How is Statistical Information Used in the Healthcare Industry

Statistical information can be used in the healthcare industry in order to understand health-related risk factors for various communities or demographic groups, to track and monitor diseases and health conditions, measure the impact of policy decisions and assess the quality of healthcare with a view to making changes and improvements. Decisions regarding public health policy are often made after the careful analysis of statistical information, but such information can also be highly useful when planning patient care and procedures in individual hospitals and other healthcare facilities.

Health statistics can be used as a form of evidence, to inform policymaking and to develop new initiatives that promote population health and well-being. Statistical information can vary greatly in terms of quality and relevance, so researchers and policymakers need to understand how to assess any information gathered in a systematic way, considering the source of information and the methods used in the gathering of scientific data or patient feedback. Policy decisions should be made based on reliable, high-quality health statistics and information.

How are healthcare statistics gathered?

Data regarding health and healthcare is gathered in a variety of ways and everyone involved in healthcare can potentially be involved to a certain extent. This means that training in this area can be invaluable when preparing new healthcare workers for the profession. Elmhurst’s direct entry Master’s in Nursing program, for example, includes a course focusing on Organization, Policy and Finance in healthcare systems. The course examines the structure, function and forces that shape US and global healthcare delivery systems and discusses policy decision-making in relation to advanced nursing roles.

Nurses in leadership roles, along with physicians, public health administrators and other healthcare workers, can be an invaluable resource when it comes to providing information and data that can be used to analyze current systems and develop healthcare policies that better serve the populations they support. Other sources of health data can include surveys and patient feedback forms, administrative and medical records, claims data from health insurance providers, disease registries and peer-reviewed literature. There are researchers, and even college students, at universities and private enterprises who focus exclusively on research into human health and these can be a good source of statistical information as well.

Within each category, there is a range of different types of information that can be gathered. When it comes to surveys for example, policymakers might consult The National Health Interview Survey which is an interview-based population survey, or The National Health and Nutrition Examination Survey which is also a population survey that uses a mix of personal interviews, physical examinations and lab tests. Alternatively, they might consult The National Ambulatory Medical Care Survey, in which researchers interview physicians and other healthcare providers to identify issues within healthcare systems that might need to be addressed.

There are pros and cons to each method of gathering healthcare statistics, and these should be considered when analyzing the information gathered and in particular when considering policy changes. Patient information is important, but it may be incomplete unless the patients have been subjected to in-depth interviews. Feedback from healthcare professionals is also useful but must be considered in the context of the region and specialty they are working in, rather than presumed to be universal. Research into health and healthcare systems should also always be considered in the context of the organizations carrying it out, especially if the funding comes from pharmaceutical companies or other enterprises that may have vested interests in producing a specific set of results.

What type of statistics can inform healthcare policy?

The National Library of Medicine identifies four main types of health statistics which measure four important types of information. These types of information are commonly known as the four Cs: Correlates, Conditions, Care and Costs. Each type of statistic can be important, but each is used in slightly different ways when it comes to healthcare analysis, decision-making and policy development.


These factors focus on how to measure the risk factors and protective factors that impact the health of individuals and groups. These can include social, personal and economic factors, such as income, life stage and education, as well as environmental factors such as air pollution and general living conditions. They also refer to behavioral factors such as nutrition, smoking, exercise habits, drug use and alcohol consumption.

Correlates, unsurprisingly, look at correlations between health outcomes and other factors. A correlation is simply a statistical measure that describes the size and direction of a relationship between two or more variables. If for example, you look at levels of alcohol consumption within a particular population and the number of health diagnoses for a specific disease in that population, you are dealing with correlates.


This factor is concerned with assessing how often and how badly particular diseases and health conditions impact a community. These are generally assessed by looking at both incidence, which is the number of new cases of a disease in a given population, and prevalence, which is the proportion of a population with a specific disease or condition. Together, incidence and prevalence represent measures of morbidity, or the disease state of a population. Conditions that are studied in this way include everything from Alzheimer’s Disease to HIV, to specific birth defects or seasonal flu.


Statistics related to care examine how healthcare is delivered to the people and populations who need it, to treat disease and illness. This can include looking at factors such as who does or does not have access to healthcare, the quality of the care people receive, and other data which can be used to assess impacts on patients, providers, diagnoses and medications, as well as factors such as patient outcomes and satisfaction.

Researchers concerned with care statistics will often examine data regarding either a specific group of patients or perhaps regarding a group of healthcare providers in a certain location. One major factor that concerns researchers focused on care, is the issue of health inequity, or health disparities. These are differences based on historic and systematic social inequities such as race, ethnicity, gender and gender identity, disability status and sexual orientation. Access to care can also be restricted by issues of infrastructure, such as public transport and community healthcare facilities.


