Bridging the gap between respiratory research and health literacy: an interactive web-based platform

Abstract

Many patients with respiratory disease lack an understanding of basic respiratory physiology and the changes occurring in their lungs due to disease. Describing how the lungs work using realistic 3D visualisation of lung structure and function will improve communication of complicated concepts, resulting in improved health literacy. We developed a web-based platform, using anatomically realistic 3D lung models, to create an interactive visualisation tool to improve health literacy for patients with respiratory disease. A small amount of non-identifying personal information including gender, age, weight, height and smoking history can be used to customise the visualisation to an individual user. 3D computer modelling was used to create a web-based application that helps people understand how their lungs work in health and disease. The web-based application includes pages describing and visualising how the lungs work and the changes that occur during asthma and damage that smoking may be doing to their lungs. The application is freely available and located at https://sites.bioeng.auckland.ac.nz/silo6/lung_new/. This application bridges the gap between computational modelling and patient education, giving a visually compelling view into the patient’s body that cannot be provided with any existing tools, hence providing a novel platform for enhancing patient–clinician interaction.

INTRODUCTION

Adequate health literacy is important in improving health outcomes by increasing patient engagement with clinicians and their pathway to improved health. ^1–3 Respiratory disease is widespread with hundreds of millions of people suffering worldwide. ⁴ However, many patients have minimal understanding of how their lungs work and the changes occurring during disease or the impact that smoking has on their lungs, although with more access to knowledge this is changing. ^5–7 Using methods that personalise health information—using simulation and visualisation techniques—has been shown to maximise the impact on the patient. ⁸ The use of these methods has also been shown to be beneficial in medical teaching and learning. ^{9 10} These types of simulation tools allow experiential learning with students using the simulation platform as a ‘virtual’ patient with which to test their decision-making. In managing respiratory conditions, patients and their families should benefit from increased understanding of their disease condition. For example, in patients with chronic obstructive pulmonary disease, adherence to medications and rehabilitation exercise has been shown to improve in patients who have a good understanding of their condition. ^{5 11}

We have previously developed a suite of advanced computational models that demonstrate the complex structure and physiology of the lungs, for example. ¹² These models allow the user to control several key mechanisms that are affected by smoking- and disease-related changes and estimate the impact on lung function. Visualisation using interactive 3D computer graphics is an essential part of communicating research outcomes from these computational models. We propose that with carefully chosen content, levels of detail and interactive controls, our modelling and visualisation techniques can improve the communication and transfer of knowledge to patients (and their families) and other non-experts in this area.

Development of this web-based application is motivated by a formative study ⁵ demonstrating that many patients with respiratory disease do not fully understand their condition or the reasons for particular therapies, such as exercise and secretion clearance. In this work, 30 patients with chronic respiratory disease were enrolled in a study to pilot the use of a mobile Pulmonary Rehabilitation programme: 23.3% of these patients were unsure of their diagnosis; 76.7% of participants said they would like to receive information and education about their condition. Key medical professionals were interviewed, and all participants acknowledged that patients’ understanding of their disease was generally poor. ⁵ Our approach aims to provide a novel interactive visual aid as a new paradigm for health literacy. The crux of this research is in visually communicating the science of how the lungs work and how this may be altered due to smoking damage and/or disease, using a minimal amount of user customisation to personalise the delivery of the information to the user.

METHODS

Computational models

A web-based platform incorporating anatomically realistic computational models of the lung including the lung surface and branching airway network (figure 1) was developed. The models are simulations (not animations) in that they are built using mathematical models that describe the physical geometry and processes occurring (ie, ventilation). These models have been published previously and are summarised in. ¹² Structure of the lung and airways is derived from medical images and can be derived for an individual. Deformation of the lung tissue is represented using a finite element continuum mechanics model. ¹³ Biophysical equations are used to simulate ventilation, and thus the visualised functions are not ‘animations’ but physically derived phenomena. ¹⁴ The solution of the airflow is illustrated using a colour spectrum within each airway branch to clearly indicate areas of high or low flow.

Figure 1.

Screenshots from https://sites.bioeng.auckland.ac.nz/silo6/lung_new showing the aspects of healthcare literacy delivery offered by our platform. (A) Information about breathing function, realistic lung shape. Motion of lungs synchronised by a traceable lung volume versus time curve. (B) Zoom feature that preserves details of the middle to very tiny airways rendered seamlessly. Demonstration of ‘asthma’ and ‘smoking’ impacts on the lungs are also included in the web platform. This figure was created by Kelly Burrowes.

