An integrated intervention for chronic care management in rural Nepal: a type 2 hybrid effectiveness-implementation study


 Background In Nepal, the burden of non-communicable, chronic diseases is rapidly rising, and disproportionately affecting low- and middle-income countries. Integrated interventions are essential in strengthening primary care systems and addressing the burden of multiple comorbidities. A growing body of literature supports the involvement of frontline providers, namely mid-level practitioners and community health workers, in chronic care management. Important operational questions remain, however, around the digital, training, and supervisory structures to support the implementation of effective, affordable, and equitable chronic care management programs. Methods A twelve-month, population-level, type 2 hybrid effectiveness-implementation study will be conducted in rural Nepal to evaluate an integrated non-communicable disease care management intervention within Nepal’s new municipal governance structure. The intervention will leverage the government’s planned roll-out of the World Health Organization’s Package of Essential Non-communicable disease interventions (WHO-PEN) program in four municipalities in Nepal, with a study population of 80,000. The intervention will leverage both the WHO-PEN and its cardiovascular disease specific technical guidelines, HEARTS, and include three evidence-based components: 1) non-communicable disease care provision using mid-level practitioners and community health workers; 2) digital clinical decision support tools to ensure delivery of evidence-based care; and 3) training and digitally-supported supervision of mid-level practitioners to provide motivational interviewing for modifiable risk factor optimization, with a focus on medication adherence, and tobacco and alcohol use. The study will evaluate effectiveness using a pre-post design with stepped implementation. The primary outcomes will be disease-specific, “at-goal” metrics of chronic care management; secondary outcomes will include alcohol and tobacco consumption levels. Discussion This is the first population-level, hybrid effectiveness-implementation study of an integrated chronic care management intervention in Nepal. As low- and middle-income countries plan for the Sustainable Development Goals and universal health coverage, the results of this pragmatic study will offer insights into policy and programmatic design for non-communicable disease care management in the future.

