The goal of this observational study is to evaluate a new home-based setup and care model for an advanced hybrid closed-loop insulin pump system (Tandem with Control-IQ). The study will look at the safety, effectiveness, costs, and impact on quality of life in adults with type 1 diabetes. The main questions it aims to answer are: * Is it safe for participants to start using the insulin pump system at home instead of the hospital? (Measured by the amount of time blood sugar is very low, under 54 mg/dL). * Does this home-based care model help participants keep their blood sugar in a healthy range? * How does this model affect the participants' quality of life, device satisfaction, and overall experience? * Does this model reduce healthcare costs and the need for hospital visits? Participants will: * Complete an online technical training course before the setup. * Receive a home visit from a specialized nurse to configure and start the insulin pump system. * Have their device data monitored remotely every 14 days by the nursing team to manage any health alerts. * Attend scheduled clinical follow-up visits at 1, 3, 6, and 12 months. * Answer surveys about their quality of life, their experience with the healthcare service, and their satisfaction with the new device.
Background and Rationale: The standard model for initiating Advanced Hybrid Closed-Loop (AHCL) systems in Spain is primarily hospital-centric. This model consumes significant healthcare resources and can lead to variability in access or delays in treatment indication. The Region of Murcia currently has a higher hospitalization rate for Type 1 Diabetes (T1D) than the national average, suggesting room for improvement in care organization. This project proposes an alternative Value-Based Healthcare (VBHC) model that shifts the initiation of the Tandem Control-IQ system to the patient's home, supported by structured online education, continuous telemonitoring, and shared clinical follow-up between the hospital and a specialized external nursing team. Study Pathway and Procedures: Eligible patients will first undergo online technical training on the AHCL system provided by a specialized nurse. Subsequently, the nurse will perform the physical setup of the system at the patient's home, configuring the device according to the medical parameters (e.g., basal rates, sensitivity factors, carbohydrate ratios) prescribed by the patient's endocrinologist. Sampling Method: Eligible participants will be selected using consecutive participant sampling to minimize selection bias. Throughout the 12-month follow-up, patients will be telemonitored every 14 days. The external nursing team will review glycemic metrics to identify automated clinical alerts. High alerts (defined as Time in Range \[TIR\] \<=50% or Time Below Range \[TBR\] \>=8%) and Medium alerts will trigger a telephone intervention. Technical issues will be resolved directly by the specialized nurses, while persistent clinical issues will trigger a protocolized referral back to the hospital's endocrinology team. Scheduled data collection for clinical indicators, questionnaires, and resource consumption will occur at baseline, and at 1, 3, 6, and 12 months. Healthcare Professionals Sub-study: A parallel evaluation will involve the participating doctors and nurses (approximately 9 physicians and 3 nurses). They will complete specific, anonymized questionnaires halfway through the study to assess their acceptance of the model, perceived experience, and the estimated time saved in hospital consultations and avoided emergency visits due to the home-based model. Data Management and Quality Assurance: Data will be prospectively collected using an electronic Case Report Form (e-CRD) hosted on a secure, centralized cloud clinical platform (ReseaArch). The system is designed with filters and restrictions to minimize data entry errors, flag out-of-range values, and detect inconsistencies. Plan for missing data: Missing data is expected to be minimal, as continuous glucose monitoring records are automatically generated and extracted from the technology used. Furthermore, the database will be reviewed at least monthly by the research team to verify the enrollment pace, ensure the completeness of the entered data, and address any missing questionnaire responses. Sample Size Assessment: The study aims to enroll 80 patients across three participating hospitals over a 1-year recruitment period. This sample size allows for the estimation of proportions with a 95% confidence interval (CI) margin of error of approximately +/- 11% under maximum indeterminacy (p=q=0.5). For continuous variables (e.g., TIR), assuming a standard deviation of 10, the precision of the mean would be 2.18, providing sufficient statistical power (alpha=0.05; beta=0.2) to detect relevant differences of 6.3 units between patient subgroups. Statistical Analysis Plan: Descriptive statistics will be used to summarize baseline characteristics and outcome variables. Continuous variables will be evaluated for normal distribution using the Kolmogorov-Smirnov test and reported as means and standard deviations (SD), or medians and interquartile ranges (IQR) if not normally distributed. Categorical