Rationale, Design and Baseline Characteristics of a Randomized Controlled Trial of a Cardiovascular Quality Improvement Strategy in India: The C-QIP Trial

Abstract

Background:

Quality of chronic care for cardiovascular disease (CVD) remains suboptimal worldwide. The Collaborative Quality ImProvement (C-QIP) trial aims to develop and test the feasibility and clinical effect of a multicomponent strategy among patients with prevalent CVD in India.

Methods:

The C-QIP is a clinic-based, open randomized trial of a multicomponent intervention versus usual care that was locally developed and adapted for use in Indian settings through rigorous formative research guided by Consolidated Framework for Implementation Research (CFIR). The C-QIP intervention consisted of 5 components: 1) electronic health records and decision support system for clinicians, 2) trained non-physician health workers (NPHW), 3) text-message based lifestyle reminders, 4) patient education materials, 5) quarterly audit and feedback reports. Patients with CVD (ischemic heart disease, ischemic stroke, or heart failure) attending outpatient CVD clinics were recruited from September 2022 to September 2023 and were randomized to the intervention or usual care arm for at least 12 months follow-up. The co-primary outcomes are implementation feasibility, fidelity (i.e., dose delivered and dose received), acceptability, adoption and appropriateness, measured at multiple levels: patient, provider and clinic site-level, The secondary outcomes include prescription of guideline directed medical therapy (GDMT) (provider-level), and adherence to prescribed therapy, change in mean blood pressure (BP) and LDL-cholesterol between the intervention and control groups (patient-level). In addition, a trial-based process and economic evaluations will be performed using standard guidelines.

Results:

We recruited 410 socio-demographically diverse patients with CVD from four hospitals in India. Mean (SD) age was 57.5 (11.7) years, and 73.0% were males. Self-reported history of hypertension (48.5%) and diabetes (41.5%) was common. At baseline, mean (SD) BP was 127.9 (18.2)/76.2 (11.6) mm Hg, mean (SD) LDLc: 80.3 (37.3) mg/dl and mean (SD) HbA1c: 6.8% (1.6%). At baseline, the GDMT varied from 62.4% for patients with ischemic heart disease, 48.6% for ischemic stroke and 36.1% for heart failure.

Conclusion:

This study will establish the feasibility of delivering contextually relevant, and evidence-based C-QIP strategy and assess whether it is acceptable to the target populations. The study results will inform a larger scale confirmatory trial of a comprehensive CVD care model in low-resource settings.

Trial registration:

Clinical Trials Registry India: CTRI/2022/04/041847; Clinicaltrials.gov number: NCT05196659

Graphical Abstract

INTRODUCTION

The burden of cardiovascular diseases (CVD) is rapidly increasing, with more than 500 million prevalent cases and 20 million deaths globally [1]. In India, CVD is more prevalent in younger population compared to other regions and represents one quarter of all-cause mortality [2]. Having CVD increases the risk of recurrent myocardial infarction, stroke, heart failure or cardiovascular death at 5 years by 20%−30% as compared to those without CVD [3]. Secondary prevention drugs (e.g., aspirin, beta-blockers, ACE-inhibitors, and statins), and behavioral interventions (e.g., smoking cessation, increasing physical activity, consuming a healthy diet, and managing stress) are effective for reducing premature mortality and morbidity [4, 5]. Lim et al. estimated that nearly half of coronary heart disease and stroke deaths could be avoided in India with the use proven CVD prevention drugs over 10 years [6].

Despite the widely documented benefits of evidence-based treatment for prevention and control of CVD, significant gaps between evidence and implementation persist for even basic pharmacotherapy including aspirin, statin, and antihypertensives [7, 8]. A community-based study in India demonstrated that less than 10% of patients with CVD were taking a combination of aspirin, statins, and antihypertensives [9]. This ‘knowledge translation gap’ is ostensibly due to several barriers to service delivery at health system-, provider- and patient- levels. A 2018 systematic review found that interventions to improve adherence to medications have mostly been complex in nature (transdisciplinary approach, a pharmacist consultation service, and a discharge educational session with materials), which makes adaptation, implementation, scalability, and sustainability difficult in practice [10]. However, low-cost, relatively simple, and innovative quality improvement strategies, such as text messages, team-based care involving non-physician health workers (NPHW), and interactive web-based or mHealth based clinical decision support system may enhance adherence to prescribed therapy and improve clinical outcomes. For example, the SPREAD trial in India (n=806 participants) showed that a community health worker-based intervention in patients with acute coronary syndrome after hospital discharge improved adherence to pharmacotherapy (odds ratio: 2.62, 95% CI: 1.32–5.19) and healthy behaviors, and reduction in systolic blood pressure (4 mmHg) at 1 year [11]. Similarly, the CARRS trial examined the impact of electronic health records and decision support system (EHR-DSS) and care coordinator facilitated care for patients with type 2 diabetes mellitus in South Asia and reported significant benefits in multiple risk factor control (relative risk: 2.24, 95% CI: 1.71 – 2.92) from this approach [12, 13].

Substantial variations exist in the types, implementation, and effectiveness of QI strategies for patients with CVD and particularly limited evidence exists on QI strategies useful to improve chronic care for CVD in developing countries such as India [14]. Further, sub-optimal coordination, care, and funding are barriers to effective translation of trial-based evidence and clinical guidelines for CVD prevention in routine clinical settings. In this paper, we aim to describe the rationale, and design of a randomized controlled trial evaluating a multicomponent quality improvement strategy for chronic care of CVD in India. In addition, we report the baseline characteristics of trial participants. The overarching goal of this trial is to evaluate the effect of a Collaborative Quality ImProvement (C-QIP) strategy on implementation and clinical outcomes among individuals with prevalent CVD in India. More specifically, C-QIP trial tests the hypothesis that among patients with prevalent CVD, the C-QIP strategy will be feasible to implement and will improve the processes of care, and clinical outcomes compared with usual care within hospitals in India.

