Burden of serious harms from diagnostic error in the USA.

BACKGROUND: Diagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts. OBJECTIVE: We sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence. METHODS: Cross-sectional analysis of US-based nationally representative observational data. We estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). Annual new cancers were taken from US-based registries (2014). Years were selected for coding consistency with prior literature. Disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories) were multiplied by literature-based rates to derive diagnostic errors and serious harms. We calculated uncertainty estimates using Monte Carlo simulations. Validity checks included sensitivity analyses and comparison with prior published estimates. RESULTS: Annual US incidence was 6.0 M vascular events, 6.2 M infections and 1.5 M cancers. Per 'Big Three' dangerous disease case, weighted mean error and serious harm rates were 11.1% and 4.4%, respectively. Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), we estimated total serious harms annually in the USA to be 795 000 (plausible range 598 000-1 023 000). Sensitivity analyses using more conservative assumptions estimated 549 000 serious harms. Results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. The 15 dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%. CONCLUSION: An estimated 795 000 Americans become permanently disabled or die annually across care settings because dangerous diseases are misdiagnosed. Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined.

Serotonin Degeneration and Amyloid-ß Deposition in Mild Cognitive Impairment: Relationship to Cognitive Deficits.

BACKGROUND: Neuropathological and neuroimaging studies have demonstrated degeneration of the serotonin system in Alzheimer's disease (AD). Neuroimaging studies have extended these observations to the preclinical stages of AD, mild cognitive impairment (MCI). Serotonin degeneration has been observed also in transgenic amyloid mouse models, prior to widespread cortical distribution of amyloid-ß (Aß). OBJECTIVE: The present study evaluated the regional distribution of the serotonin transporter (5-HTT) and of Aß in individuals with MCI and healthy older controls, as well as the contribution of 5-HTT and Aß to cognitive deficits. METHODS: Forty-nine MCI participants and 45 healthy older controls underwent positron emission tomography (PET) imaging of 5-HTT and Aß, structural magnetic resonance imaging and neuropsychological assessments. RESULTS: Lower cortical, striatal, and limbic 5-HTT and higher cortical Aß was observed in MCIs relative to healthy controls. Lower 5-HTT, mainly in limbic regions, was correlated with greater deficits in auditory-verbal and visual-spatial memory and semantic, not phonemic fluency. Higher cortical A ß was associated with greater deficits in auditory-verbal and visual-spatial memory and in semantic, not phonemic fluency. When modeling the association between cognition, gray matter volumes and Aß, inclusion of 5-HTT in limbic and in select cortical regions significantly improved model fit for auditory-verbal and visual-spatial memory and semantic, but not phonemic fluency. CONCLUSIONS: These results support the role of serotonin degeneration in the memory and semantic fluency deficits observed in MCI.

Molecular imaging of the association between serotonin degeneration and beta-amyloid deposition in mild cognitive impairment.

BACKGROUND: Degeneration of the serotonin system has been observed in Alzheimer's disease (AD) and in mild cognitive impairment (MCI). In transgenic amyloid mouse models, serotonin degeneration is detected prior to widespread cortical beta-amyloid (Aß) deposition, also suggesting that serotonin degeneration may be observed in preclinical AD. METHODS: The differences in the distribution of serotonin degeneration (reflected by the loss of the serotonin transporter, 5-HTT) relative to Aß deposition was measured with positron emission tomography in a group of individuals with MCI and a group of healthy older adults. A multi-modal partial least squares (mmPLS) algorithm was applied to identify the spatial covariance pattern between 5-HTT availability and Aß deposition. RESULTS: Forty-five individuals with MCI and 35 healthy older adults were studied, 22 and 27 of whom were included in the analyses who were "amyloid positive" and "amyloid negative", respectively. A pattern of lower cortical, subcortical and limbic 5-HTT availability and higher cortical Aß deposition distinguished the MCI from the healthy older control participants. Greater expression of this pattern was correlated with greater deficits in memory and executive function in the MCI group, not in the control group. CONCLUSION: A spatial covariance pattern of lower 5-HTT availability and Aß deposition was observed to a greater extent in an MCI group relative to a control group and was associated with cognitive impairment in the MCI group. The results support the application of mmPLS to understand the neurochemical changes associated with Aß deposition in the course of preclinical AD.

Are Mental Health and Substance Use Disorders Risk Factors for Missed Acute Myocardial Infarction Diagnoses Among Chest Pain or Dyspnea Encounters in the Emergency Department?

