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Version: 0.0.2 | Published: 20 Nov 2023 | Updated: 549 days ago
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North-West London Patient Segmentation (NWL PS)

Dataset

Summary

DOI Name:
Not Available

Documentation

Description:
The North-West London Patient Segmentation (NWL PS) dataset refers to a collection of data and categorization methods used to segment or classify patients in the North-West London region based on specific characteristics or needs. Patient segmentation is a process that divides a population into distinct groups or segments to better understand and address their healthcare needs. The NWL PS dataset includes information related to the segmentation criteria and methodologies used to classify patients within the region. It may involve variables such as demographic factors (age, gender, ethnicity), clinical characteristics (medical conditions, severity of illness), healthcare resource utilization patterns, social determinants of health (e.g., socioeconomic status, housing), and other relevant factors. The dataset may provide insights into different patient segments or categories within the North-West London population. These segments could include groups with specific healthcare needs, high-risk populations, individuals with chronic conditions, or those requiring specialized care or interventions. The NWL PS dataset serves multiple purposes. It provides a foundation for population health management and healthcare planning by enabling a better understanding of the diverse needs and characteristics of the patient population. It helps identify priority areas for intervention and resource allocation based on the specific needs of different patient segments. Healthcare providers can utilize the NWL PS dataset to tailor care delivery and interventions to the unique needs of different patient segments. By understanding the characteristics and healthcare utilization patterns of each segment, providers can develop targeted strategies to improve health outcomes, enhance care coordination, and optimize resource allocation. Policymakers and healthcare administrators can use the NWL PS dataset to inform policy decisions and allocate resources to address the specific needs of different patient segments. It supports the development of tailored healthcare services, interventions, and programs to improve population health and reduce health disparities in the North-West London region. Researchers may utilize the NWL PS dataset to conduct studies on healthcare utilization patterns, outcomes, and interventions for specific patient segments. It enables the evaluation of the effectiveness of interventions, the identification of gaps in care, and the development of evidence-based practices for improving healthcare delivery and patient outcomes. It is important to note that access to the NWL PS dataset and the specific data elements it contains may be subject to privacy regulations and governance frameworks. For more detailed information about the dataset, including its availability, specific variables, and usage guidelines, it is recommended to consult the relevant healthcare authorities or organizations responsible for managing and maintaining the NWL PS dataset in the North-West London region.
Is Part Of:
WSIC

Coverage

Spatial:
NHS Brent CCG; NHS Central London CCG; NHS Ealing CCG; NHS Hammersmith &Fulham CCG; NHS Harrow CCG; NHS Hillingdon CCG; NHS Hounslow CCG; NHS West London CCG
Typical Age Range:
0-150
Follow Up:
> 10 YEARS
Physical Sample Availability:
NOT AVAILABLE

Provenance

Origin

Purposes:
  • ADMINISTRATIVE
  • CARE
  • OTHER
Sources:
OTHER
Collection Situations:
OTHER

Temporal

Accrual Periodicity:
OTHER
Time Lag:
OTHER

Accessibility

Access

Jurisdictions:
GB
Data Controller:
Joint data controller model across North West London
Data Processor:
NHS BRENT CCG

Usage

Data Use Limitations:
NO RESTRICTION
Data Use Requirements:
  • COLLABORATION REQUIRED
  • GEOGRAPHICAL RESTRICTIONS
  • PROJECT SPECIFIC RESTRICTIONS
  • USER SPECIFIC RESTRICTION
Resource Creators:
  • NHS NWL ICS
  • Discover-NOW

Format and Standards

Vocabulary Encoding Schemes:
OTHER
Conforms To:
OTHER
Languages:
en
Formats:
OTHER