nach oben

Erschienen in:

Open Access 01.12.2017 | Study protocol

Protocol for project IMPACT (improving millions hearts for provider and community transformation): a quasi-experimental evaluation of an integrated electronic health record and community health worker intervention study to improve hypertension management among South Asian patients

verfasst von: Priscilla M. Lopez, Jennifer Zanowiak, Keith Goldfeld, Katarzyna Wyka, Ahmad Masoud, Susan Beane, Rashi Kumar, Phoebe Laughlin, Chau Trinh-Shevrin, Lorna Thorpe, Nadia Islam

Erschienen in: BMC Health Services Research | Ausgabe 1/2017

Abstract

Background

The Million Hearts® initiative aims to prevent heart disease and stroke in the United States by mobilizing public and private sectors around a core set of objectives, with particular attention on improving blood pressure control. South Asians in particular have disproportionately high rates of hypertension and face numerous cultural, linguistic, and social barriers to accessing healthcare. Interventions utilizing Health information technology (HIT) and community health worker (CHW)-led patient coaching have each been demonstrated to be effective at advancing Million Hearts® goals, yet few studies have investigated the potential impact of integrating these strategies into a clinical-community linkage initiative. Building upon this initiative, we present the protocol and preliminary results of a research study, Project IMPACT, designed to fill this gap in knowledge.

Methods

Project IMPACT is a stepped wedge quasi-experimental study designed to test the feasibility, adoption, and impact of integrating CHW-led health coaching with electronic health record (EHR)-based interventions to improve hypertension control among South Asian patients in New York City primary care practices. EHR intervention components include the training and implementation of hypertension-specific registry reports, alerts, and order sets. Fidelity to the EHR intervention is assessed by collecting the type, frequency, and utilization of intervention components for each practice. CHW intervention components consist of health coaching sessions on hypertension and related risk factors for uncontrolled hypertensive patients. The outcome, hypertension control (<140 mmHg systolic blood pressure (BP) and <90 mmHg diastolic BP), is collected at the aggregate- and individual-level for all 16 clinical practices enrolled.

Discussion

Project IMPACT builds upon the evidence base of the effectiveness of CHW and Million Hearts® initiatives and proposes a unique integration of provider-based EHR and community-based CHW interventions. The project informs the effectiveness of these interventions in team-based care approaches, thereby, helping to develop relevant sustainability strategies for improving hypertension control among targeted racial/ethnic minority populations at small primary care practices.

Trial registration

This study protocol has been approved and is made available on Clinicaltrials.gov by NCT03159533 as of May 17, 2017.

Blood pressure

CHW

Community health worker

CMS

Centers for Medicare & Medicaid Services

CVD

Cardiovascular disease

eCW

eClinicalWorks

EHR

Electronic health record

Healthfirst

HIT

Health Information Technology

IMPACT

Improving Millions Hearts for Provider and Community Transformation

LEP

limited English proficiency

MOU

Memorandum of Understanding

Meaningful Use

NCQA

National Committee for Quality Assurance

NHLBI

National Heart, Lung, and Blood Institute

NYC HANES

NYC Health and Nutrition Examination Survey

NYC

New York City

NYU-CUNY PRC

New York University-City University of New York Prevention Research Center

PCMH

Patient-Centered Medical Home

PCP

Primary care provider

Background

The Million Hearts® initiative aims to prevent heart disease and stroke in the United States (US) by mobilizing public and private sectors around a core set of objectives, with particular attention on improving blood pressure control [1]. Nationwide, there are 67 million adults with hypertension, accounting for nearly a third (30.3%) of the population. Fewer than half of these individuals have achieved control despite the wide availability of affordable generic medications and their effectiveness in reducing all-cause hospitalization risk and total health care costs [2, 3]. The burden of hypertension is particularly high in minority groups, including certain Asian American subgroups.

South Asians have disproportionately high rates of cardiovascular disease (CVD), with a unique profile of associated risk factors, including high rates of hypertension and diabetes, low rates of hypercholesterolemia and a different distribution of obesity across CVD risk factor groups [4‐17]. Age-adjusted prevalence of hypertension (diagnosed and undiagnosed together) among South Asians in New York City (NYC) is estimated to be 43%, compared to 27.5% among white adults, according to results from the 2013/2014 NYC Health and Nutrition Examination Survey (NYC HANES) [18]. South Asians face numerous cultural, linguistic, and social barriers to accessing healthcare, which may impede clinical and self-management of hypertension [19-25]. Providers may also lack the appropriate tools and resources to identify and manage South Asian hypertensive patients or refer them to culturally appropriate programs that support hypertension and diabetes control. Programs already proven effective in other communities can be adapted to address this gap and effectively improve hypertension management in the South Asian population.

Individually, health information technology (HIT) and community health worker (CHW)-led patient coaching interventions have each demonstrated effectiveness at advancing Million Hearts® goals, yet few studies have investigated the potential impact of integrating these strategies into a clinical-community linkage initiative [26‐31]. Data available through electronic health records (EHRs) can be used to identify candidates for needed follow-up, targeted risk-reducing interventions and can be designed to allow primary care providers (PCPs) to easily refer patients to counseling and other services [32‐35]. Adding CHWs to the primary care team can improve care for patients with chronic disease(s) at low cost [36]. Studies are now beginning to demonstrate that EHR access and communication between the PCP and CHW can facilitate the acceptance and effectiveness of emerging care management models and lead to improved patient outcomes [37, 38].

Building upon the strategies of the Millions Hearts® initiative and the evidence base of the effectiveness of CHW interventions, we present the protocol of a research study designed to understand the effectiveness of integrating these approaches towards hypertension management among a South Asian population [1]. Project IMPACT is a 5-year stepped wedge quasi-experimental study designed to test the feasibility, adoption, and impact of integrating a CHW-led health coaching with practice- and provider-level EHR-based interventions to improve hypertension control among South Asian patients in NYC primary care practices.

