Video Images About Decisions for Ethical Outcomes in the Emergency Department (VIDEO-ED): Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Video Images About Decisions for Ethical Outcomes in the Emergency Department (VIDEO-ED) (NCT04931797), a randomized na study. The primary outcome is Number of Participants With EHR Documentation of Advance Care Planning at 3 Months.

2. Clinical Question

The trial title is Video Images About Decisions for Ethical Outcomes in the Emergency Department (VIDEO-ED), and its official title is Using the Emergency Department Visit to Promote Advance Care Planning. The registry describes a randomized controlled trial of a video decision aid in the emergency department setting, with the aim of improving advance care planning documentation. The result therefore addresses a specific documentation outcome at a stated follow-up time; it should not be treated as a direct measure of every aspect of advance care planning or subsequent care.

3. Trial Design

The registry describes VIDEO-ED as a randomized, single-masked, parallel-group trial. It lists the phase as NA and records enrollment of 598. The sponsor is Massachusetts General Hospital. The listed study start date is 2022-04-25, the primary completion date is 2025-06-10, and the status is completed. Who was masked is not reported in the registry record.

Participants were assigned to a video arm or a control arm. The video arm is described as receiving a video decision aid and an advance care planning discussion. The control arm is described as receiving usual advance care planning services at the study site. Although an advance care planning information sheet appears in the intervention listing, the registry’s arm description for the control group refers to usual services; the record does not explain the relationship between those descriptions in further detail.

The primary outcome was the number of participants with EHR documentation of advance care planning at 3 months, assessed by Natural Language Processing. The registry also lists secondary outcomes concerning patient preferences for goals of care, concordance between stated and documented preferences, EHR documentation, patient knowledge, and engagement with advance care planning topics. Follow-up timing varies by outcome. The record does not report further details of random sequence generation, allocation concealment, masking procedures, or the trial’s original sample-size justification. Those design details should not be inferred from the posted group counts or results.

4. Participant Flow and Accounting

The registry reports how participants moved through each stage of the study. All counts below are exactly as posted; missing counts are not inferred from other stages.

Before assignment: 598 were enrolled (two were excluded due to protocol violation \[one was erroneously enrolled twice and one was ineligible per eligibility criteria\]).

Overall Study

5. Baseline Characteristics

The table reproduces the baseline characteristics posted in the registry, which describe the participants analysed at baseline and help show whether the randomized groups were comparable.

Population: 598 participants were enrolled and analyzed (two were excluded due to protocol violation; one was erroneously enrolled twice and one was ineligible per eligibility criteria).

6. Primary Endpoint

The registry lists the primary outcome as Number of Participants With EHR Documentation of Advance Care Planning at 3 Months, measured over 3 months.

The primary endpoint is the number of participants with EHR documentation of advance care planning at 3 months. The registry says that documentation was assessed using Natural Language Processing. The reported outcome is a count of participants with documentation, not a score or a time-to-event measure.

This endpoint is relevant to the stated trial aim because the study was designed to examine whether an emergency department decision aid could promote advance care planning documentation. EHR documentation provides a record-based measure that can be assessed across trial arms. It does not, by itself, establish whether a recorded preference accurately reflects a participant’s current wishes, whether clinicians accessed or followed the record, or whether care was concordant with preferences. Those are distinct questions, and the registry separately lists concordance between stated and documented preferences as a secondary outcome.

The choice of a 3-month assessment sets a defined time point for the primary comparison. The registry record does not describe the precise Natural Language Processing procedure, how ambiguous records were handled, or whether documentation outside the EHR was captured. Such details matter when interpreting the endpoint: the result concerns documentation detected under the stated assessment method and does not necessarily capture all advance care planning activity.

7. Results Posted in the Registry

• Video: 45.6% (136/298) versus 31.3% (94/300) on control; risk difference 14.3 percentage points (95% CI 6.6 to 22.0), risk ratio 1.46 (1.18–1.79); unadjusted two-proportion z-test p = <0.001.

8. Secondary Efficacy Endpoints

The registry also posts results for secondary outcomes. For each outcome below, the endpoint type, the test applied to the posted summary statistics, the result and its interpretation are given in turn. Secondary endpoints are usually not adjusted for multiple testing, so they support rather than confirm the primary finding.

