Investigating the Impact of Community Volunteerism on the Mental Health of Medical Students.

OBJECTIVE: This study aimed to analyze the impact of community service on the mental health of medical students through their perception of stress. METHODS: The 10-item Perceived Stress Scale was used to measure the stress levels of 82 medical students over a 3-month period. Additional survey questions gauged students' weekly volunteer experiences in clinical and nonclinical settings and their perceived effects on stress and quality of life. RESULTS: Results found an inverse relationship between the number of clinical volunteer hours and perceived stress (P = .0497). Nonclinical and total volunteer hours were correlated with both reduced perceived stress levels (nonclinical P = .0095, total P = .0052) and better quality of life (nonclinical P = .0301, total P = .0136). All individual perceived stress scores fell into the low or moderate stress ranges of the Perceived Stress Scale per the week-to-week analysis. CONCLUSION: The preliminary results raised important research questions about the impact of volunteering on medical student perceived stress. As medical students face higher levels of stress in comparison to the general population, it is exceedingly important to determine methods to decrease their risk of compromising their mental health. This study may aid in decision-making and research in favor of or against offering community service opportunities as part of the core medical education curriculum.

Estimating the obstetric co-morbidity burden using administrative data: The impact of the pregnancy-related assessment window.

BACKGROUND: Despite increased research using large administrative databases to identify determinants of maternal morbidity and mortality, the extent to which these databases capture obstetric co-morbidities is unknown. OBJECTIVE: To evaluate the impact that the time window used to assess obstetric co-morbidities has on the completeness of ascertainment of those co-morbidities. METHODS: We conducted a five-year analysis of inpatient hospitalisations of pregnant women from 2010-2014 using the Nationwide Readmissions Database. For each woman, using discharge diagnoses, we identified 24 conditions used to create the Obstetric Comorbidity Index. Using various assessment windows for capturing obstetric co-morbidities, including the delivery hospitalisation only and all weekly windows from 7 to 280 days, we calculated the frequency and rate of each co-morbidity and the degree of underascertainment of the co-morbidity. Under each scenario, and for each co-morbidity, we also calculated the all-cause, 30-day readmission rate. RESULTS: There were over 3 million delivery hospitalisations from 2010 to 2014 included in this analysis. Compared with a full 280-day window, assessment of obstetric co-morbidities using only diagnoses made during the delivery hospitalisation would result in failing to identify over 35% of cases of chronic renal disease, 28.5% cases in which alcohol abuse was documented during pregnancy, and 23.1% of women with pulmonary hypertension. For seven other co-morbidities, at least 1 in 20 women with that condition would have been missed with exclusive reliance on the delivery hospitalisation for co-morbidity diagnoses. Not only would reliance on delivery hospitalisations have resulted in missed cases of co-morbidities, but for many conditions, estimates of readmission rates for women with obstetric co-morbidities would have been underestimated. CONCLUSIONS: An increasing proportion of maternal and child health research is based on large administrative databases. This study provides data that facilitate the assessment of the degree to which important obstetric co-morbidities may be underascertained when using these databases.

A Novel Approach to Characterizing Readmission Patterns Following Hospitalization for Ambulatory Care-Sensitive Conditions.

BACKGROUND: Little is known about the frequency, patterns, and determinants of readmissions among patients initially hospitalized for an ambulatory care-sensitive condition (ACSC). The degree to which hospitalizations in close temporal proximity cluster has also not been studied. Readmission patterns involving clustering likely reflect different underlying determinants than the same number of readmissions more evenly spaced. OBJECTIVE: To characterize readmission rates, patterns, and predictors among patients initially hospitalized with an ACSC. DESIGN: Retrospective analysis of the 2010-2014 Nationwide Readmissions Database. PARTICIPANTS: Non-pregnant patients aged 18-64 years old during initial ACSC hospitalization and who were discharged alive (N = 5,007,820). MAIN MEASURES: Frequency and pattern of 30-day all-cause readmissions, grouped as 0, 1, 2+ non-clustered, and 2+ clustered readmissions. KEY RESULTS: Approximately 14% of patients had 1 readmission, 2.4% had 2+ non-clustered readmissions, and 3.3% patients had 2+ clustered readmissions during the 270-day follow-up. A higher Elixhauser Comorbidity Index was associated with increased risk for all readmission groups, namely with adjusted odds ratios (AORs) ranging from 1.12 to 3.34. Compared to patients aged 80 years and older, those in younger age groups had increased risk of 2+ non-clustered and 2+ clustered readmissions (AOR range 1.27-2.49). Patients with chronic versus acute ACSCs had an increased odds ratio of all readmission groups compared to those with 0 readmissions (AOR range 1.37-2.69). CONCLUSIONS: Among patients with 2+ 30-day readmissions, factors were differentially distributed between clustered and non-clustered readmissions. Identifying factors that could predict future readmission patterns can inform primary care in the prevention of readmissions following ACSC-related hospitalizations.

