manual data entry
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2021 ◽  
pp. 23-33
Author(s):  
Karen Zimmer ◽  
David Classen ◽  
Jessica Cole

Preventable medication errors continue to affect the quality and consistency in the delivery of care. While numerous studies on medication safety have been performed in the inpatient setting, a review of ambulatory patient safety by the American Medical Association found that medication safety errors were the most frequent safety problems in the outpatient arena. The leading cause of ambulatory safety problems, adverse drug events (ADEs), are common, with estimates of more than 2 million ADEs each year in the ambulatory Medicare population alone, and these events are frequently preventable. We conducted an environmental scan that allowed us to create our own categorization schema of medication safety errors in electronic healthcare records (EHRs) found in the outpatient setting and observed which of these were additionally supported in the literature. This study combines data from the California Hospital Patient Safety Organization (CHPSO), with several key articles in the area of medication errors in the EHR era. Method: To best utilize the various EHR ambulatory medication events submitted into CHPSO’s database, we chose to create a framework to bucket the near misses or adverse events (AEs) submitted to the database. This newly created categorization scheme was based on our own drafted categorization labels of events, after a high-level review, and from two leading articles on physician order entry. Additionally, we conducted a literature review of computerized provider order entry (CPOE) medication errors in the ambulatory setting. Within the newly created categorization scheme, we organized the articles based on issues addressed so we could see areas that were supported by the literature and what still needed to be researched. Results: We initially screened the CHPSO database for ambulatory safety events and found 25,417 events. Based on those events, an initial review was completed, and 19,242 events were found in the “Medication or Other Substance” and “Other” categories, in which the EHR appeared to have been a potential contributing factor. This review identified a subset of 2,236 events that were then reviewed. One hundred events were randomly selected for further review to identify common categories. The most common categories in which errors occurred were orders in order sets and plans (n=12) and orders crossing or not crossing encounters (n=12), incorrect order placed on correct patient (n=10), orders missing (n=8), standing orders (n=8), manual data entry errors (n=6), and future orders (n=6). Conclusion: There were several common themes seen in this analysis of ambulatory medication safety errors related to the EHR. Common among them were incorrect orders consisting of examples such as dose errors or ordering the wrong medication. The manual data entry errors consisted of height or weight being entered incorrectly or entering the wrong diagnostic codes. Lastly, different sources of medication safety information demonstrate a diversity of errors in ambulatory medication safety. This confirms the importance of considering more than one source when attempting to comprehensively describe ambulatory medication safety errors.


2020 ◽  
Vol 6 (4) ◽  
pp. 19-22
Author(s):  
Štefan Mozol ◽  
Patrik Grznár ◽  
Martin Krajčovič

The main object of the article is a design system for faster data actualisation in Tecnomatix Plant Simulation software through the AttributeExplorer function and Microsoft Excel. Many companies that use simulation as the optimisation tool is meet the problem of the models up to date and actualisation time demands. The designed system that uses the AttributeExplorer function of the Tecnomatix Plant Simulation reduces the actualisation time demands for activities. The end part of the article contains a comparison of the normal manual data entry and time demands for using the designed system.


2019 ◽  
Vol 27 (9) ◽  
pp. 555-561
Author(s):  
Nicola Lang ◽  
Sophie Jose ◽  
Amanda Rogers ◽  
Helen Maric ◽  
Victoria Lyon ◽  
...  

Background Better Births recommends that women receive continuity of carer in order to improve outcomes. Aim To measure changes from implementing a continuity of carer approach, in terms complicated or uncomplicated births. Method In North-West London in 2017-2018, funding was allocated to establish an early adopters' programme across six maternity units. The implementation of this programme and the outcomes in terms of birth complications and women's feedback are described. Findings Although most changes were not statistically significant, positive maternal views, and some changes in the use of diet control or insulin for women with gestational diabetes, were found. Conclusions The evaluation was limited by missing data, and in future, maternity outcomes should be extracted routinely from women's records without requiring manual data entry by midwives.


2018 ◽  
Vol 62 (1) ◽  
pp. 37
Author(s):  
Angela R. Davis ◽  
Jeff Edmunds

When the authors discovered a forgotten microfiche collection, they knew they needed to determine a process to make the information discoverable and accessible to researchers. Using a combination of manual data entry, cross-checking against printed indexes, and batch conversion of data using MarcEdit, they devised processes and workflows for creating reasonably good metadata for this large collection and for loading the MARC records into their local integrated library system. Their methods can serve as a model for any collection for which basic metadata would be useful in enhancing discovery and access.


2014 ◽  
Vol 05 (01) ◽  
pp. 284-298 ◽  
Author(s):  
A. Hsiao ◽  
A. Fenick ◽  
J. Michel

SummaryBackground: Transitioning between Electronic Medical Records (EMR) can result in patient data being stranded in legacy systems with subsequent failure to provide appropriate patient care. Manual chart abstraction is labor intensive, error-prone, and difficult to institute for immunizations on a systems level in a timely fashion.Objectives: We sought to transfer immunization data from two of our health system’s soon to be replaced EMRs to the future EMR using a single process instead of separate interfaces for each facility.Methods: We used scripted data entry, a process where a computer automates manual data entry, to insert data into the future EMR. Using the Center for Disease Control’s CVX immunization codes we developed a bridge between immunization identifiers within our system’s EMRs. We performed a two-step process evaluation of the data transfer using automated data comparison and manual chart review.Results: We completed the data migration from two facilities in 16.8 hours with no data loss or corruption. We successfully populated the future EMR with 99.16% of our legacy immunization data – 500,906 records – just prior to our EMR transition date. A subset of immunizations, first recognized during clinical care, had not originally been extracted from the legacy systems. Once identified, this data – 1,695 records – was migrated using the same process with minimal additional effort.Conclusions: Scripted data entry for immunizations is more accurate than published estimates for manual data entry and we completed our data transfer in 1.2% of the total time we predicted for manual data entry. Performing this process before EMR conversion helped identify obstacles to data migration. Drawing upon this work, we will reuse this process for other healthcare facilities in our health system as they transition to the future EMR.Citation: Michel J, Hsiao A, Fenick A. Using a scripted data entry process to transfer legacy immunization data while transitioning between electronic medical record systems. Appl Clin Inf 2014; 5: 284–298 http://dx.doi.org/10.4338/ACI-2013-11-RA-0096


2012 ◽  
Vol 39 (6Part13) ◽  
pp. 3750-3750
Author(s):  
S Zhou ◽  
S Chen ◽  
A Wahl ◽  
C Enke

1995 ◽  
Vol 41 (4) ◽  
pp. 491-494
Author(s):  
D M Baer ◽  
M L Kotschi

Abstract Decision support computer technology (DST) embedded in laboratory or hospital information systems has great potential but has rarely been successful. Through studying a pharmacokinetic program that automatically extracted data without requiring manual data entry, we have identified several barriers to the successful implementation of DST. Manual data entry is a major barrier, but so is the entry of erroneous data such as heights, weights, drug dosing times, and specimen collection times. In such a system, unanticipated changed modes of clinical practice and software changes in the system's component modules can be incompatible with the decision-support program, necessitating software revisions. We also noted that clinicians increased their ordering of laboratory tests and changes in drug doses but without improvement in patients' outcomes. This suggests that information output from the program can be misinterpreted by clinicians. In summary, DST programs should be validated in an actual working environment.


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