Saturday February 29, 2020

Medical Selfies can Improve Relationship between Patient and Doctor: Study

For the study published in the Journal of Medical Internet Research, researchers first interviewed 30 patients, clinicians and caregivers

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For the study published in the Journal of Medical Internet Research, researchers first interviewed 30 patients, clinicians and caregivers. Pixabay

Taking medical ‘selfies’ and sharing them with a doctor empowers and reassures patients and can improve their relationship with the medical practitioner, a research has found.

“Healthcare consumers feel this data is valuable, it helps them have a sense of autonomy in their care, improves their view of the service they are being provided and it enhances the relationship between doctor and patient because there is a sense of mutual respect and communication,” said Kara Burns from the Queensland University of Technology in Australia.

To gauge experiences with and attitudes to consumer-generated health photographs, the researchers conducted a two-part study. For the study published in the Journal of Medical Internet Research, researchers first interviewed 30 patients, clinicians and caregivers.

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Women taking selfie (Representational Image). VOA

In the second part, parents were asked to take photos of their children’s surgical wounds at the hospital and send it to the surgeon so that he could review healing.

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Parents said it improved their confidence in and satisfaction with the medical service and taking the photos was a useful reminder for them to check how the surgical sites were healing. The findings from the photographic trial supported conclusions drawn from the interview study.

“The parents who took part in the trial said they felt reassured and that the service was going above and beyond. They said normally the door feels shut when you leave a hospital and providing the photos was a way to stay connected and contact the surgeon afterwards,” Burns said. (IANS)

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New Wearable Sensor Can Detect Critical Changes in Heart Failure Patients

Wearable sensor to predict worsening heart failure

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Wearable sensor heart
A new wearable sensor could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs. Pixabay

A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study. This is the latest health news.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

“This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong,” says the study’s lead author Josef Stehlik from University of Utah in the US.

“Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure,” Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations. “This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status,” Stehlik said.

Wearable sensor heart
The sensor can help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life. Pixabay

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months. The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient’s heart failure was getting worse.

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Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time. On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said. (IANS)