Methods

Objectives

The primary aim of the current study is to assess the effectiveness of an integrated EHR and CHW intervention to improve hypertension control among South Asian patients with poorly controlled hypertension in 16 NYC primary care practices.

Study team

This study is led by researchers from the New York University-City University of New York Prevention Research Center (NYU-CUNY PRC), funded by the Centers for Disease Control and Prevention [39]. The NYU-CUNY PRC is a public-private academic partnership between the NYU School of Medicine and the CUNY School of Public Health, and its mission is to implement, evaluate, and disseminate community-clinical linkage interventions to reduce cardiovascular disease disparities in ethnically diverse NYC communities. For this project, researchers from the NYU-CUNY PRC partnered with Healthfirst (HF), a not-for-profit managed care organization serving more than 35,000 South Asian members in NYC. Primary care practices enrolled into the study are part of HF’s provider network [40]. The team also engaged with IPRO, the federally-funded Medicare Quality Innovation Network-Quality Improvement Organization for New York State, Washington D.C. and South Carolina, under contract with the Centers for Medicare & Medicaid Services (CMS), to train provider networks on the use of EHR systems in order to implement and monitor Million Hearts® goals, as well as training on consistency in blood pressure recordings [41]. A coalition of South Asian community-based organizations with expertise in the development and implementation of culturally tailored community-clinical linkage models was engaged to provide feedback on the CHW component of the intervention, including reviewing and adapting CHW curriculum and patients materials [42, 43]. An independent EHR consultant was also hired to provide technical assistance to practices throughout the course of the intervention.

All study protocol and procedures were reviewed by the Institutional Review Board at the NYU School of Medicine and the CUNY School of Public Health. Primary care practices identified as potential intervention sites signed two Memorandums of Understanding (MOUs) between the primary care practice and study team for each component of the intervention. For the EHR component of the intervention, the MOU included the following components: (1) EHR intervention components to be implemented; (2) training requirements; (3) aggregate and individual-level patient data extraction, confidentiality and storage procedures associated with the study. For the CHW component of the intervention, the MOU detailed: (1) recruitment strategies; (2) CHW intervention components to be implemented; and (3) individual-level patient data extraction, confidentiality and storage procedures associated with the study. Written informed consent is obtained from study participants receiving CHW services. This component of the intervention was registered via ClinicalTrials.gov by NCT03159533 as of May 17, 2017. Finally, participating academic institutions signed a data use agreement with HF that provided guidelines and protections around the usage and storage of data for research purposes.

Study design

We use a stepped wedge design to simultaneously analyze the effectiveness and implementation process of a multi-component quality improvement intervention on hypertension control tailored for a unique minority population [44, 45]. The intervention is implemented in two phases in 16 primary care practices in NYC that are part of the HF network and serve large numbers of South Asian patients. The first year of the study is dedicated to recruitment of sites, planning, and determining the specific components of the EHR and CHW interventions to be implemented. In Years 2 to 3, we implement and evaluate the EHR phase of the intervention within 16 PCP practice sites. In Years 3 to 4, we integrate the CHW-led coaching and patient education phase of the intervention with the EHR physician-level efforts in all sites. In Year 5, we assess the implementation process and use findings to develop a set of best practices and toolkits for public health and healthcare agencies regarding integrated EHR-CHW strategies to improve hypertension control.

The study design employs staggering of the EHR and integrated EHR-CHW interventions using a modified stepped wedge design. The modifications to the traditional stepped wedge design include lack of random allocation of the intervention into the practice sites due to logistical and acceptability concerns on the part of practices, and variations in the length of time between steps [44, 45]. Figure 1 demonstrates the stepped wedge design, where groups 1–5 represent clusters of 2–4 practices that have been progressively allocated into the components of the intervention by enrollment date. Data related to the study outcomes are extracted from EHR systems on a biannual basis. By the beginning of Year 3, the EHR intervention is implemented at all sites, and by the end of year 3, the linked CHW intervention is implemented at all sites [37, 38, 43].

Intervention components

Phase 1: EHR intervention

The EHR intervention components of the project were developed with input from project partners and participating clinics, and are centered on 1) generating routine hypertension patient registry reports within each practice; and 2) developing and implementing medical alerts and order sets tailored to the South Asian patient population. The features of the EHR intervention component are implemented at the participating sites after careful considerations to their baseline workflow, staff capacity, and logistical feasibility conducted through a mixed methods baseline assessment. Recommendations are made for a revised practice workflow to ensure that the proposed EHR intervention component is practical, realistic, and tailored for each individual practice.

Patient Registry - The patient registry is a feature within the EHR that allows providers to query and group information on their patients based on specified criteria, ranging from diagnoses of particular health conditions to demographic characteristics [46]. The registry allows practices to plan and prioritize patient visits, identify potential care required, and measure overall practice performance. This project provides the clinical team with training on the following competencies: understanding the functionality and potential impact of the registry; appropriately generating registry reports for follow-up care; to identify patients that have been lost-to-follow up; to incorporate registries into the day-to-day office activities; and to monitor the use, satisfaction and impact of utilizing the patient registry over time. Specifically, the project focuses on encouraging the routine generation of registry reports that identify patients with diagnosed hypertension that had a poorly controlled blood pressure reading at last clinic visit in order to help providers prioritize a follow-up visit from these patients. Alerts – Alerts may be built within the EHR to remind staff and providers to complete a particular action at the point of care [47]. These alerts can be patient-specific or “global,” meaning that they apply to any patient that satisfies specified criteria. This project provides the clinical team with training on understanding functionality and potential impact of these alerts and how to utilize them for the prevention and management of hypertension. Alerts are tailored to trigger when a blood pressure measurement is missing for the patient at the point of care, and prompts the provider for a repeat measure if elevated. In addition, for patients with a diagnosis of hypertension, an alert prompts the clinical team to create an appointment for the patient to return to the practice within 6 months if blood pressure is controlled, or within 1 month if poorly controlled [48]. Order sets – Order sets are standardized sets of evidence-based treatment guidelines that apply when linked to an alert [47, 48]. In this project, we create an order set that includes a combination of prescriptions, lab tests, and counseling orders “pre-set” for patients with hypertension. Within the counseling orders, we upload evidence-based, culturally tailored, in-language educational materials for distribution to patients fluent in a variety of South Asian languages.

