Terry L. Wahls

Barriers to obesity management: a pilot study of primary care clinicians

BackgroundObesity is an increasing epidemic in both the US and veteran populations, yet it remains largely understudied in the Veterans Health Administration (VHA) setting. The purpose of our study was to identify barriers to the effective management of obesity in VHA primary care settings.MethodsThree focus groups of clinicians from a Veterans Affairs Medical Center (VAMC) and an affiliated Community Based Outpatient Center (CBOC) were conducted to identify potential barriers to obesity management. The focus groups and previously published studies then informed the creation of a 47-item survey that was then disseminated and completed by 55 primary care clinicians.ResultsThe focus groups identified provider, system, and patient barriers to obesity care. Lack of obesity training during medical school and residency was associated with lower rates of discussing diet and exercise with obese patients (p < 0.05). Clinicians who watched their own diets vigorously were more likely to calculate BMI for obese patients than other clinicians (42% vs. 13%, p < 0.05). Many barriers identified in previous studies (e.g., attitudes toward obese patients, lack of insurance payments for obesity care) were not prevalent barriers in the current study.ConclusionMany VHA clinicians do not routinely provide weight management services for obese patients. The most prevalent barriers to obesity care were poor education during medical school and residency and the lack of information provided by the VHA to both clinicians and patients about available weight management services.

Characteristics and Predictors of Missed Opportunities in Lung Cancer Diagnosis: An Electronic Health Record–Based Study

PURPOSE Understanding delays in cancer diagnosis requires detailed information about timely recognition and follow-up of signs and symptoms. This information has been difficult to ascertain from paper-based records. We used an integrated electronic health record (EHR) to identify characteristics and predictors of missed opportunities for earlier diagnosis of lung cancer. METHODS Using a retrospective cohort design, we evaluated 587 patients of primary lung cancer at two tertiary care facilities. Two physicians independently reviewed each case, and disagreements were resolved by consensus. Type I missed opportunities were defined as failure to recognize predefined clinical clues (ie, no documented follow-up) within 7 days. Type II missed opportunities were defined as failure to complete a requested follow-up action within 30 days. RESULTS Reviewers identified missed opportunities in 222 (37.8%) of 587 patients. Median time to diagnosis in cases with and without missed opportunities was 132 days and 19 days, respectively (P < .001). Abnormal chest x-ray was the clue most frequently associated with type I missed opportunities (62%). Follow-up on abnormal chest x-ray (odds ratio [OR], 2.07; 95% CI, 1.04 to 4.13) and completion of first needle biopsy (OR, 3.02; 95% CI, 1.76 to 5.18) were associated with type II missed opportunities. Patient adherence contributed to 44% of patients with missed opportunities. CONCLUSION Preventable delays in lung cancer diagnosis arose mostly from failure to recognize documented abnormal imaging results and failure to complete key diagnostic procedures in a timely manner. Potential solutions include EHR-based strategies to improve recognition of abnormal imaging and track patients with suspected cancers.

Failure to Recognize Newly Identified Aortic Dilations in a Health Care System With an Advanced Electronic Medical Record

