Home > Full Text Reviews > Making Health Care Safer II: An Updated... > Patient Safety Practices Targeted at...

PubMed Health. A service of the National Library of Medicine, National Institutes of Health.

Making Health Care Safer II: An Updated Critical Analysis of the Evidence for Patient Safety Practices. Rockville (MD): Agency for Healthcare Research and Quality (US); 2013 Mar. (Evidence Reports/Technology Assessments, No. 211.)

Chapter 35Patient Safety Practices Targeted at Diagnostic Errors (NEW)

Kathryn M McDonald, MM, Despina Contopoulos-Ioannidis, MD, Julia Lonhart, BS, BA, Brian Matesic, BS, Eric Schmidt, BA, Noelle Pineda, BA, and John PA Ioannidis, MD.

How Important Is the Problem?

The family of patient safety targets that includes diagnostic errors, diagnostic delays, and other diagnostic misadventures is not fully defined with clear boundaries. However, one operational definition adapted from the Australian Patient Safety Foundation by Mark Graber and colleagues is that “diagnosis is unintentionally delayed (sufficient information was available earlier), wrong (another diagnosis was made before the correct one), or missed (no diagnosis ever made), as judged from the eventual appreciation of more definitive information.”1 Alternatively and similarly, Gordon Schiff and colleagues have defined diagnostic errors as “any mistake or failure in the diagnostic process leading to a misdiagnosis, a missed diagnosis, or a delayed diagnosis.”2

Depending on the definition and data source, the exact scope of the problem varies, although its magnitude is consistently impressive. A systematic review of 53 different series of autopsies reported a median error rate of 23.5 percent (range, 4.1% to 49.8%) for major errors (clinically missed diagnoses involving a principal underlying disease or primary cause of death) and 9.0 percent (range, 0% to 20.7%)1 for class I errors (the most serious subset of major errors being those likely to have affected patient outcomes).3 These data translate to approximately 35,000 patients who might have survived to discharge from United States hospitals annually had misdiagnosis not happened.(3) A Harris poll found that three in five Americans (63%) are very or extremely concerned that a diagnostic error can take place.4

Numerous disease-specific studies show that 2 percent to 61 percent of patients experienced missed or delayed diagnoses.5 Examining potential causes of delay in diagnosis for colorectal cancer (CRC), 161 of 513 patients (31.4%) with newly diagnosed CRC had at least one previously missed opportunity for their physician to initiate diagnostic workup. These patients averaged 4.2 missed imaging initiation opportunities despite a mean of 5.3 clinical indications for diagnostic workup for CRC.6 In a study of 587 patients diagnosed with lung cancer, 37.8 percent experienced missed clinical opportunities due to failure in recognizing predefined clinical indications for follow-up or failure to complete requested follow-ups. Patients with missed opportunities experienced a significantly longer median time to diagnosis than patients without missed opportunities (132 vs. 19 days, respectively; p < .001). Patient non-adherence to physician recommendations was present in 44 percent of patients with missed opportunities.7 In a survey administered to academic, community, and trainee pediatricians, 54 percent reported making a diagnostic error at least once per month and 45 percent noted making diagnostic errors that harmed patients at least once per year. Survey respondents reported that lack of pertinent historical or clinical information and team processes such as care coordination were contributors to errors.8 Furthermore, research on variation in patient outcomes related to diagnosis timing suggests room for improvement for some high stakes conditions. For example, early identification of sepsis (along with protocols for treatment pathways) has been associated with decreased mortality in surgical intensive care.9 Improving diagnostic speed, accuracy and triage to treatment of such high risk, rapidly developing conditions is another important frontier for those seeking to improve consequential diagnostic delays.

Problems in care related to diagnosis are particularly prevalent among precipitating causes for lawsuits, with studies reporting 25 percent to 59 percent of malpractice claims attributable to diagnostic errors.5,10,11 A recent study of 91,082 diagnosis-related malpractice claims from 1986 to 2005 estimated payments summing to 34.5 billion dollars (inflation-adjusted to 2010 dollars), well over one billion dollars per year. The mean per-claim payout was $378,858 (interquartile range: $72,250 to $472,000).12 Diagnosis-related claims made up 29.1 percent of total claims and accounted for the highest proportion of total payments (35.6%). In terms of severity, lethal injuries accounted for 40 percent of total payments. Another study of 10,739 malpractice claims from the 2005-2009 National Practitioner Data Bank found that diagnosis-related reasons accounted for 45.9 percent of paid claims from outpatient settings (95% confidence interval [CI], 44.4 to 47.4), the most frequently cited reason from that setting. Diagnostic reasons were the second-most frequently cited for paid claims in the inpatient setting (21.1%; 95% CI, 20.0 to 22.3) and when both settings were involved (26.7%; 95% CI, 23.9 to 29.5).13

Some have asserted that diagnostic errors are more likely to be preventable and more likely to result in patient harms than other types of errors (e.g., treatment-related errors, such as wrong-site surgery or incorrect medication dose), making the problem particularly important as well as useful to address.14 Given this potential, the purpose of this review is to assess the multitude of interventions to prevent diagnostic errors and better understand their effectiveness.

What Is the Patient Safety Practice?

Many types of patient safety practices (PSPs) have been devised to address diagnostic errors, and a number haven even been tailored to specific types of diagnostic error, root causes for the error, technologies available, and other factors. Studies of the epidemiology and etiology of diagnostic errors offer the foundation for an even richer and more robust set of potential PSPs in this area. In an analysis of physician-reported errors, Schiff and colleagues found that the most common missed or delayed diagnoses that physicians recalled were pulmonary embolism, drug reactions or overdose, various cancers, acute coronary syndrome, and stroke.2 Incidence rates could not be calculated from the convenience sample: The study focused on understanding the potential root causes of the errors. They determined that errors occurred throughout the diagnostic process and classified the reported cases using the “Diagnostic Error Evaluation and Research (DEER)” project tool. From analysis of the subgroup of major diagnostic errors, over 43 percent were related to clinician assessment (including failure/delay in considering the diagnosis, placing too much weight on competing/coexisting diagnosis) and 42 percent to laboratory and radiology testing (including failure to order needed tests, technical errors in processing specimens/tests, erroneous reading of a test). Some PSPs are designed to target these failure areas—for example, the design and application of algorithms, checklists, and related tools to help identify and weight potential diagnoses.

Viewing diagnostic errors from specific departments or specialties is another approach to understanding contributing factors and designing interventions to mitigate these in specific settings. As an example, Crosby developed a human- and system-oriented framework based on a decade of reviewing emergency department (ED) cases from an urban, public, teaching hospital.15 This framework examined ten areas, each one tied to points of leverage for development and testing of PSPs, and together demonstrating the broad scope of possible interventions to reduce diagnostic errors:

  • Patient factors: systems may be designed around areas that are more prone to risk (e.g., improved staffing with translators).
  • Human/clinician factors: interventions may aim at errors of planning separately from errors of execution, and may also be designed to address cognitive error, skill-set error, task-based error, and/or personal impairment.
  • Outside care systems, ED access, and triage: consideration of these three framework areas aims to understand patterns of failure and errors that affect patients before their arrival in the ED or initiation of care.
  • Teamwork: interventions in this area focus on communication, coordination, conflict resolution, personnel assignment practices (e.g., considerations of capability, workload), and training.
  • Local ED environment, hospital environment, hospital administration and third parties, and community level: systems and resources at each of these four additional levels of the framework have potential for effective interventions to reduce diagnostic errors within the ED and after the patient leaves.

