Primary Care Physician Gender and Electronic Health Record Workload

Author(s):  
Eve Rittenberg ◽  
Jeffrey B. Liebman ◽  
Kathryn M. Rexrode
2009 ◽  
Vol 22 (2) ◽  
pp. 112-118
Author(s):  
Neil S. Fleming ◽  
Edmund R. Becker ◽  
Steven Culler ◽  
Dunlei Cheng ◽  
Russell Mccorkle ◽  
...  

2016 ◽  
Vol 07 (02) ◽  
pp. 248-259
Author(s):  
Paul Gorman ◽  
Jeffrey Weinfeld

SummaryClinical decision support (CDS) has been shown to improve process outcomes, but overalerting may not produce incremental benefits. We analyzed providers’ response to preventive care reminders to determine if reminder response rates varied when a primary care provider (PCP) saw their own patients as compared with a partner’s patients. Secondary objectives were to describe variation in PCP identification in the electronic health record (EHR) across sites, and to determine its accuracy.We retrospectively analyzed response to preventive care reminders during visits to outpatient primary care sites over a three-month period where an EHR was used. Data on clinician requests for reminders, viewing of preventive care reminders, and response rates were stratified by whether the patient visited their own PCP, the PCP’s partner, or where no PCP was listed in the EHR. We calculated the proportion of PCP identification across sites and agreement of identified PCP with an external standard.Of 84,937 visits, 58,482 (68.9%) were with the PCP, 10,259 (12.1%) were with the PCP’s partner, and 16,196 (19.1%) had no listed PCP. Compared with PCP partner visits, visits with the patient’s PCP were associated with more requested reminders (30.9% vs 22.9%), viewed reminders (29.7% vs 20.7%), and responses to reminders (28.7% vs 12.6%), all comparisons p<0.001. Visits with no listed PCP had the lowest rates of requests, views, and responses. There was good agreement between the EHR-listed PCP and the provider seen for a plurality of visits over the last year (D = 0.917).A PCP relationship during a visit was associated with higher use of preventive care reminders and a lack of PCP was associated with lower use of CDS. Targeting reminders to the PCP may be desirable, but further studies are needed to determine which strategy achieves better patient care outcomes.primary care physician (PCP), clinical decision support (CDS), electronic health record (EHR), National Provider Identifier (NPI)


2005 ◽  
Vol 38 (3) ◽  
pp. 176-188 ◽  
Author(s):  
Lisa Pizziferri ◽  
Anne F. Kittler ◽  
Lynn A. Volk ◽  
Melissa M. Honour ◽  
Sameer Gupta ◽  
...  

BMJ Open ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. e037405
Author(s):  
Daniel Dedman ◽  
Melissa Cabecinha ◽  
Rachael Williams ◽  
Stephen J W Evans ◽  
Krishnan Bhaskaran ◽  
...  

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.


PEDIATRICS ◽  
2006 ◽  
Vol 118 (6) ◽  
pp. e1680-e1686 ◽  
Author(s):  
A. G. Fiks ◽  
E. A. Alessandrini ◽  
A. A. Luberti ◽  
S. Ostapenko ◽  
X. Zhang ◽  
...  

2013 ◽  
Vol 28 (12) ◽  
pp. 1558-1564 ◽  
Author(s):  
Michael F. Murray ◽  
Monica A. Giovanni ◽  
Elissa Klinger ◽  
Elise George ◽  
Lucas Marinacci ◽  
...  

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