Healthcare data analytics

/in , , , , , /by

Bioepinet helps clinics, hospitals, pharmaceutical companies, and other medical-based institutions generate, collect, consolidate, and analyze data in the healthcare industry. We can help your institution or organization come up with strategic ways to analyze even a massive amount of data, whether collected about your patients or in-house processes.

Even if you already have an in-house team of medical or health data analysts, your business can benefit from the experience of our highly trained and experienced biostatisticians and clinicians. To schedule a consultation, contact us. Or you may continue reading to learn more about our healthcare data analytics solutions.

 

What is Healthcare Analytics?

Healthcare analytics means the analysis of current and past healthcare data coming from sources such as hospital records and results of medical examinations. The analysis helps health institutions predict trends, improve patient care, and make good management decisions.

Healthcare data as a form of big data comes from various sources, including devices, hospital records, patients’ medical records, and medical examination results.

Healthcare data is complex. This is not only because it comes from many channels but also due to the data having different formats. This is why healthcare big data requires sophisticated technology to analyze. Besides, the collection and use of this type of data have to comply with government regulations.

Whether you need help collecting and analyzing clinical healthcare data or are looking to put in place a healthcare data analytics suite that is right for your business, know that our biostatisticians and scientists are always available for help. Contact us for more information about our biostatistics consulting solutions.

 

Why Healthcare Data Analytics?

Without data analysis and analytics in the healthcare industry, it could be difficult or even impossible for hospitals and other medical-based institutions to improve their business, healthcare, and management needs.

How many patients are more likely to come into your health institution at certain hours of the day or days of the week can be determined using insights from data from a healthcare analytics suite. With this type of information, it becomes easy for shift managers to determine the number of workers to be on duty at any given period. Data-driven decisions like this can help organizations reduce or even eliminate unnecessary labor costs.

Healthcare data analytics is important to improving patient care. By analyzing industry data alongside the digital record of every patient, it becomes easy for medical-based institutions to easily identify potential health risks for patients. Also, healthcare analytics can help healthcare managers schedule optimal medical appointments. With the analytics, they can match physician records with patient histories. This can assist the managers in scheduling the right doctors or professionals for individual clients.

On the management side, data from a healthcare analytic suite can help any business’ health care management team do its day-to-day activities effectively. These service professionals, for example, can make better budget decisions, plan ways their facility can meet established goals, make decisions about performance evaluations, to mention a few.

Other areas where healthcare analytics are important includes:

  • Electronic health records.
  • Real-time health alert.
  • Enhanced patient engagement.
  • Predictive healthcare analytics.

Because there are several ways in which healthcare data can help your institution’s needs, your clinic, hospital, or health institution needs to use the right health data analysts. Our experts will not only help you analyze your data but also see to it that you’re collecting the right data the right way.

 

How we Can Help You With Healthcare Analytics

At Bioepinet, we have highly educated, well-trained, and experienced medical data analysts providing innovative solutions. Our service experts are familiar with today’s always-improving technologies. This helps them to not only analyze data and convert them into relevant critical insights, but also assist them in carrying out research studies and clinical trials that help organizations draw conclusions or make predictions.

We also have experienced scientists who come to work every day to advance medical science through comprehensive clinical research solutions. Remember that it is important to collect data the right way. Wrong data collection approaches can lead to inaccurate data analysis. When you work with our consulting experts here at Bioepinet, whether for observational studies or clinical trials, be assured of proper data collection and analysis.

We can come into your organization for clinical trials, determining whether a surgical, medical, or behavioral intervention is working for intended patients. Our biostatisticians and medical data analysts always work together to see if a new drug, diet, or medical advice is safe for your patients. Whether for our biostatistics consulting or medical healthcare analytics, we’re always available to assist.

And if you would be needing our help for observational studies, our experts can help you collect the right to data through medical tests, exams, or questionnaires about lifestyles and other factors.

 

Why Choose Bioepinet

You probably might have come across different healthcare analytics companies on Google or the internet. Finding us, however, is never a coincidence. We have years of experience helping healthcare institutions with medical and clinical data collection and analysis, doing so at the best possible standards. Thanks to our biostatisticians and scientists who are hard at work and use strategic approaches to data analytics.

So don’t keep searching online or looking for recommendations about clinical, biostatistics, or medical analytics solutions, Bioepinet is the right consulting company to call. Our professionals work as a team to ensure the requirements of every client are met. We understand that the needs and requests of every organization vary. So, we carefully listen to and take note of all the details of your medical or clinical data analytics project before getting started.

If during the project your needs change, you can count on our knowledgeable experts to make necessary adjustments so the output or result could be exactly what your business needs.

To enjoy the professional services that always make our clients use our services over and over again, contact us today. Our experts are always available and ready to speak with you about your needs.