Within the above framework, human and clinician factors have received significant attention from researchers interested in diagnosis. Cognitive factors may affect diagnostic accuracy through rote over-learned actions or through purposive reasoning and decisionmaking processes. The cluster of automatic or quasi-automatic decisionmaking processes may be classified as heuristics, or rule-based decisionmaking processes. Heuristics aid in making decisions quickly and are important for keeping cognitive capacity high for other, more demanding, cognitive tasks. However, the very thing that makes heuristics helpful, decisions based on logical assumptions gained from experience, can also lead to systematic bias and incorrect decisionmaking when assumptions are wrong.16 Other cognitive processes affecting diagnosis involve working memory in conjunction with learned knowledge, or more plainly, information that is purposefully stored, recalled and used for completing a current goal. An example of these cognitive processes can be seen in physicians listening to their patients describe symptoms. The physician cognitively stores symptomatic information in the short term until she or he can classify the symptoms into a more general descriptive category of a diagnosis. This process is also subject to error when attention is pulled away from the task at hand or cognitive capacity is altered for others reasons (e.g., lack of sleep). The process of metacognition involves continued focusing and re-focusing attention on these cognitive processes so as to reflect on one's own potential for biases, incorrect assumptions, and reduced cognitive capacity.17 Ultimately, both human factors and the systems within which they operate have long been recognized as unique contributors to human error.18

PSPs relevant to diagnostic error are also being actively developed by those bringing more attention to this important patient safety target, and drawing on previous work in the research domains of medical problem solving, decision analytic/normative decisionmaking, and clinical diagnostic decision support.19 As health information technologies become more pervasive, electronically-supported workflow and system redesign might target preventing or mitigating diagnostic errors. PSPs in this area would be akin to computerized physician order entry with clinical decision support, though more aptly named something like computerized diagnosis management.

Why Should This Patient Safety Practice Work?

Many types of interventions, spanning a range of specialties and settings, are potentially applicable to reducing diagnostic errors. Thus, it is impossible to answer the question of why these interventions should work with one general statement. In addition to some of the frameworks described above as the bases for logic models, recent commentaries and focus group reports offer examples of why specific approaches could work (e.g., electronic clinical documentation, checklists, interventions to decrease the frequency of missed test results).20-22 For electronic documentation, for example, researchers have suggested goals and features of redesigned systems for improved diagnosis (e.g., “aid cognition through aggregation, trending, contextual relevance, and minimizing of superfluous data”) tied to specific roles for that particular approach (e.g., “providing access to information”).20

What Are the Beneficial Effects of the Patient Safety Practice?

A recently published systematic review on system-related interventions addressing organizational vulnerabilities to diagnostic errors23 based on a search from 2000 to 2009 included 43 studies. A companion piece focused on cognitively-related interventions.24 To build on the previous work, we conducted a separate systematic review, encompassing a longer time period, and with broader inclusion criteria to provide a high-level summary of categories of interventions studied. We searched MEDLINE, PSNet, bibliographies of background articles and previous systematic reviews to identify literature about effects of practices with implications for errors and delays in diagnosis. For further detail, see Appendix C.

Although numerous articles proposed or described interventions, few reported evaluations of these interventions. Singh and colleagues summarized 37 studies with no evaluations, classifying them along five process dimensions: provider-patient encounter, diagnostic test performance and interpretation, follow-up and tracking, referral-related issues, and patient-related issues.23 Their review also identified six evaluations of interventions, of which only three reported diagnostic outcomes (incidence of delayed diagnosis of injury, incidence of missed injuries, misdiagnosis rates), and none provided information on patients' downstream clinical course.23

Graber and colleagues summarized 141 articles on improving congition and human factors affecting diagnosis, 42 of which reported evaluation of interventions.24 These investigators classified the literature along three dimensions. In the first dimension, interventions to increase knowledge and expertise, the authors identified seven evaluation studies, only one of which provided information on diagnostic outcomes and clinical course for actual patients. The second dimension included interventions to improve intuitive and deliberate considerations. Among the five studies evaluating interventions for this dimension, none reported resultant effects on documented diagnoses with actual patients during clinical course of care. In the largest group of studies, interventions assigned to the third dimension of getting help from colleagues, consultants and tools, 16 of 28 studies evaluated diagnostic outcomes in actual patients. Graber and colleagues note the current scarcity of evidence for any single intervention targeting cognitive and human factors in reducing diagnostic error. The authors highlighted potential for interventions that target content-focused training, feedback on performance, simulation-based training, metacognitive training, second opinion or group decision-making, and the use of decision support tools and computer-aided technologies.

Our review identified 94 studies of PSPs targeted at patient diagnosis. These studies reported missed diagnosis, misdiagnosis, delayed diagnosis, or some other diagnostic discrepency with potential for clinical consequence. The Supplementary Evidence Table (see Appendix D, Table 2) provides basic descriptions of targeted diagnostic errors, intervention descriptions, patient outcome, study design and results with respect to the effectiveness of the proposed interventions.

Drawing from frameworks proposed by others, we classified interventions into one or more of the following six types (Figure 1):

Figure 1 is a pie chart illustrating the percentage of studies in each of the six intervention categories: Technique, Educational Interventions, Technology-based Systems Interventions, Personnel Changes, Additional Review Methods, and Structured Process Changes.

Figure 1, Chapter 35

Interventions by type. This pie chart illustrates the percentage of studies as categorized to the six intervention types: Technique, Educational, Technology-Based Systems, Personnel Changes, Additional Review Methods, and Structured Process Changes.

  • Technique (introduction of novel technologies for testing, adaptations of testing equipment, or changes in medical interventions potentially affecting diagnostic performance)
  • Additional Review Methods (introduction of additional steps from the interpretation through reporting of test results)
  • Personnel Changes (introduction of additional health care members and/or replacing certain professionals with others)
  • Educational Interventions (implementation of educational strategies)
  • Structured Process Changes (implementation of feedback systems or additional stages in the diagnostic pathway)
  • Technology-based Systems Interventions (implementation of technology-based tools at the system level—computer assistive diagnostic aids, decision support algorithms, text message alerting, pager alerts, etc.)

All six of the evaluative studies identified by Singh and colleagues,23 many of the evaluative studies identified by Graber and colleagues,24 and most of the studies included in our systematic review, reported beneficial effects along the diagnostic pathway for a broad array of intervention types. Because the evidence is predominantly from uncontrolled before-after study designs or other uncontrolled study types (Table 1) with markedly different outcomes, the strength of the evidence about interventions to reduce diagnostic errors is insufficient to draw any strong conclusions. Furthermore, the magnitude of difference attributable to interventions varied by study and clinical process. For example, some researchers demonstrated what would be moderate-to-large effects on diagnosis if the assumption of causality were made (e.g., Perno and colleagues, 2005),25 although methodologies were not designed to test causality, whereas other studies were designed to demonstrate the absence of change in diagnostic outcomes despite intervention (e.g., Thomas and colleagues, 2003).26

Table 1, Chapter 35. Study design distribution.

Table 1, Chapter 35

Study design distribution.

As a result of the state of the science in this area, no meta-analyses have been conducted. Pooled analysis may be feasible in the near future as the evaluative literature is growing rapidly in some intervention categories. Figure 2 shows particular increases for several classes of interventions: Additional Review Methods, Technology-based Systems Interventions, and Structured Process Changes. The other intervention types have not been studied much over the entire period.

Figure 2 is a graph illustrating a timeline of the years of publication of the included studies according to the six intervention types. The X-axis spans the time period from 1970 to 2011. The Y-axis plots the number of studies for the following six intervention types: Additional Review Methods; Technology-based Systems Interventions; Structured Process Changes; Technique; Educational Interventions; and Personnel Changes.

Figure 2, Chapter 35

Intervention studies by year. The graph illustrates a timeline of the included studies broken down by the six intervention types.

Few studies (5 randomized, controlled trials and 8 other designs) have evaluated patient-level clinical outcomes to reduce diagnostic errors.9,27-38 Diagnostic errors have a complex relationship with direct patient outcomes because they can play a role at many different time points in a patient's care; that is, many opportunities exist to catch diagnostic errors. If a diagnostic error is caught at any of these opportunities, then negative effects on clinical outcomes could potentially be avoided. Thus, examining the direct relationship between diagnostic errors and clinical outcomes is complex and explains why many of the articles do not report on hard patient outcomes. The remainder of this section summarizes the findings of the review.

