported ◽  
The Common ◽  
Positive Correlations

Background Collecting symptom, function and adverse event (AE) data directly from children and adolescents undergoing cancer care is more comprehensive and accurate than relying solely on their caregivers or clinicians for their interpretations. We developed the Pediatric Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (Ped-PRO-CTCAE) measurement system with input from children, parents, and clinicians. Here we report how we determined the recommended Ped-PRO-CTCAE item scoring approach. Methods Scoring approaches compared were 1) at the AE attribute (frequency, severity, interference) using ordinal and dichotomous measures, 2) a weighted composite AE item score by AE attribute (0.5 - frequency; 1.0 - severity; 1.5 - interference), and 3) overall number of AEs endorsed. Associations of each AE attribute, AE item score and overall AE score with the PROMIS® Pediatric measures of anxiety, depressive symptoms, and fatigue were examined. The ability of the overall Ped-Pro-CTCAE AE score to identify patients with PROMIS symptom T-scores worse than reference population scores was assessed. Clinician preference for score information display was elicited through interviews. Results The diverse scoring approaches yielded similar outcomes, including positive correlations of the Ped-PRO-CTCAE attributes, AE item score, and the overall AEs score with the PROMIS Pediatric measures. Clinicians preferred the most granular display of scoring information (actual score reported by the child and corresponding descriptive term). Conclusions Although three scoring approaches yielded similar results, we recommend the AE attribute level of one score per Ped-Pro-CTCAE AE attribute for its simplicity of use in clinical care and research.

scholarly journals Baseline Demographics and Clinical Characteristics Among 3471 US Patients Hospitalized With COVID-19 and Pulmonary Involvement

2020 ◽  
Author(s):  
Jennie H Best ◽  
Shalini V Mohan ◽  
Amanda M Kong ◽  
Krish Patel ◽  
John M Pagel ◽  
...  
Keyword(s):  
African American ◽  
Clinical Characteristics ◽  
Clinical Care ◽  
Pulmonary Involvement ◽  
Chronic Obstructive ◽  
The South ◽  
Health Records ◽  
Obstructive Pulmonary Disease ◽  
The Mean ◽  
Baseline Characteristics

Introduction: Coronavirus disease 2019 (COVID-19) can present as a range of symptoms, from mild to critical; lower pulmonary involvement, including pneumonia, is often associated with severe and critical cases. Understanding the baseline characteristics of patients hospitalized with COVID-19 illness is essential for effectively targeting clinical care and allocating resources. This study aimed to describe baseline demographics and clinical characteristics of US patients hospitalized with COVID-19 and pulmonary involvement.Methods: US patients with COVID-19 and pulmonary involvement during an inpatient admission from December 1, 2019, to May 20, 2020, were identified using the IBM Explorys® electronic health records database. Baseline (up to 12 months prior to first COVID-19 hospitalization) demographics and clinical characteristics, and preadmission (14 days to 1 day prior to admission) pulmonary diagnoses were assessed. Patients were stratified by sex, age, race, and geographic region.Results: Overall, 3471 US patients hospitalized with COVID-19 and pulmonary involvement were included. The mean (SD) age was 63.5 (16.3) years; 51.2% of patients were female, 55.0% African American, 81.6% from the South, and 16.8% from the Midwest. The most common comorbidities included hypertension (27.7%), diabetes (17.3%), hyperlipidemia (16.3%), and obesity (9.7%). Cough (27.3%) and dyspnea (15.2%) were the most common preadmission pulmonary symptoms. African American patients were younger (mean [SD], 62.5 [15.4] vs 67.8 [6.2]) with higher mean (SD) body mass index (33.66 [9.46] vs 30.42 [7.86]) and prevalence of diabetes (19.8% vs 16.7%) and lower prevalence of chronic obstructive pulmonary disease (5.6% vs 8.2%) and smoking/tobacco use (28.1% vs 37.2%) than White patients.Conclusions: Among US patients primarily from the South and Midwest hospitalized with COVID-19 and pulmonary involvement, the most common comorbidities were hypertension, diabetes, hyperlipidemia, and obesity. Differences observed between African American and White patients should be considered in context of the complex factors underlying racial disparities in COVID-19.

