Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study

Abstract

Patient-reported experience measures (PREM) capture critical aspects of stroke care quality that are not typically reflected in conventional clinical outcomes, particularly during care transition. This quality improvement initiative sought to incorporate PREM into standard acute stroke care and assess the impact of a Patient-Oriented Discharge Summary (PODS) on patient experience and discharge readiness. Employing a two-cycle Plan–Do–Study–Act methodology, a stroke-specific patient experience survey was developed and administered at discharge to patients admitted with stroke or transient ischemic attack (TIA) at Health Sciences North, Sudbury, Ontario. Baseline findings identified experience-related deficiencies despite high overall satisfaction, notably in discharge preparedness, shared decision-making, and information clarity. A PODS-based discharge intervention was implemented and evaluated using defect and top-box analyses. Post-implementation, overall defect rates significantly decreased, and top-box performance improved across all experience domains, most notably in the understanding of the condition and readiness for discharge. These findings indicate that systematic measurement of patient experience, coupled with structured discharge communication, can substantially enhance care transitions and bolster the quality and safety of acute stroke services.

Keywords

Patient-reported experience measures patient oriented discharge summary acute stroke care discharge communication

Background

Stroke remains a predominant cause of mortality and long-term disability globally, with over 878,000 Canadians currently living with the effects of stroke or TIA.¹ Advances in hyperacute treatment and structured stroke unit care have significantly enhanced survival and functional outcomes.² Beyond these gains, high-quality stroke care encompasses more than prompt medical intervention; it necessitates effective communication, patient engagement, and secure transitions throughout the continuum of care. PREM are increasingly acknowledged as vital indicators of healthcare quality, as they capture dimensions of care that are not reflected in traditional clinical outcomes, such as information clarity, shared decision-making, and discharge readiness.³

The significance of patient experience is particularly evident in the context of stroke care. Stroke survivors and their caregivers must swiftly assimilate complex information regarding diagnosis, medications, risk factor management, rehabilitation, and follow-up. Research consistently indicates that when patients feel informed, respected, and involved in decision-making, they are more likely to adhere to secondary prevention strategies, engage in rehabilitation, and report improved psychological and functional outcomes.^4,5 Conversely, poor communication and inadequate discharge education are associated with confusion, medication errors, caregiver burden, and increased rates of emergency department (ED) visits and readmissions.^6,7

Despite the existing evidence, the routine collection of stroke-specific PREM remains infrequent. A recent systematic review identified only two validated stroke PREM instruments, both of which were methodologically limited or impractical for routine clinical application.⁸ Consequently, most stroke units lack a structured mechanism to capture patient experience data and utilize it for improvement purposes. This omission creates a significant blind spot in quality measurement, particularly in areas such as discharge readiness and care transitions, which are recognized as high-risk periods for adverse events.⁹

Patient-oriented discharge tools are a promising strategy for addressing this issue. PODS provides structured, individualized information on medications, warning signs, and follow-up care which has demonstrated efficacy in improving patient understanding, reducing anxiety, and enhancing post-discharge safety in general medical populations.¹⁰ However, their application in acute stroke units has been limited, despite the complexity and vulnerability of this patient population.

At our institution, although clinical stroke outcomes were robust, no formal mechanism existed to systematically capture patient experiences or to assess discharge preparedness. This quality improvement (QI) initiative was designed to integrate patient-reported experience measurements into routine stroke care and to employ iterative Plan–Do–Study–Act (PDSA) cycles to identify and address gaps in discharge communication through the implementation of a PODS tool. By aligning patient experience data with evidence-based discharge practices, we aimed to strengthen the transition of care and enhance patient-centred stroke services.

Methods

Study Design

This QI initiative was a component of the MObile TIA and Stroke with AdaptiVE Workflow (MOTIVE) project. The initiative involved the execution of two PDSA cycles. The first cycle was dedicated to the creation and implementation of a patient experience survey, which served to establish a baseline for patient experience and identify existing gaps in care. The second cycle focused on evaluating a targeted intervention aimed at enhancing communication and preparedness during patient discharge. The reporting adhered to the SQUIRE 2.0 guidelines for quality-improvement studies.¹¹

Setting and Participants

The QI initiative was implemented at Health Sciences North, Sudbury, Ontario, Canada. Individuals aged > 18 years who experienced TIA or stroke and were admitted between July and November 2025 were eligible for participation. In instances where patients were unable to complete the survey due to cognitive, speech, or physical impairments resulting from stroke, such as aphasia, a substitute decision maker or caregiver completed it on their behalf.

