Electronic Patient-Reported Outcome Measure and Decision Support Tool Option for Early Intervention Service Quality: A Pilot Cluster-Randomized Pragmatic Trial

Abstract

Introduction:

The Young Children’s Participation in Environment Measure (YC-PEM) is an evidence-based and promising electronic patient-reported outcome (e-PRO) option to improve early intervention (EI) service quality, such as when designing the EI service plan.

Aim:

Establish the preliminary effectiveness of implementing the YC-PEM e-PRO and program-specific shared decision support tool option for EI service quality when designing a service plan.

Methods:

For this 2-arm pilot pragmatic trial with cluster randomization at the provider level, 76 caregivers enrolled and 57 caregivers (n = 29 intervention group; n = 28 control group) completed pre- and post-intervention measures. Intervention group caregivers completed the YC-PEM e-PRO and program-specific shared decision support tool and were compared to usual care on EI service quality indicators: (1) caregiver perceptions of family-centeredness, (2) caregiver activation for shared decision-making, (3) caregiver engagement in service design and implementation; and (4) service plan quality.

Results:

No significant group differences at baseline were noted. Pre-post EI service quality revealed no significant differences in the adjusted model (P > .05). However, intervention group families had higher rates participation-focused service plans (69.2%) versus controls (51.4%), most of which met state-level criteria for quality (84%).

Conclusion:

For EI service quality indicators, this intervention option demonstrated comparable performance to usual care. This finding suggests the intervention promoted high quality, participation-focused service planning despite no overall differences in EI service quality, warranting further testing of implementation factors and effectiveness in various service contexts.

Trial Registration Number: NCT04562038

Keywords

rehabilitation rehabilitation process clinical decision support early intervention social participation

Introduction

Early intervention (EI) programs, established under Part C of the Individuals with Disabilities Education Act, support young children’s health, well-being and developmental outcomes.^1,2 Families of young children with developmental needs may experience differences in access to and use of rehabilitation services, including those provided within EI contexts.^3
-6 EI embraces a family-centered approach to ensure equitable access and optimize high-value interventions.⁷ Targeting participation in children’s everyday valued activities is one way to meet state-level standards for high-value EI. This can be enacted through co-designing an Individualized Family Service Plan (IFSP) tailored to identify and leverage children and families’ existing strengths,⁸ address priorities and reflect outcomes to support participation in valued everyday routines, activities, and environments.^9
-16

State and programmatic EI electronic data capture systems are becoming increasingly common,¹⁷ offering data-driven decision-making opportunities. These systems support the use of evidence-based electronic assessments for more precise measurement of children’s participation and monitoring of participation-focused interventions for high value EI service delivery and improvement. The Young Children’s Participation and Environment Measure (YC-PEM) is an evidence-based and promising electronic patient-reported outcome (e-PRO)¹⁸ producing useful data for pediatric rehabilitation research and practice.^19
-28 Caregivers completing the YC-PEM e-PRO share their expertise about their young child’s current and desired levels of participation in valued activities, perceived environmental supports and barriers to participation, along with existing strategies they employ to support participation in targeted areas.^18,20,21

The YC-PEM e-PRO is a valid, reliable and feasible assessment that is increasingly used in rehabilitation research to examine children’s participation and participation-related outcomes,^{19
-23,29
-35} and how service use^23,36,37 is associated with these outcomes. To ensure that stakeholder needs informed YC-PEM e-PRO content and functionality, Khetani et al conducted concept mapping, secondary data analyses and qualitative research with primarily historically minoritized caregivers and other partners.^26,37,38 The YC-PEM e-PRO was designed to function as a common data element in health services research^39,40 and to support the development of personalized service plans responsive to family priorities, consistent with evidence and policy standards reinforcing the alignment of pediatric rehabilitation services with family priorities.^41,42 Caregivers completing the YC-PEM e-PRO are prompted to report on areas where they desire for their child’s participation to change. This information equips EI providers with insight into family priorities to foster meaningful caregiver engagement and activation for shared decision-making during the design and routine updating the EI service plan. Thus, embedding the YC-PEM e-PRO into routine organizational workflows may have the potential to monitor and improve EI service quality. The YC-PEM e-PRO has been successfully adapted across diverse research and practice contexts.^{19,24,25,43
-45} Collectively, these results merit the value of leveraging the YC-PEM e-PRO option for evidence-based EI research and practice.^46
-48

The Patient-Reported Outcomes to Strengthen Partnership in the Early Intervention Care Team (PROSPECT) project is the latest phase of community-engaged research.^{22,23,36,49
-51} PROSPECT examines the effectiveness and implementation of the YC-PEM e-PRO option when integrated with a program-specific shared decision support tool in the form of an IFSP development worksheet, applied within an EI service planning segment completed annually as part of routine workflows.⁵² Guided by the Division for Early Childhood (DEC) Recommended Family Practices,⁵³ this study aims to evaluate the preliminary effectiveness of implementing the YC-PEM-e-PRO and a shared decision support tool within EI services. Family-centered practices in EI include family participation in decision-making, collaborative service planning, and family support to achieve their goals, as aligned with core DEC themes including family-centered support, capacity building, and practitioner-family collaboration. This study uses the DEC framework to examine 4 key EI service quality indicators: (1) caregiver-reported family-centeredness of service planning, including engagement, information sharing, coordination, and respect; (2) caregiver-reported activation for shared decision-making in service plan design; (3) caregiver engagement in both service plan design and implementation; and (4) caregiver assessment of service plan quality, with attention to participation-focused outcomes and adherence to state-endorsed criteria. By evaluating these 4 indicators, the study seeks to inform best practices for delivering effective, family-centered EI services.⁵³

Study results on effectiveness, together with EI stakeholder perspectives of implementation supports, barriers, and strategies⁵⁴ will lend critical evidence to inform future scale-up implementation of this approach across EI programs with electronic data capture systems.

