Running healthcare service business operations is akin to conducting an orchestra – ensuring that the myriad of talent, equipment, infra etc. comes together to deliver good patient care services – good medical outcomes with good hospitality services, food and a superb overall experience. And all this, with a smile and ensuring that the people undergoing the treatment also smile so we need to ensure that there is optimal pain management – for the patient, as well as for all the myriad of talent delivering these services, and of course for all the business stakeholders… I am taking the liberty of calling operational analytics the pain management system for healthcare operations – allowing for spewing up the right data for data driven decisions.

Analytics is a critical business tool for every business. The complexity may vary from industry to industry, also to the level of detail each business manager may require. Good analytics can propel the business in the right direction. While analytics typically has been around for most industries for multiple decades now, the operational analytics in healthcare has generally lagged. Even today, while the bigger corporates do indulge amply in this, the smaller businesses are yet to take advantage of this, or even fully understand the need to use this at all.

Having worked with different types of institutions ranging from big corporate chains to smaller regional ones struggling to make a mark, kicking off green field operations, taken over brown field hospitals, kick starting new concepts or pulling along the laggers to perform, I can say with confidence that each time even a raw form of operational analytics applied went a very long way in streamlining operations and get more than just a few smiles on the faces of patients, employees and stakeholders alike. Especially as they realised how things became easier for them to initiate activities or take decisions that were well informed. These ‘well informed’ decisions enabled these leaders to empower their teams to work with clear objectives and with reason.

There is another reason that employees work happier and also leave a trail of patients and their families with a good experience when the leadership teams take advantage of operational analytics. Good application of operational analytics also allows for efficient operations. In the traditional sense we all read operational analytics as decent business metrics. Underlying these good metrics is an efficient flow of work which is enabled by the data driven decision making and alongside that building on process flows that remove the obstacles the teams face while delivering their tasks. When the work flows are easy for an employee, the task gets done quicker, with ease with better outcomes both quantitatively and qualitatively. But this does not just happen. We need to make it happen by constantly keeping an eye on the obstacles and not just overcoming them when these happen, but by redesigning the on-ground process flows to negate the obstacles. To make this happen, of course, needs a lot of creativity, tenacity and motivation. But the results can be outstanding. Each storey you read about any business’s big stride or turnaround, has a storey which underlines these principles.

Of course, analytics for healthcare services can be complex, a little more complex than most industries. Being a manpower intensive industry where the outcome depends more on the manpower than on the machines and equipment, the skill of each hand (be they nurses, technicians, doctors or admin staff), especially on the shopfloor, makes a huge impact on the outcomes – clinical, overall experience, as well as financial. The operational analytics, to be effective, needs information of varied types within each of the clinical and non-clinical domains along with market trends and inputs, to come together coherently to allow for tactical decisions and actions which then adds up to business intelligence thrown up for inputs for strategic direction. In all of this what needs to be considered is also that often a lot of data that needs to come together is very difficult to measure, for example wait times of different sorts - did the patient walk in well before the appointment time, after meeting the doctor, how much time did the patient wait to get the investigations done and whether this was voluntary or involuntary, so on and so forth. Each of these little data points needs to be collated efficiently with other staffing related data which may not be captured by the same source, to determine how the process really work and was it effective. And this for the multitude of things that go on for a hospital. And all of this is important because it is these factors on ground that determine whether your patients went back with a satisfactory experience, which in turn defines how the brand that you have built, or building, is being seen. I would stress here on one thing. Operational analytics is impactful when accompanied by good communication and action on ground.

Most hospitals do not have the luxury of purchasing sophisticated systems that can spew data with ease. But all is not lost even in these cases. There are ways that a systemic way of collecting data can be easily converted to good information. The key lies in the the implementation of the reporting system. Whichever system or methodolofy is deployed, it is very essential that this does not simply redeem itself to become a data collection system. Each member of each team needs to understand what the data states and what we need to read through. Only then operational analytics can be impactful.

A key point to remember through all of these practises. While technology has made life easier and more and more data driven, the one thing that these analytical tools cannot measure is the effect of the touch and feel and interactions with the patients and their families. We need to view this data through a humane lens of how alive our communication is through each touch point. This is what is the final driving force to better operations and to finally better our profit and loss statements.

Issue 64--