Utilities of Electronic Medical Records to Improve Quality of Care for Acute Kidney Injury: Past, Present, Future

Nephron ◽  
2015 ◽  
Vol 131 (2) ◽  
pp. 92-96 ◽  
Author(s):  
Kianoush Kashani ◽  
Vitaly Herasevich
Keyword(s):  
Acute Kidney Injury ◽  
Quality Of Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Kidney Injury ◽  
Improve Quality

Electronic medical records: Assessment of recorded cancer stage in support of quality of care.

2012 ◽  
Vol 30 (34_suppl) ◽  
pp. 129-129
Author(s):  
Gregory P. Hess
Keyword(s):  
Quality Of Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Positive Impact ◽  
Significant Proportion ◽  
Malignant Neoplasm ◽  
Cancer Stage ◽  
Underlying Assumption ◽  
Data Field

129 Background: Electronic medical records (EMRs) are being increasingly adopted in part driven by reports of their positive impact on patient’s quality of care. An underlying assumption is that data recorded will be relatively complete. As a field of primary importance, this study assessed the frequency with which cancer stage was recorded within an EMR data field during a historical and recent 12-month period. A random sample of records with missing stage was assessed to identify at a qualitative level reasons that stage may be omitted. Methods: Two datasets were constructed. The first comprised of oncology EMRs from 77 practices covering 476 sites of care across 34 states from 1/1/2000-12/31/2010. The second dataset from 58 practices covering 391 sites of care across 37 states. Inclusion criteria required patients to have a valid visit (i.e., not simply ‘scheduled’) and ≥ 1 diagnosis of a primary, malignant, neoplasm (except brain or spine). All data fields utilized to record stage (stage I, II, etc.) or from which stage could be reliably derived (T, M, N fields) were defined as "recorded." Practices were not required to exist in each dataset. Recorded stage by age, gender, state, and payer type was also assessed. Results: Reasons reported for absent stage within the data field included: consult visit only, written in the progress notes, text present in a scanned report, stage X (insufficient information), continuing treatment initiated elsewhere, and missing entry error. Conclusions: A significant proportion of cancer patients may not have stage recorded in the designated, searchable, data field within an EMR. The frequency of recorded stage is increasing over time. Reasons for unpopulated stage field(s) include use of nonsearchable text entries, scanned reports, and short episodes of care. Further research is needed to validate the observations in this study, determine root causes, and employ appropriate solutions. [Table: see text]

scholarly journals Electronic Medical Records and Diabetes Quality of Care: Results From a Sample of Family Medicine Practices

2007 ◽  
Vol 5 (3) ◽  
pp. 209-215 ◽  
Author(s):  
J. C. Crosson ◽  
P. A. Ohman-Strickland ◽  
K. A. Hahn ◽  
B. DiCicco-Bloom ◽  
E. Shaw ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Family Medicine ◽  
Electronic Medical Records ◽  
Medical Records

Acute kidney injury: outcomes and quality of care

QJM ◽  
2013 ◽  
Vol 106 (4) ◽  
pp. 323-332 ◽  
Author(s):  
E. Aitken ◽  
C. Carruthers ◽  
L. Gall ◽  
L. Kerr ◽  
C. Geddes ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Quality Of Care ◽  
Kidney Injury ◽  
Injury Outcomes

scholarly journals Resistance to Electronic Medical Records (EMRs): A Barrier to Improved Quality of Care

10.28945/2896 ◽  
2005 ◽  
Author(s):  
David Meinert
Keyword(s):  
Quality Of Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Healthcare Sector ◽  
Great Promise ◽  
Successful Implementation ◽  
Attitudes And Beliefs ◽  
Physician Perceptions ◽  
Widespread Adoption

While most industries have aggressively leveraged information technology (IT) to improve quality and reduce costs the healthcare sector has lagged behind. Electronic Medical Records (EMRs) hold great promise for improving quality of care yet widespread adoption is lacking. Physician acceptance is critical to widespread adoption of ambulatory EMRs, yet there is little independent research on physician perceptions. This paper attempts to address this void by reporting the results of a study of physician perceptions related to EMRs in a large, multi-specialty clinic. Physician perceptions of select EMR functions and general attitudes and beliefs are reported. While the importance and anticipated utilization of EMR functions varied, nearly 80 percent of the respondents felt an EMR should be implemented. The findings have implications for both vendors attempting to design and market EMR systems and physician executives and practice managers seeking to solicit support for EMR adoption and/or develop a successful implementation strategy.

Automated safety event monitoring using electronic medical records in a clinical trial setting: Validation study using the VA NEPHRON-D trial

2018 ◽  
Vol 16 (1) ◽  
pp. 81-89 ◽  
Author(s):  
Yuan Huang ◽  
Linda F Fried ◽  
Tassos C Kyriakides ◽  
Gary R Johnson ◽  
Susannah Chiu ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Safety Data ◽  
Kidney Injury ◽  
Medical Record Data ◽  
Electronic Medical Record Data ◽  
Record Data

Background/Aims: Electronic medical records are now frequently used for capturing patient-level data in clinical trials. Within the Veterans Affairs health care system, electronic medical record data have been widely used in clinical trials to assess eligibility, facilitate referrals for recruitment, and conduct follow-up and safety monitoring. Despite the potential for increased efficiency in using electronic medical records to capture safety data via a centralized algorithm, it is important to evaluate the integrity and accuracy of electronic medical record–captured data. To this end, this investigation assesses data collection, both for general and study-specific safety endpoints, by comparing electronic medical record–based safety monitoring versus safety data collected during the course of the Veterans Affairs Nephropathy in Diabetes (VA NEPHRON-D) clinical trial. Methods: The VA NEPHRON-D study was a multicenter, double-blind, randomized clinical trial designed to compare the effect of combination therapy (losartan plus lisinopril) versus monotherapy (losartan) on the progression of kidney disease in individuals with diabetes and proteinuria. The trial’s safety outcomes included serious adverse events, hyperkalemia, and acute kidney injury. A subset of the participants (~62%, n = 895) enrolled in the trial’s long-term follow-up sub-study and consented to electronic medical record data collection. We applied an automated algorithm to search and capture safety data using the VA Corporate Data Warehouse which houses electronic medical record data. Using study safety data reported during the trial as the gold standard, we evaluated the sensitivity and precision of electronic medical record–based safety data and related treatment effects. Results: The sensitivity of the electronic medical record–based safety for hospitalizations was 65.3% without non-VA hospitalization events and 92.3% with the non-VA hospitalization events included. The sensitivity was only 54.3% for acute kidney injury and 87.3% for hyperkalemia. The precision of electronic medical record–based safety data was 89.4%, 38%, and 63.2% for hospitalization, acute kidney injury, and hyperkalemia, respectively. Relative treatment differences under the study and electronic medical record settings were 15% and 3% for hospitalization, 123% and 29% for acute kidney injury, and 238% and 140% for hyperkalemia, respectively. Conclusion: The accuracy of using automated electronic medical record safety data depends on the events of interest. Identification of all-cause hospitalizations would be reliable if search methods could, in addition to VA hospitalizations, also capture non-VA hospitalizations. However, hospitalization is different from a cause-specific serious adverse event that could be more sensitive to treatment effects. In addition, some study-specific safety events were not easily identified using the electronic medical records. This limits the effectiveness of the automated central database search for purposes of safety monitoring. Hence, this data captured approach should be carefully considered when implementing endpoint data collection in future pragmatic trials.

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