Methods

Study Design

PROSPECT employed a 2-arm cluster-randomized pragmatic trial design within a hybrid type-1 effectiveness-implementation project design.⁵² The PROSPECT trial was registered at ClinicalTrials.gov (NCT04562038) and approved by the institutional ethics board [University of Illinois at Chicago (2020-0555) and University of Colorado (20-2380)]. Protocol details are previously published.⁵²

Participants

From October 2020 to June 2022, 161 out of 212 families were deemed eligible (see Figure 1), and therefore invited to enroll based on these inclusion criteria: Caregivers (1) were at least 18 years old; (2) identified as the parent or legal guardian of a child enrolled in EI; (3) read, wrote and spoke English; (4) had internet and telephone access; and (5) had a child 0 to 3 years old who received EI for 3 or more months. Caregivers were allocated to either the intervention or control group according to the group assignment of their EI service coordinators as aligned with a cluster-randomized trial design.⁵² Nine EI service coordinators were randomized, using computer-generated procedure, to the intervention group (n = 5) or the control group (usual care; n = 4). A total of 76 out of 161 (47%) caregivers consented and enrolled in PROSPECT (see Table 1 and Figure 1). Of those enrolled participants, 57 caregivers (n = 29 intervention group; n = 28 control group) completed both measures at pre- and post-intervention.

Figure 1.

Enrollment flow diagram.

Table 1.

Sociodemographic and Early Intervention Service Use Characteristics for Intervention and Control Group.⁵⁵.

Sociodemographic and Early Intervention service use characteristics	Intervention group (n = 39)	Control group (n = 37)
Child sex
Male, n (%)	27 (69.2%)	24 (64.9%)
Female, n (%)	12 (30.8%)	13 (35.1%)
Self-describe	-	-
Child age, M (SD)	2.22 (0.55)	2.20 (0.62)
Child age, Mdn (IQR)	2.37 [1.96, 2.60]	2.47 [1.84, 2.57]
Reason for receiving EI services
Developmental delay, n (%)	24 (61.5%)	26 (70.3%)
At risk for delay, n (%)	3 (7.69%)	3 (8.11%)
Diagnosed condition, n (%)	12 (30.8%)	8 (21.6%)
EI Service intensity, M (SD)	3.72 (2.66)	5.09 (3.12)
EI Service intensity, Mdn (IQR), (n = 74)	3.00 [2.16, 4.00]	4.29 [2.68, 6.49]
EI Service Breadth
One type of service	1 (2.63%)	0 (0.00%)
Two types of services	14 (36.8%)	15 (45.5%)
Three types of services	12 (31.6%)	10 (30.3%)
Four types of services	7 (18.4%)	7 (21.2%)
Five types of services	4 (10.5%)	1 (3.03%)
Percent of activities for which change in participation is desired, Mdn (IQR)
Home activities	0.31 [0.15;0.42]	N/A
Community activities	0.18 [0.00;0.45]	N/A
Caregiver relationship with child
Father or male legal guardian	3 (7.69%)	1 (2.70%)
Mother or female legal guardian	36 (92.3%)	36 (97.3%)
Other (eg, non-binary legal guardian, gender queer legal guardian, self-described)	-	-
Caregiver race, n (%)
American Indian/Alaskan Native	1 (2.56%)	0 (0.00%)
Asian	2 (5.13%)	2 (5.56%)
Black or African-American	6 (15.4%)	2 (5.56%)
White	29 (74.4%)	28 (77.8%)
Hawaiian or Other Pacific Islander	-	-
Other (prefer to describe)	1 (2.56%)	4 (11.1%)
Caregiver ethnicity, n (%)
Hispanic, Latinx or Spanish origin	9 (23.1%)	9 (24.3%)
Non-Hispanic, Latinx or Spanish origin	28 (71.8%)	27 (73.0%)
Unknown	2 (5.13%)	1 (2.70%)
Caregiver education, n (%)
Some high school, no diploma	0 (0.00%)	1 (2.70%)
High school graduate, diploma or equivalent (eg, GED)	10 (25.6%)	7 (18.9%)
Associates degree	2 (5.13%)	2 (5.41%)
College or University graduate	10 (25.6%)	8 (21.6%)
Some graduate coursework	3 (7.69%)	4 (10.8%)
Graduate degree	14 (35.9%)	15 (40.5%)
Caregiver annual income, n (%)
< $5000	3 (7.69%)	3 (8.11%)
$5000-$20 000	1 (2.56%)	3 (8.11%)
$20 001-$40 000	4 (10.26%)	4 (10.81%)
$40 001-$60 000	2 (5.13%)	3 (8.11%)
$60 001-$80 000	5 (12.82%)	1 (2.70%)
$80 001-$100 000	5 (12.82%)	3 (8.11%)
> $100 000	19 (48.72%)	20 (54.05%)
Caregiver perceived importance for technology-based options in EI
Very important	25 (64.1%)	23 (62.2%)
Important	5 (12.8%)	8 (21.6%)
Somewhat important	6 (15.4%)	5 (13.5%)
Not important	3 (7.69%)	1 (2.70%)

Abbreviations: EI, early intervention; GED, general education diploma; M, mean; SD, standard deviation; Mdn, median; IQR, interquartile range (25th, 75th percentiles); Service Intensity, hours of EI per month of EI service use.

