Effectiveness of a CDSS and Internet of Things-based comprehensive hypertension management system in primary health care settings: study protocol for the CATCH Trial

Abstract

Background

Cardiovascular and cerebrovascular diseases are the leading causes of death in the Chinese population, and hypertension is one of the key risk factors. However, the blood pressure control rate of hypertensive patients is low at present. The main factors include the limited capacity of primary care workers and poor self-management among hypertensives. The purpose of this program is to use a clinical decision support system (CDSS) and an Internet of Things-based comprehensive hypertension management system (CATCH) to provide decision support for the diagnosis and treatment of hypertension for primary care clinicians and to improve the standardisation of the diagnosis, monitoring, treatment, and continuous management of hypertension among them.

Methods

This study is a stepped wedge cluster randomised controlled trial conducted in 12 community health centres in the Third People’s Hospital of Longgang District, Shenzhen City, China. All participants who are registered in the community and with systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg at the screening clinic will be asked to participate in the study. The intervention is a CATCH composite of a hypertension auxiliary decision-making module, clinical diagnosis and treatment knowledge education system, and quality control system. All 12 clusters will be divided into 4 clusters and 5 stages according to a randomised method, with each stage lasting 3 months, ensuring that the entire trial will be completed within 12 months.

Discussion

The CATCH trial uses CDSS and IoT to improve hypertension management in primary care. This stepped wedge trial enhances guideline adherence and patient outcomes through remote monitoring and quality control. All centres receive the intervention, ensuring equitable access to it. Results will guide future hypertension strategies.

Trial registration

The trial was registered at the National Medical Research Registration and Record Filing Information System of China in December 2024, was retrospectively registered at the Chinese Clinical Trial Registry (ChiCTR) (Registration number: ChiCTR2500098845) https://www.chictr.org.cn/

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-025-09349-w.

Introduction

Background and rationale {6a}

Hypertension is an important modifiable risk factor for cardiovascular and cerebrovascular diseases (CVDs), which are the leading causes of death in China [1]. Shenzhen is a rapidly developing city where the population is relatively younger, but the prevalence of hypertension is generally high. A recent study reported that the age-adjusted prevalence of hypertension among adults in Shenzhen in 1997, 2009, and 2018 was 13.23%, 15.33%, and 19.20%, respectively [2, 3], showing a gradually increasing trend.

The management of hypertension is a critical strategy for mitigating the burden of chronic diseases. “The China’s Medium and Long-term Plan for the Prevention and Treatment of Chronic Diseases (2017–2025)” emphasises that primary health care institutions are the “main battlefield” for blood pressure management. Through basic public health services, two-way referral systems, and the integration of medical and preventive care, comprehensive prevention and control of hypertension, along with efficient management, are achieved [4]. Currently, primary health care workers in China face capacity limitations and personnel shortages, and there are deficiencies in adherence to the guidelines for hypertension management [5]. In addition, patients with hypertension have poor self-management ability, a lack of blood pressure monitoring and an understanding of the importance of self-management [6, 7].

Digital health has become a critical component of modern medical practice, resulting in a wider use of technologies, including telehealth, wearable devices, clinical decision support systems, etc. The effect of digital health on hypertension management was not apparent in previous studies, especially for the long-term effect. Clinical decision support system (CDSS) is characterised by the application of computerised algorithms to generate recommendations to manage hypertension [8–10], which has been trialled in some developed countries and has resulted in promising effectiveness in clinical treatment and chronic disease management [11–13]. To date, CDSS has been used to provide drug recommendations, treatment decisions [13–17], and non-drug intervention prescriptions [14–17], assess cardiovascular risk in the next 10 years [13, 18], generate follow-up plans [16, 17], and identify and diagnose hypertension [19]. At present, the research foundation of CDSS in China is limited and lacks long-term follow-up studies. Very few developed CDSS have been put into practice and completed evaluation in China [20–23]. The CDSS exhibits potential in the management of hypertension at the grassroots level in China. The CATCH developed in this study is composed of three parts. Other than the hypertension auxiliary decision-making module (CDSS), the system also functions with remote blood pressure (BP) monitoring and a quality control system.

This study will use a step-wedge cluster randomised controlled trial design, specifically an implementation trial of a clinical guideline-based decision support system for hypertension treatment. The aim is to assess whether the use of the CATCH would increase the proportion of patients receiving appropriate treatments and improve clinicians’ adherence to guidelines compared with standard clinical care.