To complement these components, participating practice staff are trained on creating customizable templates that increase the efficiency and accuracy with which staff documents vital signs and other pertinent health data, and utilizing automated appointment reminder texts and letters that can be sent to patients electronically [47]. In tandem, practices are encouraged to collaborate with IPRO, a partner in this intervention, to participate in EHR-based incentive programs, such as Meaningful Use (MU) and National Committee for Quality Assurance (NCQA) Patient-Centered Medical Home (PCMH) recognition [49, 50].

Phase 2: CHW intervention

One year after each participating clinical practice implements the EHR intervention, the CHW intervention launches. To prioritize eligible patients to enroll in this intervention, a list of South Asian patients with > = 140 systolic blood pressure and/or > = 90 diastolic blood pressure at last visit within the last 6 months is generated from the EHR at each of the participating PCP sites. Eligible patients receive a letter from their physicians inviting them to participate in the CHW intervention (a series of group and one-on-one educational sessions on hypertension self-management), and CHWs follow-up with a telephone call. CHWs were trained in a set of core competencies, including cardiovascular disease, mental health, motivational interviewing, smoking cessation, and other related topics.

CHWs deliver a standardized curriculum on hypertension management adapted from the National Heart, Lung, and Blood Institute (NHLBI) Healthy Heart, Healthy Family program, other community-based CHW and heart health educational curriculum implemented in South Asian communities, and relevant Million Hearts® Initiative materials [1, 42, 43, 51, 52]. The protocol consists of 5 monthly 60-min group health education sessions that provide the tools and strategies to promote heart health to South Asian individuals, families, and communities on high blood pressure and CVD [1, 42, 43]. All sessions employ adults learning techniques and group-based learning and activities, and materials have been culturally and linguistically adapted. Each of the group health education sessions discuss different content related to CVD, hypertension, and other CVD risk factors that are culturally relevant for South Asian populations (Table 1).

Table 1

Community Health Worker (CHW) Intervention Curriculum

Session Topic	Session Overview	Tailored Cultural Components
Session 1: Blood Pressure and the Cardiovascular System	Icebreaker/Introduction and Session Guidelines	• Highlight local health and social services resources, as well as risk factors for South Asians
	1.How the heart works & heart structure
	2. What is blood pressure and hypertension (BP numbers)
	3. How to check your blood pressure (demo and practice)
	4. Risk factors of hypertension
	5. Ways to manage blood pressure: healthy diet, physical activity, medicine (overview)
	6. Signs of heart attack and stroke & Emergency Plan
	7. Physical Activity Exercises (demo and practice)
Session 2: Healthy eating	1.Traditional South Asian diets (discussion)	• Food examples tailored for South Asian diets and dietary practices
	2. Building a healthy plate (Using Plate Method)
	3. How to choose heart healthy foods
	4. Salt and sodium
	5. How to understand a nutrition label
	6. Alcohol
	7. Tips for healthy eating while out, with little time, and on a budget
	8. Setting healthy eating goals
Session 3: Physical Activity and Stress Management	1. Importance of physical activity	• Use of Asian BMI guidelines
	2. What is a healthy weight/BMI?	• Realistic exercise options in NYC communities
	3. Calorie balance and the healthy way to lose weight	• Discussions on major stressors and ways to reduce stresses in South Asian context
	4. Ways to be active, build activity into your day, and stay motivated
	5. Sample exercises and walking program
	6. Setting physical activity goals
	7. Effect of stress on the body
	8. Emotions like anger, frustration, sadness, worry
	9. Strategies to manage stress improve self-esteem
Session 4: CVD risk factors: cholesterol, blood sugar, & smoking	1. Facts about saturated fat, trans fat, and cholesterol	• Discussion of CVD risk factors, including smoking and tobacco use, is contextualized into South Asian context
	2. Understanding nutrition labels
	3. Healthier cooking tips
	4. Diabetes - What is it, types, and symptoms
	5. Complications of diabetes & diabetes control
	6. Hidden sugar in drinks activity
	7. Effect of smoking and tobacco use on health
Session 5: Health Communication, Healthcare access & sessions review	1. Communicating with doctors	• Discussion of barriers to healthcare for South Asian patients
	2. Barriers to healthcare access
	3. Preparing for a doctor visit
	4. Accessing health care
	5. Review of all sessions

Sessions are held in PCP offices and other community spaces, and multiple timeslots of each session are held to accommodate patients’ varying schedules. Between sessions, CHWs follow up with participants at least bi-weekly by phone or in-person through a home or clinic visit. At these sessions or calls, CHWs engage in goal-setting activities regarding changes to health behaviors, medication adherence, or other issues related to hypertension control as identified jointly by patient and CHW. The CHW also makes necessary referrals to other services available in the community (i.e. exercise classes, social services, mental health, tobacco cessation, etc.).

Recruitment and eligibility.

Practices

Working in concert with HF, we identified independent PCPs in Queens and Brooklyn with multiple or single PCPs at each site that are part of HF’s network and serve significant numbers of South Asian patients (defined as practices with at least 100 HF patients, and more than 70% of patients identifying as South Asian, or over 100 South Asian patients with hypertension). Practices were required to have an operating EHR, specifically eClinicalWorks (eCW) or MDLand, for at least 12 months prior the time of the enrollment [53, 54]. These sites were contacted by HF or the NYU-CUNY PRC study team staff by telephone to assess their eligibility in terms of number of South Asian patients and general interest in the project. If the representative expressed interest, the study team scheduled a site visit, during which eligible and interested practices signed an MOU to participate in the EHR intervention, and, one year later, a second MOU to participate in the CHW intervention.