Procedure

The recruitment process began with designated and trained EI staff conducting telephone eligibility screenings of caregivers 4 weeks before their annual IFSP meeting (see Figure 2).⁵² Eligible caregivers who provided verbal consent were then directed to the project website, where they: (1) accessed the recruitment flyer, (2) identified their service coordinator, (3) created a REDCap user account online,^56,57 (4) provided informed consent and HIPAA authorization, and (5) completed baseline surveys via REDCap. Research staff sent up to 3 weekly personalized emails to verbally consented caregivers prior to their scheduled IFSP meetings. To maximize participant retention, 3 strategies were implemented: (1) automated weekly email reminders, (2) monetary compensation ($10 USD electronic gift card) for survey completion, and (3) access to program-provided childcare to offset participation time. Secondary to COVID-19 guidelines, the majority of IFSP meetings were conducted online. Caregivers completed assessments via REDCap at 2 time points: T1 (1-4 week(s) pre-annual IFSP meeting) and T2 (4-weeks post-annual IFSP meeting).

Figure 2.

Flowchart depicting participant recruitment process.

The High Value EI Research Group, comprising EI staff at the study site, closely collaborated with the academic research team.⁵² They facilitated study coordination at their site, including recruitment of service coordinators to the group. All group members, including participating service coordinators, completed an online research training program with synchronous modules and simulation activities on EI research engagement.

Intervention Group

Caregivers in the intervention group completed the YC-PEM e-PRO that captures participation across 2 primary domains. The home domain encompassed 13 types of activities organized into 4 categories (ie, basic routines [eg, personal care management]). The community domain comprised 11 types of activities across 4 categories (ie, neighborhood and community outings [eg, dining out]). For each home and community activity, caregivers rated 3 participation dimensions (1) frequency (0 = never to 7 = daily), (2) level of involvement (1 = not very involved to 5 = very involved), and (3) desire for change in participation (yes, no). When caregivers indicated a desire for change in any activity within a category, they were prompted to describe up to 3 strategies they currently employ to support their child’s participation in that category. For each setting (home and community), caregivers were asked to separately rate how environmental factors impacted their child’s participation, using a 3-point scale (1 = usually makes it harder/no to 3 = usually helps/yes). Following completion of the YC-PEM e-PRO, an online item-level summary report was generated and automatically sent to the EI team ahead of the IFSP meeting.⁵² The family’s service coordinator then integrated information from the YC-PEM e-PRO summary report into a program-specific shared decision support tool to structure opportunities for shared decision-making during the IFSP meeting.

The program-specific shared decision support tool was developed collaboratively with service coordinators in the intervention group. It consisted of a publicly available IFSP⁵⁸ template endorsed by their state that we further adapted to include structured prompts and placeholders for integrating and expanding on information from the YC-PEM e-PRO summary report. For example, we adapted the section of the IFSP template form pertaining to concerns, priorities, and resources to include a prompt for service coordinators to reference the “desire for change in participation” responses in the YC-PEM e-PRO summary report to share in decisions about activities to center in the IFSP outcomes. Together, the YC-PEM e-PRO and program-specific shared decision support tool were used to guide and enhance shared decision-making during IFSP meetings.

To ensure intervention fidelity, service coordinators in the intervention group met monthly with the research and clinical project coordinators to discuss case example(s) of their experience using the YC-PEM e-PRO summary reports and program-specific shared decision support tool.⁵²

Control Group

Usual care consisted of a standard annual meeting for developing or reviewing the IFSP in EI programs. This included a discussion between the family and their EI service coordinator about developmental assessment results and provider observations among different disciplines (eg, occupational, physical or speech therapy). It also included a semi-structured family interview conducted by the service coordinator to identify family concerns, priorities, and resources for developing the IFSP.

Measures

The following metrics were used to collect data for hypothesis testing (see Table 2).

Table 2.

Early Intervention Service Quality Indicators Mapped to Hypotheses and Metrics.

EI service quality indicator	Hypothesis	Metrics
Caregiver-reported satisfaction with family-centeredness of their EI service planning experience	Hypothesis 1 (H1): Compared to those receiving usual care, the intervention group participants (caregivers) will report greater satisfaction with “enabling and partnership” in their EI processes of care.	Measure of Processes of Care – 20 (MPOC-20) (subdomain “enabling and partnership”)
Caregiver-reported satisfaction with family-centeredness of their EI service planning experience	Hypothesis 2 (H2): Compared to those receiving usual care, the intervention group participants (caregivers) will report greater satisfaction across three domains: general and specific information exchange; coordinated and comprehensive EI care; and respectful and supportive EI care.	Measure of Processes of Care – 20 (MPOC-20) (subdomains “providing general and specific information,” “coordinated and comprehensive care,” “respectful and supportive care”)
Caregiver-reported activation for shared decision-making during EI service plan design	Hypothesis 3 (H3): Compared to those receiving usual care, the intervention group participants (caregivers) will report higher activation for shared decision-making.	Parent Patient Activation Measure (P-PAM-13)
Caregiver-reported engagement in EI service plan design and implementation	Hypothesis 4 (H4): Compared to those receiving usual care, the intervention group participants (caregivers) will report higher engagement in EI service plan design and implementation.	Parent Participation Engagement Measure (PPEM)
Caregiver-reported EI service plan quality	Hypothesis 5 (H5): Compared to those receiving usual care, the intervention group participants (caregivers) reporting greater family-centeredness of EI services will show increased odds of having participation-focused service plans meeting state-endorsed quality criteria	Two metrics for service plan quality, according to its focus on participation and meeting state-level quality criteria

Measure of Process of Care – 20 (MPOC-20)

The 20-item MPOC^59,60 assesses caregiver perceptions of the extent of family-centered care in 5 domains on a seven-point scale (1 = not at all to 7 = to a very great extent), with higher scores indicating greater extent of family-centeredness: (1) enabling and partnership (H1); (2) providing general information; (3) providing specific information about the child; (4) coordinated and comprehensive care; and (5) respectful and supportive care (H2). MPOC-20 shows acceptable to excellent internal consistency reliability (α = 0.63-0.92) and strong test-retest reliability (ICC = 0.81-0.86).⁶¹ Concurrent validity is supported by significant and positive associations with satisfaction measures and negative association with stress variables.⁶¹ Discriminative validity is supported by significant differences detected among 3 of the 4 MPOC-20 domains when comparing 3 programs with distinct service delivery approaches⁶¹ (see Table 2).

Parent Patient Activation Measure (P-PAM-13)

The P-PAM-13^62,63 was used to evaluate activation for shared decision-making. It includes 13 statements assessing caregivers’ knowledge, skills and confidence to manage their child’s care (eg, “I am confident I can figure out solutions when new problems arise with my child’s health”) (H3). Caregivers rate their activation for shared decision-making on a four-point scale (1 = disagree strongly to 4 = agree strongly), with higher scores indicating greater activation. P-PAM demonstrates excellent internal reliability (α = .90) and acceptable test-retest reliability (ICC = 0.416)⁶⁴ (see Table 2).

Parent Participation Engagement Measure (PPEM)

The PPEM⁶⁵ comprises 5 items assessing caregiver engagement in participation behaviors during their most recent service provider appointment, rated on a five-point scale with higher scores representing greater engagement (from 1 = not at all to 5 = very much). The PPEM was used to evaluate caregiver activation for shared decision-making in EI service plan design and implementation (H4) and demonstrated excellent internal consistency reliability (α = .87)⁶⁶ (see Table 2).

Service Plan Quality

EI service plan quality was evaluated according to its focus on improving participation and meeting state-level quality criteria. First, 2 staff members (MA, SR) independently performed pilot ratings using established criteria⁶⁷ to evaluate whether service plans contained outcomes focused on improving the child’s participation.⁶⁸ Ratings were compared and discussed by the research team to resolve discrepancies and ensure alignment with the criteria. Following this calibration process, and to ensure continued rigor, the same staff members (MA, SR) then rated each of the remaining EI service plans across 2 rounds, achieving strong inter-rater reliability when rating to these established criteria (mean Cohen’s Kappa = 0.90). Subsequently, 4 staff members (IL, VK, SR, CRL) mapped service plans to caregivers’ YC-PEM e-PRO data to assess family-priority responsiveness. This mapping examined whether service plans referenced activity types measurable by the YC-PEM e-PRO, and, for intervention group families, whether these activities aligned with caregiver-reported desire for participation change. These analyses generated 2 primary metrics of service plan quality based on the plan’s focus on improving the child’s participation. The first metric assessed the proportion of service plans containing participation-focused outcomes based on 4 facets outlined in contemporary participation framework for pediatric rehabilitation⁶⁸: (a) activity competence (performance of specific activities to expected standards, measured by capacity, capability, and performance skills), (b) sense of self (confidence, satisfaction, self-esteem, and self-determination), (c) preferences (valued interests and activities), and (d) environment and context (physical and social settings). Among those, the percentage of plans with a majority (>50%) of participation-focused outcomes and the mean number of targeted activities were calculated. The second metric examined family-priority alignment by calculating the proportion of participation-focused service plans that corresponded to caregiver-identified priorities from their YC-PEM e-PRO data (see Table 2).

These service plans were also rated by 2 additional research staff members (CRL, VV) and EI staff members (AP, LK) to ensure consistent application of selected criteria from the state-level Quality Individualized Family Service Plan and Outcomes continuous quality improvement tool.⁶⁹ Ratings were conducted across 3 rounds (Cohen’s Kappa ranged from 0.56 to 0.72; see Supplemental Figure). This rating was used to derive a preliminary estimate of service plan quality according to whether they met state-endorsed quality criteria (H5).

Data Analysis

Statistical analyses for this pilot cluster randomized trial adhered to the intent-to-treat principle and were conducted by a statistician blinded to participants’ group allocation.⁵² Baseline characteristics between groups were summarized using frequencies with percentages for categorical variables and medians with interquartile ranges for continuous variables. To test H1-H4, linear mixed models using domain-specific scores (calculated by averaging multiple questionnaire items) were employed to examine pre-post group differences in EI service quality, while controlling for cluster and subject dependencies.^52,70 The models were fitted on 3 endpoints: (1) caregiver perceptions of family-centeredness of EI services (H1, H2); (2) caregiver activation for shared decision-making (H3); and (3) caregiver engagement in EI service plan implementation (H4).

Each model included primary fixed effects of group (intervention vs control), time (post-treatment vs pre-treatment) and their interactions. Models adjusted for 2 potential confounders (ie, child age, condition severity as measured by number of developmental delays across 5 domains and per state’s EI eligibility criteria), as secondary fixed effects and included coordinator-level and subject-level random effects. The between-within approach was used to adjust for small cluster numbers,^71,72 with intracluster correlation coefficients (ICC) estimated at each cluster level. If ICCs at the service coordinator level were near zero, individual ICCs were reported at the subject level. Missing data were addressed using mixed model estimation under the missing at random assumption.

To test H5, 76 service plans generated during annual IFSP meetings, were abstracted from the EI program database across 4 rounds of data collection. These 76 service plans contained between 1 and 9 service outcomes, yielding a total of 265 outcomes. These outcomes were rated for their participation focus and adherence to state-endorsed quality criteria using the previously described protocols. Using post-treatment data collected 4-weeks post-annual IFSP meeting within the intervention group, univariate logistic linear regression models were employed to examine 2 sets of associations: (1) binary service plan participation focus and the 5 MPOC-20 domains; and (2) the association between binary service plan quality, defined by state-endorsed quality criteria, and the 5 MPOC-20 domains. Service plans that did not meet the 4 criteria defining participation-focused plans were categorized as a family outcome. Associations are reported as odds ratios (OR).

Our hypotheses centered on evaluating service quality during a brief but clinically significant service plan development phase that spanned approximately 1 month. Given the absence of statistically significant pre-post differences between groups at baseline and at 1 month, as well as participant attrition at later time points, we modified our analytic strategy. As outlined in our published protocol,⁵² we excluded data collected at 6- and 12-month follow-up time points to align the analytic approach with the intervention design, which targeted shared decision-making during IFSP development. This modification posed minimal statistical concerns regarding type I error inflation, as the study was originally powered to detect differences at the 1-month time point. Further analytic details were previously published.⁵²

Results

Sample Characteristics

Our final sample included 76 families (intervention; n = 39; control: n = 37) whose children received EI services (see Figure 1, Table 1). There were no significant group differences at baseline. Groups were comparable across child and caregiver sociodemographic and service use characteristics, including child sex (ie, predominantly male), child age (median: intervention = 2.37; control = 2.47), caregiver race and ethnicity (ie, mainly White, Non-Latinx), educational background, service intensity, and caregivers’ perceived importance for technology options in EI (ie, mostly in favor). Of the enrolled families, 57 (n = 29 intervention group; n = 28 control group) completed both measures at pre- and post-intervention. There were no adverse events.

Caregiver Perceptions of EI Service Quality (H1-H4)

H1: Intervention group caregivers will report greater satisfaction with enabling and partnership than those receiving usual care.

After adjusting for child age and condition severity, there were no significant pre-post differences between groups for enabling and partnership. The mean difference was −0.44 (95% CI: −1.20 to 0.32, P = .18), with a pre-intervention mean (SD) of 5.81 (1.24) out of 7.00 and a post-intervention mean (SD) of 5.62 (1.40).

H2: Intervention group caregivers will report greater satisfaction in information exchange, coordinated care, and supportive care compared to usual care.

As shown in Table 3 and Figure 3, there were no significant pre-post differences between groups in caregiver-reported family-centeredness of service design. For general and specific information exchange, the between-group mean difference was −0.09 [95% CI: −1.16 to 0.99, P = .83; pre-intervention M (SD) = 4.41 (1.90), post-intervention M (SD) = 4.28 (1.98)]. For coordinated and comprehensive care, the mean difference was −0.33 [95% CI: −1.16 to 0.50, P = .33; pre-intervention M (SD) = 6.08 (1.06), post-intervention M (SD) = 6.11 (1.22)]. For respectful and supportive care, the mean difference was −0.15 [95% CI: −0.95 to 0.65, P = .62; pre-intervention M (SD) = 6.30 (0.78), post-intervention M (SD) = 6.16 (1.09)].

Table 3.

Caregiver Perceptions of EI Service Quality.

Caregiver perceptions of family-centered care	Pre-post group differences (OR)	95% CI	P	ICC*
Enabling and partnership	−0.44	(−1.20, 0.32)	.18	0.70
General and specific information exchange	−0.09	(−1.16, 0.99)	.83	0.70
Coordinated and comprehensive care	−0.33	(−1.16, 0.50)	.33	0.51
Respectful and supportive care	−0.15	(−0.95, 0.65)	.62	0.31
Caregiver perceptions of their activation for shared decision-making	0.51	(−9.40, 10.42)	.89	0.67
Caregiver perceptions of their engagement in service plan design and implementation	−0.31	(−0.85, 0.22)	.18	0.47

Abbreviation: EI, early intervention.

ICCs were provided at subject level as the ICCs at the service coordinator level were mostly close to zero.

Figure 3.

Results of hypothesis testing comparing intervention and control groups (H1-H5).

H3: Intervention group caregivers will report higher shared decision-making activation than those receiving usual care.

Analyses controlling for child age and condition severity revealed no significant differences between groups in caregiver-reported activation for shared decision-making during service planning [mean difference = 0.51, 95% CI: −9.40 to 10.42, P = .89; pre-intervention M (SD) = 72.5 (16.3), post-intervention M (SD) = 71.9 (14.1)] (see Table 3 or Figure 3).

H4: Intervention group caregivers will report higher engagement in EI service plan design and implementation than those receiving usual care.

After adjusting for child age and condition severity, caregiver-reported engagement in aspects of service plan design and implementation did not significantly differ between groups [mean difference = −0.31, 95% CI: −0.85 to 0.22, P = .18; pre-intervention M (SD) = 4.23 (0.74), post-intervention M (SD) = 4.16 (0.67)] (see Table 3 or Figure 3).

Participation-Focused Service Plans (H5)

H5: Intervention group caregivers reporting greater family-centeredness will have higher odds of participation-focused service plans meeting state quality criteria than those receiving usual care.

More participation-focused service plans were found in the intervention group (n = 27/39, 69.2%) versus control group (n = 19/37, 51.4%). Among the intervention group, 84% met state-endorsed quality criteria, and 67% (n = 18/27) contained a majority (⩾50%) of participation-focused outcomes. These plans included an average of approximately 3 YC-PEM e-PRO activities per service plan (range = 1-7). For the control group, 37% (n = 7/19) of the participation-focused plans contained a majority (⩾50%) of participation-focused service outcomes and an average of approximately 2 YC-PEM e-PRO activities per service plan (range = 1-5). Among the intervention group with participation-focused service plans, 25/27 reported desired changes in their child’s participation. Of these, 80% (n = 20/25) had EI service plans that were responsive to caregiver-reported desired changes in their YC-PEM e-PRO (see Table 3 or Figure 3).

As shown in Table 4, analyses revealed no significant associations between caregiver-reported family-centeredness of their EI service and the odds ratio of having a service plan adhering to state-endorsed quality criteria. Within the intervention group, higher family-centeredness across 3 of 5 domains (ie, enabling and partnership, coordinated and comprehensive care, respectful and supportive care) and was associated with higher odds of having a participation-focused EI service plan. However, these associations were not statistically significant.

Table 4.

Caregiver Experiences of EI Service Quality (4-Weeks Post-Annual IFSP Meeting) as Related to Service Plan Quality.

MPOC-20	Effect of service plan quality per state criteria (OR)	95% CI	p	ICC*	Effect of service plan quality per focus on participation (OR)	95% CI	P	ICC*
Enabling and partnership	0.67	(0.26, 1.78)	.41	0.37	1.31	(0.67, 2.57)	.42	0.28
General information exchange	0.81	(0.45, 1.46)	.46	0.23	0.94	(0.58, 1.52)	.79	0.29
Specific information exchange	0.55	(0.20, 1.52)	.24	0.20	0.97	(0.56, 1.72)	.93	0.20
Coordinated and comprehensive care	0.28	0.03, 2.76)	.26	0.21	1.27	(0.72, 2.24)	.40	0.23
Respectful and supportive care	0.53	0.09, 3.23)	.47	0.26	1.47	(0.70, 3.06)	.29	0.26

Abbreviations: EI, early intervention; MPOC-20, Measure of Process of Care – 20.

ICCs were provided at the service coordinator level.

Discussion

This study contributes new preliminary evidence on the effectiveness of implementing the YC-PEM e-PRO paired with a program-specific shared decision support tool, as compared to usual care for improving EI service quality during a routine annual EI service planning phase. EI service quality is based on examining both the caregiver-reported EI service experience and assessment of EI service plan quality.

Evidence of Preliminary Effectiveness From the Caregiver Perspective

More families enrolled in this YC-PEM e-PRO pilot implementation trial compared to previous YC-PEM e-PRO pilot implementation initiatives.^22,23 We hypothesized that the intervention group caregivers would report greater satisfaction with EI service quality across 4 domains specified in H1-H4 (see Table 2). These hypotheses were not supported. After adjusting for child age and condition severity, we found no significant between-group differences in caregiver-reported EI service quality indicators.

There are several ways to interpret this finding. One possibility is that usual care and the YC-PEM e-PRO paired with the program-specific shared decision support tool may contribute equally to high EI service quality. Another interpretation is that the participating EI program is an early adopter of state-level interventions to improve family-centered care coordination,⁷³ which may have resulted in a relatively high standard of care and a ceiling effect that limited detection of additional intervention benefits. The EI program’s organizational and geographic context could make for strong implementation climate, characterized by prioritization of staff education and communication protocols using the YC-PEM e-PRO. Additionally, the organizational commitment to improving family-centered pathways within and across EI programs statewide may have supported sustained implementation.⁵⁴ Future research should engage a broader range of EI programs, particularly later adopters of quality improvement initiatives.

Alternatively, timing may have masked intervention effects, as the study targeted service quality during a routine annual service planning meeting for families already enrolled in EI services for at least 3 months. Thus, caregivers experienced the intervention within an established workflow. While the timing is based on service coordinator preference in a prior research phase,²³ stakeholders have recognized that this intervention may improve family-centered pathways into EI,⁵⁴ in which case intervention effects may have been detected if implemented during an initial meeting to develop the EI service plan.

A third consideration is the mode of delivery using the family’s usual service coordinator to deliver the intervention, which may have limited its effect. Since this study employed a pragmatic trial design,⁵² we aimed to mimic the approach adopted in routine care. However, service coordinators shared their need for increased practice with the protocol to support longer-term implementation.⁵⁴ Future studies could allocate additional time to build on the support provided during the monthly meetings among intervention group service coordinators and the research and clinical project coordinators. This could include observing selected IFSP meetings and providing feedback on how YC-PEM e-PRO responses are integrated into service plan development.

Finally, the selected outcome measures may have lacked sensitivity to detect effects for an intervention targeting service quality during a routine EI service planning phase that occurs annually in the child’s overall EI service experience. The 3 selected measures provided 3 caregiver-reported perspectives for evaluating caregiver-reported service quality. Shared decision-making has been identified as a key medical home care component driving educational service plan development, including EI.⁵ However, these outcome measures predominantly assessed quality across general service types (eg, day treatment, outpatient, in-home behavior) rather than EI-specific contexts. Therefore, their items may have lacked sensitivity to detect changes in caregiver experiences with service plan development (eg, activation for shared decision-making). Current and future trials may benefit from emerging measures, including revisions of established measures such as MPOC under development^74,75 and new measures like the Pediatric Intervention Measure of Engagement-Parent version (PRIME-P).⁷⁶ These tools afford greater capability to capture caregiver engagement during a pediatric rehabilitation session, such as an IFSP meeting to develop or update the EI service plan. PRIME-P also captures caregivers’ overall impressions about the intervention process and session-specific participation patterns. In addition, open-ended survey items may provide a complementary approach to capture caregivers’ feedback across pre- and post-intervention phases, potentially reflecting specific aspects of service quality that this study’s selected outcome measures may not sufficiently assess (eg, activation for shared decision-making during EI service plan development).

