Look how Data Analysis has changed the culture of service industry- bringing in more transparency, moulding the thought process and building up of the new objective in providing service. This is what the entire industry wise-folks were aiming at- now we have the preliminary building blocks toward a rationalized service metric that can be enforced as regulatory requirements and that can add on to the assurance value of the end customers who buy the service. The metrics could not have even been conceptualized before we had data analytics tools working in the service industry.
A case study of the Health Care providing industry through facilities can now show how even similar generalized rationalized metrics may be conceived toward building up a general standard. A general standard is always the first stepping stone of reassurance to a buyer.
A service is intangible, it is perception and the outcome of satisfaction does not have a single parameter that can be quantified. Many components build up the satisfaction of a client. Such a subjective measure has got at least some generic problems and constraints-
1. No two clients would and might have the same parameters in his/her satisfaction pack.
2. The priorities of these elements would differ too from person to person.
3. Each such parameter would have different weights when paired up with the monetary value of the service and would therefore differ in nature and content from one buyer to the other.
4. The group behaviour would be dependent on demographic and territorial and other factors.
5. The regulatory authorities are dictated by the government policies and each one of them has different considerations.
All these came as impediments till now and therefore no Generally Accepted Measures could be developed. Thanks to the data analytics practice in Business Analysis, quantitative measures came into vogue and any quantitative measures can only be meaningful unless they have comparison value. A number can become a potent force when it will be accepted and used by the people or subscribers in the service industry – when they realize the value of these numbers.
Health Care Case study:
How effectively a physician or a surgeon treats and cures her customer is something that will always be subjective, but there are many other factors in the service sector. How a patient is served, how is he or she helped while she waits for a session with the doctor, how is the patient cared for if he/she is admitted, how is the patient assuaged against payment crises – all these associated service adds up to the confidence building of a would be patient with respect to a particular facility. A section or space or country is better known for the associated service more than or at least no less than the exact treatment a patient undergoes.
In our experience in dealing with super-speciality health care facilities the following metrics are now gaining ground and are increasingly being used by the industry- and there is a sense of reassurance that has gripped by the clientele and in many cases they have started comparing them and evaluating them with respect to the payment they shell out. Following are some:
1. Average waiting time of a patient in the Out-patient department
a. This time is then qualified by the department, time of the day etc so as to come to some sort of a distribution of patients throughout the day.
2. Number of windows to cater with respect to the number of patients per window.
3. Time taken to process the paper work and redirect to the proper department or physician.
4. Facilities that are offered to the waiting clients- their cost and benefit in terms of measuring the value through increment or differential [ how much more customer is attracted by adding on one more gadget]
5. The time and effort required resolving the payment of individual clients’ issues and how many options are provided so that a patient can feel attracted and assured. [ e.g Facility specific insurance or card for repeat clients, how many counselling sessions are provided for a measured number of clients]
6. Number of times a client is asked to visit with respect to what kind of ailment and by which attending doctor in which department.
7. The total cost incurred by a client for a particular disease and the total time taken for a complete cycle of healing.
8. Total cost of the facility in terms of providing the client resources.
9. Cost of food, amenities to an admitted patient with respect to the ailment(s) under which doctor and department.
10. Cost of infrastructure apportioned to every customer.
11. Cost/Benefit analysis per customer.
12. Quantity of social benefit offered by the facility in serving the community.
13. Number of social campaigns and awareness programs a facility undertakes in a neighbourhood in any season and in epidemic eventualities.
14. Quantity of emergency elements a hospital stocks and how many times or for how much money does the facility direct a customer to go outside the facility.
15. Rate of successful operations and treatments and rate of fully cured up customers.
There are many social acts or follow ups that a facility does need to undertake- it is hardly in vogue in heavily busy facilities but industry case studies have found a remarkable improvement of health in a neighbourhood with these post-care actions.
1. Period of follow up calls and taking down the case history and the follow up history well after the care provided. – this actually binds a customer to the facility in the most positive and desirable manner.
2. Linkage disease history- history of clients’ upkeep and what and how many new ailments crop up per what type of treated patient.
3. A dynamic map of the clientele done in a facility grows up to form a demographic map of the disease and their after-effects in a neighbourhood.
4. Alarm map of disease control in a neighbourhood or service area helps the government and public authorities to take pre-emptive action before a calamity strikes in.
5. General and Seasonal requirement of medicines, resources, testing equipments and blood requirements or live saving drugs requirements in a neighbourhood.
These results are the building pillars of the health care authorities and regulatory authorities.
The health governance in countries are still not prepared to handle these measures –be they any country with any type in the development scale. However owing to these measurable help provided by the DATA ANALYTICS tools slowly a trend is coming up and is surfacing and the awareness of the people in demanding as a mandatory information for dissemination, is making these efforts a necessity- so is therefore the growing need for proper, easy handling, fast and ad-hoc tools!
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