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Digital health technologies are transforming the healthcare landscape, offering opportunities to enhance patient outcomes whilst promoting environmental sustainability. This article examines how innovative digital health initiatives can be leveraged to improve care delivery and access, prevent medical errors, empower patients for self-care, enable data-driven personalised treatments, and optimise clinical interactions - all while reducing the carbon footprint of the healthcare system.

“We are the first generation to feel the impact of climate change and the last generation that can do something about it” - Barak Obama, the ex-US president and one of the signatories of the Paris Climate Agreement.    

 

 Digital Health Initiatives (DHIs) can have a sustainable impact on health and climate. While the Lancet Countdown ranks the healthcare industry as the 5th largest contributor to planetary pollution, the climate change itself is having an impact on healthcare—creating a vicious loop flowing against the desired sustainable developmental goals (SDGs) in healthcare. Many of my colleagues at on the MSc in Global Healthcare Leadership course agree. A profound perspective in systems driving climate change and healthcare shows a considerable overlap of issues which need to be achieved for SDGs in healthcare and climate change.

 

Figure 1: Climate change and human health and wellbeing - risk and responses

 Figure 1

Source: Climate Change Report 2022 (published by the Intergovernmental Panel on Climate Change)

While learning systems in 2022 class of MGHL (MSc in Global Healthcare Leadership), I believe there is substantial evidence to support healthcare technologies, such as telehealth, artificial intelligence (AI), the Internet of Things (IoT), and electronic medical/health records (EMR/EHR), as potential solutions to achieve these SDGs. Many of these technologies have had a measurable impact on carbon footprint by reducing the need to travel, transforming the need to document, and optimising the need to interact. There is substantial evidence to support the argument. For instance, Bartlett et al. (2022) assessed that the overall carbon footprint for the mixed consultation clinic was reduced from 72.1 to 55.34 kg CO2e due to reduced travel. Similarly, an hour-long virtual consultation created 0.994 kgCO2e per consultation compared to 4.824 kgCO2e for face-to-face consultations. Not just climate, there is evidence presented demonstrating how these technologies help reduce travel and thereby, improve outcomes leading to significant savings in life and resources. Kelly et al were able to demonstrate that people living far away from healthcare facilities have had poor health outcomes and needed to travel more to seek care. This implies an increase in the carbon footprint of care. The key question is whether these developing technologies in healthcare achieve better patient outcomes while reducing the carbon footprint of care delivery.

 

In the healthcare ecosystem, three major interventions have emerged since COVID-19:

1. Optimise patient journey and interactions to achieve sustainable outcomes

Over the last decade, many providers and regulators have invested substantially to develop an in-depth understanding of patient journeys across different therapeutic areas to find opportunities to intervene and reduce patient burden. Many of these interventions have largely focused on the following:

A. Telehealth/Video Consultation: Virtual consultations—telehealth or video consultation—became popular, especially during the COVID and post-COVID era. The market is estimated to reach $50.9bn by 2032 from the current $7.1bn growing at a CAGR of 22.4%. However, these market estimates do not account for the impact on outcomes and do not assure sustainability. Most of the telehealth ecosystems are generic and do not account for demographic and therapeutic variance. Multiple publications suggest a positive impact of teleconsultation; however, researchers also suggest that it is still evolving and there is significantly more to be done. Many of my colleagues agree.

A review of longitudinal data, especially for chronic disorders (such as diabetes), suggests that making patient and physician interaction virtual is not enough. Muppavarapu K., et al, 2022, established a no-show rate of 28% for new patients and a drop-out rate of 13% for returning patients for teleconsultations. Long-term patient engagement and compliance remain a key challenge across different platforms globally.

To achieve SDGs, virtual consultation should evolve as an intervention to target patient behaviour and patient engagement.

 

B. EMR / EHR Implementation: Globally EMR / EHR have become a standard for healthcare providers. While there is a considerable variation in the implementation of EMR / EHR across systems, however, most of the providers are willing to replace their traditional patient documentation methods with digital EMR / EHRs. This reduces paper wastage substantially. According to Mediabase, the implementation of EHRs for 8.7 million patients resulted in saving 1,044 tons of paper medical records and curbing 7,000 tons of greenhouse gases through online prescription orders.

 

However, a 2023 pre-pandemic analysis of the EHR adoption rate (Jiang J. et al) suggests a considerable variation in the deployment of basic vs comprehensive EHR, especially in developed markets (such as the US). Further, in regions with high OOP (out-of-pocket) and low-tech adoption, such as developing markets of Asia, Africa and Latam, the adoption rate of EHR is considerably lower.

 

While low and variable adoption of comprehensive systems directly influences SDGs in healthcare, however, their limited use also impacts patient outcomes. Many of the providers use different, unintegrated EMR / EHR solutions which limits their interoperability and use of clinical analytics to enable modern solutions, such as predictive analytics, machine learning and gene.

 

Both telehealth or virtual consultation and EMR/EHR have the potential for multifold impact on not just patients but all other stakeholders as well. For instance, during one of our deep-dives at MGHL, we discussed how longitudinal patient journeys can develop a comprehensive understanding of patient challenges across healthcare systems and develop personalized, predictive, and comprehensive interventions for better outcomes (Figure 2).

