Carlton Moore

Medical errors related to discontinuity of care from an inpatient to an outpatient setting.

AbstractOBJECTIVE: To determine the prevalence of medical errors related to the discontinuity of care from an inpatient to an outpatient setting, and to determine if there is an association between these medical errors and adverse outcomes. PATIENTS: Eighty-six patients who had been hospitalized on the medicine service at a large academic medical center and who were subsequently seen by their primary care physicians at the affiliated outpatient practice within 2 months after discharge. DESIGN: Each patient’s inpatient and outpatient medical record was reviewed for the presence of 3 types of errors related to the discontinuity of care from the inpatient to the outpatient setting: medication continuity errors, test follow-up errors, and work-up errors. MEASUREMENTS: Rehospitalizations within 3 months after the initial postdischarge outpatient primary care visit. MAIN RESULTS: Forty-nine percent of patients experienced at least 1 medical error. Patients with a work-up error were 6.2 times (95% confidence interval [95% CI], 1.3 to 30.3) more likely to be rehospitalized within 3 months after the first outpatient visit. We did not find a statistically significant association between medication continuity errors (odds ratio [OR], 2.5; 95%CI, 0.7 to 8.8) and test follow-up errors (OR, 2.4; 95%CI, 0.3 to 17.1) with rehospitalizations. CONCLUSION: We conclude that the prevalence of medical errors related to the discontinuity of care from the inpatient to the outpatient setting is high and may be associated with an increased risk of rehospitalization.

Physician attitudes toward opioid prescribing for patients with persistent noncancer pain.

ObjectivesPhysicians frequently express dissatisfaction about caring for patients with chronic pain and frequently report that inadequate training and concern about addiction are impediments to prescribing opioids. Elderly patients with chronic pain may be at increased risk of experiencing uncontrolled pain and this patient population is increasingly being cared for by geriatricians rather than internists. We sought to determine if there is a differential impact on internists and geriatricians of the factors that adversely affect attitudes toward opioid prescribing. MethodsAnonymous survey of geriatric and internal medicine physicians at a large urban academic medical center about their beliefs and behaviors regarding opioid prescribing. ResultsOne hundred thirty-two of 187 physicians completed the survey for an overall response rate of 71%. Controlling for level of training, internists were more likely to be concerned about illegal diversion (adjusted odds ratio=10.0, P=0.004), were more concerned about causing addiction (38% vs. 0%, P<0.001), and were more likely to be concerned about their inability to prescribe the correct opioid dose (adjusted odds ratio=11.1, P=0.020). DiscussionFactors shown to have an adverse affect on opioid prescribing disproportionately impact on the attitudes of internists compared with geriatricians. Further research is needed to determine if there is also a differential impact on how internists care for their elderly patients with chronic pain.

Perioperative Management of Patients on Oral Anticoagulants: A Decision Analysis

Background . To better inform clinicians on the optimal management of patients on oral anticoagulation who need to undergo surgery or invasive procedures, the authors performed a decision analysis examining whether a perioperative aggressive or minimalist strategy results in greater quality-adjusted survival. Methods . A decision analysis model was created comparing withholding warfarin (minimalist strategy) to withholding warfarin and administering treatment-dose subcutaneous low-molecular-weight heparin (LMWH) or intravenous heparin perioperatively (aggressive strategy). The base-case analysis examined a hypothetical 60-year-old hypertensive individual with mechanical aortic valve replacement undergoing major abdominal surgery. A probabilistic sensitivity analysis was performed using a Monte Carlo simulation with quality-adjusted life expectancy (QALE) as the outcome. Secondary analyses examined patients with a mechanical mitral valve and atrial fibrillation. Sensitivity analyses were performed for each variable. Results . Under the base-case scenario, the minimalist strategy was preferred for 78% of trials in the Monte Carlo simulation, with a mean benefit of 0.003 years (95% confidence interval, -0.005 years to 0.011 years). Sensitivity analyses based on point estimates indicate that the aggressive strategy is preferred when the annual stroke rate is >5.6% or the increase in postoperative major bleeding induced by heparin is <2.0%; however, the benefit is small over the range of plausible values. Conclusions . For most patients with a mechanical aortic valve or atrial fibrillation undergoing major surgery, a minimalist strategy of simply withholding oral anticoagulation provides similar QALE as an aggressive strategy of administering perioperative subcutaneous LMWH or intravenous heparin. The aggressive therapy provides greater QALE for patients at higher risk of stroke (e.g., mechanical mitral valves), although the benefit is small.