METHODS

Study design

The C-QIP trial is a multi-site, individual-level randomized (1:1), controlled, parallel group feasibility trial with collection of implementation and effectiveness outcomes to prepare for a larger outcomes-driven hybrid type II effectiveness-implementation trial. The trial aims to demonstrate feasibility and clinical effect of a multicomponent strategy versus usual care on prescription of guideline directed medical therapy (GDMT), adherence to prescribed therapy, cardiovascular risk factor control, health-related quality of life, and costs (Figure 1). The trial is being conducted following Standards for Reporting Implementation Studies (StaRI) guidelines [15].

Figure 1.

Study design schematic.

Abbreviations: CVD=cardiovascular disease, NPHW=non-physician health worker, VITA=visual tool for medication adherence, BP=blood pressure, HR=heart rate, FBG=fasting blood glucose, HbA1c=glycated hemoglobin, BMI=body mass index, TC=total cholesterol, HDL=high density lipoprotein, LDL=low density lipoprotein, TG=triglyceride

Study setting and participants

The C-QIP trial is conducted at a diverse mix of four hospitals (2 public and 2 private) located in Delhi (northern state) and Karnataka (southern state) in India. The lead physicians of these sites participated in formative research to develop the C-QIP strategy, as well as an expert consultation meeting to co-design the C-QIP strategy for chronic care of CVD patients in the Indian context [16, 17].

Patients with confirmed diagnosis of CVD including ischemic heart disease, ischemic stroke, or heart failure regardless of ejection fraction were eligible for the study. We specifically focused on improving care for three most common forms of CVD (ischemic heart disease, stroke, heart failure) seen in most ambulatory care settings, including in India, with previously identified gaps in care and considering the core underlying principles of secondary prevention of CVD[4, 18]. Inclusion criteria included patients aged ≥18 years, both sexes, living within same city/town as one of the sites, with established diagnosis of CVD (ischemic heart disease, ischemic stroke or heart failure irrespective of ejection fraction) and willing to provide consent for study participation. However, pregnant, or breastfeeding women and patients having diseases associated with frequent hospitalization (e.g., advanced cancer, end stage renal disease), bedridden or debilitating conditions, or life expectancy <12 months that might limit completion of study follow-up were excluded from the study.

Intervention

A multicomponent and multilevel collaborative quality improvement (C-QIP) strategy was developed using a co-design approach by bringing multiple stakeholders (patients living with heart disease, caregivers, non-physician health workers (nurses, pharmacists), physicians, cardiologists, healthcare administrators, and policy makers) on a common platform (i.e., participatory research method). The co-design process and formative research involved i) a systematic scoping review of published literature[14], ii) qualitative interviews with patients, caregivers, providers, healthcare administrators, and policy makers [17], and iii) a modified Delphi survey among experts practicing cardiology or related fields of medicine[16]. The formative qualitative research and Delphi study findings that informed the development of the intervention strategy have been published previously[16]. Briefly, the scoping review examined 456 studies from 45 countries that used 186 unique interventions to improve outcomes in patients with CVD [14]. Qualitative interviews were conducted with 71 key stakeholders (including providers, patients, caregivers, and health administrators) that highlighted unique challenges and facilitators of implementing CVD quality improvement strategies [17]. A modified Delphi survey was conducted to identify and prioritize the cardiovascular quality improvement strategies in the Indian context considering three domains of priority, relative advantage, and implementation feasibility [16]. Further, in November 2020, a virtual expert consultation meeting was held with national experts in public health, health systems, academics (e.g., CVD and implementation research), government representatives, and clinicians to finalize the components of collaborative quality improvement (C-QIP) intervention. Based on data emerging from the scoping review results, qualitative interviews with diverse stakeholders, and expert recommendations, the evidence-based C-QIP strategy was developed, including five components - 1) electronic health record – decision support system (EHR-DSS) based on most recent evidence based CVD management guidelines for health care workers, 2) non-physician health workers (NPHW) facilitated care for patients with CVD, 3) text-message based reminders for patients to promote healthy behaviors and regular clinic visit attendance and laboratory testing, 4) patient diary with visual assessment tool for adherence to medications and reinforcement tool for lifestyle modifications, and, 5) quarterly audit and feedback reports for study site teams. Figure 2 includes a schematic of the C-QIP intervention components.

Figure 2.

C-QIP multicomponent strategy: Intervention flow.

Abbreviations: EHR=Electronic health records, DSS=decision support system, VITA=visual tool for medication adherence

1. Electronic health record – decision support system (EHR-DSS)

A clinical decision-support system (DSS) was developed for all four participating clinic sites. The cDSS component designed as a standalone tool was embedded within the electronic health record (EHR) developed specifically for this study and implemented across the four participating sites. The EHR component stores patient information, integrating all laboratory and consultation reports in a central online location. The DSS component provides automated decision-support prompts of guideline-recommended care tailored to each patient’s CVD condition, risk level, and adherence to medications. The CVD management plan provides instructions for treatment regimens for CVD risk factor control, including processes of care for antiplatelet therapy and blood pressure and lipid control (e.g., aspirin, ACE-inhibitor, beta-blocker, and statin use) as well as simple lifestyle advice according to the participant’s status. The algorithm and guidelines for CVD management were developed by C-QIP team, following current internationally accepted evidence, with contextual adaptations to increase relevance to the Indian population (see online supplement). The EHR-DSS is co-managed by the site physicians and NPHW. The NPHW is primarily tasked for data entry of patient demographics, medical history, medications, and clinical complaints. The site physician is responsible to review the computer generated DSS prompts (CVD management plan) and make appropriate modifications to the treatment plan and medications prescription.

2. Non-physician health worker facilitated care

One non-physician health worker (NPHW) was designated as the cardiovascular care coordinator for each clinic site for the study duration. NPHWs were from allied health fields such as nursing, social work, nutrition or had work experience in community health care. The NPHW manages all 50 participants randomized to the intervention arm and assists the physician to devise a patient-tailored CVD care plan based on patient’s CVD risk factor levels, adherence, and motivation. He/she further facilitates treatment, referral, follow-up, and investigation appointments including reminders to support the patient’s care plan. He/she encourages and motivates intervention arm participants to better self-manage risk factors (by providing the appropriate guidance and tools), promote healthier lifestyle choices (e.g., physical activity, diet, smoking cessation) and treatment adherence. NPHWs were trained on-site by the research coordinating center (RCC) team at the start of the trial over 3 days using a standardized training manual with pre- and post-training assessment of knowledge. The RCC team routinely monitors study progress and quality of care delivered by the physician-NPHW team and conducts retraining in case of staff turnover. Further, one day refresher training is planned annually. Further details on the NPHW training are provided in the online supplement.

