Improvement Knowledge

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Knowledge of a System

The health care system has an aim to improve the health of the patients it serves. This care is "made" through several processes, such as diagnostic services, assessments, plans of care, and delivery of care at the ward or in the clinic. All these processes include many steps that need to be analyzed and understood in greater detail before we plan to change and redesign processes for improved performance and outcomes. The clinical microsystems are the essential building blocks of the larger health care systems. The microsystem is the local context where patients and families, health care teams, support staff, information, and processes meet to provide care for a particular group of patients. In a pediatric hospital there are many microsystems, such as allergy, rheumatology, and diabetes clinics, neonatal intensive care units, and units for infectious disease. These different microsystems will interact horizontally with each other in planned and unplanned ways. A rheumatology patient, for example, will mainly receive care in the pediatric rheumatology clinic but may sometimes need to be cared for in the inpatient unit, which is another microsystem. Examples of other linking microsystems for the same patient might be the ophthalmologist clinic, the department of radiology, the pharmacy, or physical therapy department. Using "system thinking" invites the challenge: to make the process for the patient and family smooth and seamless. The flow of information and data should be uninterrupted, and the process should not be dependent on which day of the week it is or which insurance-plan the patient has. A microsystem can be viewed as being embedded in a larger system called the mesosystem, which in turn is imbedded in an even larger system called the macrosystem. This is illustrated in the "systems of health care" (Fig. 3) (4).

Market / Geopolitical system

Market / Geopolitical system

Figure 3 Systems of health care. Which system is the unit of practice, intervention, measurement, or policy? Source: Adapted from Ref. 4.

Another way to consider the systems of care (micro-, meso- and macrosystems) is through current organizational structures such the "multilayered health system diagram" (Fig. 4) (4). In order to improve care we need to have deep knowledge of the current system and know how to make improvements.

Knowledge of Measurement and Variation

The next dimension of improvement knowledge is variation. Processes often show variation, a lack of standardization of care, and steps in care. Understanding and studying variation over time is key to recognizing and identifying opportunities for improvement. In a stable process we still find some variation that occurs because of chance, common cause variation. But, there can also be special causes that we can discover when we follow data over time and action can be taken (16). If we react to common cause variation as if it were a special cause we might "tamper" with the system, resulting in poorer outcomes than intended. For example, blood sugar values in the normal ranges in a diabetes patient will always show some common variation. However, if we start to give extra insulin because of a higher value within the common variation, we might risk making the patient hypoglycemic, which

System levels Macrosystem

Mesosystem Microsystem

Outpatient divisions

Adolescent rheumatology unit

Example Pediatric services

Outpatient divisions

Adolescent rheumatology unit

Mesosystem Microsystem

Figure 4 Organizational layers of embedded systems. Microsystems are the building blocks that come together to form macro-organizations. Source: Adapted from Ref. 4.

Figure 4 Organizational layers of embedded systems. Microsystems are the building blocks that come together to form macro-organizations. Source: Adapted from Ref. 4.

leads us to administer extra calories, resulting in too high a blood sugar level, that is, we "tamper" with the system unnecessarily.

In pediatric rheumatology, we can analyze variation at many levels. We can gain more insight into the patients and populations we serve, the performance of our system, and the outcomes of our patients by asking some questions.

■ Do we get patients from some referral areas and not from others?

■ Do patients come late, after onset of symptoms, from some areas and early from other areas?

■ Does the frequency with which intra-articular steroids are given for the same kinds of patient vary between centers?

■ Do the rates of given vaccinations, which are recommended by guidelines, vary between groups of our patients or between centers?

■ Do outcomes differ between centers?

Only if we start to measure data over time and observe patterns in performance and outcomes can we begin to identify opportunities to improve care and through continued data measurement know if improvement activities lead to improved outcomes.

A disease registry can be an important source of information about the characteristics of the population of patients served, the performance of the provided care and multidimensional outcome measures as illustrated by examples from the Swedish Rheumatology Registry (Table 2) and disease

Table 2 The Swedish Rheumatology Registry

A "registry case": In Sweden, a web-based clinical quality registry for adult patients with rheumatoid arthritis that is used for several purposes has been created. It is built as a "feed-forward" system which means that the patient can enter data into the Health Assessment Questionnaire, get results from laboratory tests, and a joint evaluation before the visit to the rheumatologist. Thus, a patient over-view can be created and used as a template for the conversation between patient and provider to help guide decisions that need to be made. Since data are shown over time, it can help the patient and provider see trends in improvement or worsening of the disease. In addition, the data from the patients at the microsystem level can be aggregated, analyzed, and used for local learning and improvements. At the national level, unanimous patient data can be aggregated for comparison of performance measures and outcomes for benchmarking, learning, and improvement (Fig.5).

Patient o


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