Astronaut loading animation Circular loading bar

Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(5)

Customer Journey(12)

Design(36)

Solar Industry(6)

User Experience(56)

Edtech(10)

Events(34)

HR Tech(2)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(17)

Testing(9)

Android(47)

Backend(30)

Dev Ops(7)

Enterprise Solution(27)

Technology Modernization(2)

Frontend(28)

iOS(43)

Javascript(15)

AI in Insurance(35)

Insurtech(63)

Product Innovation(49)

Solutions(19)

E-health(10)

HealthTech(22)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(132)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(17)

FinTech(50)

Banking(7)

Intelligent Automation(26)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

How Hospitals Can Deliver Predictive Health Solutions Over Mobile Apps?

3 minutes read

Preventative medicine is all set to make a comeback as hospitals now have the tools that are required to collect, analyze and deliver solutions that map the trajectories of their patient’s health in a sustainable fashion. Telemedicine, as the practice is commonly known was hamstrung by the sheer bulk of the requisite instruments and the lack of interoperability within them. 

Telemedicine has now touched a new frontier as mobile applications are proving to be increasingly useful in medicine, especially in pre-emptive and predictive health solutions. As the next phase of telemedicine dawns on us, here are five ways in which hospitals can start delivering predictive health solutions to their customers via mobile telephony:

#1 Replace in-person visits with mobile engagement

In the first half of the last decade alone, both physicians and patients began to conduct more and more of their activities on mobile applications. The increasing acceptance of patients liaising with their doctors through mobile applications means that doctors can now mediate most in-person visits via mobile applications. This not only translates to greater convenience for both parties but also facilitates a robust data collection platform that is crucial to delivering predictive health solutions to patients. These have been shown to improve the rate of electronic prescribing and increase the effectiveness of healthcare professionals.

#2 Leverage analytics

Predictive analytics is proving to be a big draw for hospitals as the average patient now has a digital footprint that provides ample information regarding the patient’s well-being if processed in the right fashion. As of 2015, the average hospital was expected to be generating almost 665 terabytes of data, a goldmine that can finally be leveraged with the use of advanced analytics:

Hospitals seeking to augment their existing practices with predictive health solutions need to unify three key technologies which they have at their disposal: smartphones, predictive analytics, and the wealth of data that they generate on a daily basis. They can also help reduce the cost of re-admissions, as demonstrated in the case of Dr Patricia Newland, who had used it to prevent one of her patients from readmission.

#3 Implement advanced Tele-ICUs

Predictive algorithms, when deployed in tele-ICU settings can give doctors enough insight into patient vitals and alert doctors to signs of impending patient deterioration so they can act on time and save patients from slipping further. In fact, these algorithms can even come in handy in the hospice, as one hospital had demonstrated by implementing an automated early warning scoring system that helped caregivers administer appropriate care and respond early.

#4 Integrate wearables

There are several anecdotes from around the world as to how the Apple Watch’s state-of-the-art ECG feature helped save lives by alerting the wearer to slight anomalies in their homeostatic process. This can further be extended to patients with chronic diseases who can be equipped with wearable biosensors that collect data at regular intervals. When coupled with smartphones, sensors can be a potent combination for remote patient monitoring as it will allow doctors to set up systems that alert patients in case they display early signs of a severe ailment. This would enable hospitals to unclog their wards and make way for more severe cases that might require in-person care for the patients.

#5 Democratize Clinical Surveillance systems

Hospitals can also place comprehensive clinical surveillance systems at home for at-risk patients in their homes. This could effectively reduce 40% of all hospital admissions by bringing healthcare to the homes of those who need it the most, as demonstrated by a study by Partners Healthcare of Boston.

Staying Ahead

For young hospital chains that still seek to differentiate themselves from older chains, digitizing their operations and making full use of their data and the commoditization of the smartphone can yield staggering results. Over time, they can even create personalized models for individual patients and deliver healthcare with greater success, the likes of which will be received with great fanfare from both customers and non-customers alike.

Cancel

Knowledge thats worth delivered in your inbox

10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot