Modifying Provider Practice To Improve Assessment of Unhealthy Weight and Lifestyle in Young Children: Translating Evidence in a Quality Improvement Initiative for At-Risk Children

Abstract

Background:

We designed a quality improvement (QI) project to address the high prevalence of childhood overweight and obesity (OW/OB) in our patient population and the inconsistencies among primary care providers in recognizing and addressing OW/OB.

Methods:

We used mixed methods data collection approach to evaluate a QI project, the Childhood Healthy Behaviors Intervention (CHBI), to improve provider obesity prevention practice in two low-income, predominantly African American pediatric primary care clinics. Electronic record data were extracted from all 2–9 year well visits pre- and postintervention for frequency of appropriate diagnostic coding of OW/OB. We reviewed a random sample of records for details of health habit assessment and counseling documentation. Focused interviews were conducted to elicit provider responses regarding impressions of the intervention.

Results:

The preintervention sample of records (n = 267) was extracted from 18 providers and the postsample (n = 253) from 19 providers. Providers showed improvement in the recognition of OW/OB with appropriate diagnostic coding (52% pre, 68% post), improvement in assessment of health habits informed by the habit survey (0% pre, 76% post), improvement in counseling of healthy behaviors (86% pre, 92% post), and improvement in goal setting of healthy behaviors (12% pre, 70% post).

Conclusions:

Our findings suggest that implementing a time efficient primary care intervention with brief provider training can improve provider recognition of OW/OB, as well as improve provider behavior targeted at childhood obesity prevention. This project contributes needed QI evidence on interventions to prevent and address OW/OB in primary care settings and calls for further work to strengthen implementation in similar contexts.

Introduction

Asubstantial challenge facing pediatric healthcare providers is the epidemic of childhood overweight and obesity (OW/OB) with prevalence rates more than tripling in recent decades.¹ Nationally 31.8% of children 2–19 years of age are OW/OB² and among Hispanic and non-Hispanic black children these rates are even higher.² The adverse health effects associated with childhood OW/OB are numerous and well documented³ making primary prevention and management of childhood OW/OB paramount.

The periodic well child care (WCC) visit is the ideal opportunity for pediatric primary care providers to promote healthy growth.^4,5 Routine growth assessments occur during these visits; yet, assessment of body mass index (BMI) and categorization of weight status are underutilized^6–8 and may result in missed opportunities to intervene. Time constraints of the office visit necessitate efficient yet effective structured strategies for providers to address BMI, to counsel families with OW/OB children, and to prevent incident overweight.⁶

Best practice guidelines for obesity prevention and management during well child visits include BMI assessment of all children 2–18 years and weight category diagnosis if OW/OB. Assessment of dietary and activity behaviors, counseling on healthy lifestyle behaviors regardless of weight,^9–12 along with a Prescription for Healthy Active Living (HAL), are also recommended (https://ihcw.aap.org/Documents/Rx_BW1up_English.pdf). The Prescription for HAL is focused on 5-2-1-0 behavioral messages (Fig. 1), which the 2007 Expert Committee Recommendations on the Assessment, Prevention, and Treatment of Child and Adolescent Overweight and Obesity identified as an example of consistent evidenced-based messaging^10,12,13 to be used with all children.

Figure 1.

The 5-2-1-0 healthy behavior messages.

While obesity prevention practice guidelines exist,^10–12 the evidence about how to implement these guidelines efficiently into routine practice is limited and needs attention. One example of guideline implementation is the Maine Youth Overweight Collaborative (MYOC) project, in which Polacsek et al.¹⁴ evaluated the effects of a pediatric primary care intervention aimed at improving clinical assessment of obesity across 12 sites. The intervention included BMI percentile tracking, recognition of overweight with weight classification, introduction of the 5-2-1-0 key messages as an intervention framework, introduction of a 5-2-1-0 behavioral screening tool—later identified as the Healthy Habits Survey,¹⁵ and family counseling for management of identified 5-2-1-0 behavioral risks. Results demonstrated large improvement in clinical practice by providers. We adapted many of the elements of MYOC into our local quality improvement (QI) project.