STUDY OBJECTIVE: To assess if having a mental health and/or substance use disorder is associated with a missed acute myocardial infarction diagnosis in the emergency department (ED). METHODS: This was a retrospective cohort analysis (2009 to 2017) of adult ED encounters at Kaiser Permanente Southern California. We used the validated symptom-disease pair analysis of diagnostic error methodological approach to "look back" and "look forward" and identify missed acute myocardial infarctions within 30 days of a treat-and-release ED visit. We use adjusted logistic regression to report the odds of missed acute myocardial infarction among patients with a history of mental health and/or substance use disorders. RESULTS: The look-back analysis identified 44,473 acute myocardial infarction hospital encounters; 574 (1.3%) diagnoses were missed. The odds of missed diagnoses were higher in patients with mental health disorders (odds ratio [OR] 1.48, 95% confidence interval [CI] 1.23 to 1.77) but not in those with substance abuse disorders (OR 1.22, 95% CI 0.91 to 1.62). The highest risk was observed in those with co-occurring disorders (OR 1.90, 95% CI 1.30 to 2.76). The look-forward analysis identified 325,088 chest pain/dyspnea ED encounters; 508 (0.2%) were missed acute myocardial infarctions. No significant associations of missed acute myocardial infarction were revealed in either group (mental health disorder: OR 0.92, 95% CI 0.71 to 1.18; substance use disorder: OR 1.22, 95% CI 0.80 to 1.85). CONCLUSION: The look-back analysis identified patients with mental illness at increased risk of missed acute myocardial infarction diagnosis, with the highest risk observed in those with a history of comorbid substance abuse. Having substance use disorders alone did not increase this risk in either cohort. The look-forward analysis revealed challenges in prospectively identifying high-risk patients to target for improvement.

Rate of sepsis hospitalizations after misdiagnosis in adult emergency department patients: a look-forward analysis with administrative claims data using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) methodology in an integrated health system.

OBJECTIVES: Delays in sepsis diagnosis can increase morbidity and mortality. Previously, we performed a Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) "look-back" analysis to identify symptoms at risk for delayed sepsis diagnosis. We found treat-and-release emergency department (ED) encounters for fluid and electrolyte disorders (FED) and altered mental status (AMS) were associated with downstream sepsis hospitalizations. In this "look-forward" analysis, we measure the potential misdiagnosis-related harm rate for sepsis among patients with these symptoms. METHODS: Retrospective cohort study using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (2013-2018). Patients ≥18 years with ≥1 treat-and-release ED encounter for FED or AMS were included. Observed greater than expected sepsis hospitalizations within 30 days of ED treat-and-release encounters were considered potential misdiagnosis-related harms. Temporal analyses were employed to differentiate case and comparison (superficial injury/contusion ED encounters) cohorts. RESULTS: There were 4,549 treat-and-release ED encounters for FED or AMS, 26 associated with a sepsis hospitalization in the next 30 days. The observed (0.57%) minus expected (0.13%) harm rate was 0.44% (absolute) and 4.5-fold increased over expected (relative). There was a spike in sepsis hospitalizations in the week following FED/AMS ED visits. There were fewer sepsis hospitalizations and no spike in admissions in the week following superficial injury/contusion ED visits. Potentially misdiagnosed patients were older and more medically complex. CONCLUSIONS: Potential misdiagnosis-related harms from sepsis are infrequent but measurable using SPADE. This look-forward analysis validated our previous look-back study, demonstrating the SPADE approach can be used to study infectious disease syndromes.

Antecedent treat-and-release diagnoses prior to sepsis hospitalization among adult emergency department patients: a look-back analysis employing insurance claims data using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) methodology.

OBJECTIVES: The aim of this study was to identify delays in early pre-sepsis diagnosis in emergency departments (ED) using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach. METHODS: SPADE methodology was employed using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (KPMAS). Study cohort included KPMAS members ≥18 years with ≥1 sepsis hospitalization 1/1/2013-12/31/2018. A look-back analysis identified treat-and-release ED visits in the month prior to sepsis hospitalizations. Top 20 diagnoses associated with these ED visits were identified; two diagnosis categories were distinguished as being linked to downstream sepsis hospitalizations. Observed-to-expected (O:E) and temporal analyses were performed to validate the symptom selection; results were contrasted to a comparison group. Demographics of patients that did and did not experience sepsis misdiagnosis were compared. RESULTS: There were 3,468 sepsis hospitalizations during the study period and 766 treat-and-release ED visits in the month prior to hospitalization. Patients discharged from the ED with fluid and electrolyte disorders (FED) and altered mental status (AMS) were most likely to have downstream sepsis hospitalizations (O:E ratios of 2.66 and 2.82, respectively). Temporal analyses revealed that these symptoms were overrepresented and temporally clustered close to the hospitalization date. Approximately 2% of sepsis hospitalizations were associated with prior FED or AMS ED visits. CONCLUSIONS: Treat-and-release ED encounters for FED and AMS may represent harbingers for downstream sepsis hospitalizations. The SPADE approach can be used to develop performance measures that identify pre-sepsis.