Web-based platform

The web application uses WebGL, the web version of OpenGL to create an interactive view of the 3D lung models. WebGL uses model data to render the lung models and the resulting images are displayed on the screen of a device using the page content (including text, images and clickable buttons). The complexity and size of anatomic models is large (with a typical airway network model consisting of at least 60 000 airway branches), so it was necessary to simplify and compress the models in order for load times to be acceptable for all devices (computers and smartphones). Specifically, the model data are saved as JavaScript Object Notation (JSON) data files and compressed by limiting the number of decimals and by using the GZIP compression method. The web application was written in HTML, CSS, JS and WebGL.

This app has been designed for a broad target group including patients, health instructors (doctors, nurses, physiotherapists), students, researchers and for public health messaging related to respiratory health. Web app security issues are outside of the scope of the current work.

RESULTS

We have created a WebGL 3D visualisation showing surfaces of the lungs and the airway network (figure 1) with a simulated distribution of ventilation, found at the following link: https://sites.bioeng.auckland.ac.nz/silo6/lung_new/. The following novel features were implemented in this application:

• Realistic lung and airway geometry: The overall geometry gives a realistic impression of the lungs to the user. Texture has been added to the lung surface to mimic the imagery of the intact lung.

• Lung animation representing realistic breathing motion: This lung model ‘breathes’ using deformation simulated by our predictive models. A plot indicating the change in lung volume over time is also indicated alongside the full lung model.

• Zooming to include depth and airway size: The user can rotate or zoom in for an interactive experience. Zooming into the dense airway tree provides a fly-through-like view of the airway tree.

• Simulated ventilation in asthmatic and smoking lungs: The ventilation in each airway was pre-computed using our mathematical models. A flow spectrum was used to colourise these flow solutions.

The following pages are included in the app:

1. Breathing: This page includes a brief description of normal healthy gas exchange.

2. Asthma: This page illustrates potential changes in airflow in mild, moderate or severe asthma. These changes in ventilation are an illustration only and are predicted with airway constrictions imposed during the simulation to mimic airway narrowing in asthma. A button is also included to ‘Learn more about measuring lung function’, which leads to a page describing spirometric measurements of lung function.

3. Smoking: This page enables some personalisation of ‘my smoking lung’. The number of packs smoked per day can be selected and this alters the simulated ventilation in the model. Age, gender, height and baseline lung function (forced expiratory volume in 1 s, FEV₁) (if known) can also be added on this page to view a plot of the estimated change in lung function with increasing age.

DISCUSSION

We have created a new digital tool for health professionals and the public to receive information on respiratory (patho)physiology and the negative impacts of smoking. Our web-based platform provides educational material using compelling visualisation that aims to clarify the personal impact of disease and/or smoking on the lungs. This is a framework that links anatomically and physiologically detailed computational models to a publicly digestible visualisation, and its key strength is that it can be tailored to different pathologies or public health messaging by simulating relevant function rather than through some arbitrary rendering. While the current format of the platform will improve smoker education, we do not anticipate that provision of the web-based platform will cause behavioural change by itself; however, we do anticipate adoption of the new technology into mHealth applications as part of a more holistic programme of smoker engagement, at which point its effectiveness could be assessed.

Our application is freely available to the public, including to healthcare providers who could choose to use this as a communication tool for explaining cardiorespiratory damage to their patients. The application could be used as-is by mHealth specialists, to gain feedback on how best to target particular user groups. Our application could be run in a classroom setting as a preventative educational tool.

Personalised computational models with interactive 3D graphics and simulated lung function have not previously been used in this context. Several other interactive apps exist, which present simple representations of the lung, but these are largely aimed at anatomy education (ie, Living Lung—Lung Viewer). Our models are based on extensive research in computational physiology, giving them a sound—and internationally recognised—scientific footing. In the initial development phase, we tested the validity of this platform with community research events as part of the Medical Technologies Centre of Research Excellence (MedTech CoRE) consortium. This included exposure of the app to a range of healthcare professionals, including clinical staff, medical technology providers and innovators. Positive feedback related to the imagery and the potential impact of this was received.

The combination of visually compelling graphics, scientifically rigorous predictive models of lung function and interaction that allows the user to ‘customise’ the models to their personal data included in this web-based platform will improve public engagement with education on smoking cessation and cardio-respiratory health.