Components of a Complete Health Assessment

A complete and holistic health assessment includes the:

  • health history
  • physical, psychological, social and spiritual assessment
  • consideration of laboratory and diagnostic test results
  • review of other available health information.

First impressions

Assessment begins as soon as you meet your patient. Perhaps without even being aware of it, you’re already noting such aspects as their skin colour, speech patterns and body position. Your education as a nurse gives you the ability to organise and interpret this data. As you move on to conduct the formal nursing assessment, you’ll collect data in a more structured way. The findings you collect from your assessment may be subjective or objective.

Group dynamics

When evaluating the assessment data, you’ll start to recognise significant points and ask pertinent questions. You’ll probably find yourself starting to group related bits of significant assessment data into clusters that give you clues about your patient’s problem and prompt additional questions. For instance, if the data suggest a pattern of poor nutrition, you should ask questions that will help elicit the cause, such as:

  • Can you describe your appetite?
  • Do you eat most meals alone?
  • Do you have enough money to buy food?
  • On the other hand, if the patient reports frequent nausea, you should suspect that this may be the cause of his poor nutrition. Therefore, you’d ask questions to elicit more information about this symptom, such as:
  • Do you feel nauseated after meals? Before meals?
  • Do any of your medications upset your stomach?

History

The nursing history requires you to collect information about the patient’s:

  • biographical data
  • current physical and emotional complaints
  • past medical history
  • past and current ability to perform activities of daily living (ADLs)
  • availability of support systems, effectiveness of past coping patterns and perceived stressors
  • socioeconomic factors affecting preventive health practices and concordance with medical recommendations
  • spiritual and cultural practices, wishes or concerns
  • family patterns of illness.

Biographical data

Begin your history by obtaining biographical data from the patient. Do this before you begin gathering details about his health. Ask the patient their name, address, telephone number, birth date, age, marital status, religion and nationality. Find out who the patient lives with and get the name and number of a person to contact in case of an emergency. Also ask the patient about their health care, including the name of their general practitioner and any other health care professionals or members of the interprofessional team they have contact with, for example an asthma nurse specialist or social worker.

If the patient can’t give accurate information, ask for the name of a friend or relative who can. Always document the source of the information you collect as well as whether an interpreter was necessary and present.

Current complaints

To explore the patient’s current complaints, ask the patient about the circumstances that have brought them into contact with the health care team. Is there an aspect of their health that is concerning them or proving challenging? Patient complaints provide valuable data immediately. When you explore these initial complaints, you may uncover crucial additional information.

Insights Into Predictive Analytics and Population Level Health

In the introduction to the November 2014 issue of HealthLeaders the editor states that “individual hospitals and health systems can analyze their own data sets to find opportunities to save money and provide more effective care for individuals or groups of patients.” I have found in my work with data that there are tremendous opportunities for healthcare providers to greatly improve the lives of patients while using fewer resources through the use of predictive analytics and population level management systems. By examining data from a global or population level and using predictive statistics to identify key performance indicators providers can improve the outcomes for many of their patients.

What are the key processes that can provide such success in providing high value outcomes? I would like to illustrate how a health system can leverage data to improve care. Much can be done with basic databases and advanced statistical analysis. A system does not need to invest in expensive IT solutions to achieve good results, although for larger systems such an investment would be worthwhile, I believe.

The first step is to set goals for the analysis and population level management. It is not enough just to collect data and present it to physicians. The goals should also include action steps. One goal, for example, could be to prevent patients of primary care physicians identified as being prediabetic from progressing to type 2 diabetes. This goal identifies a population-patients with prediabetes-and an action-keeping the patients from advancing to type 2 diabetes.

Goals should focus on preventive activities or strategies. These can be at the primary level, secondary level or tertiary level. Primary preventions strategies try to prevent the occurrence of disease or increasing resistance to disease. An example of this is having as many patients as possible have flu vaccinations. Another is counseling teens to avoid smoking and using alcohol.

Secondary prevention strategies seek to identify indicators or test results in patients that would predict the likelihood of developing a disease. For instance, a provider group could try to identify all patients with hypertension in order to provide services to prevent coronary disease or strokes.

Tertiary prevention strategies seek to prevent more serious outcomes for patients with serious conditions, such as type 2 diabetes. The goal here is help patients manage their condition so as to keep them from needing emergency medical help or from being readmitted to a hospital.

Once a goal(s) is set, a healthcare system needs to collect baseline data for future reference in data analytics. For instance, for systems with a goal of keeping patients with prediabetes from developing type 2 diabetes, data should be collected that indicates what percentage of their prediabetics developed diabetes. One could look at data over a one year period or a shorter time if the patient population of prediabetics is large enough. Another approach to this goal that would generate more useful data would be to track the fasting glucose level of patients with prediabetes. Such data would indicate how variable this measure is in patients, which would be an accurate indicator of how well patients and physicians are reducing the level of this indicator or at least keep it from getting worse.

