Patient-Reported Outcomes Measurement Information System Integration Into Rheumatology Clinical Practice: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Patient-Reported Outcomes Measurement Information System Integration Into Rheumatology Clinical Practice (NCT05026853), a randomized na study. The primary outcome is Percent of Appointments at Which Patient-Reported Outcomes Measurement Information System (PROMIS) Scores Are Documented in the Electronic Medical Record (EMR) Note by the Participating Health Care Provider (HCP).

2. Clinical Question

3. Trial Design

This was a randomized, parallel-group trial with no masking. The registry lists the study as completed, with the University of Michigan as sponsor. Its title is Patient-Reported Outcomes Measurement Information System Integration Into Rheumatology Clinical Practice. The condition listed is rheumatic diseases, and the intervention is classified as behavioral.

The comparison was between PRO Integration Into Clinical Practice and Usual Care. In the integration arm, patients and health care providers received PROMIS scores through an emailed report card. In usual care, neither patients nor providers received that emailed report, although PROMIS scores remained available in the electronic medical record as usual. That distinction matters when interpreting the result: the contrast is about an additional route for sharing scores, not the presence versus absence of scores in the medical record.

The registry lists enrollment of 110. The primary outcome summary gives 46 participants in the integration arm and 55 in usual care. The registry separately notes that one appointment was cancelled and eight could not receive a score card because of technical difficulties. It does not explain how those circumstances relate to the analysis denominators or provide a fuller account of the analysis population.

The study started on 2021-09-14, and primary completion was recorded as 2023-02-27. The primary endpoint timeframe was up to 3 months. The phase is listed as not applicable. The registry record does not report the original sample-size justification, the planned statistical analysis, or whether any interim analyses were planned. Randomization is recorded, but details about sequence generation and allocation concealment are not reported in the registry record.

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.

Overall Study

Reasons for not completing this period:

Analysis population for the primary outcome, as defined in the registry: 1 appointment was cancelled and 8 were unable to receive score card due to technical difficulties.

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.

6. Primary Endpoint

The registry lists the primary outcome as Percent of Appointments at Which Patient-Reported Outcomes Measurement Information System (PROMIS) Scores Are Documented in the Electronic Medical Record (EMR) Note by the Participating Health Care Provider (HCP), measured over Up to 3 months.

The primary endpoint measured whether a participating health care provider documented PROMIS scores in the electronic medical record note for an appointment. The record says documentation was identified through electronic medical record data pulls and categorized as yes or no. The reported outcome is the count, and the percentage, of participants for whom scores were documented.

This endpoint is relevant to the study’s implementation question because an emailed score report can only inform clinical communication or decision-making if the scores are brought into the encounter or recorded in its documentation. Recording the score is therefore a practical process measure of whether information reached the clinical note. It is not a direct measure of whether the score was interpreted correctly, changed a recommendation, improved communication, or affected a patient’s health.

The intervention arm had 23 participants with documented scores among 46, while usual care had 7 among 55. The registry describes the timeframe as up to 3 months. It also notes one cancelled appointment and eight instances in which a score card could not be received because of technical difficulties. How these circumstances were handled analytically is not reported in the registry record.

7. Results Posted in the Registry

• PRO Integration Into Clinical Practice: 50.0% (23/46) versus 12.7% (7/55) on control; risk difference 37.3 percentage points (95% CI 20.4 to 54.2), risk ratio 3.93 (1.86–8.32); 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.

Percent of Appointments at Which Referrals/Recommendations Related to PROMIS Scores Are Documented in the EMR Note by the Participating HCP

• 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:
  • PRO Integration Into Clinical Practice: 37.0% (17/46) versus 10.9% (6/55) on control; risk difference 26.0 percentage points (95% CI 9.8 to 42.2), risk ratio 3.39 (1.46–7.88); unadjusted two-proportion z-test p = 0.002.
• Interpretation:
  • The 95% confidence interval excludes no difference, so the proportion with the event is statistically higher for PRO Integration Into Clinical Practice than for the control. This is an unadjusted, secondary comparison, so it is suggestive rather than confirmatory.

The secondary outcome areas extend the primary question from score documentation to related aspects of clinical practice. They include documentation of referrals or recommendations related to PROMIS scores, quality of patient-provider communication, and change in the score of the most bothersome PROMIS domain. The registry describes three secondary outcomes, but detailed numerical results are posted for only the referrals-or-recommendations documentation outcome. Results for communication quality and change in the most bothersome domain are not reported in the registry record.

