What are we aiming for? What do CGM and AID actually deliver? And how do you put them into practice?

A state-of-the-art overview after ADA 2026.

 

I have written this for two groups at once.

• The clinicians and educators who build inpatient protocols.
• And the people with diabetes who will be admitted under them.

Usually these two conversations happen in separate rooms.

They should not.

The evidence is the same for both.

What differs is what you can do with it.

 

One idea runs through everything below:

Removing a working system is not a neutral act. It is an intervention.

 

Hospitalisation is one of the hardest places to manage glucose.

Acute illness, surgery, infection, steroids, changing intake, less movement, shifting insulin needs — all of it pushes glucose around, toward both highs and lows.

 

And this is not a small group.

Around 38–40% of hospitalised patients have hyperglycaemia or diabetes, rising to 70–80% of those admitted with critical illness or for cardiac surgery.¹

 

There are two routes to a high glucose on the ward:

• Pre-existing diabetes — patients who arrive already living with it.
• Stress hyperglycaemia — any glucose >140 mg/dL (7.8 mmol/L) with no prior history of diabetes. It usually settles as the illness resolves. But up to 60% of these patients are diagnosed with diabetes within 6–12 months. The admission is a screening opportunity.¹

 

Meanwhile, more and more patients arrive already wearing a sensor or running a closed loop at home.

 

So the question is no longer whether diabetes technology belongs in hospital.

It is what it does, and how to use it well.

 

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1. What Are We Aiming For?

 

The ADA targets are deliberately pragmatic:²

• Non-ICU: 100–180 mg/dL (5.6–10.0 mmol/L)
• ICU on insulin: 140–180 mg/dL (7.8–10.0 mmol/L)

…provided those targets can be reached without significant hypoglycaemia.

 

That last clause is the whole story.

Every attempt to chase tighter control with intensive insulin drove hypoglycaemia up.¹

And hypoglycaemia tracks with worse outcomes.

So the targets sit higher than we would accept outside the hospital.

This is on purpose.

 

There is also a growing argument that one target does not fit everyone.

Much of the evidence linking inpatient hyperglycaemia to increased morbidity and mortality comes from patients with stress hyperglycaemia or without previously diagnosed diabetes, whereas the association is considerably weaker in those with established diabetes.^3–6

Patients with chronically elevated glucose appear to adapt to higher glycaemic levels, meaning that a rapid reduction in glucose—even into the conventional target range—may represent relative hypoglycaemia. This physiological stress response, often referred to as the hyperglycaemia paradox, may contribute to adverse outcomes despite glucose remaining above the biochemical hypoglycaemia threshold.¹

 

One consequence deserves to be stated plainly, because it almost never is.

Someone who has spent years building a time in range they are proud of will watch it fall apart over a week on a ward.

And will usually be told nothing about why.

 

The fall is largely intentional.

Chasing 70–140 mg/dL (3.9–7.8 mmol/L) through an acute illness, with a regimen adjusted by people who do not know that patient, has repeatedly produced more hypoglycaemia and worse outcomes.

 

In interviews with hospitalised adults, people described being tested but not told the result. And being aware their glucose was drifting while feeling powerless to act.^23,24

The anxiety is not irrational.

It is what happens when a number someone has been trained to treat is left unexplained.

 

Saying the target out loud, once, costs thirty seconds.

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2. How We Treat Today

 

 

Glucose should be actively managed in any hospitalised patient.

Insulin is generally started once glucose passes 180 mg/dL (10 mmol/L) — IV in the ICU, subcutaneous on the wards.²

 

The RABBIT trials settled the central question:

physiologic basal–bolus insulin is superior to sliding-scale alone,

with better glycaemic outcomes and fewer complications.^7,8

 

But basal–bolus is demanding.

It needs frequent monitoring, continuous dose adjustment and experienced staff.

Even specialist centres struggle to reach target.

And there is still no agreed protocol for patients on IV glucose, TPN or enteral feeding.^2,9,10

 

Much of this burden falls on junior staff with little specialist training.

It is not surprising that errors occur.

The system asks a great deal of the people least equipped for it.

 

There is a second version of that sentence, which we hear less often.

The same system routinely takes insulin away from people who have been dosing it themselves for decades.