Concordance Between Stated and Documented Preferences

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Video: 73.6% (39/53) versus 36.6% (15/41) on control; risk difference 37.0 percentage points (95% CI 18.1 to 55.9), risk ratio 2.01 (1.30–3.10); unadjusted two-proportion z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Video than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

ACP Documentation in the EHR

• Endpoint type: Binary: the number of participants with the event, compared as proportions.
• Test: Unadjusted two-proportion z-test, with a Wald 95% confidence interval for the risk difference.
• Result:
  • Video: 52.3% (156/298) versus 39.3% (118/300) on control; risk difference 13.0 percentage points (95% CI 5.1 to 20.9), risk ratio 1.33 (1.11–1.59); unadjusted two-proportion z-test p = 0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for Video than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

Patient Knowledge of ACP

• Endpoint type: Continuous: a mean value per participant, compared as a difference in means.
• Test: Unadjusted two-sample z-test for the difference in means, using the posted standard deviations.
• Result:
  • Video: mean 4.10 versus 3.10 on control; difference 1.00 (95% CI 0.83 to 1.17), standardized effect d = 0.95; z-test p = <0.001.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the mean is statistically higher for Video than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The posted secondary findings point in a direction consistent with the primary result: the video arm had more EHR documentation at the later assessment, higher concordance between stated and documented preferences, and a higher mean knowledge score at the stated assessment. These outcomes address related but distinct aspects of advance care planning. Documentation is a record-based outcome, concordance concerns agreement between expressed and documented preferences, and knowledge concerns understanding as measured by the study’s score.

This overall pattern gives context to the primary documentation result, but the outcomes are not interchangeable. A difference in documentation does not automatically imply a difference in concordance or knowledge, and a knowledge score does not establish that preferences were documented or followed. Timing also differs: the record describes the concordance outcome at 6 months, EHR documentation at 6 months, and knowledge at baseline for the control arm and immediately after the video decision aid at Day 1 for the video arm. These contrasts should be interpreted according to their own measurement and timing.

Unadjusted secondary results carry less weight because multiple outcomes and analyses create more opportunities for apparently notable findings. The registry record does not report a multiplicity adjustment or a hierarchy for interpreting secondary outcomes. Without such information, the p-values should be treated as exploratory or supportive rather than as a set of independently confirmatory tests. The number of outcomes considered also makes it important to avoid selecting only the results that appear most favorable.

The registry lists additional secondary outcome domains, including patient preferences for goals of care and patient engagement with advance care planning topics. Results for those domains are not detailed in the outcome records, so no direction or magnitude should be inferred for them. Taken together, the posted secondary findings are compatible with the primary documentation result, while leaving unanswered whether those changes translated into care that matched participants’ preferences.

Secondary outcomes registered for this trial, for reference (only those above were recalculated):

• Patient Preferences for Goals of Care
• Concordance Between Stated and Documented Preferences
• ACP Documentation in the EHR
• Patient Knowledge of ACP
• Patient ACP Engagement With ACP Topics

9. Statistical Interpretation

10. Statistical Methods Explained

For binary outcomes, the reported quantity is a difference between the proportions of participants with the event in the two arms, expressed in the registry analysis as a risk difference. General explanation: a risk difference describes an absolute contrast in event occurrence between groups. Unlike a relative measure, it is expressed on the same scale as the underlying proportions and can be understood as the difference in frequency between arms. The sponsor reports the primary risk difference as 14.3, with a 95% confidence interval from 6.6 to 22.0.

What does Fisher Exact mean?

The sponsor’s primary analysis is listed as Fisher Exact. General explanation: Fisher’s exact test evaluates evidence against a null hypothesis of no association between group assignment and a binary outcome, using the observed counts and group sizes. It is a test-based method for categorical data. The registry reports p < 0.001 for the primary comparison. A p-value is not the probability that the null hypothesis is true, nor does it describe the magnitude or practical importance of the observed difference. The risk difference and its confidence interval convey magnitude and uncertainty more directly.

How should the confidence interval be read?

General explanation: a confidence interval represents a range of values compatible with the observed data and the analysis procedure, under its assumptions. It is not a guarantee that the true effect lies within that particular interval. For the primary result, the sponsor reports a 95% interval from 6.6 to 22.0 for the risk difference. Because this interval does not include zero, it is consistent with a positive difference under the reported analysis. The interval’s width also matters: it indicates uncertainty about the size of the contrast, not merely whether the contrast is positive or negative.

What does the recalculation add?