PDSA Cycle 1: Baseline Measurement and Gap Identification

Planning and Survey Development

A multidisciplinary QI team comprising of a stroke neurologist, an advanced practice physiotherapist, a stroke nurse, and hospital leadership, including the Medicine Program Administrative Director, Clinical Manager, and Regional Stroke Program Director, developed a stroke-specific patient experience questionnaire through an iterative process that mapped the inpatient stroke journey from admission to discharge. Five core experiential domains were identified: transition into the Stroke Unit, quality of care and support, patient involvement in decision-making, clarity of information about stroke and medications, and preparedness for discharge. Survey development was guided by the Donabedian framework ¹², focusing on the process and outcome domains of healthcare quality (Box 1). Structural elements such as staffing and infrastructure were excluded because they were not expected to change during the study and were not reliably assessed through self-reports by patients. The decision to develop a new instrument rather than adapting an existing stroke PREM was informed by the findings of Cornelis et al ⁸. Their systematic review identified only two validated stroke PREM tools, both of which were either methodologically limited in their psychometric properties or impractical for routine bedside administration in an acute care quality improvement context. Consequently, our questionnaire was purpose-built to align with the specific care pathway at our institution, prioritizing clinical actionability over comprehensive psychometric profiling. Seven questions were developed to capture experiences related to care transitions, diagnostic processes, communication, shared decision-making, perceived safety, satisfaction with care, and readiness for discharge. Responses were measured using a widely adopted 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5), facilitating quantitative analysis of the patient experience.¹³ The questionnaire was pilot-tested for clarity and face validity with two stroke inpatients, and no modifications were made. Although this QI study confirmed the face validity and comprehensibility of the instrument, it did not undergo formal psychometric validation, such as assessments of construct validity and test–retest reliability. This is because the instrument was intended for pragmatic QI purposes rather than as a research-grade tool. This limitation should be considered when interpreting the findings.

Data Collection

Data collection occurred over 30 days in July 2025. The project lead identified eligible patients. A reactivation worker approached patients or caregivers upon discharge and invited them to complete an anonymous electronic survey. Participation was voluntary, and the study purpose was explained as an effort to improve the care processes.

Analysis

Survey data were systematically compiled and analyzed using Excel, and response frequencies were illustrated using bar charts. A Pareto analysis was conducted to prioritize the domains based on the proportion of defects, defined as Neutral, Disagree, or Strongly Disagree responses. In accordance with the QI methodology, performance was assessed against predefined standards, with responses below the desired threshold identified as opportunities for improvement rather than measures of relative satisfaction.¹⁴ As the instrument was designed for formative internal improvement rather than external benchmarking, neutral responses were classified as unmet care standards, consistent with defect-based and threshold-focused analytical frameworks in patient experience assessment.^14,15 For pairwise comparisons of defect proportions between cycles, Fisher's exact test was chosen because of the anticipated small cell counts in several domains. Analyses were conducted at the item-response level to increase statistical power and sensitivity to domain-specific changes ¹³, with the potential impact of within-patient clustering acknowledged in the limitations section.

Box 1.

Mapping of Survey Items to the Donabedian Framework Domains

Process Domain

Care transitions: My move from the ED or ICU to the Stroke Unit (5 South) was smooth and well-coordinated.
Diagnostic processes: I felt comfortable and safe when going for important scans (like CT or MRI).
Patient-centred care & shared decision-making: I was included in decisions about my care, recovery, and treatment goals
Communication & education: I received helpful information about my condition;
I was given information about my medications, and my questions were answered.
Discharge planning: I felt ready to leave the hospital and knew what to expect for my follow-up care, including appointments like the Stroke Prevention Clinic.

Outcome Domain

Perceived safety and comfort: I felt comfortable and safe
Satisfaction with care: I was satisfied with the overall care and support provided on the Acute Stroke Unit (5 South).
Readiness for discharge: I felt ready to leave the hospital.

PDSA Cycle 2: Patient-Oriented Discharge Summary (PODS) Intervention

Intervention

The initial PDSA Cycle results underscored the need for improvements in discharge communication and readiness. In response, the same multidisciplinary team developed a PODS. This tool, in alignment with the Canadian Stroke Best Practice Recommendations ¹⁶, was designed to enhance clarity, consistency, and patient engagement during discharge. The PODS features visual icons, personalized medication lists, symptom red flags, and clearly defined follow-up and contact information, all designed to aid patients in understanding and self-managing their condition (Appendix 1).