Participants

Prior to the launch of the CHW intervention at each site, NYU-CUNY PRC staff work in concert with practice staff to identify a list of hypertensive patients within the previous six months that, at the last office visit, were reported to have a blood pressure > = 140 systolic or > = 90 diastolic through the EHR health registry. These patients are contacted by the CHWs and encouraged to participate if eligible. To be eligible, these patients must be between 18 and 85 years of age and must not be pregnant at the time of screening. If eligible, patients complete an in-person or phone-based screening that assesses baseline demographic and logistical information, such as preferred language and availability for education sessions. CHWs also participate in ‘tabling’ at practices, where CHWs ask interested patients in the waiting room to complete a screening form. For patients not identified through the original list, but found to have an uncontrolled blood pressure reading during the screening, they are encouraged to participate. To enroll into the intervention, patients must sign a consent form. All eligible and consented patients are then randomized, within each site, to participate in the CHW intervention either immediately or in six months. The purpose of this randomization is to have the second group, participating 6 months later, serve as a comparison group to the first group, participating immediately.

Data collection, measures, primary study outcomes, and analysis

The intervention launched in January 2016 at the first round of clinical practices, with additional rounds recruited at ~3-month intervals across the next year. The baseline period for each site is defined as the period prior to launch of the EHR intervention measured in 6-month intervals that occurred after Dec 31, 2015. Thus, all practices have a minimum of two 6-month baseline periods, and some have up to 4 rounds. Each practice is considered to be in the intervention period after the 3rd day of the EHR intervention launch, and a group intervention start date is selected for each round of clinical practices to accord with the first day of the next month. The intervention period includes the group start date through August 1, 2019.

Primary study outcome at practice level: Aggregate BP

Aggregate, or practice-level, EHR data is extracted for each 6-month time period between start of baseline and the start of the CHW intervention to evaluate the effect of the EHR intervention components. This data is also collected from the launch of the CHW intervention to August 2019 to evaluate the integrated effect of the EHR and CHW interventions. The primary outcome is the proportion of patients with a diagnosis of hypertension seen in the past 6 months deemed to be well-controlled (systolic blood pressure < 140 and diastolic blood pressure < 90) at last visit, following the indicator definition recommended by the NCQA [51]. The denominator includes all patients diagnosed with hypertension. Data extracted also includes demographics for patients seen for an office visit, as well as the proportion of these patients with a diagnosis of hypertension in the EHR by demographic subgroup (age group, sex). In addition, we monitor the proportion of hypertensive patients that report being a smoker and the proportion of these patients who were referred to smoking cessation during the past 6 months.

The impact of the EHR intervention on proportion of patients seen in the past 6 months with a diagnosis of hypertension deemed to be well-controlled at last visit will be examined in a mixed effects Poisson model, using pre-intervention time periods for comparison (see eq. 1):

$$ \log \left({C}_{it}\right)=\mu +{\beta}_1t+{\beta}_2{I}_{it}+{\beta}_3{I}_{it}\left(t-{s}_i\right)+{b}_i+\log \left({E}_{it}\right), $$

(1)

where C _it is the number of patients in site i who had controlled hypertension during period t. Each period is 6 months, and t = 0 is the baseline period. I _it is an indicator variable, and I _it = 1 if site i has started using the EHR at period t, I _it = 0 otherwise. s _i is the time period when the EHR starts at site i. E _it is the number of patients at site i who were diagnosed as hypertensive during period t. Log(E _it) is considered the “offset” in the Poisson regression model. b _i is a random effect for site i with mean 0 and variance $ {\upsigma}_b^2 $. The estimation via model (1) takes into account a general time trend, and allows for the intervention effects to grow over time following implementation of intervention. Our primary outcome is the proportion of patients who have controlled hypertension after the site has been using the EHR intervention components in the previous 6 months. This effect (after taking into account general time trends) will be captured by β ₂ + β ₃. We will conduct tests with these null and alternative hypotheses: H ₀ : β ₂ + β ₃ = 0 vs. H _A : β ₂ + β ₃ ≠ 0.

Secondary outcomes at practice level: Fidelity to EHR intervention

At the time of enrollment, each site that agreed to a scheduled visit was asked to complete three surveys prior to the launch of the EHR intervention. The first, a practice needs assessment survey, was administered either on paper or online via a web-enabled instrument developed in SNAP Survey software [55]. The survey assessed: (1) the estimated volume of patients seen per week at the site and the estimated proportion of patients that identify as South Asian; (2) provider knowledge and practices regarding hypertension control and the US Million Hearts initiative; (3) type of EHR system in use at the site and sophistication of its current usage; and (4) whether the site was interested in the CHW component, EHR component, or both components of the intervention. In the second survey, each provider within each site was asked to complete a provider needs assessment to determine: (1) basic demographics of each provider; (2) if/how each provider uses a standardized hypertension treatment protocol, clinical decision support software, the health registry, team-based management of care, and/or patient education/support groups; and (3) how the provider learns of hypertension guidelines. And third, the staff member most experienced with the EHR was asked to complete an EHR Checklist survey, which assessed: (1) MU and PCMH recognition status; (2) frequency of use of specific tools within the EHR, like customized templates, registry reports, and alerts, which allowed for an assessment of fidelity to key intervention components prior to the start of the EHR component of the intervention; and (3) where and how the practice documents counseling and education provided to patients. Throughout the EHR intervention, fidelity to intervention is assessed by collecting the type, frequency, and utilization of registry reports, alerts, and order sets for each practice.