EI program involvement in this trial has guided their commitment to prioritize adoption of the YC-PEM e-PRO option into their upgraded electronic data capture system to support both annual family progress reviews and broader service quality improvement initiatives. By facilitating meaningful caregiver discussions in quality intervention goal-setting for their children, the EI program recognized the tool’s performance advantage in strengthening family-centered organizational workflows.⁵⁴ This adoption may also afford for longitudinal collection of YC-PEM e-PRO data that would be needed for examining a broader range of child outcomes beyond their traditional developmental and functional measures.⁷⁷ YC-PEM e-PRO implementation could enable examining cost effectiveness for scalability across EI programs with electronic data capture systems and through state-level electronic data infrastructures.⁵⁴

Evidence of Preliminary Effectiveness Based on the EI Service Record

We hypothesized that the EI service plans for the intervention group would demonstrate higher quality through adherence to state-level criteria and their greater participation focus. This hypothesis was partially supported. Compared to the control group, intervention group families demonstrated a greater percentage of participation-focused service plans, greater emphasis on participation within EI service plans, and higher odds of having a participation-focused service plan when reporting greater family-centered care across most dimensions. Higher mean number of activities in the intervention group likely reflects prior documented benefits of the YC-PEM e-PRO in facilitating the selection of activities when co-designing the IFSP with families.⁵⁴ Our findings are consistent with prior evidence, suggesting that most service plans adequately reflected at least 1 area of caregiver-reported desired change from their YC-PEM e-PRO.

These collective results suggest that the YC-PEM e-PRO option can serve as an effective tool for designing quality EI service plans. In contrast, these promising results were not replicated when using state-level criteria that endorse participation-focused and family-centered EI service plans, potentially due to the positively skewed ratings in the subset of EI service plan data available. A related pragmatic trial is underway, for which we have approval to access complete EI service plans rather than only the outcomes section. This will enable a more comprehensive evaluation of this intervention’s impact against state-endorsed quality criteria for service plans.⁵⁴

Manual rating of service plans to ascertain their focus on participation is consistent with existing implementation methods such as the Method for Using Audit and Feedback in Participation Implementation.⁷⁸ However, feasibility of these analyses limit their sustainability and scalability, suggesting the potential value for exploring automated analytic approaches for ongoing quality assurance and service improvement initiatives.^79,80 Artificial intelligence (AI) has been increasingly used in participation-focused pediatric rehabilitation; however, implementation in complex goal-setting and care planning processes remains limited.^81
-83 Findings suggest potential applications of natural language processing, an AI approach, for automating both PEM data classification and EI service plan quality analyses.^79,80

Limitations

Results of this study should be interpreted in light of several limitations. Despite cluster randomization at the service coordinator level, social desirability bias may have inflated control group estimates, potentially obscuring the YC-PEM e-PRO’s effect. Enrollment rates were higher than prior research phases, perhaps owing to the study site’s increased familiarity with the YC-PEM e-PRO from prior research engagement.^49,50 However, the small sample size (ie, 76 total enrolled caregivers compared to 89 caregivers per group needed for sample size estimates) limited statistical power for detecting meaningful group differences.⁵² Data collection relied on caregiver-reported assessments rather than video or audio-based methods due to privacy concerns and limited resources. While this approach was efficient and minimized privacy risks, it may introduce bias and miss details captured through skilled observation. Future studies may incorporate video and/or audio-based methods for evaluating intervention fidelity and its hypothesized effects.⁵² EI service plan quality analyses used established rating criteria and a rigorous rating process, but potential rater bias cannot be ruled out.

Enrollment rates may have been affected during COVID-19 lockdown and the timing and nature of automated follow-up emails from an unfamiliar staff member sent through REDCap. We attempted to diversify our study sample by implementing more personalized emails outreach between October 2021 and May 2022, which was a minor adjustment to our procedure outlined in the protocol paper.⁵² It included contacting 50 eligible and interested families, of which 17 enrolled. Nevertheless, our final sample remained skewed toward families with higher educational attainment and income levels. Following this study, we partnered with historically minoritized EI families to upgrade YC-PEM e-PRO content and functionality, with the aim of diversifying participant reach in future trials.⁸⁴

Conclusion

The YC-PEM e-PRO intervention was comparable to a high level of usual care across 4 EI service quality indicators during an EI service planning phase: family-centeredness, activation for shared decision-making, engagement in service design and implementation, and designing participation-focused service plans for most families. EI service plans in the intervention showed a greater participation focus, and caregivers reporting family-centered service experiences had greater odds of having participation-focused service plans. This combination of findings and the EI program’s commitment to adopt the YC-PEM e-PRO in their electronic data capture system supports the need for future phases of health services and implementation research designed to address current sample and measurement limitations.

