Akashic for healthcare · Hospitals & health systems
Every patient deserves one record. Not seven.
Admissions, labs, imaging, claims, and paper registers each hold a fragment of the patient. Akashic resolves them into one governed longitudinal record, with consent and audit built into the platform, not the policy binder.
Rahul Sharma · one record
Resolved record · 3 registrations merged
Built for hospitals, health networks, and public health programmes · governed end to end
The 2 a.m. admission is a data problem.
How it plays out today
A patient arrives in emergency at 2 a.m. Their history sits in the ward HIS, a lab system, a scan archive, an insurer's claim file, and a paper register two districts away. The clinician treats with a partial picture. The hospital absorbs the risk. The patient repeats their story for the fifth time.
1
Every department keeps its own patient
Admissions, labs, imaging, and billing each hold their own version of the record. None of them agree, and no clinician sees all of them at once.
2
Duplicate identities, reconciled by hand
The same person registered three ways across departments and campuses. Matching them happens manually, after the fact, if at all.
3
Compliance lives in documents, not systems
Consent and access rules sit in policy binders while the systems that actually serve the data enforce none of them. Audit preparation is an annual emergency.
None of these are people problems. All of them are architecture problems.
The 2 a.m. admission is a data problem.
A patient arrives in emergency at 2 a.m. Their history sits in the ward HIS, a lab system, a scan archive, an insurer's claim file, and a paper register two districts away. The clinician treats with a partial picture. The hospital absorbs the risk. The patient repeats their story for the fifth time.
Point of care
The clinician sees only the system in front of them.
The missing history is not absent. It is scattered across systems that were never joined around the patient.
The fragmented patient
On Akashic: resolved into one patient record
Duplicate identities merged
Consent checked before access
Allergy conflict surfaced
Every source record attached
HIS · LIS · PACS · claims · consent · audit
1
Every department keeps its own patient
Admissions, labs, imaging, and billing each hold their own version of the record. None of them agree, and no clinician sees all of them at once.
2
Duplicate identities, reconciled by hand
The same person registered three ways across departments and campuses. Matching them happens manually, after the fact, if at all.
3
Compliance lives in documents, not systems
Consent and access rules sit in policy binders while the systems that actually serve the data enforce none of them. Audit preparation is an annual emergency.
None of these are people problems. All of them are architecture problems.
Nobody should have to tell their story five times at 2 a.m.
Scroll through your own hospital: the players you already have, and what changes when their data lands on one governed record.
- 01
The players
Every system holds a piece of the patient.
Wards, labs, imaging, pharmacy, the insurer: each keeps its own version of the person. None of them agree.
- 02
The systems speak
Every record starts streaming.
Admissions, results, scans and claims land on the governed foundation as they're written, not when someone exports them.
- 03
One patient forms
Three registrations. One person.
Master data resolves duplicate identities into one longitudinal record, with consent and masking enforced by the platform.
- 04
Care answers back
The full history reaches the bedside.
The 2 a.m. clinician sees everything, with sources attached. The patient tells their story once.
One longitudinal record, governed at the source.
Akashic doesn't rip out your HIS or LIS. It unifies what they hold into one patient truth, enforces consent and masking at the platform layer, and answers clinical and operational questions with the source attached.
01 / Unify
Every system, one patient
Data Pipelines connect HIS, LIS, imaging metadata, pharmacy, and claims as they change. Master Data resolves duplicate registrations into one golden patient record.
02 / Govern
Consent enforced by the platform
Role-based access, PII masking, and consent rules execute at the graph layer. Every access is stamped and traceable, so the audit trail writes itself.
03 / Predict
Capacity and risk, forecast on your own history
Models trained on your admissions, seasonality, and supply data forecast bed demand, flag readmission risk, and keep pharmacy stock ahead of need.
04 / Act
Answers at the point of care
Clinicians ask in plain language and get the full history with sources. Administrators watch live occupancy and flow instead of last week's census.
Every module runs on the same governed foundation · every answer arrives with its lineage
What changes on the ward.
Same clinicians. Same systems of record. A complete picture where there were fragments.
BeforeHistory assembled by phone calls between departments
AfterOne longitudinal record at the point of care
BeforeConsent enforced by policy documents
AfterConsent enforced by the platform itself
BeforeAudit preparation measured in weeks
AfterEvery access already stamped and traceable
BeforeCapacity planned on last month's census
AfterBed and supply demand forecast on live signals
Let's talk about your patients' record.
Whether it's a single hospital untangling duplicate registrations or a health system building one governed patient truth across campuses, we'd like to show you what that architecture looks like.