What is evaluation of hematuria by primary care physicians? Use of electronic medical records to assess practice patterns with intermediate follow-up

2014 ◽  
Vol 32 (2) ◽  
pp. 128-134 ◽  
Author(s):  
Anna Buteau ◽  
Casey A. Seideman ◽  
Robert S. Svatek ◽  
Ramy F. Youssef ◽  
Gaurab Chakrabarti ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Primary Care Physicians ◽  
Practice Patterns ◽  
Is Evaluation

scholarly journals What Results Should Be Returned from Opportunistic Screening in Translational Research?

2020 ◽  
Vol 10 (1) ◽  
pp. 13 ◽  
Author(s):  
Colin M. E. Halverson ◽  
Sarah H. Jones ◽  
Laurie Novak ◽  
Christopher Simpson ◽  
Digna R. Velez Edwards ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Primary Care Physicians ◽  
Ethical Issues ◽  
Opportunistic Screening ◽  
Test Results ◽  
Undue Burden ◽  
Positive Results

Increasingly, patients without clinical indications are undergoing genomic tests. The purpose of this study was to assess their appreciation and comprehension of their test results and their clinicians’ reactions. We conducted 675 surveys with participants from the Vanderbilt Electronic Medical Records and Genomics (eMERGE) cohort. We interviewed 36 participants: 19 had received positive results, and 17 were self-identified racial minorities. Eleven clinicians who had patients who had participated in eMERGE were interviewed. A further 21 of these clinicians completed surveys. Participants spontaneously admitted to understanding little or none of the information returned to them from the eMERGE study. However, they simultaneously said that they generally found testing to be “helpful,” even when it did not inform their health care. Primary care physicians expressed discomfort in being asked to interpret the results for their patients and described it as an undue burden. Providing genetic testing to otherwise healthy patients raises a number of ethical issues that warrant serious consideration. Although our participants were enthusiastic about enrolling and receiving their results, they express a limited understanding of what the results mean for their health care. This fact, coupled the clinicians’ concern, urges greater caution when educating and enrolling participants in clinically non-indicated testing.

scholarly journals Improving Compliance with Screening of Diabetic Patients for Microalbuminuria in Primary Care Practice

2013 ◽  
Vol 2013 ◽  
pp. 1-3 ◽  
Author(s):  
Abeer Anabtawi ◽  
L. Mary Mathew
Keyword(s):  
Primary Care ◽  
Quality Control ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Primary Care Physicians ◽  
Primary Care Practice ◽  
Compliance Rate ◽  
Care Practice ◽  
Diabetic Patients ◽  
Modest Improvement

Studies showed suboptimal compliance rate of primary care physicians with microalbuminuria screening. This study evaluated impact of electronic medical records (EMR) and computerized physicians reminders on compliance rate and showed small to modest improvement. Combining EMR with quality control monitoring has significantly improved compliance [OR 1.556, 95% CI 1.251–1.935, ].

scholarly journals Reversing Frailty Levels in Primary Care Using the CARES Model

2017 ◽  
Vol 20 (3) ◽  
pp. 105-111 ◽  
Author(s):  
Olga Theou ◽  
Grace H. Park ◽  
Antonina Garm ◽  
Xiaowei Song ◽  
Barry Clarke ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Frailty Index ◽  
Community Dwelling ◽  
Care Plan ◽  
Pilot Phase ◽  
Clinical Frailty Scale ◽  
Positive Effect

BackgroundThe purpose of this manuscript was to evaluate the effectiveness of the Community Actions and Resources Empowering Seniors (CARES) model in measuring and mitigating frailty among community-dwelling older adults.MethodsThe CARES model is based on a goal-oriented multidisciplinary primary care plan which combines a comprehensive geriatric assessment (CGA) with health coaching. A total of 51 older adults (82 ± 7 years; 33 females) participated in the pilot phase of this initiative. Frailty was measured using the Clinical Frailty Scale (CFS) and the Frailty Index (FI-CGA) at baseline and at six-month follow-up.ResultsThe FI-CGA at follow-up (0.21 ± 0.08) was significantly lower than the FI-CGA at baseline (0.24 ± 0.08), suggesting an average reduction of 1.8 deficits. Sixty-one per cent of participants improved their FI-CGA and 38% improved CFS categories. Participants classified as vulnerable/frail at baseline were more responsive to the intervention compared to non-frail participants.ConclusionPilot data showed that it is feasible to assess frailty in primary care and that the CARES intervention might have a positive effect on frailty, a promising finding that requires further investigations. General practitioners who participate in the CARES model can now access their patients’ FI-CGA scores at point of service through their electronic medical records.

scholarly journals Factors affecting the mature use of electronic medical records by primary care physicians: a systematic review