3. Text-messages for healthy lifestyle

Participants randomized to the intervention arm receive text-messages for behavioral modifications (e.g., diet, physical activity, smoking/tobacco cessation, and alcohol quitting), for improving adherence to prescribed therapy, and for reminders for the next clinic visit or lab tests. The text-messages are tailored based on patient’s lifestyle habits. For example, smoking cessation and alcohol quitting messages are only sent to those patients who self-reported smoking or alcohol use at baseline visit. Text messages are sent automatically using EHR-DSS and in local languages (Hindi or Kannada) as preferred by the participant (see online supplement for sample text messages).

4. Patient diary

Participants randomized to the intervention arm received a diary that contains a visual assessment tool for medication adherence (VITA) [11] and reinforcement tool for behavioral strategies and for setting risk factor control goals (e.g., weight management, blood pressure, blood cholesterol and blood glucose control). NPHW provide instructions to the intervention arm participants to use the patient diary effectively, document the goals, and track these on monthly or quarterly basis as per the participant care plan (a sample of VITA tool is provided in the online supplement).

5. Audit and feedback report

The audit and feedback report are shared with all participating site investigators on quarterly basis to demonstrate the performance of their clinic site in terms of managing intervention arm participants against the benchmark set by the American College of Cardiology (ACC) to effectively manage patients with established CVD and for secondary prevention of CVD [19, 20]. The audit and feedback report includes intervention arm participants’ profiles and summary estimates of the proportion of participants receiving aspirin, ≥ 2 blood pressure lowering medicines, statins, and glucose lowering medicines (for patients with diabetes) as well as aggregate clinic-level mean systolic and diastolic blood pressure, LDLc and HbA1c values. The report also includes a template of QI Review report to guide the team to plan and implement their site-specific goals (e.g., recruitment, follow-ups, risk factor control, prescription of GDMT); see example of audit report in the online supplement.

Control arm (usual care)

Participants randomized to the control arm received a leaflet (i.e., printed information) on healthy behaviors to prevent recurrent CVD events. This is delivered by a different team member (i.e., not by the designated NPHW) to minimize the risk of contamination. Further, to avoid contamination between the two groups, patients randomized to the intervention group are exclusively managed by a trained cardiovascular care coordinator. Patients in the usual care group are only contacted once in a year by a research assistant before their next scheduled annual study visit. In addition, two participants from the same household were not recruited in the trial because that carried the risk of two individuals going to two different treatment arms. Although the EHR is used to record data of both treatment groups, the EHR has additional DSS features activated only for patients randomized to the intervention arm, which is restricted for view by the trial physicians and cardiovascular care coordinator. For example, when the cardiovascular care coordinator logs in the EHR, option for CDSS becomes available and functional. Whereas, if anyone else logs in the EHR, CDSS are not available to the Research Assistant responsible for data collection in the control group.

Participant recruitment and randomization

The recruitment goal was 100 participants at each of the four clinic sites for a total sample size of 400 participants. Clinic staff (designated screening officer or site investigator) initially screened for potentially eligible participants from clinical records and outpatient clinics based on inclusion and exclusion criteria. Eligible participants attending the outpatient clinic at the four participating sites were approached and invited to participate and recruited prospectively. Participants were briefed about the study, and if they provided written consent, then they were enrolled and randomly allocated to one of the study groups.

Restricted randomization of variable block size was used for the trial, stratified by the four clinic sites. The block allocation sequence for each site (n=100) was computer-generated centrally at the research coordinating center by allocating 50 participants to the intervention arm and 50 participants to the usual care arm. The randomization allocation was provided to sites using an interactive web response system. Blinding of participants and study personnel was not possible due to the nature of the intervention.

Participants follow up and study assessments

The first clinic visit includes screening, randomization, and baseline assessment including demographics, social/lifestyle habits, clinical measures (i.e., blood pressure, heart rate, weight, body mass index). Further laboratory investigations were performed for fasting blood glucose, glycated hemoglobin, and lipids profile. If serum creatinine, sodium and potassium values were available from the routine examination, these data were also extracted at baseline visit. In addition, validated questionnaires were used for the assessment of self-care, and EQ5D-5L to assess health related quality of life, global health assessment scale for mental health assessment and a validated tool to assess patient’s treatment satisfaction, health service use, and costs of care associated with outpatient and inpatient care.

In the usual care group, participants receive routine care/standard care protocol followed at the participating hospitals without access to the DSS or the trained cardiovascular care coordinator. The clinic visit for the intervention group participants is conducted by a multidisciplinary team including a cardiologist, general medicine doctor or both, and trained non-physician health worker, who is the cardiovascular care coordinator for this trial. For participant randomized to the intervention arm, the site physician reviews CVD management plan, accepts/rejects DSS management prompts, and updates medications and patient management plans accordingly. Participants randomized to the intervention arm are scheduled to have follow-up visits on a 3-monthly basis and more frequently in case of poorly controlled blood pressure (BP: >140/90 mmHg), or high-risk heart failure patients. Intermediate visit assessment for intervention arm participants includes interval history, presenting complaints, self-care measures and lab investigations as prescribed by the physician. All intermediate visits by study participants are documented in the EHR (retrospectively for the control group patients when they attend the annual study visit). The post-randomization follow-up period range from 12 – 24 months (mean 18 months follow-up) depending on participant enrollment in the study. The average follow-up period is 18 months. At annual visit and end of study visit, all participants will be assessed for study outcomes, including interval history, presenting complaints, serious adverse events, BP measures, laboratory investigations, self-care behaviors, quality of life, treatment satisfaction, health service utilization, and costs of care (Table 1).

Table 1.

Schedule of evaluations.