Rate of diagnostic errors and serious misdiagnosis-related harms for major vascular events, infections, and cancers: toward a national incidence estimate using the "Big Three".

BACKGROUND: Missed vascular events, infections, and cancers account for ~75% of serious harms from diagnostic errors. Just 15 diseases from these "Big Three" categories account for nearly half of all serious misdiagnosis-related harms in malpractice claims. As part of a larger project estimating total US burden of serious misdiagnosis-related harms, we performed a focused literature review to measure diagnostic error and harm rates for these 15 conditions. METHODS: We searched PubMed, Google, and cited references. For errors, we selected high-quality, modern, US-based studies, if available, and best available evidence otherwise. For harms, we used literature-based estimates of the generic (disease-agnostic) rate of serious harms (morbidity/mortality) per diagnostic error and applied claims-based severity weights to construct disease-specific rates. Results were validated via expert review and comparison to prior literature that used different methods. We used Monte Carlo analysis to construct probabilistic plausible ranges (PPRs) around estimates. RESULTS: Rates for the 15 diseases were drawn from 28 published studies representing 91,755 patients. Diagnostic error (false negative) rates ranged from 2.2% (myocardial infarction) to 62.1% (spinal abscess), with a median of 13.6% [interquartile range (IQR) 9.2-24.7] and an aggregate mean of 9.7% (PPR 8.2-12.3). Serious misdiagnosis-related harm rates per incident disease case ranged from 1.2% (myocardial infarction) to 35.6% (spinal abscess), with a median of 5.5% (IQR 4.6-13.6) and an aggregate mean of 5.2% (PPR 4.5-6.7). Rates were considered face valid by domain experts and consistent with prior literature reports. CONCLUSIONS: Diagnostic improvement initiatives should focus on dangerous conditions with higher diagnostic error and misdiagnosis-related harm rates.

Missed acute myocardial infarction in the emergency department-standardizing measurement of misdiagnosis-related harms using the SPADE method.

OBJECTIVES: Diagnostic error is a serious public health problem. Measuring diagnostic performance remains elusive. We sought to measure misdiagnosis-related harms following missed acute myocardial infarctions (AMI) in the emergency department (ED) using the symptom-disease pair analysis of diagnostic error (SPADE) method. METHODS: Retrospective administrative data analysis (2009-2017) from a single, integrated health system using International Classification of Diseases (ICD) coded discharge diagnoses. We looked back 30 days from AMI hospitalizations for antecedent ED treat-and-release visits to identify symptoms linked to probable missed AMI (observed > expected). We then looked forward from these ED discharge diagnoses to identify symptom-disease pair misdiagnosis-related harms (AMI hospitalizations within 30-days, representing diagnostic adverse events). RESULTS: A total of 44,473 AMI hospitalizations were associated with 2,874 treat-and-release ED visits in the prior 30 days. The top plausibly-related ED discharge diagnoses were "chest pain" and "dyspnea" with excess treat-and-release visit rates of 9.8% (95% CI 8.5-11.2%) and 3.4% (95% CI 2.7-4.2%), respectively. These represented 574 probable missed AMIs resulting in hospitalization (adverse event rate per AMI 1.3%, 95% CI 1.2-1.4%). Looking forward, 325,088 chest pain or dyspnea ED discharges were followed by 508 AMI hospitalizations (adverse event rate per symptom discharge 0.2%, 95% CI 0.1-0.2%). CONCLUSIONS: The SPADE method precisely quantifies misdiagnosis-related harms from missed AMIs using administrative data. This approach could facilitate future assessment of diagnostic performance across health systems. These results correspond to ∼10,000 potentially-preventable harms annually in the US. However, relatively low error and adverse event rates may pose challenges to reducing harms for this ED symptom-disease pair.

Controversies in diagnosis: contemporary debates in the diagnostic safety literature.