Results of Randomized, Controlled Trials

Primary and secondary comparative quantitative outcomes data were available in 13 randomized trials, and are summarized in Appendix Table 1 (See Appendix D). Seven trials (9 comparisons) addressed diagnostic accuracy outcomes, and 3 trials (5 comparisons) addressed outcomes related to further diagnostic test use. Six trials (8 comparisons) addressed outcomes related to further therapeutic management. Five trials (7 comparisons) addressed direct patient-related outcomes. Three trials addressed composite outcomes (diagnostic accuracy and therapeutic management, and therapeutic management and patient outcome). One trial addressed time to correct therapeutic management, and another trial addressed time to diagnosis.

Trials evaluated various interventions. The control group used most often was usual care. No trials had high risk of bias, whereas 9 and 5 trials had moderate and low risk of bias, respectively.

Statistically significant improvements were seen for at least 1 outcome in all but 3 trials. Of the 3 trials with non–statistically significant improvements, one was a noninferiority trial that showed no more diagnostic errors occurred during work-up of abdominal pain among patients given morphine and those not given morphine26. Two trials that involved patients with mental conditions38,39 reported no beneficial diagnostic error effects from computerized decision-support systems. Only 1 trial34 reported improvements in direct patient outcomes; whether improvements were related to the comparison against the randomized concurrent control group or a preintervention period was unclear.

Use of Additional Review Methods

The most common intervention type evaluated was the review of test interpretation (n=36).9,29-31,40-71 Most studies showed a positive impact on diagnostic performance of an additional review step (usually by a separate reader, sometimes from the same specialty and other times from another specialty). However, in some cases, the detection of errors came at a high cost in terms of additional false positives. Not all studies reported the tradeoffs between sensitivity and specificity. Some of the studies targeted higher risk patients for enriched review. However, the systems to support such targeting were neither described nor evaluated.

Diagnostic Techniques

The studies of interventions related to medical techniques (n=14)26,31,72-83 demonstrated that technologies as well as diagnostic test selection might either enhance diagnosis (e.g., visual enhancements via ultrasound-guided biopsy, changes to number of biopsy cores, cap-fitted colonoscopy) or impede it (e.g., medical interventions for pain relief in patients with abdominal pain). In the latter cases, the interventions hypothesized to impede diagnosis did not have that effect, and interventions expected to enhance diagnostic accuracy did not always do so.

Personnel Changes

Six studies36,37,67,69,84,85 compared the impact on diagnosis of substituting one type of professional for another, or adding another professional to the care team. The three studies67,69,85 that added a specialist to examine the interpretation of a test result reported an increase in case detection, although the studies were quite small and targeted narrow patient populations.

Educational Interventions

Ten studies employed educational interventions35,61-64,86-90 for various targets: consumers, community doctors, and intensive care unit doctors and nurses. Strategies targeted at professionals produced improvements. Only two studies targeted consumers (parents, candidates for screening) and both intervened on a behavior that occurs much earlier than actual diagnosis (e.g., awareness of symptom seriousness with the intent of reducing office visits in ways that would not adversely affect diagnosis)86

Structured Process Changes

Twenty six studies25,35,36,38,39,63,65,69,70,79-82,89,91-102 examined interventions that added structure to the diagnostic process; this structure included, among other things, triage protocols, feedback steps, and quality improvement processes (“Q-Track”, Toyota Production Process). Most interventions included the addition of a tool, often a checklist or a form (i.e., to guide and standardize physical examination of a patient). Some of the studies centered on laboratory processes, whereas others occurred during clinical management. Results were mixed for these types of interventions, with positive results (e.g., improved diagnosis) only among studies that were not randomized, controlled trials (RCTs). Two of the three RCTs tested interventions in mental health diagnosis.

Technology-Based Systems Interventions

Twenty nine studies9,27,28,32-34,103-117 included computerized decision support systems and alerting systems (e.g., for abnormal lab results), most associated with improvements to processes on the diagnostic pathway (e.g., critical laboratory value relayed to clinician in a more timely manner).

Some interventions related to specific symptoms (e.g., computer aided diagnostic tool for abdominal pain interpretation), while others intervened at the level of a particular test (e.g., electronic medical record alert for positive fecal occult blood (FOBT) cancer screening test results).

Studies With Interventions that Corresponded to Multiple Categories

Twenty-four studies9,31,35,36,38,61-63,65-70,79-83,85,89,90,102,118 combined approaches in a variety of ways and also covered a broad range of clinical areas, with mixed results. These studies are included in the categories above. Twenty of the 23 studies combined two categories of intervention in almost every permutation possible (11 of 15 combinations). All but three studies included at least one of the two predominant categories in this set of multiple category interventions: Additional Review Methods (11/23) and Structured Process Changes (13/23). With combined approaches comes an inherent complexity in the intervention. However, the results from studies of combined intervention strategies largely parallel those reported above. With only one to four studies for any combination set, it is not possible to draw any conclusions about whether benefits are enhanced with more complex interventions. In addition, these more complex approaches may be more costly, but this information was not reported.

Notifying Patients of Test Results

Another potential grouping of PSPs focuses on the interface between the system and the patient. Indeed interim care processes such as patient notification of test results has gained attention at the national level.119 However, no studies evaluated this intervention with comparative designs. The review by Singh and colleagues identified seven studies of patient preferences or satisfaction with different options for receipt of test results.23 However, they also found no studies that tested ways to reduce error using an intervention that affected test notification. One of the articles identified in the Singh review by Casalino and colleagues found a 7.1 percent rate of apparent failures to inform patients of an abnormal test result, and identified an association between use of simple processes by physician practices for managing results and lower failure rates.120 A systematic review of failures to follow-up test results with ambulatory care patients reported that failed follow-ups ranged from 1 percent to 62 percent depending on type of test result, and these failures were associated with missed cancer diagnoses. Electronic record systems appeared to exert a mild protective effect against failed follow-ups, although the authors note the pool of literature was small in this analysis.121

What Are the Harms of the Patient Safety Practice?

In general evaluations of PSPs have not assessed unintended adverse effects. However, some of the screening test literature is applicable to maintaining a balanced perspective on diagnostic error reduction. For example, an excluded study by Molins and colleagues122 reported on the negative effects of multiple mammogram screening (patient anxiety, higher costs, poorer subsequent screening attendance). Although this study did not involve an intervention to reduce diagnostic error per se, it was similar to some of the included interventions with added testing. Although none of the studies in our review evaluated direct patient harm, some reported false positive rates.

How Has the Patient Safety Practice Been Implemented, and In What Contexts?

The context in which a PSP is implemented depends on the specific type of diagnostic error and PSP being examined. The studies identified in our literature search covered a range of subspecialties, settings, and patient populations, with varying contexts. Most of the interventions studied have not been tested in more than one site, with some even more appropriately categorized as proof of concept. For diagnostic practice, another important context is the sequence of events and the role of time itself. Sometimes these factors are embedded in the patient safety target analyzed, as is the case for delayed diagnosis, which was an outcome in 26 studies included in the Appendix Supplementary Evidence Table.

Are There Any Data About Costs?

The main source of information about costs related to diagnostic error is derived from malpractice claims, as noted in an earlier section. In terms of costs of implementing some of the PSPs reviewed, no information was reported, but would likely range from low to high depending upon the PSP. For example, a PSP that involves an additional reviewer of imaging tests might double the cost of that step in the diagnostic process for all patients, meaning a relatively large investment per diagnostic error averted. For PSPs that compared the results of one technology to another, the cost might be more or less, though often, technologies that perform with greater accuracy cost more because they deliver a clinical benefit. For PSPs that revise a workflow to follow a structured process, the start-up cost would depend on whether a structured process is already available and can be adapted inexpensively or if workgroups have to spend significant time to reengineer a local process. In either case, the cost may still be relatively low compared with interventions that have ongoing incremental costs. Finally, information technology PSPs to reduce diagnostic errors may be relatively expensive, though these costs could vary as well.