Implementation

The PODS was implemented over three months, involving 63 consecutive patients discharged from the Acute Stroke Unit. A trained stroke nurse provided structured discharge education utilizing the PODS framework and systematically reviewed each section with both patients and their caregivers. To support intervention fidelity, the designated stroke nurse used a standardized PODS checklist for each discharge. The project lead evaluated the patient-reported responses and offered feedback to ensure the consistent and comprehensive delivery of all PODS components. The delivery was intentionally restricted to a single trained stroke nurse during this cycle, thereby minimizing the variability in the administration of the intervention. In subsequent PDSA cycles, implementation will be expanded to include stroke nurses across rotational shifts, supported by standardized training sessions to ensure delivery consistency and enable formal evaluation of fidelity across multiple providers.

Evaluation

The evaluation of patient experience following the introduction of PODS was conducted using the same questionnaire as in PDSA Cycle 1, allowing for a direct comparison with the baseline data. Descriptive statistics and top-box analysis were used to examine changes in patient-reported outcomes, with 95% confidence intervals calculated for defect proportions and α-level set at 0.05. Pairwise comparisons of defect proportions between cycles were conducted using Fisher's exact test. Defect rates were analyzed to determine the extent of the improvements, and a deterministic sensitivity analysis was conducted by adjusting the baseline defect counts by ±1 response to evaluate the robustness against sampling variability.

Results

The study sample consisted of an equal distribution of female and male participants, each representing 50% of the total sample. The electronic survey platform automatically recorded an average completion time of 57 s from the first-item display to the final submission, reflecting the instrument's design of seven single-item Likert-scale questions, each requiring a single tap or click.

The majority of the respondents (65%) were admitted with a diagnosis of stroke, while 35% were diagnosed with a transient ischemic attack (TIA). The surveys were primarily completed by patients, accounting for 94% of the responses, with the remaining 6% being completed by caregivers. In the initial PDSA cycle, 26 patients completed the seven-item survey, yielding 182 item-level responses. In the subsequent PDSA cycle, 63 patients completed the same survey, generating 441 item-level responses. Defect and top-box analyses were conducted at the item response level to enhance statistical power and sensitivity to domain-specific variations. The analytical implications of this approach, including the potential effect of within-patient clustering, are addressed in the limitations section.

PDSA Cycle 1: Baseline Experience and Defect Analysis

Initial patient experience ratings were notably high across all domains, with the majority of respondents indicating agreement or strong agreement. The absence of disagreement or strong disagreement responses produced a ceiling effect, limiting the utility of the mean-based analyses. Defects were defined as neutral, disagree, or strongly disagree responses to the questions. At baseline, defect rates ranged from 0.0% to 19.2% across the survey domains, with the highest rates observed in discharge readiness (19.2%), inclusion in decision-making (15.4%), and receipt of helpful information regarding the patient's condition (11.5%). No defects were identified in the domain evaluating the smoothness of transfer from the ED or ICU to the Stroke Unit (Table 1). The defect proportions and corresponding 95% confidence intervals for each survey domain are presented in Table 2. The Pareto analysis confirmed that discharge readiness, inclusion in decision-making, and condition-related information collectively accounted for the majority of baseline defects (Figure 1).

Figure 1.

Pareto chart % of defects by survey category.

Table 1.

Comparison of Defect Percentages Between PDSA Cycle 1 and Cycle 2.

