scholarly journals A national electronic health record for primary care

2019 ◽  
Vol 191 (2) ◽  
pp. E28-E29 ◽  
Author(s):  
Nav Persaud
Keyword(s):  
Primary Care ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health

scholarly journals Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e037405
Author(s):  
Daniel Dedman ◽  
Melissa Cabecinha ◽  
Rachael Williams ◽  
Stephen J W Evans ◽  
Krishnan Bhaskaran ◽  
...  
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Electronic Health Record ◽  
Observational Studies ◽  
Meta Analysis ◽  
Data Sources ◽  
Health Record ◽  
Two Stage ◽  
One Stage ◽  
Electronic Health

ObjectiveTo identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources.DesignA systematic review of published studies.Data sourcesPubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening.Study selectionObservational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases.Results6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies.ConclusionsComparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.

Identifying Factors Predicting Immunization Delay for Children Followed in an Urban Primary Care Network Using an Electronic Health Record

PEDIATRICS ◽  
2006 ◽  
Vol 118 (6) ◽  
pp. e1680-e1686 ◽  
Author(s):  
A. G. Fiks ◽  
E. A. Alessandrini ◽  
A. A. Luberti ◽  
S. Ostapenko ◽  
X. Zhang ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Record ◽  
Health Record ◽  
Care Network ◽  
Electronic Health

scholarly journals Comparing Electronic Health Record Portals to Obtain Patient-Entered Family Health History in Primary Care

2013 ◽  
Vol 28 (12) ◽  
pp. 1558-1564 ◽  
Author(s):  
Michael F. Murray ◽  
Monica A. Giovanni ◽  
Elissa Klinger ◽  
Elise George ◽  
Lucas Marinacci ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Record ◽  
Family Health ◽  
Family Health History ◽  
Health Record ◽  
Health History ◽  
Electronic Health

scholarly journals Use of electronic health record data from diverse primary care practices to identify and characterize patients’ prescribed common medications

2018 ◽  
Vol 26 (1) ◽  
pp. 172-180 ◽  
Author(s):  
Allison M Cole ◽  
Kari A Stephens ◽  
Imara West ◽  
Gina A Keppel ◽  
Ken Thummel ◽  
...  
Keyword(s):  
Primary Care ◽  
Adverse Events ◽  
Electronic Health Record ◽  
Research Network ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Care Practices ◽  
Electronic Health ◽  
Primary Care Practices

We use prescription of statin medications and prescription of warfarin to explore the capacity of electronic health record data to (1) describe cohorts of patients prescribed these medications and (2) identify cohorts of patients with evidence of adverse events related to prescription of these medications. This study was conducted in the WWAMI region Practice and Research Network (WPRN)., a network of primary care practices across Washington, Wyoming, Alaska, Montana and Idaho DataQUEST, an electronic data-sharing infrastructure. We used electronic health record data to describe cohorts of patients prescribed statin or warfarin medications and reported the proportions of patients with adverse events. Among the 35,445 active patients, 1745 received at least one statin prescription and 301 received at least one warfarin prescription. Only 3 percent of statin patients had evidence of myopathy; 51 patients (17% of those prescribed warfarin) had a bleeding complication. Primary-care electronic health record data can effectively be used to identify patients prescribed specific medications and patients potentially experiencing medication adverse events.

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