scholarly journals User Evaluation of the Swedish Patient Accessible Electronic Health Record: System Usability Scale (Preprint)

2020 ◽  
Author(s):  
Maria Hägglund ◽  
Isabella Scandurra
Keyword(s):  
Electronic Health Record ◽  
Ease Of Use ◽  
Survey Study ◽  
Health Record ◽  
Patient Portal ◽  
Data Set ◽  
System Usability Scale ◽  
System Usability ◽  
National Patient ◽  
Electronic Health

BACKGROUND Transparency is increasingly called for in health care, especially, when it comes to patients’ access to their electronic health records. In Sweden, the e-service Journalen is a national patient accessible electronic health record (PAEHR), accessible online via the national patient portal. User characteristics and perceived benefits of using a PAEHR influence behavioral intention for use and adoption, but poor usability that increases the effort expectancy can have a negative impact. It is, therefore, of interest to explore how users of the PAEHR Journalen perceive its usability and usefulness. OBJECTIVE The aim of this study was to explore how the users of the Swedish PAEHR experience the usability of the system and to identify differences in these experiences based on the level of transparency of the region. METHODS A survey study was conducted to elicit opinions and experiences of patients using Journalen. The data were collected from June to October 2016. The questionnaire included questions regarding the usability of the system from the System Usability Scale (SUS). The SUS analysis was the focus of this paper. Analysis was performed on different levels: nationally looking at the whole data set and breaking it down by focusing on 2 different regions to explore differences in experienced usability based on the level of transparency. RESULTS During the survey period, 423,141 users logged into Journalen, of which 2587 unique users completed the survey (response rate 0.61%). The total mean score for all respondents to the SUS items was 79.81 (SD 14.25), which corresponds to a system with good usability. To further explore whether the level of transparency in a region would affect the user’s experience of the usability of the system, we analyzed the 2 regions with the most respondents: Region Uppsala (the first to launch, with a high level of transparency), and Region Skåne (an early implementer, with a low level of transparency at the time of the survey). Of the participants who responded to at least 1 SUS statement, 520 stated that they had received care in Region Skåne, whereas 331 participants had received care in Region Uppsala. Uppsala’s mean SUS score was 80.71 (SD 13.41), compared with Skåne’s mean of 79.37 (SD 13.78). CONCLUSIONS The Swedish national PAEHR Journalen has a reasonably good usability (mean SUS score 79.81, SD 14.25); however, further research into more specific usability areas are needed to ensure usefulness and ease of use in the future. A somewhat higher SUS score for the region with high transparency compared with the region with low transparency could indicate a relationship between the perceived usability of a PAEHR and the level of transparency offered, but further research on the relationship between transparency and usability is required.

scholarly journals Development and evaluation of a novel user interface for reviewing clinical microbiology results

2018 ◽  
Vol 25 (8) ◽  
pp. 1064-1068 ◽  
Author(s):  
Adam Wright ◽  
Pamela M Neri ◽  
Skye Aaron ◽  
Thu-Trang T Hickman ◽  
Francine L Maloney ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Clinical Microbiology ◽  
Block Design ◽  
Health Record ◽  
Time On Task ◽  
Microbiology Laboratory ◽  
System Usability Scale ◽  
System Usability ◽  
Laboratory Results ◽  
Electronic Health

Abstract Background Microbiology laboratory results are complex and cumbersome to review. We sought to develop a new review tool to improve the ease and accuracy of microbiology results review. Methods We observed and informally interviewed clinicians to determine areas in which existing microbiology review tools were lacking. We developed a new tool that reorganizes microbiology results by time and organism. We conducted a scenario-based usability evaluation to compare the new tool to existing legacy tools, using a balanced block design. Results The average time-on-task decreased from 45.3 min for the legacy tools to 27.1 min for the new tool (P < .0001). Total errors decreased from 41 with the legacy tools to 19 with the new tool (P = .0068). The average Single Ease Question score was 5.65 (out of 7) for the new tool, compared to 3.78 for the legacy tools (P < .0001). The new tool scored 88 (“Excellent”) on the System Usability Scale. Conclusions The new tool substantially improved efficiency, accuracy, and usability. It was subsequently integrated into the electronic health record and rolled out system-wide. This project provides an example of how clinical and informatics teams can innovative alongside a commercial Electronic Health Record (EHR).

scholarly journals Electronic Health Record Acceptance by Physicians: A Single Hospital Experience in Daily Practice