Predictors of 30-Day Hospital Readmission among Maintenance Hemodialysis Patients: A Hospital’s Perspective

BACKGROUND AND OBJECTIVES Over 35% of patients on maintenance dialysis are readmitted to the hospital within 30 days of hospital discharge. Outpatient dialysis facilities often assume responsibility for readmission prevention. Hospital care and discharge practices may increase readmission risk. We undertook this study to elucidate risk factors identifiable from hospital-derived data for 30-day readmission among patients on hemodialysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Data were taken from patients on maintenance hemodialysis discharged from University of North Carolina Hospitals between May of 2008 and June of 2013 who received in-patient hemodialysis during their index hospitalizations. Multivariable logistic regression models with 30-day readmission as the dependent outcome were used to identify readmission risk factors. Models considered variables available at hospital admission and discharge separately. RESULTS Among 349 patients, 112 (32.1%) had a 30-day hospital readmission. The discharge (versus admission) model was more predictive of 30-day readmission. In the discharge model, malignancy comorbid condition (odds ratio [OR], 2.08; 95% confidence interval [95% CI], 1.04 to 3.11), three or more hospitalizations in the prior year (OR, 1.97; 95% CI, 1.06 to 3.64), ≥10 outpatient medications at hospital admission (OR, 1.69; 95% CI, 1.00 to 2.88), catheter vascular access (OR, 1.82; 95% CI, 1.01 to 3.65), outpatient dialysis at a nonuniversity-affiliated dialysis facility (OR, 3.59; 95% CI, 2.03 to 6.36), intradialytic hypotension (OR, 3.10; 95% CI, 1.45 to 6.61), weekend discharge day (OR, 1.82; 95% CI, 1.01 to 3.31), and serum albumin <3.3 g/dl (OR, 4.28; 95% CI, 2.37 to 7.73) were associated with higher readmission odds. A decrease in prescribed medications from admission to discharge (OR, 0.20; 95% CI, 0.08 to 0.51) was associated with lower readmission odds. Findings were robust across different model-building approaches. CONCLUSIONS Models containing discharge day data had greater predictive capacity of 30-day readmission than admission models. Identified modifiable readmission risk factors suggest that improved medication education and improved transitions from hospital to community may potentially reduce readmissions. Studies evaluating targeted transition programs among patients on dialysis are needed.

Follow-up of outpatient test results: a survey of house-staff practices and perceptions.

Failure to follow up outpatient test results is a potential patient safety concern; however, data about how house-staff physicians follow up on tests are sparse. The authors sought to assess internal medicine house-staff practices and perceptions regarding the follow-up of outpatient tests and identified barriers to timely follow-up. Seventy-five of 111 eligible house staff at a large urban teaching hospital (68%) completed the survey. Seventy-four percent reported they were sometimes unable to follow up on test results, 78% were at least somewhat worried about inadequate follow-up, and 46% stated that they have seen a patient’s medical condition worsen due to a delay in test result follow-up at least a few times a year. Barriers to timely follow-up included lack of a reminder system (40%), difficulty accessing results (24%), too many competing demands on time (27%), and uncertainty about who should follow up on results (16%).

Predictive value of alert triggers for identification of developing adverse drug events

Objective: Adverse drug events (ADEs) are the most common type of iatrogenic injury in hospitalized patients. However; the ability of electronic triggers to identify patients at high risk for inpatient ADEs before they occur has not been well studied. The objective of this study was to assess the positive predictive value of event triggers to detect developing ADEs. Methods: We conducted a prospective observational study in patients at a university-based teaching hospital during a 5-month period. Patients were monitored using electronic triggers designed to detect patients at increased risk for 4 types of ADEs: hypoglycemia, hypokalemia, hyperkalemia, and thrombocytopenia. Each patient for whom a trigger fired was followed to determine whether a drug-induced markedly abnormal laboratory result occurred between 1 and 72 hours after the initial trigger firing. Results: Overall, the triggers fired 611 times on 456 patients. Of the 456 patients, 101 experienced 1 or more related ADEs between 1 and 72 hours after the initial trigger firing. The positive predictive value of the triggers and median time from trigger firing to ADE was 31% and 11.6 hours for hypoglycemia, 4.0% and 17 hours for hypokalemia, 31% and 25.4 hours for hyperkalemia, and 21% and 48.4 hours for thrombocytopenia. Conclusion: Computerized triggers have sufficient predictive value to detect developing ADEs and can help clinicians avert ADEs. More research is required to determine whether real-time, primary-prevention alerts may reduce the incidence of ADEs.

