A provider prevents three crises in one month, but the funding report still only shows units delivered. The supervisor can describe the avoided ER visit, the stabilized staffing pattern, and the case manager coordination, but the payment model has no clear place to recognize that value. This is the tension future HCBS funding models must solve.
Funding should reward controlled risk, not only completed service activity.
Traditional cost vs outcomes review often struggles when prevention works quietly. A person remains stable, a crisis does not occur, and community life continues. Stronger funding models need to connect that stability to preventative value and early intervention, while aligning with the wider Value, Impact & System Sustainability Knowledge Hub focus on system strength, measurable impact, and long-term service sustainability.
Why future funding must move beyond activity alone
Activity-based funding is simple to count. Hours, visits, units, and tasks can be checked quickly. The problem is that HCBS value is not created only by the presence of activity. It is created when support keeps people safe, reduces avoidable escalation, maintains independence, stabilizes housing, improves health coordination, and protects continuity.
Future funding models will need to recognize the difference between low activity because a person is stable and low activity because need is hidden. They will also need to distinguish between high service intensity that prevents larger system cost and high service intensity that is not producing the expected control. This requires a stronger evidence base than billing data alone.
The most credible models will not reward providers for vague claims. They will require proof. The principle is similar to proving HCBS value without gaming the numbers: prevention, stability, and outcomes must be documented in ways funders can test.
Operational example 1: A prevention-weighted payment model
A home and community-based services provider supports adults with recurring crisis risks linked to medication disruption, behavioral health escalation, and unstable informal support. Under a traditional model, the provider is paid for authorized support hours. The funding does not clearly recognize early intervention work that prevents emergency service use.
The provider and funder pilot a prevention-weighted approach. The base authorization remains in place, but an added prevention component is tied to documented early action. The goal is not to pay for imagined savings. It is to recognize verified control activity that reduces avoidable escalation.
The workflow begins with risk identification. Supervisors and case managers agree which people meet the prevention cohort criteria. Required fields must include: baseline risk factors, prior crisis history, current support intensity, early warning indicators, supervisor review notes, case manager contacts, clinical coordination where relevant, and outcome after intervention.
Frontline staff are trained to document changes that matter: missed medication access, sleep disruption, refusal of essential routines, increased isolation, repeated cancellation of appointments, or new environmental stress. The supervisor reviews patterns within a defined timeframe and decides whether the situation requires case manager notification, clinical consultation, family contact, or a temporary support adjustment.
One person begins missing evening medication prompts after a change in pharmacy delivery. Staff identify the pattern before crisis behavior increases. The supervisor contacts the pharmacy, informs the case manager, adjusts staff reminders, and documents stabilization over the next week. Under the pilot model, this is counted as prevention evidence because the team controlled a known risk before emergency escalation.
Cannot proceed without: documented baseline risk, dated evidence of change, supervisor decision-making, and confirmation that the intervention was proportionate. Auditable validation must confirm: the prevention payment is linked to recorded action and measurable stabilization, not a general statement that support “helped.”
Operational example 2: A stability incentive for complex community support
A community-based residential services provider supports people with complex needs who are at risk of placement disruption. Historically, funding reviews have focused on whether staffing levels are high. The provider wants a fairer model that asks whether staffing intensity is maintaining community stability and preventing higher-cost system use.
The funder agrees to test a stability incentive. It does not replace base funding. Instead, it creates a structured way to recognize sustained community tenure, reduced emergency relocation, improved continuity, and effective escalation control for people with high support needs.
The provider first defines what stability means for this population. It is not the absence of every incident. For some people, value is shown through fewer high-severity incidents, faster recovery, reduced police or ER contact, fewer staff injuries, better medication adherence, and maintained participation in preferred routines. This avoids unfair comparison with lower-acuity populations.
Supervisors review each person monthly. They examine incident trends, staffing continuity, health coordination, case manager communication, family concerns, and goal progress. If incidents repeat, the question is not simply whether the service failed. Leaders ask whether the plan was followed, whether escalation thresholds were appropriate, whether staffing skill mix was sufficient, and whether the person’s support needs have changed.
