Investigative research report · Interactive dashboard and scenario model
The Wait for Care
Improving timely patient access across the care continuum, with the proposed Timely Care Access Model, its operating measures, and a scenario engine for testing capacity and process decisions before they are funded.
- Primary care
- Specialty care
- Hospital care
- Research
- Accountability
- Timely care
The patient waits across organizational boundaries
A patient can get an appointment and still not receive timely care
The visit may produce an unaccepted referral, a diagnostic test that cannot be scheduled, or a hospital discharge plan that no outpatient team has agreed to carry out. Each department can record a completed task while the clinical question remains unresolved.
An investigation of access must therefore follow the patient’s need across those boundaries and ask who remained responsible when progress stopped. This dashboard turns the investigative report The Wait for Care into working tools: the Timely Care Access Model, its operating specification and measures, an episode tracer, and a scenario engine for testing capacity and process decisions. It also carries the companion CARE Index from More Capacity, Longer Waits on its own labeled tab.
The decision for healthcare leaders
Adopt a common definition of timely appropriate care, make unresolved demand visible, and pilot a connected pathway spanning primary care, one specialty, and hospital discharge.
Establish the baseline before setting improvement targets. Evaluate waiting time together with clinical safety, continuity, equity, patient burden, and workforce capacity.
National context
The queue is visible in every part of the continuum
31 days
Average new-patient wait across six specialties in 15 large metros in 2025, the longest in the survey’s history.
AMN Healthcare 2025 survey, as reported in More Capacity, Longer Waits.
34.8%
Share of 103,737 referral scheduling attempts across a 34-clinic network with a documented completed visit.
Patel et al., JGIM 2018 (single system, historical).
25%+
Admitted ED patients boarding 4 hours or longer in non-peak months, rising to about 35 percent in winter.
Janke et al., Health Affairs 2025, as reported in More Capacity, Longer Waits.
29.7%
U.S. adults reporting no usual source of care in 2023, with 13.9 percent of children.
Milbank Memorial Fund 2026 Primary Care Scorecard.
Three investigative questions
What an institutional investigation should ask first
Where does elapsed time accumulate?
Reconstruct the patient-level chronology from the original request, not from the most recent booking.
Which patients fail to receive the intended care?
Averages calculated only among completed appointments exclude people still in the queue or who abandoned the process.
What happened to their clinical needs while they waited?
Administrative closure can obscure failure when staff mark a referral complete after unanswered calls.
Working definition
Timely access is completion, not a booked slot
The report defines timely access as completion of a clinically appropriate action within a prospectively documented timeframe, with an accountable team responsible for communication and follow-through. Timeliness is conditional on need. An emergency, a time-sensitive diagnostic concern, a routine consultation, and planned surveillance require different pathways.
The investigative hypothesis is that some delay comes from insufficient staffed capacity, while another portion comes from how existing capacity is organized and how work passes between teams. These causes require different responses, which is why the Scenario Model tab separates structure changes from process changes.
The proposed Timely Care Access Model
Six operating functions connected through a shared episode record
Primary, specialty, and hospital services are routes within a network. Patients may enter any route, move between them, or require several in parallel. Emergency escalation bypasses routine scheduling and authorization workflows. Select any function or route to see its required action, accountable role, and the evidence that it was completed.
A shared episode record preserves the original request time across all services.
Operating function
Recognize the need
Register the request once and capture barriers and contact preferences.
- Required action
- Register the request once; capture barriers and contact preferences.
- Accountable role
- Intake lead
- Completion evidence
- Episode ID and original timestamp
Figure 3. Conceptual architecture of the Timely Care Access Model. Original conceptual synthesis informed by Levesque et al. (2013), the Institute of Medicine (2015), and the evidence reviewed. Arrows show possible handoffs, not mandatory progression or a validated causal model.
Table 1. Minimum operating specification for each access function
| Function | Required action | Accountable role | Completion evidence |
|---|---|---|---|
| Recognize need | Register the request once; capture barriers and contact preferences. | Intake lead | Episode ID and original timestamp |
| Assess urgency | Clinical review sets route, due time, and safety instructions. | Designated clinical reviewer | Priority, rationale, reviewer, due time |
| Arrange care | Receiving service accepts; match capacity and address barriers. | Access coordinator with service lead | Named receiving team and agreed next step |
| Deliver care | Complete the appropriate assessment, advice, test, or treatment. | Treating clinical team | Qualifying clinical event and timestamp |
| Confirm follow-through | Review results; inform patient; confirm next owner and actions. | Current episode clinical owner | Communicated plan and acknowledged handoff |
| Review results | Examine delays, failed access, equity, safety, and workload. | Executive access council | Actions with owners and review dates |
Source: The Wait for Care, Table 1.
