When you look at your dashboard and see a twenty percent no show rate, it is hard not to feel that something in the system is quietly working against you. Telehealth has helped in many settings, and several large studies show that virtual visits often come with lower no show rates than traditional in person care, yet small avoidable errors still chip away at access and throughput. One of the most overlooked sources of those errors is basic time zone handling.
If you run or oversee an outpatient clinic, especially one with therapy services or multiple locations, time is not just a clinical constraint. It is a capacity, revenue, and staff workload issue. When an appointment fires at the wrong local time, you lose more than one slot, you burn staff effort, increase phone volume, and give patients a reason to doubt that virtual care is reliable.
At the same time, platforms such as Solum Health are leaning into this operational layer. Solum presents itself as an AI powered front office for healthcare, with a unified inbox and AI intake automation for outpatient facilities, built for therapy specialties and integrated with EHR and practice management systems, with measurable time savings. In that context, time zone handling is not a side feature, it is part of the basic promise.
In plain terms, time zone handling for telehealth scheduling is the discipline of making sure that a ten in the morning appointment represents the same exact moment for every person involved, regardless of where they are.
At a technical level, it usually means that the scheduling system:
At an operations level, it means that when your team promises a slot, the time shown in the call summary, the text reminder, the calendar invite, and the telehealth link all align. Patients experience one reality. Staff experience one reality. You do not spend lunch break deciphering who meant what.
Most effective configurations follow the same backbone, even if the software looks different from clinic to clinic.
Every appointment is stored with a single reference time, often a global standard. This gives the system one source of truth and prevents drift when devices move or settings change.
The system identifies the local time zone for each participant. That can come from patient profiles, provider profiles, or device settings. The key is to avoid guesswork. If you treat every patient as if they live in the same city as the clinic, problems appear as soon as someone travels.
The stored appointment time remains untouched. What changes is how it appears on the screen. Patients and providers see the appointment translated into their own local time. The underlying record, the thing your reports rely on, stays consistent.
Once an appointment is confirmed, the time is anchored. If the patient later travels, the visit still occurs at the intended moment. The display adjusts to the new local time, but the appointment does not quietly slide forward or backward.
The time a scheduler reads in the interface, the time printed on intake instructions, the time in reminders, and the time embedded in telehealth links all match. That sounds obvious, yet many workflows still rely on manual copy and paste steps where discrepancies creep in.
If your practice uses a unified inbox or an AI powered front office, pay attention to how those channels represent time. Calls, texts, and portal messages should echo the same local time expression, otherwise the whole advantage of consolidation is blunt.
When administrators walk through these steps themselves, not just in a test environment but using live workflows, they often spot small gaps that explain recurring frustration on the phones.
If time zone handling is configured correctly, the appointment stays anchored to the moment that was confirmed. The patient sees that moment expressed in the new local time, but you do not need to reschedule purely because they traveled.
No. Time zone issues can arise even inside one state, for example when daylight saving rules change, when providers or staff work remotely, or when your systems are hosted in a different region from your clinic.
Taken one by one, these are small events. However, in large appointment datasets, even modest reductions in confusion can have a visible effect, especially when telehealth already tends to perform better on completion rates in many settings.
Clear language helps. Phrases such as your local time are often more digestible for patients than technical labels. The goal is to make the time feel obvious at a glance.
Manual fixes work for small telehealth programs. As volume grows and you add channels such as a unified inbox, patient portals, and automated reminders, it becomes unrealistic to expect staff to catch every inconsistency by hand.
Handled with care, time zone logic fades into the background. Patients see consistent times, staff trust what is on the screen, and your telehealth program can focus on what it is really meant to do, expand access and lighten the load on your team.
