scholarly journals Sharing electronic health records with patients: Who is using the Care Information Exchange portal? A cross-sectional study. (Preprint)

10.2196/23481 ◽  
2020 ◽  
Author(s):  
Ana Luisa Neves ◽  
Katelyn R Smalley ◽  
Lisa Freise ◽  
Paul Harrison ◽  
Ara Darzi ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Information Exchange ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Health Records ◽  
Care Information ◽  
Electronic Health

scholarly journals Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population

BMJ Open ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. e029594 ◽  
Author(s):  
Concepción Violán ◽  
Quintí Foguet-Boreu ◽  
Sergio Fernández-Bertolín ◽  
Marina Guisado-Clavero ◽  
Margarita Cabrera-Bean ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Electronic Health Records ◽  
Cross Sectional Study ◽  
Secondary Outcome ◽  
Sectional Study ◽  
Cross Sectional ◽  
Health Records ◽  
Soft Clustering ◽  
Fuzzy C Means ◽  
Electronic Health

ObjectivesThe aim of this study was to identify, with soft clustering methods, multimorbidity patterns in the electronic health records of a population ≥65 years, and to analyse such patterns in accordance with the different prevalence cut-off points applied. Fuzzy cluster analysis allows individuals to be linked simultaneously to multiple clusters and is more consistent with clinical experience than other approaches frequently found in the literature.DesignA cross-sectional study was conducted based on data from electronic health records.Setting284 primary healthcare centres in Catalonia, Spain (2012).Participants916 619 eligible individuals were included (women: 57.7%).Primary and secondary outcome measuresWe extracted data on demographics, International Classification of Diseases version 10 chronic diagnoses, prescribed drugs and socioeconomic status for patients aged ≥65. Following principal component analysis of categorical and continuous variables for dimensionality reduction, machine learning techniques were applied for the identification of disease clusters in a fuzzy c-means analysis. Sensitivity analyses, with different prevalence cut-off points for chronic diseases, were also conducted. Solutions were evaluated from clinical consistency and significance criteria.ResultsMultimorbidity was present in 93.1%. Eight clusters were identified with a varying number of disease values: nervous and digestive; respiratory, circulatory and nervous; circulatory and digestive; mental, nervous and digestive, female dominant; mental, digestive and blood, female oldest-old dominant; nervous, musculoskeletal and circulatory, female dominant; genitourinary, mental and musculoskeletal, male dominant; and non-specified, youngest-old dominant. Nuclear diseases were identified for each cluster independently of the prevalence cut-off point considered.ConclusionsMultimorbidity patterns were obtained using fuzzy c-means cluster analysis. They are clinically meaningful clusters which support the development of tailored approaches to multimorbidity management and further research.

scholarly journals Primary Care Medication Safety Surveillance with Integrated Primary and Secondary Care Electronic Health Records: A Cross-Sectional Study

Drug Safety ◽  
2015 ◽  
Vol 38 (7) ◽  
pp. 671-682 ◽  
Author(s):  
Artur Akbarov ◽  
Evangelos Kontopantelis ◽  
Matthew Sperrin ◽  
Susan J. Stocks ◽  
Richard Williams ◽  
...  
Keyword(s):  
Primary Care ◽  
Electronic Health Records ◽  
Secondary Care ◽  
Medication Safety ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Health Records ◽  
Safety Surveillance ◽  
Electronic Health

scholarly journals Health of Spanish centenarians: a cross-sectional study based on electronic health records

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Antonio Gimeno-Miguel ◽  
Mercedes Clerencia-Sierra ◽  
Ignatios Ioakeim ◽  
Beatriz Poblador-Plou ◽  
Mercedes Aza-Pascual-Salcedo ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Health Records ◽  
Electronic Health

scholarly journals Physician Specialty and Variations in Adoption of Electronic Health Records

2013 ◽  
Vol 04 (02) ◽  
pp. 225-240 ◽  
Author(s):  
S. Banerjee ◽  
R. Kaushal ◽  
L.M. Kern ◽  
Z. M. Grinspan
Keyword(s):  
Electronic Health Records ◽  
Reference Group ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Physician Specialty ◽  
Cross Sectional ◽  
Health Records ◽  
Ehr Adoption ◽  
Electronic Health ◽  
Over Time