Context Studies estimate that clinicians may not recognize 3% to 30% of abnormal test results in a timely manner, leading to potential malpractice suits, treatment delays, and patient harm. Contribution This study examined the electronic health records of 91 patients with newly detected aortic dilations on computed tomography and found documentation in the record that the clinical service was aware of the finding for only 42% within 3 months and 66% within 4 years of the scan. No evidence existed of patient harm associated with failure to document these findings. Implication Strategies are needed to ensure that clinicians have recognized and documented abnormal test results. The Editors Evidence is growing that missed test results constitute an important threat to patient safety (1). Studies from both the inpatient and ambulatory care settings suggest that 3% to 30% of abnormal test results may not be recognized by providers in a timely manner (25). Missed test results are more than just an academic curiosity; they are a common cause of medical malpractice suits and, more important, can result in treatment delays, which can harm patients (6, 7). Despite evidence that missed test results are ubiquitous, less is known about this threat to patient safety than about many other types of medical errors. For example, in a landmark Institute of Medicine report (8), discussion of missed test results is largely absent, whereas medication errors are mentioned repeatedly (9). Attention to missed test results may be lacking because empirical data on the epidemiology and consequences of missed test results are limited and focus on chronic conditions that are not perceived to require urgent attention from busy clinicians (2, 10, 11). We sought to examine how often newly identified abdominal aortic aneurysms were accompanied by evidence of clinician recognition of the abnormality in the electronic medical record (EMR). More specifically, we examined the conditions under which abdominal aortic aneurysms were identified on computed tomography (CT), the manner in which the aneurysms were described by radiologists, and the timeliness of evidence of aneurysm recognition in the EMR by the clinical teams. Methods The institutional review boards of the Iowa City and Omaha Veterans Affairs Medical Centers approved this project. Data Collection We obtained radiology reports from consecutive patients who underwent CT of the abdomen and pelvis during 2003 in any of 2 midwestern Veterans Affairs medical centers. The reports contained 3 sections: the indications for the study (for example, abdominal pain), a detailed reading of the scan, and the radiologists summary of important findings. As of 2003, all CT reports and clinical notes were stored in the Veterans Affairs EMRComputerized Patient Information System. Although each of the medical centers generally followed established radiology guidelines for CT reporting, including when the radiologist should contact clinical teams directly regarding unanticipated study findings, neither medical center had firm protocols in place for what did or did not constitute an unanticipated finding, as is commonplace in clinical practice today. We used the CT data to search for patients who had abdominal aortic abnormalities in the infrarenal or suprarenal regions. We identified these aortic dilations by looking for 3 general phrases that would broadly encompass the language that radiologists use when describing the aorta with the assistance of a practicing radiologist member of the investigative team; these terms were aort, aneurysm, and AAA. Two of the investigators then performed keyword searches of the CT reports by using these terms. We intentionally did not limit our search to more specific phrases, such as aortic aneurysm, because a variety of radiologic criteria are used to define aortic aneurysms; therefore, radiologists may differ greatly in deciding which aortic abnormalities qualify as aneurysms as opposed to more general terms, such as ectasias or dilations (12). Likewise, we intentionally did not apply rigid size criteria (for example, 2.8 cm or 3.0 cm) to aortic abnormalities, because radiologists commonly use discretion when applying size thresholds to individual patients and before deciding which aortic abnormalities are clinically concerning (13). We reviewed the radiology report for each patient with a dilation and entered the following information into a Microsoft Access (Microsoft, Redmond, Washington) database: the patients last name and last 4 numbers of the Social Security Number, date of and indication for the CT (classified as asymptomatic screening, symptoms or clinical concern, follow-up of known AAA, or incidental [any dilation discovered on CT not ordered specifically for signs or symptoms, screening, or follow-up of a known AAA]), maximum abdominal aorta size, the descriptive terms the radiologist used to describe the dilation (categorized as ectasia, aneurysm, aneurysmal, AAA, or