ABSTRACT
Background: Healthcare delivery now mandates shorter visits despite the need for more data entry, under-mining patient-provider interaction. Furthermore, enhancing access to the outcomes of prior tests and imaging conducted on the patient, along with accurately documenting medication history, will significantly elevate the quality of healthcare service delivery. Objective: To enhance the efficiency of clinic visits, we have devised a patient-provider portal that systematically gathers symptom and clinical data from patients through a computer algorithm known as Automated Assessment of Cardiovascular Examination (AACE). We intended to assess the quality of computer-generated Electronic Health Records (EHRs) with those documented by physicians. Methods: We conducted a cross-sectional study employing a paired-sample design, focusing on individuals seeking assessment for active cardiovascular symptoms at outpatient adult cardiovascular clinics. Participants initially completed the AACE, and subsequently, in the first protocol, patients were subjected to routine care without providing the AACE forms to examining physicians. In the second protocol, the AACE form was presented to the physician before the examination, and participants were subjected to routine care. We assessed the impact of AACE forms generated through computerized history-taking method on the examination, considering various clinical outcomes and satisfaction surveys. Results: We included non-randomized eligible patients who visited seven general cardiology outpatient clinics between September 18, 2023, and October 27, 2023. These clinics were staffed by the same physicians who were unaware of the content and details of the study. A total of 762 patients (394 patients in protocol 1 and 368 patients in protocol 2) were included in the study. The mean overall impression score for computer-generated EHRs was higher versus physician EHRs (4.2 vs. 2.6; p < .001). Our study demonstrated that EHRs created by physicians' exhibit inaccuracies or deficiencies in various pieces of information. In the second protocol, in which the AACE form was presented to the physician before the examination, it was determined that the examination time was shorter, the number of tests requested, and the number of new drugs prescribed were less. Conclusions: We observed that the patient-provider portal, systematically collecting symptom and clinical data from patients through a computer algorithm known as AACE, yielded records that were of higher quality, more comprehensive, better organized, and more relevant compared to those documented by physicians.
ABSTRACT
AIM: The increasing global popularity of smartphone usage has increased concerns about the negative effects of smartphone addiction, such as lack of sleep, sedentary life, bad eating habits, anxiety, stress, and depression, especially among the young population. These problems caused by smartphone addiction are also well-known risk factors for atherosclerosis. However, according to our observation, there is no research in the literature that directly shows the relationship between smartphone addiction and subclinical atherosclerosis. In this study, carotid intima-media thickness, an important surrogate marker in demonstrating subclinical atherosclerosis, was used to examine the relationship between smartphone addiction and subclinical atherosclerosis. MATERIALS AND METHOD: This cross-sectional study was conducted on 96 high school students aged between 13 and 22 years. A smartphone addiction questionnaire consisting of 33 questions was applied to measure smartphone addiction. Along with the socio-demographic characteristics of the patients, factors such as eating habits, sleep patterns, and activity levels were also questioned. The mean carotid intima-media thickness was measured by an experienced sonographer according to the published and accepted methods. RESULTS: When we set the threshold for smartphone addiction at over 66 points, we discovered that the group with smartphone addiction had considerably thicker carotid intima-media (0.68 ± 0.2 versus 0.45 ± 0.1; p < 0.001). In addition, logistics regression analysis had shown that smartphone addiction level independently affects the carotid intima-media thickness (odds ratio:1.111; %95 GA:1.057-1.168, p < 0.001). CONCLUSION: Smartphone addiction may help prediction of subclinical atherosclerosis via carotid intima-media thickness among teenagers.