 

In interviews with older adults admitted for surgery, participants described their insulin being locked away on admission.

Doses arriving late, or after meals.

Waiting for a doctor to authorise a correction they would have given themselves in seconds.²³

 

One participant with forty years of type 1 diabetes described losing control of his own insulin as 23 "like having your arms chopped off."

Across a larger multi-centre study the themes recurred: no control over glucose management, no involvement in care planning, meals arriving out of step with insulin.²⁴

 

This matters clinically, not only experientially.

Being able to self-administer insulin in hospital is independently associated with greater inpatient treatment satisfaction.²⁸ 

And staff themselves describe the current arrangement as offering less safety than it appears to.²⁵

 

The asymmetry is worth naming.

Errors made by a stretched ward team are treated as system problems, which they are.

Errors avoided by an experienced patient are treated as luck.

 

The person in the bed is often the most experienced insulin user in the room.

 

Not always. But often enough that it should be asked, not assumed.

 

This is precisely the gap technology should fill.

 

 

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3. What Does CGM Deliver?

 

 

 

Compared with intermittent fingersticks, CGM offers real-time values, trend data, detection of nocturnal hypoglycaemia and postprandial peaks, and less nursing workload. 

 

The glycaemic effect, however, is modest.

 

A meta-analysis of six randomised trials in 979 hospitalised patients showed only small improvements in time in range — on average around +7% TIR, with considerable heterogeneity.¹¹

 

The spread is instructive. DIATEC achieved roughly +15%, the largest gain of any trial.

But only because CGM was combined with structured insulin titration algorithms and specialist diabetes support.¹²

 

Other trials, including TIGHT¹³ and Thabit's pilot under non-specialist teams,¹⁴ showed limited benefit.

 

CGM provides information. Someone still has to act on it. The benefit lives in the protocol, not the sensor.

 

 

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4. How to Implement CGM

 

[FIGURE 5 — CGM accuracy within EHR during AIDING Trial]

 

No CGM is formally approved for inpatient use.

Yet professional recommendations now support continuing CGM in patients already using it at home — provided an institutional protocol exists.²

Accuracy (MARD) is somewhat lower in hospital, and several common medications affect readings.

The protocol is what turns a home device into a safe clinical tool.

 

Most inpatient protocols share the same six building blocks:¹⁵

1. Assessment. Is the patient conscious, able to engage, and not on IV insulin? (Some centres now permit CGM even during IV insulin.)
2. Validation against POC. A paired fingerstick once or twice daily, ~20% agreement threshold. Beyond that, revert to POC. Low and high cut-offs (e.g. 80 and 250 mg/dL) trigger a confirmatory fingerstick.
3. Documentation. A defined place in the EHR — nursing flowsheets, structured templates or SmartPhrases.
4. Defined responsibilities. Who documents, who decides on continuation, who assesses at weekends. Endocrinology-led, pharmacist-led or nurse-led all work. Clarity matters more than the model.
5. Remote monitoring (optional). Dexcom Follow supports up to 25 patients, LibreLinkUp up to 20 — with consent, since everyone at the station can see real-time glucose.
6. Special situations. Imaging, surgery, delivery, and a discharge handover plan.

 

Richer protocols tend to produce better control.

Simpler ones cost less nursing time, less patient burden and less money.

The right balance is local — and choosing it deliberately is itself a sign of a mature programme.

 

Step 2 generates the most friction at the bedside. 

It is better explained than defended.

 

Someone who wears a sensor usually trusts it more than a hospital meter, and in daily life is usually right to.

In hospital, two things change: accuracy is lower in acutely ill patients, and several inpatient medications interfere.

 

The paired fingerstick is not a comment on the device, or on the person wearing it.

It is the mechanism that permits insulin to be dosed from that sensor at all.

It is the price of keeping it, not evidence of distrust.

 

People who retained their wearable technology during admission described it as one of the few things that let them stay on top of their own care — though some staff were unfamiliar with how it worked.²³ 

Both of those are fixed by the same protocol.

 

 

[FIGURE 6 — Attitudes and behaviors with technology: 28% aware of policies]

 

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5. What Does AID Deliver?