Survey Questions / Likert Ratings (1–5)	PDSA Cycle 1 (n = 26)						PDSA Cycle 2 (n = 63)						p-Value (Fisher's Exact Test)
Survey Questions / Likert Ratings (1–5)	5 (n = 26)	4 (n = 26)	3 (n = 26)	2 (n = 26)	1 (n = 26)	% of defects	5 (n = 63)	4 (n = 63)	3 (n = 63)	2 (n = 63)	1 (n = 63)	% of defects	p-Value (Fisher's Exact Test)
Q1: I was satisfied with the overall care and support provided on the Acute Stroke Unit (5 South).	15	10	1	0	0	3.85	24	35	4	0	0	6.35	1*
Q2: I was given information about my medications, and my questions were answered.	12	13	1	0	0	3.85	35	26	2	0	0	3.17	1*
Q3: I felt comfortable and safe when going for important scans (like CT or MRI).	11	13	2	0	0	7.69	31	29	3	0	0	4.76	0.6199*
Q4: I received helpful information about my condition.	10	13	3	0	0	11.54	35	26	2	0	0	3.17	0.15*
Q5: I was included in decisions about my care, recovery, and treatment goals.	13	9	4	0	0	15.38	25	37	1	0	0	1.59	0.023**
Q6: I felt ready to leave the hospital and knew what to expect for my follow-up care, including appointments like the Stroke Prevention Clinic.	8	13	5	0	0	19.23	28	33	2	0	0	3.17	0.02**
Q7: My move from the Emergency Department (ED) or Intensive Care Unit (ICU) to the Stroke Unit (5 South) was smooth and well-coordinated.	9	17	0	0	0	0	31	32	0	0	0	0	1*
Cumulative defects across all domains			Defects: 16/182			8.79%			Defects: 14 / 441			3.17%	0.0062**

Footnotes: *Non-significant; **Significant; Likert Ratings (5: Strongly Agree, 4: Agree, 3: Neutral (neither agree nor disagree), 2: Disagree, 1: Strongly Disagree).

Table 2.

Defect Proportions and 95% Confidence Intervals by Survey Domain Across PDSA Cycles.

Survey Questions	PDSA Cycle 1% Defects	PDSA Cycle 1 95% CI	PDSA Cycle 2% Defects	PDSA Cycle 2 95% CI
Q1: I was satisfied with the overall care and support provided on the Acute Stroke Unit (5 South).	3.85%	(0.7%, 18.9%)	6.35%	(2.5%, 15.2%)
Q2: I was given information about my medications, and my questions were answered.	3.85%	(0.7%, 18.9%)	3.17%	(0.9%, 10.9%)
Q3: I felt comfortable and safe when going for important scans (like CT or MRI).	7.69%	(2.1%, 24.1%)	4.76%	(1.6%, 13.1%)
Q4: I received helpful information about my condition.	11.54%	(4.0%, 29.0%)	3.17%	(0.9%, 10.9%)
Q5: I was included in decisions about my care, recovery, and treatment goals.	15.38%	(6.2%, 33.5%)	1.59%	(0.3%, 8.5%)
Q6: I felt ready to leave the hospital and knew what to expect for my follow-up care, including appointments like the Stroke Prevention Clinic.	19.23%	(8.5%, 37.9%)	3.17%	(0.9%, 10.9%)
Q7: My move from the Emergency Department (ED) or Intensive Care Unit (ICU) to the Stroke Unit (5 South) was smooth and well-coordinated.	0.00%	(0.0%, 12.9%)	0.00%	(0.0%, 5.7%)
Cumulative defects across all domains	8.79% (16/182)	(5.5%, 13.8%)	3.17% (14/441)	(1.9%, 5.3%)

95% confidence intervals calculated using the Wilson score method for proportions.

To evaluate the robustness of sampling variability within the baseline cohort, a deterministic sensitivity analysis was performed by adjusting the defect counts in Cycle 1 by ±1 response, which equated to an approximate variation of ±3.85% (1/26 × 100). This adjustment resulted in defect rates ranging from 8.24% to 9.34% (15/182 = 8.24%; 16/182 = 8.79%; 17/182 = 9.34%), in contrast to the 3.17% observed in cycle 2 (14/441 = 3.17%). The direction of the effect remained consistent across all perturbation scenarios, with the observed reduction in defect rates from Cycle 1 to Cycle 2 being maintained under each condition, thereby confirming the stability of the observed improvements. However, the small baseline sample size (n = 26) introduces inherent measurement imprecision, where a single response change can alter defect rates by approximately 3.85%. Consequently, the findings should be interpreted with appropriate caution regarding the precision of baseline estimates.