Operational ownership
The access coordinator tracks progress and removes administrative barriers. The sending service follows up when it does not receive acknowledgment, and retains coordination responsibility until acceptance is confirmed.
A scheduling status alone cannot transfer clinical responsibility.
Clinical responsibility
The designated clinician decides urgency and appropriateness. A scheduler should not independently downgrade risk because a preferred appointment is unavailable. Acceptance establishes the receiving team’s obligations, including who will respond to new symptoms or new results.
The minimum episode record
An episode contains one index clinical need and can include multiple linked tasks. The original timestamp remains unchanged when a task is rerouted, rescheduled, or transferred. A separate audit trail records changes, the reason, and the person authorizing them.
- Episode identifier
- Request time
- Clinical question
- Route
- Original due time
- Current due time
- Priority
- Accountable people
- Service events
- Barriers
- Contact attempts
- Patient preferences
- Results
- Disposition
The minimum viable implementation can use existing referral and scheduling systems with a shared worklist and governed reporting layer. A new dashboard does not create access by itself.
Episode tracer
The original request time never resets
The proposed model retains the original request timestamp even when responsibility changes. It records the interval to a first qualifying clinical action and the longer interval to a communicated plan or documented resolution. A dashboard that restarts the clock at each rebooking can report an episode as on time when the patient has waited weeks past the clinical window. Trace one hypothetical episode below, then change the dates.
Trace one episode
All inputs are days counted from the original request (day 0). Defaults are hypothetical.
Episode timeline (days from original request)
- Original request and events
- Clinical due date
- Interval a reset clock would report
Original clock (Timely Care Access Model)
Request to qualifying service
41 days
Due day 32
Request to communicated plan
49 days
Includes result review and patient communication
Reset clock (what many dashboards report)
Booking to visit
17 days
Reported as on time
Elapsed time hidden
24 days
Waiting the patient experienced but the report omits
Reporting conflict. The reset clock reports this episode as on time while the original clock shows it overdue.
First qualifying action
The predefined clinical service that counts as care delivered for this pathway. An acknowledgment, a scheduled slot, or an unanswered advice message alone does not count.
Clinical resolution
The presenting question has an agreed disposition or ongoing management plan. It does not imply a cure. Diagnostic steps, treatment, and follow-up can remain active after the first appointment.
Original and revised deadlines
Report performance against original and revised deadlines side by side. A revised deadline needs a clinical reason, a named authorizer, and an audit trail entry.
Triage and commitments
Commitments must reflect clinical need
The research reviewed does not establish one safe deadline for every complaint. The priority structure below is an operating design requiring local clinical approval, not a medical triage algorithm. Clinical leaders approve condition-specific criteria, local coverage, reassessment intervals, and escalation responsibility.
Priority structure
Select a priority to see its scheduling commitment and protection rule (Table 2).
Scheduling commitment
Immediate clinical assessment and emergency routing under established protocols.
Escalation and protection
Do not place in the routine queue or await routine authorization.
Table 2. Proposed priority structure requiring local clinical approval
| Priority | Scheduling commitment | Escalation and protection |
|---|---|---|
| Emergency | Immediate clinical assessment and emergency routing under established protocols. | Do not place in the routine queue or await routine authorization. |
| Time sensitive | Condition-specific deadline selected by qualified clinicians. | Escalate threatened deadlines before expiry; arrange a safe alternative. |
| Routine | Prospectively agree a clinically acceptable window and patient preferences. | Track original request age; offer alternatives with informed agreement. |
| Planned follow-up | Book against a clinical recall or surveillance due date. | Do not repeatedly postpone planned care to accommodate new requests. |
| Changing or uncertain need | Prompt qualified review determines or revises the route. | Reassess new information; retain the original deadline and revision history. |
Source: The Wait for Care, Table 2.
Is this delay voluntary?
A patient elects a later date than the earliest suitable offer. Choose the reason the patient gave.
