Hospital-based Patient Navigation and Smoking Cessation: Complete Statistical Analysis

1. Trial at a Glance

This page covers the registry results for Hospital-based Patient Navigation and Smoking Cessation (NCT03452371), a randomized na study. The primary outcome is Number of Participants With Prescription for an FDA-approved Smoking Cessation Medication.

2. Clinical Question

The clinical question is whether hospital-based patient navigation, compared with enhanced traditional care, was associated with a different number of participants whose medical chart indicated that a prescription for an FDA-approved smoking-cessation medication had been sent to their pharmacy by three months. The registry describes a pilot randomized controlled trial among smokers hospitalized on general internal medicine or family medicine services.

The primary endpoint concerns a prescription sent to a pharmacy, not whether a participant filled or used that prescription, and not whether smoking cessation occurred. Self-reported quitting and medication utilization were among the secondary outcomes. This distinction matters: the primary comparison addresses a recorded care process, while the secondary outcomes address participant-reported behavior or other aspects of treatment and readiness. The trial results describe the observed differences and their uncertainty; they do not by themselves establish that navigation caused any difference.

3. Trial Design

The registry describes a completed, randomized, parallel-group pilot trial with no masking. The two behavioral intervention arms were patient navigation and enhanced traditional care. The record reports enrollment of 44 participants. In the primary outcome results, the enhanced traditional care arm included 21 participants and the patient navigation arm included 23. The registry does not report the method used to generate the random sequence or whether allocation was concealed.

Patient navigation involved meeting with a trained navigator in person when she was available or by telephone, with up to ten hours of navigation over three months. Enhanced traditional care consisted of usual smoking-cessation care for smokers plus additional support resources. The trial assessed participants at three months. The primary outcome was determined by chart review; secondary outcomes included self-reported cessation, medication utilization, stage of change, nicotine-dependence score, and other tobacco-treatment support.

The registry identifies the study as a pilot randomized controlled trial and lists its status as completed. The record does not report the original sample-size justification, target enrollment rationale, a prespecified analysis plan, or a planned analysis population. These omissions limit what can be said about the intended precision or inferential approach. No masking was used, which is relevant when interpreting self-reported outcomes and care processes that could be affected by knowledge of assignment. The primary endpoint was based on chart review, but the registry does not describe how consistently charts were reviewed or whether reviewers were unaware of assignment.

The registered outcomes focus on the three-month assessment. Follow-up beyond that period is not reported in the registry record. The registry lists five secondary outcomes, while numerical secondary findings are posted for self-reported smoking cessation, medication utilization, and stage of change. Numerical results for the Fagerstrom score and other tobacco-treatment support 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

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 Number of Participants With Prescription for an FDA-approved Smoking Cessation Medication, measured over Three months.

The primary endpoint counts participants whose medical chart showed that a prescription for an FDA-approved smoking-cessation medication had been sent to their pharmacy. It is assessed at three months and is based on chart review, with the result recorded as yes or no for each participant. The registry reports 9 participants with this endpoint in enhanced traditional care and 11 in patient navigation.

This outcome is used to assess whether the care pathway resulted in a documented prescription being sent. It is a process-of-care measure: it captures prescribing and transmission to a pharmacy, rather than medication dispensing, medication use, adherence, or successful cessation. Those are distinct events and should not be treated as interchangeable. The registry separately lists medication utilization and self-reported smoking cessation as secondary outcomes.

Using a chart-based measure can make the endpoint less dependent on participants recalling a prescription, but its interpretation still depends on the completeness and accuracy of the medical record. The registry does not report validation procedures for the chart review, whether prescriptions sent outside the reviewed record would be captured, or whether reviewers were blinded to treatment assignment. Accordingly, the endpoint describes what the reviewed charts recorded, not every possible prescribing or medication-use event.

The outcome is clinically relevant as a marker of whether a medication was prescribed, but it is not itself a measure of quitting. The primary comparison should therefore be read as a comparison of documented prescribing, with the behavioral outcomes considered separately.

7. Results Posted in the Registry

• Patient Navigation Intervention: 47.8% (11/23) versus 42.9% (9/21) on control; risk difference 5.0 percentage points (95% CI -24.4 to 34.4), risk ratio 1.12 (0.58–2.14); unadjusted two-proportion z-test p = 0.741.

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.