PDSA Cycle 2: Post-Implementation Defect Analysis

Following the introduction of PODS, there was a notable reduction in defect rates across all previously identified domains of care. Specifically, defects in patient participation in decision-making decreased from 15.4% to 1.6%, and those related to discharge preparedness decreased from 19.2% to 3.2%, respectively. Similarly, the provision of essential condition-related information reduced the defects from 11.5% to 3.2%. Furthermore, defects in medication information and response to patient inquiries declined from 9.6% to 3.2%, and those concerning comfort and safety during imaging procedures decreased from 9.2% to 4.8%. Notably, the domain assessing transitions from the Emergency Department (ED) or Intensive Care Unit (ICU) to the Stroke Unit remained defect-free throughout both PDSA cycles. Overall, the defect rates across all domains decreased from 8.8% (16 of 182 responses) in PDSA Cycle 1 to 3.2% (14 of 441 responses) in PDSA Cycle 2 (Table 1; for 95% confidence intervals by domain, see Table 2), a difference that was statistically significant by Fisher's exact test (p = 0.006).

Top-Box Analysis

Given the high baseline satisfaction scores, a top-box analysis (Table 3) was performed to evaluate respondents selecting the highest response category (“strongly agree”). After PODS implementation, top-box scores increased across all seven survey domains. The most significant improvement was in receiving helpful information about the patient's condition, with top-box responses rising from 38.5% pre-intervention to 55.6% post-intervention, an increase of 17.1 percentage points (pp). Improvements were noted in transition smoothness from the ED or ICU to Stroke Unit (34.6% to 49.2%; +14.6 pp) and overall care satisfaction (57.7% to 69.8%; +12.1 pp). Additional increases in top-box performance were observed for medication education (+9.4 pp), inclusion in decision-making (+8.7 pp), discharge readiness (+7.3 pp), and comfort during imaging (+5.3 pp) (Figure 2). The implementation of the PODS reduced experience-related defects and enhanced top-box performance across domains, with no observed deterioration in patient-reported experience.

Figure 2.

Comparison of Defect Percentages Between PDSA Cycle 1 and Cycle 2.

Table 3.

Top-Box Analysis of Patient Experience.

Survey Questions	Pre-Intervention Top Box (%)	Post-Intervention Top Box (%)	Improvement
My move from the Emergency Department (ED) or Intensive Care Unit (ICU) to the Stroke Unit (5 South) was smooth and well-coordinated.	34.60%	49.20%	14.60%
I felt comfortable and safe when going for important scans (like CT or MRI).	42.30%	47.60%	5.30%
I was satisfied with the overall care and support provided on the Acute Stroke Unit (5 South).	57.70%	69.80%	12.14%
I was included in decisions about my care, recovery, and treatment goals.	50.00%	58.70%	8.73%
I received helpful information about my condition.	38.50%	55.60%	17.10%
I was given information about my medications, and my questions were answered.	46.20%	55.60%	9.40%
I felt ready to leave the hospital and knew what to expect for my follow-up care, including appointments like the Stroke Prevention Clinic.	30.80%	38.10%	7.32%

Discussion

This QI initiative demonstrates that a systematic evaluation of patient experience, followed by a targeted discharge communication intervention, can substantially enhance discharge readiness and perceived quality of care among patients hospitalized with acute stroke. Utilizing a two-cycle PDSA approach, we initially identified a deficiency in discharge preparedness despite high satisfaction with inpatient stroke care. Our study results indicate that PODS implementation is significantly associated with enhanced patient-reported understanding and confidence at discharge, consistent with previous studies.^10,17

Several alternative explanations for the observed improvements are considered. First, the PODS were administered by a single trained stroke nurse, suggesting that the improvements may be attributed to the provider's specific communication skills rather than the intervention itself. Although a structured PODS checklist and feedback based on patient-reported responses were employed to ensure consistency, the potential influence of individual provider factors cannot be entirely ruled out. Second, a Hawthorne effect, whereby increased attention during structured discharge interactions, rather than the intervention's content, affects patient experience, cannot be ruled out in the absence of a concurrent control group, which limits causal inference. Notably, the improvements were not uniform across all domains. Domains directly targeted by PODS, such as discharge readiness, condition-related information, and medication education, exhibited significantly greater gains than those less directly addressed, such as comfort during imaging and transition of care. This pattern aligns more closely with a content-specific intervention effect than with a generalized attention effect. Third, temporal confounding resulting from increased staff awareness of discharge communication during the study period cannot be entirely excluded, although the relatively short study timeframe and the absence of concurrent improvement initiatives mitigate this risk.

