Healthcare Data Analytics Solutions

Enabling healthcare
providers improve the
quality of care and optimise
operational efficiencies.
HEALTHCARE is a highly dynamic industry whose credibility to a large extent depends on improving your organisation’s efficiency and performance.
One of the most reliable ways to do this is to analyse your operations, using data analytics and business intelligence (BI) to gain insights into the current state of operations. Thereafter, build healthcare data strategies based on it to improve productivity in services.
At Data Nectar, we comprehend every data available from your healthcare KPIs in Operation, Finance, Patient Care, etc. like average patient stay, average wait time to current ER occupancy, hospital readmission rates, and many more to give us valuable BI insights that drive results.
Data analytics and Business Intelligence (BI) can transform the healthcare industry by bringing in limitless solutions from the huge amount of data collected at various touchpoints.

Data Nectar is engaged in providing accurate solutions based on the historical data mined from the vast resources. Our industry experience since 2019 promises to open limitless possibilities for the custom application of data analysis in healthcare that we offer, from:
  • Epidemic Forecast
  • Early Detection
  • Disease Remedies
  • Risk Assessment
  • Preventive Care
  • Enhancing Quality of life
Data Nectar Technosys understands that healthcare data is one of the most complex and humongous of all industries. This difficult and delicate process requires a high level of security and connectivity, which only an embedded analytics solution can provide.

Our data analysis and BI solutions experts stay on top of all the evolving policies, processes, and regulations in the healthcare sector, and ensure that all the insights generated from your data are converted into actionable insights.

We have ready-to-plug data warehouse and data visualization templates for fast implementation. We take insights from your own raw data, to minimise overall costs, and boost revenues.

Get in touch with us if you are looking to harness the power of healthcare analytics at both macro and micro levels for effective streamlining of operations, delivery quality, and improving patient care.

Are you looking for custom BI solution for your hospital and?

Book a 30-minutes free consultation with our Business Intelligence experts today.
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How to leverage healthcare analytics


Understanding healthcare kips


This KPI allows you to measure and track (hospital) business objectives while considering patient satisfaction and capacity management. It is calculated based on the average time a patient must wait from entering a hospital until they are diagnosed by a healthcare professional.


This metric measures the number of beds currently occupied in the ER, compared to the total number of beds available. Monitored in real-time, this KPI is crucial as it keeps the staff aware of the current ‘occupancy’ status in the ER with increased agility.


This metric tracks the average patient admission and stay in hospital time. The KPI that tracks the different categories, varies based on the recovery period required. For instance, eye surgery will require a shorter stay, while an abdominal surgery will need a longer stay.


This KPI tracks how many patients are getting readmitted within 1 month after the initial visit. It also measures the percentage of unplanned patient readmissions out of the total number of readmission cases. High readmissions rate may indicate a range of issues in both effectiveness of treatment and quality of care.


This KPI tracks the number of staff present to attend to the patients in a hospital over a certain period (morning shift, night shift). The staff-to-patient ratio is a useful metric that besides improving workforce sustainability, aims to improve the quality of patient care.


This KPI measures the efficiency of your lab to process certain test results. An important indicator of patient satisfaction, this metric is calculated by creating a breakdown for each type of test processed in the lab (considering some lab tests take longer than others to complete).


This metric measures the time between the patient starting to experience symptoms, to the time of hospitalisation. This KPI is frequently used to determine the course of care. The time of symptom onset can be obtained by data mining from the medical record and/or planned interviews done after the critical event.


This KPI tracks the number of operative and non-operative patients in a hospital, and the entire process around it. From factors to segment a case into a particular category (operative or non-operative), admission process and hospital and treatment packages for patient care are analysed.
Let’s have a conversation to know more KPIs that can help you make better decisions
on improving the quality of care!
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