For one resident, nighttime agitation increases after a roommate change. Staff document the pattern, the supervisor revises the evening routine, a behavioral health clinician is consulted, and the case manager is updated. The outcome is not immediate perfection, but severity reduces and the person remains safely in the community. The stability incentive recognizes that controlled risk and preserved placement have system value.
This model strengthens commissioner confidence because it makes high-intensity support explainable. It also protects against weak claims because the provider must show the link between staffing, decisions, evidence, and outcome movement. The model aligns with fair comparison principles described in apples-to-apples value comparison in community care, especially where acuity and risk mix differ sharply.
Required fields must include: community tenure, disruption risk, incident severity, emergency contacts, staffing continuity, supervisor decisions, plan revisions, and outcome trend. Auditable validation must confirm: stability is being measured against the person’s real risk profile and not against an unrealistic low-risk benchmark.
Operational example 3: A shared-savings model with safeguards
A regional funder wants to test a shared-savings model for HCBS providers that reduce avoidable hospital use. The idea sounds attractive, but the provider’s leadership team knows it carries risk. If poorly designed, shared savings can reward under-service, selective enrollment, or inflated claims about avoided cost.
The provider proposes a guarded model. Savings can only be considered where there is clear baseline risk, documented support activity, and reliable outcome comparison. People cannot be excluded because they are complex. The model must account for acuity, risk mix, clinical need, housing instability, and available informal support.
The operational process starts with cohort selection. The funder, provider, and case management representatives agree which population group is included. They define baseline hospital use, ER visits, crisis contacts, and service intensity over a set review period. They also agree what will not count as provider-created savings, such as unrelated hospital trends or changes caused by external eligibility shifts.
Supervisors then monitor people in the cohort through structured review. Staff record early warning signs, care plan actions, missed visits, medication concerns, and escalation outcomes. Clinical partners are involved where health risk is central. If a person avoids hospitalization after effective early action, the provider can submit the evidence for review. If a person is not hospitalized because support was reduced and need was hidden, the model must detect that through quality safeguards.
Cannot proceed without: a defined cohort, baseline utilization, agreed comparison period, risk adjustment method, quality safeguards, and documented service action. Auditable validation must confirm: any shared-savings claim is supported by evidence and does not come from reduced access, ignored need, or inappropriate service limitation.
This model gives funders a practical route to reward system value while protecting people. It also encourages providers to invest in better supervision, care coordination, documentation, and early escalation. The shared saving becomes a result of stronger service control, not a financial shortcut.
Governance requirements for future funding models
Future funding models will only be credible if governance is strong enough to protect people and prove value. Leaders should review whether incentives are changing practice in the intended way. A prevention incentive should increase early action, not paperwork. A stability incentive should improve continuity and risk control, not suppress incident reporting. A shared-savings model should reduce avoidable system cost without reducing access to necessary support.
Governance review should include finance, operations, quality, case management input, and clinical input where relevant. The review should look at outcome trends, complaints, incidents, missed visits, staffing pressure, hospitalization patterns, and authorization changes. If risk repeats, leaders must decide whether the funding model needs adjustment, whether support intensity is insufficient, or whether evidence capture is too weak to justify the claim.
This is where future payment reform becomes operational rather than theoretical. Providers must show what changed, who acted, what was recorded, what escalation occurred, and what outcome improved. Funders must be able to see that money is supporting measurable community value, not just activity volume.
Conclusion
Future HCBS funding models must reward prevention, stability, and measurable community value without weakening accountability. The strongest models will preserve base support while adding fair recognition for documented risk control, avoided escalation, community tenure, and outcome improvement.
This requires clear evidence, fair comparison, and strong governance. Providers that can connect service decisions to prevention outcomes will be better positioned to show sustainable value. Funders will gain a clearer picture of what strong community support actually prevents, protects, and improves. That is how cost vs outcomes thinking becomes a practical foundation for the next generation of HCBS funding.