Evaluations/Visits	Screening	Baseline	Intermediate	12-month Follow-up	End of study
Signed informed consent	x
Assess Eligibility	x
Enrolment/Randomization	x
Demographics		x
Medical history		x
Family history		x
Social History (lifestyle/habits)		x	x	x	x
Self-care questions		x		x	x
Quality of Life, short (Global Health Scale))		x		x	x
Treatment Satisfaction questions		x		x	x
Processes of care questions		x		x	x
Costs of care questions		x		x	x
Acceptability: providers and patient interviews		Sub-sample		Sub-sample	Sub-sample
Blood pressure and heart rate		x	x	x	x
Height		x		x	x
Weight, BMI (calculated), Waist Circumference		x		x	x
General Physical Examination		x		x	x
Serum Creatinine		x		x	x
Serum Sodium, Potassium and Liver enzymes		x		x	x
Fasting blood glucose		x	x	x	x
Glycated hemoglobin A1c (HbA1c)		x	x	x	x
Lipids (TC, HDL, LDL, TG)		x	x	x	x
Medications: antiplatelets, blood pressure lowering, and cholesterol lowering medications		x	x	x	x
Serious adverse event reporting		x	x	x	x

Abbreviations: BMI=body mass index, TC=total cholesterol, HDL=high density lipoprotein, LDL=low density lipoprotein, TG=triglyceride

Study outcomes

Since, CQIP is a feasibility trial, the primary outcomes chosen are based on the recommendations of Proctor et. al to assess implementation of an evidence-based practice or strategy[21, 22]. The co-primary implementation outcomes in CQIP trial are: 1) feasibility (extent to which C-QIP strategy is successfully used at four sites, patient recruitment and attrition rates, intervention delivery mode, delivery time, and adaptations), 2) fidelity (adherence to study protocol i.e., dose delivered and dose received), 3) adoption (willingness of providers and patients to use the C-QIP strategy, e.g., DSS prompts review, patient’s compliance to DSS recommended follow-up clinic visits, self-care habits as recommended by physician, use of VITA tool and patient diary), and 4) acceptability from the perspectives of providers and patients (to assess the reaction, attitudes, and skills of the providers and NPHW pre and post training, use of EHR-DSS management plan for the intervention group patients, DSS prompts acceptance, acceptance of patient diary, VITA tool, text-messages for lifestyle modification (Table 2).

Table 2.

C-QIP Trial implementation outcomes, indicators, timepoint, and measurement approach.

Outcomes (Definition)	Indicator(s)	Timepoint	Measurement approach
Feasibility (extent to which C-QIP strategy was successfully implemented)	Rate of recruitment, per month through the recruitment period. Proportion of target participants who were willing to participate and participated, of those who were invited. Representativeness of participants to general patients with CVD at large. Proportion of patients attending follow-up visits (retention rate) No. of participants who drop-out or refused participation during the study period Proportion of participants completing final study assessment Recruitment, training and retention of NPHWs and whether they are able deliver the intervention Time taken to analyse and send quarterly audit reports. Time taken to review audit reports by site physicians and NPHW. Time taken to deliver patient diary, VITA tool and explain text message based reminders schedule for healthy lifestyle	Baseline, and Follow-up visits	Participant screening and enrolment log Study eCRFs Quarterly audit and feedback reports Site monitoring visit Qualitative in-depth interviews with patients, physicians, and NPHWs (to understand recruitment methods, barriers and facilitators to recruitment, participation, usefulness of training, satisfaction with training) Exit interviews with patients and NPHWs to understand reasons for discontinuation.
Fidelity (degree to which C-QIP strategy was delivered as planned)	Proportion of the participant and provider fidelity with all aspects of the intervention strategy, of those who were enrolled. Proportion of participants for whom C-QIP strategy was adapted, of those who were enrolled. Intervention dose delivered vs dose received for all 5 C-QIP strategy components: i) EHRDSS, ii) NPHW facilitated care, iii) text-messages, iv) patient diary + VITA tool, v) audit and feedback report. No. of DSS prompts reviewed, accepted or rejected and subsequent changes in medication prescription. Delivery of intervention by NPHW as per protocol. Adherence to study protocol No. of Audit and Feedback reports sent to sites, reviewed by site teams. No. of text-messages sent to patients and received or seen by patients.	Baseline, and Follow-up visits	Study eCRFs Quarterly audit and feedback reports Site monitoring visit Structured fidelity ratings using Likert scale Assessment of reasons for non-adherence to study protocol Qualitative in-depth interviews with patients, physicians, and NPHWs (reasons for non-fidelity and to understand experience of implementing the C-QIP strategy, barriers, reasons for adaption or withdrawal of intervention.
Adoption (uptake, utilization of C-QIP strategy)	Proportion of target sites, site team members, who were willing to participate, participated, of those who were invited to participate. Proportion of patients who discontinued because of adverse effects, lack of efficacy of those who were enrolled. Use of EHR for data collection Use of DSS prompts. Use of patient diary Use of VITA tool Use of text-messages Use of audit reports Level of engagement and Interaction between Physicians, NPHW and patients (adequacy and impact)	Follow-up visits	Study eCRFs System usability scale (SUS) Quarterly audit and feedback reports Site monitoring visit Cognitive interviews and focus groups with patients, physicians, and NPHWs Contextual needs for the adoption of C-QIP strategy
Acceptability (extent to which providers and patients perceive C-QIP strategy to be agreeable or satisfactory)	Acceptability of combined multi-level C-QIP strategy before and after intervention delivery Acceptance of EHR-DSS prompts by site physicians. Acceptance of audit reports by site team Acceptance of PDSA worksheet by healthcare providers Acceptance of NPHW facilitated care by physicians and patients. Acceptance of patient diary and VITA tool by patients Acceptance of text-messages by patients	Baseline and Follow-up visits	End of study (EOS) acceptability survey Quarterly audit and feedback reports Site monitoring visit Qualitative in-depth interviews with patients, physicians, and NPHWs ease of use, burden, comprehensibility, most/least helpful components, met expectations, intent to continue behaviours and suggestions for improvement
Costs (total costs incurred to design and implement C-QIP strategy from a healthcare system and societal perspectives)	Direct and indirect costs related to the development, implementation and maintenance of C-QIP strategy, Patient costs related to outpatient and inpatient care during the trial Indirect costs (lost productivity) during the trial Willingness to pay for the C-QIP strategy from provider and patient’s perspectives	Study development phase Study implementation phase	Activity-based costing approach Study eCRFs Project budget sheets and administrative data Qualitative interviews with patients, physicians, and NPHWs Willingness to pay survey
Appropriateness (relevance of C-QIP strategy from the providers and patients’ perspectives)	Proportion of providers for whom the C-QIP strategy became routine practice, of those who participated. Proportion of participants with sustained positive outcomes (e.g., BP reduction), of those who were enrolled. Perceived fit, relative advantage, or compatibility of C-QIP strategy at the participating sites. NPHW training outcomes (post-training change in knowledge and core skills) Integration of C-QIP strategy in the normal clinical workflow of the four participating hospitals Integration and usefulness of text-message based reminders, patient-diary and VITA tools in improving patient self-care goals	Baseline Follow-up visits	End of study (EOS) survey Quarterly audit and feedback reports Knowledge test after training; observer ratings of NPHWs skill acquisition Qualitative in-depth interviews with patients, physicians, and NPHWs to understand discontinuation, modification or sustainability of C-QIP strategy and reasons for these. Nomad and CSAT Patient diary + VITA tool