other), and location in the report where the aortic dilation was mentioned (detailed reading or summary). We also collected information from the radiology report on whether the radiology team contacted the clinical team about the aortic abnormality that was identified. After reviewing the CT reports, at least 1 study investigator reviewed the complete EMR of each patient with a new aortic dilation to search for documentation suggesting recognition of the aortic abnormality and to examine subsequent patient management. We reviewed all data sources in what is widely considered to be one of the most advanced and complete EMRs in the United States. In particular, for each patient, we reviewed all inpatient and outpatient clinical notes, all nursing notes, imaging and operative reports, and summary lists of each patients medical problems. To improve the accuracy of our review, we also performed a keyword search of all clinical encounters maintained in the EMR by using the same terms that were used in the review of the CT reports. The medical record review commenced with verification that the aortic dilation detected by CT was not identified previouslywe excluded patients with previously identified dilation. The EMR of all patients determined to have new abnormalities underwent full medical record review to collect an array of information, including patient demographic characteristics (age, race, and sex), aneurysm risk factors (tobacco use, hypertension, and family history of aneurysms), and significant active comorbid conditions (for example, end-stage heart failure, dementia, metastatic cancer, or renal failure) that might make a patients aortic dilation irrelevant in the opinion of their health care providers; such patients were excluded from further analysis. We also collected data on the frequency of each patients contact with the Veterans Affairs health care system for 1 year after the initial CT. In particular, we recorded whether each patient had any follow-up contact with the provider who ordered the initial CT and the total number of clinic visits and telephone contacts that each patient had during follow-up. For all eligible patients, we collected information from the EMR about how much time elapsed between the initial CT until evidence appeared that a clinician recognized the aortic dilation. We considered a dilation recognized if the abnormality was explicitly mentioned anywhere in the EMR or if there was evidence of a relevant consultation (for example, vascular surgery) or follow-up imaging (for example, abdominal ultrasonography or magnetic resonance imaging). We considered a dilation missed only if the EMR showed no documentation of recognition or evidence of monitoring or treatment of the dilation. We also collected information about the clinical setting in which the initial CT was ordered (outpatient or clinic visit, inpatient, or emergency department visit) and the type of provider who ordered the CT, including their educational training (physician, nurse, or nurse practitioner), specialty (primary care, surgery, or other), and whether the ordering provider was a resident or staff physician. Statistical Analysis We used univariate methods (mean, median, and SD) to describe the demographic characteristics, aneurysm risk factors, and amount of contact with the Veterans Affairs health care system that patients with new aortic abnormalities had. We used bivariate methods (t test, Fisher exact test, or analysis of variance) to examine whether the radiology reports differed between patients with smaller abnormalities (<5.5 cm) and patients with larger abnormalities that would typically warrant consideration of surgical repair (5.5 cm). On the basis of discussion among the investigative team, which included internists, a radiologist, and a vascular surgeon, we made an a priori decision to define timely recognition of a new aortic dilation as an abnormality for which we could find evidence in the EMR of recognition by the clinical team within 3 months of the index CT. We used bivariate methods to explore the relationship between timely recognition and important clinical factors available in our data set (for example, aorta size, clinical setting in which the initial CT was ordered, ordering provider, and whether patients had follow-up contact with the provider who ordered the CT). We performed sensitivity analysis by using alternative definitions of timely follow-up (for example, recognition of the aneurysm within 6 months) to examine the robustness of our findings. We also performed a time-to-event analysis in which the outcome of interest was recognition of the aortic abnormality and in which patient deaths were accounted for through censoring. To ensure the validity of our results, we performed 15% of abstractions in duplicate, including all aortic abnormalities for which the first reviewer found no evidence of clinician recognition in the EMR. All reviewers agreed (= 1.0) on the p

