Relevance of data
The type of data collected is influenced by both the length
of time spent with the person (e.g. same-day surgery versus
surgery that necessitates a long recovery in an intensive
care unit) and the nature of the care required (e.g. assistance
with the birth of a baby versus support and home care
throughout a terminal illness). A general guideline to follow
is to gather only data that are helpful when planning and
delivering care. It would be inappropriate, for example, to
collect a detailed sexual history on an adolescent admitted
to the hospital overnight after a slight concussion. Con-
versely, you should ask such questions if a pregnant woman
is admitted to the hospital for observation for vaginal bleed-
ing during her first trimester.
Practical considerations
Before conducting an interview, first check to see if the
person has presented before at the health facility. A personal
record will provide data collected during previous visits, and
these data should not be repeatedly sought, unless there is a
need to validate them. Additionally, repetitious questioning
can be annoying and may cause the person to question the
lack of communication among healthcare providers. A
careful review of the personal record before commencing
the interview helps prevent these problems.
Before meeting a person for the first time, it is helpful to
take a minute to think carefully about the type of data
needed to plan quality care. After a comprehensive health
assessment has been completed, the priority of the identified
health problems will dictate future interactions.
Structuring the assessment
Because many different types of data are collected during
the assessment, there is a need to structure data collection
systematically. A variety of
assessment frameworks
are
available that provide systematic guidelines specifically
developed for a health assessment to ensure that comprehen-
sive, holistic data are collected for each person which will
lead to the identification of health problems. Frameworks
may be modified to suit the individual and the personal pref-
erence of the nurse or midwife. Once you are familiar with
these assessment frameworks, you can focus on the person
rather than worrying about what to assess next.
Most schools of nursing and midwifery and healthcare
institutions use one or more assessment frameworks and
have established a
minimum data set
that specifies what
information should be collected. They then use a structured
health assessment form to organise or cluster these data.
Many nursing and midwifery assessment guides are based
on holistic models rather than medical models. Holistic
models encompass the physiological, psychological, socio-
cultural, intellectual and spiritual aspects of each person.
Examples of assessment frameworks include:
•
The human needs framework (Maslow, 1943) which
uses a hierarchy of human needs identifying five levels
Unit III Thoughtful practice and the process of care
274
•
The functional health patterns framework (Gordon,
2010) which identifies 11 functional health patterns and
organises personal data into these patterns
•
The human response patterns framework which suggests
health status is evidenced by observable phenomena that
can be classified into one of the response patterns. This
can then be used as a model for organising data
collection
•
The head-to-toe framework which provides baseline
data and uses a comprehensive systematic approach that
can be undertaken in a timely manner to prioritise care.
See Table 15-1 for an overview of the human needs, func-
tional health patterns and head-to-toe assessment frameworks.
The body systems model used to organise data collection
is an example of a medical model. This framework organ-
ises data collection according to organ and tissue function in
various body systems. Although it is helpful in identifying
health problems related to physiological factors, it neglects
a person’s problems and strengths in psychosocial, cultural
and spiritual dimensions of health and well-being.
DATA COLLECTION
Subjective and objective data
There are two types of data: subjective and objective.
Sub-
jective data
are information perceived only by the affected
person; that is, what the person is experiencing. These data
cannot be perceived or verified by anyone else. Despite this,
subjective data are sometimes capable of measurement; for
example, pain scales may be used to measure a person’s
experience of pain. Examples of subjective data are when a
parent indicates that their child is ill or when a person states
that they are feeling cold, nervous or nauseated. Subjective
data are also called symptoms or clinical manifestations.
Objective data
are observable and measurable data that
can be seen, heard or felt by someone other than the person
experiencing them. Objective data observed by one nurse or
midwife can be verified by another nurse or midwife
observing the same person. Examples of objective data are
an elevated temperature reading (e.g. 39°C), skin that is
moist, and refusal to look at or eat food. Objective data are
also called signs or clinical manifestations. Table 15-2 com-
pares subjective and objective data.
Paying attention to both subjective and objective data
promotes critical thinking and clinical reasoning because the
two types of data complement and clarify one another.
Consider what you know about the types of data
that may be collected during an assessment and apply it
to the scenario. As part of your assessment of Claire you
have discovered that she is stressed about her upcoming
exams and her menstrual cycle is causing swings in her
blood glucose levels. Claire also wants to fit in with her
friends and when they go out she wants to do the same
things they do, which includes drinking alcohol. She