Number of Participants With Self-reported Smoking Cessation

• 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:
  • Patient Navigation Intervention: 8.7% (2/23) versus 4.8% (1/21) on control; risk difference 3.9 percentage points (95% CI -10.7 to 18.6), risk ratio 1.83 (0.18–18.70); unadjusted two-proportion z-test p = 0.605.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Patient Navigation Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Utilization of Smoking Cessation Medication

• 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:
  • Patient Navigation Intervention: 30.4% (7/23) versus 38.1% (8/21) on control; risk difference -7.7 percentage points (95% CI -35.7 to 20.4), risk ratio 0.80 (0.35–1.82); unadjusted two-proportion z-test p = 0.592.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Patient Navigation Intervention and the control. The interval gives the range of effects that remain compatible with the data.

Number of Participants With Stage of Change for Smoking Cessation

• 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:
  • Patient Navigation Intervention: 17.4% (4/23) versus 14.3% (3/21) on control; risk difference 3.1 percentage points (95% CI -18.4 to 24.6), risk ratio 1.22 (0.31–4.82); unadjusted two-proportion z-test p = 0.778.
• Interpretation:
  • The 95% confidence interval includes no difference, so these data do not show a statistically significant difference between Patient Navigation Intervention and the control. The interval gives the range of effects that remain compatible with the data.

The registry lists secondary outcomes covering self-reported cessation, use of smoking-cessation medication, stage of change, nicotine-dependence score, and other tobacco-treatment support. Numerical findings are posted for the first three of these. Across those binary outcomes, the estimates do not all point in the same direction, and the reported intervals leave substantial uncertainty. Numerical results for the Fagerstrom score and other tobacco-treatment support are not reported in the registry record.

These outcomes relate to the primary result by describing different parts of the cessation process. A prescription sent to a pharmacy is a recorded care action; medication utilization concerns use, while self-reported cessation concerns reported behavior. Stage of change provides a separate measure of readiness. Agreement across outcomes could offer a coherent descriptive pattern, but disagreement is not inherently contradictory because the measures capture different events and can be affected by different sources of error. The secondary findings do not establish whether the primary process-of-care outcome changed.

The secondary comparisons are unadjusted, and the registry does not report a plan for controlling the chance of false-positive findings across multiple outcomes. When many outcomes are examined, interpreting each nominal p-value as if it were the only test can overstate the strength of evidence. The lack of a reported multiplicity approach means these secondary results should carry less inferential weight than a prespecified primary comparison. They are best treated as exploratory descriptions rather than independent confirmation of a treatment effect.

The registry record does not report how missing secondary outcome data were handled, whether the outcomes were assessed in all randomized participants, or whether the secondary hypotheses and analysis methods were prespecified. Those omissions make it difficult to distinguish a planned pattern of analyses from selective availability of results. The secondary outcomes can therefore inform questions for future research, but they should not be used to make a definitive claim about the intervention’s effect.

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

• Number of Participants With Self-reported Smoking Cessation
• Number of Participants With Utilization of Smoking Cessation Medication
• Number of Participants With Stage of Change for Smoking Cessation
• Mean Fagerstrom Test Score for Nicotine Dependence
• Use of Other Tobacco Treatment Support

9. Statistical Interpretation

10. Statistical Methods Explained

The primary result is a binary outcome: each participant either did or did not have a prescription sent to a pharmacy according to chart review. For such an outcome, an arm-level risk describes the fraction of participants with the event. The posted risks are 0.429 for enhanced traditional care and 0.478 for patient navigation. The absolute comparison is expressed as a risk difference, calculated in the posted analysis as the patient-navigation risk minus the enhanced-traditional-care risk. Its estimate is 0.050.

What does the risk difference express?

A risk difference is an absolute contrast between the event probabilities in two groups. A value of zero corresponds to equal observed risks; a positive value means the event was more frequent in the intervention arm, and a negative value means it was less frequent. Here the direction of the point estimate is positive, but the interval ranges from -0.244 to 0.344. This range communicates that the estimate is uncertain and that plausible values include both directions. It is not a statement that every value in the interval is equally likely.

What does the p-value add?

The reported p-value for the primary comparison is 0.741 and is labeled unadjusted. A p-value describes how compatible the observed data are with a specified null model, typically one in which the compared risks do not differ. It is not the probability that the null hypothesis is true, the probability that a result occurred by chance, or a measure of clinical importance. A large p-value does not establish equivalence. Interpretation should be considered alongside the effect estimate and its interval, particularly when the interval is wide.

Why report relative measures too?

