urban health patient portal

How to access the MyHealth patient portal?

Patient Portal - Urban Health Patient Portal Our Patient Portal is designed for our established patients. Through our patient portal you may securely access your personal health records. You may be able to view and manage changes to your …

What is a patient portal?

We would like to show you a description here but the site won’t allow us.

What is urban health care?

This health center is a Health Center Program grantee under 42 U.S.C. 254b, and a deemed Public Health Service employee under 42 U.S.C 233 (g) –(n)“This health center receives HHS funding and has Federal Public Health Service (PHS) deemed status with respect to certain health or health-related claims, including medical malpractice claims ...

What is a health record portal?

Background: As the use of electronic medical records (EMRs) spreads, health-care organizations are increasingly offering patients online access to their medical records. Studies evaluating patient attitudes towards viewing elements of their records through secure, electronic patient portals have generally not included medically underserved patients or those with HIV/AIDS.

What is the importance of health information technology?

1 Studies have indicated that the use of electronic health records (EHRs) may lead to improvements in operational efficiency and patient outcomes. 2, 3 EHR systems are also expanding to include online portals that allow patients to perform actions, such as scheduling office visits and exchanging electronic messages with health care providers. Certain patient populations are less likely to use electronic systems and this ‘digital divide’ could bar them from realizing the benefits that electronic systems could provide. 4, 5 Research shows that patients are less likely to sign up for patient portals due to racial disparities, 6 and that older people and people with low socioeconomic status are less likely to use the Internet7 and Web-based programs. 5, 8, 9

How does electronic messaging improve patient engagement?

Studies indicate that a ‘digital divide’ may exist, where certain patient populations may be using electronic messaging less frequently. This study aims to determine which patient characteristics are associated with different levels of usage of an electronic patient-provider messaging system in a diverse urban population.

What are the factors associated with higher levels of messaging usage?

The largest factor associated with higher levels of messaging usage was the number of messages received by the patient. Patients who received more messages had a much higher messaging rate and lower odds of sending zero messages. The effects of age on messaging usage were not straightforward. As compared with Millennials, older generational age was seen as a moderate predictor of sending more messages, and the expected number of messages sent increased as the age grouping increased. However, compared to Millennials, the youngest generation, Generation X and Baby Boomers had increased odds of sending zero messages while the oldest generations did not. Our study found nuanced electronic messaging usage patterns for patients based on health status. Patients with more diagnoses and more office visits tended to send more messages, but they also had higher odds of sending zero messages. We also observed that factors that are generally associated with social disparities and the ‘digital divide’ persisted in this population after controlling for many covariates. Patients who were male, of nonwhite race, who had a non-English language preference, who used public insurance or were uninsured and who lived in ZIP codes with higher levels of poverty and lower levels of high school graduation tended to have decreased electronic messaging usage.

What are the associations between sending and receiving messages?

First, the cross-sectional nature of our data does not consider whether the patient or the provider sent the first message in a messaging chain, therefore we cannot determine whether the patients or the providers initiated contact. Second, we counted all messages exchanged with the patient, which would include communications such as automated reminders and billing inquiries. It is therefore possible that a bulk of a patient’s messaging did not involve their provider. A third limitation is in the interpretation of the excess zero count modelled in the ZINB model. While it is probable that a lack of messaging could be due to certain structural factors that would preclude the sending of electronic messages, this study is unable to identify what those factors are. Fourth, this study also had a large amount of missing data, leading to an exclusion of 26.54% of MyChartusing patients from the final regression analyses. A majority of these exclusions were due to missing ethnicity and race data. It is possible that the excluded participants may have different characteristics from the sample that was studied. Fifth, this study collected diagnoses for a limited number of chronic conditions whereas a previous study used a comorbidity index that considered both ICD-9 codes and demographic information, 16 which could account for the differences seen when considering the patient’s health status. Finally, this study was performed in an urban environment and may not be generalisable to other health care settings.