Local Problem

Among Children's National Health System primary care centers in Washington, DC are two community-based group academic sites in the most impoverished wards in the city, serving a population of low-income African American families with Medicaid. In 2014, there were 12 attending physicians and one nurse practitioner, as well as trainees (pediatric fellows, residents, medical students, and nurse practitioner students), who conducted the centers' 15,000 annual visits, assisted by nursing and support staff. Providers at the centers frequently reported encountering children who were overweight, obese, or had excessive weight gain between visits. This is consistent with the most recently reported data for state obesity rates—where DC ranked among the highest in the nation with an OW/OB prevalence rate of 35% for children aged 10–17, significantly greater than the 31.3% nationwide.¹⁶ Comparative state obesity prevalence rates for children under 10 years are not available; however, obesity prevalence in a subset of 2–4 year low-income children in DC in 2011 was 13.1% with no significant improvement from 2008.¹⁷

In our practice, although BMI was available in the electronic health record (EHR) for all children, providers varied in their consistency and approach to coding for OW/OB and in addressing weight and lifestyle concerns. No consistent or standard strategy had been adopted to guide and standardize practice among providers. Consequently, whether providers were providing care based on best practice guidelines in this high-risk population of children was unclear.

Intended Improvement

We chose a QI approach to improve our group practice OW/OB counseling and prevention. QI has been described as “systematic data-driven efforts to improve the quality, safety, and value of healthcare.”¹⁸ Healthcare providers are challenged to provide high quality care to patients by implementing evidenced based practice based on traditional clinical research findings; the QI process determines whether the intended practice change has occurred and, subsequently, how this impacts patient outcomes.¹⁹ Our QI project concentrated on provider practice change; resulting patient outcomes will be evaluated in a future project.

QI evaluates the intended change in practice using pre/post data collection and analysis, with clearly identified outcomes and methods in a specific setting.²⁰ In contrast to traditional research, QI projects typically require a shorter time line and do not require sample size calculations (i.e., power analysis) or statistical tests of significance.²¹ The findings determine if further refinement in the targeted practice change is needed.¹⁹ Several authors have provided comprehensive comparisons of traditional clinical research and QI.^19–23

We designed a QI project—the Childhood Healthy Behavior Intervention (CHBI)—to translate the 5-2-1-0 evidence into primary care practice in a low-income urban population using the RE-AIM framework²⁴ to guide implementation planning.²⁵ The acronym RE-AIM consists of five components: Reach the target population, Efficacy or Effectiveness of the intervention, Adoption by stakeholders, Implementation or consistent delivery of the intervention, and Maintenance or sustainability of the intervention.²⁶ The components of RE-AIM as applied to CHBI can be found in Table 1. We focused on improving provider behavior during primary care WCC visits for children aged 2–9 years to take advantage of a previously studied age-specified habit survey tool, the 5-2-1-0 Healthy Habit Questionnaire (Ages 2–9) (HHQ) (www.letsgo.org/wp-content/uploads/pages-from-healthcare-section-3-talking-2-21.pdf), and to narrow our focus to younger ages, which have been identified as an ideal time to intervene to prevent obesity.^27–29

Table 1.

The RE-AIM Conceptual Framework Applied to Childhood Healthy Behavior Intervention

RE-AIM components	Definition	Component applied to CHBI
Reach	Refers to the intended population	Reach all members of the target audience of pediatric primary healthcare providers and nursing staff at the two pediatric primary care sites through education about all of the elements of CHBI
Effectiveness	Refers to the impact of the program	Measure the consistent utilization of CHBI as intended by providers with targeted patients by auditing documentation in the patients' EHR and through provider satisfaction interviews
Adoption	Refers to institutions or individuals who will deliver the program	Measure acceptance of CHBI by the stakeholders by compliance with documentation as intended in the targeted patients' EHR and through provider interviews
Implementation	Refers to the consistent delivery of the program	Measure the application of CHBI as intended by providers through audit of targeted patients' EHR and provider interviews
Maintenance	Refers to the sustainability of the program and change in behavior over time	Modify CHBI based on results of EHR analysis and provider interviews; monitor the continued use of all aspects of CHBI use as intended with each change cycle

CHBI, Childhood Healthy Behavior Intervention; EHR, electronic health record.