The registry also reports risk ratios and odds ratios for the primary comparison: the risk ratio is 1.116 with an interval from 0.581 to 2.144, and the odds ratio is 1.222 with an interval from 0.372 to 4.018. A risk ratio compares event probabilities as a ratio, while an odds ratio compares event odds. These measures answer a different scale of question from the absolute risk difference. They should not be confused with the number of participants experiencing the outcome, and they do not remove uncertainty in the underlying data. With a binary outcome, the absolute difference is often easier to interpret as a change in event probability, while relative measures can offer a complementary description.

How should the counts and denominators be read?

The primary counts are 9 in enhanced traditional care and 11 in patient navigation; the arm sizes are 21 and 23. A count alone does not account for the number of participants in each arm, so interpretation should use the corresponding group size and the reported risks. These are arm-level results. The registry does not report whether every randomized participant contributed to each outcome, how missing outcome information was handled, or the analysis population used. No conclusion about missingness or an intention-to-treat analysis can therefore be made from the record.

What does randomization contribute?

Random assignment is intended to make treatment groups comparable on average, including on factors that were not measured. It does not guarantee balance in a small trial, and it does not prevent bias from missing data, measurement, or departures from assigned treatment. The trial is described as randomized and parallel, but the registry does not report sequence generation, allocation concealment, adherence, crossovers, or other implementation details. No masking was used. These features matter especially for participant-reported outcomes and for care processes that may be influenced by awareness of group assignment.

The registry reports no adjusted analyses. The comparisons should therefore be read as the posted unadjusted arm-level contrasts, not as estimates adjusted for baseline characteristics or other covariates. No regression model, stratification procedure, or covariate-adjustment plan is reported in the registry record. The same restraint applies to the secondary outcomes: their unadjusted results should not be interpreted as confirmatory evidence when the approach to multiple testing is not reported.

Finally, the planning figures are separate from the observed outcome analysis. They use the observed primary effect as a starting point and illustrate sample sizes under stated planning assumptions. They do not recover the trial’s original design rationale, which is not reported in the registry record. The result itself remains the observed randomized comparison, with uncertainty conveyed by its interval.

11. Confidence Intervals and Precision

The primary risk-difference estimate is 0.050, and its reported interval extends from -0.244 to 0.344. Because the interval includes zero, the data are compatible with no difference in the underlying risks. Because it also extends to values on either side of zero, it allows for lower as well as higher risk in patient navigation. The interval is broad relative to the point estimate, so the estimate is not precise enough to distinguish these possibilities well.

A confidence interval is a way to describe statistical uncertainty around an estimate under the method used to construct it. In general, an interval that is narrower indicates greater precision, while a wider interval indicates that the data leave a broader range of effects plausible. The interval does not mean that there is a particular probability that the true effect lies within the specific reported bounds. The registry record does not state the confidence level or interval-construction method, so those details should not be inferred.

The relative measures are also uncertain: the primary risk ratio is 1.116, with a reported interval from 0.581 to 2.144, and the odds ratio is 1.222, with an interval from 0.372 to 4.018. These ranges include the value corresponding to no relative difference. Taken together, the absolute and relative results show that the point estimate alone is an incomplete summary; the uncertainty is substantial.

The small arm sizes and limited number of observed events contribute to the difficulty of estimating a binary outcome precisely. The registry does not report missing-data details or whether the analysis included every randomized participant, which further limits assessment of precision and potential bias. The appropriate conclusion is not that the arms are equivalent, but that the posted estimate leaves considerable uncertainty about the direction and size of any difference.

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 sample-size figures are planning illustrations based on the observed primary effect, not the original design assumptions for this trial. The trial’s own sample-size justification is not reported in the registry record. The stated illustration 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 to a stated fraction of the observed effect.

For the primary endpoint, using 100% of the observed effect gives 1,575 participants per arm for 80% power and 2,108 participants per arm for 90% power. Planning for 75% of the observed effect gives 2,794 participants per arm for 80% power and 3,739 participants per arm for 90% power. Planning for 50% of the observed effect gives 6,269 participants per arm for 80% power and 8,391 participants per arm for 90% power. These figures are participants per arm, not total participants or total events.

In plain terms, the 80% and 90% power columns describe different planning targets for the chance of detecting the stated effect under the assumptions. The higher power target requires a larger planned sample. The rows also illustrate that smaller effects need more participants to detect, because a smaller separation between groups is harder to distinguish from sampling variation. The curve should be read in the same planning context: it relates the assumed effect size to the sample size needed under the stated assumptions.