Primary study outcome at individual level: Individual-level BP control

For assessment of the CHW intervention, the primary outcome of interest is hypertension control after 6 months among patients receiving the CHW intervention compared to those who are not receiving the CHW intervention. For this analysis, a mixed effect logistic regression model will be used to estimate the CHW effect on hypertension, accounting for clustering by clinical site (see eq. 2):

$$ \log \left[\frac{P\left({Y}_{ij}=1\right)}{1-P\left({Y}_{ij}=1\right)}\right]=\mu +{\beta}_1{H}_i+{b}_j, $$

(2)

where Y _ij indicates state of hypertension control at the end of 6 months for patient i in site j. Y _ij = 1 if patient achieved hypertension control, Y _ij = 0 otherwise. H _i = 1 if patient i was randomized to CHW in the first 6 month period, H _i = 0 otherwise. b _j is a random effect for site j with mean 0 and variance $ {\upsigma}_b^2 $. μ + b _i is the log odds of hypertension control for patients randomized to the control group in the first 6 months. β ₁ represents the log odds ratio of hypertension control for those randomized to CHW compared to those randomized to the control group. We will conduct a test with the following null and alternative hypotheses: H ₀ : β ₁ = 0 vs. H _A : β ₁ ≠ 0 to assess whether or not the CHW intervention had an effect on hypertension control after 6 months.

A secondary analysis of individual-level data will also be conducted among HF patients with a diagnosis of hypertension to further assess factors that might be associated with improved outcomes following the implementation of the EHR intervention. The outcome for individual-level analyses is hypertension control at last visit (systolic blood pressure (SBP) <140 and diastolic blood pressure (DBP) <90) [56]. Through the partnership with HF, we collect body mass index, age, gender, HbA1c, cholesterol levels, zip code, smoking status and frequency, diabetes diagnosis, past cardiac events, and healthcare utilization information on individual HF patients seen in the office and had a diagnosis of hypertension in the year prior to the start of the EHR system at the practice. The analysis of the binary outcome (hypertension control) will be conducted using mixed effects logistic regression.

Discussion

Project IMPACT builds upon the evidence base of the effectiveness of CHW and Million Hearts® Initiatives and proposes a unique integration of provider-based EHR and community-based CHW interventions. Millions Hearts® initiatives have demonstrated effectiveness at the health systems level and at the community level with English speaking minority communities [57, 58]. However, there exists a critical need to tailor, translate, and disseminate these initiatives for minority communities with limited English proficiency (LEP) with a high burden of CVD, such as the South Asian population. Thus, the focus of the IMPACT Project is the implementation and integration of evidence-based initiatives for the South Asian community to address hypertension control. Specifically, the study protocol described here tests the effectiveness of the CHW model embedded within the health care system to facilitate improved health outcomes by providing culturally tailored health promotion strategies, complementing physician-led efforts. Study findings can potentially provide translatable and scalable models for other LEP communities.

Despite its innovation, there are limitations that remain. The first, practices are not randomized to time-point. In other words, practices that enrolled first were the first to implement the EHR intervention, and subsequent practices that enrolled later receive the intervention at a later time. Randomization is not feasible for two reasons: (1) practice staff do not want to wait longer than is necessary to participate, and (2) recruitment and enrollment into the intervention is an intensive effort on the part of all partners involved, and waiting until 16 practices are enrolled would greatly delay study implementation and disrupt the study timeline. Second, our analysis of the impact of the EHR-component of the intervention is limited to HF participants only, given the nature of the partnership with HF and clinical sites.

This study’s strengths and innovation rests in several areas. First, the intervention takes evidence-based HIT strategies supported by the Million Hearts® Initiative and translates them to address CVD prevention among South Asians, a targeted disparity group with a high CVD burden and unique cultural barriers to health promotion and disease prevention. Second, the study integrates culturally tailored CHW programs into clinical practice initiatives to improve CVD outcomes for ethnic minority and immigrant populations with substantial language barriers to health care access and disease prevention. Using a hybrid effectiveness- implementation model, we evaluate the effectiveness of integrating these two evidence-based strategies (EHR-based tools for improved patient panel management and team-based care including CHWs) into health care delivery systems by partnering with a multi-stakeholder network that includes insurers, providers, and front-line quality improvement agencies. The partnerships guiding this protocol were critical to the process of provider engagement, accessing patient data to evaluate study effectiveness, and the provision of technical assistance and training. Cross-sector partnerships can enhance the sustainability of community-clinical linkage programs, and future studies should assess the potential and impact of partnering with multiple payers to enhance the reach of these types of programs and strategies. These findings will have implications for translating similar strategies for other LEP communities, including Asian and Hispanic Americans, and to other clinical settings. Finally, the project informs the effectiveness of these interventions in team-based care approaches, thereby, helping to develop relevant sustainability strategies.

Acknowledgements

We would like to acknowledge and thank Joanne Vanterpool, MBA and Susan Hollander, MPH, CPHQ, from IPRO, the federally-funded Medicare Quality Innovation Network-Quality Improvement Organization, for their substantial contributions to the implementation of the EHR intervention and their review of key EHR components in this protocol. We would also like to thank the coalition of providers, community members, and community health workers that provided their unique perspective and suggestions in the creation of this protocol.

Funding

The funding source: This study is supported by grant number U48DP005008 from the Centers for Disease Control and Prevention (CDC). Author’s contributions are additionally supported in part by grant number U58DP005621 from the Centers for Disease Control and Prevention (CDC), P60MD000538, U54MD000538-15, R01DK110048-01A1, UL1TR001445 from the National Institutes of Health (NIH). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH and CDC.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Both the EHR and CHW components of this project were submitted to the Institutional Review Boards (IRBs) of the NYU School of Medicine and CUNY Graduate School of Public Health and Health Policy. NYU’s IRB deemed both components of the project as non-human subjects research, and waived the need for IRB approval. CUNY’s IRB approved both components of the project.

