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Keeping Pace With Great Expectations
My sister—bless her heart—favors the communication style and cadence of bygone eras. Most of us are used to rapid-fire text exchanges with delays measured in minutes. Her replies, by contrast, can feel like a letter crossing the Atlantic circa 1776—when battles dragged on because no one had heard the peace treaty was signed.
She also prefers the languid, meandering banter of phone calls over just-the-facts texts. So when I message her, I often hear my phone ring in response.
I thought about her pace while considering the incredible speed of change at the intersection of technology and service. A few examples:
Ever since I started using it, ChatGPT has set the standard for automated or bot interactions. It finally delivers what I’ve always wanted—the answer to my question. The difference between traditional Googling and an LLM experience like GPT, as most now know, is akin to being told where something might be—“You can look on those shelves over there”—versus being handed the item you asked for.
I almost never “Google” anything anymore. To be clear, I’ll use ChatGPT as my example because that’s what I primarily use. Others may prefer Gemini, Grok, Anthropic, or something else—the point is that a new standard for this experience has been set.
Along with leaving Google in the dust, GPT made a mockery of Siri. I can’t be the only one tired of asking Apple’s assistant for something only to hear, “I can’t show that in the car” (fine—just tell me), or “I found this on the web,” followed by links—again, much like “You can look on those shelves over there.”
I experimented with Shortcuts on my iPhone to reach GPT via voice command and got it working, but it was clunky. I wanted to access GPT the same way I could Siri.
Apple seems to have gotten the message. After installing the latest software update this week, I can ask Siri to ask GPT directly. A new standard had been set, one Apple realized it couldn’t match natively, so it did the smart thing and passed the baton. It gave users what they wanted rather than pretending what it offered was good enough. Sometimes you have to know when you’re beaten and, as they say, “join ’em.”
Two small Amazon examples further illustrate how the service bar keeps rising. The other day, I submitted an order for a box of energy/protein bars and got a prompt: “Hey, you just ordered these—are you sure you want more?” I surely did not, and I appreciated the nudge. The best customer interactions—the ones that build the most trust and loyalty—are often those in which the seller tells us we don’t need what we’re trying to buy.
Then, this morning, I noticed the subject line in a “We just delivered your item” email from Amazon stated exactly how long it took from the moment I pressed the order button until the package hit my doorstep. That’s owning the process and boldly laying out performance.
The point is that everything around us is improving very quickly. As we all know, healthcare lags in delivering the kind of experience consumers expect elsewhere. Think of these expectations as bars being set all around you. There is a general bar—regardless of service or industry. You can aim for it, or dismiss it as unrealistic with, “We can’t do that in healthcare.” Fine. But there’s also an industry-specific bar. You can strive to be the best in healthcare. More granularly, you can aim to be the best in your market or segment (for example, the best rural facility).
Either way, the pace of innovation and improvement that sufficed 20 years ago belongs to a bygone era. To stay above water, you must do more than tread—you have to swim, stay observant, and, if not a trailblazer, at least a very fast follower.
The bottom line is if you’re doing the digital equivalent of telling patients or caregivers where to look for something rather than handing them what they need, you’re in a bad place—especially if your competition is serving it up with a smile.
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Thoughts on this piece? Drop me a line aguerra@healthsystemCIO.com
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| | Chero Goswami, Chief Information & Digital Officer, Providence, discusses linking observation to disciplined governance and resilient operations. He emphasizes rounding to validate workflows, plain-language patient design, and a ‘three hops to the patient’ rule for prioritization. The program focuses on product, practice, and performance variation, standardizing what improves outcomes. Resilience centers on modernized business-continuity planning, rehearsed electronic failover, and shared accountability among infrastructure, security, risk, and operations leaders, with vendor diversification to reduce risk. | | | | |
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Full Interviews From Our AI Special Report
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| | Mouneer Odeh, VP, Chief Data and AI Officer, Cedars-Sinai, discusses building AI grounded in data quality and governance. He outlines a balanced mix across EHR platforms, best of breed tools, and in house builds, plus a shift from projects to product management for adoption and measurable outcomes. He describes promptathons training non IT teams to co create agents using RAG and institutional policies, backed by oversight and champions, to scale clinician centered impact. | | | |
| | Epic’s dominance as EHR steward makes it the industry’s gatekeeper of hospital software, shaping which ideas reach the bedside. Praised for patient-centricity, disciplined execution, and configurable technology, it also concentrates power through opacity that can hinder the pluralism healthcare requires. Graham Walker, MD, Co-Director, Advanced Development, The Permenante Medical Group, calls for far greater transparency and asks whether any single firm should wield such influence over global healthcare and AI’s evolution. | | | |
| | Dan Brown, CTO, AGFA HealthCare, argues that agile enterprise Imaging platforms let CIOs convert fragmented, siloed imaging into a connected clinical asset. By unifying data across specialties, embedding imaging seamlessly into the EMR, and leveraging cloud, streaming, continuous delivery, and cybersecurity, organizations gain speed. Flow-driven orchestration, intelligent reporting, and AI augmentation reduce burnout and errors while boosting productivity. Brown stresses change management and vendor partnership as prerequisites to scale enterprise imaging and improve patient care. | | | |
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| | Cyber incidents are disrupting finances, operations, and bedside care at large U.S. systems, with leaders citing clinical and financial harm, according to KLAS & EY. Organizations are prioritizing identity and access controls, third-party risk, and managed services while moving from compliance checklists to risk-based governance tied to patient safety, downtime reduction, and operational resilience. The report highlights talent shortages, nonhuman identities, and social-engineering fraud, and contends cybersecurity should enable secure virtual care and AI-driven innovation. | | | |
| | Nallan Sriraman, CTO, Mass General Brigham, argues that hyperscaler outages expose systemic fragility in SaaS and make resilience a duty of care. He urges SaaS leaders to design for failure via multi-cloud, cross-region redundancy, dependency isolation, and transparent recovery. The letter calls for transparency, proactive failure testing, and shared standards with cloud providers and customers. As healthcare’s cloud adoption grows, Sriraman warns service-level reliability remains the vendor’s responsibility and that patient safety depends on it. | | | |
| | Elizabeth Straw, Asst. Professor, Healthcare AI & Cybersecurity, University College London; and Cybersecurity Researcher, UC San Diego, introduces CIPHER, an open-source platform that quantifies patient harms from hospital cyberattacks. Using global incident data and frontline narratives, CIPHER maps disruptions over time, linking attacks to missed cancer follow-ups, delayed stroke care, failed door access, silenced monitors, compromised blood storage, and medication barriers. The project invites healthcare, research, and policy partners to collaborate globally and strengthen hospital cyber-resilience. | | | |
| | Regular audits and assessments of AI systems make organizations more than three times likelier to realize high GenAI value, a Gartner survey finds. The study ties greater value to five practices: ongoing assessments; customized, role-based training (ethics training); AI-specific usage policies; investment in governance features and third-party tools; and safely expanding deployments beyond low-risk users. | | | |
| | Christopher Plummer, Senior Cybersecurity Architect at Dartmouth Health, recounts a demo medical device likely infected via public Wi-Fi with WannaCry-style SMB malware. Because it was segmented and treated as “untrusted,” the device could not move laterally or vertically, averting clinical impact. The episode—marked by 20,000+ outbound connection attempts and an alert from a managed service partner—highlights the value of onboarding in isolation, device vetting, avoiding MAC-address bypasses, and layered defenses to improve detection and response. | | | | |
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