implementation. The primary outcomes will be disease-specific, "at-goal" metrics of chronic care management; secondary outcomes will include alcohol and tobacco consumption levels. Discussion This is the first population-level, hybrid effectiveness-implementation study of an integrated chronic care management intervention in Nepal. As low-and middle-income countries plan for the Sustainable Development Goals and universal health coverage, the results of this pragmatic study will offer insights into policy and programmatic design for non-communicable disease care management in the future.
background The burden of non-communicable diseases (NCDs) is rising globally, [1,2] and four major NCD classes -cardiovascular disease, chronic respiratory disease, diabetes, and cancer -contribute to more deaths globally than all other diseases combined, with enormous health and economic implications currently and in the future. [3,4] This is especially true in low-and middle-income countries (LMICs), where governments are struggling to plan for the increasing health and financial implications of these pandemics. [5] As governments strive to achieve the Sustainable Development Goals [6] and work towards universal health coverage, [7] the rising NCD pandemic poses significant barriers to these aspirations.
In spite of this growing need for long-term chronic disease care, LMIC healthcare systems are not well-equipped to address this disease burden. [8] Historically focused on delivering acute, episodic care, these healthcare systems lack the capacity to provide on-going longitudinal care for patients with diseases best managed across a lifetime. This is especially true for patients with multiple chronic conditions, who often struggle to receive care for co-morbid diseases without numerous, fragmented encounters. [9] Health workforce shortages, and an emphasis on physician-provided care, have contributed to significant access, coverage, and quality deficits. [10,11] There is a growing body of evidence that chronic diseases in LMICs can be wellmanaged, especially at the primary care level, by mid-level practitioners (MLPs). [10,[12][13][14][15][16][17][18][19][20][21] MLPs offer a feasible, affordable, and high-quality alternative to traditionally physician-delivered care. This can help to circumvent access barriers, thereby leading to fewer late-stage presentations and complications of otherwise manageable chronic conditions. [20] Evidence suggests the quality of MLP-delivered care improved when they are well-managed, assigned clear scopes of work for which they are appropriately-trained, and receive supportive supervision [22][23][24] by senior clinicians with continual, improvement-focused feedback. [20] Simultaneously, the role of community health workers (CHW) is increasingly recognized as an important augmentation to facility-based care delivery strategies, offering critical linkages, referrals, and coordination of care within communities. [25][26][27] The potential value of CHW-augmented chronic care management has only recently become of major interest. [12][13][14][15][16][17][18][27][28][29] Global experience suggests that the greatest benefits come from CHWs when they are accredited, well-managed, salaried, continually trained and supervised, integrated into strong primary care systems, and part of continual data feedback loops with facility-based providers. [25] Taken together, the need and opportunity for LMIC healthcare systems -already struggling with workforce shortages -to build strong chronic care programs managed by MLPs and augmented with CHWs is compelling. However, there is a paucity of large-scale implementation data available to evaluate such models of care delivery, making it difficult for LMIC policy-makers to decide whether to adopt these strategies.
In response to the growing need for evidence-based NCD service delivery, the World Health Organization has compiled a set of protocols within the Package of Essential Historically, in many LMICs, there has been scant emphasis placed on risk factor reduction through lifestyle modification for NCD prevention or to reduce risk factors for the progression of these diseases when already diagnosed. While many of the contributing etiologies for NCD epidemics are far upstream of individuals' lives, and out of their control, [45] there are certain risk factors that are modifiable by patients, families, and health workers. Among others, it is widely documented that alcohol and tobacco consumption directly contribute to the development and progression of cardiovascular disease, diabetes, and chronic obstructive pulmonary disease (COPD). [46] These risk factors have been marked as priority targets for NCD control moving forward, including in both the WHO-PEN and HEARTS protocols. [8,47] WHO-PEN Protocol #2 (and republished in HEARTS), "Health Education and Counseling on Healthy Behaviors," describes risk factor modification. [31] However, while emphasizing health education, there is often very little guidance provided to health workers for meaningful engagement with patients and communities to accomplish these difficult lifestyle modification goals. There are many limitations to purely knowledge-focused approach health education, verses one that emphasizes self-efficacy and patients' own values. [48] Motivational interviewing (MI), originally validated in substance-abuse interventions, approaches behavior change through a style characterized by empathy and collaboration aimed towards the patient's readiness for change. [49] Trial data demonstrate the efficacy of MI for behavior change such as smoking and alcohol cessation. [50][51][52][53][54][55] These data raise the possibility of MI program development, led by MLPs within LMICs, as a viable strategy for improving risk factor modification interventions, and specifically, as an augmentation to WHO-PEN, to strengthen its impact. Since many communities struggle with a lack of healthy nutritional options, dietary improvements are often difficult to realize. Reducing alcohol and tobacco consumption, however, are realistic options for risk factor modification interventions in even the poorest communities worldwide. Recent WHO-PEN guidance on "brief interventions" for alcohol and tobacco, in concert with MI-related interventions, offer practical options for addressing these challenges in the primary care setting. [48] In Nepal, the burden of NCDs is rapidly growing, [56][57][58] within the context of an overburdened healthcare system. [12,58,59] Nepal's government is committed to achieving the Sustainable Development Goals and universal healthcare, and has a specific focus on expanding health services for NCDs. In addition to recently enshrining the right to healthcare into its Constitution, [60] Nepal's government has committed to addressing the NCD epidemic by launching a Multisectoral Action Plan in 2014 [61] and establishing the Nepal Non-communicable Disease & Injury Poverty Commission in 2016. [58] Furthermore, the Ministry of Health and Population has committed to a step-wise national implementation of PEN. [58,59,62] Nonetheless, the way forward will be challenging, and innovative strategies are clearly needed to accomplish these ambitious goals. [58] Nepal has an extensive history of both MLP and CHW interventions. [63][64][65] Recent evidence from within the country has demonstrated the potential for CHWs to be involved in hypertension management. [66] Many communities rely on MLPs for primary care, [43,67] and there has been some experience with MLPs using CDS tools for algorithmic care provision. [43] However, to date there are no large-scale implementation data of integrated, MLP-and CHW-based NCD care management at the population level. Similarly, while there has been some anecdotal description of MI being utilized in urban areas for select populations, there is no population-level data surrounding the use of MI for NCD risk modification. As the country endeavors to develop cross-sectoral strategies to address the growing NCD epidemic, these staffing models, coupled with CDS tools and MI-based adherence and risk modification, are important policy and programmatic considerations.
We will conduct a type 2 hybrid effectiveness-implementation trial (where effectiveness and implementation are simultaneously tested with equal priority simultaneously) [68,69] to evaluate an integrated NCD care management intervention. The intervention will leverage the Nepali government's planned rollout of WHO-PEN in two rural districts. In addition to the government's roll-out, the intervention will include three evidence-based components: 1) NCD care provision by MLPs and CHWs that is integrated between facilities and communities; 2) CDS tools for MLPs and CHWs to optimize adherence to best practices; and 3) training and supervision of MLPs in using MI to facilitate tobacco and alcohol cessation.

