scholarly journals Academic Nursing Center Primary Care Quality Improvement Using an Electronic Health Record and a Practice-Based Research Network

2014 ◽  
Vol 04 (09) ◽  
pp. 637-643
Author(s):  
Thomas A. Mackey ◽  
Laura Rooney ◽  
Delyse Hart
Keyword(s):  
Primary Care ◽  
Quality Improvement ◽  
Electronic Health Record ◽  
Care Quality ◽  
Research Network ◽  
Health Record ◽  
Primary Care Quality ◽  
Practice Based Research ◽  
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.

Achievable Benchmarks of Care for Primary Care Quality Indicators in a Practice-Based Research Network

2008 ◽  
Vol 23 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Andrea M. Wessell ◽  
Heather A. Liszka ◽  
Paul J. Nietert ◽  
Ruth G. Jenkins ◽  
Lynne S. Nemeth ◽  
...  
Keyword(s):  
Primary Care ◽  
Quality Indicators ◽  
Care Quality ◽  
Research Network ◽  
Primary Care Quality ◽  
Practice Based Research

scholarly journals Patient Portal Use, Perceptions of Electronic Health Record Value, and Self-Rated Primary Care Quality Among Older Adults: Cross-sectional Survey (Preprint)

2020 ◽  
Author(s):  
Dori A Cross ◽  
Zachary Levin ◽  
Minakshi Raj
Keyword(s):  
Older Adults ◽  
Primary Care ◽  
Electronic Health Record ◽  
Care Quality ◽  
Health Record ◽  
Patient Portal ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Value Perception ◽  
Primary Care Quality

BACKGROUND Older adults are increasingly accessing information and communicating using patient-facing portals available through their providers’ electronic health record (EHR). Most theories of technology acceptance and use suggest that patients’ overall satisfaction with care should be independent of their chosen level of portal engagement. However, achieving expected benefits of portal use depends on demonstrated support from providers to meet these expectations. This is especially true among older adults, who may require more guidance. However, little is known about whether misalignment of expectations around technology-facilitated care is associated with lower perceptions of care quality. OBJECTIVE The aims of this study were to analyze whether older adults’ assessment of primary care quality differs across levels of patient portal engagement and whether perceptions of how well their provider uses the EHR to support care moderates this relationship. METHODS We conducted a cross-sectional survey analysis of 158 older adults over the age of 65 (average age 71.4 years) across Michigan using a 13-measure composite of self-assessed health care quality. Portal use was categorized as none, moderate (use of 1-3 functionalities), or extensive (use of 4-7 functionalities). EHR value perception was measured by asking respondents how they felt their doctor’s EHR use improved the patient–provider relationship. RESULTS Moderate portal users, compared to those who were extensive users, had lower estimated care quality (–0.214 on 4-point scale; <i>P</i>=.03). Differences between extensive portal users and nonportal users were not significant. Quality perception was only particularly low among moderate portal users with low EHR value perception; those with high EHR value perception rated quality similarly to other portal user groups. CONCLUSIONS Older adults who are moderate portal users are the least satisfied with their care, and the most sensitive to perceptions of how well their provider uses the EHR to support the relationship. Encouraging portal use without compromising perceptions of quality requires thinking beyond patient-focused education. Achieving value from use of patient-facing technologies with older adults is contingent upon matched organizational investments that support technology-enabled care delivery. Providers and staff need policies and practices that demonstrate technology adeptness. Older adults may need more tailored signaling and accommodation for technology to be maximally impactful.

scholarly journals Primary Care Practices’ Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement

2018 ◽  
Vol 37 (4) ◽  
pp. 635-643 ◽  
Author(s):  
Deborah J. Cohen ◽  
David A. Dorr ◽  
Kyle Knierim ◽  
C. Annette DuBard ◽  
Jennifer R. Hemler ◽  
...  
Keyword(s):  
Primary Care ◽  
Quality Improvement ◽  
Electronic Health Record ◽  
Health Record ◽  
Electronic Health Record Data ◽  
Record Data ◽  
Care Practices ◽  
Electronic Health ◽  
Primary Care Practices

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
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