A recalculated estimate based on posted summary statistics is an unadjusted comparison, not a replacement for the sponsor’s analysis. The registry records no discrepancy for the primary outcome, and the sponsor’s reported risk difference and interval agree closely with the simple recalculation after rounding. Where the sponsor reports its own analysis, that analysis takes precedence. These calculations do not reconstruct an adjusted model or account for participant-level information that is not in the registry record.

How do continuous outcomes differ?

The posted knowledge outcome is continuous and is reported as a mean with a standard deviation. The sponsor used a two-sided t-test and reported a mean difference of 1.0, with a 95% confidence interval from 0.9 to 1.2 and p < 0.001. General explanation: a mean difference compares the average scores between groups, while the standard deviation describes variation among individual scores within a group. A t-test assesses evidence about a difference in means under its assumptions. The registry record does not report further details about the score’s scale or its validation.

Why can over-dispersion matter?

General explanation: over-dispersion occurs when observed variability is greater than a statistical model assumes. If a model assumes less variability than is present, standard errors can be too small and uncertainty can be understated. This issue is relevant to some count or clustered-data models, but the primary endpoint is listed as a binary participant count and the reported sponsor method is Fisher Exact. The registry does not report an over-dispersion model or a need for one; it would be inappropriate to infer such a concern from these results.

Across all methods, the distinction between a descriptive contrast and an inferential test is important. The group counts describe the posted observations; the risk difference summarizes the contrast; the confidence interval characterizes uncertainty under the analysis; and the p-value assesses compatibility with a null model. None of these quantities alone establishes the broader clinical meaning of documentation or addresses unreported design and analysis choices.

11. Confidence Intervals and Precision

The primary estimate is reported as a risk difference of 14.3, with a 95% confidence interval from 6.6 to 22.0. The interval is entirely on the positive side of zero, so the reported result supports a positive difference in documentation between the arms under the sponsor’s analysis. Its endpoints also show that the exact magnitude remains uncertain: the data are compatible with a range of positive differences, rather than one precisely known value.

General explanation: confidence intervals express statistical uncertainty around an estimate. A narrower interval generally indicates greater precision, while a wider interval indicates more uncertainty about the size of the effect. Precision is distinct from bias: an estimate can be precise yet systematically biased, or imprecise without being biased. The registry information alone does not resolve all possible sources of bias, including how missing outcome data were handled.

The primary confidence interval is based on the sponsor’s Fisher Exact analysis of the risk difference. The simple recalculation from the posted summary statistics is close to the sponsor’s result, and the registry indicates no discrepancy. The sponsor’s own analysis remains the reference result. The interval should not be read as a measure of individual variation, nor does it indicate that every participant’s outcome would be similar to the group average.

The secondary outcomes have their own estimates and intervals, but their interpretation also depends on outcome timing, sample sizes, measurement, and the number of analyses considered. Smaller secondary samples can yield less precise estimates. In particular, the concordance result is based on smaller group counts than the primary endpoint, so its interval should be considered in that context. Statistical precision does not by itself establish whether an outcome is important to patients or whether a difference has practical consequences.

12. Planning a Similar Trial: Sample Size

This is a planning illustration, not a re-evaluation of the original trial. It asks: if a new study wanted to detect a difference like the one observed, or a smaller one, how large would it need to be? It is deliberately not “observed power” of the finished trial, which is not a meaningful quantity.

The planning figures are participants per arm for the binary and continuous outcomes described. They are not total event counts. For the primary binary outcome, the illustrations use 181 participants per arm for 80% power and 242 participants per arm for 90% power when planning for 100% of the observed effect. The rows for 75% and 50% of the observed effect show larger required group sizes. The same pattern appears in the other listed planning illustrations: smaller assumed effects require more participants.

General explanation: power is the probability that a specified study design would detect an effect of a chosen size under its planning assumptions, if that effect were true. The 80% and 90% columns describe two alternative planning targets. A design targeting 90% power requires more participants than one targeting 80% power for the same assumed effect, all else equal. These columns are planning quantities, not a description of what happened in the completed trial.

The planning illustration assumes a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set to the stated fraction of the observed effect. For time-to-event outcomes, the stated convention is total events; the outcomes listed in these planning figures are not time-to-event outcomes, so their quantities are participants per arm. The trial’s own original design assumptions and sample-size justification are not reported in the registry record. These planning calculations are based on observed effects and are not observed power.

Observed trial group sizes should not be confused with these hypothetical planning requirements. The planning rows ask how many participants per arm might be needed under particular assumptions; they do not show that the original trial was designed using those assumptions, nor do they establish whether a trial was adequately powered in retrospect. Assumptions about the underlying event rate and effect size are especially consequential for binary outcomes, so planning illustrations should be read as conditional examples rather than guarantees.