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

About Million Hearts ®. Million Hearts Campaign. Health and Human Services. https://millionhearts.hhs.gov/about-million-hearts/index.html. Accessed 29 March 2017.

Valderrama AL, Gillespie C, King SC, George MG, Hong Y, Gregg E. Vital signs: awareness and treatment of uncontrolled hypertension among adults-United States, 2003–2010. Morb Mortal Wkly Rep (MMWR). 2012;61(35):703–9. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6135a3.htm.

Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care. 2005;43:521–30.CrossRefPubMed

Anand SS, Yusuf S, Vuksan V, et al. Differences in risk factors, atherosclerosis, and cardiovascular disease between ethnic groups in Canada: the study of health assessment and risk in ethnic groups (SHARE). Lancet. 2000;356:279–84.CrossRefPubMed

Narayan KM, Aviles-Santa L, Oza-Frank R, et al. Report of a National Heart, lung, and blood institute workshop: heterogeneity in cardiometabolic risk in Asian Americans in the U.S. opportunities for research. J Am Coll Cardiol. 2010;55:966–73. https://doi.org/10.1016/j.jacc.2009.07.075. CrossRefPubMed

Sheth T, Nair C, Nargundkar M, Anand S, Yusuf S. Cardiovascular and cancer mortality among Canadians of European, south Asian and Chinese origin from 1979 to 1993: an analysis of 1.2 million deaths. CMAJ. 1999;161:132–8.PubMedPubMedCentral

Tillin T, Forouhi N, Johnston DG, McKeigue PM, Chaturvedi N, Godsland IF. Metabolic syndrome and coronary heart disease in south Asians, African-Caribbeans and white Europeans: a UK population-based cross-sectional study. Diabetologia. 2005;48:649–56.CrossRefPubMed

Wild SH, Fischbacher C, Brock A, Griffiths C, Bhopal R. Mortality from all causes and circulatory disease by country of birth in England and Wales 2001-2003. J Public Health (Oxf). 2007;29:191–8.CrossRef

Ye J, Rust G, Baltrus P, Daniels E. Cardiovascular risk factors among Asian Americans: results from a National Health Survey. Ann Epidemiol. 2009;19:718–23. https://doi.org/10.1016/j.annepidem.2009.03.022.CrossRefPubMed

10.

Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89:1322–7.CrossRefPubMedPubMedCentral

11.

Asian/Pacific American Heritage: May 2011. United States Census Bureau. http://www.census.gov/newsroom/releases/archives/facts_for_features_special_editions/cb11-ff06.html . Accessed 29 March 2017.

12.

Asian American Federation. Asian Americans in New York City: A Decade of Dynamic Change 2000–2010. http://www.aafederation.org/pdf/AAF_nyc2010report.pdf. Accessed 29 March 2017.

13.

Enas EA, Garg A, Davidson MA, Nair VM, Huet BA, Yusuf S. Coronary heart disease and its risk factors in first-generation immigrant Asian Indians to the United States of America. Indian Heart J. 1996;48:343–53.PubMed

14.

Misra R, Patel T, Kotha P, et al. Prevalence of diabetes, metabolic syndrome, and cardiovascular risk factors in US Asian Indians: results from a national study. J Diabetes Complicat. 2010;24:145–53. https://doi.org/10.1016/j.jdiacomp.2009.01.003.CrossRefPubMed

15.

Rajpathak SN, Gupta LS, Waddell EN, et al. Elevated risk of type 2 diabetes and metabolic syndrome among Asians and south Asians: results from the 2004 new York City HANES. Ethn Dis. 2010;20:225–30.PubMed

16.

Esperat MC, Inouye J, Gonzalez EW, Owen DC, Feng D. Health disparities among Asian Americans and Pacific islanders. Annu Rev Nurs Res. 2004;22:135–59.PubMed

17.

Yi SS, Thorpe LE, Zanowiak JM, Trinh-Shevrin C, Islam NS. Clinical characteristics and lifestyle behaviors in a population-based sample of Chinese and south Asian immigrants with hypertension. Am J Hypertens. 2016;29(8):941–7. https://doi.org/10.1093/ajh/hpw014.CrossRefPubMedPubMedCentral

18.

Fei K, Rodriguez-Lopez J, Ramos M, Islam N, Trinh-Shevrin C, Yi S, Chernov C, Perlman S, Thorpe LE. Racial/ethnic subgroup disparities in hypertension prevalence: results from the 2013-14 new York City health and nutrition examination survey (NYC HANES). Prev Chronic Dis. In Press.

19.

Abe-Kim J, Takeuchi D, Hwang WC. Predictors of help seeking for emotional distress among Chinese Americans: family matters. J Consult Clin Psychol. 2002;70:1186–90.CrossRefPubMed

20.

Narikiyo T, Kameoka V. Attributions of mental illness and judgements about help-seeking among Japanese Americans and white-American students. J Couns Psychol. 1992;39 http://psycnet.apa.org/fulltext/1992-40455-001.html. Accessed 29 March 2017.

21.

Shin JK. Help-seeking behaviors by Korean immigrants for depression. Issues Ment Health Nurs. 2002;23:461–76.CrossRefPubMed

22.

Chin JJ, Mantell J, Weiss L, Bhagavan M, Luo X. Chinese and south Asian religious institutions and HIV prevention in new York City. AIDS education and prevention: official publication of the international society for AIDS. Education. 2005;17:484–502. https://doi.org/10.1521/aeap.2005.17.5.484.

23.

Islam NS, Wyatt LC, Patel SD, et al. Evaluation of a community health worker pilot intervention to improve diabetes management in Bangladeshi immigrants with type 2 diabetes in new York City. Diabetes Educ. 2013;39:478–93. https://doi.org/10.1177/0145721713491438.CrossRefPubMedPubMedCentral

24.