CHBI was designed to (1) improve the consistency of healthcare providers' attention to BMI and documentation of OW/OB weight classification codes in the EHR and (2) improve health habit assessment and delivery of 5-2-1-0 messages targeted at prevention and treatment of childhood OW/OB.

Methods

Childhood Healthy Behavior Intervention

The CHBI was designed as an efficient practice modification to avoid burdening the time-limited WCC visit; the CHBI protocol sequence can be found in Table 2. The intervention included provider BMI assessment of all children aged 2–9, EHR documentation of appropriate OW/OB diagnostic code, as well as habit assessment and habit counseling, and application of two standardized tools: the HHQ and the prescription for HAL. The HHQ is a self-administrated 10-item survey related to the 5-2-1-0 acronym: fruit/vegetable intake (5), screen time (2), physical activity (1), and sugar-sweetened beverage consumption (0) (Fig. 1). The items on the HHQ included yes/no responses, continuous numeric values, and identification of a priority behavior the parent desired to change. At the end of the visit, the provider handed the family a copy of the prescription for HAL, which helped to outline the 5-2-1-0 plan and to set goals with the parent and/or child. The form had space for the provider's and parent or child's signatures, to indicate agreement with the plan.

Table 2.

Childhood Healthy Behavior Intervention Protocol

Activity	By whom	When
Arrives to office for child's 2–9 years WCC visit, checks in at front desk	Patient/parent	Arrival to office for appointment
Obtains vital signs and records in EHR with BMI autocalculated; gives HHQ to parent for completion in examination room	Nursing staff	Appointment time
HHQ completed	Parent	Before provider's arrival to examination room
Review of paper HHQ results, patient's BMI in EHR	Provider	Upon entry to examination room, or before entry
Query parents whether they are willing to discuss child's weight and healthy nutrition and physical activities during the visit; discuss results/present habits and BMI classification of child with patient/parent	Provider	During WCC visit
Discuss healthy habit recommendations through goal setting on prescription for HAL	Provider	During WCC visit
Complete prescription for HAL goals with patient/parent based on parental determination of reasonable goals for home setting	Provider	During WCC visit
Provide parent/child with completed prescription for HAL and designated 5210 handouts for home use	Provider	During WCC or at conclusion of the visit
Documentation in EHR	Provider	During or at conclusion of WCC visit during documentation completion
Classification of BMI as appropriate for BMI 85th–95th percentile, ICD-9 code V85.53; or BMI >95th percentile, ICD-9 code V85.54 with diagnostic coding
HHQ results
HAL goals set by parent/child/provider

HAL, healthy active living; HHQ, healthy habit questionnaire; ICD-9, International Statistical Classification of Diseases and Related Healthy Problems, Ninth Revision; WCC, well child care.

The entire clinical staff attended either one or two 30-minute in-person training sessions led by the project leader about the CHBI QI project. A review of best practice recommendations, the proposed intervention and survey forms, and instructions for completing documentation of the intervention in the EHR were covered. Providers were coached with sample language to use in the visit based loosely on motivational interviewing techniques,³⁰ such as asking permission to discuss the child's weight and habits, using open-ended questions and reflective listening, and assessing which habits the parents were willing to change. Staff members who were not present for both sessions were provided with individual training. The entire staff received e-mail reminders before the onset and during the intervention about the correct implementation of CHBI. We piloted the intervention for 2 weeks after which minor adjustments were made to improve workflow.

Evaluation

We used mixed methods to evaluate the CHBI, including quantitative EHR measures pre/post intervention and a qualitative measure of provider satisfaction postintervention.