13. How the Sample Size Is Derived

Power is the probability that a study of a given size rejects the null hypothesis when a specific true effect exists. It depends on four things: the effect to detect, the variability of the outcome, the significance level (here a two-sided α of 0.05, so z_1−α/2 = 1.960) and the desired power (z_1−β = 0.842 for 80% and 1.282 for 90%).

Formula

n is the number of participants in each arm, p₀ and p₁ are the control and treatment proportions, and p̄ is their average.

Worked calculation for this trial

1. Control proportion p₀ = 0.313; treatment proportion p₁ = 0.456; average p̄ = 0.385.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6881 = 1.3487.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6806 = 0.5728.
4. n = (1.3487 + 0.5728)² / (0.1430)² = 180.4, rounded up to 181 participants per arm for 80% power.

The smaller-effect rows in the table above repeat the same calculation with the effect multiplied by 0.75 and 0.5 (for ratios, applied to the logarithm of the ratio).

R code

alpha <- 0.05
z_a   <- qnorm(1 - alpha / 2)          # two-sided
p0 <- 0.313333333333333                          # control proportion
p1 <- 0.456375838926175                          # treatment proportion
n_per_arm <- function(power, frac = 1) {
  q1 <- p0 + (p1 - p0) * frac               # smaller effect = fraction of the observed difference
  pbar <- (p0 + q1) / 2
  z_b <- qnorm(power)
  ceiling(round((z_a * sqrt(2 * pbar * (1 - pbar)) + z_b * sqrt(p0 * (1 - p0) + q1 * (1 - q1)))^2 / (q1 - p0)^2, 6))
}
for (f in c(1, 0.75, 0.5))
  cat(sprintf("%3.0f%% of observed effect: n per arm = %s (80%% power), %s (90%% power)\n", 100 * f,
              format(n_per_arm(0.80, f), big.mark = ","), format(n_per_arm(0.90, f), big.mark = ",")))

# Check against R's built-in function (unrounded n per arm)
cat("power.prop.test:", round(power.prop.test(p1 = p0, p2 = p1, power = 0.80)$n, 1), "\n")

# Simulation: how often does the z-test reject at the 80%-power sample size?
set.seed(4931797)
n    <- n_per_arm(0.80)
reps <- 20000
x0 <- rbinom(reps, n, p0); x1 <- rbinom(reps, n, p1)
ph <- (x0 + x1) / (2 * n)
z  <- ((x1 - x0) / n) / sqrt(ph * (1 - ph) * 2 / n)
cat(sprintf("Simulated power at n = %s per arm: %.3f (%d replicates)\n", format(n, big.mark = ","), mean(abs(z) > z_a, na.rm = TRUE), reps))

Output from running the code

100% of observed effect: n per arm = 181 (80% power), 242 (90% power)
 75% of observed effect: n per arm = 316 (80% power), 423 (90% power)
 50% of observed effect: n per arm = 697 (80% power), 932 (90% power)
power.prop.test: 180.4 
Simulated power at n = 181 per arm: 0.794 (20000 replicates)

The simulation draws many pairs of event counts at the planned sample size and counts how often the two-proportion z-test rejects the null. It should land close to the target power; at very small required sample sizes it can fall below it, because the normal approximation is rough there.

14. Analyses Reported by the Sponsor

The sponsor reports the primary comparison using Fisher Exact, with the risk difference as the effect measure. The reported result is a risk difference of 14.3, a 95% confidence interval from 6.6 to 22.0, and p < 0.001. The simple recalculation from the posted group counts gives a closely agreeing unadjusted result after rounding. The registry marks no discrepancy for this outcome.

Recalculation is useful as a check on the arithmetic implied by the posted summary statistics, but it does not reproduce every possible feature of the sponsor’s analysis. It cannot account for participant-level data or adjustments that are not included in the registry record. The sponsor’s own analysis therefore takes precedence. In this case the reported and recalculated primary comparisons agree closely, rather than indicating a material conflict.

The same principle applies to other outcomes: a recalculated unadjusted estimate can help interpret the posted counts or means, but it should not be presented as if it were the sponsor’s full analysis. For the 6-month EHR outcome, the sponsor reports a risk difference of 13.0, a 95% confidence interval from 5.1 to 20.9, and p = 0.002. For the knowledge outcome, the sponsor reports a mean difference of 1.0, a 95% confidence interval from 0.9 to 1.2, and p < 0.001. These are the registry’s stated analyses and should be distinguished from any summary-statistic recalculations.