 

Figure 2: Integrating patient data to develop interventions beyond EMR/EHR and Telehealth

Figure 2

 

Through its data-backed and time-proven patient engagement loop, the company was able to drive an increase of 8%-10% in patient engagement rate across hybrid channels (in-person and virtual) and reported a considerable decline of HbA1c level in engaged diabetic patients in one of the largest hospital chains in Middle East. While the compliance rate to prescribed treatment and diagnostics improved considerably, patient’s need to travel for consultation and diagnostics was reduced by well over 30%--thereby, having a considerable environmental impact.

 

2. Reduce patient harm and empowering patient to take control of their health

Decision support tools, such as risk calculators, treatment decision algorithms, and symptom checkers, have been considered as means to standardise care and optimise patient journeys. Further, when these tools are built on RWE and clinical analytics, they offer a chance to reduce human errors, such as misdiagnosis, over/under dosing, etc.—thereby, reducing the threat of hospitalisation and death. Olson C.H. et al, 2014 demonstrated that an automated algorithm can predict the risk of hospital readmission among elderly patients and can help HCPs make informed choices about these patients, thereby, reducing the need for re-hospitalisation and associated carbon footprint. Similarly, Campbell. I.M. et al 2023, demonstrated that CDS (clinical decision support) with a comprehensive in-EHR patient tracking system could improve genetic testing follow-up, thereby promoting preventive care and interventions and reducing the burden on the system and environment.

 

Additionally, giving patients control of their health through personalised content and POCD (point-of-care devices/diagnostics), such as wearables, can help reduce patient harm, promote early engagement, reduce the risk of hospitalisation and thereby, reduce the carbon footprint of health. Offer Amer et al 2016 demonstrated a significant reduction in heart failure (HF) re-hospitalisation in acute decompensated HF patients who were offered ReDS (remote dielectric sensing)-guided fluid management. Similarly, in the VEST trial, Olgin J. et al 2019 achieved a significant reduction in total and arrhythmic mortality through a wearable cardioverter defibrillator (WCD) provided compliance with the device was maintained. Further, day-to-day wearables (such as smartwatches and trackers) have demonstrated a significant reduction in risk to patients and helped in the collection of critical data for further therapeutic advancement, especially in precision cardiology. Steinhubl, S. R. et al. (2018) demonstrated a significantly higher rate of identification of AF occurrence in patients susceptible to AF with the help of a self-applied ECG patch compared to patients with delayed ECG monitoring.

There is substantial evidence available to conclude that remote monitoring and wearable devices can give patients better control of their health and thereby, reduce the risk of hospitalisation and risk of death. While the impact of either is yet to be documented and linked to the impact on climate, however, these solution developers need to measure the climate impact of the outcomes achieved.

 

 3. Optimising Pharma <> Physician engagement

As COVID-19 dawned globally, pharma and physician engagement dropped significantly. While there was a need to advance dialogue between pharma and providers to optimise treatment and access during the turbulent time, however, due to increased risk and restrictions, many of the companies partnered with solution providers to create remote interaction solutions, such as e-detailing (including voice and video detailing) and virtual reps.

 

In the post-COVID era too, the utility of these tools has been significant. Continuing with such tools has not only optimised pharma <> physician interaction and increased rep productivity but also has had a significant impact on climate. In a health-related QoL among medical representatives study, Kotlo et al. 2015 highlighted that on average a rep travelled about 15Kms+ to complete his allocated sales call. According to the UK Government (Figure 3), an average petrol car emits 170 gms CO2eq per kilometre, which implies that medical representatives, to complete their daily calls, end up emitting 2.5 Kg of CO2eq (assuming sales reps are travelling with an average petroleum-based car).

 

Figure 3: The carbon footprint of travel per kilometer (2022), Our World In Data

Figure 3

 

 

There are about 156,626 medical sales reps in the US. If a rep is emitting about 2.5 Kg of CO2eq daily to make his sales call, that implies that the US alone emits about 143K metric tons of CO2eq in a year just for medical sales calls.

 

However, this carbon footprint can be reduced substantially. There are companies which have deployed rep productivity tools, such as virtual sales force, to optimise sales efforts and improve productivity for pharma companies. On average, by integrating these solutions with the traditional field force sales model, the company has been able to reduce travel needs by 30%-35% and in some cases replace the need for on-ground field force completely, thereby making a substantial impact on CO2eq emitted to complete the sales call.

 

While the three big trends discussed above indicate a substantial impact of upcoming technologies on healthcare and climate, however, before evaluating the impact of health tech or DHIs on climate and sustainability, it is also important to account for the sustainability impact generated by the development of tech infrastructure through standardised methodology. Unfortunately, there are limited standardised tools available to measure the impact of both, the lifecycle of tech deployment in healthcare and the outcomes achieved. Frameworks, such as Life-cycle assessment (LCA), Environmentally Extended Input-Output Analysis (EEIOA) and Comprehensive Environment Assessment (CEA) are being used, however, each has certain limitations while accounting net impact of health-tech.

 

Currently, there is limited understanding of the direct and indirect impact of different health-tech interventions on the climate, however, as sustainable accounting becomes mandatory, the healthcare and life sciences industry will need to establish green accounting algorithms, which can demonstrate the impact of technology on healthcare and climate simultaneously. 

 

About the author:

Anuj Gupta is a current student on MSc in Global Healthcare Leadership course, jointly run with Said Business School. He is an experienced healthcare business advisor, working with global healthcare companies to help them achieve sustainable and better outcomes through innovative and digital solutions.

Opinions expressed are those of the author/s and not of the University of Oxford. Readers' comments will be moderated - see our guidelines for further information.

 

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