EHR review

EHR data fields of interest from WCC visits included BMI percentile, basic sociodemographic information, and provider documentation of BMI percentile classification, demonstrated by an International Statistical Classification of Diseases and Related Healthy Problems, Ninth Revision (ICD-9) code such as “Overweight,” “Obesity,” “Morbid Obesity,” or the appropriate BMI percentile category code. In-depth narrative review of a sample of EHRs was then completed to examine the details of healthy habit assessment and counseling documentation.

EHR data were extracted from all WCC visits for children 2–9 years during two designated 4-week periods, one preintervention and one 4 weeks after implementation of CHBI, defined as the postintervention period. EHRs that appeared in both pre- and postsamples were excluded (n = 7), as well as those of the project leader (n = 81).

Selection of EHRs for the in-depth narrative review began with all EHRs extracted from the pre- and postperiods above (n = 520). These EHRs were stratified first by pre- or post-CHBI intervention period and then by BMI status, either normal or OW/OB, resulting in four groups. Twenty-five records were randomly selected from each group for a total of 100 records.

Provider interviews

Providers were given a copy of the interview questions during the educational session. Focused individual interviews were conducted with all nontrainee providers (n = 12) to gather general impressions of the intervention, problems encountered with use of the intervention (e.g., time involved, disruptions to patient flow), ability to use the intervention consistently, and feedback about whether individual practice had changed as a result of the intervention. The project leader conducted all of the interviews in-person in a private office. Interviews lasted ∼10 minutes during which time responses were recorded in writing. At the conclusion of the interview, the project leader immediately entered the responses as close to verbatim as possible into a Word document. Resident physicians and students were not included in provider interviews due to their sporadic or temporary presence on-site.

Analysis

EHR review

EHR data were downloaded onto Excel worksheets and imported into SPSS (version 22.0). Data were cleaned and descriptive analysis completed. Frequencies of the outcome variable of interest, identification of OW/OB (BMI percentile) as measured by the presence of an appropriate ICD-9 diagnostic code, were compared pre- and post-CHBI.

Narrative EHR review

An analysis matrix was created to compare the range and completeness of documented diet and exercise behaviors by providers against the standardized HHQ. Provision of related education of healthy behavior goal setting was compared to standard 5-2-1-0 goals (e.g., as contained in the prescription for HAL). Frequencies of meeting the standard were then calculated and compared pre- and post-CHBI. Resident physicians were included in EHR review since their visits were conducted under the supervision of an attending physician.

Provider interviews

All interviews were double coded inductively and recurrent patterns identified from which larger themes were named. Two project team members reached 95% agreement with coding.

Ethical considerations

Institutional Review Board approval was obtained from Children's National Health System and The Catholic University of America before implementation. All extracted EHR data reports were de-identified. Provider interview content was transcribed and assigned a nonidentifying project number.

Results

From the 4-week preintervention period, 267 WCC visit EHRs were extracted from 18 providers, including 6 pediatric residents. The postintervention sample included 253 WCC visit EHRs from 19 providers, including 7 pediatric residents. The combined sample of 520 records for the pre/post comparison of appropriate BMI classification excluded those of the project leader to eliminate bias; the full sample of 601 was used to present demographic and BMI percentile categories (Table 3).

Table 3.

Demographic Data, Pre- and Post-Childhood Healthy Behavior Intervention Implementation Timeframes, Children 2 through 9 Years with Well Child Visits

Variable description	Pre-CHBI sample (n = 311^a), n (%)	Post-CHBI sample (n = 290^a), n (%)
Site
Site 1	173 (55.6)	174 (60.0)
Site 2	138 (44.4)	116 (40.0)
Age in years
2	74 (23.8)	58 (20.0)
3	37 (11.9)	30 (10.3)
4	34 (10.9)	37 (12.8)
5	30 (9.6)	43 (14.8)
6	28 (9.0)	30 (10.3)
7	35 (11.3)	32 (11.0)
8	34 (10.9)	42 (14.5)
9	39 (12.5)	18 (6.2)
Gender
Male	153 (49.2)	142 (49.0)
Female	158 (50.8)	148 (51.0)
Race/ethnicity
African American	306 (98.4)	290 (100)
White	3 (1.0)	—
Hispanic/Latino	2 (0.6)	—
Insurance
Medicaid	276 (88.8)	262 (90.3)
Commercial insurance	28 (9.0)	21 (7.2)
None/self-pay	7 (2.2)	7 (2.4)
Residence
DC Ward 7/8	248 (79.8)	238 (82.1)
Other DC Ward	34 (10.9)	29 (10.0)
MD/VA	29 (9.3)	23 (7.9)
Weight status by BMI percentile
Normal (5–84.9%)	203 (65.2)	185 (63.8)
Overweight (OW) (85–94.9%)	54 (17.4)	58 (20.0)
Obese (OB) (95% and >)	54 (17.4)	47 (16.2)
OW/OB	108 (34.8)	105 (36.2)

