scholarly journals The Effect of Adoption of an Electronic Health Record on Duplicate Testing

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Todd C. Kerwin ◽  
Harmony Leighton ◽  
Kunal Buch ◽  
Azriel Avezbadalov ◽  
Hormoz Kianfar
Keyword(s):  
Electronic Health Record ◽  
First Year ◽  
Health Record ◽  
Improve Quality ◽  
Repeat Testing ◽  
Quality Of Patient Care ◽  
Before And After ◽  
Electronic Health ◽  
Implementation Of Ehr

Background. The electronic health record (EHR) has been promoted as a tool to improve quality of patient care, reduce costs, and improve efficiency. There is little data to confirm that the use of EHR has reduced duplicate testing. We sought to evaluate the rate of performance of repeat transthoracic echocardiograms before and after the adoption of EHR.Methods. We retrospectively examined the rates of repeat echocardiograms performed before and after the implementation of an EHR system.Results. The baseline rate of repeat testing before EHR was 4.6% at six months and 7.6% at twelve months. In the first year following implementation of EHR, 6.6% of patients underwent a repeat study within 6 months, and 12.9% within twelve months. In the most recent year of EHR usage, 5.7% of patients underwent repeat echocardiography at six months and 11.9% within twelve months. All rates of duplicate testing were significantly higher than their respective pre-EHR rates (p<0.01for all).Conclusion. Our study failed to demonstrate a reduction in the rate of duplicate echocardiography testing after the implementation of an EHR system. We feel that this data, combined with other recent analyses, should promote a more rigorous assessment of the initial claims of the benefits associated with EHR implementation.

AIRA, an Artificial Intelligence Realistic Assistant that will save your time, a before-and-after study during Pandemic (Preprint)

2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Junior ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Medical Care ◽  
Health Screening ◽  
Urgent Care ◽  
Health Record ◽  
Before And After ◽  
Electronic Health ◽  
The Impact ◽  
Before And After Study

BACKGROUND AIRA is an AI designed to reduce the time that doctors dedicate filling out EHR, winner of the first edition of MIT Hacking Medicine held in Brazil in 2020. As a proof of concept, AIRA was implemented in administrative process before its application in a medical process. OBJECTIVE The aim of the study is to determinate the impact of AIRA by eliminating the Medical Care Registration (MCR) on Electronic Health Record (EHR) by Administrative Officer. METHODS This is a comparative before-and-after study following the guidance “Evaluating digital health products” from Public Health England. An Artificial Intelligence named AIRA was created and implemented at CEAC (Employee Attention Center) from HCFMUSP. A total of 25,507 attendances were evaluated along 2020 for determinate AIRA´s impact. Total of MCR, time of health screening and time between the end of the screening and the beginning of medical care, were compared in the pre and post AIRA periods. RESULTS AIRA eliminated the need for Medical Care Registration by Administrative Officer in 92% (p<0.0001). The nurse´s time of health screening increased 16% (p<0.0001) during the implementation, and 13% (p<0.0001) until three months after the implementation, but reduced in 4% three months after implementation (p<0.0001). The mean and median total time to Medical Care after the nurse’ Screening was decreased in 30% (p<0.0001) and 41% (p<0.0001) respectively. CONCLUSIONS The implementation of AIRA reduced the time to medical care in an urgent care after the nurse´ screening, by eliminating non-value-added activity the Medical Care Registration on Electronic Health Record (EHR) by Administrative Officer.

ED syphilis and gonorrhea/chlamydia cotesting practices before and after the implementation of an electronic health record-based alert

2021 ◽  
pp. emermed-2020-210331
Author(s):  
James S Ford ◽  
Tasleem Chechi ◽  
Michella Otmar ◽  
Melissa Baker ◽  
Sarah Waldman ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Underserved Populations ◽  
Cohort Analysis ◽  
Treponema Pallidum ◽  
Interrupted Time Series ◽  
Health Record ◽  
Interrupted Time Series Analysis ◽  
Syphilis Testing ◽  
Before And After ◽  
Electronic Health

