Patient Centric Research
Charting our path toward supporting holistic healthcare decision-making
We are dedicated to place patients at the forefront of healthcare decisions. Our patient-centered research revolves around creating patient-centered evidence, recognized by payers and regulators. As your trusted partner, we conduct preference studies (e.g., DCE), health utility studies, qualitative research, and clinical outcome assessments using innovative approaches. Choose us to achieve impactful, patient-focused outcomes.
Patient centricity at every stage
Understanding the unmet need for relevant product development
Understanding the facilitators and barriers to support increased utilization/access
Optimizing study design and capturing the relevant measures thought the clinical phases
Regulatory / Market Access
Capturing utilities for economic evaluation, secondary analysis of trial data and/or RWD
Patient voices are instrumental at every step. They provide essential guidance, lending real-world perspectives to research and development. By actively involving patients/caregivers throughout the product lifecycle, we enhance our capacity to create healthcare solutions that are not only effective but also compassionate, respectful of individual needs, and patient-driven.
How do we make a difference?
Our ultimate objective is to enhance patient outcomes, but achieving this goal hinges on active engagement and the seamless integration of patient perspectives. Without their input, our efforts lack the depth and precision needed to make a tangible difference in their lives. We go beyond the conventional methods and embrace cutting-edge approaches to integrate patient-centricity at every step, thus cultivating patient-centered evidence that resonates with payers, regulators, and healthcare providers. At ConnectHEOR, making a difference means prioritizing patients and delivering solutions that truly matter.
Everything you may need
- Discrete Choice Experiments (DCE)
- Quantitative Risk Benefit Assessment (QBRA) using Multi Criteria Decision Analysis (MCDA)
- Delphi panels
Health Utility Studies
Utility estimation from existing tools (EQ-5D)
Utility mapping and generation
Q-TWIST analysis (Quality-adjusted Time Without Symptoms of disease and Toxicity)
Clinical Outcome Assessment
Instrument design and development
Data analytics using diverse biostatistics applications
Scientific communication and dissemination
Patient-public involvement (PPI)
Qualitative evidence synthesis (literature reviews)
Patient journey studies
Assessing patient preferences to improve efficacy of treatment for Urinary Incontinence
A pharmaceutical company specializing in urology and urogynecology, was faced with the challenge of improving their treatment for urinary incontinence. They aimed to gain a comprehensive understanding of patient preferences regarding treatment options, specifically focusing on the efficacy in reducing symptoms and the burden of adverse effects. The company wanted to understand the patient preferences for a specific treatment for urinary incontinence, to further modify the treatment and understand the unmet need with respect to symptom reduction, burden due adverse effects.
To address this issue, we undertook a multifaceted research approach, combining mixed method research (surveys + in-depth interviews) and discrete choice experiment.
- A targeted literature review was conducted to gain insights into existing research on urinary incontinence treatments and patient preferences.
- To inform the discrete choice experiment, in-depth interviews were conducted with a select group of patients to qualitatively explore their experiences, concerns, and preferences regarding treatment options.
2.Discrete Choice Experiment:
- A discrete choice experiment was conducted to quantitatively assess patient preferences for various treatment attributes.
- Treatment choices were detailed in terms of attributes such as efficacy in reducing symptoms and the likelihood of experiencing typical adverse events.
- A fractional orthogonal design was utilized to combine choice sets, ensuring efficient data collection and analysis.
- The conditional logit model was used for data analysis, allowing for the estimation of preference weights for different treatment attributes.
- Marginal rates of substitution were calculated to demonstrate the relative value of trade-offs between the various attributes, shedding light on the trade-offs patients were willing to make in their treatment choices.
- Online Survey on HRQOL Impact:
- To gain a deeper understanding of the Health-Related Quality of Life (HRQOL) impact of adverse events associated with treatment, an online survey was administered.
- The survey collected data on adverse event attributes and their impact on patients’ daily lives.
- Regression analysis was performed to analyze the relationships between adverse events and their effects on HRQOL.