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Prasad Nagool
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In the current economic scenario, healthcare organisations suffer from budget restrictions and increasing healthcare cost. Hospitals are now expected to efficiently and effectively treat patients in a way that ensures best hospital clinical outcomes.
There is large amount of clinical and financial data with the hospital but it is rarely used. Having useful software is a key to assemble all this data to achieve better efficiency in working and planning of the hospital. Along with proper and effective healthcare planning and decision making in any hospital or health institution, the data collected needs to be fully analysed. Well analysed data will assist the decision makers to detect and control emerging and endemic health problems, monitor progress towards health goals and maximise profit.
Hospital data analytics can help:
- In identifying areas of improvement
- In minimising the operational costs
- In reducing the costs for chronic illness
- In enhancing customer engagement
- Lessen fraud in billing issues
- Improve return on investment
- Identifying the areas for growth
Case study: This is a chain of hospitals. Out of which we have considered one hospital for our analysis.
This is a big hospital with daily OPD of around 500-700 patients. There were two counters for OPD registration and one counter for billing. The OPD timings started from 9 AM and due to rush would continue till 4 PM. The patient were required to go to the registration counter, pay the registration/ OPD fees then were directed to the waiting area and from there to one of the doctor cabins depending on the patient ailment.
Problems with the system
- Long queues for patient
- Patient waiting time was more
- Doctors time was wasted
- Hospital needs to pay doctor extra for extra time
The hospital used HMIS System. Analysis was done for the average waiting time from the time the patient registration was done and then time when patient checked in to the doctor cabin. The average waiting time was 45-50 minutes.
After the analysis a solution was proposed. Two registration counters were converted to billing and additional one billing counter was added. So total four billing counters were made. Four tablets with HMIS installed were distributed between the semi-skilled staff and mobility was added for registration. Patient registration was done using tablets at the entry point of the hospitals. Registration data was captured and the patient was directed to payment counter. Once the payment was done the patient name adds in the doctor waiting list, then patient goes to the waiting area. If the doctor’s appointment is full for that day the patient was sent to the enquiry counter for taking future date appointment. By doing this the average patient wait time was reduced to 15 – 20 minutes.
Benefits
- Average patient waiting time was reduced
- Average patient seen by doctor was increased
- Patient management was easy
- Helped in smooth operation
This is how information technology along with data analysis, provided information to the managing committee or the directors of the hospitals to take decisions efficiently. Data Analysis improved their profit margin, hospital clinical outcome and patient care.