Follow-up of Markedly Elevated Serum Potassium Results in the Ambulatory Setting: Implications for Patient Safety

Failure to follow up outpatient test results in a timely manner is a growing patient safety concern. To investigate the follow-up of markedly elevated serum potassium levels in the ambulatory setting, the authors reviewed the medical records of all patients seen in a large primary care practice between September 1, 2003, and August 31, 2004, with potassium levels≥5.8mEq/L. Of the 12914 serum potassium tests performed, there were 109 cases of markedly elevated serum potassium levels in 86 patients. The median potassium level was 5.9mEq/L (range, 5.8-7.3). More than half the patients were recalled to the clinic specifically for repeat testing; however, 25% of patients had no repeat tests until they were seen at routine follow-up visits. The median time to a repeat potassium level was 6 days (range, 0-445). Patients≥65 years old had a lower likelihood of having repeat testingwithin 1 week (odds ratio = 0.38,P= .03).

Impact of an electronic health record on follow-up time for markedly elevated serum potassium results.

Follow-up of abnormal ambulatory laboratory results is often suboptimal. The impact of an ambulatory electronic health record (EHR) on follow-up of markedly elevated blood potassium (K +) results was investigated via a retrospective medical record review—before and after EHR implementation—of patients at an adult primary care practice who had a nonhemolyzed K+ ≥ 6.0 mEq/L. In all, 188 patients in the pre-EHR group and 30 in the EHR group satisfied inclusion criteria. The mean K+ for the 2 groups was 6.3 mEq/L. The EHR group had 4.5 times the odds (95% confidence interval = 1.3-15.8) of having their episodes of hyperkalemia followed up within 4 days. Patients in the EHR group were also more likely to have their blood K+ rechecked within 4 days (63.3% vs 43.6%; P = .044). An ambulatory EHR with a results management system improves documentation and time to follow-up for patients with markedly abnormal lab results.

Factors Associated with Time to Follow-up of Severe Hyperkalemia in the Ambulatory Setting:

Background. Few studies have investigated the time it takes physicians to follow up abnormal outpatient laboratory results. Methods. Medical record review of all adult patients seen at a primary care practice between January 2002 and December 2005 with serum potassium results ≥ 6.0 mEq/L. We used a proportional hazards model to assess factors associated with time to follow-up for episodes of hyperkalemia. Results. 259 of 48 333 serum potassium results met inclusion criteria. The median follow-up time was 3 days; after 30 days, 10% of cases had no follow-up. Residing in the same zip code as the clinic (HR = 1.39; P = .029), degree of hyperkalemia (HR = 2.97; P < .001), and renal insufficiency (HR = 1.41; P = .015) were associated with decreased time to repeat testing. Conversely, African Americans (HR = .51; P = .007) had increased time to repeat testing. Conclusions. Follow-up of abnormal laboratory results in outpatients is suboptimal and research is needed to better understand factors that delay follow-up. (Am J Med Qual 2007;22:428-437)

Using natural language processing to extract abnormal results from cancer screening reports

Objectives Numerous studies show that follow-up of abnormal cancer screening results, such as mammography and Papanicolaou (Pap) smears, is frequently not performed in a timely manner. A contributing factor is that abnormal results may go unrecognized because they are buried in free-text documents in electronic medical records (EMRs), and, as a result, patients are lost to follow-up. By identifying abnormal results from free-text reports in EMRs and generating alerts to clinicians, natural language processing (NLP) technology has the potential for improving patient care. The goal of the current study was to evaluate the performance of NLP software for extracting abnormal results from free-text mammography and Pap smear reports stored in an EMR. Methods A sample of 421 and 500 free-text mammography and Pap reports, respectively, were manually reviewed by a physician, and the results were categorized for each report. We tested the performance of NLP to extract results from the reports. The 2 assessments (criterion standard versus NLP) were compared to determine the precision, recall, and accuracy of NLP. Results When NLP was compared with manual review for mammography reports, the results were as follows: precision, 98% (96%–99%); recall, 100% (98%–100%); and accuracy, 98% (96%–99%). For Pap smear reports, the precision, recall, and accuracy of NLP were all 100%. Conclusions Our study developed NLP models that accurately extract abnormal results from mammography and Pap smear reports. Plans include using NLP technology to generate real-time alerts and reminders for providers to facilitate timely follow-up of abnormal results.