Since the 2015 publication of the National Academy of Medicine's (NAM) Improving Diagnosis in Health Care (Improving Diagnosis in Health Care. In: Balogh EP, Miller BT, Ball JR, editors. Improving Diagnosis in Health Care. Washington (DC): National Academies Press, 2015.), literature in diagnostic safety has grown rapidly. This update was presented at the annual international meeting of the Society to Improve Diagnosis in Medicine (SIDM). We focused our literature search on articles published between 2016 and 2018 using keywords in Pubmed and the Agency for Healthcare Research and Quality (AHRQ)'s Patient Safety Network's running bibliography of diagnostic error literature (Diagnostic Errors Patient Safety Network: Agency for Healthcare Research and Quality; Available from: https://psnet.ahrq.gov/search?topic=Diagnostic-Errors&f_topicIDs=407). Three key topics emerged from our review of recent abstracts in diagnostic safety. First, definitions of diagnostic error and related concepts are evolving since the NAM's report. Second, medical educators are grappling with new approaches to teaching clinical reasoning and diagnosis. Finally, the potential of artificial intelligence (AI) to advance diagnostic excellence is coming to fruition. Here we present contemporary debates around these three topics in a pro/con format.

Serious misdiagnosis-related harms in malpractice claims: The "Big Three" - vascular events, infections, and cancers.

Background Diagnostic errors cause substantial preventable harm, but national estimates vary widely from 40,000 to 4 million annually. This cross-sectional analysis of a large medical malpractice claims database was the first phase of a three-phase project to estimate the US burden of serious misdiagnosis-related harms. Methods We sought to identify diseases accounting for the majority of serious misdiagnosis-related harms (morbidity/mortality). Diagnostic error cases were identified from Controlled Risk Insurance Company (CRICO)'s Comparative Benchmarking System (CBS) database (2006-2015), representing 28.7% of all US malpractice claims. Diseases were grouped according to the Agency for Healthcare Research and Quality (AHRQ) Clinical Classifications Software (CCS) that aggregates the International Classification of Diseases diagnostic codes into clinically sensible groupings. We analyzed vascular events, infections, and cancers (the "Big Three"), including frequency, severity, and settings. High-severity (serious) harms were defined by scores of 6-9 (serious, permanent disability, or death) on the National Association of Insurance Commissioners (NAIC) Severity of Injury Scale. Results From 55,377 closed claims, we analyzed 11,592 diagnostic error cases [median age 49, interquartile range (IQR) 36-60; 51.7% female]. These included 7379 with high-severity harms (53.0% death). The Big Three diseases accounted for 74.1% of high-severity cases (vascular events 22.8%, infections 13.5%, and cancers 37.8%). In aggregate, the top five from each category (n = 15 diseases) accounted for 47.1% of high-severity cases. The most frequent disease in each category, respectively, was stroke, sepsis, and lung cancer. Causes were disproportionately clinical judgment factors (85.7%) across categories (range 82.0-88.8%). Conclusions The Big Three diseases account for about three-fourths of serious misdiagnosis-related harms. Initial efforts to improve diagnosis should focus on vascular events, infections, and cancers.

Describing the Evidence Base for Accreditation in Undergraduate Medical Education Internationally: A Scoping Review.

PURPOSE: To summarize the state of evidence related to undergraduate medical education (UME) accreditation internationally, describe from whom and where the evidence has come, and identify opportunities for further investigation. METHOD: The authors searched Embase, ERIC, PubMed, and Scopus from inception through January 31, 2018, without language restrictions, to identify peer-reviewed articles on UME accreditation. Articles were classified as scholarship if all Glassick's criteria were met and as nonscholarship if not all were met. Author, accrediting agency, and study characteristics were analyzed. RESULTS: Database searching identified 1,379 nonduplicate citations, resulting in 203 unique, accessible articles for full-text review. Of these and with articles from hand searching added, 36 articles were classified as scholarship (30 as research) and 85 as nonscholarship. Of the 36 scholarship and 85 nonscholarship articles, respectively, 21 (58%) and 44 (52%) had an author from the United States or Canada, 8 (22%) and 11 (13%) had an author from a low- or middle-income country, and 16 (44%) and 43 (51%) had an author affiliated with a regulatory authority. Agencies from high-income countries were featured most often (scholarship: 28/60 [47%]; nonscholarship: 70/101 [69%]). Six (17%) scholarship articles reported receiving funding. All 30 research studies were cross-sectional or retrospective, 12 (40%) reported only analysis of accreditation documents, and 5 (17%) attempted to link accreditation with educational outcomes. CONCLUSIONS: Limited evidence exists to support current UME accreditation practices or guide accreditation system creation or enhancement. More research is required to optimize UME accreditation systems' value for students, programs, and society.