Unsurprisingly, researchers in this area are generally trying to obtain and analyze information on how much healthcare costs, and why. They may be engaged in assessing the direct economic costs of health care, such as the price of health insurance and the factors that drive growth in national or local healthcare spending, or they may be looking at the economic and societal costs of health care and poor health in certain populations.

How is statistical information used to inform healthcare policy?

Statistics can assist policymakers in identifying existing economic, social or environmental issues that impact public health and that can potentially be addressed by changes in public policy, legislative changes, education campaigns or other initiatives. For example, statistical analysis could identify issues concerning the aging of the population, the spread of certain diseases, the incidence of birth defects or childhood disorders, the decline of health and well-being in specific age groups or other sectors of the population, or preventative health measures that could be put in place. The following are just some of the ways that statistical information can be used in healthcare policy.

Disease prevention and control

As already mentioned, statistical information is often gathered on the incidence and prevalence of a variety of diseases, from HIV to seasonal flu, and from dementia to cancer. In studying these conditions, researchers will often be looking at ways to control, prevent, treat and manage these conditions, and also at ways to support people who suffer from them and their loved ones.

Preventative care can ease the burden on healthcare systems and improve the quality of life of patients, helping to prevent incidences of illness, the recurrence of some diseases and patient readmissions to healthcare systems. Preventative measures can also promote better patient outcomes, increased overall health and wellness and lower health insurance costs, especially when it comes to high-risk patients and those managing long-term or chronic diseases.

Preventative healthcare can include cancer screenings and other routine health screenings, well-child visits, vaccination programs and initiatives that focus on education in a wide range of health-related areas such as nutrition, drug and alcohol use, sexual health and prenatal care. Other preventative programs might simply focus on supporting patients in quitting smoking or developing appropriate exercise regimes or stress management techniques.

They could also focus on general safety, injury prevention, basic first aid or the use of publicly available medical equipment such as defibrillators. Research can also identify risk factors that could have previously gone unnoticed and promote more regular health screening or lifestyle changes to those at risk, as potentially effective preventative care.

Improving patient care

Statistical information can enable decision-makers in health systems, along with clinicians and other healthcare staff, to make better care decisions for patients. Research involving patients who are managing chronic health conditions can ascertain what types of care facilities and other resources these patients need and what sort of support can be helpful to them and their families.

Simple advice and extra support for specific patients, such as those going through pregnancy and childbirth, or raising children with chronic conditions, can be offered in order to promote better outcomes for all involved, and treatment plans can be adapted as statistics show which types of plans seem to work best for which patients and populations.

Planning for extra care facilities, care in the community initiatives, and other support and resources, can mean that the elderly, including those with dementia, the disabled, and their families and carers, have the right sort of structures in place to enable better and more effective patient care. All these things can lead to a better quality of life, improved health and well-being and even longer and more productive lives for various groups of patients.

Better health management of vulnerable populations

Certain populations may require more proactive health management than others. Population health management is essentially the process of changing and adapting policies and practices to improve clinical outcomes for a specific group of people. Using statistical information, certain populations such as the very young, the very old, those with chronic conditions or specific risk factors, and those living with disabilities, can be better supported by healthcare systems and related services.

This can be done via better care coordination, more tailored treatment plans, support groups, education, community adaptations, better resource provision, and other initiatives. This can lead to improved patient engagement and outcomes, and a healthier population overall.

Lowering healthcare costs

Statistical information can be very useful when it comes to identifying factors such as wasted resources, underused services and inefficient processes that can drive up the cost of effectively delivering healthcare services to specific areas and populations. In addition, the above-mentioned factors, such as putting in place effective preventative health initiatives, can reduce costs in the long run, by preventing disease, reducing treatment needed due to early detection, or limiting the impact of a health issue due to early intervention.

Identifying, reducing, or eliminating risk factors, along with proactive health and safety initiatives such as vaccinations or education around home safety and injury prevention, can in fact prevent many diseases and injuries completely. In turn, this can significantly reduce healthcare costs, and free up clinician’s time and resources to enable a stronger focus on the patients who do require a high level of care.

The gathering and analysis of reliable statistical information can have a significant impact on care, costs, and patient outcomes, so it is vital that we continue to put in place easy ways to attain it. This can involve the training of physicians, nurses and other healthcare staff, to properly record and use important information. It can also involve the funding of medical research that can inform local and national policymaking and creat a culture in which we facilitate the use of such data to continue to improve healthcare systems at every level.