4 Ways Big Data Helps In Home Healthcare

As per a study, 94 percent of the respondents estimate that interoperability and next-generation data will enable surplus data sharing. The report also predicts that by 2040 technological, scientific, and interoperable data will transform healthcare. This also implies in how data impacts home healthcare.

Healthcare system gathers and stores immense data acquired from Internet of Medical Things, telemedicine platforms, EHR (Electronic Health Records), and public records. This data helps healthcare professionals to manage home healthcare effectively. This article highlights how big data helps in home healthcare.

Key Takeaways of Home Healthcare

Home healthcare includes a wide range of medical services provided at your house for an injury or a disease. Home healthcare is convenient, inexpensive, and as effective as care provided in a hospital.

Here are key takeaways of home healthcare that every patient and healthcare provider must be aware of.

1. Care for the Elderly

As per US Census Bureau, year 2030 will be an important demographic year of the USA as all Baby Boomers will be older that 65 years. Thus, the population is expected to increase at a slow pace and become ethnically and racially diverse. With aging population and rise in elderly people, home healthcare opens lucrative opportunities.

As per CDC reports, 41.9 percent of the people above 65 years experience obesity and 66.7 percent face hypertension. Reports claim that heart disease, cancer, and Covid-19 are leading causes of death amongst people above 65 years.

Home healthcare is recommended for the elderly as this eliminates the risk of exposure to harmful bacteria and viruses, and provides care of the weak ones.

2. Home Healthcare Services

Patients are provided with a range of healthcare services which include:

1.  Nutrition and intravenous therapy

2. Wound care for surgical or pressure sores

3. Injections

4. Monitoring unstable or serious health conditions

The goal of a home healthcare provider is to heal a patient and help them to gain independence. A provider assures that patients are able to maintain healthy condition and become self-sufficient.

3. Expectations From Home Healthcare Staff

Physicians order home care for the patient and refer a home health agency. This agency schedules an appointment and asks patients’ needs. The agency sends daily updates to doctors about progress and care. A home healthcare staff is expected to:

1. Check respiration rate, temperature, and blood pressure.

2. Regulate eating habits.

3. Administer medications and recommended treatments.

4. Check patients’ safety at home and update doctor for any emergencies.

A home healthcare staff monitors health through telemedicine applications, wearable devices, or remote monitoring. Health data collected from these platforms alerts caregivers during emergencies or any shift in vitals. Change in medications by doctors are alerted via data procured from these platforms too.

Role of Big Data in Home Healthcare

Healthcare providers use big data to solve issues and improve care for the patients. Below are a ways in which physicians use big data in home healthcare.

1. To Reduce Accidental Deaths

According to a report by CDC, West Virginia ranked first in the household injury with a rate of 38.4 percent, followed by New Mexico (38.2 percent) and Wisconsin (30.5 percent). The top five cause of accidental deaths in the USA are suffocation or chocking, falls, poisoning, burns or fires, and drowning.

Data on health conditions of each family member, surrounding environment, and residential place reduces the number of fatalities at home. Big data plays a crucial role in bringing deaths caused due to drug abuse under control.

As per a research, EHR data estimates 97 percent of people who are risk of using chronic opioid in the future. This data allows medical staff to provide education about opioid misuse at homes.

CDC reports that till April 2021, there were around 100,306 deaths caused due to drug overdose in the USA. The number increased from 28.5 percent from 78,056 deaths during the same timeframe the year before. Predictions gained from big data eliminates such deaths in households.

2. Patient Monitoring

As per a report published by Insider Intelligence, approximately 70.6 US patients will use remote patient monitoring solutions by 2025. Healthcare systems are turning to remote monitoring due to improved outcomes and reduced expenses.

RPM is a useful channel for home healthcare for developing relationship between caregivers, to gain access to real-time health data, and to manage chronic conditions from homes.

As per AAMC (Association of American Medical Colleges), the USA is anticipated to face shortage of around 122,000 physicians by the end of 2032. Reduction in the number of physicians presents an opportunity for the RPM solution to reach patients at every home and provide access to quality care.

Patient monitoring devices offers data on vitals, sudden shift in health, sleep patterns, medications prescribed, and more. This data is used to monitor patients at home, send alerts, schedule appointments, and keep track of high-risk patients in the vicinity.

3. Identifying Disease Patterns

Every disease has a pattern, for instance cold or cough are noticeable only during seasonal changes, dusty weather, or extreme temperatures. People suffering from dust allergies or asthma fall sick during this period.

Healthcare data offers clinicians access to patients’ illnesses, cause, and helps to identify a pattern before the onset of disease.

This aids providers to prepare a prevention and treatment plan for the disease. WHO collaborated with NREVSS (National Respiratory and Enteric Virus Surveillance System).

Around 300 clinical labs and 100 public health across 50 states participated in the virology surveillance for influenza. Data from the laboratories offer information on the intensity and timing of the influenza virus activity, thus, tracing out a pattern for the disease. Disease patterns can be detected and used for home care to maintain safety of the patients.

4. Preventing Hospital Readmissions

As per AHRQ (Agency for Healthcare Research and Quality), around $41 billion is spent on patient readmission within a month from discharge. Further, hospital readmissions leads to penalties and in 2017 more than 2500 hospitals were penalized for readmissions. Incorporation of home healthcare prevents hospital expenses and penalties.

Big data is effective in reducing readmissions. The University of Texas Medical Branch (UTMB) implemented a data analytics program for updating data and to provide it to healthcare professionals for gaining insights in unplanned readmissions, all-cause readmissions, and ED (Emergency Department) visits.

UTMB scrutinized data and filtered patients according to admission diagnosis, discharge date, unit, intervention, and provider. The data highlighted that readmissions was a common issue amongst patients with heart failure. The UTMB collaborated with outpatient care management to devise a plan for patients suffering from heart diseases.

Root cause analysis was conducted, and data obtained helped to reduce hospital readmissions by 14.5 percent and averted $1.9 million of readmission expenses. Decrease in readmissions and expenses paves way for home healthcare for acute and chronic condition patients.

Telemedicine applications prevents readmissions by offering features such as video consultation, chats, e-prescription, exchange of PHI, and patient monitoring. Patients can schedule follow-ups or book appointments from home, and can alert their physicians during medical emergencies too.

Big data is a useful tool in the healthcare industry and is expected to continue to rise in the upcoming years. Incorporation of artificial intelligence for big data analysis simplifies complex disease patterns and leaves no room for error.

AI algorithms are designed and taught complex disease pattern by entering vast data gathered from samples. Healthcare providers can benefit from such technology for enhancing care and outcome.