Overweight was defined as BMI between the 85th and 95th percentiles and obesity as a BMI at or greater than the 95th percentile on the 2000 CDC BMI growth charts for children aged 2–20 years of the same age and sex (CDC, 2000).

Demographic sample analysis included all records, including those of Principal Investigator.

DC, District of Columbia; MD, Maryland; OW/OB, overweight/obesity; VA, Virginia.

Sample characteristics of the children are shown in Table 3. Of note, more than 35.4% of the children had BMI's consistent with OW/OB in both samples; combined sample results (n = 601) indicate that 18.6% were OW and 16.8% were OB.

BMI EHR diagnostic coding results revealed an increase from 52.2% preintervention to 68.1% postintervention of accurate diagnostic coding by providers for children who were OW/OB by BMI percentile (Table 4). This improved recognition of abnormal weight postintervention occurred at a higher rate in the obese groups.

Table 4.

Correct Coding Comparison: Pre-Childhood Healthy Behavior Intervention Classification of Abnormal BMI (n = 92) and Post-Childhood Health Behavior Intervention Implementation Classification of Abnormal BMI (n = 90)

BMI diagnostic code	Correct code applied pre-CHBI, n (%)	Correct code applied post-CHBI, n (%)
BMI 85–94.99% or overweight (n = 44)	16 (36.4)	28 (53.8)
BMI ≥95% or obesity (n = 48)	32 (66.7)	34 (87.2)
Total (n = 92)	48 (52.2)	62 (68.1)

EHR Reviews

The 50 preintervention EHRs reviewed for narrative content represented 14 providers, including 3 pediatric residents. For the 50 postintervention EHRs reviewed, 13 providers, including 3 pediatric residents, were represented. In the presample of EHR, no HHQs were documented. In the postsample, 76% of providers documented use of the HHQ; the majority of providers—9 of 13—had 100% compliance, 2 had 78% or greater, 1 had 33%, and 1 did not use at all. Compared to EHRs without HHQ documentation, those that included the HHQ provided more detailed and consistent nutrition and exercise documentation for all children regardless of weight status.

In pre-CHBI records provider dietary assessments followed standard prepopulated EHR templates with good documentation of 3 meals/day, type and servings of milk, servings of water and juice, and the nonspecific notation “all food groups.” Activity assessment was more variable with almost no active play described and low documentation of screen time. Records of children with documented OW/OB revealed minimal additional nutrition and exercise assessments beyond the standard assessment typically used for all children. Comparison of pre- and post-health habit documentation is found in Table 5.

Table 5.

Comparison of Pre-Childhood Healthy Behavior Intervention and Post-Childhood Health Behavior Intervention Chart Documentation Health Habits

Health habit variables	Pre-CHBI (n = 50), n (%)	Post-CHBI (n = 50), n (%)
Fruit/vegetable Servings	0 (0)	39 (76)
Dinner with family days per week	2 (4)	39 (76)
Breakfast days per week	1 (2)	39 (76)
Fast food consumption per week	0 (0)	39 (76)
Screen-time amounts per day	33 (66)	46 (92)
TV in room where child sleeps	0 (0)	39 (76)
Computer in room where child sleeps	0 (0)	39 (76)
Time per day spent in active play	1 (2)	40 (80)
Servings per day
100% juice	46 (94)	49 (98)
Fruit drinks or sports drinks	0 (0)	39 (76)
Soda or punch	37 (74)	46 (92)
Water	41 (82)	49 (98)
Whole milk	12 (24)	48 (98)
Nonfat or reduced fat milk	35 (70)	48 (98)