The posted secondary comparison for referral or recommendation documentation points in the same direction as the primary process outcome: more participants had this documentation in the integration arm than in usual care. This directional consistency is relevant because it links score sharing not only with recording scores but also with recording related actions. It does not establish that the reports caused a particular clinical action or that any action improved patient outcomes.

The secondary endpoint is related to, but distinct from, the primary endpoint. A provider may document a score without recording a referral or recommendation, and a referral or recommendation may be documented for reasons not fully captured by the score-report process. The communication and symptom-domain outcomes would address other dimensions, but their results are not available in the registry record, so they cannot be used to confirm or qualify the numerical pattern.

Secondary results generally carry less weight than a prespecified primary result because they can involve more comparisons and may be more vulnerable to chance findings or selective emphasis. The registry record does not report a multiplicity adjustment, an analysis plan, or a hierarchy for interpreting secondary outcomes. The posted secondary p-value is unadjusted. It should therefore be interpreted as an individual comparison rather than as evidence that accounts for all the outcome tests considered in the study.

Taken together, the available secondary information is broadly aligned with the primary documentation result, but the incomplete posted results and unadjusted testing limit how much can be inferred across the full set of secondary outcomes. The primary endpoint remains the clearest numerical result in the registry record.

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

• Percent of Appointments at Which Referrals/Recommendations Related to PROMIS Scores Are Documented in the EMR Note by the Participating HCP
• Quality of Patient-provider Communication
• Change in Score of the Most Bothersome PROMIS Domain

9. Statistical Interpretation

10. Statistical Methods Explained

The primary outcome is binary: each participant’s appointment is classified according to whether PROMIS scores were documented in the electronic medical record note. A binary outcome can be summarized as a count of participants with the event and a denominator, and compared between randomized groups. Here, documentation is the event of interest. This definition helps keep the statistical result tied to what was actually measured rather than to broader outcomes that were not directly assessed by the primary endpoint.

What does the risk difference express?

The risk difference compares the event proportions between groups by subtracting the control-group proportion from the intervention-group proportion. It is an absolute contrast, so it describes the difference in the chance of documentation between assigned groups on the proportion scale. The registry posts a risk difference of 0.373 and a confidence interval from 0.203 to 0.542. A positive value means the documented-event proportion was higher in the intervention arm. The interval does not cross zero, which is consistent with a positive group difference under the reported analysis.

The registry also posts group proportions of 0.5 for the integration arm and 0.127 for usual care. These values express the outcome within each group and provide context for the absolute comparison. The counts and denominators are important alongside proportions: 23 of 46 in the integration arm and 7 of 55 in usual care had documentation. Neither the proportion nor the count alone fully describes the comparison; each needs the corresponding group context.

How do the relative measures differ?

The risk ratio is the event proportion in the intervention arm divided by the event proportion in the control arm. Its posted value is 3.929, with a confidence interval from 1.856 to 8.316. It describes a relative contrast, not an absolute increase. The odds ratio compares the odds of the event between groups; the posted value is 6.857, with a confidence interval from 2.57 to 18.29. Odds and risks are different quantities, so the odds ratio can be farther from one than the risk ratio, especially when the event is not rare. These measures complement the risk difference but do not replace it.

What does the p-value tell the reader?

The posted primary comparison has an unadjusted p < 0.001. In general, a p-value measures how incompatible the observed data are with a specified null model, assuming that model and the analysis assumptions hold. It is not the probability that the null hypothesis is true, and it is not a measure of effect size. The term unadjusted indicates that the reported p-value is not described as corrected for multiple comparisons. The registry record does not report a multiplicity procedure or a full statistical analysis plan.

A p-value should be considered with the estimated effect, its confidence interval, the endpoint definition, and the study design. A small p-value does not remove uncertainty about the magnitude or generalizability of the result. Nor can it account for possible measurement or implementation issues, such as how consistently providers documented scores. The unmasked design and the documentation-based outcome are relevant context for interpretation.

Why is a confidence interval useful?

In general, a confidence interval gives a range of estimates compatible with the observed data and the method used to construct the interval. It communicates precision as well as direction. A narrower interval indicates greater statistical precision than a wider interval, while an interval that includes the null value leaves more uncertainty about the direction of the effect. A confidence interval is not a guarantee that the true effect lies within its bounds, and it does not account for bias that may arise outside the statistical model.