2021 ◽  
Vol 1 (1) ◽  
pp. 6-17
Author(s):  
Andrija Pavlovic ◽  
Nina Rajovic ◽  
Jasmina Pavlovic Stojanovic ◽  
Debora Akinyombo ◽  
Milica Ugljesic ◽  
...  
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Electronic Health Record ◽  
Technology Acceptance ◽  
Daily Practice ◽  
Ease Of Use ◽  
Future Research ◽  
Health Record ◽  
Cross Sectional ◽  
Electronic Health

Introduction: Potential benefits of implementing an electronic health record (EHR) to increase the efficiency of health services and improve the quality of health care are often obstructed by the unwillingness of the users themselves to accept and use the available systems. Aim: The aim of this study was to identify factors that influence the acceptance of the use of an EHR by physicians in the daily practice of hospital health care. Material and Methods: The cross-sectional study was conducted among physicians in the General Hospital Pancevo, Serbia. An anonymous questionnaire, developed according to the technology acceptance model (TAM), was used for the assessment of EHR acceptance. The response rate was 91%. Internal consistency was assessed by Cronbach’s alpha coefficient. A logistic regression analysis was used to identify the factors influencing the acceptance of the use of EHR. Results: The study population included 156 physicians. The mean age was 46.4 ± 10.4 years, 58.8% participants were female. Half of the respondents (50.1%) supported the use of EHR in comparison to paper patient records. In multivariate logistic regression modeling of social and technical factors, ease of use, usefulness, and attitudes towards use of EHR as determinants of the EHR acceptance, the following predictors were identified: use of a computer outside of the office for reading daily newspapers (p = 0.005), EHR providing a greater amount of valuable information (p = 0.007), improvement in the productivity by EHR use (p < 0.001), and a statement that using EHR is a good idea (p = 0.014). Overall the percentage of correct classifications in the model was 83.9%. Conclusion: In this research, determinants of the EHR acceptance were assessed in accordance with the TAM, providing an overall good model fit. Future research should attempt to add other constructs to the TAM in order to fully identify all determinants of physician acceptance of EHR in the complex environment of different health systems.

scholarly journals Validation of a Novel Electronic Health Record Patient Portal Advance Care Planning Delivery System

2018 ◽  
Vol 20 (6) ◽  
pp. e208 ◽  
Author(s):  
Seuli Bose-Brill ◽  
Michelle Feeney ◽  
Laura Prater ◽  
Laura Miles ◽  
Angela Corbett ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Delivery System ◽  
Advance Care Planning ◽  
Health Record ◽  
Patient Portal ◽  
Care Planning ◽  
Advance Care ◽  
Electronic Health

scholarly journals Development of a Cancer Care Summary Through the Electronic Health Record

2016 ◽  
Vol 12 (2) ◽  
pp. e231-e240 ◽  
Author(s):  
Laurie L. Carr ◽  
Pearlanne Zelarney ◽  
Sarah Meadows ◽  
Jeffrey A. Kern ◽  
M. Bronwyn Long ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Cancer Care ◽  
Query Language ◽  
Primary Care Providers ◽  
Urgent Care ◽  
Health Record ◽  
Patient Portal ◽  
Care Providers ◽  
Improvement Project ◽  
Electronic Health

Introduction: Our objective was to improve communication concerning lung cancer patients by developing and distributing a Cancer Care Summary that would provide clinically useful information about the patient’s diagnosis and care to providers in diverse settings. Methods: We designed structured, electronic forms for the electronic health record (EHR), detailing tumor staging, classification, and treatment. To ensure completeness and accuracy of the information, we implemented a data quality cycle, composed of reports that are reviewed by oncology clinicians. The data from the EHR forms are extracted into a structured query language database system on a daily basis, from which the Summaries are derived. We conducted focus groups regarding the utility, format, and content of the Summary. Cancer Care Summaries are automatically generated 4 months after a patient’s date of diagnosis, then every 6 months for those receiving treatment, and on an as-needed basis for urgent care or hospital admission. Results: The product of our improvement project is the Cancer Care Summary. To date, 102 individual patient Summaries have been generated. These documents are automatically entered into the National Jewish Health (NJH) EHR, attached to correspondence to primary care providers, available to patients as electronic documents on the NJH patient portal, and faxed to emergency departments and admitting physicians on patient evaluation. Conclusion: We developed a sustainable tool to improve cancer care communication. The Cancer Care Summary integrates information from the EHR in a timely manner and distributes the information through multiple avenues.