Study aims
As above, we will conduct a type 2 hybrid effectiveness-implementation trial to evaluate an integrated NCD care management intervention in rural Nepal. The intervention is described in depth in the Supplementary File 1.

Study implementers
Healthcare workers and research staff from the non-profit organization Nyaya

Health Nepal, their collaborators in the Ministry of Health and Population and Nepal
Health Research Council, and collaborating researchers form the study team will lead the study. Nyaya Health Nepal has been working in a public-private partnership with the Ministry of Health and Population for over ten years in rural Nepal to deliver community-and facility-based health services, and this study will leverage this pre-existing partnership and care delivery network. Nyaya Health Nepal operates with a United States-based non-profit organization, Possible, to advance national and global healthcare systems policy and practice priorities.

Study setting
The study will take place in Achham and Dolakha districts of Nepal across four municipalities. Following recent healthcare decentralization, Nepal's 750 municipalities manage primary healthcare delivery. The intervention will be implemented in a step-wise fashion in coordination with municipal-level government authorities and study staff.
Achham is a remote, impoverished district of 260,000 people, with large migrant populations and a history of social disruption during the Nepali civil conflict. [70][71][72][73][74] Achham has one of the highest district-level under-five mortality rates [75] and one of the lowest human development indices in the country. [76] The study implementers have been delivering some NCD-related care at the district-level Bayalpata Hospital and to communities within the hospital's catchment population since 2008. Bayalpata Hospital serves approximately 90,000 outpatient and 3,000 inpatient visits per year. CHW services include proactive case detection, care coordination, and counseling. The study will include a catchment population of approximately 50,000 in Achham across two municipalities.
The second district is Dolakha, one of the hardest hit districts in the 2015

earthquakes.[77] Nyaya Health Nepal's work in Dolakha is based at Charikot Primary
Health Care Center, which serves approximately 60,000 outpatients per year, with similar CHW services to those in Achham's. The study will include a population of approximately 30,000 in Dolakha across two municipalities. Thus, the total expected study population will be 80,000.
Within the context of the public private partnership between the government and Nyaya Health Nepal, no user fees are charged for any facility-based or communitybased services, in either Achham or Dolakha, thereby mitigating financial access barriers to care delivery and study participation.
Within the study setting, MLPs for the NCD intervention are locally defined as the Nepali cadre of Health Assistants, who have three years of post-secondary medical training. The CHWs in this intervention have secondary-school-level education, and are fully employed, with on-going supervision by Community Health Nurses (CHNs).
They receive initial training of approximately one month when they are hired, and on-going weekly trainings to continually improve their skillsets. The CHWs are employed by the public-private partnership between Nyaya Health Nepal and the Ministry of Health and Population. They are distinct from the robust Female Community Health Volunteer network that exists throughout Nepal, [63,78] who have historically focused on vaccination, public health messaging, and other community preventive interventions rather than on household care delivery and follow-up. These staffing, supervision and training structures are described in greater detail in the Supplemental File 1 and 2.

