The provision of diagnosis at emergency department discharge: a pilot study: Table 1

A Scoping Review of Emergency Department Discharge Risk Stratification

INTRODUCTION

Although emergency department (ED) discharge presents patient-safety challenges and opportunities, the ways in which EDs address discharge risk in the general ED population remains disparate and largely uncharacterized. In this study our goal was to conduct a review of how EDs identify and target patients at increased risk at time of discharge.

METHODS

We conducted a literature search to explore how EDs assess patient risk upon discharge, including a review of PubMed and gray literature. After independently screening articles for inclusion, we recorded study characteristics including outcome measures, patient risk factors, and tool descriptions. Based on this review and discussion among collaborators, major themes were identified.

RESULTS

PubMed search yielded 384 potentially eligible articles. After title and abstract review, we screened 235 for potential inclusion. After full text and reference review, supplemented by Google Scholar and gray literature reviews, we included 30 articles for full review. Three major themes were elucidated: 1) Multiple studies include retrospective risk assessment, whereas the use of point-of-care risk assessment tools appears limited; 2) of the point-of-care tools that exist, inputs and outcome measures varied, and few were applicable to the general ED population; and 3) while many studies describe initiatives to improve the discharge process, few describe assessment of post-discharge resource needs.

CONCLUSION

Numerous studies describe factors associated with an increased risk of readmission and adverse events after ED discharge, but few describe point-of-care tools used by physicians for the general ED population. Future work is needed to investigate standardized tools that assess ED discharge risk and patients' needs upon ED discharge.

Identifying Emergency Department Symptom-Based Diagnoses with the Unified Medical Language System

INTRODUCTION

Many patients who are discharged from the emergency department (ED) with a symptom-based discharge diagnosis (SBD) have post-discharge challenges related to lack of a definitive discharge diagnosis and follow-up plan. There is no well-defined method for identifying patients with a SBD without individual chart review. We describe a method for automated identification of SBDs from ICD-10 codes using the Unified Medical Language System (UMLS) Metathesaurus.

METHODS

We mapped discharge diagnosis, with use of ICD-10 codes from a one-month period of ED discharges at an urban, academic ED to UMLS concepts and semantic types. Two physician reviewers independently manually identified all discharge diagnoses consistent with SBDs. We calculated inter-rater reliability for manual review and the sensitivity and specificity for our automated process for identifying SBDs against this "gold standard."

RESULTS

We identified 3642 ED discharges with 1382 unique discharge diagnoses that corresponded to 875 unique ICD-10 codes and 10 UMLS semantic types. Over one third (37.5%, n = 1367) of ED discharges were assigned codes that mapped to the "Sign or Symptom" semantic type. Inter-rater reliability for manual review of SBDs was very good (0.87). Sensitivity and specificity of our automated process for identifying encounters with SBDs were 84.7% and 96.3%, respectively.

CONCLUSION

Use of our automated process to identify ICD-10 codes that classify into the UMLS "Sign or Symptom" semantic type identified the majority of patients with a SBD. While this method needs refinement to increase sensitivity of capture, it has potential to automate an otherwise highly time-consuming process. This novel use of informatics methods can facilitate future research specific to patients with SBDs.

Characteristics and Risk Factors of Out-of-Hospital Cardiac Arrest Within 72 Hours After Discharge

OBJECTIVE

To determine the characteristics and risk factors for patients who developed out-of-hospital cardiac arrest (OHCA) within 72 hours after emergency department (ED) discharge.

METHODS

A nested case-control study (1:4 ratio) was conducted in 5 EDs from January 2002 to December 2011. The study group consisted of adults experiencing nontraumatic OHCA who revisited ED within 72 hours after discharge. Patients matched in sex, age group and chief complaints were selected for the control group. Demographic data, discharge diagnosis, discharge vital signs and laboratory result were collected. Etiologies of cardiac arrest and whether the events were expected or related to the 1st ED visit were reviewed.

RESULTS

In all, 1,657,870 patients were discharged during the study period; 109 developed OHCA within 72 hours of ED discharge (6.6/100,000 per year). The mean age was 64.7 years and 67.9% were men. After comparison with the control group, a higher heart rate (88.5 ± 18.23 versus 81.7 ± 15.93 beat per minutes, P = 0.003) and higher serum creatinine level (2.2 ± 2.30 versus 1.4 ± 1.38 mg/dL, P = 0.002) remain the statistical significant characteristics of study group by conditional logistic regression. Approximately 60% events were expected or unrelated to the 1st ED visit. Among patients whose OHCA were unexpected and related to the 1st ED visit, 71.4% had a cardiac cause. Of these, 20% had chest pain, but 40% had angina-equivalent symptoms during 1st presentation.

CONCLUSIONS

A higher discharge heart rate and higher creatinine level are risk factors in these patients.

Do emergency department patients receive a pathological diagnosis? A nationally-representative sample

INTRODUCTION

Understanding the cause of patients' symptoms often requires identifying a pathological diagnosis. A single-center study found that many patients discharged from the emergency department (ED) do not receive a pathological diagnosis. We analyzed 17 years of data from the National Hospital Ambulatory Medical Care Survey (NHAMCS) to identify the proportion of patients who received a pathological diagnosis at ED discharge. We hypothesized that many patients do not receive a pathological diagnosis, and that the proportion of pathological diagnoses increased between 1993 and 2009.

METHODS

Using the NHAMCS data from 1993-2009, we analyzed visits of patients age ≥18 years, discharged from the ED, who had presented with the three most common chief complaints: chest pain, abdominal pain, and headache. Discharge diagnoses were coded as symptomatic versus pathological based on a pre-defined coding system. We compared weighted annual proportions of pathological discharge diagnoses with 95% CIs and used logistic regression to test for trend.

RESULTS

Among 299,919 sampled visits, 44,742 met inclusion criteria, allowing us to estimate that there were 164 million adult ED visits presenting with the three chief complaints and then discharged home. Among these visits, the proportions with pathological discharge diagnosis were 55%, 71%, and 70% for chest pain, abdominal pain, and headache, respectively. The total proportion of those with a pathological discharge diagnosis decreased between 1993 and 2009, from 72% (95% CI, 69-75%) to 63% (95% CI, 59-66%). In the multivariable logistic regression model, those more likely to receive pathological diagnoses were females, African-American as compared to Caucasian, and self-pay patients. Those more likely to receive a symptomatic diagnosis were patients aged 30-79 years, with visits to EDs in the South or West regions, and seen by a physician in the ED.

CONCLUSION

In this analysis of a nationally-representative database of ED visits, many patients were discharged from the ED without a pathological diagnosis that explained the likely cause of their symptoms. Despite advances in diagnostic testing, the proportion of pathological discharge diagnoses decreased. Future studies should investigate reasons for not providing a pathological diagnosis and how this may affect clinical outcomes.