scholarly journals Electronic Health Record Goes Personal World-wide

2009 ◽  
Vol 18 (01) ◽  
pp. 40-43 ◽  
Author(s):  
PS Lee ◽  
WS Jian ◽  
CH Kuo ◽  
YC Li
Keyword(s):  
Electronic Health Record ◽  
Content Standards ◽  
Health Record ◽  
Patient Portal ◽  
Consumer Empowerment ◽  
Privacy And Security ◽  
Healthcare Data ◽  
The World ◽  
Personal Use ◽  
Electronic Health

Summary Objective Increasing patient demand for convenient access to their own healthcare data has led to more personal use of the Electronic Health Record (EHR). With “consumer empowerment” being an important issue of EHR, we are seeing a more “patient-centric” approach of EHR from countries around the world. Researchers have reported on issues in EHR sharing including concerns on privacy and security, consumer empowerment, competition among providers, and content standards. This study attempts to analyze prior research and to synthesize comprehensive, empirically-based conceptual models of EHR for personal use. Methods We use “B2C(2B)” to represent this new behavior of EHR sharing and exchange, with “consumer” in the center stage. ResultsBased on different information sharing mechanisms, we summarized the “B2C(2B)” behavior into three models, namely, the Inexpensive data media model, the Internet patient portal model and the Personal portable device model. Models each have their own strengths and weaknesses in their ways to share patient data and to address privacy and security concerns. Conclusion Personal use of EHR under the B2C(2B) model does look promising based on our study. We started to observe a trend that governments around the world are embarking on related projects. With multiple stake-holders involved, we are only beginning to understand the complexity of such undertakings.

scholarly journals Potential of an Electronic Health Record-Integrated Patient Portal for Improving Care Plan Concordance during Acute Care

2019 ◽  
Vol 10 (03) ◽  
pp. 358-366 ◽  
Author(s):  
Anuj K. Dalal ◽  
Patricia Dykes ◽  
Lipika Samal ◽  
Kelly McNally ◽  
Eli Mlaver ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Acute Care ◽  
Transitions Of Care ◽  
Care Plan ◽  
Health Record ◽  
Patient Portal ◽  
Intention To Treat ◽  
Electronic Health ◽  
The Impact ◽  
Treat Analysis

Background Care plan concordance among patients and clinicians during hospitalization is suboptimal. Objective This article determines whether an electronic health record (EHR)-integrated patient portal was associated with increased understanding of the care plan, including the key recovery goal, among patients and clinicians in acute care setting. Methods The intervention included (1) a patient portal configured to solicit a single patient-designated recovery goal and display the care plan from the EHR for participating patients; and (2) an electronic care plan for all unit-based nurses that displays patient-inputted information, accessible to all clinicians via the EHR. Patients admitted to an oncology unit, including their nurses and physicians, were enrolled before and after implementation. Main outcomes included mean concordance scores for the overall care plan and individual care plan elements. Results Of 457 and 283 eligible patients approached during pre- and postintervention periods, 55 and 46 participated in interviews, respectively, including their clinicians. Of 46 postintervention patients, 27 (58.7%) enrolled in the patient portal. The intention-to-treat analysis demonstrated a nonsignificant increase in the mean concordance score for the overall care plan (62.0–67.1, adjusted p = 0.13), and significant increases in mean concordance scores for the recovery goal (30.3–57.7, adjusted p < 0.01) and main reason for hospitalization (58.6–79.2, adjusted p < 0.01). The on-treatment analysis of patient portal enrollees demonstrated significant increases in mean concordance scores for the overall care plan (61.9–70.0, adjusted p < 0.01), the recovery goal (30.4–66.8, adjusted p < 0.01), and main reason for hospitalization (58.3–81.7, adjusted p < 0.01), comparable to the intention-to-treat analysis. Conclusion Implementation of an EHR-integrated patient portal was associated with increased concordance for key care plan components. Future efforts should be directed at improving concordance for other care plan components and conducting larger, randomized studies to evaluate the impact on key outcomes during transitions of care. Clinical Trials Identifier NCT02258594.