Objectives {7}

The objective of the trial is to evaluate the effectiveness of the CATCH in managing the blood pressure of hypertensive residents in the community, thereby improving hypertension management for community residents.

Trial design {8}

The study will conduct a stepped wedge cluster randomised controlled trial in 12 community health centres of the Third People’s Hospital of Longgang District, Shenzhen City, China. All 12 centres will be divided into 4 clusters based on the geographical distribution. Each cluster will be included as the control group and sequentially cross over to the intervention group as the trial progresses. The order of rolling out the clusters is set using computer-generated random numbers. Five stages and a three-month interval will be designed for crossover according to the Essential Public Health Service of hypertension management. This design allows all clusters involved in the trial to receive the intervention by the end of the trial in a randomised order.

Methods: participants, interventions, and outcomes

Study setting {9}

All research physicians and relevant staff will receive face-to-face training on the use of CDSS. A manual book developed by the research team, providing instructions on workflow and operations of the present study, is provided to the research doctors.

Eligibility criteria {10}

Inclusion criteria

1. Age ≥ 35 years.

2. Permanent resident of Shenzhen (residence time ≥ 6 months).

3. Patients with a definite diagnosis of essential hypertension (systolic blood pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg three times on different days, and a secondary cause has been initially excluded).

4. Contracted family doctor in the community health centre participating in this study and regular visits (at least three times standardised follow-up visits were completed from January 1, 2024, to December 31, 2024, including at least 1 outpatient follow-up).

5. Blood pressure was higher than 140/90 mmHg at the last follow-up.

6. Those who sign the informed consent form.

Exclusion criteria

1. Patients are eligible for referral to an upper-level hospital due to uncontrolled blood pressure.

2. Reluctance to take antihypertensive drugs.

3. Intolerance to 2 or more of the 4 antihypertensive drugs, including Angiotensin-Converting Enzyme Inhibitor(ACEI), Angiotensin II Receptor Blocker(ARB), β-receptor blocker, Calcium channel blockers(CCB), Diuretics.

4. Physician diagnosed or patient self-reported chronic kidney disease with eGFR < 60 mL/min·1.73 m² or receiving dialysis.

5. Comorbidities with other physician-diagnosed or patient self-reported serious illnesses, such as malignant tumour and liver insufficiency, etc.

6. Self-reported patients with atrial fibrillation ever diagnosed by a specialist.

7. Being in the acute phase of any disease, or a period of instability.

8. There are cognitive and communication difficulties.

Who will take informed consent? {26a}

Before participation, researchers will provide a clear explanation of the study purpose, procedures, and risks to participants. Written informed consent will be obtained from all participants.

Additional consent provisions for collection and use of participant data and biological specimens {26b}

No biological specimens are collected in this study; no additional consent provision for collection and future use of participant data is included in the informed consent form.

Interventions

Explanation for the choice of comparators {6b}

Participants in the control group will be required to carry out HBPM, but receive the usual clinical diagnosis and treatment, until they are switched to the intervention group.

Intervention description {11a}

Clinical decision support system (CDSS) and Internet of Things-based comprehensive hypertension management system (CATCH)

The CATCH has three technologies: (1) CDSS for scale-up of standardised diagnosis and treatment, as well as guideline compliance among Primary Health Centres (PHCs); (2) IOT (remote BP monitoring device) and patients’ APP to improve BP monitoring and capacity of BP self-management among hypertension patients; (3) Instant quality control system for identifying and correcting improper practice among the PHCs (Fig. 1).

Fig. 1.

Introduction to the functions of the CATCH system

The core function of CATCH is the CDSS component that is developed based on China’s “National Guidelines for the Prevention and Management of Hypertension at the Grassroots Level (2020 Edition)” [24], and the hypertension guidelines of the USA and Europe [25, 26]. The CDSS provides decision support to clinicians in the diagnosis and treatment of hypertension with information on disease key tips, auxiliary examination suggestions, medication safety warnings, referral patient screening, personalised information reminders, and hypertension treatment plan recommendations and treatment support. The education system provides a series of hypertension-related diagnosis and treatment knowledge, and pre-treatment education. The quality control system monitored the diagnosis and treatment behaviours of clinicians by extracting and analysing background data according to the guidelines.