These findings are critical because transitions of care represent one of the highest-risk periods for adverse events following stroke.¹⁸ Although stroke units have achieved considerable success in improving survival and neurological outcomes ², patients and caregivers must rapidly assimilate complex information regarding medications, secondary prevention, rehabilitation, and follow-up care after stroke. Our baseline data indicated that even in a high-performing stroke unit, patients remained uncertain about their readiness to leave the hospital after discharge. This observation aligns with previous studies demonstrating that discharge communication is often fragmented, inconsistent, and difficult for patients to recall, particularly after an acute neurological event.^6,7,18,19

The introduction of PODS directly addresses this gap by standardizing and simplifying discharge communication while preserving the individualized content. Improvements were observed in multiple discharge-related domains, including understanding of medications, knowledge of warning signs, and clarity of follow-up plans. These improvements are consistent with prior studies in general medical populations, which have shown that patient-centered discharge tools enhance comprehension, reduce anxiety, and decrease post-discharge safety risks.²⁰ Our study extends this evidence to the acute stroke population, where cognitive impairment, aphasia, and caregiver involvement render structured discharge communication critical.¹⁹ Significantly, the intervention did not compromise the areas that were already performing effectively. Patient satisfaction with inpatient care and care transitions remained high, indicating that PODS enhanced the discharge process without disrupting the existing clinical workflows. The successful integration of PODS into routine practice further attests to its feasibility and acceptability among staff and patients.¹⁰

From a systems perspective, this study demonstrates how PREM can be operationalized as fundamental quality metrics of stroke care. Traditional stroke quality indicators primarily focus on door-to-needle times, imaging, and mortality; however, these do not capture the experiences of patients navigating complex transitions.²¹ By embedding PREM into routine care and linking them to iterative improvement cycles, our approach addresses the critical gap between clinical performance and patient-centered outcomes.

This study addresses a critical gap in the literature, representing one of the initial evaluations of PODS in the context of an acute stroke unit. While the PODS has shown efficacy in general medical populations ^10,17, its application to this high-acuity, neurologically vulnerable population expands the existing evidence base and provides a practical, replicable model for stroke centers aiming to incorporate patient-centered discharge interventions into routine quality improvement efforts.

Limitations

This study had some limitations. First, it was conducted at a single regional stroke center, which may limit the generalizability of the findings to settings with fewer resources or different discharge processes. Second, the small baseline sample size (n = 26) introduces inherent measurement imprecision, wherein a single response change alters defect rates by approximately 3.85%; therefore, baseline proportions should be interpreted as approximate estimates. Third, survey responses may be subject to recall bias, social desirability bias, or the effects of cognitive impairment, despite caregivers completing the survey when necessary. Fourth, the absence of a concurrent control group limits causal inference, as improvements in Cycle 2 may have been influenced by increased staff awareness rather than by PODS alone. However, the stable baseline and repeated use of the same instrument enhanced internal validity.

Fifth, analyses conducted at the item-response level may underestimate standard errors because of within-patient correlations. A supplementary patient-level analysis revealed a directionally consistent reduction in the proportion of patients with at least one defective response, from 46.2% in Cycle 1 to 17.5% in Cycle 2, supporting the robustness of the findings. Sixth, regression to the mean cannot be entirely excluded given the high baseline scores; however, consistent improvements across multiple independent domains argue against this as the sole explanation. Seventh, as PODS were delivered by a single trained nurse, the influence of provider-specific communication skills on the observed improvements cannot be fully excluded. Eighth, the instrument was developed for pragmatic QI purposes and did not undergo formal psychometric validation, including assessments of construct validity and test-retest reliability. Finally, this initiative focused on patient-reported experiences rather than downstream clinical outcomes; future research should evaluate whether PODS leads to measurable reductions in healthcare utilization and adverse events in the long term.

Conclusion

This two-cycle QI initiative demonstrated that integrating PREM into routine acute stroke care is feasible and impactful. Despite high baseline satisfaction, systematic measurements revealed significant gaps in discharge readiness and communication. The implementation of PODS significantly reduced experience-related defects and improved top-box performance across key domains, without disrupting existing workflows. These findings underscore the value of PREM as complementary quality indicators to traditional clinical metrics and demonstrate that embedding patient-centered discharge tools within iterative improvement cycles can strengthen care transitions and enhance the safety and quality of stroke services. Future research should evaluate whether improvements in discharge experience associated with PODS translate into measurable reductions in hospital readmission and emergency department visits, and assess the sustainability and scalability of the intervention across regional stroke networks.

Data Privacy and Informed Consent

All survey responses were collected anonymously through an electronic platform, and no personally identifiable information was recorded. Participation was voluntary, and verbal consent was obtained prior to completing the survey. Data were stored on password-protected institutional servers accessible only to the QI team members. Conflicts of Interest: The authors declare no conflicts of interest.