15. Multiplicity, Missing Data and Analysis Populations

Several outcomes are listed for VIDEO-ED, including the primary EHR documentation outcome and secondary measures related to preferences, concordance, documentation, knowledge, and engagement. The registry record does not report whether statistical testing across these outcomes was adjusted for multiplicity, whether a hierarchy was used, or whether a particular secondary outcome was designated as confirmatory. That absence limits how strongly a collection of nominal p-values can be interpreted.

General explanation: when many hypotheses are tested, the chance of at least one apparently unusual result can increase, even if none of the underlying effects is real. Multiplicity procedures can address this issue, but they may also change the threshold used to interpret individual results. Without a reported plan, secondary p-values should be read as unadjusted evidence for their individual comparisons, not as proof that every secondary finding has been independently confirmed. The primary endpoint remains the clearest focal result in the registry record.

The registry record also does not report the analysis population, how participants with missing outcome information were handled, or whether the analyses followed an intention-to-treat principle. Those omissions matter because a comparison based on available records can differ from one based on all randomized participants if outcome availability is related to group assignment or outcome status. The posted arm counts do not, by themselves, show how missing data were treated or whether all randomized participants were included in each analysis.

Other analysis details are not reported in the registry record, including whether covariate adjustment was planned or performed and how the Natural Language Processing assessment was validated for this endpoint. This does not establish that those procedures were absent; it means the registry record does not describe them. Readers should avoid filling these gaps with assumptions. The interpretation can rely on the sponsor’s reported test and effect estimate while recognizing that the record does not provide a complete statistical analysis plan or full accounting of missingness and analysis populations.

16. Safety Results

The registry reports serious adverse events as affected participants divided by participants at risk.

Deaths

Other (non-serious) adverse events

Participants with at least one non-serious event at or above the registry's 0% reporting threshold.

The registry lists zero serious adverse events among 298 participants at risk in the video group and zero among 300 participants at risk in the control group. It also lists zero other adverse events in each group. Deaths are recorded as 58 in the video group and 45 in the control group. The registry does not provide additional detail in the listed safety terms to explain the deaths or their relationship, if any, to study participation.

These figures should be read as registry counts, not as proof that an intervention caused or prevented an event. The record does not report event definitions beyond the categories listed, the observation period for these safety counts, the causes of death, or an analysis comparing the groups. Counts alone do not establish whether differences are attributable to chance, participant characteristics, or other factors. In particular, the recorded deaths should not be interpreted as treatment-related based on this information.

The absence of recorded serious or other adverse events in these entries does not establish that no events occurred outside the registry’s reporting framework. Safety interpretation requires information on ascertainment, timing, classification, and follow-up, which is not reported in the registry record. These figures therefore describe what is posted, without supporting a broader comparative safety conclusion.

17. What the Result Does, and Does Not, Mean

The primary result indicates more participants with EHR documentation of advance care planning in the video arm than in the control arm at 3 months, with a sponsor-reported risk difference of 14.3 and a 95% confidence interval from 6.6 to 22.0. This is a finding about documentation detected in the EHR using Natural Language Processing. It is not, on its own, a measure of whether participants made a decision, whether the record accurately reflected their wishes, or whether care followed those wishes.

The distinction between process and outcome is important. Documentation may support communication, but the endpoint does not measure all conversations or decisions, and it does not directly establish what happened during later care. The registry lists concordance between stated and documented preferences as a secondary outcome, which addresses a related question but is not the primary endpoint. Even concordance does not alone establish that preferences were followed in clinical practice.

The trial’s randomized parallel-group design provides a structured comparison between the assigned intervention and control conditions. The posted result is compatible with a difference between those groups in the measured outcome. However, the registry record does not report all information needed to evaluate the analysis population, missing data handling, multiplicity, or implementation details. The observed association should therefore be described within the stated design and outcome rather than extended to unmeasured effects.

The result does not establish that the video decision aid changes every participant’s knowledge, preferences, engagement, or subsequent care. Nor does it show that the effect will be the same in other settings or populations. The registry identifies the setting as an emergency department and the control condition as usual advance care planning services at the study site; further detail about setting characteristics and generalizability is not reported in the registry record.

