scholarly journals Development of standard indicators to assess use of electronic health record systems implemented in low-and medium-income countries

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244917
Author(s):  
Philomena Ngugi ◽  
Ankica Babic ◽  
James Kariuki ◽  
Xenophon Santas ◽  
Violet Naanyu ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Quality Indicators ◽  
Nominal Group Technique ◽  
Data Entry ◽  
Nominal Group ◽  
Health Record ◽  
Actual System ◽  
Middle Income ◽  
Actual Usage ◽  
Electronic Health

Background Electronic Health Record Systems (EHRs) are being rolled out nationally in many low- and middle-income countries (LMICs) yet assessing actual system usage remains a challenge. We employed a nominal group technique (NGT) process to systematically develop high-quality indicators for evaluating actual usage of EHRs in LMICs. Methods An initial set of 14 candidate indicators were developed by the study team adapting the Human Immunodeficiency Virus (HIV) Monitoring, Evaluation, and Reporting indicators format. A multidisciplinary team of 10 experts was convened in a two-day NGT workshop in Kenya to systematically evaluate, rate (using Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) criteria), prioritize, refine, and identify new indicators. NGT steps included introduction to candidate indicators, silent indicator ranking, round-robin indicator rating, and silent generation of new indicators. 5-point Likert scale was used in rating the candidate indicators against the SMART components. Results Candidate indicators were rated highly on SMART criteria (4.05/5). NGT participants settled on 15 final indicators, categorized as system use (4); data quality (3), system interoperability (3), and reporting (5). Data entry statistics, systems uptime, and EHRs variable concordance indicators were rated highest. Conclusion This study describes a systematic approach to develop and validate quality indicators for determining EHRs use and provides LMICs with a multidimensional tool for assessing success of EHRs implementations.

scholarly journals Development of Standard Indicators to Assess Use of Electronic Health Record Systems Implemented in Low- and Medium-Income Countries

2020 ◽  
Author(s):  
Philomena Njeri Ngugi ◽  
Ankica Babic ◽  
James Kariuki ◽  
Xenophon Santas ◽  
Violet Naanyu ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Quality Indicators ◽  
Nominal Group Technique ◽  
Data Entry ◽  
Nominal Group ◽  
Health Record ◽  
Actual System ◽  
Middle Income ◽  
Actual Usage ◽  
Electronic Health

Abstract BackgroundElectronic Health Record Systems (EHRs) are being rolled out nationally in many low- and middle-income countries (LMICs) yet assessing actual system usage remains a challenge. We employed a nominal group technique (NGT) process to systematically develop high-quality indicators for evaluating actual usage of EHRs in LMICs.Methods An initial set of 14 candidate indicators were developed by the study team adapting the HIV Monitoring, Evaluation, and Reporting indicators format. A multidisciplinary team of 10 experts was convened in a two-day NGT workshop in Kenya to systematically evaluate, rate (using Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) criteria), prioritize, refine, and identify new indicators. NGT steps included introduction to candidate indicators, silent indicator ranking, round-robin indicator rating, and silent generation of new indicators. Results: Candidate indicators were rated highly on SMART criteria (4.05/5). NGT participants settled on 15 final indicators, categorized as system use (4); data quality (3), system interoperability (3), and reporting (5). Data entry statistics, systems uptime, and EHRs variable concordance indicators were rated highest. ConclusionThis study describes a systematic approach to develop and validate quality indicators for determining EHRs use and provides LMICs with a multidimensional tool for assessing success of EHRs implementations.

scholarly journals Formal representation of patients’ care context data: the path to improving the electronic health record

2020 ◽  
Vol 27 (11) ◽  
pp. 1648-1657
Author(s):  
Tiago K Colicchio ◽  
Pavithra I Dissanayake ◽  
James J Cimino
Keyword(s):  
Electronic Health Record ◽  
Data Entry ◽  
Data Sources ◽  
Health Record ◽  
Formal Representation ◽  
Semantic Relationships ◽  
Navigation Data ◽  
Multiple Data ◽  
Context Data ◽  
Electronic Health

Abstract Objective To develop a collection of concept-relationship-concept tuples to formally represent patients’ care context data to inform electronic health record (EHR) development. Materials and Methods We reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources. Results We annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts. Conclusions We produced a robust set of 82 tuples useful to represent patients’ care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.

scholarly journals Data Migration: A Thorny Issue in Electronic Health Record Transitions—Case Studies and Review of the Literature

ACI Open ◽  
2020 ◽  
Vol 04 (01) ◽  
pp. e48-e58
Author(s):  
Richard Schreiber ◽  
Lawrence Garber
Keyword(s):  
Electronic Health Record ◽  
Case Studies ◽  
Panel Discussion ◽  
Data Entry ◽  
Data Migration ◽  
Health Record ◽  
Research On Evaluation ◽  
Electronic Health ◽  
American Medical Informatics Association ◽  
Experiential Research

Abstract Objective To review the existing literature regarding data migration during electronic health record (EHR)-to-EHR transitions and add two case studies on this topic. Methods Very few publications exist that detail the processes and potential pitfalls of data migration during EHR transitions. One of the authors participated in a panel discussion at the American Medical Informatics Association symposium in 2015; at the time, only five empiric or experiential research articles on any aspect of EHR transitions were available. Of those, only two mentioned their experiences with data migration or conversions. A detailed PubMed and CINAHL (Cumulative Index to Nursing and Allied Health Literature) search in March 2019 yielded only one more article giving details about data migration. Results The two new case studies contrast starkly: one relied on manual abstraction and data entry, whereas the other leveraged several electronic tools. The literature reflects this diversity of approach: no two sites have reported the same approaches. The authors identify nine domains of potential consequences of the currently available techniques and offer mitigating strategies. Discussion Very little empiric information exists in the peer-reviewed literature regarding data migrations during EHR-to-EHR transitions; yet the case studies reflect that much remains suitable for a prospective study. Conclusion This report adds two new case studies to the six already reported in the literature. There is a wide disparity in techniques of data migration, each with its own set of pros and cons, which sites must consider during an EHR-to-EHR transition. Such transitions would benefit from prospective research on evaluation and knowledge discovery.