variables will be expressed as frequencies and percentages. Comparisons between groups (e.g., by gender or educational level) will be performed using Student's t-test or the Mann-Whitney U test for continuous variables, and the Chi-square or Fisher's exact test for categorical variables. Multivariate analyses, including multiple linear or logistic regression models, will be conducted as appropriate to adjust for potential confounders. Statistical significance will be set at a two-tailed p-value \<0.05. Economic Evaluation: An economic evaluation will be conducted from the perspective of the Healthcare System, considering only direct medical costs. Unit costs will be assigned based on the official healthcare tariffs of the Murcian Health Service (SMS). Since the study lacks a comparator group, outcomes will be expressed using cost-outcome and cost-utility indicators, such as cost per unit of Time in Range (TIR) and Quality-Adjusted Life Years (QALYs) accumulated over 12 months. QALYs will be calculated using the EQ-5D-5L index scores based on the validated Spanish tariffs. Any estimation of "gains" (e.g., QALYs gained or TIR gained) will be conducted explicitly as an exploratory analysis, using a before-after counterfactual compared against the patient's own baseline state. To manage the underlying uncertainty in costs and health outcomes, a deterministic sensitivity analysis will be performed by constructing three scenarios (baseline, most favorable, and least favorable) using the 95% confidence intervals of the variables.
Study Type
OBSERVATIONAL
Enrollment
80
Hospital General Universitario Santa Lucía
Cartagena, Murcia, Spain
Percentage of Time Below Range (TBR) <54 mg/dL
Safety of the home-based initiation model will be evaluated by measuring the percentage of time participants spend with sensor glucose levels strictly below 54 mg/dL (Level 2 hypoglycemia), as recorded by the continuous glucose monitoring (CGM) system
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Percentage of Time in Range (TIR) 70-180 mg/dL
Clinical effectiveness will be evaluated by measuring the percentage of time participants spend with sensor glucose levels between 70 and 180 mg/dL, as recorded by the continuous glucose monitoring (CGM) system.
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Percentage of Time Above Range (TAR)
Clinical effectiveness will be evaluated by measuring the percentage of time participants spend with sensor glucose levels above 180 mg/dL (Level 1 and 2 hyperglycemia), as recorded by the continuous glucose monitoring (CGM) system
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Percentage of Time in Tight Range (TITR) 70-140 mg/dL
Clinical effectiveness will be evaluated by measuring the percentage of time participants spend with sensor glucose levels between 70 and 140 mg/dL, as recorded by the continuous glucose monitoring (CGM) system
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Change in Glycated Hemoglobin (HbA1c) Levels
Clinical effectiveness will be assessed by measuring the change in HbA1c percentage from baseline to evaluate long-term glycemic control
Time frame: Baseline and Month 12
Mean Sensor Glucose
Mean glucose level (mg/dL) measured by the continuous glucose monitoring (CGM) system
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Glycemic Variability Assessed by Coefficient of Variation (CV)
Percentage of the coefficient of variation of sensor glucose levels, used as a measure of glycemic variability
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Total Insulin Units Consumed
Total daily units of insulin consumed by the participant via the advanced hybrid closed-loop system
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Percentage of Time With Active System
Percentage of time the advanced hybrid closed-loop system is active and operating in closed-loop model
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Incidence of Severe Hypoglycemia
Number of severe hypoglycemia episodes requiring assistance from another person during the follow-up period
Time frame: 12 months
Incidence of Diabetic Ketoacidosis (DKA)
Number of episodes of diabetic ketoacidosis and related hospital admissions during the follow-up period
Time frame: 12 months
Change in Quality of Life Assessed by the ViDa1 Questionnaire
Quality of life will be measured using the unabbreviated scale Vida con Diabetes tipo 1 (ViDa1) questionnaire, a specific instrument validated in Spain for adults with type 1 diabetes. The questionnaire consists of 34 items rated on a 5-point Likert scale (from 1 = strongly disagree to 5 = strongly agree). Scores are calculated by summing the items for each of its 4 dimensions: * Interference with life (12 items): Score ranges from 12 to 60. Higher scores indicate greater interference with daily life (a worse outcome). * Self-care (11 items): Score ranges from 11 to 55. Higher scores indicate better disease self-care (a better outcome). * Well-being (6 items): Score ranges from 6 to 30. Higher scores indicate greater physical and psychological well-being (a better outcome). * Disease worry (5 items): Score ranges from 5 to 25. Higher scores indicate greater fear and worry about the disease (a worse outcome).
