Unlocking Insights
in Heart Failure
Heart Failure Dataset Insights
Our dataset° provides valuable insights into Heart Failure, including but not limited to:
+23 500
N Patients
with Heart Failure
37.5%
% 80+ years' old patients at diagnosis
5+
years
Mean Follow-Up Period
17.2 %
Mean 1-year mortality
Top 3 Combinations at Discharge **
- (ACE-I or ARB or ARNI) + BB
- (ACE-I or ARB or ARNI) + BB + MRA
- (ACE-I or ARB or ARNI) + BB + MRA + SGLT2-I
Top 5 Comorbidities
- Hypertension
- Diabetes Mellitus
- Chronic kidney disease
- Cancer
- Myocardial infarction
9.97%
Average 30D
readmission*
68%
% Males
* 30D readmission: 30-day readmission | ** ACE-I: Angiotensin-Converting Enzyme Inhibitors, ARB: Angiotensin Receptor Blockers, ARNI: Angiotensin Receptor-Neprilysin Inhibitor, MRA: Aldosterone Receptor Antagonists, BB: Beta Blockers, SGLT2-I: Sodium-Glucose Transport Protein 2 (SGLT2) Inhibitors
Note that the estimated patient counts provided (prior to inclusion/exclusion criteria) are specific to our Belgian dataset. The LynxCare datasets continue to expand, encompassing real-world data from hospitals across Europe. Complete the request feasibility form linked above to discuss your study needs with one of our RWE experts.
Closing the Gap
The Value of Unstructured Data in Heart Failure.
Comorbidity Data Gap
The majority of clinical trials on heart failure exclude patients with significant comorbidities, which can lead to a lack of real-world representation. Our data asset offers insights into the relationship between specific comorbidities, adverse events, and treatment outcomes in heart failure patients, bridging this important knowledge gap and informing comprehensive care decisions. For example, our data reveals a higher prevalence of comorbidities such as chronic kidney disease (10%) (NLP enriched) compared to structured data alone (5%).
Reason for Treatment Line Switch
Structured data alone provides only a partial understanding of treatment decisions in heart failure. By combining structured data with rich EHR narrative data, we can gain deeper insights into the reasons for treatment line switches, such as adverse events and individual patient characteristics.For instance, our data shows a higher detection rate of autoimmune diseases (13.5%) (NLP enriched) compared to structured data alone (4.7%).
Real-World Insights
Leveraging our real-world dataset, with a mean follow-up time of over four years, we can analyze adverse events, treatment patterns, and overall survival in heart failure patients in real time. These insights provide valuable information about the patient journey and can help guide treatment decisions.
Unpacking The Data
The Sources Behind Our Insights
Unlock Research Questions
Our dataset offers life science companies unparalleled insights into the relationship between specific biomarkers, comorbidities, and treatment outcomes in heart failure.
Research Question/ Endpoints
Demographics
Comorbidities
Lab results & echocardiography
Hospital visits & admissions
Survival
Biomarkers, genetic drivers
Hospital visit & admissions
Survival
Biomarkers, Genetic drivers
Outcomes
Adverse events
Complications
Titration / Dosing
Treatment dynamics
Incidence & Prevalence
Adherence
Efficacy
Indication split
Safety profile
How Pharma Can Leverage LynxCare's Dataset
Clinical Trial Design
Our granular and quality-controlled real-world dataset can help design clinical trials that better reflect real-world scenarios.
Synthetic Control Arm
Our dataset can be used to create synthetic control arms, which can be used to evaluate the effectiveness of new treatments.
Market Access
Our dataset can help pharma companies gain a better understanding of the market and generate granular value dossiers for HEOR.
Medical Affairs
Our dataset can help medical affairs teams better understand the clinical outcomes and real-world evidence associated with their products.
How Hospitals Can Benefit from a LynxCare Database
Improving Patient Care
Find more relevant medical information thanks to LynxCare's disease-specific NLP pipeline for a better patient and population understanding.
Research & Network Opportunities
Initiate or participate in national and international multi-center, multi-country RWE studies.
Benefit from network of KOLs.
Scientific Research
Initiate or participate in (pharma- or physician initiated) peer-reviewed (multi-center, multi-country) publications
Increased Clinical Trial Participation
More effective patients/cohort selection through clinical NLP, enrolling more patients in clinical trials
Improve your Data Quality
Receive feedback on the clinical data quality of your hospital’s database.
Benefit from data science training provided
World-Class Expertise.
The LynxCare Advantage
Differentiating factors from other NLP providers & established RWD vendors
Building Trust
Quality Control and Data Freshness
Quality Control
Data Freshness
OMOP CDM Data Warehouse
Patient Insights
More Than Numbers
Individualized Care
Cross-Disciplinary Collaboration
Impact on Patient Outcomes
The Future of Heart Failure Treatment
How LynxCare Can Help
Personalized Medicine
By providing insights into individual pathways of heart failure patients, our data asset enables clinicians to tailor treatments to specific patient needs, opening up the possibility of personalized medicine (ATTR-CM, Cardiorenal syndrome, SGLT-2 eligibility,...)
Improved Outcomes
By providing insights into the clinical pathway of heart failure patients, our data asset aims to ultimately improve patient outcomes by providing valuable insights for clinicians and researchers (e.g. impact on mortality when admitted via geriatrics).
Continued Innovation
With our comprehensive dataset and world-class expertise, we aim to continue to drive innovation in heart failure treatment and management, ensuring that the latest insights and solutions are available to healthcare providers and researchers.
° LynxCare datasets concern datasets within the LynxCare's European hospital network. The hospitals are the data controllers. No commitment before site approval on RWE request.