Electronic Health Record for Forensic Dentistry

2008 ◽  
Vol 47 (01) ◽  
pp. 8-13 ◽  
Author(s):  
T. Dostálová ◽  
P. Hanzlíček ◽  
Z. Teuberová ◽  
M. Nagy ◽  
M. Pieš ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Data Entry ◽  
Structured Data ◽  
Health Record ◽  
Forensic Dentistry ◽  
Disaster Victim Identification ◽  
Health Records ◽  
Victim Identification ◽  
Electronic Health

Summary Objectives: To identify support of structured data entry for electronic health record application in forensic dentistry. Methods: The methods of structuring information in dentistry are described and validation of structured data entry in electronic health records for forensic dentistry is performed on several real cases with the interactive DentCross component. The connection of this component to MUDR and MUDRLite electronic health records is described. Results: The use of the electronic health record MUDRLite and the interactive DentCross component to collect dental information required by standardized Disaster Victim Identification Form by Interpol for possible victim identification is shown. Conclusions: The analysis of structured data entry for dentistry using the DentCross component connected to an electronic health record showed the practical ability of the DentCross component to deliver a real service to dental care and the ability to support the identification of a person in forensic dentistry.

Evaluation of voice-based data entry to an electronic health record system for dentistry

2013 ◽  
Vol 33 (4) ◽  
pp. 204-210 ◽  
Author(s):  
Karel Chleborad ◽  
Karel Zvara ◽  
Tatjana Dostalova ◽  
Karel Zvara ◽  
Radek Hippmann ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Data Entry ◽  
Electronic Health Record System ◽  
Health Record ◽  
Record System ◽  
Electronic Health

Distributed Electronic Documentation Practices of Homecare Admission: Informing Electronic Health Record Design Guidelines

2017 ◽  
Vol 61 (1) ◽  
pp. 573-577
Author(s):  
Yushi Yang ◽  
Ellen J. Bass ◽  
Paulina Sockolow
Keyword(s):  
Home Care ◽  
Electronic Health Record ◽  
Clinical Judgment ◽  
Data Entry ◽  
Clinical Decision ◽  
Design Guidelines ◽  
Health Record ◽  
Admission Process ◽  
Electronic Health ◽  
Data Elements

Home care nurses complete many activities as part of the admission process. A pilot study of the home care admission process indicated that a nurse distributes data entry tasks between the patient’s home and a post-documentation period later in the day. We found evidence of a strategy to document information that requires direct observation (either from the patient or through viewing the home environment) in the home. We found evidence of a strategy to document outside of the home for data elements based on clinical judgment or assessments as well as information supported by clinical decision support in the Electronic Health Record (EHR). These finding inform recommendations for data entry and navigation design guidelines for home care admission EHR systems.

Do Electronic Health Record Systems Increase Medicare Reimbursements? The Moderating Effect of the Recovery Audit Program

2021 ◽  
Author(s):  
Kartik K. Ganju ◽  
Hilal Atasoy ◽  
Paul A. Pavlou
Keyword(s):  
Information Systems ◽  
Electronic Health Record ◽  
Data Entry ◽  
Healthcare Research ◽  
Health Record ◽  
Patient Complexity ◽  
Electronic Health ◽  
Copy And Paste ◽  
Value Of It ◽  
Audit Program

Electronic health record (EHR) systems allow physicians to automate the process of entering patient data relative to manual entry in traditional paper-based records. However, such automated data entry can lead to increased reimbursement requests by hospitals from Medicare by overstating the complexity of patients. The EHR module that has been alleged to increase reimbursements is the Computerized Physician Order Entry (CPOE) system, which populates patient charts with default templates and allows physicians to copy and paste data from previous charts of the patient and other patients’ records. To combat increased reimbursements by hospitals from Medicare, the Centers for Medicare & Medicaid Services implemented the Recovery Audit Program first as a pilot in six states between 2005 and 2009 and then, nationwide in the entire United States in 2010. We examine whether the adoption of CPOE systems by hospitals is associated with an increase in reported patient complexity and if the Recovery Audit Program helped to attenuate this relationship. We find that the adoption of CPOE systems significantly increases patient complexity reported by hospitals, corresponding to an estimate of $1 billion increase in Medicare reimbursements per year. This increase was attenuated when hospitals were regulated by the Recovery Audit Program. Notably, those recovery auditors who developed the ability to identify the use of default templates, copied and pasted data, and cloned records were the most effective in reducing increased reimbursements. These findings have implications on how to combat Medicare reimbursements paid by taxpayer dollars with the Recovery Audit Program and how this information technology (IT) audit can prevent the misuse of information systems to create artificial business value of IT by hospitals. Contributions to information systems and healthcare research, practice, and public policy are discussed. This paper was accepted by Chris Forman, information systems.

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