The Continuing Problem of Missed Test Results in an Integrated Health System with an Advanced Electronic Medical Record

BACKGROUND Missed results can cause needless treatment delays. However, there is little data about the magnitude of this problem and the systems that clinics use to manage test results. METHODS Surveys about potential problems related to test results management were developed and administered to clinical staff in a regional Veterans Administration (VA) health care network. The provider survey, conducted four times between May 2005 and October 2006, sampling VA staff physicians, physician assistants, nurse practitioners, and internal medicine trainees, asked questions about the frequency of missed results and diagnosis or treatment delays seen in the antecedent two weeks in their clinics, or if a trainee, the antecedent month. RESULTS Clinical staff survey response rate was 39% (143 of 370), with 40% using standard operating procedures to manage test results. Forty-four percent routinely reported all results to patients. The provider survey response rate was 50% (441 of 884) overall, with responses often (37% overall; range 29% to 46%) indicating they had seen patients with diagnosis or treatment delays attributed to a missed result; 15% reported two or more such encounters. DISCUSSION Even in an integrated health system with an advanced electronic medical record, missed test results and associated diagnosis or treatment delays are common. Additional study and measures of missed results and associated treatment delays are needed.

Predicting resource utilization in a Veterans Health Administration primary care population: comparison of methods based on diagnoses and medications.

BackgroundValid methods of predicting resource utilization in primary care populations are needed. We compared the predictive validity of a method based on diagnoses from administrative data (Adjusted Clinical Groups [ACGs]) and a method using medication profiles (Chronic Disease Index [CDI]). MethodsThis retrospective cohort study included 31,212 primary care patients in a Veterans Health Administration (VA) network who received outpatient medication prescriptions in 1999 and who had VA utilization in 1999 and 2000. ACG and CDI classifications were determined using 1999 data. Analyses compared the predictive validity with respect to outpatient clinic visits and days of hospital care. ResultsBoth ACGs and CDI explained a higher proportion of the variance in outpatient visits than demographic data alone. However, explained variance was higher for ACGs. For example, ACGs explained 30.2% of the variance in total visits in 1999, compared with 8.8% for the CDI. Results were similar for 2000, although the explained variance declined for both methods (eg, 16.3% and 5.7%, respectively, for total visits). Results were similar in analyses examining the discrimination of the 2 methods to predict hospital use; for example, c statistics for ACGs and CDI scores were 0.86 versus 0.70, respectively (P <0.05), for 1999 and 0.72 and 0.65, respectively (P <0.05), for 2000. ConclusionAmong VA patients, ACGs had superior predictive validity than the CDI, a newer nonproprietary method based on pharmacy data. The findings suggest that diagnosis-based measures could be preferable for ambulatory case-mix adjustment and are valid across a wide range of populations.

A Multimodal Intervention for Patients with Secondary Progressive Multiple Sclerosis: Feasibility and Effect on Fatigue

BACKGROUND Multiple sclerosis is an autoimmune disease influenced by environmental factors. OBJECTIVES The feasibility of a multimodal intervention and its effect on perceived fatigue in patients with secondary progressive multiple sclerosis were assessed. DESIGN/SETTING This was a single-arm, open-label intervention study in an outpatient setting. INTERVENTIONS A multimodal intervention including a modified paleolithic diet with supplements, stretching, strengthening exercises with electrical stimulation of trunk and lower limb muscles, meditation, and massage was used. OUTCOME MEASURES Adherence to each component of the intervention was calculated using daily logs. Side-effects were assessed from a monthly questionnaire and blood analyses. Fatigue was assessed using the Fatigue Severity Scale (FSS). Data were collected at baseline and months 1, 2, 3, 6, 9, and 12. RESULTS Ten (10) of 13 subjects who were enrolled in a 2-week run-in phase were eligible to continue in the 12-month main study. Of those 10 subjects, 8 completed the study and 6 subjects fully adhered to the study intervention for 12 months. Over a 12-month period, average adherence to diet exceeded 90% of days, and to exercise/muscle stimulation exceeded 75% of days. Nutritional supplements intake varied among and within subjects. Group daily average duration of meditation was 13.3 minutes and of massage was 7.2 minutes. No adverse side-effects were reported. Group average FSS scores decreased from 5.7 at baseline to 3.32 (p=0.0008) at 12 months. CONCLUSIONS In this small, uncontrolled pilot study, there was a significant improvement in fatigue in those who completed the study. Given the small sample size and completer rate, further evaluation of this multimodal therapy is warranted.

Coexistent Wegener's granulomatosis and anti-glomerular basement membrane disease

Wegeners granulomatosis and Goodpastures syndrome represent two major causes of a pulmonary-renal syndrome. We describe the clinical course and morphologic features of a patient in whom pulmonary manifestations of Wegeners granulomatosis developed and were followed six months later by anti-glomerular basement membrane disease. Although we regard this as a unique and probably fortuitous association, a genetic predisposition or a secondary form of anti-GBM disease cannot be excluded.

