A clinic can have open hours on three sides of town, yet a new patient still hears, “Nothing until next month.” If that sounds familiar, you are not alone. National survey work on physician access has found average waits of more than twenty days for a first specialty appointment in major U.S. cities, especially when schedules are fragmented by location and referral source. Merritt Hawkins survey of physician appointment wait times has become a shorthand reference for that reality.
Multi location appointment search is one of the quieter responses to that problem. It is not a new discipline, it is a more disciplined way to use capacity you already own.
From an operations standpoint, it matters in three places that you care about every week: access, throughput, and workload. If staff can see openings across locations in a single view, they can match patients to timely appointments instead of guessing or bouncing calls. When more of the schedule is actually filled, throughput improves without adding providers. And when the search is centralized instead of manual, the front desk spends less time in calendar purgatory, more time resolving issues that truly require human judgment.
Solum Health fits into this picture with a very specific stance. The company presents itself as an AI powered unified inbox and intake automation platform for outpatient facilities and specialty practices, integrated with EHR and practice management systems and built to show measurable time savings instead of vague efficiency claims. Multi location appointment search plugs naturally into that kind of environment, one place where messages arrive, one place where intake is handled, and one place where staff can see usable capacity across sites.
For glossary purposes, we can be precise. Multi location appointment search is the ability to look across more than one clinic location at once, see eligible appointment slots in a unified view, then book directly from that view while schedules update in real time.
It is not just having multiple calendars in the same system. The distinguishing features are consolidation and shared logic. Availability is aggregated into a single search layer, then filtered by rules that are consistent across locations, for example visit type, provider credentials, or required room resources. When the appointment is booked, all underlying schedules reflect that change immediately.
Three core characteristics tend to show up in mature implementations. First, a consolidated view of capacity across locations. Second, real time synchronization that preserves schedule accuracy. Third, clear rules for what counts as an eligible appointment, so staff trust that what they see is bookable.
Even if vendors describe it differently, the mechanics usually follow the same arc. I find it helpful to break that arc into four parts so you can map it to your own systems.
First, availability is aggregated across locations. The scheduling layer collects open slots from each site, along with attributes such as provider, visit type, and duration. If you already use concepts like a golden record for patient identity, you know why consistent data matters here.
Second, search criteria are applied. Staff or patients can specify a date range, a preferred provider group, a maximum travel radius, or other filters that reflect your access policy. The system drops any slots that do not meet those criteria.
Third, results are ordered. This step shapes behavior more than most people realize. You can choose earliest available, closest clinic, continuity with the same clinician, or a combination. A clinic that frames access around “first available anywhere” will see very different patterns from one that prioritizes continuity above all else.
Fourth, booking and updates occur. Once an appointment is selected, the system writes back to the underlying schedules and removes that slot from search results. Accuracy matters here, so you want clean integrations to your EHR and practice management tools, not a separate shadow calendar that staff forget to reconcile.
If you are already exploring concepts like intake prefill from EHR to reuse existing patient data, or building a least privilege access model for staff, multi location search will feel like a natural extension of that same discipline.
If you are asking, “What would it take to implement this in my network,” you are already in the right mindset. In practice, the steps are less exotic than they sound, but they do require rigor.
Step one: Standardize what an appointment means. Align visit types, durations, and basic eligibility rules across locations as much as clinical reality allows. Total uniformity is not realistic, but large idiosyncrasies will make search results confusing.
Step two: Decide what you want the search to optimize. You can choose speed of access, continuity with a trusted provider, location convenience, or a clear hierarchy among the three. Your decision here should line up with what you are already measuring in access and quality dashboards. Findings from advanced access scheduling research show that once organizations commit to shorter lead times as a core metric, system design tends to follow.
Step three: Connect the dots technically. That means wiring your scheduling tool into the same environment that handles communication, intake, and tasking. Many clinics now pursue an message read receipts strategy, a paper free patient intake process, and AI agents for patient intake and scheduling as part of a single front door rather than separate projects. Multi location search fits best when it rides along that same integrated stack.
Step four: Start with a contained pilot. Many leaders begin with one specialty or a cluster of locations that share similar workflows. The goal is not a grand reveal, it is a tight feedback loop, what works, what confuses staff, what causes patient complaints, and how often you see unused capacity pulled into active use.
Step five: Measure rigorously. You cannot manage what you never quantify. At minimum, track time to first available appointment, schedule fill rates across locations, and the share of calls or messages that are resolved on the first touch. External research on outpatient wait times has linked long waits to lower patient satisfaction, especially when people perceive avoidable delays. Health Affairs research on outpatient wait times illustrates that effect clearly.
There are a few predictable failure points that are worth naming plainly, so you can avoid them.
Inconsistent rules across locations are the first. If one site uses thirty minute evaluation visits and another uses sixty, or if double booking is allowed in some clinics and forbidden in others, search results will mislead staff. This is where a shared golden record of visit definitions is not an abstract data idea, it is a governance tool.
Weak access controls are a second risk. If you centralize availability and communication in a unified environment but ignore concepts like least privilege access, you simply move clutter and risk into a new place. Multi location search should sit inside a security model that already defines who can see which calendars and who can book on whose behalf.
A third pitfall is treating the work as a one time configuration. Schedules drift, service lines grow, payer rules change. That is why many organizations revisit their access setup quarterly and align it with other projects, for example efforts to measure ROI of AI agents in outpatient clinics or to expand automation beyond intake into recurring outreach and reminders.
What is the difference between multi location appointment search and traditional scheduling
Traditional scheduling focuses on one location at a time and usually one calendar at a time. Multi location appointment search pulls availability from several locations into a unified view, then applies shared rules to show staff or patients the most appropriate open slots.
Is multi location appointment search only relevant for large organizations
It is most visible in larger networks, but even a two or three site practice can benefit. The main advantages, shorter waits and fewer manual steps, show up as soon as you have patients who are willing to travel a little farther in exchange for a sooner appointment.
Does this approach eliminate local scheduling control
No. Each location keeps its own constraints, for example which services are offered, which providers are on which panel, and what room resources exist. Multi location search simply exposes eligible capacity so staff can match patients to the right slot more quickly.
How does multi location appointment search affect patient experience
Patients are less likely to hear “nothing for several weeks” when there is in fact an opening at a nearby site. That alone can reduce frustration. When combined with clear communication and modern tools like AI assisted intake, it also shortens the back and forth that often delays care.
Can multi location appointment search reduce no shows
It can contribute. By offering more timely and convenient appointments, clinics chip away at the avoidable side of no shows, things like long lead times or difficult travel. It is not a full solution on its own, but it pairs well with reminder workflows and data quality work that already exists in many outpatient settings.
If you want to move this forward in your own clinic, start small and specific. Map where you already have schedule variability across locations. Decide what you want the search to prioritize, speed, continuity, or proximity. Align basic visit definitions. Then ask a simple question, can your current communication and intake environment, ideally a unified inbox and AI intake automation stack, actually support this kind of search logic. If the answer is “not yet,” that gives you a clear next project rather than a vague aspiration.
In a world where access, staff burnout, and financial performance are all under pressure, using the capacity you already have, in a smarter and more transparent way, is one of the rare moves that helps on all three fronts at once.