Internet of Things (IoT) blood pressure monitoring

After recruitment, all participants will receive a unified model of an internationally certified upper-arm home blood pressure monitor with a data uploading function. This monitor is operated by the WeChat app and enables patients’ blood pressure monitoring and health education for patients. The participants are required to carry out home blood pressure monitoring (HBPM) during the study. The HBPM will be measured once a week. For each measurement, participants are required to take three BP measures in the daytime and three times in the nighttime with one-minute intervals for each time. The mean value of BP will be calculated and uploaded automatically. Participants who do not reach the targeted blood pressure are required to monitor continuously for at least 5 days a week before the next follow-up appointment, and the mean blood pressure value will be used for the generation of CDSS recommendations.

Criteria for discontinuing or modifying allocated interventions {11b}

Patient will be withdrawn if they withdraw their informed consent, are lost to follow-up, or fail to comply with the protocol.

Strategies to improve adherence to interventions {11c, 11d}

All research institutions have been qualified to carry out the project prior to recruitment. To improve adherence to the study protocol, researchers will explain the entire study protocol to participants before enrollment, ensuring that they understand and are able to comply with the study schedule. After randomisation, researchers will maintain close contact with participants to ensure continuous engagement. Continuous monitoring of HBPM will be conducted throughout the study period to ensure full compliance with quality standards. To facilitate this process, a website has been developed for real-time tracking of study progress and quality assurance, enabling the extraction and systematic review of participant data every two weeks for progress monitoring. The study employs an automated data collection system through a pre-designed structured platform, with quality control mechanisms integrated as a core component of the CDSS. Additionally, regular on-site audits will be conducted to verify physicians’ adherence to study protocols and operational standards.

Outcomes {12}

• Primary outcome: Mean difference of the changes of the systolic blood pressure (SBP) and the diastolic blood pressure (DBP) from the first measurement to the last measurement between intervention and control groups.

• Secondary outcomes: (1) Difference in management rates between intervention and control groups after 12 months; (2) Blood pressure control rates between intervention and control groups after 12 months; (3) The adherence to the guideline rate of hypertension patients.

Participant timeline {13}

There will be five stages of the study, which will last for one year (Fig. 2). In the first stage, baseline data will be collected at the screening outpatient. After recruiting the patients according to the inclusion and exclusion criteria, all participants are in the control group. Information on demographic characteristics, medical history, lifestyle factors, blood pressure, and other physical measures will be collected. In the second stage, group 1 will be rolled over to the intervention group. The participants in the intervention group will receive diagnosis and treatment by the research doctors with antihypertensive recommendations generated from the CDSS. While conventional diagnosis and treatment strategies will continue to be provided, the other community health centres will continue to be in the control group. In stages III to V, group 2, group 3, and group 4 will then cross over to the intervention group, respectively. At Stage V, all community health centres will receive the intervention (Fig. 3).

Fig. 2.

Stepped wedge cluster randomised controlled trial design

Fig. 3.

Schedule of enrolment, interventions, and assessments

Sample size {14}

Sample size estimation was performed based on the systolic blood pressure levels (standard deviation = 15.3 mmHg [11, 22]). The intra-cluster correlation coefficient (ICC) was set as 0.1 [22] with a significance level (α) of 0.05 and a statistical power of 80%. The average difference in systolic blood pressure changes between the intervention group and the control group was assumed to be 5 mmHg.

The sample size calculation was performed using PASS 2021 software. Based on the inclusion and exclusion criteria, 70 eligible hypertensive patients were planned to be recruited from each community health centre, resulting in a total of 840 hypertensive patients to be recruited. Due to the possibility of dropout during the trial, an individual dropout rate of 30% [22, 27] was considered. Therefore, each community health centre finally included 92 patients, resulting in a total of 1100 patients with hypertension.

Recruitment {15}

Participants are hypertensive patients registered in the 12 community health service centres affiliated with the Third People’s Hospital of Longgang District, Shenzhen, China. All communities are in the same district and have similar economic status. To be eligible, each community health service centre should have more than 500 registered hypertensive patients. The inclusion and exclusion criteria for participants as follows were developed prior to the recruitment.

Assignment of interventions: allocation {16a, 16b, 16c}

Twelve community health centres are divided into 4 groups. Random numbers are generated by a computer-based “randomisation software” program that determines the order in which the four groups enter the intervention.

Assignment of interventions: blinding {17a, 17b}

The blinding method could not be used in this study because the significant differences in intervention measures and the dynamics of the study design made it impossible for doctors and patients to complete the study process without their knowledge.

