Every year, G2 publishes its Buyer Behavior Report, based on an annual survey of more than 1,900 B2B software buyers, to understand their plans, behaviors, and attitudes. Although a respondent’s industry is collected, the questions themselves do not delve into the specific nuances of different industries.
The 2023 Buyer Behavior Report found that healthcare respondents consider AI functionality and a one-year ROI timeline to be critical factors in their software buying process.
Based on those data points, G2 conducted a specialized survey to target healthcare technology buyers and understand how they are quantifying ROI, where they see AI having the most impact in the industry, and what current AI strategy they have in place.
Opinions differ on its true potential, but AI is here to stay. The healthcare sector has already seen incredible use cases of this technology, such as earlier disease detection, transforming patient engagement, and administrative automation.
Our survey data shows a strong acceptance of AI in general but different applications and guiding frameworks among healthcare organizations. Regardless of how they invest in technology, organizations overwhelmingly see the benefit of AI both for their individual needs and the healthcare sector at large.
Let’s dive into a few major takeaways from the G2 healthcare tech buyer survey results. Stay tuned for future installments that dig into other data points not covered in this article.
G2 surveyed 208 healthcare B2B software buyers to understand what considerations inform their buying process, how their organization measures ROI, and their biggest hopes and concerns regarding AI within healthcare. Of these respondents, 44% work for health systems, 38% work for hospitals, and 18% work for private practices.
Buyer priorities and measuring healthcare software ROI
AI or not, 80% of respondents plan to increase their technology budget within the next 12 months. Product innovations continue to emerge in the market, vying for the attention of healthcare organizations. Buyers seek solutions with the latest AI and machine learning capabilities, and 82% believe that ROI can be achieved faster if a product utilizes this technology.
As for how healthcare organizations quantify ROI, the chart below highlights the five most popular answers from respondents.
According to respondents, improved staff productivity is the most common metric used to measure software ROI.
While 90% said they have sufficient technological resources to perform their jobs, a recent report from the CDC indicates nearly half of healthcare workers often feel burned out. Administrative workload often overburdens healthcare providers, detracting from time spent providing quality clinical care to patients. Products with advanced machine learning and AI capabilities can alleviate this growing problem, automating tedious workflows that bog healthcare workers down.
Metrics around patient outcomes and satisfaction also factor greatly into measuring ROI. While it feels dystopian to frame patients as consumers, patient experience plays a vital role in health outcomes.
Patients want a seamless, efficient experience when seeking care. Clunky mobile apps, convoluted visit summaries, and concerningly short visits with providers all contribute negatively to this experience. These factors ultimately play into trust, which is more important than ever as buyers want to know their data is in safe hands amid AI criticisms and growing cybersecurity breaches.
Speaking of data, when respondents were asked about software deployment, 61% said they typically deploy on the cloud.
Cloud adoption continues to gain traction within the healthcare industry as it improves collaborative care, data interoperability, and overall patient experience. However, cloud migration comes with its own costs and risks, and some organizations prefer to stick with on-premises deployment. Of the 39% of respondents who typically deploy on-premises, nearly half cited security and compliance concerns related to cloud deployment.
Healthcare data breaches are extremely costly for both organizations and the patients whose data are compromised. While cloud computing touts improved privacy and security, buyers must still take an active role in protecting their data. Key responsibilities include maintaining compliant workflows, auditing system configurations regularly, and promoting good data hygiene practices among employees.
In addition to security concerns, 35% of respondents who deploy on-premises cited a lack of cloud IT strategy and dedicated staff capacity to support cloud adoption.
This is where service providers can support, budget willing. Slightly more than one-third of respondents (37%) report working with third-party consultants to support software implementation and adoption. Larger systems, like an EHR or HMIS, may require more support than an internal team can handle, but 64% of respondents rely on internal teams to ensure software adoption.
Buyers should research potential vendors extensively before contracting their services, ensuring alignment on compliance needs, project scope, and reasonable timelines and benchmarking.
Buyer sentiment towards AI in healthcare
Shifting focus to AI highlights, 83% of respondents say it's important that the software they purchase incorporates AI. Patient engagement software is the most common existing investment that already utilizes some form of it, followed by EHR and medical billing solutions. Almost half of respondents also admitted feeling pressure to embrace AI.
While there’s good reason to adopt AI and advanced machine learning, healthcare organizations need to be intentional about their strategy. Making impulsive purchases and decisions can lead to financial and social damage, with products being underutilized and sensitive health data being compromised. Nearly 88% of respondents believe their organization can adopt and utilize AI responsibly, but 26% do not have an AI strategy for current and future technology investments.
Administrative and operational benefits factor most commonly into existing strategies as organizations try to address staff burnout and enhance productivity. When zooming out to the entire sector, respondents see patient experience, remote patient monitoring (RPM), and chronic care management as the biggest areas for AI impact.
Technological advancements have brought an incredible level of personalization to the patient experience.
Patients can access medical information more readily, translate complex medical jargon into digestible terms, and avoid preventable health conditions. Notably, clinical decision support products rely on advanced analytics and AI to help providers detect and diagnose conditions earlier and more precisely nowadays. RPM technology works with wearables and mobile devices to manage chronic conditions like diabetes and hypertension, monitoring vitals and hormone levels in real time to transform the care approach from reactive to proactive.
Roughly one-third of respondents said they have not implemented a policy around the use of generative AI tools like ChatGPT yet. If organizations can budget the time and funds, which they should, then mapping out an intentional AI strategy can pay dividends in the long run.
A solid, defined strategy leads to more confident buying decisions, smarter project planning, and reduced risk of data privacy incidents. Whether or not healthcare organizations are ready to launch an AI plan, their employees are making use of this technology right now.
What can healthcare organizations do with this information?
While this is the first of several installments to share the survey findings, software buyers in healthcare should use these initial insights as a comparison tool for their organization’s existing buying process and technology strategy.
Each organization’s needs will differ, but general themes likely proliferate everywhere: patient experience, staff productivity, interoperability, and data security. How each organization chooses to address these topics is what makes the difference.
Understand the current pain points by polling internal teams and identify smart projects where AI and machine learning can make a positive impact. Solidify reasonable metrics for measuring ROI at the beginning of the buying process rather than later.
Like I said at the beginning, AI isn’t going anywhere, so organizations need to confidently know why they’re going with it.
Check out G2’s 2024 healthcare trends to learn how smart AI investments can improve ROI.
Edited by Jigmee Bhutia
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