^*Success measure for feasibility of implementation will be considered at a threshold of an average ≥80% retention of participants randomized to the intervention group across participating sites. Likewise, fidelity will be measured by ≥80% delivery of C-QIP intervention components as per trial protocol, and ≥80% acceptability of C-QIP strategy by key stakeholders (site physicians, NPHWs, and intervention arm patients) across all four sites.

DSS=decision support system; NPHW=non-physician health worker; VITA=visual tool for medication adherence; eCRFs=electronic case report forms; EOS=end of study; PDSA=plan do study act; Nomad=normalization measure development questionnaire; CSAT=clinical sustainability assessment tool; SUS=system usability scale

Previous feasibility trials have specified subjective thresholds a priori such as achieving a retention rate of at least 80%. The National Center for Complementary and Alternative Medicine (NCCIH) guidelines, suggest adherence benchmarks such as at least 70% of participants retention in each arm per scheduled group sessions would be necessary to demonstrate feasibility[23]. Thus, the threshold for feasibility, fidelity, and acceptability of C-QIP strategy is hypothesized to be at least 80% during the trial duration. Our prespecified threshold of 80% fidelity, feasibility and acceptability or adoption was guided by the previous results of the quality improvement trials for cardiovascular risk reduction in India such as the CARRS Trial, mWELLCARE trial, and mPOWER heart study [13, 24, 25]. Further, results of this feasibility trial will set the benchmarks and thresholds for implementation outcomes and inform a future larger outcomes-driven trial of hybrid type 2 effectiveness- implementation trial. A questionnaire with a combination of closed and open-ended questions will be provided to each intervention group participant and care provider to gather their views of the C-QIP strategy at the end of study. Likert scales will be used to explore levels of agreement with different statements on acceptability of different aspects of the C-QIP strategy. In addition to these outcome, the RE-AIM framework will be used as an evaluation framework to assess the implementation outcomes of the C-QIP strategy in terms of – Reach (who is exposed to intervention and benefitted); Effectiveness (what are the benefits of the intervention); Adoption (where is the intervention implemented and who did implement it), Implementation (how is the intervention implemented, how is the implementation adapted by the implementers) and Maintenance (how much is the implementation cost)

Secondary outcomes include processes of care measures (e.g., prescription of GDMT, and patient’s adherence to prescribed therapy), and measures of clinical impact, including mean changes in BP, LDLc, and HbA1c, adherence to healthy behaviors as recommend by the physician e.g., adherence to diet plan, adherence to recommended goals for physical activity and tobacco cessation for those reported to smoking or chewing tobacco at baseline. The GDMT for ischemic heart disease is defined as use of “antiplatelet drug + lipid lowering drug (statin) + ≥ 2 BP lowering drugs”. The GDMT for ischemic stroke is defined as use of “antiplatelet + lipid lowering drug (statin) + ACEi or ARB / Diuretic” and for heart failure patients, use of “ACEi/ARNI + Beta blocker + MRA + SGLT2i. In addition, mean changes in health-related quality of life using EQ5D-VAS and mental health (assessed using Global Health scale) and cost of care will be reported between the intervention and control group participants.

Process evaluation

The process evaluation of the C-QIP trial will be guided by RE-AIM [26] and Consolidated Framework for Implementation Research (CFIR) [27]. The RE-AIM will be used as an evaluation framework to assess the implementation outcomes of the C-QIP trial in terms of – Reach, Effectiveness, Adoption, Implementation and Maintenance. The CFIR will be used as an explanatory framework to understand the determinants influencing the RE-AIM dimensions and ‘why and how’ the implementation process led to certain results (see online supplement eTable 2 for indicators selected to inform process evaluation based on RE-AIM and CFIR constructs).

Semi-structured interviews will be conducted with providers directly involved in the implementation process to explore their acceptability, barriers, and enablers of delivering the intervention. In addition, in-depth interviews with patients will be conducted to explore their experience of taking part in the study (both groups). Purposive sampling will be utilized to ensure diversity (by age, sex, comorbidities, socio-economic status, and location) within the trial population. All interviews will be transcribed (verbatim), translated, anonymized, and checked for accuracy. An interpretive thematic analysis will be conducted using MAXQDA software. In addition, explanatory sequential analyses to explore and explain variability in implementation across patient (age, sex), study personnel (physician, care coordinator), and site levels (public and private).

Economic evaluation

International standard guidelines will be followed to conduct the economic evaluation. The capital and recurring cost of delivering the C-QIP strategy will be costed using the activity-based costing method [salaries of NPHW, cost of training, cost of patient record system, for educational materials, and overhead costs (facility and administration) minus costs attributable only to research activities e.g., salaries of research assistant]. In addition, health expenditures associated with outpatient and inpatient care (direct and indirect costs associated with productivity loss) will be estimated from healthcare and societal perspective. Considering that the C-QIP trial is being conducted at public and private hospitals, we will adopt a multi-payer perspective and healthcare system perspective to account for differences in the healthcare costs incurred in public and private sector[28, 29]. The multi-payer perspective is particularly useful in LMIC settings with a high heterogeneity of payers and comprises costs borne by health care providers, private health insurance as well as out-of-pocket expenditures by patients. The cost of care from patient perspective will collect resource use data related to medications and therapeutic procedures, medical supplies, diagnostic tests other than laboratory tests covered by study, travel, routine clinic visits (outside the study), emergency room visits, and hospitalizations -- research staff at each clinic site will take detailed information regarding hospitalization including duration of stay, procedures, diagnostics, and will seek consent from the participant to obtain a copy of the discharge summary for each hospital admission. In addition, we will estimate the indirect costs associated with productivity loss, and wage/income loss. A willingness to pay survey will also be conducted at the end of study by interviewing patients and physicians participating in the trial regarding their perceived value of the C-QIP strategy. In addition, we will incorporate qualitative data to provide competing beliefs and perceptions from patients, caregivers, providers, and health administrators about the economic factors that may impede/facilitate long-term sustainability of the C-QIP strategy.