Supplemental Material

sj-doc-1-jpx-10.1177_23743735261448450 - Supplemental material for Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study

Supplemental material, sj-doc-1-jpx-10.1177_23743735261448450 for Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study by Venkadesan Rajendran, PT, PhD, MEd, GCStroke, MPT (Neurology), BPT, Susan Bursey, PT, BSc. P. T, Chantal Liddard, RN, M.N, BScN, Lisa Zeman, RN, and Ravinder-Jeet Singh, MD in Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study

Supplemental Material

sj-doc-2-jpx-10.1177_23743735261448450 - Supplemental material for Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study

Supplemental material, sj-doc-2-jpx-10.1177_23743735261448450 for Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study by Venkadesan Rajendran, PT, PhD, MEd, GCStroke, MPT (Neurology), BPT, Susan Bursey, PT, BSc. P. T, Chantal Liddard, RN, M.N, BScN, Lisa Zeman, RN, and Ravinder-Jeet Singh, MD in Improving Patient Experience and Discharge Readiness in Acute Stroke Care Through a Patient-Oriented Discharge Summary: A Two-Cycle Quality Improvement Study

Footnotes

Acknowledgements

We sincerely thank all participants for taking the time to complete the survey, as it provides us with valuable information to improve our service.

Authors’ Contribution

The initial proposal was conceived by VR and RJS. VR took the lead in writing the first draft. The proposal was critically reviewed by SB, CL, and LZ, whose contributions were invaluable for refining the proposal. All authors approved this proposal.

Consent for Publication

Not applicable.

Data Availability Statement

Data available upon request.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article

Ethical Approval

The Health Sciences North Research Ethics Board (HSN REB) has conducted a review of this project (#25-21) and determined that it is exempt from requiring REB approval, as it complies with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS 2 - 2022).

Funding

This quality improvement initiative was implemented as a component of the MOTIVE project, which received funding from the Ontario Ministry of Health Innovation Fund.

ORCID iDs

Venkadesan Rajendran

Susan Bursey

Chantal Liddard

Ravinder-Jeet Singh

Supplemental Material

Supplemental material for this article is available online.

References

Public Health Agency of Canada. Stroke in Canada. Canada.ca. Published June 23, 2022. Updated 2022. Accessed January 21, 2026. https://www.canada.ca/en/public-health/services/publications/diseases-conditions/stroke-in-canada.html

Stroke Unit Trialists’ Collaboration. Organised inpatient (stroke unit) care for stroke. Cochrane Database Syst Rev. 2013;2013(9):CD000197. doi: 10.1002/14651858.CD000197.pub3. Update in: Cochrane Database Syst Rev. 2020 Apr 23;4:CD000197. doi: 10.1002/14651858.CD000197.pub4. PMID: 24026639; PMCID: PMC6474318.

Wolf

Niederhauser

Marshburn

LaVela

. Reexamining “defining patient experience”: the human experience in healthcare. Patient Experience Journal. 2021;8(1):16–29. doi: 10.35680/2372-0247.1594

Haley

Marino

Sheehan

Rhodes

Kissela

Roth

. Stroke survivor and family caregiver reports of caregiver engagement in stroke care. Rehabil Nurs. 2019;44(6):302–10. doi: 10.1097/rnj.0000000000000100. PMID: 31689247.

Lutz

Young

Cox

Martz

Creasy

. The crisis of stroke: experiences of patients and their family caregivers. Top Stroke Rehabil. 2011;18(6):786–97. doi: 10.1310/tsr1806-786. PMID: 22436315; PMCID: PMC3822775.

Kripalani

LeFevre

Phillips

Williams

Basaviah

Baker

. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–41. doi: 10.1001/jama.297.8.831. PMID: 17327525.

DeSai

Janowiak

Secheli

, et al. Empowering patients: simplifying discharge instructions. BMJ Open Qual. 2021;10(3):e001419. doi: 10.1136/bmjoq-2021-001419. PMID: 34521621; PMCID: PMC8442096.

Cornelis

den Hartog

Bastemeijer

Roozenbeek

Nederkoorn

Van den Berg-Vos

. Patient-Reported experience measures in stroke care: a systematic review. Stroke. 2021;52(7):2432–5. doi: 10.1161/STROKEAHA.120.034028. Epub 2021 May 10. PMID: 33966497.