For a risk difference, zero is the no-difference value. For a risk ratio or odds ratio, one is the no-association value. The posted intervals for the primary comparison lie on the effect side of their respective null values. This is consistent with the primary p-value, but the estimate and interval remain specific to the registry’s endpoint, population, and analysis.

What should be taken from the analysis record?

The registry record posts descriptive group results and an unadjusted comparison for the primary outcome, but it lists zero analyses in its analysis count. A full account of model specification, covariate adjustment, handling of missing observations, and prespecified testing is not reported in the registry record. The numerical comparison should therefore be described as the posted unadjusted analysis rather than as a fully documented model-based result.

In general, random assignment is intended to make comparison groups similar in expectation, while an unmasked study can still have differences in care or recording practices after assignment. The analysis of a binary endpoint can be affected by the definition of the event, the denominator, and the handling of appointments where the intervention could not be delivered. The registry notes a cancelled appointment and technical difficulties affecting score-card receipt, but does not report how these were treated in the primary analysis. No additional assumptions about those choices can be made from the registry record.

11. Confidence Intervals and Precision

Precision is conveyed by the confidence intervals around the posted comparisons. For the primary risk difference, the registry reports an estimate of 0.373 and bounds of 0.203 and 0.542. The entire interval is positive, so the posted analysis supports a difference in the direction of more documentation with emailed reports. The interval still spans a range of possible effect sizes; the point estimate should not be treated as an exact effect that would necessarily recur in another setting.

The relative comparisons also have intervals: the risk ratio is 3.929, with bounds of 1.856 and 8.316, and the odds ratio is 6.857, with bounds of 2.57 and 18.29. Each interval excludes its no-association value of one. The measures express different scales, so their interval widths and numerical values cannot be compared as if they were the same quantity.

Confidence intervals describe sampling uncertainty under the analysis method. They do not capture every source of uncertainty, including possible differences in documentation practice, delivery problems, or limits to applying the findings beyond the study context. The record does not report details of the interval-construction method or an adjusted analysis. The endpoint is also a process measure, so statistical precision about documentation does not establish precision about outcomes that were not measured by that endpoint.

The primary counts offer a direct view of how much information underlies the comparison: 23 participants had documentation in the integration arm, and 7 had documentation in usual care. The interval should be considered alongside these counts and their denominators, rather than interpreted in isolation. The posted estimates are compatible with a positive difference, while uncertainty remains about its magnitude and about how well the result would transport to other clinical settings or workflows.

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 estimates are participants per arm, not total events. They are illustrations based on the observed effect, not the trial’s original design calculation. The stated assumptions are a two-sided significance level of 0.05, equal allocation between the two arms, and a normal approximation. The effect to detect is set at the stated fraction of the observed effect. The original trial’s sample-size assumptions and justification are not reported in the registry record.

For each effect-size scenario, the 80% power column gives the planned participants per arm for a design that would have an 80% chance of detecting an effect of that specified size under the stated assumptions, if that effect were the true one. The 90% power column gives the corresponding planning number for a higher chance of detecting that effect. These are design probabilities under assumptions, not guarantees about what a future study will find.

The rows describe planning for 100%, 75%, and 50% of the observed effect. The corresponding estimates are 24 and 31 participants per arm for 80% and 90% power at 100% of the observed effect; 39 and 51 for 75%; and 77 and 102 for 50%. Smaller effects are harder to distinguish from random variation, so detecting them at the same power generally requires more participants. The planning estimates are illustrations anchored to this trial’s observed effect, which may itself be imprecise.

This is not observed power. Observed power calculated from the estimated effect and observed sample is not a useful substitute for examining the effect estimate and its confidence interval. The planning figures should instead be read as conditional design illustrations under the stated assumptions.

