The healthcare industry is a vital part of every state and country. Every leader's primary initiative is to ensure its citizens' health and well-being by providing them with plenty of facilities and easy access to healthcare. The world is booming with technology, and many aspects of our lives have turned more digital than manuals. We control our house's lights through a mobile application. The stores are using gadgets to scan and generate the grocery bill that we bring to the counter. The information that we are feeding into our computers enters into a large pool of data.
The world has become so digital that every minute the data pool is getting bigger and bigger. In the last two years, around 90% of the world's data got created. Every day the data that generates is about 2.5 quintillion bytes, which is way beyond our measurement. The same number of data gets generated, enlarging the data pool day by day. Big data has changed the way we manage and share information within and across any industry.
Like many other industries, the healthcare industry has gone digital, and data analytics is playing a substantial role in enhancing quality. Big data in the healthcare industry refers to the massive volumes of information created due to the adoption of technologies used to store patient data and record management. It also helps in managing the hospital's performance that is otherwise too complex for other technologies.
Data analytics's application to the healthcare system has brought many positive changes in the hospital's performance, and patient satisfaction—the vast quantities of information produced were later analyzed using different technologies. A healthcare data analyst plays a significant role in enhancing the healthcare industry's efficiency by performing statistical analysis on a large dataset. They also extract and retrieve information that can benefit the organization in the longer run.
Besides extracting data, the following aspects highlight a data analyst's role to enhance healthcare efficiency.
- Improved staffing
One of the biggest questions faced by shift managers working in a hospital is about the number of people on a shift. Putting too many people on a shift will add the risk of having unnecessary labor costs. On the other hand, fewer workers on a shift will deteriorate the customer care quality leading to poor patient outcomes. With healthcare data analytics, you can search between different resources and get an estimate of how many patients are likely to visit hospitals in a day or at a particular time of the day. Before visiting a doctor, we schedule an appointment. You can gauge the number of patients going to visit the hospital other than those visiting in an emergency. Knowing the estimate of visiting patients can help you decide the number of workers you need in a shift ensuring the quality of services to be intact. With data analytics, the researchers have identified the admitting pattern of patients in the hospital. This information has provided more opportunities for hospital management to ace their services.
- Updating health records
Previously when the technology was not much trending in the healthcare industry, the record maintenance was manual. A person has to take the pain of maintaining the files keeping them in their racks, and looking for the ones required. One of the best data analytics features is that it has transformed the record maintenances and have introduced electronic health records. With EHRs, every patient has their digital records that include their demographic, medical history, allergies, and lab tests. EHRs can be useful in triggering alerts and warnings to patients to get their new lab tests done. They can also come in handy in tracking the patient's prescriptions records assessing if the patient is following the doctor's order or not. Many hospitals are still struggling to incorporate the EHRs in their systems, depending on their technology updates and the flexibility of resources.
- Identifying high-risk patients
Data analytics can also work as predictive analytics to make useful predictions regarding patients and their hospital records. The effective use of data analytics can predict high-risk chances among patients and assist in chronic disease management. In case of emergencies, the patient's readmissions frequently happen, leading to hospital management's inefficiency. Data analytics can help enhance care by predicting the high-risks earlier, enabling the hospital staff to provide personalized care and take measures for the disease's prevention before going out of hand.
- Real-time alerts
Another wonder of data analytics is that it can send real-time alerts to the patients. The customer decisions support software analyzes the medical data on the spot, assesses the risk factors, and alerts healthcare professionals while making their prescriptive decisions. The data analytics are crucial in determining the databases to extract past and present information about a patient. It also sends schematic predictions and alerts healthcare professionals to improve their treatment methods.
- Increasing cybersecurity
As the hospitals are recording sensitive information about their patients, updating their records, personal and medical details, there is a high risk of security breaches. Big data can eliminate such risks by predicting the possible attack and alerting the data analysts to prepare the counter strategy to prevent data. Using data analytics to study the history of cyberattacks, the number of attempts made, and the system planned can help analysts devise a more robust plan to overcome this hurdle.
- Removing medication errors
Dealing with human life and helping them to ease the pain is rewarding but risky at the same time. A single error made in the medication or recording the taste can alter the whole treatment course, endangering the patient's safety. With data analytics, it is far easier to research a hospital's database, assess the patient's medical records, and analyze their improvement history. Suppose there are some recorded incidents of side effects of reactions. In that case, big data can send details to the doctor about particular medicines that may not work for the patient.
Conclusion
Technology has its advantages and drawbacks, but it is more useful in the healthcare industry than dangerous. With skilled individuals appointed to analyze the databases and train health professionals to use such technology, the hospitals can do wonders. Automated records have not only eliminated the human errors that were frequent when recording the information manually. Still, it has also changed the doctor's way of prescription. Data analytics have also increased customer engagement as people will rely more on automated reports knowing fewer errors. We are more likely to revisit a hospital after a better experience. We will also recommend it to our loved ones. Our recommendations to tour loved ones are beneficial for them and benefit the hospital as they boost their revenue.
