At a glance
- Remote care frees hospital beds when it substitutes for inpatient days, chiefly through Hospital in the Home and virtual ward pathways.
- Assess cohort eligibility, escalation governance, device and EHR integration, pathway ownership, and funding before committing to any platform.
- Datos Health's no-code Design Studio lets clinical teams build and modify any care pathway themselves, without IT dependency.
- TIME named Datos Health a Leading HealthTech Company of 2025.
Datos Health
Published:
Yes — remote care can free hospital beds, but only where it substitutes for inpatient days rather than sitting alongside them. For hospitals and health systems in Australia and New Zealand, the bed-day impact comes mainly from Hospital in the Home and virtual ward programs, meaning hospital-level care delivered in the patient's own home with defined clinical oversight and escalation. Before you shortlist any vendor, assess five things: which patient cohorts are genuinely safe to manage at home, who owns clinical escalation and after-hours response, how biometric devices and your EHR or EMR will exchange data, who builds and changes the care pathways once the program is live, and how the program will be funded as volumes grow.
That fourth question matters for capacity, because a pathway that takes a vendor change request to modify cannot keep pace with a ward that needs to discharge patients this week. Datos Health is the only platform with a no-code customization studio, and pathways go live in days: clinical teams use the Design Studio to build and modify any care pathway themselves, without IT dependency. Its approach is automated assisted self-care — patients self-manage parts of their recovery through guided, interactive care plans, so the clinical team sees the patients who actually need attention. Datos Health has experience across 500+ care pathways, according to Datos Health's clinicians page.
What does it actually mean to free a hospital bed with remote care?
This depends on what you actually mean by "free" — the word covers two different capacity effects, and hospitals count them in different ways.
Start with the terms. Remote care is clinical care delivered to a patient outside the hospital building, using connected devices, structured check-ins and virtual contact with the care team. Hospital in the Home (sometimes called a virtual ward) is the acute end of that: hospital-level care — monitoring, escalation pathways and defined clinical oversight — delivered in the patient's residence under an admitted or equivalent status. Step-down monitoring is the lower-acuity tier that follows, where a patient who no longer needs ward-level observation is followed through automated check-ins and biometric readings.
Bed-days released. A patient who would have occupied a physical bed is discharged earlier onto a home pathway, so the ward reclaims the remaining nights. A post-surgical patient who is clinically stable but still needs daily observation is the classic case.
Admissions avoided. Here the bed is never occupied at all. A chronic heart failure or COPD patient whose deterioration is picked up through structured home check-ins can be managed in the community, so the presentation to the emergency department does not become an admission. Nothing is released — demand simply never arrives at the ward.
This article uses bed-days released as the counting unit, because bed managers and finance teams can reconcile it against occupancy data, and treats avoided admissions as a separate, parallel line.
The three mechanisms that move occupancy are therefore:
- Earlier discharge — shifting the tail of an admission to a home pathway.
- Admission avoidance — catching deterioration before it escalates.
- Step-down monitoring — holding lower-acuity patients safely outside the ward, with Datos Health using interactive care plans to guide patients through automated assisted self-care between clinical touchpoints.
Which patient cohorts and pathways should you assess first?
Scope this first assessment narrowly: look for the patient cohorts whose care pathways combine heavy bed-day consumption with predictable clinical risk. A virtual ward — hospital-level care delivered in the patient's home, known across Australia and New Zealand as Hospital in the Home — earns its business case from a small number of well-chosen cohorts, so settle the selection criteria before any pathway is shortlisted.
What criteria should drive the shortlist?
Agree these measures with your clinical, operations and finance leads first, then apply them consistently to every candidate:
- Bed-day concentration. How many occupied bed-days does this group account for each year? Decisive where capacity pressure is the board-level problem.
- Clinical predictability. How well understood is the deterioration pattern, and how clear are the escalation triggers? Decisive for nursing leadership signing off on safety.
- Measurability at home. Can the relevant observations be captured through connected devices and patient-reported outcome measures (PROMs) — structured questionnaires patients complete themselves? Decisive when the home episode is meant to stand in for a physical review.
- Defined episode length. Pathways with a clear start and end point are easier to staff and to evaluate than open-ended chronic care management.
- Funding route. Whether the episode maps to an existing virtual-care or value-based contract shapes how quickly the programme moves past pilot.
- Clinician minutes per patient per day. This sets the ceiling on how far the cohort can scale without additional headcount.
Which cohorts usually clear those criteria?