SummaryObjective: Efforts to promote adoption of electronic health records (EHRs) have focused on primary care physicians, who are now expected to exchange data electronically with other providers, including specialists. However, the variation of EHR adoption among specialists is underexplored.Methods: We conducted a retrospective cross-sectional study to determine the association between physician specialty and the prevalence of EHR adoption, and a retrospective serial cross-sectional study to determine the association of physician specialty and the rate of EHR adoption over time. We used the 2005–2009 National Ambulatory Medical Care Survey. We considered fourteen specialties, and four definitions of EHR adoption (any EHR, basic EHR, full EHR, and a novel definition of EHR sophistication). We used multivariable logistic regression, and adjusted for several covariates (geography, practice characteristics, revenue characteristics, physician degree).Results: Physician specialty was significantly associated with EHR adoption, regardless of the EHR definition, after adjusting for covariates. Psychiatrists, dermatologists, pediatricians, ophthalmologists, and general surgeons were significantly less likely to adopt EHRs, compared to the reference group of family medicine / general practitioners. After adjustment for covariates, these specialties were 44 – 94% less likely to adopt EHRs than the reference group. EHR adoption increased in all specialties, by approximately 40% per year. The rate of EHR adoption over time did not significantly vary by specialty.Conclusions: Although EHR adoption is increasing in all specialties, adoption varies widely by specialty. In order to insure each individual’s network of providers can electronically share data, widespread adoption of EHRs is needed across all specialties.Citation: Grinspan ZM, Banerjee S, Kaushal R, Kern LM. Physician specialty and variations in adoption of electronic health records. Appl Clin Inf 2013; 4: 225–240http://dx.doi.org/10.4338/ACI-2013-02-RA-0015

Sharing electronic health records with patients - Who is using the Care Information Exchange portal? A cross-sectional study. (Preprint)

2020 ◽  
Author(s):  
Ana Luisa Neves ◽  
Katelyn R Smalley ◽  
Lisa Freise ◽  
Paul Harrison ◽  
Ara Darzi ◽  
...  
Keyword(s):  
Health Status ◽  
Digital Literacy ◽  
Educational Level ◽  
Information Exchange ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Patient Portals ◽  
Cross Sectional ◽  
Health Records ◽  
Care Information

BACKGROUND Sharing electronic health records with patients has been shown to improve patient safety and quality of care, and patient portals represent a powerful and convenient tool to enhance patient access to their own healthcare data. However, adoption rates vary widely across countries and, within countries, across regions and health systems. A better understanding of the characteristics of users and non-users is critical to understand which groups remain underserved or excluded from using such tools. OBJECTIVE To identify the determinants of usage of the Care Information Exchange (CIE), a shared patient portal program in the United Kingdom. METHODS A cross-sectional study was conducted, using an online questionnaire. Individual-level data from patients registered in the CIE portal were collected, including age, gender, ethnicity, educational level, health status, postcode, and digital literacy (using the eHEALS tool). Registered individuals were defined as having an account created in the portal, independent of their actual use of the platform, and users were defined as having ever used the portal. Multivariate logistic regression was used to model the probability of being a user. Statistical analysis was performed in R, and Tableau ® was used to create maps of the proportion of CIE users by postcode area. RESULTS A total of 1,083 subjects replied to the survey (+186% of the estimated minimum target sample). The proportion of users was 61.6% (n=667), and within these, the majority (57.7%, n=385) used the portal at least once a month. To characterise the users and non-users of the system, we performed a sub-analysis of the sample, including only participants that have provided at least information regarding gender and age category. The sub-analysis included 650 individuals (59.8% women, 84.8% over 40 years). The majority of the subjects were white (76.6%, n=498), resident in London (64.7%, n=651), and lived in North West London (55.9%, n=363). Individuals with a higher educational degree (undergraduate/professional or postgraduate/higher) had higher odds of being a portal user (adjusted OR = 1.58 (95%CI [1.04 - 2.39]), and 2.38 (95%CI [1.42 - 4.02], respectively), compared to those with a secondary degree or below. Higher digital literacy scores (<30) were also associated with higher odds of being a user (adjusted OR = 2.96 (95%CI [2.02 - 4.35]). Those with a good overall health status had lower odds of being a user (adjusted OR = 0.58 (95%CI [0.37 - 0.91]). CONCLUSIONS This work adds to the growing body of evidence highlighting the importance of educational aspects (educational level and digital literacy) in the adoption of patient portals. It is critical that further research not only describes, but also systematically addresses these inequalities through patient-centred interventions aiming to reduce the digital divide. Healthcare providers and policymakers must partner in investing and delivering strategic programs that improve access to technology and digital literacy, in an effort to improve digital inclusion and reduce inequities in delivery of care. CLINICALTRIAL Not applicable.

scholarly journals QT interval and antidepressant use: a cross sectional study of electronic health records

BMJ ◽  
2013 ◽  
Vol 346 (jan29 3) ◽  
pp. f288-f288 ◽  
Author(s):  
V. M. Castro ◽  
C. C. Clements ◽  
S. N. Murphy ◽  
V. S. Gainer ◽  
M. Fava ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Qt Interval ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Health Records ◽  
Antidepressant Use ◽  
Electronic Health
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