BackgroundThe prevalence of syphilis is increasing in many countries, including the USA. The ED is often used by underserved populations, making it an important setting to test and treat patients who are not evaluated in outpatient clinical settings. We aimed to assess the utility of an ED-based syphilis and gonorrhoea/chlamydia cotesting protocol by comparing testing practices before and after its implementation.MethodsWe implemented an electronic health record (EHR) alert that prompted clinicians to order syphilis testing in patients undergoing gonorrhoea/chlamydia testing. We performed a retrospective cohort analysis that compared outcomes between the preimplementation period (January–November 2018) and the postimplementation period (January–November 2019). Patients were tested for Treponema pallidum antibody (TPA) using a multiplex flow immunoassay (MFI), and positive results were confirmed by rapid plasma reagin (RPR). The primary implementation outcome was the number of syphilis tests/month, and the primary clinical outcome was the number of syphilis diagnoses/month (defined as positive TPA MFI and RPR). We performed an interrupted time-series analysis to evaluate the effect of implementing the alert over time.ResultsFour-hundred and ninety-four and 1106 unique patients were tested for syphilis in the preimplementation and postimplementation periods, respectively. Syphilis testing increased by 55.6 tests/month (95% CI 45.9 to 65.3, p<0.001) following alert implementation. Patients tested in the postimplementation period who were tested using the alert were much younger (difference: 14 years (95% CI 12 to 15)) and were more likely to be female (difference: 15% (95% CI 8 to 21)) and African-American (difference: 11% (95% CI 5 to 17)) than patients tested by clinician-initiated testing. Presumptive syphilis diagnoses increased from 3.4 diagnoses/month to 7.9 diagnoses/month (difference, 4.5 (95% CI 2.2 to 6.9), p<0.001).ConclusionsOur study demonstrates that use of a targeted EHR alert testing protocol can increase syphilis testing and diagnosis and may reduce clinician bias in testing.

scholarly journals 1082 Using an Electronic Health Record (EHR) to Collect and Use Quality-Of-Life Data for AASM Process and Outcomes Quality Measures

SLEEP ◽  
2018 ◽  
Vol 41 (suppl_1) ◽  
pp. A402-A402 ◽  
Author(s):  
B Staley ◽  
B T Keenan ◽  
S Simonsen ◽  
R Warrell ◽  
R Schwab ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Electronic Health Record ◽  
Quality Measures ◽  
Health Record ◽  
Life Data ◽  
Electronic Health

scholarly journals Diabetes and Hypertension Quality Measurement in Four Safety-Net Sites

2014 ◽  
Vol 05 (03) ◽  
pp. 757-772 ◽  
Author(s):  
R. Benkert ◽  
P. Dennehy ◽  
J. White ◽  
A. Hamilton ◽  
C. Tanner ◽  
...  
Keyword(s):  
Electronic Health Record ◽  
Quality Measurement ◽  
Safety Net ◽  
Lessons Learned ◽  
Health Record ◽  
Partnership Model ◽  
Safety Net Clinics ◽  
Electronic Health ◽  
Query Algorithms

SummaryBackground: In this new era after the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the literature on lessons learned with electronic health record (EHR) implementation needs to be revisited.Objectives: Our objective was to describe what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics, specifically feasibility of data retrieval, measurements over time, quality of data, and how our teams used this data.Methods: A cross-sectional study was conducted from October 2008 to October 2012 in four safety-net clinics located in the Midwest and Western United States. A data warehouse that stores data from across the U.S was utilized for data extraction from patients with diabetes or hypertension diagnoses and at least two office visits per year. Standard quality measures were collected over a period of two to four years. All sites were engaged in a partnership model with the IT staff and a shared learning process to enhance the use of the quality metrics.Results: While use of the algorithms was feasible across sites, challenges occurred when attempting to use the query results for research purposes. There was wide variation of both process and outcome results by individual centers. Composite calculations balanced out the differences seen in the individual measures. Despite using consistent quality definitions, the differences across centers had an impact on numerators and denominators. All sites agreed to a partnership model of EHR implementation, and each center utilized the available resources of the partnership for Center-specific quality initiatives.Conclusions: Utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models.Citation: Benkert R, Dennehy P, White J, Hamilton A, Tanner C, Pohl JM. Diabetes and hypertension quality measurement in four safety-net sites: Lessons learned after implementation of the same commercial electronic health record. Appl Clin Inf 2014; 5: 757–772http://dx.doi.org/10.4338/ACI-2014-03-RA-0019

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