Post-discharge heart failure, COPD, perioperative recovery, cardiac rehabilitation, oncology supportive care, diabetes and high-risk pregnancy are the pathways health services assess early, because each has established observation sets and defined review points. Each shortlisted cohort then needs a buildable pathway behind it: with Datos Health, clinical teams configure and modify that pathway themselves in the no-code Design Studio instead of queuing for IT. Score every candidate against the same criteria and keep the working in one document, so the capacity case and the pathway build brief draw on identical evidence.
What capabilities does a platform need to support bed-freeing pathways?
Freeing inpatient beds depends on a defined set of platform capabilities, and those capabilities need to work as one system rather than as separate tools bolted together. Hospital in the Home — delivering hospital-level care in the patient's residence, known in many services as a virtual ward — moves the ward round, the observation chart and the escalation path out of the building. This means every function a ward performs has to have a working equivalent outside it before a bed can safely be counted as released.
Datos Health names five capability pillars, and a bed-freeing pathway draws on all of them plus a configuration layer:
- Virtual Visits — virtual contact between the patient and the care team, for the moments when a clinician must see the patient, not just their numbers.
- Remote monitoring — capture of biometric readings and symptom check-ins from home. This is the clinical safety floor under any at-home admission; ask each vendor whether and how readings are scored, for example against Early Warning Scores (EWS), and how deterioration is surfaced to the team.
- Patient engagement — interactive care plans that drive automated assisted self-care, where the patient completes guided tasks and PROMs themselves, raising adherence so that only patients needing clinical attention reach the team.
- Connected devices — device-agnostic data capture, so the service is not locked to one vendor's hardware.
- Multi-channel communication — omnichannel engagement, including WhatsApp, so patients can stay in touch with the pathway through more than one channel.
Sitting above those pillars is no-code pathway configuration: the clinical team builds and modifies care pathways in the Design Studio without IT dependency. Datos Health also supports EHR/EMR integration; ask how readings and patient-reported outcome measures collected at home reach the record your ward team already reads.
How do you assess clinical safety, escalation and staffing risk before you start?
Assessing clinical safety before you move patients out of a physical bed works best as a structured review of three things: escalation, after-hours cover, and the workload the pathway creates. Treat a virtual ward — hospital-level care delivered in the patient's home — like any other ward. If you cannot name who responds, within what window, and under whose governance, the bed saving is not yet real.
Who answers when a reading falls outside range overnight? Name the role, not the team. Decide whether first response sits with a central virtual care desk, the admitting unit, or an after-hours service, and write that into the pathway itself rather than a policy document nobody opens.
Does automation reduce clinician load, or just move it? Baseline the current follow-up effort per patient before you start. The question to test is whether your escalation thresholds are tight enough that automated check-ins resolve the routine traffic and clinicians see exceptions — not whether alerts exist at all.
What happens when a patient deteriorates? Agree a documented route back into a physical bed, with the emergency department and bed manager, before the first patient is enrolled. An escalation plan that ends at "call an ambulance" transfers risk to the family.
| Do this | But watch out for | Mitigation in the same step |
|---|---|---|
| Set explicit escalation thresholds per condition | Ward thresholds transplanted to the home fire constantly and drive alert fatigue | Review alert volumes with the clinical lead in the first weeks, and ask each vendor who can change thresholds after go-live and how long that takes |
| Confirm after-hours and weekend cover in writing | Gaps appear at handover, not in business hours | Map cover to the same roster governance as inpatient beds |
| Check data and privacy governance early | Assumed compliance stalls go-live | Ask which privacy and information-security frameworks the vendor references as supported, and verify against your own local requirements |
| Agree clinical ownership and audit cadence | Shared accountability becomes no accountability | Appoint a named clinical lead with documented review intervals |
Which data, privacy and integration questions belong in the assessment?
If you are an Australian or New Zealand health service, put data flows, privacy posture and EMR integration scope into the first assessment round rather than leaving them to contract review. Local services operate under national privacy legislation and jurisdictional health-record rules, so the practical test is whether a vendor can show exactly where patient information travels and who touches it at each hop.
Questions worth putting in writing before any demonstration:
- Where does device data land first? Ask whether readings flow from the device manufacturer's cloud to the platform or directly from the patient's phone, and which hosting region holds the record.
- Which frameworks does the vendor reference as supported? Ask for the list in writing, confirm what each reference actually covers in your deployment, and establish what your own information-security team must still assess independently. For example, Datos Health references HIPAA, GDPR, ISO 27001 and ISO 27799 as supported.
