Bhasale and colleagues10 and Fischer and coworkers13 collected patient outcome data; they specifically examined incidents that had “harmed” patients or had “potential for harm.” Ely and associates12 also studied incidents causing patients harm by investigating possible causes of these incidents. Dovey and colleagues11 reported physician-observed errors regardless of whether they were associated with an adverse event. Britten and coworkers16 analyzed misunderstandings between patients and physicians that had adverse consequences for taking medicines. Gandhi and associates14 described communication between primary care physicians and specialists. Holden and colleagues15 investigated deaths in general practices. All these studies attempted some categorization of medical errors. Bhasale and associates10 and Fischer and colleagues13 defined 4 incident cate gories and then assessed preventability. Dovey and coworkers11 and Ely and associates12 placed medical errors into categories, and Bhasale and colleagues10 listed a number of contributing factors. Britten and coworkers16 and Gandhi and associates14 categorized clinician communication problems. Holden and colleagues15 classified clinician actions that led to preventable deaths.
Due to the multiple methods used in the 7 studies and the descriptive nature of the studies, a standard assessment of quality and quantitative synthesis of data were not possible. Six studies used practicing community-based primary care physicians as their main study group. The study by Gandhi and coworkers, of communication between primary care physicians and specialists,14 was performed in an academic institution.
We derived the following classification system (outlined in Tables 2 and 3) from the errors and preventable adverse events reported in these 7 studies.10-16Table 2 defines the three main categories of preventable adverse events related by primary care physicians: diagnosis, treatment, and preventive services. These offer descriptors of what went wrong in the care of the patient but not of the level of harm. For example, a patient who was prescribed and took an incorrect drug has experienced a preventable adverse event. As a consequence, that patient may suffer no ill effects (a near miss), may die from anaphylaxis, or may experience some intermediate outcome (such as a rash).
Table 3 outlines “process errors” that clarify why something went wrong. For example, Why was the patient prescribed an incorrect drug? The answer may lie with a clinician factor (the doctor took an inadequate history), a communication factor (not dealing with a language or cultural barrier), an administrative factor (the medical chart was missing), or a blunt end factor (Medicare regulations). Often, multiple factors may be involved.
Classification of preventable adverse events in primary care
|Related to symptoms|
|Related to prevention|
Classification of process errors in primary care
|Procedural skills error|
|Clinician–clinician or health care system personnel|
|Ancillary providers (physical therapy, occupational therapy, etc)|
|Blunt end factors|
|Personal and family issues of clinicians and staff|
|Insurance company regulations|
|Funding and employers|
|Physical size and location of practice|
|General health care system|
The results of this literature synthesis are important for 3 main reasons. First, they offer a summary of the current state of published research. Second, by synthesizing the results of this small body of literature, we were able to develop a working classification system of preventable adverse events (what went wrong) and process errors (why did it go wrong). Third, this classification may clarify the relations between patient safety, process errors, and preventable adverse events in primary care.
Other published classification systems of medical errors and preventable adverse events range from sparse (3 categories with 19 root causes)17 to dense (80 categories with more than 12,000 branching trees).18They generally derive from studies of safety in non-medical industries17 or from studies emphasizing hospital care.2,18 In a recent review of the medical literature, Wilson and Sheikh noted the lack of a typology of medical errors in primary care and reasoned that the key safety issues in primary care are in the arenas of diagnosis, prescribing, communication, and organizational change.5 Their conclusions are congruent with ours, and our more structured classification system contains these arenas.
The classification in Table 3 was generated from research in primary care settings by using data from practicing family physicians and general practitioners. (A more complete version of Table 3 may be found at http://www.jfponline.com.) If the classification is valid and useful, it should assist clinicians and researchers in understanding how process errors and preventable adverse events happen during the practice of primary care. Models assist us in understanding these relations. Among previously proposed models are the “Swiss Cheese”19 and the “Toxic Cascades.”20 The Swiss Cheese model postulates that barriers exist to prevent adverse events, but they are like slices of Swiss cheese with many holes (or errors) in them. Adverse events happen when the holes in many layers temporarily line up. The Toxic Cascades model conceptualizes 4 levels of threats to patient safety: trickles, which leave little trace of their existence; creeks, which have potential seriousness; rivers, which are the actual errors that harm patients; and torrents, which are errors that lead to a patient’s death or serious injury. From our classification, we can define some of the holes in the Swiss Cheese and name many trickles and creeks in primary care Toxic Cascades.