Recorded preference
Record the offer, the preference, and the agreed plan without deleting elapsed time. Review the clinical suitability of the later date if risk could change.
Receiving alternative
If the organization cannot meet the clinical window, escalation identifies another service able to accept the patient within the window.
Revised, clinically justified plan
A qualified clinician documents why a later date is safe, with the revision and its authorizer kept in the audit trail.
Immediate assessment
When necessary, the patient is assessed now. Promising a date without staffed capacity creates an unsafe expectation.
Measure timely care without hiding unresolved demand
Eight core measures, reviewed side by side
The Timely Care Access Model avoids a single composite access score in its first version, because a weighted index can make deterioration in one service disappear behind improvement in another. Present the core measures together, retain service-specific detail, and compare like urgency categories. Select a measure to read its definition and reporting safeguard.
On-time appropriate care
- Operational definition
- Episodes with a predefined qualifying clinical service completed by the original due time, divided by all eligible episodes due in the period.
- Reporting safeguard
- Open overdue and failed-access episodes remain in the denominator. Report missing due times separately.
Denominator honesty check: on-time appropriate care
Enter one period’s episodes. The calculator applies the model’s denominator rule and shows what a completed-only report would claim. Defaults are hypothetical.
Completed care
Unresolved and other dispositions (stay in the denominator)
Reported separately
On-time appropriate care
63.5%
612 of 964 eligible episodes
Completed-only report
80.5%
Overstates by 17.0 points
Unresolved demand
96
Open episodes past due
Missing due time
2.4%
Data-quality review required
Where the eligible episodes went
Referral follow-through
Receipt of a specialist note is only one checkpoint. Enter referral episodes due for completion in the period. Defaults are hypothetical.
Referral follow-through
52.5%
All three checkpoints complete
Largest loss
100
Before specialty input
Advice-only share of input
23.3%
Report separately from in-person care
Referral follow-through funnel
External completion should be confirmed rather than automatically classified as failure because a local appointment record is absent.
Table 3. Proposed core measures and denominator rules
| Measure | Operational definition | Reporting safeguard |
|---|---|---|
| On-time appropriate care | Episodes with a predefined qualifying clinical service completed by the original due time / all eligible episodes due in the period. | Open overdue and failed-access episodes remain in the denominator. Report missing due times separately. |
| Elapsed time | Original request to qualifying service; separately, original request to communicated episode plan or resolution. | Median and 90th percentile among completed episodes, paired with open-episode age and overdue counts. |
| Unresolved demand | Count and age of active episodes, including those overdue for the next clinical action. | Show entries, completed care, other dispositions, and reopening; never use closure alone as success. |
| Referral follow-through | Episodes with completed specialty input, reviewed recommendation, and patient communication / referral episodes due for completion. | Separate advice-only resolution from in-person care still required and from external completion. |
| Primary care availability | Third next available suitable appointment by visit type and continuity option. | Snapshot supply measure; pair with actual patient waits and unsuccessful requests. |
| Hospital transition times | Admission decision to inpatient management and to bed transfer; discharge to required completed follow-up. | Keep intervals separate; report clinical route, urgency, and overdue follow-up. |
| Patient burden and equity | Reported attempts, travel, cost barriers, and understanding; on-time rates by relevant population groups. | Use consistent eligibility, review missing data, protect small cells, and show group denominators. |
| Safety and capacity | Delay-related incidents, deterioration while waiting, return visits, continuity, overtime, inbox work, and staffed capacity. | Use clinical review and case-mix context; do not treat all return visits as caused by access failure. |
Source: The Wait for Care, Table 3.
Scenario model
Test structure and process before funding either
Waiting lists grow when incoming work exceeds completed work over time. The engine applies the report’s accounting identity week by week: next backlog = current backlog + new eligible requests − completed care − separately documented other dispositions. It adds two mechanisms from the companion research: usable capacity is smaller than nominal slots, and no-shows rise with lead time, which can tip a queue from manageable to runaway. Four scenarios follow the Emrick SPO discipline: baseline, structure-only, process-only, and combined.
Access flow simulator
Choose a starting preset, then edit any assumption. All four scenarios recalculate together.
Hypothetical primary care clinic operating near its capacity threshold.
Route assumptions
Structure lever
Process levers
Baseline
0
open episodes at end
Structure-only
0
open episodes at end
Process-only
0
open episodes at end
Combined
0
open episodes at end
Persistent demand and capacity deficit. Even the combined scenario ends with demand above effective capacity.