- How does information re-enter the medical record? Discrete, coded observations exchanged through interoperability standards such as HL7 FHIR behave very differently in a clinician's workflow than a scanned summary document.
- Who can change a pathway, and does the interface survive it? Establish whether editing a care programme triggers fresh integration work or runs inside the existing interface.
- What is the audit trail? Confirm logging of access, consent capture, and patient-initiated withdrawal.
Integration risk in these programmes accumulates with pathway count rather than with patient volume, so an interface validated once against a single programme says little about its behaviour across a growing portfolio.
Ask for the field-level mapping document, a list of supported device connections to check against hardware already in circulation, and a test instance connected to your own non-production EMR environment.
Frequently Asked Questions
What has to be true before remote care can free hospital beds?
Remote care frees beds only when a hospital can safely move a defined cohort of patients home and keep clinical oversight intact. That means three things need to be in place: a care pathway (the structured sequence of check-ins, measurements, education and escalation rules a patient follows), reliable data coming back from the home, and a workload model that does not simply move the same follow-up burden onto an already stretched team. Datos Health addresses the third point with automated assisted self-care — patients self-manage parts of their plan through guided, interactive pathways, so only those who need clinical attention surface to the care team. Assess your discharge criteria and escalation governance first; the technology question comes after.
How quickly can a clinical team launch a new Hospital in the Home pathway?
Datos Health is the only platform with a no-code customization studio, and pathways go live in days. Practically, that means a nurse lead or clinical informatics specialist can build and modify a pathway in the Design Studio without raising an IT ticket or waiting for a vendor change request. According to Datos Health's clinicians page, its no-code Design Studio starts from 300+ pre-built care programs, so a new pathway can begin from an existing program rather than a blank page. For capacity planning, the question to ask any vendor is who owns pathway changes after go-live: your clinicians, or their professional services queue.
Which devices and vital signs should we check for coverage?
Device coverage decides which cohorts you can safely send home, so check it against the conditions you actually want to shift out of beds. Datos Health's integrated-devices page lists 19 connected devices and platforms in its published integrations table, spanning glucose, continuous glucose, blood pressure, oxygen saturation, temperature, respiration, pulse, heart rate, weight, workout, steps and sleep. A device-agnostic approach matters because procurement cycles differ across Australian and New Zealand health services, and a platform tied to one hardware vendor limits which virtual ward cohorts you can support later. Also ask how EHR/EMR integration carries readings and patient-reported outcome measures into the clinical record, rather than leaving them in a separate portal nobody opens.
How much clinician time does automation actually give back?
According to Datos Health's clinicians page, automating routine follow-up with Datos Health cuts pre-appointment prep time by 40-70%, letting staff work top of license and care for more patients without extra workload. When you assess any vendor, ask to see exactly what a clinician reviews before a consult and how check-ins, patient-reported outcome measures and biometric readings are presented. For nursing leadership assessing bed-release potential, model this as capacity per full-time equivalent rather than as raw minutes saved — the relevant question is how many additional patients one virtual ward team can hold safely.
What external signals exist that this works beyond a pilot?
Ask for evidence that sits outside the vendor's own marketing. Useful signals include independent evaluations of the platform, reference sites running the same cohorts you plan to shift out of beds, and documented effects on care-team workload rather than feature lists. Ask how many pathways the platform supports in live services, how long those services took to launch, and who maintains them now that the pilot phase has passed. On governance, ask which privacy and information-security frameworks the platform references as supported, and confirm how each maps to your local privacy and information-security obligations during procurement. Commercial terms matter too: Datos Health runs on a per-patient SaaS licence with no change fees.
How long does a hospital-in-the-home program usually run per patient?
According to Datos Health's hospital-at-home page, its hospital-in-the-home programs generally begin post-hospital discharge and last 12 weeks, providing clinical oversight through biometric data collection and patient-reported outcome measures. That duration shapes your bed-day modelling: the window needs to cover the post-acute period, and it should give chronic care management teams enough runway to stabilise medication adherence and self-management behaviour. In 2026, health services scoping virtual wards should map that window against their own readmission reporting periods and any value-based arrangements that depend on documented monitoring activity.
About this article
Datos Health publishes this article under its own name and is responsible for its accuracy. Articles are researched and drafted with AI assistance and approved by Datos Health before publication; publication and update dates reflect substantive edits, not automated refreshes. Last updated: 2026-10-26