Statistical evidence and clinical meaning are related but different. The reported p-value and confidence interval address uncertainty about the comparison under the stated method. They do not decide whether the size of the documentation difference is important to participants or clinicians. That judgment would require context about how documentation is used and whether it improves outcomes that matter to patients, which the primary endpoint does not measure.

18. Why This Trial Matters Statistically

VIDEO-ED illustrates why the outcome definition matters in clinical trials. Advance care planning includes conversations, preferences, records, and decisions about care, but a trial must operationalize those concepts into measurable outcomes. Here, the primary endpoint is EHR documentation at a specified follow-up point. That choice yields a countable record-based measure, while also setting clear limits on what the result can establish.

The trial also demonstrates the value of reporting an absolute comparison with an interval. The sponsor’s risk difference and confidence interval communicate both the direction and plausible range of the documentation contrast, rather than relying on a p-value alone. Readers can distinguish evidence against a no-difference model from uncertainty about the magnitude of the difference. This distinction is central to responsible interpretation of trial results.

Secondary outcomes broaden the statistical picture by addressing concordance and knowledge, but they also raise questions about multiple testing and interpretation across distinct constructs. The registry lists several areas of interest, and the posted secondary findings should be considered in light of outcome timing, sample size, and the absence of reported multiplicity procedures. A consistent direction is informative context, not a substitute for a prespecified analysis plan.

Finally, the planning illustrations show how sample-size requirements depend on assumptions about effect size and desired power. They are not a retrospective measure of trial quality and do not reveal the original design rationale. Separating planning calculations from observed results helps prevent a common misreading: a study’s observed data cannot be converted into a measure of observed power that proves its conclusions are reliable. The most useful statistical reading combines the design, endpoint, estimate, uncertainty, and reporting limitations.

19. Limitations

• The posted summary statistics are the only data these results rest on; patient-level data, full protocols and statistical analysis plans are not available.
• Recalculated results are simple, unadjusted calculations from posted summaries. They do not replace the sponsor's prespecified analysis.

The registry record gives limited detail on who was masked, how randomization and allocation concealment were implemented, and what analysis population was used. It also does not report how missing outcome data were handled. These gaps prevent a full assessment of possible bias and of whether the posted analysis included all randomized participants.

The primary outcome depends on EHR documentation detected by Natural Language Processing. The registry does not report the processing algorithm, validation results, handling of ambiguous text, or whether documentation outside the EHR was captured. A record-based measure can miss advance care planning that was discussed but not entered in the EHR, and the posted endpoint does not show whether recorded preferences were followed in care.

The intervention description includes a video decision aid and discussion, while the control arm is described as usual services; the intervention listing also mentions an information sheet. The registry record does not explain the detail or fidelity of these components, the extent of participant exposure, or whether usual services varied. The result therefore applies to the intervention and comparison as described, without allowing a more detailed account of implementation.

The registry does not report the trial’s original sample-size justification, multiplicity plan, or complete statistical analysis plan. Secondary outcome interpretation is consequently limited, especially when several domains are listed. The record also lacks detail on safety-event ascertainment and the context of reported deaths. These are reporting limitations, not evidence that any particular procedure was absent or that a particular bias occurred.

20. Related Tutorials

21. Related Statistical Calculators

22. Sources

• ClinicalTrials.gov: Video Images About Decisions for Ethical Outcomes in the Emergency Department (VIDEO-ED) — NCT04931797.
• Registry record last updated 2026-10-21; status last verified 2026-09.
• Results first posted 2026-10-21.
• Data retrieved from ClinicalTrials.gov on 2026-11-09.
• Group sizes, means, event counts and sponsor-reported p-values are reproduced as posted. Effect estimates, confidence intervals and p-values not attributed to the sponsor are independently calculated from the posted summary statistics.

23. Record Summary

VIDEO-ED is registered as a completed, randomized, single-masked, parallel-group trial sponsored by Massachusetts General Hospital. It compares a video decision aid and advance care planning discussion with usual advance care planning services at the study site. Enrollment is recorded as 598.

The primary outcome is EHR advance care planning documentation at 3 months, assessed by Natural Language Processing. The sponsor reports a risk difference of 14.3, a 95% confidence interval from 6.6 to 22.0, and p < 0.001. The posted counts show more participants with documentation in the video arm than in the control arm.

Secondary findings concern documentation, concordance, and knowledge. The registry record does not report key details about missing data, analysis populations, multiplicity adjustment, or the original sample-size justification. The results should be interpreted as evidence about the measured outcomes and not as direct proof of preference-concordant care or broader clinical benefit.