Molecular imaging of serotonin degeneration in mild cognitive impairment.

Neuropathological and neuroimaging studies have consistently demonstrated degeneration of monoamine systems, especially the serotonin system, in normal aging and Alzheimer's disease. The evidence for degeneration of the serotonin system in mild cognitive impairment is limited. Thus, the goal of the present study was to measure the serotonin transporter in vivo in mild cognitive impairment and healthy controls. The serotonin transporter is a selective marker of serotonin terminals and of the integrity of serotonin projections to cortical, subcortical and limbic regions and is found in high concentrations in the serotonergic cell bodies of origin of these projections (raphe nuclei). Twenty-eight participants with mild cognitive impairment (age 66.6±6.9, 16 males) and 28 healthy, cognitively normal, demographically matched controls (age 66.2±7.1, 15 males) underwent magnetic resonance imaging for measurement of grey matter volumes and high-resolution positron emission tomography with well-established radiotracers for the serotonin transporter and regional cerebral blood flow. Beta-amyloid imaging was performed to evaluate, in combination with the neuropsychological testing, the likelihood of subsequent cognitive decline in the participants with mild cognitive impairment. The following hypotheses were tested: 1) the serotonin transporter would be lower in mild cognitive impairment compared to controls in cortical and limbic regions, 2) in mild cognitive impairment relative to controls, the serotonin transporter would be lower to a greater extent and observed in a more widespread pattern than lower grey matter volumes or lower regional cerebral blood flow and 3) lower cortical and limbic serotonin transporters would be correlated with greater deficits in auditory-verbal and visual-spatial memory in mild cognitive impairment, not in controls. Reduced serotonin transporter availability was observed in mild cognitive impairment compared to controls in cortical and limbic areas typically affected by Alzheimer's disease pathology, as well as in sensory and motor areas, striatum and thalamus that are relatively spared in Alzheimer's disease. The reduction of the serotonin transporter in mild cognitive impairment was greater than grey matter atrophy or reductions in regional cerebral blood flow compared to controls. Lower cortical serotonin transporters were associated with worse performance on tests of auditory-verbal and visual-spatial memory in mild cognitive impairment, not in controls. The serotonin system may represent an important target for prevention and treatment of MCI, particularly the post-synaptic receptors (5-HT4 and 5-HT6), which may not be as severely affected as presynaptic aspects of the serotonin system, as indicated by the observation of lower serotonin transporters in MCI relative to healthy controls.

Association between serotonin denervation and resting-state functional connectivity in mild cognitive impairment.

Resting-state functional connectivity alterations have been demonstrated in Alzheimer's disease (AD) and mild cognitive impairment (MCI) before the observation of AD neuropathology, but mechanisms driving these changes are not well understood. Serotonin neurodegeneration has been observed in MCI and AD and is associated with cognitive deficits and neuropsychiatric symptoms, but the role of the serotonin system in relation to brain network dysfunction has not been a major focus of investigation. The current study investigated the relationship between serotonin transporter availability (SERT; measured using positron emission tomography) and brain network functional connectivity (measured using resting-state functional MRI) in 20 participants with MCI and 21 healthy controls. Two SERT regions of interest were selected for the analysis: the Dorsal Raphe Nuclei (DRN) and the precuneus which represent the cell bodies of origin and a cortical target of projections of the serotonin system, respectively. Both regions show decreased SERT in MCI compared to controls and are the site of early AD pathology. Average resting-state functional connectivity did not differ between MCI and controls. Decreased SERT in DRN was associated with lower hippocampal resting-state connectivity in MCI participants compared to controls. Decreased SERT in the right precuneus was also associated with lower resting-state connectivity of the retrosplenial cortex to the dorsal lateral prefrontal cortex and higher resting-state connectivity of the retrosplenial cortex to the posterior cingulate and in patients with MCI but not in controls. These results suggest that a serotonergic mechanism may underlie changes in brain functional connectivity in MCI. Hum Brain Mapp 38:3391-3401, 2017. © 2017 Wiley Periodicals, Inc.

An index for measuring overuse of health care resources with Medicare claims.