SPO discipline.
Open episodes by week, four scenarios
- Baseline
- Structure-only
- Process-only
- Combined
Estimated queue time at end of horizon (days)
Little’s Law estimate: open episodes divided by weekly completions, times 7. Excludes later dates patients choose.
| Scenario | Open at end | Change | Queue time (days) | Demand to effective capacity | No-show rate at end | Completed per week |
|---|---|---|---|---|---|---|
| Baseline | 0 | 0 | 0 | 0 | 0 | 0 |
Why queues tip near capacity
Illustrative single-server queueing relationship from standard theory (relative wait = utilization / (1 − utilization)). It is not calibrated to any clinic. The marker shows the baseline demand to effective capacity ratio, capped at 0.97 for display.
Nominal slots are not usable capacity
Nominal slots per week
0
Usable slots
0
Effective after no-shows
0
Baseline, final week
Review repeat contacts, returned referrals, avoidable rebooking, and canceled sessions before interpreting demand as entirely new work. Some improvements will require additional clinical capacity, extended coverage, or external partnerships; make those requirements explicit rather than absorbing them as unpaid work.
Time released is not yet capacity
Staff time released becomes capacity only if it can be deployed to needed work. Rebuild templates around the time a tool frees, or the gain disappears.
Better referral completion can raise demand
An intervention that improves referral completion can initially increase specialty demand, exposing previously unmet need. That is not necessarily failure.
Advanced access has a limit
Responsive scheduling fails if demand permanently exceeds capacity (Murray and Berwick 2003). The persistent deficit preset shows that case.
Companion composite from More Capacity, Longer Waits
The Emrick CARE Access Model and CARE Index
CARE (Continuum Access Reliability for the Enterprise) scores five layers of the patient’s path and absorbs three existing Emrick frameworks without changing their formulas: the Front Door Reliability Score (FDRS) feeds the front door layer, the Diagnostic Access Equity Index (DAEI) is the diagnostic layer, and the SPO model is the scenario engine.
Front Door Reliability Score
FDRS = 0.30 Experience + 0.40 Access + 0.30 Throughput, less 2.5 x max(0, (portal share − assisted support share − 20) / 100).
Weighted sum
8.07
Friction penalty
0.25
FDRS
7.82
x 10 = 78.2 in Layer F
Diagnostic Access Equity Index
DAEI = 0.20 Geography + 0.25 Timeliness + 0.20 Affordability and administration + 0.20 Diagnostic closure + 0.15 Equity.
DAEI (Layer D)
65.7
Generally stable
Layer D score 65.7
Domains under 50
Equity
DAEI concealment check
CARE metrics
Each metric converts to 0 to 100 by linear interpolation between its floor (score 0) and target (score 100), capped at both ends.
F. Front door and primary care (layer weight 0.25) 0
78.2
Within-layer weight 0.40. Score 0R. Referral and specialty handoff (0.20) 0
H. Hospital throughput (0.25) 0
N. Navigation, coverage, and network integrity (0.15) 0
CARE Index
Band
Strained
Recurrent queue failures at one or more handoffs.
CARE Index = 0.25 F + 0.20 R + 0.15 D + 0.25 H + 0.15 N
Layer scores, composite, and strata on the band scale
Concealment warning
The composite reads Strained or better while the conditions below are true. This warning cannot be suppressed.
Equity strata
Every metric and the composite are reported by payer, race and ethnicity, preferred language, rurality, and disability, plus age group and behavioral health diagnosis. Enter stratum layer scores.
Stratum A (worked example)
Stratum B (optional, hypothetical values)
Concealment rule: when the composite is 50 or above, a warning fires if (a) any reported stratum scores 10 or more points below the composite or falls one or more bands lower, (b) any enterprise layer is under 50, or (c) any DAEI domain is under 50. Strata with fewer than 30 episodes are combined over a longer window rather than dropped.
