Diabetes Treatment in Rural Guatemala
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 89
- 试验地点
- 1
- 主要终点
- Patients meeting their HgbA1c treatment goal
研究概览
简要总结
In this study, the investigators will be using a smartphone application that the investigators developed to guide community health workers through the clinical assessment of patients with diabetes including collection of demographic data and past medical history, assessment of medication history, adherence, and adverse effects, measurement of glycemic control, screening for complications, medication administration and titration, and patient counseling.
详细描述
The burden of chronic adult diseases is surging worldwide, particularly type 2 diabetes, the prevalence of which is expected to double by 2030. The diabetes epidemic will primarily impact developing countries, with 80% of adult cases occurring in low- and middle-income countries (LMICs). Because many LMICs currently face a shortage of health professionals, the increasing burden of noncommunicable diseases, like type 2 diabetes, will tax already strained health systems. Furthermore, because many LMIC health care systems were developed to target acute illnesses and communicable disease, they are ill-prepared to treat and manage chronic adult disease. The divergence between the growing burden of chronic disease and the development of the health systems necessary to treat these diseases indicate the potential for a grave health, economic, and human crisis in the following decades. The WHO has consequently demanded that physicians designs systems providing "Innovative Care for Chronic Conditions" to meet this challenge4.
However, existing tools may provide a foundation for solutions to this growing crisis. Community Health Workers (CHWs, as known as health promoters) have become central to global health strategies since the Alma Ata Declaration of 1978, particularly in regions with physician shortages. In recent years, CHWs have had notable success in targeting childhood disease, particularly malnutrition and diarrhea, and offer a growing variety of primary care services. The success of these programs in providing consistent, sustainable care at the local level implies that longitudinal treatment for chronic adult diseases could be provided through parallel structures. While the treatment of chronic disease has become increasingly complex, the proliferation of smartphone and tablets across the globe have raised hopes that mobile health technology (mHealth) platforms can provide CHWs with algorithmic guidance on assessing and treating a broader set of diseases. The potential use of mHealth is a burgeoning field of global health research. The combination of CHWs and mHealth guidance may provide a solution to the rise of chronic disease in regions with physician shortages and weak health systems.
While many mHealth applications have been developed for Diabetes (over 1,000 are commercially available), only a small percentage (7.6%) are targeted to providers - and even fewer to providers in LMICs. Instead, these tools most commonly serve as tools for patient self-management, patient education, and medication adherence. A handful of programs have utilized smartphone technology to connect remote patients to health care workers in LMICs as well as to provide clinical guidance to providers, but such programs have been minimal and publications have been process oriented. In addition to improving diabetes care in the target population, the project also seeks to add to the evidence for this approach by designing an application-based algorithm that can assist CHWs in providing long-term diabetes care, titrating first- and second-line oral diabetes medications, and identifying dangerous diabetes complications in a setting of a lower middle-income country with a low physician density.
To test this delivery approach,the investigators focused on developing a diabetes treatment program in San Lucas Tolimán, Guatemala. This program seeks to provide treatment to diabetics living in the group of 19 rural villages with a combined population of 17,000, which surround San Lucas. San Lucas is an ideal community for studying these topics because it is facing a heavy burden of untreated Type II Diabetes, has medical personnel with mHealth experience, and has a well-developed CHW program. This CHW program is sponsored by the San Lucas Mission (SLM), an NGO providing health services in the area and a University of Wisconsin and Stanford University partner organization. Local health workers describe the increase in Type II Diabetes as an epidemic and there are few systems in place to provide community members with diabetes screening or effective and consistent treatment. Startling regional data on Type II Diabetes supports this concern: in Guatemala, the prevalence of diabetes has been estimated at 9.1-9.4%, with over 40% of cases undiagnosed22-24. The prevalence of diabetes has doubled over the past 30 years25. Fortunately, San Lucas has already developed a strong CHW program, including a tablet-based mHealth application that targets early childhood malnutrition, through a collaboration between the San Lucas Mission and Stanford School of Medicine. This application has enhanced the successful malnutrition program, allowing CHWs to more easily identify and manage malnutrition and decreasing training requirements for CHWs26. Utilizing the existence of the CHW program infrastructure and the established mHealth platform, the project seeks to develop and implement a CHW-led diabetes treatment program in San Lucas that is assisted by a smartphone application.
In order to inform the development of the smartphone application and program protocols, the investigators conducted a community needs assessment during the summer of 2016. Clinical data was used to provide a baseline estimate of diabetes prevalence and distribution in the communities as well as demographic risk factors. Interviews were conducted with local physicians, CHWs, and managers of the CHW system to understand current methods of diabetes treatment and define the limitations of these systems. Out of the 119 patients currently diagnosed with diabetes in the rural communities, 31 were interviewed to illuminate how the disease is currently diagnosed and treated, the effect the disease has on patient lifestyles, and patients' desired attributes for a diabetes treatment program. Finally,the investigators visited local diabetes clinics to determine the current state of diabetes treatment, the availability of medications and resources, and the level of care provided to patients.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Willing to provide written informed consent
- •Willing to comply with all study procedures and be available for the duration of the study
- •Male or female, at least 18 years of age
- •Prior diagnosis of type 2 diabetes
- •Resident of one of the rural communities served by the CHW network of San Lucas Tolimán, Guatemala
排除标准
- •Type 1 diabetes
- •Women who are pregnant
- •Current use of insulin
- •Renal insufficiency (eGRF <30 mL/min/1.73 m2)
- •Unable to provide informed consent -
结局指标
主要结局
Patients meeting their HgbA1c treatment goal
时间窗: 3,6,9 and 12 months
Percentage of patients meeting treatment goal for HgbA1c compared to this percentage at baseline. Treatment goal will be A1c ≤7 for most patients, A1c ≤8 for patients age 65 or older or who have 2 or more comorbidities, or other individualized goal for select patients as determined by the medical director
Change in HgbA1c
时间窗: 3,6,9 and 12 months
Change in mean percent of HgbA1c compared to value at baseline.
次要结局
- Waist circumference(3,6,9 and 12 months)
- Community Health Worker adherence(3,6,9 and 12 months)
- Fasting blood glucose(3, 6, 9 and 12 months)
- Referrals for more advanced care(3,6,9 and 12 months)
- BMI(3,6,9 and 12 months)
- Blood pressure(3,6,9 and 12 months)
- Diabetic complications(3,6,9 and 12 months)
- Medication adherence(Through study completion, an average of 1 year)
- Medication adverse effects(Through study completion, an average of 1 year)