Data collection and management

Plans for assessment and collection of outcomes {18a, 19}

Patient data are collected by the CATCH. Baseline information is collected at the first visit, and information on blood pressure, drug usage, and emerging comorbidities is collected at each follow-up visit (Table 1). Each enrolled participant is required to have a follow-up visit every three months for a total of four times, all of which are entered by a trained physician with baseline and follow-up information in the system. Moreover, the home self-measured blood pressure value of each enrolled patient is automatically passed into the system.

Table 1.

Subject information collection form

Information	Baseline	Routine follow-up	Additional follow-up	Last outpatient follow-up
Informed consent	√
Demographic information	√
Medical history, family history	√
Drug allergies	√
Lifestyle factors	√	√	√	√
Physical examination (blood pressure, heart rate, weight, height, waist circumference, BMI)	√	√	√	√
Home blood pressure monitoring	√	√	√	√
Comorbidities	√	√	√	√
Laboratory tests (blood routine, urine routine, blood biochemistry)	√			√
Electrocardiogram	√			√
Medication adherence	√	√		√
Medications	√	√		√
Prescription for this visit	√	√		√
Record of this referral	√	√		√
Returns		√		√
Feedback on quality control of diagnosis and treatment process (intervention group)		√		√

Statistical methods {20a, 20b, 20c}

The analyses and reporting of the results will follow the Consolidated Standards of Reporting Trials guidelines for cluster-randomised controlled trials [28]. Comparative analyses between the intervention and control groups will be performed using intention-to-treat analysis (ITT). Descriptive analyses will be performed on general demographic characteristics such as gender, age and ethnicity, laboratory test indicators such as routine blood, urine, blood biochemistry, and physical indicators such as body mass index and waist circumference. Measurements will be expressed as $\overline{x}\pm s$ and counts as frequencies or percentages (%).

Due to the cRCT design, a linear mixed effects model with random effects, adjusting for baseline values, possible time trends, and central clustering effects, will be used to assess the difference in the mean change in subjects’ blood pressure from baseline to post CDSS intervention. The mixed model will contain two fixed effects, which are intervention variables and time indicators; the locations and subjects measured multiple times during the five follow-ups will be input into the model as random effects. Estimated intervention effect sizes (risk ratio [RR] for binary outcomes and mean difference in continuous outcomes) will be reported with 95% confidence intervals (CI) and P values. The secondary endpoints of continuous variables will also be analysed by linear mixed-effect model, and the secondary endpoints of categorical variables will be analysed by mixed-effect logistic regression. We will also conduct exploratory analyses of the effects of each primary endpoint and secondary endpoint indicator according to different subgroups, such as age, gender, marital status, literacy, and disease history. Missing data will be addressed using multiple imputation by chained equations (MICE) under the assumption of missing at random (e.g. lifestyle factors including smoking, alcohol consumption, and physical activity). All statistical analyses will be performed using two-sided tests. Results will be considered statistically significant at a P value < 0.05.

Oversight and monitoring {5d, 21a, 23}

The core members of this trial committee, including clinical trial experts and statisticians from the National Clinical Research Center for Cardiovascular Diseases at Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen, will provide advisory support for developing the trial protocol, monitoring data, supervising safety, and reporting adverse events. Periodic research audits will be carried out to ensure the trial’s adherence to the predetermined protocol and active progression. Additionally, the committee will hold at least one meeting per month to ensure the smooth progression of the trial.

Adverse event reporting and harms {22}

Throughout the study period, all adverse events (AEs) and serious adverse events (SAEs) will be closely monitored and documented.

Plans for communicating important protocol amendments to relevant parties (e.g. trial participants, ethical committees) {25}

Any changes to the protocol that could affect the study conduct, participant safety, or outcomes, including alterations to eligibility criteria, outcomes, analyses, or study procedures, will be submitted for review and approval to the Biomedical and Clinical Trial Ethics Committee of Shenzhen Hospital, Fuwai Hospital, Chinese Academy of Medical Sciences before being implemented.