Islam NS, Zanowiak JM, Wyatt LC, et al. A randomized-controlled, pilot intervention on diabetes prevention and healthy lifestyles in the new York City Korean community. J Community Health. 2013;38(6):1030–41. https://doi.org/10.1007/s10900-013-9711-z.CrossRefPubMedPubMedCentral

25.

Ursua R, Islam N, Aguilar D, et al. Predictors of hypertension among Filipino immigrants in the northeast US. J Community Health. 2013;38(5):847–55. https://doi.org/10.1007/s10900-013-9689-6.CrossRefPubMedPubMedCentral

26.

Cardiovascular disease: Team-based care to improve blood pressure control. The Community Guide, 2012. https://www.thecommunityguide.org/findings/cardiovascular-disease-team-based-care-improve-blood-pressure-control. Accessed 29 March 2017.

27.

Walsh JM, McDonald KM, Shojania KG, et al. Quality improvement strategies for hypertension management: a systematic review. Med Care. 2006;44:646–57.CrossRefPubMed

28.

Cardiovascular disease: Clinical Decision-Support Systems (CDSS). The Community Guide, 2013. https://www.thecommunityguide.org/findings/cardiovascular-disease-clinical-decision-support-systems-cdss. Accessed 29 March 2017.

29.

Viswanathan M, Kraschnewski JL, Nishikawa B, et al. Outcomes and costs of community health worker interventions: a systematic review. Med Care. 2010;48:792–808. https://doi.org/10.1097/MLR.0b013e3181e35b51.CrossRefPubMed

30.

Martinez J, Ro M, Villa NW, Powell W, Knickman JR. Transforming the delivery of care in the post-health reform era: what role will community health workers play? Am J Public Health. 2011;101:e1–5. https://doi.org/10.2105/AJPH.2011.300335.CrossRefPubMedPubMedCentral

31.

Brownstein JN, Chowdhury FM, Norris SL, et al. Effectiveness of community health workers in the care of people with hypertension. Am J Prev Med. 2007;32:435–47.CrossRefPubMed

32.

Persell SD, Dunne AP, Lloyd-Jones DM, Baker DW. Electronic health record-based cardiac risk assessment and identification of unmet preventive needs. Med Care. 2009;47:418–24. https://doi.org/10.1097/MLR.0b013e31818dce21.CrossRefPubMed

33.

Persell SD, Lloyd-Jones DM, Friesema EM, Cooper AJ, Baker DW. Electronic health record-based patient identification and individualized mailed outreach for primary cardiovascular disease prevention: a cluster randomized trial. J Gen Intern Med. 2013;28:554–60. https://doi.org/10.1007/s11606-012-2268-1.CrossRefPubMed

34.

Fellows JL, Mularski R, Waiwaiole L, et al. Health and economic effects from linking bedside and outpatient tobacco cessation services for hospitalized smokers in two large hospitals: study protocol for a randomized controlled trial. Trials. 2012;13:129. https://doi.org/10.1186/1745-6215-13-129.CrossRefPubMedPubMedCentral

35.

Kruse GR, Kelley JH, Linder JA, Park ER, Rigotti NA. Implementation of an electronic health record-based care management system to improve tobacco treatment. J Gen Intern Med. 2012;27:1690–6. https://doi.org/10.1007/s11606-012-2174-6.CrossRefPubMedPubMedCentral

36.

Adair R, Wholey DR, Christianson J, White KM, Britt H, Lee S. Improving chronic disease care by adding laypersons to the primary care team: a parallel randomized trial. Ann Intern Med. 2013;159:176–84. https://doi.org/10.7326/0003-4819-159-3-201308060-00007.CrossRefPubMed

37.

Walton JW, Snead CA, Collinsworth AW, Schmidt KL. Reducing diabetes disparities through the implementation of a community health worker-led diabetes self-management education program. Fam Community Health. 2012;35:161–71. https://doi.org/10.1097/FCH.0b013e31824651d3.CrossRefPubMed

38.

Islam N, Nadkarni S, Peretz P, Matiz LA, Hirsch G, Kane E, Collinsworth A, Kangovi S, Godfrey WK, Hyde J, Matos S, Kumar R, Lopez P, Zhong L, Thorpe L, and Trinh-Shevrin C. Integration of Community Health Workers into Primary Care Health Systems: The Time for New York is Now! NYU-CUNY Prevention Research Center. October 2016. NY, NY. http://www.med.nyu.edu/prevention-research/sites/default/files/prevention-research2/NYU-CUNY%20PRC%20-%20Integration%20of%20CHWs%20into%20Primary%20Care%20Systems.pdf. Accessed 29 March 2017.

39.

NYU-CUNY Prevention Research Center. http://www.med.nyu.edu/prevention-research/nyu-cuny-prevention-research-center. Accessed 29 March 2017.

40.

Healthfirst. http://healthfirst.org/. Accessed 29 March 2017.

41.

IPRO. http://ipro.org/. Accessed 29 March 2017.

42.

Kwon S, Patel S, Choy C, Zanowiak J, Rideout C, Yi S, Wyatt L, Taher MD, Garcia - Dia MJ, Kim SS, Denholm TK, Kavathe R, Islam NS. Implementing health promotion activities using community-engaged approaches in Asian American faith-based organizations in new York City and New Jersey. Transl Behav Med. In Press.

43.

Islam N, Riley L, Wyatt L, Tandon SD, Tanner M, Ratnam-Mukjerji R, Rey M, Trinh-Shevrin C. Protocol for the DREAM project (diabetes research, education, and action for minorities): a randomized trial of a community health worker intervention to improve diabetic management and control among Bangladeshi adults in NYC. BMC Public Health. 2014;14(1):177. https://doi.org/10.1186/1471-2458-14-177. CrossRefPubMedPubMedCentral

44.