Patient- and system-related barriers for the earlier diagnosis of colorectal cancer

BackgroundA cohort of colorectal cancer (CRC) patients represents an opportunity to study missed opportunities for earlier diagnosis. Primary objective: To study the epidemiology of diagnostic delays and failures to offer/complete CRC screening. Secondary objective: To identify system- and patient-related factors that may contribute to diagnostic delays or failures to offer/complete CRC screening.MethodsSetting: Rural Veterans Administration (VA) Healthcare system. Participants: CRC cases diagnosed within the VA between 1/1/2000 and 3/1/2007. Data sources: progress notes, orders, and pathology, laboratory, and imaging results obtained between 1/1/1995 and 12/31/2007. Completed CRC screening was defined as a fecal occult blood test or flexible sigmoidoscopy (both within five years), or colonoscopy (within 10 years); delayed diagnosis was defined as a gap of more than six months between an abnormal test result and evidence of clinician response. A summary abstract of the antecedent clinical care for each patient was created by a certified gastroenterologist (GI), who jointly reviewed and coded the abstracts with a general internist (TW).ResultsThe study population consisted of 150 CRC cases that met the inclusion criteria. The mean age was 69.04 (range 35-91); 99 (66%) were diagnosed due to symptoms; 61 cases (46%) had delays associated with system factors; of them, 57 (38% of the total) had delayed responses to abnormal findings. Fifteen of the cases (10%) had prompt symptom evaluations but received no CRC screening; no patient factors were identified as potentially contributing to the failure to screen/offer to screen. In total, 97 (65%) of the cases had missed opportunities for early diagnosis and 57 (38%) had patient factors that likely contributed to the diagnostic delay or apparent failure to screen/offer to screen.ConclusionMissed opportunities for earlier CRC diagnosis were frequent. Additional studies of clinical data management, focusing on following up abnormal findings, and offering/completing CRC screening, are needed.

Prevalence of Delayed Clinician Response to Elevated Prostate-Specific Antigen Values

OBJECTIVE To assess the frequency of delayed response to an abnormal prostate-specific antigen (PSA) value. PATIENTS AND METHODS Retrospective review of prostate cancer cases diagnosed between January 1, 2000, and December 31, 2005, in a rural Department of Veterans Affairs health care system serving 44,000 veterans across 2 states. Clinician response was defined as a reference to the elevated PSA result in clinical notes, orders for further evaluation, treatment of presumed prostatitis, or a urology visit or referral. Delay was measured as days between an abnormal PSA result and clinician response. RESULTS We identified 327 men who met inclusion criteria with an abnormal PSA value before prostate cancer diagnosis. At first PSA elevation, median age was 64 years; 94% were younger than 75 years. Of the 327 men, 253 (77.4%) had a timely (< or =30 days) response to an abnormal PSA value; 23 (7.0%) had between 31 and 180 days; 24 (7.3%), between 181 and 360 days; and 27 (8.3%), more than 360 days between an abnormal PSA measurement and clinician response. The delayed group had nearly an additional years (309 days) lapse before completed urologic consultation and prostate gland biopsy (313 days) as compared with the timely group. The presence of urologic symptoms, abnormal results from rectal examination, higher PSA values, and higher PSA velocity (P<.05) were associated with timely clinician response to an abnormal PSA measurement. CONCLUSION In a cohort of men with prostate cancer and an antecedent abnormal PSA value, 15.6% had more than 180 days between an abnormal PSA measurement and clinician response. These findings add to the growing literature demonstrating that missed results occur more frequently than is generally appreciated. Improved systems for clinical data management are needed.

Diagnostic errors and abnormal diagnostic tests lost to follow-up: a source of needless waste and delay to treatment.

Diagnostic errors are an important and often underappreciated source of medical error, needless delays to treatment, and needlessly wasted resources. Almost 65% of diagnostic errors have an important contribution of system errors, of which many are an abnormal test result that was lost to follow-up, that is, missed results. These system problems that contribute to missed results may represent low-hanging fruit for those who wish to reduce diagnostic errors in their institution. The rate of missed results and associated treatment delay are discussed. The system factors and human factors that contribute to these errors are discussed along with strategies that can be adopted to reduce these errors.