Hysterectomy utilization among newly diagnosed endometrial cancer patients by body mass index category: A real-world analysis using a claims and electronic health record database.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e17112-e17112
Author(s):  
Debra E. Irwin ◽  
Ellen Thiel
Keyword(s):  
Endometrial Cancer ◽  
Electronic Health Record ◽  
Real World ◽  
Patient Population ◽  
Morbidly Obese ◽  
Health Record ◽  
Newly Diagnosed ◽  
Data Set ◽  
Electronic Health

e17112 Background: For endometrial cancer (EC), laparoscopic hysterectomy (LH) is an effective, minimally invasive surgical treatment; however, this approach may not be recommended for obese patients due to increased risk for complications. Methods: This retrospective study utilized insurance claims linked to electronic health record (EHR) data contained in the IBM MarketScan Explorys Claims-EHR Data Set. Newly diagnosed EC patients (1/1/2007 - 6/30/2017) with continuous enrollment during a 12-month baseline and 6-month follow-up period were selected. Patients were stratified into four BMI subgroups based on baseline BMI on the EHR: normal or underweight (BMI < 25), overweight (BMI 25- < 30), obese (BMI 30- < 40), morbidly obese (BMI > 40), and were required to have had a hysterectomy within the follow-up period. Emergency room visits and rehospitalization within 30 days of hysterectomy were measured. Results: A total of 1,090 newly-diagnosed EC patients met the selection criteria, of whom, 16% were normal/underweight, 19% were overweight, 39% were obese, and 26% were morbidly obese. The proportion of patients receiving LH increased as BMI category increased (Table 1). Among those with LH between 6% and 15% had an ER visit or rehospitalization in 30 days, and rates were higher among other hysterectomy modalities. Conclusions: This real-world analysis shows that LH is utilized in a high proportion of morbidly obese EC patients, despite that it is frequently deemed infeasible in this patient population. Although the rate of ER visits and rehospitalization is lower among LH patients than those undergoing traditional hysterectomy across all BMI strata, further research is needed to determine the optimal patient population to receive LH.[Table: see text]

scholarly journals Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study (Preprint)

2020 ◽  
Author(s):  
Tjardo D Maarseveen ◽  
Timo Meinderink ◽  
Marcel J T Reinders ◽  
Johannes Knitza ◽  
Tom W J Huizinga ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Machine Learning ◽  
Electronic Health Record ◽  
Support Vector ◽  
Free Text ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Data Set ◽  
Record Data ◽  
Electronic Health

BACKGROUND Financial codes are often used to extract diagnoses from electronic health records. This approach is prone to false positives. Alternatively, queries are constructed, but these are highly center and language specific. A tantalizing alternative is the automatic identification of patients by employing machine learning on format-free text entries. OBJECTIVE The aim of this study was to develop an easily implementable workflow that builds a machine learning algorithm capable of accurately identifying patients with rheumatoid arthritis from format-free text fields in electronic health records. METHODS Two electronic health record data sets were employed: Leiden (n=3000) and Erlangen (n=4771). Using a portion of the Leiden data (n=2000), we compared 6 different machine learning methods and a naïve word-matching algorithm using 10-fold cross-validation. Performances were compared using the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPRC), and F1 score was used as the primary criterion for selecting the best method to build a classifying algorithm. We selected the optimal threshold of positive predictive value for case identification based on the output of the best method in the training data. This validation workflow was subsequently applied to a portion of the Erlangen data (n=4293). For testing, the best performing methods were applied to remaining data (Leiden n=1000; Erlangen n=478) for an unbiased evaluation. RESULTS For the Leiden data set, the word-matching algorithm demonstrated mixed performance (AUROC 0.90; AUPRC 0.33; F1 score 0.55), and 4 methods significantly outperformed word-matching, with support vector machines performing best (AUROC 0.98; AUPRC 0.88; F1 score 0.83). Applying this support vector machine classifier to the test data resulted in a similarly high performance (F1 score 0.81; positive predictive value [PPV] 0.94), and with this method, we could identify 2873 patients with rheumatoid arthritis in less than 7 seconds out of the complete collection of 23,300 patients in the Leiden electronic health record system. For the Erlangen data set, gradient boosting performed best (AUROC 0.94; AUPRC 0.85; F1 score 0.82) in the training set, and applied to the test data, resulted once again in good results (F1 score 0.67; PPV 0.97). CONCLUSIONS We demonstrate that machine learning methods can extract the records of patients with rheumatoid arthritis from electronic health record data with high precision, allowing research on very large populations for limited costs. Our approach is language and center independent and could be applied to any type of diagnosis. We have developed our pipeline into a universally applicable and easy-to-implement workflow to equip centers with their own high-performing algorithm. This allows the creation of observational studies of unprecedented size covering different countries for low cost from already available data in electronic health record systems.

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