 

[FIGURE 7 — AID versus standard insulin therapy in hospital]

 

Automated insulin delivery adds the missing component.

Instead of only displaying glucose, AID acts.

 

The effect is of a different order.

A systematic review and meta-analysis of randomised inpatient trials found approximately a +24 to +25 percentage point improvement in TIR — with reduced hyperglycaemia, lower variability, lower mean glucose, and no increase in hypoglycaemia.¹⁶

 

Benefits held across diverse populations.

The strongest effects were in patients with highly variable insulin requirements, including pancreatic surgery¹⁷ and haemodialysis.¹⁸

 

The AIDING trial

The clearest inpatient evidence comes from AIDING, presented as an abstract at the 2026 ADA Scientific Sessions.¹⁹

 

Unlike most earlier work, which focused on type 2 diabetes, AIDING enrolled both type 1 and type 2 patients across three US academic health systems.

Participants were randomised to Omnipod 5 with Dexcom G7 versus multiple daily injections plus CGM.

 

 

[FIGURE 8 — AIDING trial: time in range by treatment group]

 

• Omnipod 5: TIR 67.7%, time <54 mg/dL (3.0 mmol/L) 0.17%
• MDI + CGM: TIR 40.8%, time <54 mg/dL (3.0 mmol/L) 2.3%

A +27% TIR gain, without increasing clinically significant hypoglycaemia.

 

Notably, the benefit was visible from day one — before the optimisation that usually accumulates over several pod changes.

AIDING also showed that AID can be systematically initiated in insulin-treated patients admitted for something else entirely.

 

AIDING did not simply test a device. It tested an entire care model.

 

 

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6. How to Implement AID

 

[FIGURE 9 — Setup remote monitoring AIDING trial]

Two situations must be separated. They demand very different things from a hospital.

• Continuing AID in a patient who already uses it — the everyday scenario.
• Systematically initiating AID in patients who were not using it — what AIDING did.

 

Almost everything AIDING required belongs to the second.

For the first, the additional work is modest.

 

 

#1 Continuing AID in a patient who already uses it

 

If a CGM protocol exists, most of the groundwork is done. What is needed on top:

1. An assessment of who can keep wearing their pump. Can the patient still manage the device, and do they have their own supplies? Essentially the same judgement already made for CGM.
2. A CGM protocol, as above.
3. A place in the EHR to record the pump. Device and insulin type, settings, and every bolus delivered.
4. Carbohydrate counts for hospital meals — optional, but they make accurate bolusing far easier.
5. A specialist diabetes team available for support. This one is not optional. When a device problem arises, someone has to be reachable.

 

For patients who arrive on their own AID, the incremental work is an assessment, a place to document the pump, and a team to call.

 

Point 1 is one line in a protocol and the most consequential thing that happens on the day of admission.

The useful reframing: the question is not "can this device stay on?" but four narrower ones.

Who is managing it? With what supplies? Documented where? And who is called at 2am?

Answer those and the device is rarely the problem.

 

There will be admissions where the answer is genuinely no — the patient is too unwell, or cannot engage.

In my experience people accept that readily when it is explained.

What is not accepted, and should not be, is a blanket policy applied without asking.

 

For anyone reading this who uses a pump or sensor, the practical corollary is short.

• Bring your own supplies: pods or infusion sets, sensors, a charger, your usual needles, and your pump settings written down somewhere that is not only on your phone. Hospitals almost never stock these.
• Ask on day one whether self-management is possible on your ward. In one study, people were frustrated to learn only afterwards that it had been an option nobody mentioned.²³
• And ask who the diabetes team is, and how they are reached at weekends.

 

#2 Systematically initiating AID — what AIDING required

 

[FIGURE 10 — Informatics needs: no site was trial-ready]

 

A major finding was that none of the participating centres were initially "AID-ready".