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 = 0.127; treatment proportion p₁ = 0.500; average p̄ = 0.314.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.6562 = 1.2860.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.6009 = 0.5057.
4. n = (1.2860 + 0.5057)² / (0.3727)² = 23.1, rounded up to 24 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 <- 0.127272727272727                          # control proportion
p1 <- 0.5                          # 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(5026853)
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 = 24 (80% power), 31 (90% power)
 75% of observed effect: n per arm = 39 (80% power), 51 (90% power)
 50% of observed effect: n per arm = 77 (80% power), 102 (90% power)
power.prop.test: 23.1 
Simulated power at n = 24 per arm: 0.833 (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. Multiplicity, Missing Data and Analysis Populations

Multiplicity arises when several outcomes or comparisons are examined. Even if each test is conducted at a conventional threshold, the chance of at least one apparently notable result can increase as the number of tests grows. This is why interpretation often depends on a prespecified primary endpoint, a defined testing hierarchy, or an adjustment strategy. The registry lists one primary outcome and three secondary outcome areas, but does not report a multiplicity plan or an analysis hierarchy in the registry record.

The primary comparison is reported with an unadjusted p-value. The secondary comparison with numerical results is also reported with an unadjusted p-value. Those values do not reflect an adjustment for other outcomes. The primary endpoint is the main focus of interpretation, while secondary results should be treated as supportive or exploratory unless a prespecified confirmatory strategy is documented. Such a strategy is not reported in the registry record.

The registry reports zero analyses in its analysis count, and no reported analysis records are listed. This does not erase the posted outcome summaries and comparisons, but it means the record does not provide a full account of the statistical analysis methods, the prespecified models, or whether the posted comparisons match a prior analysis plan. The analysis plan, covariate choices, and any interim analyses are not reported in the registry record.

Missing-data handling is also not reported in the registry record. The record notes that one appointment was cancelled and eight were unable to receive a score card because of technical difficulties. It does not state whether these observations were excluded, included in another way, or handled using an imputation method. It also does not describe a sensitivity analysis for missing or unavailable outcome information.

The analysis population is not fully described. The primary outcome gives group denominators of 46 and 55, while the adverse-event summary uses 55 participants at risk in each group. The record does not explain the relationship between those denominators. It would be inappropriate to infer the analysis set, reasons for the differing counts, or the consequences for the results without further information. Details on intention-to-treat or per-protocol analysis are not reported in the registry record.

15. 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’s serious adverse event summary reports zero serious adverse events in each group, with 55 participants at risk in the PRO Integration Into Clinical Practice group and 55 at risk in Usual Care. It reports zero other adverse events and zero deaths in both groups. These figures describe what was recorded in the registry’s adverse-event summary.

Zero recorded events does not prove that no adverse events occurred outside the reported collection or observation process. The record does not provide further detail about how adverse events were defined, collected, or attributed, nor does it give a safety analysis plan. The at-risk counts in this summary differ from the primary outcome denominators, and the registry record does not explain that difference. The safety counts should therefore be read as their own reported summary, not as a direct extension of the primary endpoint analysis.

The adverse-event summary is descriptive. It does not establish an absence of risk, and it does not support a broader safety conclusion about the intervention beyond the recorded figures.

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

The main result concerns whether PROMIS scores appeared in the electronic medical record note. Documentation was recorded for 23 participants in the PRO Integration Into Clinical Practice arm and 7 in Usual Care. The posted risk difference is 0.373, with a confidence interval from 0.203 to 0.542, and the unadjusted p-value is p < 0.001. The direction and uncertainty of this comparison support a higher documentation rate in the arm receiving emailed reports within this study.

This endpoint is a measure of implementation and recording. It does not show, by itself, whether providers used the scores in a clinical decision, whether patients and providers communicated more effectively, or whether symptoms changed. Those are separate questions. Although the registry lists communication quality and change in the most bothersome PROMIS domain as secondary outcome areas, results for those outcomes are not reported in the registry record.

The intervention was an emailed report card shared with patients and health care providers. Usual care retained access to PROMIS scores in the electronic medical record, but did not include the emailed report. The finding therefore concerns the added report-card workflow, not the general availability of PROMIS scores. It also reflects a trial with no masking and an outcome based on provider documentation, which may depend on recording practices as well as on whether scores were seen or discussed.

The comparison should not be generalized automatically to other clinics, health systems, populations, or ways of sharing patient-reported outcomes. The registry record does not report enough detail about participant characteristics, implementation fidelity, or analysis choices to judge how closely other settings would match this trial. Nor does the primary result establish that an intervention works or fails as a clinical treatment; it answers a narrower documentation question.

The most defensible interpretation is that the posted randomized comparison found more documented PROMIS scores in the integration arm during the stated timeframe. The magnitude remains uncertain, and the result does not resolve whether score sharing affected communication, clinical actions, or patient health.

