Introduction to Clinical Statistics for EBP – Morbidity (Frequency) Measures

abacus morbidity frequency

Morbidity measures are about Frequencies

This Podcast provides an introduction to clinical epidemiology, the foundation of clinical statistics that are used in evidence-based practice (EBP).  This podcast introduces morbidity or frequency measures of incidence, prevalence, and incidence density and why these concepts are important for advanced nursing practice. In addition, a brief overview of research designs to obtain incidence and prevalence data is included.  Scroll down to the podcast player to listen to the podcast. 

“Statistical thinking will one day be as necessary

for efficient citizenship

as the ability to read and write.”       


Samuel S. Wilks  (1951) paraphrasing H. G. Wells


Click Here to get Cathy’s Introduction to Clinical Statistics: Morbidity Measures Handout!
Epidemiology is derived from the Greek: epi – upon; demos – people; logos – thought. Epidemiology is all about observing the population to identify the types of health problems that exist in that population, identifying the risk factors that lead to these health problems, and then using these data to make recommendations for prevention and treatment.

Clinical epidemiology is the observation of specific patient populations using strong scientific methods.  Those evidence-based observations are used to guide clinical decision-making for individual patients. Therefore, one needs to be able to interpret the statistics used in clinical epidemiology to make sense of the evidence for practice decisions.

How Advanced Practice Nurses (APNs) Make Decisions Using Clinical Epidemiological Concepts

Clinical epidemiology and EBP are linked.  APNs need to keep up with the literature to keep their practice up to date so they can make accurate decisions for their patients. APNs need to be able to understand and interpret the clinical statistics in the results sections of the studies they are reading. APNs then apply these results to answer questions of diagnosis (which test is the best to diagnose disease X?), treatment (which intervention is most effective?), and prognosis (what kind of predictions can be made about mortality or quality of life?).

Nurse administrators need to understand clinical statistics also to help them make the case for decisions about staffing and management.

As advanced clinicians appraise the research literature, they need to ask themselves questions about the researcher’s methods and interpretation of the results.  They need to be able to differentiate useful from useless data so that they can prioritize and plan evidence-based health care, and so that they can evaluate the effect of interventions. They use this knowledge to compare level of disease among populations to help direct health policy decisions.

Quick Overview of Concepts Discussed in the Podcast

Morbidity refers to a diseased or unhealthy state of being. We can count the occurrences of a diseased or unhealthy state by focusing on specific conditions, symptoms or health problems in a population — that’s why morbidity measures are also referred to as frequency measures.

The question that morbidity measures answer is, “How common is disease X?” You can ask about the frequency of specific signs or symptoms or health problems, too. This question produces an occurrence rate – “How common is cancer in X population?”  “How common is shortness of breath in patients with Y?” Once you know occurrence rates you can anticipate the level of care that patients may require.

In healthcare, we talk about comorbidities all the time. Comorbid conditions are two or more disease states in an individual that are present at the same time. For example, we frequently see a patient with coronary artery disease (CAD) who also has hypertension or diabetes (or both!).

You frequently see morbidity linked with mortality (e.g., “M & M Rounds”).  Mortality refers to a state of living (i.e., everyone is mortal) and is another term for death. Predictive scoring tools (AKA disease severity scores), such as an APACHE, SAPS, or SOFA scores; Glasgow Coma scale, etc. estimate morbidity in terms of disease severity and are used to predict patient outcomes such as mortality.

The frequency of clinically relevant measures are fractions that are expressed as, in general, the number of people experiencing the event/outcome you are interested in divided by the number of people in whom the event could have occurred.

The morbidity measures I talk about in the podcast are incidence, prevalence, and incidence density. In this podcast I’ll define the terms and explain why APNs should understand these concepts for patient decision-making. Scroll down to the podcast player to listen to the podcast. Notes from this podcast can be found in the free handout.
Click Here to get Cathy’s Introduction to Clinical Statistics: Morbidity Measures Handout!


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Higginson, I. J., & Constantini, M. (2003). Epidemiology of symptoms of advanced illness. In M. B. Max and J. Lynn (Eds.), Interactive textbook on clinical symptom research (Chp. 19). Retrieved from

Jekel, J. F., Katz, D. L., Elmore, J. G., & Wild, D. M. G. (2007). Epidemiology, biostatistics, and preventive medicine (3rd ed.). Philadelphia, PA: Saunders Elsevier.

Macha, K., & McDonough, J. P. (2012). Epidemiology in advanced nursing practice. Sudbury, MA: Jones and Bartlett Learning.

Morbidity vs Mortality. (n.d.). Diffen LLC, Web. 16 Oct 2016.

Straus, S. E., Richardson, W. S., Glasziou, P., & Haynes, R. B. (2010). Evidence-based medicine: How to practice and teach EBM (4th ed.). New York: Churchill Livingstone.