All required modifications to their EHR systems before the trial could run.^19,21

 

Five components did the heavy lifting:

• Clearly defined responsibilities. Responsibility shifts from patient to team. Nurses validated CGM accuracy, delivered boluses, responded to alarms and documented insulin. Dietitians supplied carbohydrate counts. Diabetes specialists supervised insulin. Primary teams managed the underlying illness.
• Structured CGM validation. Only validated sensor values could drive dosing. Requirements relaxed as confidence grew — from six to two checks per day — with alerts at <80 mg/dL and >300 mg/dL for over an hour.
• EHR integration. Validation workflows, pump order sets, documentation pathways, MARs and refill workflows — folded into existing nursing workflows rather than run in parallel.
• Remote monitoring. A ward-level platform for nurses, plus one for the diabetes team. This remains the hardest piece to reproduce outside a trial: current data platforms can lag by 30 minutes to several hours.²⁰
• Education and 24/7 support. Just-in-time training at the point of need,22 alongside a reachable diabetes team. Diabetes champion programmes help sustain this as staff rotate.¹⁵

 

[FIGUREN 11–14 — Roles & responsibilities / validation / bolus delivery.]

 

One observation from the pregnancy closed-loop work generalises well beyond pregnancy.

Clinicians concluded that the best results came from a three-way collaboration between the team, the person with diabetes, and the algorithm — and that the technology was not a panacea on its own.²⁷

That is as good a description of an inpatient AID programme as any protocol document has managed.

 

 

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Why Not Everyone Yet: The Case for Restraint on Starting

 

It is tempting, looking at these numbers, to put every hyperglycaemic inpatient on CGM and everyone on insulin on AID. Several things argue for restraint.

• The benefit of strict inpatient glucose control is not firmly established. Much of the evidence linking glucose to outcomes is correlational. The mortality signal is strongest for spontaneous hyper- and hypoglycaemia rather than for the values we manage in known diabetes. Both may partly be markers of how sick a patient is.^3–6
• The CGM benefit is small, and access is limited. Around +7% TIR is real but modest. CGM remains off-label in hospital and generally not reimbursed for inpatient use.¹¹
• AID carries a genuine operational burden. And the discharge question is unresolved: if a patient starts AID in hospital but cannot access it at home, they may need to be transitioned back to injections before leaving — which could lengthen the stay.

That last point has not been studied. It follows logically, and it deserves an answer.

It is, in my view, the most important open question in the field right now.

 

None of this argues against the technology.

It argues against rolling it out faster than the evidence, the reimbursement and the discharge pathway can support.

 

And note what these cautions have in common.

Every one of them concerns starting technology in people who were not using it.

None of them touches the case for continuing what a patient already runs.

Because that case never rested on time in range in the first place.

 

 

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Conclusion

 

For all the heterogeneity between trials, the studies point in one direction.

Diabetes technology works in hospital — modestly with CGM, substantially with AID.

 

But the practical priority for most hospitals does not depend on those numbers at all.

Support the patients who already have this technology.

 

Removing a working system is an intervention, with its own consequences.

Competence leaves the room.

Dosing passes to staff managing an unfamiliar regimen under time pressure.

Insulin arrives late.

Corrections wait for authorisation.^23,24,25

 

Self-administration, where it is safe, tracks with better satisfaction and fewer timing failures.²⁸

 

Not one of those arguments needs the TIR evidence to be strong.

They hold even if the +7% turns out to be worth less than we hope.

 

So let patients keep the devices they walk in with.

Build the basic protocol around it: assessment, validation against POC, a place in the EHR, and a specialist team within reach.

That is inexpensive, it is already recommended, and it earns the experience a hospital would need for anything larger.

 

And build in the part that costs nothing.

Say what target you are aiming for, and why.

Explain that validation is what keeps the sensor in play.

Ask, rather than assume, who is managing the insulin.

Tell people before admission that self-management may be possible.

 

The qualitative literature is consistent on this.

What people remember is not the protocol.

It is whether anyone talked to them.^23,24

 

As CGM becomes cheaper, as AID becomes simpler to run, and as outpatient access broadens, the case for offering this to more inpatients will only strengthen.

 

The technology is ready. The task now is to build the hospitals around it, in the right order.