Exploring classification of birth defects severity in national hospital discharge databases compared to an active surveillance program.

OBJECTIVE: To explore the extent to which the severity of birth defects could be differentiated using severity of illness (SOI) and risk of mortality (ROM) measures available in national discharge databases. METHODS: Data from the 2012-14 National Inpatient Sample (NIS) was used to identify hospitalizations with one or more major birth defects reported annually to the National Birth Defects Prevention Network using the International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) diagnosis codes. Each hospitalization also contained a 4-level SOI and 4-level ROM classification measure. For each birth defect and for each individual birth defect-related ICD-9-CM code, we calculated mean and median SOI and ROM, the proportion of hospitalizations in each level of SOI and ROM, the inpatient mortality rate, and level of agreement between various existing or derived severity proxies in the NIS and the Texas Birth Defects Registry (TBDR). RESULTS: Mean SOI ranged from 1.5 (cleft lip alone) to 3.7 (single ventricle), and mean ROM ranged from 1.1 (cleft lip alone) to 3.9 (anencephaly). As a group, critical congenital heart defects had the highest average number of co-occurring defects, mean SOI, and ROM, whereas orofacial and genitourinary defects had the lowest SOI and ROM. We found strong levels of agreement between TBDR severity classifications and NIS severity classifications defined using Level 3 or 4 SOI or ROM Level 3 or 4. CONCLUSIONS: This preliminary investigation demonstrated how severity indices of birth defects could be differentiated and compared to a severity algorithm of an existing surveillance program.

From primary care to the revolving door of hospital readmission: Relevance of Geoffrey Rose's call for a population strategy.

The high-risk strategy in prevention has remained the preferred approach in health care. High-profile research predominantly emphasizes specific high-risk subgroups such as those who have extremely high cholesterol and super-utilizers of emergency departments. Dr. Geoffrey Rose's alternative population approach, though well established in principle, has failed to come to fruition in primary care research, aside from a few exceptions. The population approach extends intervention efforts to more moderate-risk people, attempting to shift the overall distribution in a positive direction, effecting change in more of the population. Despite requiring more initial investment due to the larger target group, the health-related gains and downstream cost savings through a population strategy may yield greater long-term cost-effectiveness than the high-risk strategy. We describe the example of extending prevention efforts from super-utilizers (e.g. those with ≥3 readmissions per year) to include those who readmit in moderate frequency (1-2 per year) in terms of potential hospital days and associated medical costs averted.

Emergency Department High Utilizers among Family Medicine Patients.

BACKGROUND: Increases in emergency department (ED) use are contributing to inefficient health care spending and becoming a public health concern. Previous studies have identified characteristics of ED high utilizers aimed at designing interventions to improve efficiency. We aim to expand on these findings in a family medicine outpatient population. METHODS: We conducted a retrospective analysis on a population of ED high utilizers, defined as those who had been to the ED 6 or more times in 1 year, including medical and demographic characteristics from 2015 to 2017. RESULTS: Compared with our source population, ED high utilizers were most commonly female, African American, or single and insured by Medicare or Medicaid. They did not have a chronic pain or substance use diagnosis, but more than half had a psychiatric condition. The only demographic characteristic that changed over time was home location from 2015 to 2017 (P < .05). Less than 10% of ED high utilizers were the same over 3 years. CONCLUSIONS: Most demographic characteristics did not change over time, whereas individuals did change. Interventions aimed at improving efficiency of ED use should be geared toward unchanging characteristics rather than individuals. The only demographic characteristic that did change significantly was home location that correlated in time with the availability of new EDs providing support for a theory of supply-sensitive ED use.