Are There Any Data About the Effect of Context on Effectiveness?

The evidence base for this topic does not yet include an examination of the influence of contextual factors during implementation.

Conclusions and Comment

The original “Making Health Care Safer” report did not consider diagnostic errors because just a decade ago, few studies had quantified the prevalence and clinical consequence of this patient safety target. As a result, much of the literature over this period has focused on quantifying the scope of the problem, and elucidating potential causal pathways that result in failures in diagnosis. Very few intervention studies have tested strategies to reduce diagnostic errors. However, frameworks for filling in the evidence gaps are beginning to emerge.

This review identified over 90 evaluations of interventions to reduce diagnostic errors, many of which had a reported positive effect on at least one end point, including statistically significant improvements in at least one end point in 10 of the 13 randomized trials. Mortality and morbidity end points were seldom reported.

We also identified two previous systematic reviews of cognitive and systems-oriented approaches to improve diagnostic accuracy that mostly found proof-of-concept strategies not yet tested in practice. Our review built on the previous systematic reviews by grouping PSPs targeting diagnostic errors from an organizational perspective into changes that an organization might consider more generically (techniques investment; personnel configurations; additional review steps for higher reliability; structured processes; education of professionals, patients, families; and information and communications technology–based enhancements), as opposed to individual clinicians looking for ways to improve their own cognitive processing in specific diagnostic contexts. Although many of the PSPs tested thus far target diagnostic pathways for specific symptoms or conditions, grouping interventions into common leverage points will support future development in this field by the various stakeholders who seek to reduce diagnostic problems. Involvement of patients and families has received minimal attention, with only two studies addressing education of consumers.

Data synthesis is difficult because few studies have used randomized designs, comparable outcomes, or similar interventions packages. The existing literature may be susceptible to reporting biases favoring “positive” results for different interventions. It is expected that with heightened awareness of the problem, the number of studies in this field will increase further in the future, including more randomized trials and studies testing different approaches: for example, policy-level efforts. However, the range of outcomes assessed in the studies that we reviewed highlights the known lack of tools to routinely measure the effect of interventions to decrease diagnostic errors. Additional work is needed on appropriate measurements of diagnostic errors and consequential delays in diagnosis. A final limitation, especially for synthesis, is the diversity of interventions that are reverse-engineered on the basis of the many diagnostic targets; the diverse tailored needs for each clinical situation (for example, protocols designed for specific work-up pathways); and the variety of specialized personnel, and even patients, receiving educational or cognitive-support approaches.

Evidence is also lacking on the costs of interventions and implementation, particularly how to reduce diagnostic errors without producing other diagnostic problems, such as overuse of tests. Eventually reaching the correct diagnosis with inefficient testing strategies (for example, some sequences of multiple test ordering) is not the appropriate pathway to improved diagnostic safety. Our review found a paucity of studies that assessed both sensitivity and specificity of interventions addressing diagnostic performance in the context of mitigating diagnostic errors. Thus, although we found several promising interventions, evaluations need to be strengthened before any specific PSPs are scaled up in this domain.

Alongside the literature scoping the problem and generating ideas for potential solutions, some are also working on policy level efforts. Singh and Vij describe potential institutional-level policies for communicating test results within the clinical team and to the patient.123 These types of policies respond to national attention (e.g., the Joint Commission Patient Safety Goals), spotlighting this part of the diagnostic pathway as ripe for intervention. They note that the area of notifying patients about their test results is an emerging area for intervention testing.

In conclusion, our review demonstrates that the nascent field of diagnostic error research is growing, with new interventions being tested that involve technical, cognitive, and systems-oriented strategies. The framework of intervention types developed in the review provides a basis for categorizing and designing new studies, especially randomized, controlled trials, in these areas. A summary table is located below (Table 2).

Table 2, Chapter 35. Summary table.

Table 2, Chapter 35

Summary table.