In both pre- and postintervention EHRs, 5-2-1-0 counseling documentation existed as part of the prepopulated standard template that providers could elect to use. A small increase in 5-2-1-0 message documentation was seen due to CHBI (86% pre; 92% post). However, providers recorded distribution of the prescription for HAL with goal setting in 35 of 50 EHRs in the post-CHBI sample (70%) compared to 6 of 50 pre-CHBI EHRs (12%); none of the pre-EHRs contained a notation that the paper HAL was supplied.

Provider Interviews

Provider interview results (n = 12) revealed satisfaction with most aspects of the intervention. Positive features included improved efficiency and workflow (n = 11), ability to implement the protocol consistently (n = 11), improved dietary and activity assessment when using CHBI (n = 7), and facilitated engagement with parents in a dialog about their child's health habits (n = 7). Negative aspects of the CHBI included the following: electronic documentation was time consuming (n = 10), some parents had difficulty completing the HHQ (n = 10), CHBI needs some modification (n = 6), and inconsistency with handout distribution by nursing staff (n = 5).

Discussion

Establishing an intervention for primary care obesity prevention in young children is essential. Early childhood is a crucial time to recognize and address behaviors that may lead to unhealthy weight status later in life.^27,29 Obesity incidence is highest in younger children³¹ and primary care providers should play a key role in addressing weight at an early age.³² Healthcare providers have cited lack of time as a factor limiting counseling of families with OW/OB children,^6,33 and time efficient interventions may serve to overcome this barrier, ease the burden of cost, and increase the likelihood of their use. We found that CHBI improved provider recognition of OW and OB through diagnostic coding, an important element representing awareness of weight status. This recognition prompted providers to direct their discussions with the parent around the child's weight and health status. Consistency among providers was improved for health habit assessment and delivery of 5-2-1-0 patient education. A large majority of providers who participated in the CHBI reported no increase in time needed to obtain a more comprehensive dietary and activity habit history using the HHQ and felt that the CHBI improved the workflow. This suggests that our simple intervention may be time efficient and applicable to other similar settings to improve practice.

Our findings of provider improvement are consistent with the findings of the MYOC¹⁴ with improvements in weight classification of overweight: CHBI pre 52.2% and post 68.1% compared with MYOC pre 19% and post 75%; and use of behavioral screening tool: CHBI pre 0% and post 76% compared with MYOC pre 0% and post 82%. Both CHBI and MYOC practice introduced use of a behavioral screening tool during the practice intervention. Provider counseling of 5-2-1-0 messages in both studies: CHBI pre 86% and post 92% as measured by documentation of counseling by provider; MYOC pre 54%–78% and post 79%–92% as measured by parent postvisit survey. CHBI providers improved from 0% to 70% with prescription for HAL form distribution to families. While the change in practice results demonstrated by CHBI was not as large as MYOC, the CHBI was not as extensive and detailed as MYOC, which had more extensive provider training, multiple provider surveys, parental surveys, and measurement of additional clinical practice indicators. Our simple intervention was able to achieve measurable change with less extensive efforts. Our costs were small and were mainly related to staff time spent in training, ∼30–60 minutes per individual.

The prevalence of OW/OB in this sample of low-income African American children exceeds reported national and local rates. Data from visit records in our 2–9 year sample indicate rates of combined OW/OB in the combined samples at 35.4% higher than the rate for DC children 10–17 years with no available comparative data for children in DC younger than 10 years. Recently released National Health and Nutrition Examination Survey data from 2011 to 2014³⁴ indicate that estimated obesity prevalence in children 2–5 years was 8.9%; obesity prevalence in the same age group in the project population was 13.1%. These data confirm that an effective intervention started at an early age in the targeted high-risk patient population is strongly indicated to address OW/OB through primary prevention.