Time frame: Baseline, Month 3, Month 6, and Month 12
Change in Diabetes Distress Assessed by the PAID-20 Questionnaire
Disease burden and diabetes-related emotional distress will be measured using the unabbreviated scale, the Problem Areas In Diabetes (PAID) questionnaire. The questionnaire consists of 20 items, each rated from 0 (not a problem) to 4 (a serious problem). The scores for each item are summed and then multiplied by 1.25 to generate a total score. The total score ranges from a minimum value of 0 to a maximum value of 100. Higher scores indicate severe diabetes distress, representing a worse outcome
Time frame: Baseline, Month 3, Month 6, and Month 12
Health-Related Quality of Life Assessed by the EQ-5D-5L Questionnaire
General health-related quality of life will be measured using the unabbreviated scale, the EuroQol 5-Dimension 5-Level (EQ-5D-5L) questionnaire. The instrument consists of two parts. First, a descriptive system evaluating 5 dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), which are used to calculate the EQ-Index score based on validated tariffs. The EQ-Index score ranges from a minimum value of 0 to a maximum value of 1. Second, a Visual Analogue Scale (VAS) rating current overall health, ranging from a minimum value of 0 (worst health you can imagine) to a maximum value of 100 (best health you can imagine). For both the EQ-Index and the VAS, higher scores indicate better health, representing a better outcome.
Time frame: Baseline, Month 1, Month 3, Month 6, and Month 12
Patient Experience Assessed by the howRwe Questionnaire
Patient experience regarding the healthcare service and the home-based initiation model will be evaluated using the unabbreviated scale, the howRwe (How are we doing) questionnaire, which assesses the patient-staff relationship and overall system functioning. The questionnaire consists of 4 items, each rated on a 4-point scale from 0 (poor) to 3 (excellent). The scores for each item are summed to generate a total summary score. The total score ranges from a minimum value of 0 to a maximum value of 12. Higher scores indicate a better patient experience with the healthcare service, representing a better outcome
Time frame: Month 1, Month 3, Month 6, and Month 12
Device Satisfaction Assessed by the Diabetes Impact and Device Satisfaction Scale (DIDS)
Patient satisfaction with the technology and the psychosocial impact of the treatment will be measured using the unabbreviated scale, the Diabetes Impact and Device Satisfaction (DIDS) Scale. The instrument consists of 11 items, each rated on a 10-point Likert scale. It is scored by calculating the mean of the items for its two subscales: * Device Satisfaction (7 items): The score ranges from a minimum value of 1 to a maximum value of 10. Higher scores indicate greater satisfaction with the insulin delivery device, representing a better outcome. * Diabetes Impact (4 items): The score ranges from a minimum value of 1 to a maximum value of 10. Higher scores indicate a greater negative impact of diabetes on the user's daily life (e.g., worry, sleep interruptions), representing a worse outcome.
Time frame: Baseline, Month 3, Month 6, and Month 12
Cost-Utility Indicator: Quality-Adjusted Life Years (QALYs) Accumulated
The cost-utility indicator will be evaluated using the total direct medical costs and the QALYs accumulated over the follow-up period. QALYs will be calculated using the EQ-5D-5L questionnaire index scores based on validated tariffs. Since the study lacks a comparator group, any estimation of "QALYs gained" will be conducted explicitly as an exploratory analysis, using a before-after counterfactual compared against the patient's own baseline state.
Time frame: 12 months
Direct Healthcare Costs and Resource Consumption
The economic impact the home-based initiation model will be evaluated by quantifying total direct healthcare costs from the perspective of the Healthcare System. This includes the consumption of resources such as scheduled and unscheduled primary care visits, emergency room visits, hospital admissions, and specialized endocrinology consultations.
Time frame: 12 months
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