Study populations
For primary quantitative outcomes, the study population will include adult patients (≥18 years of age) who qualify for a diagnosis of hypertension, type II diabetes, and/or COPD, according to WHO-PEN guidelines, and are engaged in longitudinal care by Nyaya Health Nepal's team in Achham and Dolakha. The study will limit enrollment to the catchment areas served by both the facility-level and CHW-level services deployed by Nyaya Health Nepal. Study participants will be initially enrolled during facility-based visits at Bayalpata Hospital and Charikot Primary Health Care Center prior to the completion of intervention roll-out, and are considered engaged in longitudinal care if they have at least one follow-up hospital visit after 12 months of their initial visit. Digital health records that link between the facility-based EHR and the CHWs' mobile-phone applications will be utilized to share patient data across settings, when available. CHWs can identify potential patients in the community and refer them to the facility for diagnosis confirmation, following which they could be included in the study. Patients' receipt of care will not be contingent upon their enrollment in the study; all patients will continue to receive care per routine service delivery. This represents an exhaustive convenience sampling method as all eligible patients identified at Bayalpata Hospital and Charikot Primary Health Care Center may be enrolled in the study.
Exclusion criteria are (1) individuals planning to migrate from the study area prior to twelve months of exposure to the intervention, or (2) individuals explicitly requesting exclusion from the study or declining to consent (see Supplemental File 3) for the study.
For implementation components, staff members, patients, community leaders, and government officials will be approached for key informant interviews (KIIs) and focus group discussions (FGDs), as described below.

Study design
This is a prospective, mixed-methods type 2 hybrid effectiveness-implementation study to evaluate an integrated NCD care management intervention. We plan to apply both qualitative and quantitative methods in a complementary manner, [79] in order to meaningfully assess both patient-level and population-level outcomes and the effectiveness of the implementation strategy. We will study the intervention's impact on patients' disease management outcomes after 12 months of being enrolled in NCD care using a pre-post design across both sites.
1) We will study the implementation of the intervention utilizing both quantitative and qualitative methods applying the RE-AIM (Reach, Efficacy, Adoption, Implementation, and Maintenance) framework [80].
Data collection is developed and integrated within the routine course of delivering care, which is an ethical, acceptable, and affordable approach in this setting. See

Study outcomes
The study has two Specific Aims: effectiveness (Specific Aim 1) and implementation (Specific Aim 2), as detailed in Table 1. For Specific Aim 1, the primary outcome will be the proportion of patients who meet disease-specific, evidence-based control measures at the completion of their initial twelve months engaged in treatment.
These "at-goal" metrics aim to serve as simplified measures to assess disease control status, recognizing the limitations associated with multiple disease-specific metrics in settings like rural Nepal, especially for patients with multiple co-morbid conditions. These are presented in Table 2.  ¥Chronic obstructive pulmonary disease: The 2017 update to the GOLD guidelines [83] define COPD exacerbation as an "acute worsening of respiratory symptoms that results in additional therapy." We used the Anthonisen criteria of worsening sputum volume, sputum purulence, and increased dyspnea to define the "worsening of respiratory symptoms" specified in the GOLD guidelines. We established a threshold of no more than one Anthonisen criterion as a pragmatic tool for determining clinical status.
Secondary outcomes for Specific Aim 1 will include the following. We will assess the individual "at goal" rates per condition. We will assess the persistence of the intervention for the subset of patients for whom we have the data (i.e., those enrolled within 12 months of the start of the study) on their 24 months' outcome.
Additionally, we will examine the tobacco and alcohol status of enrolled patients, specifically focusing on the proportion of patients who were tobacco users and/or alcohol drinkers at the time of enrollment, who have stopped all tobacco and / or alcohol intake, or reduced their intake by >50%, by the completion of the study period (Table 1).
For Specific Aim 2, the RE-AIM framework will be utilized to assess the implementation of the study intervention, with RE-AIM metrics as listed in Table 1.