In the small sample of EHR reviews, children with elevated weight did not appear to prompt providers to comply more often with the protocol. Noncompletion of HHQ data fields was found in 11 of 50 postintervention audited EHRs, with rates of nondocumentation for overweight or obese children (n = 6) similar to normal weight children (n = 5). HHQ result documentation can be used to track habit changes by the child at subsequent visits and may be used to understand changes in weight. Improved habit assessment of risk behaviors through use of the HHQ apprises the provider and ultimately the parent, informing counseling for change in home diet and activity habits, aimed to obesity prevention in normal weight children, and weight modification for OW/OB children.

Despite improvements in EHR documentation of OW/OB classifications, additional improvements are needed to target accurate coding of OW/OB since nearly 32% of OW/OB postrecords were not coded. Provider education regarding the importance of early recognition of OW is key since OW was missed more often than OB. These findings lead us to focus on the maintenance step of our RE-AIM framework, to suggest modifications that will further improve the implementation and effectiveness of the CHBI. For example, targeted reminders through e-mails, EHR messaging, and regular random EHR audit results by provider may serve to remind providers of this practice initiative. New providers to the practice will need appropriate training with the CHBI protocol.

Additional areas of focus for the maintenance step of RE-AIM include the lack of concordance between the HHQ and prescription for HAL surveys and time needed to document the HHQ and HAL results in the EHR. There were some inconsistencies related to nursing staff that may have led to improper HHQ distribution and some concerns about whether all parents understood the survey and instructions for completing as some surveys and some questions were not answered as intended. Verbal query by nursing staff with direct data input of HHQ responses into the EHR and/or using selected HHQ questions are under consideration to improve compliance. However our project reached all clinical staff, with fairly consistent use by providers and high adoption by nursing staff, all in keeping with the RE-AIM framework for a successful intervention or QI project.

There were several limitations in our project. Providers were not surveyed regarding their training or skill set to address obesity prevention or management either before or after introduction to the CHBI. Parents were not surveyed about CHBI; information regarding parental perceptions of CHBI and acceptability of the survey forms and counseling delivered by the provider should be considered and addressed in the future. Consideration of factors such as the child's age, gender, and parents' willingness to discuss their child's weight and how these factors may impact provider behavior were not examined and should be considered in the future.

While ideally we would have collected information from the providers regarding their perceptions of feasibility and acceptability before implementing CHBI, we elected to implement our intervention due to the nature of our academic setting where practice improvements are routinely introduced and regarded favorably. Provider interviews were not audio recorded, which might have introduced bias in the collected interview data.

This QI initiative had an additional limitation: a 4-week evaluation timeframe to identify adoption by providers that may have been too short to expect full compliance with all aspects of the intervention. The CHBI protocol included several practice initiatives for the targeted age group: HHQ completion, prescription for HAL goal completion, BMI percentile classification, and documentation in the EHR of HHQ results and HAL goals in a new format. Although the sample size of 18–19 providers was small, it included 2 clinic sites and a variety of provider roles that would likely be found in other similar settings.

It is unclear whether standardizing provider behavior during WCC visits will actually improve OW/OB prevalence; we were unable to collect outcome data on BMI as the QI cycle time was too short and this will be considered in future evaluation. However, changing provider behavior to include the recognition of abnormal weight is an important and logical first step in this process.

Conclusions

In summary, the Childhood Healthy Behavior Intervention (CHBI) contributes needed evidence on interventions to prevent and address OW/OB in primary care settings. The CHBI demonstrated a positive impact on clinical practice through improved recognition with accurate diagnostic codes for OW/OB. Increased consistency in the assessment of children's habits occurred among providers with implementation of the HHQ, which helped inform the prescription for HAL for the child and parent. Discussion of healthy habits at every well visit with parents is an important step toward the goal of primary prevention of obesity in children. Utilization of a uniform standardized approach for assessment, management, and follow-up of healthy habits based on an evidence-based intervention is expected in the long term to contribute to improvement in the BMI of children in the practice.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

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