Big Data has been buzzing for the past several years and many industries have successfully harnessed its analytical powers. Not so healthcare which is just beginning to make use of the power. Service providers are now beginning to help healthcare professionals structure and analyze their data. Healthcare data is unstructured, non-standardized, and highly sensitive. Sourcing such data, structuring, analysing and presenting it in a form that can be understood by the user is a great challenge.
Despite the sensitive nature of healthcare data, Big Data analytics can help healthcare in many ways.
1. Smart Phones
Smart phones used as pedometers and calorie counters are just the tip of the iceberg. One now hears of wearable devices such as Jawbone, FitBit and GearFit that allow you to upload data directly for compilation. Word has it that mobile diagnostic tool boxes are just round the corner where you can share your statistics with your doctor who can then advise you based on the data you upload. This constant interaction will help early detection and thus prevention.
2. Predictive Modelling
Once you upload your data, it can be compared to other similar data and predictions can be made regarding the current and future state of your health. The Pittsburgh Data Alliance has set up a program where data from various sources such as insurance records, wearable sensors, and social media is assimilated and analyzed to design a comprehensive healthcare package for an individual. Such a package could be effectively put to use in both private as well as a hospital practice.
3. Research
Research data comprises a major portion of healthcare data. The Obama administration launched a Virtual Research Data Centre through CMS (Centers for Medicare and Medicaid Services) as a part of its Big Data initiative. Researchers can now access, manipulate and analyze research data using their own devices and tools. This has helped considerably reduce the cost of research. It is also easier to rope in professionals for analysis and structuring since digital data is highly portable. EHR (Electronic Health Records) has further facilitated research since physicians can submit data electronically.
4. EHR
While there are many who refute it, EHR has many more advantages than submitting data for research. EHR or Electronic Medical Records (EMR) as they are also called can greatly improve efficiency. Physicians, nurses, and other hospital staff can easily access all information about a patient from a single source. This one single source need only be updated and can alert those concerned about potential health threats. It also eliminates any communication gaps that may exist in manual record keeping. There are of course many counter arguments to this and many of them are valid arguments. However, as with any new technology, experience will help resolve many issues as well the economical and procedural advantages of EMR cannot be denied.
5. Private Practice
Doctors in private practice benefit from Big Data in many ways. Not only does Big Data facilitate accounting and turnover, it also assists doctors in the decision making process. Having all the patient’s health related information presented in a structured form makes it easier for doctors to assess the situation and advise the patient. Physicians may also be able to predict likely outcomes of symptoms and take preventive action. With the next generation becoming more tech savvy than the last, doctors better strap up their devices.
6. Remember Doctor on Call?
Remember the days when we talked about Doctor on Call? The phrase is now changing to Doctor Online. With patients being more aware and knowledgeable, they can discuss their conditions with doctors online and get Eprescriptions. It would not be unrealistic to predict an “online clinic” where doctors “listen” to the patient’s complaints and prescribe medications based on emailed medical history.
7. Better Nursing Care
EMR would facilitate better nursing care as nursing data such as family history, family response to health issues, community care, psychiatric and emotional data and much more. Doctors’ orders can be entered online for the nurse practitioner and discussions regarding treatment plan may be discussed on conference calls. HIMSS (Healthcare Information and Management Systems Society) initiated a workgroup under the name of Big Data Principles Workgroup and presented the Guiding Principles for Big Data in Nursing. This and other initiatives in the area of Big Data in nursing have been underway in the recent past.
8. Wearables
David Patterson of Emdeon believes that healthcare wearables would be a big step towards improving the health of the general population. Patients can monitor their own health. The Consumer Electronics Show in Las Vegas last year introduced devices that can track blood pressure, oxygen saturation, heart rate and other vitals. It is estimated that by 2018 the total number of wearables in use will be more than 125 million. The challenge lies in setting up the network and backend support to process the data.
9. Remote Monitoring
Eight million people were being home monitored by the end of 2012. Home monitoring can reduce costs and free up beds for the critically ill. For example, the cardiac cast can automatically transmit data to remote servers. In case of a problem the patient can be contacted or reached by EMTs.
10. Personalized Medicine
Tailored treatment plans and medication is increasingly becoming a reality saving dollars and adverse effects of unnecessary medications. What is required is a tool that can analyze health data and match it to pharmacological data at the level of individuals.
Concluding Remarks
Healthcare has begun to adopt Big Data in a big way. What Big Data can do for healthcare is beyond imagination. But there are many challenges along the way. The first is the unstructured and non-standardized nature of healthcare data. Secondly, regulatory compliance, ethics, and confidentiality must be met. Not all patients are willing to make their health data public. There is the additional concern of recursive errors. Once some wrong data enters the system it is there to stay. Despite these challenges, and considering the level of automation that Big Data can bring, one may well see a day when patients medicate themselves without ever seeing a doctor.