As data is being collected and analyzed for variability and trends, clinicians along with support staff such as nurse coordinators should determine a variety of prevention strategies that can be employed to improve the outcomes. Administration should be involved in these decisions as their input on the costs of providing such services is important, especially in a value-based reimbursement environment. Strategies can be drawn from best practices research and from insights gained from clinician experience.

It is important that several strategies be employed concurrently in the designed prevention services. From the perspective of data analytics trying one strategy at a time provides much less predictive power than employing several at a time. Analyzing the interaction of several strategies through complex analysis provides much more useful information that can be used to provide better care.

For instance, strategies for the treatment of prediabetics could include having patients test their glucose level every three months, referring the patient to nutrition services if their payer will cover it or if there is a nutritionist on staff, have the patient join the YMCA as the Y has a nationally recognized diabetes prevention program that will work with physicians and providers, and have the patient keep a journal of their diet and exercise. Patients can even be asked to report selections from their journals through a patient portal, as directed by their physician.

After a sufficient data is collected as determined by a data analysis professional, it should be analyzed to determine what progress is being made in achieving the set goals. Using predictive analytics not only can progress be determined but also the most effective strategies or treatments can be identified that lead to the outcomes being measured. For instance, in the prediabetic example it may be determined that the best strategies are having the patient join the YMCA preventive program, report on his/her progress through a patient portal and interact with the nurse coordinator after each of the glucose tests.

Once the predictive analytic results are in the information should be shared with the clinical staff, including physicians. The results should be discussed in a group setting and ways to implement the new findings of the analysis should be discussed. Not all clinicians may be on board to modify the care that they provide but if several are then their progress in providing better care can be shared in future meetings. This will be very useful in motivating other physicians and staff to adopt the recommended changes, especially if the data from the clinicians adopting the recommended changes show success in their prevention work.

The work on providing improved care is not completed after the implementation of strategies shown to be effective by predictive analytics. Data should continue to be collected. Long-term data collection can provide refined strategies that deliver even better results. Plus, research and experience may identify new strategies that can produce even better care outcomes with improved savings for the providers. These new strategies can be implemented and after a period of time data analysis can indicate whether such strategies are effective for the providers. A word of caution, even though research of effective treatment by scientists and providers may show a strategy generally effective, it may not be in a given care setting. The strategy may not match the skill set of the providers, for instance.

In summary, a well-defined program of predictive data analytics and population health management can produce much better outcomes for the patient and the providers. The steps of collecting baseline data, identifying several strategies implemented concurrently, the continuation of data collection, the analysis of the data and the implementation of the best strategies as identified in the analysis should be carefully followed for optimum results. As payers such as Medicare base more of their reimbursement on the achievement of certain population level outcomes it is very important for healthcare systems to adopt the strategies that I have identified.

How to Collect Bee Pollen Without the Mess

By the time you finish reading this article, you will have an understanding of how some of the best bee pollen in the world is being collected for your benefit. While New Zealand isn’t close for everyone, several bee farmers can tell you how to collect bee pollen without any mess whatsoever.

One New Zealand company collects their pollen and manufactures it using GMP standards, but the collection of bee pollen is generally the same around the world.

The Basics of Collecting Bee Pollen

Most people don’t like the idea of collecting bee pollen or honey because they don’t want to get stung. Collecting honey is different, so it’s important to understand that these two things are not the same, nor are the methods by which you collect them.

Collecting pollen takes some clever skill, and a little know how, but learning how to collect pollen is essential to doing it safely. Before you get hyped up about collecting the pollen, you need to understand the method by which the bees collect it before they bring it to their hive. Bees carefully collect it from the most select flowering plants with their tongues, and they pass it back to a basket on their legs.

Their legs are bristly with hairs that the pollen sticks to as they make their way around the flower. This means that potentially a bee could hold tons of pollen during the course of their collection! Once they complete their collection, they will then carry it back to their hive. When they do, we have to be clever in making it possible to collect it by our own methods!

Creating the Clever Bee Pollen Trap

The easiest way to set it up to collect bee pollen is to create an environment that makes it possible without hurting the bees. The little homes that bee farmers build have little trap doors that the bees must fly through in order to get to their hive, and as they do, the mesh will capture the pollen. Now, while it doesn’t sound as though you would get a lot you might be surprised.

Bees collect thousands of pounds of pollen each year, because they need it in order to survive. They do to feed off the pollen, while the Queen Bee feeds off of the royal jelly which is also a different substance from honey and pollen.

Even the bees know what is good for them, and as a result they stay busy! They make it easy for us to get this pollen from the flowers; otherwise you can imagine it would be quite a tedious process to collect pollen. Some bee farmers put little trays below the mesh netting where the pollen can drop off, and all they need to do is take that tray, get the pollen, and then start the process.

In conclusion, collecting pollen is possible because the bees do the hard work upfront by collecting it from flowering plants. Bee farmers use mesh netting where the pollen is collected from their legs as they fly back to their hive. This is how pollen is collected for the purpose of manufacturing it and selling it to us for good health. The next time you see a bee, say thank you! They do us a huge favor!

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