Health ANALYTICS is emerging as an important sector of Public Health sector, where using Analytics, Public Health experts are able to accurately understand the disease demographics, disease pattern and intricate relationship between various elements of Public health like, age, gender, ethnicity, location, terrain, income levels, vulnerability, disease history, , Disease burden , preventive and curative planning.

TOOLS OF COLLECTING MASSIVE PATIENT DATA AND ANALYZING THEM TO DRAW IMPORTANT INSIGHTS AND INFORMATION THEREBY HELPING PHYSICIANS AND HEALTH CARE PROVIDERS IN IMMEDIATE AND INTRINSIC DECISION-MAKING. DHANUSH DATA ANALYTICS CAPABILITIES PROVIDE CLINICAL INSIGHTS INTO CARE MANAGEMENT AND IMPROVE DELIVERY SERVICES.

HOW DHANUSH ANALYTICS IMPROVE PATIENT CARE:

• Health care decisions deal with sensitive information, require timely information and action and sometimes have life or death consequences. Each of these features creates barriers to the pervasive use of data analytics. Dhanush Analytics solution regularly collects and tabulates the data and patient demographics through staffing and infrastructure in their own servers and server setup facilitated by the Central Government
• Data analytics have the potential to transform health care. Routine doctor visits that are impossible in rural, remote and tribal areas are replaced by regularly monitoring patient health status and remote consultations by accessing the health care analytics and patient demographics and data
• As health care system is increasingly data reliant now, data analytics help in deriving insights on waste of resources, track physician performance and health of population and identify people at risk for chronic and infectious diseases. With the information at hand, Dhanush efficiently allocates resources, population health and care
• Through the implementation of health care analytics Dhanush has set up new methods to evaluate the performance and effectiveness of practitioners and give them required feedback
• Data is gathered from direct observation, complaints, practice patterns, patient outcomes and resource use in order to track and improve the practices of health care providers
• Ongoing health care analytics help identify patterns that lead to a greater understanding of population health. EHR (Electronic Health Records) provides Dhanush system detailed information that help cut costs by reducing unnecessary care. Predictive analytics estimates individual patient costs, so our system can allocate better personnel and resources to reduce waste and maximize efficiency
• Predictive analytics predict which patients are at higher risk for disease though metrics modelled on patient health habits and medical conditions, socio-economic factors and environment and Dhanush health care system readily intervenes and arranges for early intervention and prevent long-term systemic costs

CHALLENGES OF DHANUSH DATA ANALYTICS:

• Physicians and patients rely on high-standards for data analytics tools in health care. These have proven challenging to the designers of these tools. Predictions require careful identification of decisions and unsafe and incorrect data not based on real patient data, often lead to wrong treatment recommendations. Sometimes the patient does not desire to pursue the best clinical decision
• The sensitive nature of patient demographics and data are major concerns about privacy. Patients are concerned about the security of their data and it being used in ways that are detrimental or disadvantage to them and damage their reputations
• Health care data split among different entities often increases the cost of using data to provide value
• Another challenge is data quality. Analytics to be of any value must be based on good and well-structured data. Success of data analytics in health care depends upon availability and utilization of quality data

POLICY RECOMMENDATIONS:

• Policy changes to diminish the barriers to health analytics Priority should be making sure all Primary health centres and sub centres can record, use and share patient data in useful ways
• Health care providers need data analytics capabilities to better coordinate and improve value of care
• Real-time alerting should be done with effective CDS (Clinical Decision Support) software that analyzes medical data on spot providing health practitioners with insights and advices at the time of decision-making
• Enhance patient engagement by directly involving patients in self-monitoring and all this vital information along with specific health trends can help to identify potential risks. Patients become more independent and unnecessary visits are reduced
• Data analytics in healthcare allows for strategic planning. Care managers should analyze checkup results in different demographic groups and identify problems regarding delivery of care and review their strategies according to insights
• Today with the arrival of video conferences, wireless devices, smart phones, Telemedicine has come into full bloom. Delivery of remote clinical services in rural, tribal and remote areas are possible using high-speed real time data. Doctors should use Telemedicine along with predictive analytics to predict acute medical events in advance, prevent hospitalizations and deterioration of patient's conditions