Curran GM, Bauer M, Mittman B, Pyne JM, Stetler C. Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact. Med Care. 2012;50:217–26. https://doi.org/10.1097/MLR.0b013e3182408812.CrossRefPubMedPubMedCentral

45.

Handley MA, Schillinger D, Shiboski S. Quasi-experimental designs in practice-based research settings: design and implementation considerations. J Am Board Fam Med. 2011;24:589–96. https://doi.org/10.3122/jabfm.2011.05.110067.CrossRefPubMed

46.

Gliklich RE, Dreyer NA, Leavy MB, editors. Registries for Evaluating Patient Outcomes: A User's Guide. 3rd edition. Agency for Healthcare Research and Quality (US); Section IV, Technical, Legal, and Analytic Considerations for Combining Registry Data With Other Data Sources. https://www.ncbi.nlm.nih.gov/books/NBK208607/?report=reader. Accessed 29 March 2017.

47.

Clinical Decision Support: More than just ‘Alerts’ Tipsheet. Centers for Medicare & Medicaid Services. https://www.cms.gov/regulations-and-guidance/legislation/EHRincentiveprograms/downloads/clinicaldecisionsupport_tipsheet-.pdf. Accessed 29 March 2017.

48.

Reference card from the seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure (JNC 7). https://www.nhlbi.nih.gov/files/docs/guidelines/phycard.pdf. Accessed 29 March 2017.

49.

Meaningful Use. CMS. https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html?redirect=/EHRIncentivePrograms/. Accessed 29 March 2017.

50.

Patient Centered Medical Home. NCQA. http://www.ncqa.org/Programs/Recognition/Practices/PatientCenteredMedicalHomePCMH.aspx. Accessed 29 March 2017.

51.

National Heart Lung and Blood Institute. Healthy Heart, Healthy Family: A community health worker’s manual for the Filipino community. http://www.nhlbi.nih.gov/health/prof/heart/other/chdfilipino/intro.htm. Accessed 29 March 2017.

52.

Project IMPACT CHW training materials. http://www.med.nyu.edu/prevention-research/projects/project-impact. Accessed 29 March 2017.

53.

eClinicalWorks. https://www.eclinicalworks.com/. Accessed 29 March 2017.

54.

MDLand. http://www.mdland.com/. Accessed 29 March 2017.

55.

SNAP Software. https://www.snapsurveys.com/. Accessed 29 March 2017.

56.

NCQA Hypertension Control Measure. https://www.hrsa.gov/quality/toolbox/measures/hypertension/. Accessed 29 March 2017.

57.

Kaiser Permanente Colorado high blood pressure and cholesterol management program. https://millionhearts.hhs.gov/files/SS_Colorado.pdf. Accessed 29 March 2017.

58.

Ferdinand KC, Patterson KP, Taylor C, Fergus IV, Nasser SA, Ferdinand DP. Community-based approaches to prevention and management of hypertension and cardiovascular disease. J Clin Hypertens (Greenwich, Conn). 2012;14:336–43. https://doi.org/10.1111/j.1751-7176.2012.00622.x.CrossRef

Titel: Protocol for project IMPACT (improving millions hearts for provider and community transformation): a quasi-experimental evaluation of an integrated electronic health record and community health worker intervention study to improve hypertension management among South Asian patients
verfasst von: Priscilla M. Lopez
Jennifer Zanowiak
Keith Goldfeld
Katarzyna Wyka
Ahmad Masoud
Susan Beane
Rashi Kumar
Phoebe Laughlin
Chau Trinh-Shevrin
Lorna Thorpe
Nadia Islam
Publikationsdatum: 01.12.2017
Verlag: BioMed Central
Erschienen in: BMC Health Services Research / Ausgabe 1/2017
Elektronische ISSN: 1472-6963
DOI: https://doi.org/10.1186/s12913-017-2767-1

Live-Webinar: Aktuelle Leitlinien bei Herz-Kreislauf-Erkrankungen

Springer Medizin

Protocol for project IMPACT (improving millions hearts for provider and community transformation): a quasi-experimental evaluation of an integrated electronic health record and community health worker intervention study to improve hypertension management among South Asian patients

Abstract

Background

Methods

Discussion

Trial registration

Background

Methods

Objectives

Study team

Study design

Intervention components

Phase 1: EHR intervention

Phase 2: CHW intervention

Practices

Participants

Data collection, measures, primary study outcomes, and analysis

Primary study outcome at practice level: Aggregate BP

Secondary outcomes at practice level: Fidelity to EHR intervention

Primary study outcome at individual level: Individual-level BP control

Discussion

Acknowledgements

Funding

Availability of data and materials

Competing interests

Publisher’s Note

Live-Webinar: Aktuelle Leitlinien bei Herz-Kreislauf-Erkrankungen

Springer Medizin

Abstract

Background

Methods

Discussion

Trial registration

Background

Methods

Objectives

Study team

Ethics and data sharing approvals

Study design

Intervention components

Phase 1: EHR intervention

Phase 2: CHW intervention

Practices

Participants

Data collection, measures, primary study outcomes, and analysis

Primary study outcome at practice level: Aggregate BP

Secondary outcomes at practice level: Fidelity to EHR intervention

Primary study outcome at individual level: Individual-level BP control

Discussion

Acknowledgements

Funding

Availability of data and materials

Ethics approval and consent to participate

Consent for publication

Competing interests

Publisher’s Note

Weitere Artikel der Ausgabe 1/2017

Are performance measurement systems useful? Perceptions from health care

The personal and workplace characteristics of uninsured expatriate males in Saudi Arabia

Challenges, uncertainties and perceived benefits of providing weekend allied health services—a managers’ perspective

The ecology of medical care on an isolated island in Okinawa, Japan: a retrospective open cohort study

Training nurses in task-shifting strategies for the management and control of hypertension in Ghana: a mixed-methods study

Are physicians aware enough of patient radiation protection? Results from a survey among physicians of Pavia District– Italy