 

Kind regards, 

Inge

 

 

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References

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2. American Diabetes Association Professional Practice Committee. 16. Diabetes care in the hospital: Standards of Care in Diabetes—2026. Diabetes Care. 2026;49(Suppl 1):S315-S334. doi:10.2337/dc26-S016.
3. Falciglia M, Freyberg RW, Almenoff PL, D'Alessio DA, Render ML. Hyperglycemia-related mortality in critically ill patients varies with admission diagnosis. Crit Care Med. 2009;37(12):3001-3009. doi:10.1097/CCM.0b013e3181b083f7. 
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13. Hirsch IB, Draznin B, Buse JB, Raghinaru D, Spanbauer C, Umpierrez GE, et al. Results from a randomized trial of intensive glucose management using CGM versus usual care in hospitalized adults with type 2 diabetes: the TIGHT study. Diabetes Care. 2025;48(1):118-124. doi:10.2337/dc24-1779. 
14. Thabit H, Rubio J, Karuppan M, Mubita W, Lim J, Thomas T, et al. Use of real-time continuous glucose monitoring in non-critical care insulin-treated inpatients under non-diabetes speciality teams in hospital: a pilot randomized controlled study. Diabetes Obes Metab. 2024;26(11):5483-5487. doi:10.1111/dom.15885. 
15. Clements JN. From arrival to discharge: leveraging personal CGM to improve outcomes throughout the hospital experience. Presented at the American Diabetes Association Scientific Sessions; June 2026.
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18. Bally L, Gubler P, Thabit H, Hartnell S, Ruan Y, Wilinska ME, et al. Fully closed-loop insulin delivery improves glucose control of inpatients with type 2 diabetes receiving hemodialysis. Kidney Int. 2019;96(3):593-596. doi:10.1016/j.kint.2019.03.006. 
19. Parab R, Davis G, Lal R, Brown S, Usman S, Hughes MS, et al. Automated insulin delivery improves glycemic control in hospitalized patients with diabetes regardless of baseline hemoglobin A1c. Diabetes. 2026;75(Suppl 1):1849-P. 
20. Davis GM, Hughes MS, Lal RA, et al. Automated insulin delivery with remote real-time continuous glucose monitoring for hospitalized patients with diabetes: a multicenter, single-arm, feasibility trial. Diabetes Technol Ther. 2023;25(10):707-715. doi:10.1089/dia.2023.0304.
21. Cook CB, Wellik KE, Kongable GL, Shu J. Assessing inpatient glycemic control: what are the next steps? / Implementation of inpatient insulin orders with a commercial electronic health record system. J Diabetes Sci Technol. 2014;8(1):8-13.
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23. Lange Ferreira C, Habte-Asres H, Forbes A, Winkley K. 'Why, can I not have control of my own insulin?': qualitative exploration amongst older adults with diabetes with lived experience of surgical hospital admission. Health Expect. 2025;28(6):e70509. doi:10.1111/hex.70509.
24. Mansbridge SE, Kozlowska O, Lumb A, Rea R, et al. A multi-centre qualitative study of experiences of managing diabetes mellitus among adults while hospitalised. Diabet Med. 2026;43:e70256. doi:10.1111/dme.70256.
25. Lange Ferreira C, Habte-Asres H, Forbes A, Winkley K. "It is a false safety net": a qualitative exploration of multiprofessional staff experiences of insulin management in hospitalised older or frail adults with diabetes undergoing surgery. PLoS One. 2025;20(10):e0332088. doi:10.1371/journal.pone.0332088.
26. Lawton J, Kimbell B, Closs M, Hartnell S, Lee TTM, Dover AR, Reynolds RM, Collett C, Barnard-Kelly K, Hovorka R, Rankin D, Murphy HR. Listening to women: experiences of using closed-loop in type 1 diabetes pregnancy. Diabetes Technol Ther. 2023;25(12):845-855. doi:10.1089/dia.2023.0323.
27. Lawton J, Rankin D, Hartnell S, Lee T, Dover AR, Reynolds RM, Hovorka R, Murphy HR, Hart RI; AiDAPT Collaborative Group. Healthcare professionals' views about how pregnant women can benefit from using a closed-loop system: qualitative study. Diabet Med. 2023;40(5):e15072. doi:10.1111/dme.15072.
28. Rutter CL, Jones C, Dhatariya KK, et al. Determining in-patient diabetes treatment satisfaction in the UK — the DIPSat study. Diabet Med. 2013;30(6):731-738. doi:10.1111/dme.12095.