CARE maturity model and alignment with FDRS and DAEI
| CARE level | Description | Typical FDRS band | Typical DAEI maturity level |
|---|---|---|---|
| 1. Siloed | Each department owns its own queue; wait data are anecdotal; no closed-loop referral tracking | Reactive | Departmental |
| 2. Measured | Standard definitions (TNAA, request-to-appointment, ECAT components) reported monthly | Defined | Accessible |
| 3. Orchestrated | Referral closure tracked end to end; command function spans ambulatory and inpatient flow; SPO scenarios precede capacity decisions | Standardized | Integrated |
| 4. Equity-accountable | All metrics stratified; concealment warnings drive resource allocation; executive compensation tied to strata gaps | Optimized | Equity-managed |
| 5. Anticipatory | Predictive demand and no-show models, coverage-risk forecasting, and surge plans adjust capacity before queues form | Adaptive | Population-optimized |
An enterprise cannot claim a level until it meets every lower level. Source: More Capacity, Longer Waits, Table 5.
Leading indicators and escalation triggers
| Leading indicator | Trigger | Required response |
|---|---|---|
| Clinic TNAA (weekly) | Rises 2 consecutive weeks, or exceeds 7 days for new visits | Backlog burn-down plan; release held slots; SPO process-only scenario |
| No-show rate in appointments booked more than 14 days out | Exceeds 1.5 times the same-week rate | Shorten lead time; targeted risk-tier reminders |
| Referral-to-scheduled interval | Median over 5 business days in any specialty | Navigator escalation; eConsult routing review |
| Adult inpatient occupancy | 85 percent or more on 3 consecutive days | Surge protocol; elective smoothing review; hospital at home intake |
| Admitted boarding more than 4 hours | Above 25 percent for a week | Command center bed huddle; discharge-before-noon push |
| Avoidable days | Any patient medically ready more than 24 hours without discharge | Daily post-acute and payer escalation |
| Prior authorization clock breaches | Any breach of the 72-hour or 7-day CMS-0057-F clocks | Payer escalation log; regulatory complaint pathway |
| Coverage renewal due list | Attributed patients with a Medicaid renewal due within 60 days | Proactive renewal assistance before scheduled specialty or imaging care |
| ED self-pay share | Rises 1 point in a quarter | Financial counseling at the front door; presumptive eligibility screening |
| Directory verification failures | More than 10 percent of a specialty’s listings fail secret shopper | Remove or correct listings; recompute effective network |
Source: More Capacity, Longer Waits, Table 4.
Evidence
What the research supports, and how strongly
The published evidence supports several components of a stronger access system, but it does not validate the combined model or identify one optimal configuration. Interactive rebuilds sit above each published figure; open the figure to compare.
Figure 1. Findings in an advanced access review (study counts)
- Favorable and statistically significant
- Other favorable finding
- No favorable finding
Adadja et al. (2026), 29 studies. Counts are not effect sizes or certainty ratings. Bar segments measured from the published figure.
Figure 2. Individualized discharge planning compared with routine discharge
Gonçalves-Bradley et al. (2022), Cochrane review. Separate panels use different units; dashed lines mark no difference. The readmission result is a relative effect, not an 11 percentage-point absolute reduction.
National context from More Capacity, Longer Waits
New-patient wait by specialty, 2025 (days)
AMN Healthcare 2025 survey, 15 large metros. OB/GYN and cardiology approximately 42 and 33 days.
eConsult and eReferral: days to first specialty visit
Chen et al., NEJM 2013; NYC Health + Hospitals (internal data, not peer reviewed); AJMC 2019.
The referral funnel: of 100 referrals
Weiner et al. 2010 (urban academic primary care, patients 65 and older). Duke network: 34.8 percent documented complete; completed referrals waited 20.1 days versus 41.7 days for incomplete ones (Patel et al. 2018).
No-shows rise with lead time
Green and Savin 2008 source data: about 4 percent same day, about 37 percent at 60 or more days. Only these two published points are shown.
20%
Adults 65 and older with ED stays over 8 hours in 2024, up from 12 percent in 2017 (Haimovich et al. 2025).
781,000
Unnecessary hospital days in Florida’s 2025 survey of 95 hospitals, about 2,140 beds occupied year-round (Florida Hospital Association).
96
Labor and delivery unit closures from January 2024 to May 2026, adding about 25 minutes of travel (March of Dimes 2026).