References

1.
Graber ML. Next steps: envisioning a research agenda. Advances in health sciences education : theory and practice. 2009;14 Suppl 1:107–12. Epub 2009/08/12. [PubMed: 19669917] [Cross Ref]
2.
Schiff GD, Hasan O, Kim S, Abrams R, Cosby K, Lambert BL, et al. Diagnostic error in medicine: analysis of 583 physician-reported errors. Archives of internal medicine. 2009;169(20):1881–7. Epub 2009/11/11. [PubMed: 19901140] [Cross Ref]
3.
Shojania KG, Burton EC, McDonald KM, Goldman L. Changes in rates of autopsy-detected diagnostic errors over time: a systematic review. JAMA. 2003;289(21):2849–56. Epub 2003/06/05. [PubMed: 12783916] [Cross Ref]
4.
Newswire P. Americans Are Concerned About Hospital-Based Medical and Surgical Errors. Wall Street Journal Online's Health Industry Edition. 2004.
5.
Schiff GD, Kim S, Abrams R, Cosby K, Lambert B, Elstein AS, et al. Diagnosing Diagnosis Errors: Lessons from a Multi-institutional. In: Henriksen K, Battles JB, Marks ES, Lewin DI, editors. Advances in Patient Safety: From Research to Implementation (Volume 2:. Advances in Patient Safety. Rockville (MD): 2005. [PubMed: 21249820]
6.
Singh H, Daci K, Petersen LA, Collins C, Petersen NJ, Shethia A, et al. Missed opportunities to initiate endoscopic evaluation for colorectal cancer diagnosis. Am J Gastroenterol. 2009;104(10):2543–54. Epub 2009/06/25. [PMC free article: PMC2758321] [PubMed: 19550418] [Cross Ref]
7.
Singh H, Hirani K, Kadiyala H, Rudomiotov O, Davis T, Khan MM, et al. Characteristics and predictors of missed opportunities in lung cancer diagnosis: an electronic health record-based study. J Clin Oncol. 2010;28(20):3307–15. Epub 2010/06/10. [PMC free article: PMC2903328] [PubMed: 20530272] [Cross Ref]
8.
Singh H, Thomas EJ, Wilson L, Kelly PA, Pietz K, Elkeeb D, et al. Errors of diagnosis in pediatric practice: a multisite survey. Pediatrics. 2010;126(1):70–9. Epub 2010/06/23. [PMC free article: PMC2921702] [PubMed: 20566604] [Cross Ref]
9.
Moore LJ, Jones SL, Kreiner LA, McKinley B, Sucher JF, Todd SR, et al. Validation of a screening tool for the early identification of sepsis. The Journal of trauma. 2009;66(6):1539–46. discussion 46-7. Epub 2009/06/11. [PubMed: 19509612] [Cross Ref]
10.
Phillips RL Jr., Bartholomew LA, Dovey SM, Fryer GE Jr., Miyoshi TJ, Green LA. Learning from malpractice claims about negligent, adverse events in primary care in the United States. Quality & safety in health care. 2004;13(2):121–6. Epub 2004/04/08. [PMC free article: PMC1743812] [PubMed: 15069219]
11.
Selbst SM. Pediatric emergency medicine: legal briefs. Pediatric emergency care. 2005;21(3):214–8. Epub 2005/03/04. [PubMed: 15744204]
12.
Tehrani AS, Lee H, Mathews S, Shore A, Frick KD, Makary M, et al., editors. 20-year Summary of U.S. Malpractice Claims for Diagnostic Errors from 1985-2005; 33rd Annual Meeting of the Society for Medical Decision Making; 2011; Chicago, IL.
13.
Bishop TF, Ryan AM, Casalino LP. Paid malpractice claims for adverse events in inpatient and outpatient settings. JAMA. 2011;305(23):2427–31. Epub 2011/06/16. [PubMed: 21673294] [Cross Ref]
14.
Ely JW, Graber ML, Croskerry P. Checklists to reduce diagnostic errors. Acad Med. 2011;86(3):307–13. Epub 2011/01/21. [PubMed: 21248608] [Cross Ref]
15.
Cosby KS. A framework for classifying factors that contribute to error in the emergency department. Annals of emergency medicine. 2003;42(6):815–23. Epub 2003/11/25. [PubMed: 14634609] [Cross Ref]
16.
Tversky A, Kahneman D. Judgment under Uncertainty: Heuristics and Biases. Science. 1974;185(4157):1124–31. Epub 1974/09/27. [PubMed: 17835457] [Cross Ref]
17.
Metcalfe J, Shimamura AP. Metacognition : knowing about knowing. Cambridge, Mass. London: MIT Press; 1994.
18.
Reason J. Human error: models and management. BMJ. 2000;320(7237):768–70. Epub 2000/03/17. [PMC free article: PMC1117770] [PubMed: 10720363]
19.
Berner ES. Diagnostic error in medicine: introduction. Advances in health sciences education : theory and practice. 2009;14 Suppl 1:1–5. Epub 2009/08/12. [PubMed: 19669914] [Cross Ref]
20.
Schiff GD, Bates DW. Can electronic clinical documentation help prevent diagnostic errors? N Engl J Med. 2010;362(12):1066–9. Epub 2010/03/26. [PubMed: 20335582] [Cross Ref]
21.
Winters BD, Aswani MS, Pronovost PJ. Commentary: Reducing diagnostic errors: another role for checklists? Acad Med. 2011;86(3):279–81. Epub 2011/02/25. [PubMed: 21346432] [Cross Ref]
22.
Wahls TL, Cram P. Proposed interventions to decrease the frequency of missed test results. Advances in health sciences education : theory and practice. 2009;14 Suppl 1:51–6. Epub 2009/08/12. [PubMed: 19669920] [Cross Ref]
23.
Singh H, Graber M, Kissam SM, Sorensen AV, Lenfestey NF, Tant EM, et al. System-related interventions to reduce diagnostic errors: a narrative review. BMJ Qual Saf. 2011 [PMC free article: PMC3677060] [PubMed: 22129930] [Cross Ref]
24.
Graber ML, Kissam S, Payne VL, Meyer AN, Sorensen A, Lenfestey N, et al. Cognitive interventions to reduce diagnostic error: a narrative review. BMJ Qual Saf. 2012;21(7):535–57. Epub 2012/05/01. [PubMed: 22543420] [Cross Ref]
25.
Perno JF, Schunk JE, Hansen KW, Furnival RA. Significant reduction in delayed diagnosis of injury with implementation of a pediatric trauma service. Pediatric emergency care. 2005;21(6):367–71. Epub 2005/06/09. [PubMed: 15942513]
26.
Thomas SH, Silen W, Cheema F, Reisner A, Aman S, Goldstein JN, et al. Effects of morphine analgesia on diagnostic accuracy in Emergency Department patients with abdominal pain: a prospective, randomized trial. J Am Coll Surg. 2003;196(1):18–31. Epub 2003/01/09. [PubMed: 12517545]
27.
Bogusevicius A, Maleckas A, Pundzius J, Skaudickas D. Prospective randomised trial of computer-aided diagnosis and contrast radiography in acute small bowel obstruction. Eur J Surg. 2002;168(2):78–83. Epub 2002/07/13. [PubMed: 12113275] [Cross Ref]
28.
Kuperman GJ, Teich JM, Tanasijevic MJ, Ma'Luf N, Rittenberg E, Jha A, et al. Improving response to critical laboratory results with automation: results of a randomized controlled trial. J Am Med Inform Assoc. 1999;6(6):512–22. Epub 1999/12/01. [PMC free article: PMC61393] [PubMed: 10579608]
29.
Dudley M, Channer KS. Assessment of the value of technician reporting of electrocardiographs in an accident and emergency department. J Accid Emerg Med. 1997;14(5):307–10. Epub 1997/10/08. [PMC free article: PMC1343097] [PubMed: 9315933]
30.
Nam YS, Pikarsky AJ, Wexner SD, Singh JJ, Weiss EG, Nogueras JJ, et al. Reproducibility of colonic transit study in patients with chronic constipation. Dis Colon Rectum. 2001;44(1):86–92. Epub 2002/01/24. [PubMed: 11805568]
31.
Beigi B, Uddin JM, McMullan TF, Linardos E. Inaccuracy of diagnosis in a cohort of patients on the waiting list for dacryocystorhinostomy when the diagnosis was made by only syringing the lacrimal system. Eur J Ophthalmol. 2007;17(4):485–9. Epub 2007/08/03. [PubMed: 17671919]
32.
Major K, Shabot MM, Cunneen S. Wireless clinical alerts and patient outcomes in the surgical intensive care unit. Am Surg. 2002;68(12):1057–60. Epub 2003/01/09. [PubMed: 12516808]
33.
Etchells E, Adhikari NK, Wu R, Cheung M, Quan S, Mraz R, et al. Real-time automated paging and decision support for critical laboratory abnormalities. BMJ Qual Saf. 2011;20(11):924–30. Epub 2011/07/05. [PubMed: 21725046] [Cross Ref]
34.