Biostatistics and statistics

/in , , /by

Statistics is the mathematical science that is concerned with data collection, analysis, and interpretation. Biostatistics is the application of statistical methods to a broad range of biological topics. This includes the design of biological experiments, the gathering and evaluation of data from the experiments, and the evaluation of the outcomes.

The amount of available information to inform healthcare choices and decisions and the application of data science in the healthcare industry has become important in recent years. Biostatistics services play a primary function in the public health sector, letting scientists support choices made regarding patient care and enhanced focus on medical research and comprehend all the presented data. Besides, it is crucial to understand the statistical and scientific principles behind the decision-making and the importance of biostatistics in health delivery and patient care.

What is biostatistics? This is the discipline of study that connects biology and statistics by applying traditional statistical methods used in clinical trials and public health. Biostatistical consulting involves expert professionals behind the science, establishing connections to determine, for instance, whether a recognized treatment is functional or the cause behind an identified illness. Technically, biostatistics consulting converts available clinical trial and public health data into meaningful information.

Furthermore, through the application of biostatistics, clinical researchers are capable of drawing inferences from collected data. Biostatistics includes clinical research in a vast range of ways as a collaborative work from the beginning to the end, including but not limited to the sectors below.

  • Design and development of clinical research frameworks. In an ideal setting, biostatistics services are required in a clinical research study at the start to improve the clinical creation team through study objectives, strategies of data evaluation, and general study design to enhance study results. A primary element of the study design, for instance, is the size sample, a sector of specialization for any biostatistics expert. A significantly small size sample will lead to an underpowered study that can result in no relevant conclusions. In contrast, a large sample size can be a waste of money and time.
  • Data management and monitoring. Biostatisticians support the development of data management strategies and determine areas of prospective vulnerability in data gathering. Biostatisticians also develop a high standard of validity in the collection and evaluation of data.
  • Data evaluation and reporting. Biostatisticians take data gathered as a section of a clinical research examination and apply statistical methods to summarize that information and report the presence of any strange data patterns or variables. Statistical methods and a description of the technique involved, visual representations such as tables or graphs, and data interpretation are later included in clinical study reporting, ideally as a portion of the collaborative work between biostatisticians and researchers.

The implementation of biostatistics in the healthcare sector keeps growing together with innovations in the industry. Anywhere data-based decisions can:

  • Support the general public health and other related policies
  • Improve the efficiency of healthcare programs
  • Result in enhanced healthcare effectiveness and patient outcomes

The field of biostatistics is essential, and BioepiNet offers the best clinical data science among other biostatistical services; improve your data gathering and evaluation.

What is statistics? This mathematical branch deals with gathering, compiling, evaluation, interpretation, and presentation of data. Statistics can be used solve a social, industrial, or scientific problem. The statistician starts with a statistical model or study population. Population might include a broad range of topics, such as each atom making up a crystal or everyone living in a particular country. Statistics consists of all data aspects, including the planning of data gathering based on the design of experiments and surveys. Besides, when census information cannot be gathered, statisticians collect information by creating detailed experiment surveys and design samples. Representative sampling guarantees that conclusions and inferences can be generalized to the whole population. In an experimental study, individuals are assigned to two groups: a control group and a treatment group. The treatment group is exposed to a treatment or intervention whereas the control group does not receive that specific treatment. Contrary, an observational study does not include treatment or intervention assignment; we follow individuals without assigning them a treatment or intervention.

Statistical firms typically apply two primary statistical methods in data analysis: descriptive statistics that summarize information from a sample using frequencies, means, and standard deviation; and inferential statistics that draw conclusions from data that is subject to random variation such as sampling errors, measurement errors, among others. Descriptive statistics are descriptive coefficients that summarize a particular set of data that can represent the whole or a portion of a population; they are broken down into measures of variability (spread) and measures of central tendency. Conclusions are drawn based on a probability theory framework that focuses on dealing with random phenomena analysis.

Furthermore, statistical consulting companies use a standard statistical process to test the connection between two statistical data sets and synthetic data drawn from the preferred model. A hypothesis is given for the statistical association between the two sets of data. This is compared as an option to an idealized null hypothesis of no connection between the two sets of data. Rejecting the null hypothesis is conducted by applying statistical tests that can quantify the aspect in which the theory can be proved to be false, based on the data used in the research. Besides working with the null hypothesis, two fundamental forms of errors are noted: type I errors and Type II errors. The former is a “false positive,” which is a falsely rejected null hypothesis; on the other hand, the latter is a “false negative,” which is when the null hypothesis is not rejected. The real difference between the population is missed. Many problems are connected with this type of framework, ranging from getting an adequate size sample to specifying a sufficient null hypothesis.

BioepiNet is the perfect company for you for any biostatistics and statistics services; this where accuracy meets value!