BACKGROUND: Overuse can be defined as use of a service when the risk of harm exceeds its likely benefit. Yet, there has been little work with composite measures of overuse. OBJECTIVE: Our goal was to create a composite measure of overuse with claims data. DESIGN: Observational study using 5% of Medicare claims from 2008. SETTING: All inpatient and outpatient settings of care, excluding nursing homes. PARTICIPANTS: Older Americans receiving health care services in hospitals or outpatient settings. MEASURES: We applied algorithms to identify specific cases of overuse across 20 previously identified procedures and used multilevel modeling techniques to examine variation in overuse across all procedures. Included in the model were patient-level factors and both procedure and regional fixed effects for the 306 hospital referral regions (HRR). These estimated regional fixed effects, representing the systematic, region variation in overuse across all measures, was then normalized compared with the overall average to generate a Z score for each HRR. The resulting "Overuse Index" was then compared with total costs, 30-day postdischarge mortality, and total mortality at the HRR level, graphically, and associations were tested using Spearman ρ. RESULTS: The Overuse Index varied markedly across regions, but 23 were higher than the average (P<0.05). The Index was positively associated with total costs (ρ=0.28, P<0.0001). It was positively correlated with 30-day postdischarge mortality (ρ=0.18 P≤0.005), and neither positively or negatively correlated with total mortality. CONCLUSIONS: This study confirms previous research hypothesizing that systematic regional variation in overuse exists and is measurable. Addition research is needed to validate index and to test its predictive and concurrent validity in panel data.

Systematic overuse of healthcare services: a conceptual model.

A perfect storm of factors influences the overuse of healthcare services in the USA. Considerable attention has been placed on geographic variation in utilization; however, empiric data has shown that geographic variation in utilization is not associated with overuse. While there has been renewed interest in overuse in recent years, much of the focus has been on the overuse of individual procedures. In this paper we argue that overuse should be thought of as a widespread and pervasive phenomenon that we coin as systematic overuse. While not directly observable (i.e., a latent phenomenon), we suggest that systematic overuse could be identified by tracking a portfolio of overused procedures. Such a portfolio would reflect systematic overuse if it is associated with higher healthcare costs and no health benefit (including worse health outcomes) across a healthcare system. In this report we define and conceptualize systematic overuse and illustrate how it can be identified and validated via a simple empirical example using several Choosing Wisely indicators. The concept of systematic overuse requires further development and empirical verification, and this paper provides an important first step, a conceptual framework, to that end.

Identifying possible indicators of systematic overuse of health care procedures with claims data.

BACKGROUND: Health care quality is frequently described with measures representing the overall performance of a health care system. Despite the growing attention to overuse of health care resources, there is little experience with aggregate measures of overuse. OBJECTIVE: To identify a set of possible indicators of overuse that can be operationalized with claims data and to describe variation in these indicators across the hospital referral regions (HRRs). DESIGN: Using an environmental scan, we identified published descriptions of overused procedures. We assessed each procedure's feasibility for measurement with claims and developed algorithms for occurrences of procedures in patients unlikely to benefit. Using a 5% sample of Medicare claims from 2008, we calculated summary statistics to illustrate variance in the use across HRRs. RESULTS: A total of 613 procedures were identified as overused; 20 had abundant frequency and variance to be possible measures of systematic overuse. These included 13 diagnostic tests, 2 tests for screening, 1 for monitoring, and 4 therapeutic procedures. The usage varied markedly across HRRs. For illustration, 1 HRR used computed tomography for rhinosinusitis diagnosis in 80 of 1000 beneficiaries (mean usage across HRRs was 14/1000). Among 1,451,142 beneficiaries, 14% had at least one overuse event (range, 8.4%-27%). CONCLUSIONS: We identified a set of overused procedures that may be used as measures of overuse and that demonstrate significant variance in their usage. The implication is that an index of overuse might be built from these indicators that would reveal systematic patterns of overuse within regions. Alternatively, these indicators may be valuable in the quality improvement efforts.

The state of overuse measurement: a critical review.

Health care overuse contributes to unnecessary expenditures and patient exposure to harm. Understanding and addressing this problem requires a comprehensive set of valid metrics. This article describes and critiques the current state of overuse measurement through a review of the published and gray literature, measures clearinghouses and ongoing work by major measure developers. Our review identified 37 fully specified measures and 123 measurement development opportunities. Many services were considered overuse due to the extension of diagnostic or screening services to low-risk populations. There were more diagnostic or therapeutic overuse measures than for screening or monitoring/surveillance. Imaging services is a major focus of current measures, but opportunities exist to expand overuse measurement in medication, laboratory services. Future development of overuse measures would benefit from new empirical research and clinical guidelines focused on identifying indications or populations for which there is likely to be no or low benefit.