Fitzgerald M, Cameron P, Mackenzie C, Farrow N, Scicluna P, Gocentas R, et al. Trauma resuscitation errors and computer-assisted decision support. Arch Surg. 2011;146(2):218–25. Epub 2011/02/23. [PubMed: 21339436] [Cross Ref]
35.
Chern CH, How CK, Wang LM, Lee CH, Graff L. Decreasing clinically significant adverse events using feedback to emergency physicians of telephone follow-up outcomes. Annals of emergency medicine. 2005;45(1):15–23. Epub 2005/01/07. [PubMed: 15635301] [Cross Ref]
36.
Vernon DD, Furnival RA, Hansen KW, Diller EM, Bolte RG, Johnson DG, et al. Effect of a pediatric trauma response team on emergency department treatment time and mortality of pediatric trauma victims. Pediatrics. 1999;103(1):20–4. Epub 1999/01/26. [PubMed: 9917434]
37.
Sakr M, Angus J, Perrin J, Nixon C, Nicholl J, Wardrope J. Care of minor injuries by emergency nurse practitioners or junior doctors: a randomised controlled trial. Lancet. 1999;354(9187):1321–6. Epub 1999/10/26. [PubMed: 10533859]
38.
Rollman BL, Hanusa BH, Lowe HJ, Gilbert T, Kapoor WN, Schulberg HC. A randomized trial using computerized decision support to improve treatment of major depression in primary care. J Gen Intern Med. 2002;17(7):493–503. Epub 2002/07/23. [PMC free article: PMC1495078] [PubMed: 12133139]
39.
Schriger DL, Gibbons PS, Langone CA, Lee S, Altshuler LL. Enabling the diagnosis of occult psychiatric illness in the emergency department: A randomized, controlled trial of the computerized, self-administered PRIME-MD diagnostic system. Annals of emergency medicine. 2001;37(2):132–40. ISI:000166803800002. [PubMed: 11174229]
40.
Ciatto S, Del Turco MR, Morrone D, Catarzi S, Ambrogetti D, Cariddi A, et al. Independent double reading of screening mammograms. J Med Screen. 1995;2(2):99–101. Epub 1995/01/01. [PubMed: 7497164]
41.
Duijm LE, Groenewoud JH, Fracheboud J, de Koning HJ. Additional double reading of screening mammograms by radiologic technologists: impact on screening performance parameters. J Natl Cancer Inst. 2007;99(15):1162–70. Epub 2007/07/27. [PubMed: 17652282] [Cross Ref]
42.
Howard J, Sundararajan R, Thomas SG, Walsh M, Sundararajan M. Reducing missed injuries at a level II trauma center. J Trauma Nurs. 2006;13(3):89–95. Epub 2006/10/21. [PubMed: 17052086]
43.
Manion E, Cohen MB, Weydert J. Mandatory second opinion in surgical pathology referral material: clinical consequences of major disagreements. The American journal of surgical pathology. 2008;32(5):732–7. Epub 2008/03/25. [PubMed: 18360282] [Cross Ref]
44.
Nordrum I, Johansen M, Amin A, Isaksen V, Ludvigsen JA. Diagnostic accuracy of second-opinion diagnoses based on still images. Hum Pathol. 2004;35(1):129–35. Epub 2004/01/28. [PubMed: 14745735]
45.
Raab SS, Stone CH, Jensen CS, Zarbo RJ, Meier FA, Grzybicki DM, et al. Double slide viewing as a cytology quality improvement initiative. Am J Clin Pathol. 2006;125(4):526–33. Epub 2006/04/22. [PubMed: 16627263] [Cross Ref]
46.
Singh P, Warnakulasuriya S. The two-week wait cancer initiative on oral cancer; the predictive value of urgent referrals to an oral medicine unit. British dental journal. 2006;201(11):717–20. discussion 4. Epub 2006/12/13. [PubMed: 17159958] [Cross Ref]
47.
Bruner JM, Inouye L, Fuller GN, Langford LA. Diagnostic discrepancies and their clinical impact in a neuropathology referral practice. Cancer. 1997;79(4):796–803. Epub 1997/02/15. doi: 10.1002/(SICI)1097-0142(19970215)79:4<796::AID-CNCR17>3.0.CO;2-V [pii] [PubMed: 9024718]
48.
Canon CL, Smith JK, Morgan DE, Jones BC, Fell SC, Kenney PJ, et al. Double reading of barium enemas: is it necessary? AJR American journal of roentgenology. 2003;181(6):1607–10. Epub 2003/11/25. [PubMed: 14627582]
49.
Carew-McColl M. Radiological interpretation in an accident and emergency department. Br J Clin Pract. 1983;37(11-12):375–7. Epub 1983/11/01. [PubMed: 6671078]
50.
Espinosa JA, Nolan TW. Reducing errors made by emergency physicians in interpreting radiographs: longitudinal study. BMJ. 2000;320(7237):737–40. Epub 2000/03/17. [PMC free article: PMC27314] [PubMed: 10720354]
51.
Galasko CS, Monahan PR. Value of re-examining x-ray films of outpatients attending accident services. Br Med J. 1971;1(5750):643–4. Epub 1971/03/20. [PMC free article: PMC1795440] [PubMed: 5548841]
52.
Kwek BH, Lau TN, Ng FC, Gao F. Non-consensual double reading in the Singapore Breast Screening Project: benefits and limitations. Annals of the Academy of Medicine, Singapore. 2003;32(4):438–41. Epub 2003/09/13. [PubMed: 12968545]
53.
Lind AC, Bewtra C, Healy JC, Sims KL. Prospective peer review in surgical pathology. Am J Clin Pathol. 1995;104(5):560–6. Epub 1995/11/01. [PubMed: 7572817]
54.
Lufkin KC, Smith SW, Matticks CA, Brunette DD. Radiologists' review of radiographs interpreted confidently by emergency physicians infrequently leads to changes in patient management. Annals of emergency medicine. 1998;31(2):202–7. Epub 1998/02/24. [PubMed: 9472181]
55.
Murphy R, Slater A, Uberoi R, Bungay H, Ferrett C. Reduction of perception error by double reporting of minimal preparation CT colon. Br J Radiol. 2010;83(988):331–5. Epub 2009/08/05. [PMC free article: PMC3473446] [PubMed: 19651707] [Cross Ref]
56.
Parameswaran L, Prihoda TJ, Sharkey FE. Diagnostic efficacy of additional step-sections in colorectal biopsies originally diagnosed as normal. Hum Pathol. 2008;39(4):579–83. Epub 2008/02/22. [PubMed: 18289637] [Cross Ref]
57.
Raab SS, Grzybicki DM, Mahood LK, Parwani AV, Kuan SF, Rao UN. Effectiveness of random and focused review in detecting surgical pathology error. Am J Clin Pathol. 2008;130(6):905–12. Epub 2008/11/21. [PubMed: 19019767] [Cross Ref]
58.
Robson N, van Benthem PP, Gan R, Dixon AK. Casualty X-ray reporting: a student survey. Clin Radiol. 1985;36(5):479–81. Epub 1985/09/01. [PubMed: 4075715]
59.
Thiesse P, Ollivier L, Di Stefano-Louineau D, Negrier S, Savary J, Pignard K, et al. Response rate accuracy in oncology trials: reasons for interobserver variability. Groupe Francais d'Immunotherapie of the Federation Nationale des Centres de Lutte Contre le Cancer. J Clin Oncol. 1997;15(12):3507–14. Epub 1997/12/13. [PubMed: 9396404]
60.
Westra WH, Kronz JD, Eisele DW. The impact of second opinion surgical pathology on the practice of head and neck surgery: a decade experience at a large referral hospital. Head & neck. 2002;24(7):684–93. Epub 2002/07/12. [PubMed: 12112543] [Cross Ref]
61.
Seltzer SE, Hessel SJ, Herman PG, Swensson RG, Sheriff CR. Resident film interpretations and staff review. AJR American journal of roentgenology. 1981;137(1):129–33. Epub 1981/07/01. [PubMed: 6787863]
62.
McPhee SJ, Bird JA, Jenkins CN, Fordham D. Promoting cancer screening. A randomized, controlled trial of three interventions. Archives of internal medicine. 1989;149(8):1866–72. Epub 1989/08/01. [PubMed: 2764657]
63.
Kundel HL, Nodine CF, Krupinski EA. Computer-displayed eye position as a visual aid to pulmonary nodule interpretation. Invest Radiol. 1990;25(8):890–6. Epub 1990/08/01. [PubMed: 2394571]
64.
Thomas HG, Mason AC, Smith RM, Fergusson CM. Value of radiograph audit in an accident service department. Injury. 1992;23(1):47–50. Epub 1992/01/01. [PubMed: 1541500]
65.
Ross PD, Huang C, Karpf D, Lydick E, Coel M, Hirsch L, et al. Blinded reading of radiographs increases the frequency of errors in vertebral fracture detection. J Bone Miner Res. 1996;11(11):1793–800. Epub 1996/11/01. [PubMed: 8915788] [Cross Ref]
66.