Sample size calculation and statistical analysis

The C-QIP feasibility trial primary objectives are to address whether data collection protocols are feasible, intervention fidelity is maintained, and participant adherence and retention are achieved. As per the guidelines for conducting feasibility trials from the National Center for Complementary and Integrative Health (NCCIH), National Institutes of Health, US, feasibility indicators include participant completion rates and times for specific components, perceived burden and reasons for noncompletion. Furthermore, feasibility issues include obtaining permission from participating sites, demonstrating access and capability to merge data across sources. For quantitative studies, a sample of 30 per group (intervention and control) is recommended to establish feasibility[23]. However, to estimate parameters such as proportions within treatment groups, adherence to an intervention strategy or correlations among variables and confidence intervals (CIs), a sample size of 70–100 per group is adequate. Previous systematic review of sample sizes for feasibility trials using data of the WHO International Standard Randomized Controlled Trial Number (ISRCTN) registry from 2013 to 2020 showed the median sample size was 30 (IQR 20–50)[30], another review from the UK Clinical Research Network (UKCRN) found mean sample size of 36 participants per arm (range: 10 to 300 participants)[31]. In this C-QIP feasibility trial our goal is to examine the CI around feasibility process outcomes such as acceptance rates, adherence rates, proportion of eligible participants who are consented or who agree to be randomized and secondary clinical outcomes such as prescription of guidelines directed medical therapy, adherence to prescribed therapy and changes in mean blood pressure at the end of the trial, thus, a sample size of at least 70 per arm is adequate, depending on the point estimate and CI width. Thus, we proposed to recruit 100 participants per site (taking into account 10% drop-out rate), and selected 2 public and 2 private outpatient CVD clinics to demonstrate the feasibility outcomes in Indian context.

The overall target sample size estimated for this feasibility trial was 400 patients randomized from four CVD clinics (100 patients per clinic). The intervention implementation outcomes such as feasibility, acceptability, adoption will consider multi-level analysis, i.e., patient, provider, and clinic site-level factors. The primary analyses for secondary outcomes such as prescription of medications (provider-level), adherence to prescribed treatment, mean changes in blood pressure and blood lipids (patient-level) will be conducted with the intention to treat principle. Being a feasibility study, the trial is not designed to be adequately powered to detect a difference in clinical outcomes between the two study arms. However, appropriate regression methods will be used to evaluate potential efficacy of the intervention. Effect sizes will be presented as risk ratios for binary outcomes, and as mean differences for continuous outcomes; 95% confidence intervals will be given for both and p value <0.05 will be considered for statistical significance. Data analysis will be performed using STATA 18.0. Additionally, using mixed-methods analysis (combining quantitative trial data and qualitative process evaluation interview data) and data triangulation, we will report heterogeneity in intervention effects and implementation across participants sites due to differential acceptability or adoption of different components of C-QIP strategy across sites, major patient sub-groups (by age, sex, and comorbidities) and provider type. However, we will not be able to estimate the treatment effect or benefits of single intervention components.

Ethics

The trial protocol and patient information sheet-informed consent document were reviewed and approved by the institutional ethics committee of the Public Health Foundation of India (TRC-IEC-382.2/18) and Health Ministry Screening Committee in India (2018–0491). All participating sites have also obtained local ethics committee approval. Participation in this study is voluntary, and a signed consent form was obtained from each trial participant.

Funding

This study is supported by the Fogarty International Centre, National Institutes of Health (NIH), United States (grant award: 1K43TW011164). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the paper and its final contents.

RESULTS

Baseline characteristics of study participants

The C-QIP trial began recruitment in September 2022 and completed target recruitment in September 2023. A total of 410 participants were randomized over 12 months (n=205 participants randomized to each group: usual care and intervention group) and 9 patients dropped out at baseline visit. We present the baseline characteristics of 401 trial participants with complete baseline data, overall and stratified by public and private hospitals, are shown in Table 3. Trial participants were middle-aged (mean (SD) age: 57.5 (SD) years) and predominantly males (73.1%). Two-thirds of participants had prior coronary heart disease (74.6%), followed by ischemic stroke (18.5%) and heart failure (18.0%). Nearly half of the participants reported a history of either hypertension (48.4%) or diabetes (41.6%), and one-third (27.7%) had both conditions. At baseline, mean (SD) BP was 127.8/76.2 (18.2/11.6) mmHg, mean (SD) LDL-cholesterol: 80.4 (37.2) mg/dL, and mean (SD) HbA1c: 6.8% (1.6%). At baseline, the GDMT was 62.4% for patients with coronary heart disease, 48.6% for ischemic stroke and 36.1% for heart failure. Most participants (91%) self-reported taking medications as prescribed by the doctor.

Table 3:

Baseline characteristics of trial participants.

