Hospital Analytics

data-driven decisions
A fast-growing, multi-specialty hospital in the state operating with a staff of 400+ healthcare professionals, and facilitated by a 90 beds setup; implemented business intelligence solution for better information dissemination across departments and to improve patient satisfaction.

Reduced readmission rate
Time faster availability of reports pertaining operational KPIs
Improved patient satisfaction
A fast-growing, multi-specialty hospital in the state operating with a staff of 400+ healthcare professionals, and facilitated by a 90 beds setup offering orthopaedics, cardiology and urology consulting, and treatment.

Disparate legacy systems generating important operational data were posing a challenge for the administration to carry data visualisation and hospital data analytics to answer specific business problems. Besides this, the operational reporting methodologies were more of manual heavy lifting and lacked pace and accuracy required to manage business growth.
A multispeciality hospital
Orthopedics, Cardiology, Urology
  • Enterprise ETL on HMS & Tally Accounting system
  • Data warehouse
  • Custom reports & Dashboards
  • Managed BI and ETL Services
The hospital was facing the challenge of reducing patient satisfaction tracked through the patient exit and follow up forms. Considering it was a rapidly emerging multi-specialty hospital, it was drawing attention from the administration.

Analysing the root cause for reducing patient satisfaction was a challenge since many factors were in the equation, and fragmented information was being produced across their IT systems. Recognising Data as the most reliable source of business intelligence, the hospital took a data-driven approach to address the business problem.

Data Nectar was expected to come up with a data analytics solution to extract the insights that could reveal the right area to be focussed, to address the patient satisfaction challenge. Also, the system was expected to produce weekly reports to be consumed by various operational departments for better planning of training and resource utilisation.

  • Declining Patient Satisfaction
  • Inadequate Operational Reporting
  • Declining patient satisfaction
  • Higher readmission rates
  • Lack of regular insights into operational efficiencies
Approach was to aggregate important data from across the system, visualise and analyse KPI interrelations to spot the cause of low patient satisfaction.

Business intelligence system was developed to ingest data from disparate business applications Hospital Administration System, Patient Survey, HRM system. ETL, Data Warehouse were designed with data cubes and marts to enable faster results for user queries.

Distribution of readmission rate across departments in conjunction with the ‘staff-to-patient’ ratio & ‘average hospital stay’ data helped reveal the right area to act upon. A reduced staff-to-patient ratio and higher hospital stay duration were leading to increased overtime by staff and thereby, reduced quality of care. These factors were contributing significantly to a higher readmission rate of 22%. Drill through dashboards and custom reports helped the administrators take corrective measures around staff hiring, training, and scheduling.

Comparative KPIs data helped the hospital to prepare department-specific targeted programs to improve initial treatment & patient discharge procedures to enhance the quality of care and minimise chances of readmission.
  • Staff to patient ratio
  • Re-admission rate
  • Average Stay time/diseases/doctor
  • Patient Wait time
  • Patient survey
  • Lab report turnaround time
  • Doctor to Patient ratio
  • Load on nursing staff
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