Supplemental Material

sj-docx-1-rpo-10.1177_27536351261445239 – Supplemental material for Electronic Patient-Reported Outcome Measure and Decision Support Tool Option for Early Intervention Service Quality: A Pilot Cluster-Randomized Pragmatic Trial

Supplemental material, sj-docx-1-rpo-10.1177_27536351261445239 for Electronic Patient-Reported Outcome Measure and Decision Support Tool Option for Early Intervention Service Quality: A Pilot Cluster-Randomized Pragmatic Trial by Vera C. Kaelin, Sabrin Rizk, Yi-Fan Chen, Jodi Dooling-Litfin, Elizabeth Lerner Papautsky, Natalie E. Leland, Natalie J. Murphy, Beth M. McManus, Carla R. Lage, Vivian Villegas, Lindsay Kuznicki, Amanda Pedrow, Mary A. Khetani, MA Khetani, NE Leland, EL Papautsky, BM McManus, JD Litfin, YF Chen, VC Kaelin, S Rizk, CR Lage, V Villegas, NE Leland, JD Litfin, A Pedrow, L Kuznicki, VC Kaelin, MA Khetani, NE Leland, NJ Murphy, EL Papautsky, BM McManus and JD Litfin. in Advances in Rehabilitation Science and Practice

Footnotes

Acknowledgements

This work is dedicated to our esteemed colleague Kelly Kearns, a service coordinator who significantly contributed to PROSPECT and passed away from cancer in May 2022. Ms. Kearns will be remembered for her commitment and passion to ensuring that family priorities are centered in EI service design and delivery. We thank members of Rocky Mountain Human Services (Andrea Simpson) and members of the Children’s Participation in Environment Research Lab (CPERL; Marlene Angulo, Zurisadai Salgado, Julia Sim, Ivana Lucero, Lauren Frame, Lilyanna Patton, Dianna Bosak) and our administrative staff at the University of Illinois Chicago (Faith Thurmond, Michelle Belcher, Grace Sinay, Jiehuan Sun) for their assistance, mentorship, and/or sponsorship to ensure timely data collection, management, data preparation, manuscript preparation, and/or analyses of data reported on in this study during the COVID-19 pandemic. We also thank our colleagues at Wegile (Sanjeev Chauhan, Pankaj Sandhu, and Sumit Oberoi) for their technical expertise and partnership in developing the PROSPECT intervention and supporting data collection.

The authors acknowledge the contributions of the following collaborators who were members of the High Value Early Intervention Research Group:

Jamie Bane, Shannon Banks, Amber Derryberry-Lesher, Kelsy Drummond, Kelsey Granzen, Willow Gray, Ann Howell, Taylor Mattlin, Nicolette Peters, Laura Sciarcon, and Julia Spratt

Finally, Carla R. Lage is now affiliated with the Occupational Therapy Program, Bond University, Australia. Vera Kaelin is now affiliated with the Eastern Switzerland University of Applied Sciences, Switzerland. Yi-Fan Chen is now affiliated with the University of Pittsburgh, United States

Author Note

Carla R. Lage and Vera Kaelin contributed to this research while pursuing their PhD in Rehabilitation Sciences at University of Illinois Chicago. Yi-Fan Chen contributed to this research while employed as a biostatistician in the Center for Clinical and Translational Science at University of Illinois Chicago.

ORCID iDs

Sabrin Rizk

Yi-Fan Chen

Natalie E. Leland

Natalie J. Murphy

Carla R. Lage

Vivian Villegas

Mary A. Khetani

Ethical Considerations

This study was approved by the institutional ethics boards at the University of Illinois, Chicago (2020-0555) and the University of Colorado (20-2380). The PROSPECT trial was registered at ClinicalTrials.gov (NCT04562038).

Consent to Participate

Written informed consent was obtained from all participating caregivers prior to data collection.

Author Contributions

The authors contributed to this paper as follows: study conceptualization, funding acquisition, supervision, resources; MA Khetani, NE Leland, EL Papautsky, BM McManus, JD Litfin; methodology, formal analysis, and project administration; YF Chen, VC Kaelin, S Rizk, CR Lage, V Villegas, NE Leland; data curation; JD Litfin, A Pedrow, L Kuznicki, VC Kaelin; interpretation of results; MA Khetani, NE Leland, NJ Murphy, EL Papautsky, BM McManus, JD Litfin. All authors and members of our High Value Early Intervention Group Members contributed to writing the original draft and providing critical review.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by grants from the American Occupational Therapy Foundation award (AOTFIR20KHETANI; M. Khetani), and National Center for Advancing Translational Sciences of the National Institutes of Health (UL1TR002003; M. Khetani), and institutional funds through the University of Illinois Chicago, including their Bridge to Faculty Postdoctoral Scholar Program (S. Rizk) and Graduate College Dean’s Scholar Fellowship (V. Kaelin). The content is solely the responsibility of the authors and does not necessarily represent the official views of these funding agencies.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: The Young Children’s Participation in Environment Measure (YC-PEM) e-PRO version that was used in this study is licensed for distribution through CanChild Centre for Childhood Disability Research. M. Khetani has shared in the revenue from YC-PEM sales via a sponsored contract to the University of Illinois, Chicago, for mentored training to advance knowledge translation activities in her lab.

Data Availability Statement

Ethics approval was obtained prior to participant recruitment. All participants provided written informed consent for study participation and were informed about their rights to withdraw at any time and compensated with a gift card. The use of these data aligns with their intended purpose and the approved protocol. Data have been anonymized and may be available upon request to the corresponding author, provided that existing institutional review board and data use agreement approval is provided and protocol is followed.

Supplemental Material

Supplemental material for this article is available online.

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