	All participants (N=401)	Public Hospitals (n=181)	Private Hospitals (n=220)
Age (years; mean, SD)	57.5 (11.7)	54.7 (10.9)	59.8 (11.8)
Male, n (%)	293 (73.1%)	139 (76.8%)	154 (70.0%)
Education (years; mean, SD)	10.7 (5.5)	8.2 (5.4)	12.8 (4.7)
Household Income (monthly) Indian rupees, mean (SD)	24248.1 (19162.3)	27339.8 (24409.3)	21704.6 (12906.0)
Laboratory Parameters
Systolic BP (mm Hg; mean, SD)	127.8 (18.2)	126.5 (20.8)	128.9 (15.8)
Diastolic BP (mm Hg; mean, SD)	76.2 (11.6)	76.0 (12.6)	76.5 (10.7)
Total cholesterol (mg/dL; mean, SD)	144.6 (44.0)	140.2 (41.1)	148.1 (45.9)
LDLc (mg/dL; mean, SD)	80.4 (37.2)	69.2 (31.6)	89.4 (39.0)
FBG (mg/dL; mean, SD)	122.2 (54.9)	117.6 (52.4)	128.2 (57.8)
HbA1c (%; mean, SD)	6.8 (1.6)	6.5 (1.4)	7.0 (1.7)
Medical history
Coronary Heart Disease, n (%)	299 (74.6%)	161 (89.0%)	138 (62.7%)
Myocardial Infarction, n (%)	127 (31.7%)	90 (49.7%)	37 (16.8%)
Heart failure, n (%)	72 (18.0%)	32 (17.7%)	40 (18.2%)
Ischemic stroke, n (%)	74 (18.5%)	1 (0.6%)	73 (33.2%)
Hypertension, n (%)	194 (48.4%)	51 (28.2%)	143 (65.0%)
Diabetes, n (%)	167 (41.6%)	69 (38.1%)	98 (44.5%)
Hypertension and Diabetes, n (%)	111 (27.7%)	34 (18.8%)	77 (35.0%)
Medications at baseline visit
Antiplatelet	353 (88.0%)	158 (87.3%)	195 (88.6%)
Lipid lowering (Statin)	345 (86.0%)	155 (85.6%)	190 (86.4%)
ACEi/ARB	238 (59.4%)	135 (74.6%)	103 (46.8%)
ARNI	38 (9.5%)	17 (9.4%)	21 (9.5%)
Beta-blockers	284 (70.8%)	165 (91.2%)	119 (54.1%)
CCBs	71 (17.7%)	21 (11.6%)	50 (22.7%)
Diuretics	166 (41.5%)	92 (50.8%)	74 (33.6%)
Participants with Coronary Heart Disease	N=295	N=158	N=137
Antiplatelet + Lipid lowering drug (statin) + ≥ 2 anti-hypertensive drugs	184 (62.4%)	124 (78.5%)	60 (43.8%)
Antiplatelet + Lipid lowering drug (statin) + ACEi or ARB + Beta Blocker	134 (45.4%)	103 (65.2%)	31 (22.6%)
Participants with Ischemic stroke	N=74	N=2	N=72
Antiplatelet + Lipid lowering drug (statin)	55 (74.3%)	2 (100%)	53 (73.6%)
Antiplatelet + Lipid lowering drug (statin) + ACEi or ARB / Diuretic	36 (48.6%)	2 (100%)	34 (47.2%)
Antiplatelet + Lipid lowering drug (statin) + ≥ 2 anti-hypertensive drugs	26 (35.1%)	2 (100%)	24 (33.3%)
Participants with Heart failure	N=72	N=32	N=40
ACEi / ARNI + Beta blocker + MRA	26 (36.1%)	19 (59.4%)	7 (17.5%)
ACEi/ARNI + Beta blocker + MRA + SGLT2i	17 (23.6%)	14 (43.8%)	3 (7.5%)
Participants forgot to take medicines in last one month, n (%)	59 (14.8%)	38 (21.0%)	21 (9.6%)
Participants stopped medication on his/her own, n (%)	19 (4.8%)	14 (7.7%)	5 (2.3%)

Abbreviations: C-QIP=Collaborative Quality ImProvement trial, SD=standard deviation, BP=blood pressure, FBG=fasting blood glucose, HbA1c=glycated hemoglobin, LDLc=low density lipoprotein cholesterol, ACEi=Angiotensin-converting-enzyme inhibitors, ARB=Angiotensin receptor blockers, ARNI=Angiotensin receptor-neprilysin inhibitor, CCB=Calcium channel blockers, MRA=Mineralocorticoid receptor antagonist

All randomized participants will be followed-up for an average of 18 months and the final study visits completion are expected by October 2024.

DISCUSSION

The C-QIP trial tests the feasibility of implementation, and preliminary effect of a multicomponent strategy on processes of care and risk factors, in comparison to usual care, among patients with CVD in India. Implementation outcomes will be evaluated using a mixed-methods approach guided by RE-AIM and CFIR. The self-reported adherence to medications is objectively evaluated by measurements of within-trial changes in blood pressure and cholesterol. The C-QIP trial completed recruitment on schedule (within 12 months), despite the challenges posed by the COVID-19 pandemic during the overall study period. Participants’ baseline characteristics are much as expected in a cohort with recognized and treated cardiovascular risk factors[11, 32, 33]. The younger age of the participants in India is in keeping with the observation that CVD afflicts people at a younger age in low- and middle-income countries.

Adherence to evidence-based CVD treatment diminishes in the long-term due to myriad factors such as greater pill burden, clinical inertia, complexity of care and higher treatment costs. Reduced adherence does relate to increased cardiovascular risks. The evidence-based treatment for CVD could be best delivered using a multicomponent strategy addressing barriers to care at the health system, provider, and patient-levels, but there is an important outstanding question: Will patients and healthcare providers adopt such a strategy; will they really use a strategy comprising of decision-supported electronic health records, non-physician health workers, text-messages, audit and feedback and patient education materials including reinforcement tools and VITA tools? The C-QIP trial seeks to address these implementation research questions using a type 1 hybrid implementation trial.

Challenges in developing and implementing the C-QIP strategy

Co-designing and implementing CVD DSS management prompts based on the most recent CVD treatment algorithm and guidelines required numerous iterations of testing between the study and software design teams. With feedback from site physicians, the EHR-DSS was calibrated to provide general CVD management prompts for blood pressure, blood cholesterol and blood glucose control among patients with either ischemic heart disease, ischemic stroke, or heart failure but with enough discretion for physicians to personalize care for individual patients. Clinic site teams and patients were also involved in integrating the care coordination/EHR-DSS functions in their local hospital setting and clinical workflow (e.g., timing, location, use of laptop vs electronic tablets vs printing DSS prompts for physician review). The involvement of local clinic staff facilitated incorporation of the intervention into each clinic’s existing setup, without major system overhaul or neglecting the need for patient-centered care. The key roles and responsibilities of the cardiovascular care coordinator remain the same across the four participating sites, though the educational qualifications of each cardiovascular coordinator varied due to study personnel availability.

