The Indian healthcare system in India is poised for a data-driven transformation, delivering value based care backed by a well-defined digital and analytics strategy. One of the most data-intensive, data rich fields, data flows in from disparate sources, posing several challenges in data aggregation and data governance policies. The data deluge apart, healthcare sector is grappling with a demand for skilled data analysts, who can accurately leverage data to engage patients and drive operational efficiency.
Let’s define healthcare analytics and who the different stakeholders in it are:
Demystifying healthcare analytics is Rohit Kumar, cofounder of THB and the Chief of Analytics at the Gurgaon-based clinical research and data analytics startup. According to Kumar, Healthcare Analytics is a generic terminology and can be viewed differently by different stakeholders — a) doctors are more interested in clinical analytics, such as personalized treatment where data drives decision making and can suggest the next course of treatment for a specific patient that will give optimal result; b) for government or organizations it can imply using collated data to identify patterns in disease occurrence/recurrence or even treatment; c) for providers it entails automating tasks or minimizing errors by performing first level of diagnosis through algorithms or generating x-rays reports through image processing.
Role of Healthcare analytics in improving patient outcomes and paring costs
According to IBM, analytics in healthcare can play a key role in reducing high-risk healthcare problems and usher in evidence based personalized medicine. Some of the key areas addressed by healthcare analytics are:
- Bringing personalization and engagement into healthcare via patient centricity
- Analytics as an enabler for evidence-based medicine and disease prevention
- Building a pro-active, sustainable healthcare system and usher in accountability and transparency
- Providing supply forecasting, dynamic budgeting and reducing overall cost
- Promoting data-centricity and data literacy
How to kick-start a career as a healthcare data analyst in India?
Healthcare has emerged as a high-impact field with a deep emphasis on patient-centricity, and the field has seen a boom in US and Canada with the surge in genomic science (science of finding complex diseases with genetics) and computational medical treatment. Ideally, the first step is getting a masters in data analytics and start by gaining experience in healthcare sector. By and large, that’s the stock answer.
- One of the biggest challenge in healthcare analytics is unstructured data. Data comes in all forms and shape and there is always chance of new type of case coming up. So general tabular format of data may not work
- Also, variables needs to be taken in totality, few variables cannot give reliable answers. So the quantum of data especially breadth of data is huge. That needs models/algorithms to be flexible enough to incorporate new information and infer accordingly
- Data and medical may not always point to the same answer, and in those cases medical wins; so basic clinical knowledge needs to be developed. And there needs to be enough checks and balances to stop suggesting blunders.
- Since things get outdated fast in healthcare, one has to keep pace with the changes. by updated models periodically or incorporating machine learning early
Must-have skills required to make the cut
In this data-intensive field, data comes in from various sources, (such as clinical and patient data, HIS, ERP, LIS, CRM, PIS, and other tech systems). What kind of data gets high priority? According to Kumar, in healthcare, analysts have to work a lot with textual data of medicine, diagnosis, complaints.
Here’s how you can make a head-start by beefing up on these core areas:
- Textual analysis gets high priority and it is always good to have domain knowledge
- There is not a set coding language for this field but you need a language that will give flexibility in playing around with large and unstructured data. Python does that task pretty well
- For many medical problems programming language, R already has readymade libraries and it can help start things fast. If either data size is large or complicatedly structured, then you can explore big data solutions
- For journal / article statistics knowledge is a must
- Basic medical knowledge is preferred at least around problem statement
- Structuring data in usable format will require problem solving skill and open mind
Best Practices to keep in mind when working as healthcare analyst:
- Defining the problem statement precisely and craft a solution accordingly. Generic solutions normally don’t work in healthcare as margin of error is very small.
- Checking the accuracy and knowing the sources of data is very important. You should know which data is machine/system generated and which is manually entered (or say where data accuracy is high versus low)
- Privacy of data is of utmost importance. When doing analytics make sure never to use any Personal Identifiable Information (PII) of patient.
Emerging Job roles in Healthcare analytics
Clinical Data Analyst: Job roles spans abstracting and verification of data sets and performing analysis aimed at enhancing patient outcomes and clinical quality. Leading and educating the team about data collection and finding opportunities for data improvement is also part of the brief.
Healthcare Business Analyst: Job responsibilities span performing business analysis, clinical decision support and carrying out client interaction. The ideal candidate must have familiarity with medical terminologies and excellent problem solving skills. For the role of senior business analyst, proficiency in SAS, SQL, Hadoop and Hive is a must. Job responsibilities include using statistical techniques in customer segmentation and profiles, creating and reviewing models and providing technical leadership
While there is no definitive figure on salary in healthcare vertical, a quick glance at job board reveals that fresher with no industry experience get an overall package starting at INR 6 lakh, the figure goes up to INR 10 lakh (2+ years’ experience) and INR 15 lakh (5 years onwards).
Top Companies hiring Healthcare Analysts
McKinsey & Company: The global management consulting company is always on a lookout for analytical minds who are passionate about big data and are proficient in BI and ETL tools such as Jira, GIT, Ambari and have the knowhow of writing big data queries.
Accenture: This global software giant collaborates with several healthcare partners and is one of the best places to kick-start your analytics career. Perks include deploying the best state-of-the-art data driven predictive models to tackle business problems, teaming up with some of the best global clients in delivering competitive advantage.
Philips: One of the leading healthcare vendors, Philips is on a lookout for junior and senior data analysts who have the knowhow of managing analytical projects and can deftly manage high volume, complex data.
Indian Startups in Healthcare sector
Artivatic Data Labs Private Limited, is combining AI with genomic science to bolster the enterprises to tap into unlimited possibilities. According to the startup, the technology will revolutionize healthcare and will fuel preventive and predictive healthcare.
THB: Another startup driving clinical research backed by analytics is THB. The startup provides operational analytics tool and leverages clinical analytics for smart patient engagement.