Jiang Y, Nishikawa RM, Schmidt RA, Toledano AY, Doi K. Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications. Radiology. 2001;220(3):787–94. Epub 2001/08/30. [PubMed: 11526283]
67.
Trotter MJ, Bruecks AK. Interpretation of skin biopsies by general pathologists: diagnostic discrepancy rate measured by blinded review. Arch Pathol Lab Med. 2003;127(11):1489–92. Epub 2003/10/22. doi: OA3050 [pii] 10.1043/ 1543-2165(2003)127<1489:IOSBBG>2.0.CO;2[doi] [PubMed: 14567717]
68.
Peldschus K, Herzog P, Wood SA, Cheema JI, Costello P, Schoepf UJ. Computer-aided diagnosis as a second reader: spectrum of findings in CT studies of the chest interpreted as normal. Chest. 2005;128(3):1517–23. Epub 2005/09/16. [PubMed: 16162752] [Cross Ref]
69.
Tsai JJ, Yeun JY, Kumar VA, Don BR. Comparison and interpretation of urinalysis performed by a nephrologist versus a hospital-based clinical laboratory. Am J Kidney Dis. 2005;46(5):820–9. Epub 2005/10/29. [PubMed: 16253721] [Cross Ref]
70.
Goodyear N, Ulness BK, Prentice JL, Cookson BT, Limaye AP. Systematic assessment of culture review as a tool to assess errors in the clinical microbiology laboratory. Arch Pathol Lab Med. 2008;132(11):1792–5. Epub 2008/11/04. [PubMed: 18976017] [Cross Ref]
71.
Hamady ZZ, Mather N, Lansdown MR, Davidson L, Maclennan KA. Surgical pathological second opinion in thyroid malignancy: impact on patients' management and prognosis. Eur J Surg Oncol. 2005;31(1):74–7. Epub 2005/01/12. [PubMed: 15642429] [Cross Ref]
72.
Attard AR, Corlett MJ, Kidner NJ, Leslie AP, Fraser IA. Safety of early pain relief for acute abdominal pain. BMJ. 1992;305(6853):554–6. Epub 1992/09/05. [PMC free article: PMC1883284] [PubMed: 1393034]
73.
Resnick NM, Brandeis GH, Baumann MM, DuBeau CE, Yalla SV. Misdiagnosis of urinary incontinence in nursing home women: prevalence and a proposed solution. Neurourol Urodyn. 1996;15(6):599–613. discussion 8. Epub 1996/01/01. doi: 10.1002/(SICI)1520-6777(1996)15:6<599::AID-NAU2>3.0.CO;2-A [pii] 10.1002/(SICI)1520-6777(1996)15:6<599::AID-NAU2>3.0.CO;2-A [doi] [PubMed: 8916113]
74.
Borgstein PJ, Gordijn RV, Eijsbouts QA, Cuesta MA. Acute appendicitis--a clear-cut case in men, a guessing game in young women. A prospective study on the role of laparoscopy. Surg Endosc. 1997;11(9):923–7. Epub 1997/09/19. [PubMed: 9294274]
75.
Vermeulen B, Morabia A, Unger PF, Goehring C, Grangier C, Skljarov I, et al. Acute appendicitis: influence of early pain relief on the accuracy of clinical and US findings in the decision to operate--a randomized trial. Radiology. 1999;210(3):639–43. Epub 1999/04/20. [PubMed: 10207461]
76.
Prieto VG, Argenyi ZB, Barnhill RL, Duray PH, Elenitsas R, From L, et al. Are en face frozen sections accurate for diagnosing margin status in melanocytic lesions? Am J Clin Pathol. 2003;120(2):203–8. Epub 2003/08/23. [PubMed: 12931550] [Cross Ref]
77.
Kokki H, Lintula H, Vanamo K, Heiskanen M, Eskelinen M. Oxycodone vs placebo in children with undifferentiated abdominal pain: a randomized, double-blind clinical trial of the effect of analgesia on diagnostic accuracy. Arch Pediatr Adolesc Med. 2005;159(4):320–5. Epub 2005/04/06. [PubMed: 15809382] [Cross Ref]
78.
Hewett DG, Rex DK. Cap-fitted colonoscopy: a randomized, tandem colonoscopy study of adenoma miss rates. Gastrointest Endosc. 2010;72(4):775–81. Epub 2010/06/29. [PubMed: 20579648] [Cross Ref]
79.
Brossner C, Madersbacher S, Bayer G, Pycha A, Klingler HC, Maier U. Comparative study of two different TRUS-guided sextant biopsy techniques in detecting prostate cancer in one biopsy session. European urology. 2000;37(1):65–71. Epub 2000/02/15. [PubMed: 10671788]
80.
Naughton CK, Miller DC, Mager DE, Ornstein DK, Catalona WJ. A prospective randomized trial comparing 6 versus 12 prostate biopsy cores: impact on cancer detection. The Journal of urology. 2000;164(2):388–92. Epub 2000/07/14. [PubMed: 10893592]
81.
Presti JC Jr., Chang JJ, Bhargava V, Shinohara K. The optimal systematic prostate biopsy scheme should include 8 rather than 6 biopsies: results of a prospective clinical trial. The Journal of urology. 2000;163(1):163–6. discussion 6-7. Epub 1999/12/22. [PubMed: 10604337]
82.
Ravery V, Goldblatt L, Royer B, Blanc E, Toublanc M, Boccon-Gibod L. Extensive biopsy protocol improves the detection rate of prostate cancer. The Journal of urology. 2000;164(2):393–6. Epub 2000/07/14. [PubMed: 10893593]
83.
Weatherburn G, Bryan S, Nicholas A, Cocks R. The effect of a picture archiving and communications system (PACS) on diagnostic performance in the accident and emergency department. J Accid Emerg Med. 2000;17(3):180–4. Epub 2000/05/20. [PMC free article: PMC1725383] [PubMed: 10819379]
84.
de Lacey G, Barker A, Harper J, Wignall B. An assessment of the clinical effects of reporting accident and emergency radiographs. Br J Radiol. 1980;53(628):304–9. Epub 1980/04/01. [PubMed: 7378697]
85.
Jacobs MJ, Edmondson MJ, Lowry JC. Accuracy of diagnosis of fractures by maxillofacial and accident and emergency doctors using plain radiography compared with a telemedicine system: a prospective study. Br J Oral Maxillofac Surg. 2002;40(2):156–62. Epub 2002/08/16. [PubMed: 12180212]
86.
McCarthy PL, Sznajderman SD, Lustman-Findling K, Baron MA, Fink HD, Czarkowski N, et al. Mothers' clinical judgment: a randomized trial of the Acute Illness Observation Scales. J Pediatr. 1990;116(2):200–6. Epub 1990/02/01. [PubMed: 2405140]
87.
Fridriksson S, Hillman J, Landtblom AM, Boive J. Education of referring doctors about sudden onset headache in subarachnoid hemorrhage. A prospective study. Acta Neurol Scand. 2001;103(4):238–42. Epub 2001/05/01. [PubMed: 11328195]
88.
Thaler T, Tempelmann V, Maggiorini M, Rudiger A. The frequency of electrocardiographic errors due to electrode cable switches: a before and after study. J Electrocardiol. 2010;43(6):676–81. Epub 2010/07/02. [PubMed: 20591441] [Cross Ref]
89.
Gleadhill DN, Thomson JY, Simms P. Can more efficient use be made of x ray examinations in the accident and emergency department? Br Med J (Clin Res Ed) 1987;294(6577):943–7. Epub 1987/04/11. [PMC free article: PMC1246007] [PubMed: 3107669]
90.
Linver MN, Paster SB, Rosenberg RD, Key CR, Stidley CA, King WV. Improvement in mammography interpretation skills in a community radiology practice after dedicated teaching courses: 2-year medical audit of 38,633 cases. Radiology. 1992;184(1):39–43. Epub 1992/07/01. [PubMed: 1609100]
91.
Enderson BL, Reath DB, Meadors J, Dallas W, DeBoo JM, Maull KI. The tertiary trauma survey: a prospective study of missed injury. The Journal of trauma. 1990;30(6):666–9. discussion 9-70. Epub 1990/06/01. [PubMed: 2352294]
92.
Klassen TP, Ropp LJ, Sutcliffe T, Blouin R, Dulberg C, Raman S, et al. A randomized, controlled trial of radiograph ordering for extremity trauma in a pediatric emergency department. Annals of emergency medicine. 1993;22(10):1524–9. Epub 1993/10/01. [PubMed: 8214829]
93.
Biffl WL, Harrington DT, Cioffi WG. Implementation of a tertiary trauma survey decreases missed injuries. The Journal of trauma. 2003;54(1):38–43. discussion 4. Epub 2003/01/25. [PubMed: 12544897] [Cross Ref]
94.
Soundappan SV, Holland AJ, Cass DT. Role of an extended tertiary survey in detecting missed injuries in children. The Journal of trauma. 2004;57(1):114–8. discussion 8. Epub 2004/07/31. [PubMed: 15284560]
95.
Ursprung R, Gray JE, Edwards WH, Horbar JD, Nickerson J, Plsek P, et al. Real time patient safety audits: improving safety every day. Quality & safety in health care. 2005;14(4):284–9. Epub 2005/08/04. [PMC free article: PMC1744058] [PubMed: 16076794] [Cross Ref]