Based on the C-QIP trial experience, the individual components of the intervention such as clinical DSS, NPHW, text-message based reminders for health lifestyle, audit and feedback reports and patient education materials will require contextual customization before widespread adoption or implementation. From challenges in infrastructure or digitalization (e.g., clinics may not have reliable internet/computer access) to difficulties in recruitment or availability of clinic resources (e.g., clinic staff, investigators, nurses), we observed that involving local clinic site staff early on was helpful to integrate the quality improvement strategy into contextual norms and help identify workarounds to the challenges presented.

Currently, the utilization of EHR in India is significantly lower compared to developed countries, and the use of cDSS is even lower. However, the penetration of EHR in India has increased, particularly post COVID-19 pandemic with recently launched national operational guidelines and standards regarding EHR use, data ownership and interoperability [34]. The new initiative by the National Health Authority, Government of India, “Ayushman Bharat Digital Mission”, is designed to bridge the existing gaps among different stakeholders and facilitate the creation of infrastructure to support the adoption of digital healthcare platforms among healthcare providers. In addition, new operational guidelines on non-communicable diseases by the Ministry of Health and Family Welfare, Government of India, advocate the implementation of cDSS in healthcare settings. Further, the Indian government has launched two important initiatives: national telemedicine service (eSanjeevani, [35]) and NCD Portal in India [36], with impressive nation-wide reach through government health facilities. Both initiatives offer huge implications for future integration of cDSS designed in the C-QIP trial for the next phase expansion, if found to be successful in improving chronic CVD care quality. This trial seeks to allow NPHWs to work at the top of their scope of practice and minimize other clinic resource use. We aim to create a toolkit for chronic care of CVD that can be translated (i.e., produce generalizable knowledge) and implemented in other settings with minimal influence of the research specific resources, staff, and external funding.

Previously, clinic-based intervention using a trained nurse practitioner in the EUROACTION cluster randomized trial in patients with prior coronary heart disease showed a reduction in smoking (10.4%, p=0.06) and greater use of statins in the intervention group (6.0%, p=0.04) at 12 months [37]. The COACH trial among 525 patients with CVD, type 2 diabetes, hypercholesterolemia, or hypertension evaluating a nurse practitioner/health worker-based intervention, demonstrated improved risk factors and quality of life at one year [38]. The ProActive Heart trial involving 430 patients with myocardial infarction using telephone-based reminders showed no change in health status compared to usual care, and reported that the cost of these interventions were high [39]. Recently, the BETTER CARE-HF trial involving 2,211 patients with heart failure demonstrated increased prescription of GDMT (MRAs) with the use of an automated, patient-specific, electronic health record-embedded alert compared to the message (relative risk: 1.67; 95% CI: 1.21–2.29; P = 0.002) and usual care (relative risk: 2.53; 95% CI: 1.77–3.62; P < 0.0001)[40]. Furthermore, EXTRA-CVD trial in Africa involving 297 people with HIV showed significantly lowered BP and non-HDL-c with the implementation of a multicomponent nurse-led strategy for CVD risk reduction in primary care settings [41]. In the Indian context, SPREAD trial demonstrated the effectiveness of using a training community health worker and patient education materials on improvement on medication adherence and CVD risk factor control[11]. A recent cluster randomized trial of a coordinated, multifaceted intervention of assessment, education, and feedback vs usual care in 1049 patients with atherosclerotic CVD and type 2 diabetes, increased prescription of evidence-based therapies in high income settings of the United States [42].

However, there are no published implementation trials of a comprehensive package of multifactorial intervention for chronic care of CVD in South Asia. For these reasons, we sought to comprehensively assess a multicomponent intervention tailored to chronic care of CVD in Indian context. The C-QIP trial introduced and combines several features to enable providers and empower self-care among patients with CVD. If successful in achieving its primary outcome, then the trial will provide high quality evidence for implementation of this approach more broadly throughout India and potentially other LMICs. Data from the study’s process evaluation will provide critical insights into what site- and personnel-level factors are necessary for successful implementation of C-QIP intervention. The study team is also exploring potential funding models (e.g., partnership or subscription model, provider incentives or performance-based financing) and automation of data management, and real-time data monitoring not only to maintain financial support for these activities but also to minimize costs to achieve long-term sustainability.

The C-QIP trial has some strengths and limitations. First, the multicomponent strategy focuses on empowering patients to self-care (using VITA tool and text-message based reminders), enables healthcare teams to provide evidence-based treatment and creates opportunity for standardized care across public and private hospitals with EHR-DSS tool co-designed and adapted for local context. Trial sites comprised of a diverse mix of public and private hospitals from two different regions in India. Training manuals and intervention tools were developed with input from site staff that would use them. While a cluster randomized trial design was an alternative that the study team considered, we used the individual patient randomized design for logistical reasons. This may result in some contamination of intervention. Learning from our previous experience of implementing a similar trial in diabetes patients in India[13], we have designed the trial to avoid contamination by minimizing the chance of any contact with the NPHW (cardiovascular care coordinator) and patients in the control group, however, the possibility of some contamination occurring cannot be ruled out, which highlights an important limitation of this feasibility randomized trial. On the other hand, there is the potential for a Hawthorne effect favoring the control group in the trial; because the intervention is unblinded, the physicians may, consciously or otherwise, improve the levels of usual care. Further, the C-QIP strategy combines several evidence-based components to provide a comprehensive CVD care in Indian context. It is therefore not possible to assess the isolated impact of each component on outcomes, although we will attempt to do mediation and moderation analysis to ascertain the effect of intervention components. This study is not powered to show an effect on clinical outcomes and therefore, future studies in this area must employ a large confirmatory randomized trial design across India with longer term follow-ups to evaluate the impact of C-QIP strategy on clinical endpoints.

In summary, the C-QIP trial is a pragmatic implementation study evaluating a contextually relevant, evidence-based strategy and has the potential to bring effective and comprehensive CVD care within the economic reach of patients and providers in India. This is now a high priority in developing countries such as India where disproportionately greater CVD burden lies, yet majority of patients with CVD receive limited long-term preventive care and, even when its available, it often remains unaffordable and of sub-optimal quality.