Table 6. Selected evidence and its role in the proposed model
| Source | Design and scope | Contribution | Key limitation |
|---|---|---|---|
| Levesque et al., 2013 | Conceptual access framework | Access includes the ability to reach and use care. | Framework rather than intervention evaluation. |
| Adadja et al., 2026 | Systematic review; 29 studies | Responsive primary care scheduling. | Heterogeneous designs; limited ED evidence. |
| Engström et al., 2025 | Systematic review of personal continuity | Protect continuity alongside speed. | Much evidence is observational. |
| Peeters et al., 2024 | Systematic review; 72 studies | Specialist advice and referral design. | Low or very low certainty; heterogeneous endpoints. |
| Olayiwola et al., 2016 | Cluster-randomized cardiology study | Separate advice from visit pathways. | One setting and specialty; pathway selection matters. |
| Patel et al., 2018 | Single-system referral analysis | Track the full referral process. | Historical and not nationally representative. |
| Janke et al., 2026 | Multicenter observational study | Measure inpatient management handoff. | Variation does not establish effects of a repair. |
| Gonçalves-Bradley et al., 2022 | Cochrane review; 33 trials overall | Individualized discharge planning. | Predominantly older medical patients; costs uncertain. |
| Murphy et al., 2026 | Systematic review; 25 studies | Track authorization-related barriers. | Total attributable harm remains uncertain. |
| W. C. Chen et al., 2025 | Radiation oncology quality improvement | Improve authorization information flow. | Nonrandomized and setting-specific. |
| D. W. Chen et al., 2025 | Cross-sectional portal assessment | Provide multilingual entry routes. | Login accessibility rather than clinical outcomes. |
| M. Chen et al., 2024 | Cancer navigation systematic review | Address patient-specific barriers. | Oncology evidence requires adaptation elsewhere. |
| Vakkalanka et al., 2026 | Matched Medicare comparison | Consider selected home-care options. | Residual selection and confounding possible. |
Source: The Wait for Care, Table 6. Showing 13 of 13 sources.
A practical pilot and evaluation plan
Begin with one bounded pathway that crosses settings
A primary care referral to cardiology, followed when appropriate by diagnostic testing, hospitalization, and outpatient follow-up, is one possible pilot. Include patients managed without hospitalization, or the project selects only a subset of the access journey. Ninety days is a practical launch period, not proof of long-term effectiveness.
Days 1 to 30
Select one primary, specialty, and discharge pathway; reconcile records; map barriers; establish baseline and clinical timing rules.
Leads: clinical sponsor, operations, analytics, patient partners.
Decision evidence: agreed cohort, reliable timestamps, denominator rules, capacity assessment.
Days 31 to 60
Pilot intake, triage, receiving-team acknowledgment, navigation, and daily overdue review.
Leads: service leads and access coordinator.
Decision evidence: documented ownership; unresolved episodes reviewed; safety issues acted on.
Days 61 to 90
Refine templates and handoffs; compare with baseline and a suitable comparison service where feasible.
Leads: quality and analytics with clinical leads.
Decision evidence: timeliness, continuity, equity, workload, and safety reviewed together.
After day 90
Continue observation and extend only if results and resources support it.
Lead: executive access council.
Decision evidence: sustained improvement, adequate follow-up, and no unacceptable balancing harm.
Source: The Wait for Care, Table 4. A proposed implementation sequence rather than externally validated deadlines.
Local investigation checklist
Records and interviews needed to test the model locally (Table 5). Check each item as it is obtained.
0 of 18 evidence items obtained
Where is time lost?
Who does not reach care?
Is capacity insufficient?
Who is accountable at a handoff?
Whose barriers remain unresolved?
Did improvement cause better outcomes?
The executive access council
Resolves conflicts that individual departments cannot settle. It approves measure definitions and capacity decisions, reviews safety signals, and assigns responsibility for failed handoffs. An operational huddle addresses today’s unresolved work; a monthly review examines recurring causes and resource needs.
- Executive operations
- Primary care
- Specialty care
- Hospital medicine
- Nursing
- Scheduling
- Revenue cycle
- Quality
- Analytics
- Patient representation
Build the business case honestly
Include navigation, clinical triage, specialist advice, interpreter services, data maintenance, patient travel, and the burden placed on families. Keep four quantities separate:
- Cash expenditure
- Staff time released
- Usable clinical capacity
- Potential avoided utilization, which stays a scenario until measured with an appropriate comparison
Run charts first
Retrieve several months of historical data when reliable. Use weekly run charts initially rather than treating the first month as a sufficient baseline.