These are not observed power. They are not a retrospective measure of the probability that the trial detected an effect, and they do not show what the trial was originally designed to achieve. They are illustrative calculations based on the observed result, which is itself uncertain.

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 = 0.429; treatment proportion p₁ = 0.478; average p̄ = 0.453.
2. First term: z_1−α/2 × √[2p̄(1−p̄)] = 1.96 × 0.7040 = 1.3799.
3. Second term: z_1−β × √[p₀(1−p₀) + p₁(1−p₁)] = 0.842 × 0.7032 = 0.5918.
4. n = (1.3799 + 0.5918)² / (0.0497)² = 1,574.5, rounded up to 1,575 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 <- 0.428571428571429                          # control proportion
p1 <- 0.478260869565217                          # 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(3452371)
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 = 1,575 (80% power), 2,108 (90% power)
 75% of observed effect: n per arm = 2,794 (80% power), 3,739 (90% power)
 50% of observed effect: n per arm = 6,269 (80% power), 8,391 (90% power)
power.prop.test: 1574.5 
Simulated power at n = 1,575 per arm: 0.801 (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

The registry names a primary endpoint and five secondary outcomes. The primary endpoint is the chart-based count of participants with a prescription sent to a pharmacy. Secondary outcomes cover self-reported smoking cessation, medication utilization, stage of change, nicotine-dependence score, and other tobacco-treatment support. Numerical secondary results are posted for three outcomes; numerical results for the other two are not reported in the registry record.

Testing several outcomes creates a multiplicity issue: even if none of the interventions has an effect, examining many comparisons can increase the chance that at least one appears unusually positive or negative. Statistical approaches can address this by controlling an overall error rate or by treating secondary comparisons as exploratory. The registry does not report a multiplicity adjustment, a hierarchy for secondary outcomes, or a prespecified distinction between confirmatory and exploratory tests. The unadjusted secondary p-values should therefore be interpreted cautiously and should not be treated as if they were independent confirmatory evidence.

The registry does not report the analysis plan, including whether adjustment for baseline variables was intended, how model assumptions were checked, or which statistical population was used. It also does not report missing-data counts, reasons for missingness, imputation procedures, or sensitivity analyses. The record consequently does not establish whether each outcome analysis included all randomized participants or only participants with available outcome information. Missing data can affect both the estimated group comparison and its uncertainty, especially when availability differs by arm or relates to outcome status.

Although randomization is reported, the registry does not describe how sequence generation or allocation concealment was implemented. No masking was used. These registry entries do not demonstrate that bias occurred, but they are relevant when judging the strength of the evidence, particularly for self-reported outcomes. Without further analysis details, the posted arm-level comparisons are most appropriately interpreted as unadjusted results whose robustness to missingness and analytic choices cannot be assessed from 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 reports zero serious adverse events among 21 participants at risk in enhanced traditional care and zero among 23 participants at risk in patient navigation. It also reports zero other adverse events in each arm and zero deaths in each arm. No serious adverse event terms are listed.

These figures mean that no events in the reported categories were recorded for the participants included in the safety counts. They do not show that the risk of an adverse event is zero, nor do they establish that the arms have equivalent safety. With limited numbers of participants, uncommon events may not appear in the observed results. The registry does not report definitions for the event categories, the method or duration of safety surveillance, or whether all participants contributed complete safety follow-up.

Safety counts should be read as descriptive registry results rather than as a comprehensive estimate of risk. The absence of reported events in this trial does not rule out events that were not detected, not collected, or not included in the posted record.

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

The primary result describes the number of participants whose charts recorded a prescription for an FDA-approved smoking-cessation medication being sent to a pharmacy within three months. The observed counts were 9 in enhanced traditional care and 11 in patient navigation. The estimated risk difference was 0.050, with a reported interval from -0.244 to 0.344. This is a positive point estimate, but the interval is broad and includes no difference as well as effects in either direction.

The finding therefore does not establish that patient navigation increased prescribing, and it does not establish that the approaches were equivalent. It also does not answer whether participants filled prescriptions, used medication, or stopped smoking. Those are distinct outcomes. Self-reported cessation and medication utilization appear as secondary outcomes, and their posted results also have substantial uncertainty.

The study is identified as a pilot randomized controlled trial. Its results are useful as an estimate from a randomized comparison and as a description of the outcomes recorded in the trial, but they are not precise enough to support a firm conclusion about the size or direction of an effect. The registry does not report an original sample-size justification, analysis plan, missing-data handling, or analysis population, so the intended inferential framework and the sensitivity of results to analytic choices cannot be assessed.