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Rana Melissa Rahal ◽  
Jay Mercer ◽  
Craig Kuziemsky ◽  
Sanni Yaya
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Electronic Medical Records ◽  
User Satisfaction ◽  
Medical Records ◽  
Financial Incentives ◽  
Primary Care Physicians ◽  
Transition Planning ◽  
Narrative Synthesis ◽  
Factors Influencing

Abstract Background Despite a substantial increase in the adoption of electronic medical records (EMRs) in primary health care settings, the use of advanced EMR features is limited. Several studies have identified both barriers and facilitating factors that influence primary care physicians’ (PCPs) use of advanced EMR features and the maturation of their EMR use. The purpose of this study is to explore and identify the factors that impact PCPs’ mature use of EMRs. Methods A systematic review was conducted in accordance with the Cochrane Handbook. The MEDLINE, Embase, and PsycINFO electronic databases were searched from 1946 to June 13, 2019. Two independent reviewers screened the studies for eligibility; to be included, studies had to address factors influencing PCPs’ mature use of EMRs. A narrative synthesis was conducted to collate study findings and to report on patterns identified across studies. The quality of the studies was also appraised. Results Of the 1893 studies identified, 14 were included in this study. Reported factors that influenced PCPs’ mature use of EMRs fell into one of the following 5 categories: technology, people, organization, resources, and policy. Concerns about the EMR system’s functionality, lack of physician awareness of EMR functionality, limited physician availability to learn more about EMRs, the habitual use of successfully completing clinical tasks using only basic EMR features, business-oriented organizational objectives, lack of vendor training, limited resource availability, and lack of physician readiness were reported as barriers to PCPs’ mature use of EMRs. The motivation of physicians, user satisfaction, coaching and peer mentoring, EMR experience, gender, physician perception, transition planning for changes in roles and work processes, team-based care, adequate technical support and training, sharing resources, practices affiliated with an integrated delivery system, financial incentives, and policies to increase EMR use all had a favorable impact on PCPs’ use of advanced EMR features. Conclusions By using a narrative synthesis to synthesize the evidence, we identified interrelated factors influencing the mature use of EMRs by PCPs. The findings underline the need to provide adequate training and policies that facilitate the mature use of EMRs by PCPs. Trial registration: PROSPERO CRD42019137526.

scholarly journals Clinical Features Observed in General Practice Associated With the Subsequent Diagnosis of Progressive Supranuclear Palsy

2021 ◽  
Vol 12 ◽  
Author(s):  
Mary J. Kwasny ◽  
Denise M. Oleske ◽  
Jorge Zamudio ◽  
Robert Diegidio ◽  
Günter U. Höglinger
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Electronic Medical Records ◽  
Clinical Features ◽  
Random Forests ◽  
Medical Records ◽  
Primary Care Physicians ◽  
Case Control Study ◽  
Case Control ◽  
Control Study

Background: Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder that is difficult for primary care physicians to recognize due to its progressive nature and similarities to other neurologic disorders. This case-control study aimed to identify clinical features observed in general practice associated with a subsequent diagnosis of PSP.Methods: We analyzed a de-identified dataset of 152 PSP cases and 3,122 matched controls from electronic medical records of general practices in Germany. We used a random forests algorithm based on machine learning techniques to identify clinical features (medical conditions and treatments received) associated with pre-diagnostic PSP without using an a priori hypothesis. We then assessed the relative effects of the features with the highest importance scores and generated multivariate models using clustered logistic regression analyses to identify a subset of clinical features associated with subsequent PSP diagnosis.Results: Using the random forests approach, we identified 21 clinical features associated with pre-diagnostic PSP (odds ratio ≥2.0 in univariate analyses). From these, we constructed a multivariate model comprising 9 clinical features with ~90% likelihood of identifying a subsequent PSP diagnosis. These features included known PSP symptoms, common misdiagnoses, and 2 novel associations, diabetes mellitus and cerebrovascular disease, which are possible modifiable risk factors for PSP.Conclusion: In this case-control study using data from electronic medical records, we identified 9 clinical features, including 2 previously unknown factors, associated with the pre-diagnostic stage of PSP. These may be used to facilitate recognition of PSP and reduce time to referral by primary care physicians.

908-P: Predictive Model for Glycemic Level of People with Diabetes Mellitus Using Data Extracted from Electronic Medical Records in Primary Care

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 908-P
Author(s):  
SOSTENES MISTRO ◽  
THALITA V.O. AGUIAR ◽  
VANESSA V. CERQUEIRA ◽  
KELLE O. SILVA ◽  
JOSÉ A. LOUZADO ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Primary Care ◽  
Predictive Model ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Glycemic Level ◽  
Using Data
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