Interrupted time series
When data support it, test whether changes exceed prior trends with adequate pre- and post-intervention observations. A comparable service strengthens interpretation.
Fidelity and effectiveness
Did the receiving team acknowledge ownership, address barriers, and review overdue episodes? A negative result may reflect design, capacity, or inconsistent implementation.
References
Sources for both reports
The Wait for Care lists 14 peer-reviewed and authoritative sources. More Capacity, Longer Waits lists 126 sources for its national evidence and the CARE model, numbered as in that report.
- The Wait for CareAdadja, J., Lafrance, S., Gnanvi, J., Bergeron, F., Boutin, A., Breton, M., Guertin, J. R., & Berthelot, S. (2026). Association of advanced access with primary care performance: A systematic review. Annals of Family Medicine, 24(3), 239-251. https://doi.org/10.1370/afm.250593
- The Wait for CareChen, D. W., Watanabe, M., Xie, S., Huston-Paterson, H. H., Banerjee, M., & Haymart, M. R. (2025). Language barriers and access to hospital patient portals in the US. JAMA Network Open, 8(10), e2537864. https://doi.org/10.1001/jamanetworkopen.2025.37864
- The Wait for CareChen, M., Wu, V. S., Falk, D., Cheatham, C., Cullen, J., & Hoehn, R. (2024). Patient navigation in cancer treatment: A systematic review. Current Oncology Reports, 26(5), 504-537. https://doi.org/10.1007/s11912-024-01514-9
- The Wait for CareChen, W. C., Carpenter, C., Sidiqi, B., Pattison, A. J., Hwang, J., Pappas, D., & Potters, L. (2025). Integrating prior authorization into clinical workflows to improve care access and the practitioner experience. JAMA Network Open, 8(12), e2549093. https://doi.org/10.1001/jamanetworkopen.2025.49093
- The Wait for CareEngström, S. G., André, M., Arvidsson, E., Östgren, C. J., Troein, M., & Borgquist, L. (2025). Personal GP continuity improves healthcare outcomes in primary care populations: A systematic review. British Journal of General Practice, 75(757), e518-e525. https://doi.org/10.3399/BJGP.2024.0568
- The Wait for CareGonçalves-Bradley, D. C., Lannin, N. A., Clemson, L., Cameron, I. D., & Shepperd, S. (2022). Discharge planning from hospital. Cochrane Database of Systematic Reviews, 2022(2), CD000313. https://doi.org/10.1002/14651858.CD000313.pub6
- The Wait for CareInstitute of Medicine. (2015). Transforming health care scheduling and access: Getting to now. The National Academies Press. https://www.nationalacademies.org/read/20220
- The Wait for CareJanke, A. T., Haimovich, A. D., Cussen, M., Fung, C. M., Samuels-Kalow, M. E., Baymon, D. E., Berlyand, Y., Burke, L. G., Patterson, B. W., Hekman, D. J., Copenhaver, M. S., Niforatos, J. D., Sabbatini, A. K., Hall, M. K., Hwang, U., Sifnugel, N., Sangal, R. B., Venkatesh, A. K., Glass, G., … Friedman, A. B. (2026). Time to inpatient management for boarding emergency department patients. JAMA, 336(11), 976-979. https://doi.org/10.1001/jama.2026.13302
- The Wait for CareLevesque, J.-F., Harris, M. F., & Russell, G. (2013). Patient-centered access to health care: Conceptualizing access at the interface of health systems and populations. International Journal for Equity in Health, 12, Article 18. https://doi.org/10.1186/1475-9276-12-18
- The Wait for CareMurphy, J., Beauchamp, N., Sun, K. J., Lau, B. D., Wilson, R. F., Lobner, K., Conway, S. J., Hill, P. M., & Johnson, P. T. (2026). Adverse effects of health plan prior authorization on clinical effectiveness and patient outcomes: A systematic review. The American Journal of Medicine, 139(1), 24-32.e1. https://doi.org/10.1016/j.amjmed.2025.08.018
- The Wait for CareOlayiwola, J. N., Anderson, D., Jepeal, N., Aseltine, R., Pickett, C., Yan, J., & Zlateva, I. (2016). Electronic consultations to improve the primary care-specialty care interface for cardiology in the medically underserved: A cluster-randomized controlled trial. Annals of Family Medicine, 14(2), 133-140. https://doi.org/10.1370/afm.1869
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