scholarly journals The Digitization of Patient Care: A Review of the Effects of Electronic Health Records on Health Care Quality and Utilization

2019 ◽  
Vol 40 (1) ◽  
pp. 487-500 ◽  
Author(s):  
Hilal Atasoy ◽  
Brad N. Greenwood ◽  
Jeffrey Scott McCullough
Keyword(s):  
Electronic Health Records ◽  
Health Informatics ◽  
Health Care Quality ◽  
Clinical Care ◽  
Academic Research ◽  
Care Quality ◽  
Health Records ◽  
Policy Practice ◽  
Electronic Health ◽  
Cost Implications

Electronic health records (EHRs) adoption has become nearly universal during the past decade. Academic research into the effects of EHRs has examined factors influencing adoption, clinical care benefits, financial and cost implications, and more. We provide an interdisciplinary overview and synthesis of this literature, drawing on work in public and population health, informatics, medicine, management information systems, and economics. We then chart paths forward for policy, practice, and research.

Linking electronic health records and in-depth interviews to inform efforts to integrate social determinants of health into health care delivery: Protocol for a qualitative research study (Preprint)

2022 ◽  
Author(s):  
Annemarie Hirsch ◽  
T. Elizabeth Durden ◽  
Jennifer Silva
Keyword(s):  
Electronic Health Records ◽  
Health System ◽  
Social Determinants ◽  
Clinical Care ◽  
Unintended Consequences ◽  
Social Needs ◽  
Free Text ◽  
Latina Women ◽  
Health Records ◽  
Depth Interviews

BACKGROUND Health systems are attempting to capture social determinants of health (SDoH) in electronic health records (EHR) and use these data to adjust care plans. To date, however, methods for identifying social needs, which are the SDoH prioritized by patients, have been underexplored, and there is little guidance as to how clinicians should act on SDoH data when caring for patients. Moreover, the unintended consequences of collecting and responding to SDoH are poorly understood. OBJECTIVE The objective of this study is to use two data sources, EHR data and patient interviews, to describe divergences between the EHR and patient experiences that could help identify gaps in documentation of SDoH in the EHR; highlight potential missed opportunities for addressing social needs; and identify unintended consequences of efforts to integrate SDoH into clinical care. METHODS We are conducting a qualitative study that merges discrete and free-text data from EHRs with in-depth interviews with women residing in rural, socio-economically deprived communities in the Mid-Atlantic region of the United States. Participants had to confirm that they had at least one visit with the large health system that serves the region. Interviews with the women included questions regarding health, interaction with the health system, and social needs. Next, with consent, for each participant we extracted discrete data (e.g., diagnoses; medication orders) and free-text clinician notes from this health system’s EHRs between 1996 and the year of the interview. We used a standardized protocol to create an EHR narrative, a free-text summary of the EHR data. We used NVivo to identify themes in the interviews and the EHR narratives. RESULTS To date, we have interviewed 88 women, including 51 White women, 19 Black women, 14 Latina women, 2 mixed Black and Latina women, and 2 Asian Pacific women. We have completed the EHR narratives on 66 women. The women range in age from 18 to 90. We found corresponding EHR data on all but 4 of the interview participants. Participants had contact with a wide range of clinical departments (e.g., psychiatry, neurology, infectious disease) and received care in various clinical settings (e.g., primary care clinics, emergency departments, inpatient hospitalizations). A preliminary review of the EHR narratives revealed that the clinician notes were a source of data on a range of SDoH, but did not always reflect the social needs that participants described in the interviews. CONCLUSIONS This study will provide unique insight into the demands and consequences of integrating SDoH into clinical care. This work comes at a pivotal point in time, as health systems, payors, and policy makers accelerate attempts to deliver care within the context of social needs.