Springer

Hodges

Lanning

Tupper

Skolarus

. Using qualitative data to inform the adaptation of a stroke preparedness health intervention. Qual Res Med Healthc. 2023;6(3):10639. doi: 10.4081/qrmh.2022.10639. PMID: 37440990; PMCID: PMC10336881.

10.

Hahn-Goldberg

Huynh

Chaput

, et al. Implementation, spread and impact of the patient oriented discharge summary (PODS) across Ontario hospitals: a mixed methods evaluation. BMC Health Serv Res. 2021;21(1):361. doi: 10.1186/s12913-021-06374-8. PMID: 33865385; PMCID: PMC8052788.

11.

Ogrinc

Davies

Goodman

Batalden

Davidoff

Stevens

SQUIRE 2.0 (standards for QUality improvement reporting excellence): revised publication guidelines from a detailed consensus process. BMJ Qual Saf. 2016;25(12):986–92. doi: 10.1136/bmjqs-2015-004411. Epub 2015 Sep 14. PMID: 26369893; PMCID: PMC5256233.

12.

Ayanian

Markel

. Donabedian's lasting framework for health care quality. N Engl J Med. 2016;375(3):205–7. doi: 10.1056/NEJMp1605101. PMID: 27468057.

13.

Sullivan

Artino

Jr . Analyzing and interpreting data from Likert-type scales. J Grad Med Educ. 2013;5(4):541–2. doi: 10.4300/JGME-5-4-18. PMID: 24454995; PMCID: PMC3886444.

14.

Benneyan

Lloyd

Plsek

. Statistical process control as a tool for research and healthcare improvement. Qual Saf Health Care. 2003;12(6):458–64. doi: 10.1136/qhc.12.6.458. PMID: 14645763; PMCID: PMC1758030.

15.

Anhang Price

Elliott

Zaslavsky

, et al. Examining the role of patient experience surveys in measuring health care quality. Med Care Res Rev. 2014;71(5):522–54. doi: 10.1177/1077558714541480. Epub 2014 Jul 15. PMID: 25027409; PMCID: PMC4349195.

16.

Nelson

Shi

Lindsay

, et al. Canadian Stroke best practice recommendations advisory committee, in collaboration with the Canadian stroke consortium, Canadian neurological sciences federation, and CanStroke recovery trials platform. Canadian stroke best practice recommendations: rehabilitation, recovery and community participation following stroke. Part one: stroke rehabilitation planning for optimal care delivery, 7th edition update 2025. Am J Phys Med Rehabil. 2026;105(1):59–75. doi: 10.1097/PHM.0000000000002802 Epub 2025 Nov 19. PMID: 41257448.

17.

Hahn-Goldberg

Okrainec

Huynh

Zahr

Abrams

Co-creating patient-oriented discharge instructions with patients, caregivers, and healthcare providers. J Hosp Med. 2015;10(12):804–7. doi: 10.1002/jhm.2444. Epub 2015 Sep 25. PMID: 26406116.

18.

Johnson

Gardener

Gutierrez

, et al. Transitions of care stroke disparities study (TCSD-S) investigators. The effect of 30-day adequate transitions of acute stroke care on 90-day readmission or death. J Stroke Cerebrovasc Dis. 2024;33(9):107842. doi: 10.1016/j.jstrokecerebrovasdis.2024.107842. Epub 2024 Jun 30. PMID: 38955245; PMCID: PMC11347106.

19.

Becker

Zumbrunn

Beck

, et al. Interventions to improve communication at hospital discharge and rates of readmission: a systematic review and meta-analysis. JAMA Netw Open. 2021;4(8):e2119346. doi: 10.1001/jamanetworkopen.2021.19346. PMID: 34448868; PMCID: PMC8397933.

20.

Pellet

Solano Araujo

Kathirkamu

Hilfiker

Bartholdi

Mabire

. Implementing a patient-oriented discharge summary to improve hospital-to-home transitions in older adults: lessons from a hybrid study. Front Health Serv. 2026;5:1730127. doi: 10.3389/frhs.2025.1730127

21.

Alcock

Sawatzky

Strome

Doerksen

. Exploring stroke outcomes following a door-to-needle quality improvement project. Can J Neurol Sci. 2020;47(2):167–75. doi: 10.1017/cjn.2020.7. PMID: 31918789.

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