Sampling strategy and power calculations
We will use exhaustive convenience sampling to screen all eligible patients seen across two facilities over a twelve month period into the analysis cohort. Based on historical formative data of patient volume seen at these two facilities, and accounting for an expected 30% attrition rate, we conservatively expect that at least 1000 patients will be eligible for enrollment into the cohort.
With this conservative number of 1000 as our expected sample size based on this convenience sampling, we conducted power calculations to determine the statistical power to detect a change in the "at goal" status. We calculate power based on a simplified design to compare paired proportions using a two-sided McNemar's test with an 0.05 Type I error (alpha) level. The primary outcome is the proportion of patients who achieve their NCD control target ("at goal status") after 12 months of being engaged in care. We used SAS version 9.4 (Cary, NC) to estimate power to detect a 5% difference between discordant proportions, i.e. proportions of patients whose "at goal" status changed from "not at goal" at baseline to "at goal" at followup, and vice-versa, in multiple scenarios where the total proportion of discordant patients ranged from 10% to 40% of all patients. Based on these assumptions, our power to detect a 5% difference in the discordant pairs is 69%, when the total discordant proportion is 40%, and the power is 99% when 10% of all patients were discordant.

Data collection
Quantitative data Quantitative data for patient outcomes will be extracted from the facility-based EHR and the CHW's mobile phone application (Supplemental File 5), and will be used to assess Specific Aims 1 and 2. (Table 1) All implementation-related data for evaluating the performance of MLPs and CHWs (Table 1) will be collected by the responsible MLP and CHW supervisors in digitized checklists within the EHR and mobile phone application. Access to protected health information will be controlled and defined by user access groups according to clinician status. Data to be analyzed will be extracted via secure data queries from the EHR system in aggregate, partially de-identified form with external researchers signing a data sharing and use agreement prior to analysis. Cleaned, de-identified datasets will be made publicly available via a data repository.
Costing data for the intervention will be collected utilizing a "top-down" method, as described by the Joint Learning Network [84]. This method will document direct and indirect costs associated with the NCD care delivery intervention described here and related administrative functions (including planning and administration; training; supervision and monitoring and evaluation; data management; and continuous surveillance) will be disaggregated. Full methodology of direct and indirect costs is provided by the Joint Learning Network [84], and will be utilized for this study. For the purposes of this pragmatic study, this methodology will be appropriate to estimate the additional marginal costs of the intervention (rather than cost-savings or secondary cost implications) as compared to general standard of care.

Qualitative data
Qualitative data will be used for Specific Aim 2. (Table 2) Staff members, patients, community leaders, and government officials will be approached for KIIs and FGDs.
Purposive sampling will be used, aiming to maximize heterogeneity across sex, socioeconomic position, healthcare issues, geographic location, age, caste-class, and other attributes. For each group, five key informant interviews will be conducted at each time point, as described below. One focus group discussion per group will be conducted at each time point.
KII and FGD guides will be developed in advance, and will vary across the study period, exploring specific topics of concern. A locally validated, seven-domain framework of healthcare delivery analysis will be used to inform data collection. [85] These seven domains include health service operations, supply chains, equipment, personnel, outreach, societal factors, and structural factors. Qualitative data collection will focus on these areas to assess the implementation of the intervention.
FGDs and KIIs will occur prior to the initiation of the intervention, and in intervals of six months throughout the study period, to assess on-going implementation status.
All sessions will be conducted in Nepali. All qualitative data will be stored on a Research Electronic Data Capture (REDCap) database. [86] REDCap user access will be defined so that researchers only have access to de-identified study data. Any paper copies of data forms will be stored in locked cabinets inside locked rooms at district facilities. Once all data are fully transcribed and validated for quality, all paper copies will be destroyed. REDCap data will be deleted twelve months after the completion of the study period.