Discussion

This study employs a stepped wedge cluster randomised controlled trial design, integrating clinical decision support systems (CDSS) and Internet of Things (IoT) technology to offer an innovative solution for hypertension management in primary healthcare settings. This design ensures that each participating community health centre ultimately receives the intervention, meeting ethical standards and allowing for the gradual assessment of the intervention’s impact during implementation. The study leverages CDSS and IoT technology to provide guideline-based hypertension management recommendations, enhancing clinicians’ decision-making capabilities and improving patient self-management through remote blood pressure monitoring and education systems. The core of the CATCH system is a CDSS developed based on China’s “National Guidelines for the Prevention and Management of Hypertension at the Grassroots Level (2020 Edition)” as well as hypertension guidelines from the USA and Europe. It offers personalised treatment suggestions based on individual patient characteristics, thereby increasing the precision and effectiveness of treatment.

However, the study has certain limitations. Given the nature of the intervention, a double-blind design was not feasible, as both doctors and patients were aware of the intervention, which could introduce bias. Although the study minimised the potential impact of this bias through objective blood pressure measurements and standardised data collection processes, the relatively short follow-up period of 12 months restricts the assessment of the long-term effects of the intervention, particularly regarding patient adherence and sustained blood pressure control. Additionally, the study was conducted in only 12 community health centres in Longgang District, Shenzhen, with similar economic and social backgrounds, which may limit the generalizability of the results. Future research should validate the intervention in a broader range of regions and populations and conduct longer-term follow-ups to comprehensively evaluate its long-term impact.

Despite these limitations, the design and implementation of this study provide valuable insights for the future dissemination of similar interventions in primary healthcare settings. By optimising the application of CDSS and IoT technology in hypertension management and assessing long-term effects through extended follow-ups, future research can further enhance hypertension management capabilities in primary healthcare and provide robust support for alleviating the disease burden associated with hypertension.

Trial status

Protocol version 4.4 commenced on December 11, 2024. The recruitment will commence in December 2024, and it is expected that all community health centres will complete follow-up by mid-2026.

Abbreviations

CDSS

Clinical decision support system

CATCH

CDSS And Internet of Things Based Comprehensive Hypertension Management System

IoT

Internet of Things

CVDs

Cardiovascular and cerebrovascular diseases

BP

Blood pressure

SBP

Systolic blood pressure

DBP

Diastolic blood pressure

PHCs

Primary health centres

HBPM

Home blood pressure monitoring

Authors’ contributions {31b}

YCL acted as the principal investigator to take responsibility for all aspects of the study. KP, KX, XYL, and YCL designed the study. KX calculated the sample size. KP generated the random allocation sequence. KX and BJL recruited the study participants. BJL and KX wrote the manuscript. YXL, KP, KX, XYL, CXL, YS, GYH, WL, XRC, and ZLN contributed to the manuscript. BJL, LW, CXL, XRC, and ZLN performed daily data monitoring. All authors contributed to critical revisions and approved the final version of the article.

Funding {4}

This work was supported by the Guangdong Basic and Applied Basic Research Foundation (No. 2021A1515220173), the Program for Guangdong Introducing Innovative and Entrepreneurial Teams (NO. 2019ZT08Y481), the National Science and Technology Major Project of the Ministry of Science and Technology of China (No. 2023ZD0503506), the Shenzhen Clinical Research Centre for Cardiovascular Diseases Fund (No. 20220819165348002), the Yong Talent Program of the Academician Fund, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen (No. YS-2020-006), the Shenzhen Science and Technology Program (No. JCYJ20230807150800002), and the National Natural Science Foundation of China (No. 72404283).

Data availability {29, 31a}

Data sharing is not applicable to this article as no datasets were generated or analysed. However, once the datasets generated by the study are fully anonymised and the main findings have been published, they will be made available through an open-access repository

Declarations

Ethics approval and consent to participate {24, 27, 30}

This study adheres to the Declaration of Helsinki and the “Ethical Review of Biomedical Research” guidelines. This study has been reviewed and approved by the Biomedical and Clinical Trial Ethics Committee of Shenzhen Hospital, Fuwai Hospital, Chinese Academy of Medical Sciences [IEC2024BG028(05.2)].

The intervention of the study is a health education and treatment-assisted decision-making system based on China’s current guidelines for the management of hypertension and aimed at primary care physicians; the final medical decision remains with the physician, and there is no risk of adverse effects that may result from clinical treatment measures. Follow-up visits will be part of routine care and carry no additional risk. Participants may choose not to answer any questions during follow-up. Patient data will be encrypted and securely stored. Personal information will remain confidential, and no identifiable data will be reported.

Consent for publication {31c, 32}

Informed consent materials can be obtained from the corresponding author upon request.

Competing interests

The authors declare no competing interests.