Fig. 56.1
The Donabedian model of quality of care: interrelated components of structure, process, and outcome
The Donabedian Model (Part 1): Structure
“Structure” in the Donabedian model refers to the characteristics of the setting and providers in and through which health care takes place.
Structural Measure at the Health System Level
An example of a structural measure that assesses quality at the level of the overall health-care system is the adequacy of the health-care workforce to meet the needs and demands of the population that it serves.
The growing elderly population will increase the demand for surgical services.
In the Donabedian model, the projected shortage of surgeons represents a potential structural flaw that will affect downstream processes and outcomes.
Structural Measure at the Institution Level
Examples of structural measures at the institution level include hospital accreditation status, nurse-to-patient ratios, availability of specialty services (e.g., interventional radiology, transplant services), teaching status or affiliation with academic institutions, and hospital volume.
From an institutional standpoint, accreditation activities are often integral to performance and quality improvement efforts.
There are inconsistent findings regarding accreditation status and quality indicators.
In colorectal surgery, supporters of accreditation have proposed that accrediting programs for rectal cancer or inflammatory bowel disease may be beneficial in promoting higher quality and more standardized care for these patient populations.
The volume-outcome relationship is the observed association between provider case volume and patient outcomes, usually with increasing provider volume (hospital or surgeon) associated with improved patient outcomes.
Proponents of the volume-outcome relationship argue that regionalizing high-risk procedures to select high-volume providers can save patient lives.
Critics argue that it is unclear whether increased volume leads to improved quality or whether high-quality care attracts more volume, and volume measures penalize low volume but high-quality providers.
Health-care payers have incorporated structural measures into their criteria for “Centers of Excellence” to incentivize patients to utilize qualifying facilities or providers.
Structural Measure at the Practitioner Level
Examples of structural measures at the practitioner level include board certification and subspecialty training.
Overall, studies have generally shown improved outcomes for surgeons with specialty training.
However, it was unclear if the additional training or having a specialized practice was responsible for the difference in outcomes.
The Limitations of Structural Measures of Quality
The most significant downside to structural measures is their relative immutability, especially from the perspective of an individual surgeon.
While structural measures may have an important role in policy discussions and population-based planning, there may be little that the surgeon can change in the structure of their practice to ultimately impact patient outcomes.
The Donabedian Model (Part 2): Process
Process refers to what providers do to the patient or do for the patient; essentially, everything that occurs in the continuum of patient care constitutes a process of care.
The literature contains numerous clinical practice guidelines that describe treatment processes and algorithms that comply with the standard of care or represent best practices (e.g., NCCN, ASCRS Practice Parameters).
The difference between practice guidelines and process measures is that guidelines are often qualitative recommendations that often include gray areas of variable appropriateness, allowing for a physician’s clinical judgment and patient preferences.
In contrast, process measures (e.g., SCIP) are quantitative measurements, have simplistic measurement algorithms, and can be used to set standards of care.
A good process measure has the following characteristics: (1) it is explicit in its inclusion and exclusion criteria (denominator); (2) it is rigid in its requirements for satisfying the process (numerator); and (3) it is linked to outcomes.
These quality indicators establish the standard of care that patients should receive; they are explicit, quantitative, and evidence-based; and there is a growing trend by regulatory bodies and payers to use such quality indicators to set standards for appropriate care (e.g., perioperative antibiotics, normothermia, DVT prophylaxis).
Following baseline measurement of an organization’s adherence to a set of quality indicators, tailored interventions can then be designed and implemented to target areas of poor performance.
One of the best ways to identify processes of care is through randomized controlled trials (RCTs).
Limitations of Process Measures
One of the limitations of process measures is that it is often difficult to prove that performance of a process measure directly results in improved patient outcomes.
A second limitation is that there are no validated quality indicators for many areas in surgery where quality improvement may be warranted.
A third limitation is that data collection to measure adherence to process measures or quality indicators is often labor- and cost-intensive.
There also may be limited benchmarks against which an organization’s performance can be compared.
The Donabedian Model (Part 3): Outcomes
Outcomes are the end result of receiving health care.
Traditionally, surgeons have examined their outcomes through morbidity and mortality conferences.
The objectives of outcome measurement are to evaluate and compare providers as a means to inform providers and patients, adjust financial compensation, and facilitate quality assurance and improvement.
In order to make valid comparisons between providers, appropriate patient risk adjustment must be performed.
Patient factors + Effectiveness of care + Random variation = Outcome.
“Patient factors” represent the patient’s variables, such as their diagnosis, age, gender, socioeconomic status, comorbidities, and illness severity.
“Effectiveness of care” relates to the nature of the intervention being studied.
“Random variation” is perhaps best described by the saying: “You can do everything wrong and have a good outcome, and you can do everything right and have a bad outcome.”
In addition to objective or “hard” patient outcomes such as mortality or complications, there are also subjective patient-reported outcomes such as patient satisfaction, functional status, and quality of life.Related posts:
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