General statistical interpretation also distinguishes absence of strong evidence from evidence of absence. A large p-value or an interval that includes zero does not show that two approaches are identical. It indicates that the observed data do not sharply distinguish among a range of possible differences. The data support describing the observed results and their uncertainty, not making a definitive causal or clinical claim.

17. Why This Trial Matters Statistically

This trial is statistically informative because it illustrates the difference between an observed direction of effect and a precise estimate. For the primary endpoint, the point estimate favors a higher recorded prescription risk in patient navigation, but its interval is wide and crosses zero. Treating the point estimate alone as a conclusion would ignore substantial uncertainty; treating the p-value alone as proof of no difference would make a different error.

The endpoint also highlights the importance of defining what an outcome actually measures. A prescription sent to a pharmacy is a documented care process, not medication use or smoking cessation. Keeping these outcomes distinct prevents the result from being interpreted as evidence about an event the endpoint did not measure. The secondary outcomes offer related but non-identical perspectives, and their mixed directions reinforce the need to interpret each measure on its own terms.

The pilot designation and the small arm sizes make the precision issue especially visible. Binary outcomes with limited observed counts can yield broad uncertainty, so larger-sample planning illustrations should not be mistaken for a statement about the trial’s original design or for retrospective power. The record’s lack of a reported multiplicity strategy, analysis plan, and missing-data procedures also shows why registry results need both numerical interpretation and careful attention to what is not documented.

For clinical researchers, the central statistical lesson is to consider the effect estimate, its interval, the outcome definition, and the analysis context together. The posted findings describe an uncertain randomized comparison; they do not provide a definitive answer about whether navigation changes the primary outcome.

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 primary limitation is statistical precision. The registry reports 21 participants in enhanced traditional care and 23 in patient navigation for the primary outcome, with 9 and 11 events, respectively. The primary risk-difference interval extends from -0.244 to 0.344, leaving substantial uncertainty about both direction and magnitude. The trial’s pilot designation is important context, but the original sample-size justification is not reported in the registry record.

The study was unmasked. This is relevant because assignment could be known during care, and some secondary outcomes rely on self-report. The primary endpoint is chart-based, but the registry does not describe chart-review procedures, reviewer masking, validation, or how prescriptions recorded outside the reviewed chart would be captured. It also does not report allocation concealment or the random-sequence method.

The registry does not report missing-data counts or handling, the analysis population, adherence to assigned intervention, or sensitivity analyses. It is therefore not possible to determine from the record whether each outcome analysis included all randomized participants or whether missingness could have influenced comparisons. No adjusted analyses are reported, and no multiplicity approach for the secondary outcomes is described.

Assessment is reported at three months. Longer-term outcomes are not reported in the registry record, so durability beyond that assessment cannot be evaluated. The intervention description specifies up to ten hours of navigation over three months, but the record does not report the amount of navigation actually received or implementation fidelity. Finally, the primary measure captures prescriptions sent, not dispensing, medication use, or cessation. These limitations define the scope of the result and caution against extending it to outcomes that were not measured by the primary endpoint.

19. Related Tutorials

20. Related Statistical Calculators

21. Sources

• ClinicalTrials.gov: Hospital-based Patient Navigation and Smoking Cessation — NCT03452371.
• Registry record last updated 2020-03-31; status last verified 2020-03.
• Results first posted 2020-03-31.
• 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

NCT03452371 is a completed, randomized, parallel-group pilot trial of hospital-based patient navigation versus enhanced traditional care for smokers hospitalized on general internal medicine or family medicine services. The registry reports no masking and enrollment of 44 participants. Patient navigation could be delivered in person or by telephone, with up to ten hours over three months.

The primary endpoint was the chart-based count of participants with a prescription for an FDA-approved smoking-cessation medication sent to a pharmacy by three months. The registry reports 9 of 21 in enhanced traditional care and 11 of 23 in patient navigation. The risk-difference estimate is 0.050, with a reported interval from -0.244 to 0.344 and an unadjusted p-value of 0.741. The estimate is imprecise and does not establish a difference or equivalence.

Secondary results are posted for self-reported cessation, medication utilization, and stage of change. Numerical findings for the Fagerstrom score and other tobacco-treatment support are not reported in the registry record. The record also does not report the original sample-size justification, analysis plan, multiplicity approach, or missing-data handling.