17. Why This Trial Matters Statistically

This trial addresses a statistical question that is often central to implementation research: whether making patient-reported information more visible in the clinical encounter changes a measurable step in care. The primary endpoint is not a symptom score or a clinical event, but documentation of PROMIS scores in the electronic medical record note. Keeping that distinction clear prevents a process outcome from being mistaken for evidence of a health benefit.

The study also illustrates how the choice of comparison shapes interpretation. PROMIS scores remained available in the electronic medical record in usual care, while the intervention added an emailed report card for patients and providers. The observed contrast therefore speaks to the additional sharing mechanism rather than to whether outcomes were measured at all. That can help readers understand what an implementation effect represents.

Several statistical summaries add complementary perspectives. The risk difference expresses the absolute contrast, while the risk ratio and odds ratio express relative contrasts. Confidence intervals describe uncertainty in those estimates, and an unadjusted p-value addresses compatibility with a no-difference model under the analysis. None of these summaries addresses every source of uncertainty, and none should be read as a substitute for the endpoint definition or the study design.

The registry record also highlights why completeness of reporting matters. Details about the analysis plan, multiplicity, missing-data handling, and analysis populations are not reported. Secondary outcomes are listed, but numerical results are not posted for all of them. These gaps limit assessment of how the reported result fits into the full set of planned questions and how technical delivery issues were handled.

For clinical researchers, the key statistical lesson is to connect an estimate to the operational outcome that generated it. A difference in documentation may be meaningful for workflow evaluation, but its downstream significance requires evidence from outcomes that measure communication, decisions, or patient experience. The posted result provides one part of that broader assessment, not the whole.

18. 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 leaves several trial-specific questions unresolved. It notes that one appointment was cancelled and eight could not receive a score card because of technical difficulties, but does not explain how those cases were handled in the primary analysis. Because intervention delivery is central to the comparison, the absence of information about these appointments limits assessment of implementation and the analysis denominator.

The primary endpoint depends on what was documented in an electronic medical record note. The registry says documentation was identified through electronic medical record data pulls and categorized as yes or no, but does not report validation procedures, reviewer reliability, or how ambiguous records were classified. The endpoint may therefore capture the recording process without fully capturing whether scores were reviewed or discussed.

The study was unmasked. The registry does not describe steps taken to limit differences in provider behavior or documentation beyond the assigned intervention. This matters because providers in the integration arm received a report card, while usual-care providers did not receive an emailed report, and the outcome itself was provider documentation. The record does not give implementation-fidelity results or details about how consistently reports were received or used.

Further limitations arise from reporting gaps. The original sample-size justification, full statistical analysis plan, handling of missing data, analysis populations, and multiplicity approach are not reported in the registry record. The registry lists additional secondary outcome areas but posts detailed numerical results for only one secondary comparison. Without fuller results and methods, readers cannot assess the complete pattern of outcomes or determine how prespecified the posted analyses were.

The record does not provide participant characteristics or enough information to judge how broadly the findings apply across rheumatology settings. The safety summary also uses denominators that differ from the primary outcome denominators, without an explanation. These are limits on interpretation; they do not establish that the posted primary comparison is invalid, but they leave important context unresolved.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Patient-Reported Outcomes Measurement Information System Integration Into Rheumatology Clinical Practice — NCT05026853.
• Registry record last updated 2024-04-30; status last verified 2024-04.
• Results first posted 2024-04-30.
• 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.

22. Record Summary

NCT05026853 is a completed, randomized, unmasked, parallel-group study sponsored by the University of Michigan. It examined PROMIS integration into rheumatology clinical practice, comparing an emailed score report shared with patients and health care providers against usual care, where scores remained available in the electronic medical record.

The primary outcome was documentation of PROMIS scores in the electronic medical record note, assessed over up to 3 months. The registry reports documentation for 23 participants in the integration arm and 7 in usual care. The posted unadjusted risk difference is 0.373, with a confidence interval from 0.203 to 0.542 and p < 0.001. The registry also lists secondary outcome areas involving referral or recommendation documentation, communication quality, and change in the most bothersome PROMIS domain; results are not reported for all listed outcomes.

The record notes one cancelled appointment and eight instances of technical difficulty preventing score-card receipt. Details of missing-data handling, the original sample-size rationale, multiplicity, and the full analysis plan are not reported in the registry record.