Data analysis
Analysis for Specific Aim 1: effectiveness In order to assess the effectiveness of the intervention, as described above, the primary outcome will utilize disease-specific "at goal" metrics for each of the three study diseases: hypertension, type II diabetes, and COPD. We hypothesize that the integrated intervention will lead to a 10% increase in the "at goal" status of the combined disease cohorts, over a twelve-month follow up period.
We will use conditional multivariable logistic regression to assess patient outcomes at 12 months follow up, adjusting for potential confounding and/or effect modification by patients' demographics (including age, sex, caste), municipality, district, mean distance to the hospital, and engagement in care (defined as number of facility-based and community-based encounters). We additionally hypothesize a 10% improvement in the status of each of the two secondary outcomes: tobacco and alcohol use, as measured by patient-reported outcomes in Table 1.
As a secondary analysis for Specific Aim 1, namely the time-varying nature of the outcomes, we will assess the longitudinal effect of the intervention, as measured in three-monthly intervals, throughout the study period, compared to baseline statistics at the time of each village-cluster enrollment. Variables will be considered as either nominal or continuous (linear effect) predictors, and the generalized linear model framework will be used to estimate effect of time-varying repeated measure intervention implementation over the several steps of the wedged design.
Differential impact from time of intervention will be evaluated with test of month × intervention interaction. Models will be fit using generalized estimating equations, e.g., using SAS Proc Genmod, to calculate valid standard errors in the presence of repeated measures over time and possibly correlated outcomes at the municipality level. Assumptions of over-or under-dispersion will be examined closely, and an estimated scale parameter or negative binomial models will be used as needed.

Analysis for Specific Aim 2: RE-AIM implementation framework
In this mixed-methods study, Specific Aim 2 will be assessed using the RE-AIM framework for implementation trials. [80] A full list of metrics, separated by each domain of the RE-AIM framework, is presented in Table 1. Additional details regarding the supervision and audit structure for MLPs and CHWs can be found in Supplemental File 1 and 2.
For the (M)aintenance of the intervention, we will assess the costs of the intervention, using the Joint Learning Network methodology [84]. Cost data will be analyzed and presented (Table 1)  For quantitative data within Specific Aim 2, a similar methodology of generalized estimating equations, as described above in the section on Specific Aim 1 analysis, will be applied. Data will be assessed in three-month intervals.
For qualitative data within Specific Aim 2, analysis will be on-going and iterative, so as to continually inform further qualitative data collection, focusing on timely and relevant implementation issues. Data from KIIs and FGDs will transcribed and coded using Grounded Theory Methodology. [87,88] NVivo software will be used for qualitative data analysis. [89] discussion

Ethical approval and consent
This study has been approved by the Ethical Review Board of the Nepal Health Research Council (#177/2018). Within the study, all patients will provide verbal informed consent to have their de-identified data analyzed and published. Care provision will be unrelated to consent, and there will be no difference in care provision based on consent status. Verbal informed consent will also be provided by all KII and FGD participants. No incentives will be provided to study participants, to avoid any conflict of interest or coercion to participate. Protocol modifications will be promptly communicated to the IRB and on the trial registry website by members of the research study team.

Safety considerations
There are minimal risks posed to patients, staff, or other key informants. The predominant risk is disclosure of protected health information, and/or qualitative data from KIIs or FGDs. All patient information will be stored on secure databases, and data access privileges will be heavily restricted. Unless otherwise deemed necessary for a specific analysis, all analyses will be conducted using a limited dataset. Qualitative data will be stored and protected as described above.

Data sharing
All deidentified data from this study will be made publicly available for other researchers to analyze at their discretion in the future, to further this field of research. Deidentified summaries of qualitative data will be made available as well.

Dissemination plan
Domestically within Nepal, six-monthly update meetings will be held between researchers and the Ministry of Health and Population to review on-going results.
When completed, results of the study will be presented at the annual National provision will be unrelated to consent, and there will be no difference in care provision based on consent status. Verbal informed consent will also be provided by all KII and FGD participants. No incentives will be provided to study participants, to avoid any conflict of interest or coercion to participate.

Consent for publication:
Not applicable.

Availability of data and materials:
The datasets supporting the conclusions of the study will be made publicly available in de-identified form upon conclusion of the study. The final trial dataset (in limited identifier format) will be accessible to researchers at the research performance site in Nepal-Nyaya Health Nepal-and co-investigators assisting with data analysis.
Participating research institutions will enter into data sharing agreements (namely between the research performance site in Nepal-Nyaya Health Nepal-and any foreign institutions where investigators are assisting with data analysis) covering terms of access to specific limited datasets; provisions for storing, sharing, and using data; and methods for securing data transfer.