A consensus-based process to define standard national data elements for a canadian emergency department information system

CJEM ◽  
2001 ◽  
Vol 3 (04) ◽  
pp. 277-283 ◽  
Author(s):  
◽  
Grant Innes ◽  
Michael Murray ◽  
Eric Grafstein
Keyword(s):  
Emergency Department ◽  
Information System ◽  
Quality Improvement ◽  
Working Group ◽  
Clinical Care ◽  
Care Quality ◽  
Emergency Physicians ◽  
Data Set ◽  
System Data ◽  
Data Elements

Abstract Canadian hospitals gather few emergency department (ED) data, and most cannot track their case mix, care processes, utilization or outcomes. A standard national ED data set would enhance clinical care, quality improvement and research at a local, regional and national level. The Canadian Association of Emergency Physicians, the National Emergency Nurses Affiliation and l’Association des médecins d’urgence du Québec established a joint working group whose objective was to develop a standard national ED data set that meets the information needs of Canadian EDs. The working group reviewed data elements derived from Australia’s Victorian Emergency Minimum Dataset, the US Data Elements for Emergency Department Systems document, the Ontario Hospital Emergency Department Working Group data set and the Canadian Institute for Health Information’s National Ambulatory Care Reporting System data set. By consensus, the group defined each element as mandatory, preferred or optional, and modified data definitions to increase their relevance to the ED context. The working group identified 69 mandatory elements, 5 preferred elements and 29 optional elements representing demographic, process, clinical and utilization measures. The Canadian Emergency Department Information System data set is a feasible, relevant ED data set developed by emergency physicians and nurses and tailored to the needs of Canadian EDs. If widely adopted, it represents an important step toward a national ED information system that will enable regional, provincial and national comparisons and enhance clinical care, quality improvement and research applications in both rural and urban settings.

The effect of electronic health records on the use of clinical care guidelines for patients with medically complex conditions

2011 ◽  
Vol 142 (10) ◽  
pp. 1133-1142 ◽  
Author(s):  
James Fricton ◽  
D. Brad Rindal ◽  
William Rush ◽  
Thomas Flottemesch ◽  
Gabriela Vazquez ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Care ◽  
Health Records ◽  
Care Guidelines ◽  
Electronic Health

scholarly journals Awareness of the Care Team in Electronic Health Records

2011 ◽  
Vol 02 (04) ◽  
pp. 395-405 ◽  
Author(s):  
L.G. Wilcox ◽  
S. Collins ◽  
S. Feiner ◽  
O. Mamykina ◽  
D.M. Stein ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Medical Center ◽  
Academic Medical Center ◽  
Physician Assistants ◽  
Care Team ◽  
Accurate Information ◽  
Care Providers ◽  
Health Records ◽  
Electronic Health ◽  
Attending Physicians

SummaryObjective: To support collaboration and clinician-targeted decision support, electronic health records (EHRs) must contain accurate information about patients’ care providers. The objective of this study was to evaluate two approaches for care provider identification employed within a commercial EHR at a large academic medical center.Methods: We performed a retrospective review of EHR data for 121 patients in two cardiology wards during a four-week period. System audit logs of chart accesses were analyzed to identify the clinicians who were likely participating in the patients’ hospital care. The audit log data were compared with two functions in the EHR for documenting care team membership: 1) a vendor-supplied module called “Care Providers”, and 2) a custom “Designate Provider” order that was created primarily to improve accuracy of the attending physician of record documentation.Results: For patients with a 3–5 day hospital stay, an average of 30.8 clinicians accessed the electronic chart, including 10.2 nurses, 1.4 attending physicians, 2.3 residents, and 5.4 physician assistants. The Care Providers module identified 2.7 clinicians/patient (1.8 attending physicians and 0.9 nurses). The Designate Provider order identified 2.1 clinicians/patient (1.1 attending physicians, 0.2 resident physicians, and 0.8 physician assistants). Information about other members of patients’ care teams (social workers, dietitians, pharmacists, etc.) was absent.Conclusions: The two methods for specifying care team information failed to identify numerous individuals involved in patients’ care, suggesting that commercial EHRs may not provide adequate tools for care team designation. Improvements to EHR tools could foster greater collaboration among care teams and reduce communication-related risks to patient safety.

Sign in / Sign up

Export Citation Format

Share Document