96.
Raab SS, Andrew-Jaja C, Condel JL, Dabbs DJ. Improving Papanicolaou test quality and reducing medical errors by using Toyota production system methods. Am J Obstet Gynecol. 2006;194(1):57–64. Epub 2006/01/04. [PubMed: 16389010] [Cross Ref]
97.
Raab SS, Grzybicki DM, Sudilovsky D, Balassanian R, Janosky JE, Vrbin CM. Effectiveness of Toyota process redesign in reducing thyroid gland fine-needle aspiration error. Am J Clin Pathol. 2006;126(4):585–92. Epub 2006/08/30. [PubMed: 16938657] [Cross Ref]
98.
Raab SS, Tworek JA, Souers R, Zarbo RJ. The value of monitoring frozen section-permanent section correlation data over time. Arch Pathol Lab Med. 2006;130(3):337–42. Epub 2006/03/08. [PubMed: 16519561] [Cross Ref]
99.
Raab SS, Jones BA, Souers R, Tworek JA. The effect of continuous monitoring of cytologic-histologic correlation data on cervical cancer screening performance. Arch Pathol Lab Med. 2008;132(1):16–22. Epub 2008/01/10. [PubMed: 18181668] [Cross Ref]
100.
Mueller CA, Klaassen-Mielke R, Penner E, Junius-Walker U, Hummers-Pradier E, Theile G. Disclosure of new health problems and intervention planning using a geriatric assessment in a primary care setting. Croat Med J. 2010;51(6):493–500. Epub 2010/12/17. [PMC free article: PMC3012401] [PubMed: 21162161]
101.
de Vries EN, Eikens-Jansen MP, Hamersma AM, Smorenburg SM, Gouma DJ, Boermeester MA. Prevention of surgical malpractice claims by use of a surgical safety checklist. Ann Surg. 2011;253(3):624–8. Epub 2011/01/07. [PubMed: 21209590] [Cross Ref]
102.
Lewis G, Sharp D, Bartholomew J, Pelosi AJ. Computerized assessment of common mental disorders in primary care: effect on clinical outcome. Fam Pract. 1996;13(2):120–6. Epub 1996/04/01. [PubMed: 8732321]
103.
Wexler JR, Swender PT, Tunnessen WW Jr., Oski FA. Impact of a system of computer-assisted diagnosis. Initial evaluation of the hospitalized patient. Am J Dis Child. 1975;129(2):203–5. Epub 1975/02/11. [PubMed: 1091140]
104.
Wellwood J, Johannessen S, Spiegelhalter DJ. How does computer-aided diagnosis improve the management of acute abdominal pain? Ann R Coll Surg Engl. 1992;74(1):40–6. Epub 1992/01/01. [PMC free article: PMC2497469] [PubMed: 1736794]
105.
Selker HP, Beshansky JR, Griffith JL, Aufderheide TP, Ballin DS, Bernard SA, et al. Use of the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI) to assist with triage of patients with chest pain or other symptoms suggestive of acute cardiac ischemia. A multicenter, controlled clinical trial. Ann Intern Med. 1998;129(11):845–55. Epub 1998/12/29. [PubMed: 9867725]
106.
Poon EG, Kuperman GJ, Fiskio J, Bates DW. Real-time notification of laboratory data requested by users through alphanumeric pagers. J Am Med Inform Assoc. 2002;9(3):217–22. Epub 2002/04/25. [PMC free article: PMC344581] [PubMed: 11971882]
107.
Gur D, Sumkin JH, Rockette HE, Ganott M, Hakim C, Hardesty L, et al. Changes in breast cancer detection and mammography recall rates after the introduction of a computer-aided detection system. J Natl Cancer Inst. 2004;96(3):185–90. Epub 2004/02/05. PubMed. [PubMed: 14759985]
108.
Kakeda S, Moriya J, Sato H, Aoki T, Watanabe H, Nakata H, et al. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR American journal of roentgenology. 2004;182(2):505–10. Epub 2004/01/23. [PubMed: 14736690]
109.
Cupples TE, Cunningham JE, Reynolds JC. Impact of computer-aided detection in a regional screening mammography program. AJR American journal of roentgenology. 2005;185(4):944–50. Epub 2005/09/24. [PubMed: 16177413] [Cross Ref]
110.
Ramnarayan P, Winrow A, Coren M, Nanduri V, Buchdahl R, Jacobs B, et al. Diagnostic omission errors in acute paediatric practice: impact of a reminder system on decision-making. BMC medical informatics and decision making. 2006;6:37. Epub 2006/11/08. [PMC free article: PMC1654143] [PubMed: 17087835] [Cross Ref]
111.
Fenton JJ, Taplin SH, Carney PA, Abraham L, Sickles EA, D'Orsi C, et al. Influence of computer-aided detection on performance of screening mammography. N Engl J Med. 2007;356(14):1399–409. Epub 2007/04/06. [PMC free article: PMC3182841] [PubMed: 17409321] [Cross Ref]
112.
Park HI, Min WK, Lee W, Park H, Park CJ, Chi HS, et al. Evaluating the short message service alerting system for critical value notification via PDA telephones. Ann Clin Lab Sci. 2008;38(2):149–56. Epub 2008/05/13. [PubMed: 18469361]
113.
Piva E, Sciacovelli L, Zaninotto M, Laposata M, Plebani M. Evaluation of effectiveness of a computerized notification system for reporting critical values. Am J Clin Pathol. 2009;131(3):432–41. Epub 2009/02/21. [PubMed: 19228648] [Cross Ref]
114.
Singh H, Wilson L, Petersen LA, Sawhney MK, Reis B, Espadas D, et al. Improving follow-up of abnormal cancer screens using electronic health records: trust but verify test result communication. BMC medical informatics and decision making. 2009;9:49. Epub 2009/12/17. [PMC free article: PMC2797509] [PubMed: 20003236] [Cross Ref]
115.
David CV, Chira S, Eells SJ, Ladrigan M, Papier A, Miller LG, et al. Diagnostic accuracy in patients admitted to hospitals with cellulitis. Dermatol Online J. 2011;17(3):1. Epub 2011/03/24. [PubMed: 21426867]
116.
Olsson SE, Ohlsson M, Ohlin H, Dzaferagic S, Nilsson ML, Sandkull P, et al. Decision support for the initial triage of patients with acute coronary syndromes. Clin Physiol Funct Imaging. 2006;26(3):151–6. Epub 2006/04/28. [PubMed: 16640509] [Cross Ref]
117.
Pozen MW, D'Agostino RB, Selker HP, Sytkowski PA, Hood WB Jr. A predictive instrument to improve coronary-care-unit admission practices in acute ischemic heart disease. A prospective multicenter clinical trial. N Engl J Med. 1984;310(20):1273–8. Epub 1984/05/17. [PubMed: 6371525] [Cross Ref]
118.
Thomas DC, Spitzer WO, MacFarlane JK. Inter-observer error among surgeons and nurses in presymptomatic detection of breast disease. J Chronic Dis. 1981;34(12):617–26. Epub 1981/01/01. [PubMed: 7309826]
119.
Davis Giardina T, S H. Should patients get direct access to their laboratory test results?: An answer with many questions. JAMA: The Journal of the American Medical Association. 2011;306(22):2502–3. [PubMed: 22122864] [Cross Ref]
120.
Casalino LP, Dunham D, Chin MH, Bielang R, Kistner EO, Karrison TG, et al. Frequency of Failure to Inform Patients of Clinically Significant Outpatient Test Results. Arch Intern Med. 2009;169(12):1123–9. [PubMed: 19546413]
121.
Callen JL, Westbrook JI, Georgiou A, Li J. Failure to Follow-Up Test Results for Ambulatory Patients: A Systematic Review. J Gen Intern Med. 2011. Epub 2011/12/21. [PMC free article: PMC3445672] [PubMed: 22183961] [Cross Ref]
122.
Molins E, Comas M, Roman R, Rodriguez-Blanco T, Sala M, Macia F, et al. Effect of participation on the cumulative risk of false-positive recall in a breast cancer screening programme. Public Health. 2009;123(9):635–7. Epub 2009/09/08. [PubMed: 19733372] [Cross Ref]
123.
Singh H, Vij M. Eight recommendations for policies for communicating abnormal test results. Jt Comm J Qual Patient Saf. 2010;36:226–32. [PubMed: 20480756]
Cover of Making Health Care Safer II
Making Health Care Safer II: An Updated Critical Analysis of the Evidence for Patient Safety Practices.
Evidence Reports/Technology Assessments, No. 211.

PubMed Health Blog...

read all...

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...