Clinical complexity and hospital admissions in the December holiday period

Abstract

Background Christmas and New Year's holidays are risk factors for hospitalization, but the causes of this "holiday effect" are uncertain. In particular, clinical complexity (CC) has never been assessed in this setting. We therefore sought to determine whether patients admitted to the hospital during the December holiday period had greater CC compared to those admitted during a contiguous non-holiday period. Methods This is a prospective, longitudinal study conducted in an academic ward of internal medicine in 2017-2019. Overall, 227 consecutive adult patients were enrolled, including 106 cases (mean age 79.4±12.8 years, 55 females; 15 December-15 January) and 121 controls (mean age 74.3±16.6 years, 56 females; 16 January-16 February). Demographic characteristics, CC, length of stay, and early mortality rate were assessed. Logistic regression analyses for the evaluation of independent correlates of being a holiday case were computed. Results Cases displayed greater CC (17.7±5.5 vs 15.2±5.9; p = 0.001), with greater impact of socioeconomic (3.51±1.7 vs 2.9±1.7; p = 0.012) and behavioral (2.36±1.6 vs 1.9±1.8; p = 0.01) CC components. Cases were also significantly frailer according to the Edmonton Frail Scale (8.0±2.8 vs 6.4±3.1; p<0.001), whilst having similar disease burden, as measured by the CIRS comorbidity index. Age (OR 1.02; p = 0.039), low income (OR 1.97, 95% CI 1.10-3.55; p = 0.023), and total CC (OR 1.06; p = 0.014) independently correlated with the cases. Also, cases showed a longer length of stay (median 15.5 vs 11 days; p = 0.0016) and higher in-hospital (12 vs 4 events; p = 0.021) and 30-day (14 vs 6 events; p = 0.035) mortality.

Radiotherapy interruption due to holidays adversely affects the survival of patients with nasopharyngeal carcinoma: a joint analysis based on large-scale retrospective data and clinical trials

“…The association between holidays and unfavorable health-related outcomes exists in different nationalities, cultures, and ethnicities, so there must be an intrinsic cause of the “holiday effect” [ 34 , 35 ]. RT efficacy in clinical practise is deemed to be determined based on the information related to both disease-related factors and psychosocial components, which usually interact with each other constantly in an unpredictable manner [ 35 ]. This is a hitherto unexplored area in NPC and has never been assessed.…”

The Impact of Month on Joint Arthroplasty In-Hospital Outcomes: The December Effect

“…After December was found to have the lowest overall complication rate, a particular focus was directed to analyze outcomes in December compared with the rest of the months. This analysis of December was noteworthy given the disruptions in health outcomes in December that have been previously described in the general medical literature [ [10] , [11] , [12] ].…”

“…There are several plausible social and societal explanations for this December effect, which is opposite to the unfavorable health outcomes during the December holidays that have been documented in the general medical literature [ [10] , [11] , [12] ]. Although the evidence base is evolving, patient and family engagement is a marker of high-quality health care and is associated with improved health outcomes and lower use of health services [ 16 ].…”

“…However, because such seasonal studies typically analyze data pooled by yearly quarters or seasons, the assessment of the unique impact of specific months remains lacking. The understanding of monthly variation in outcomes is important since the December holiday season has been identified as a risk factor in the medical literature for unfavorable health outcomes and worsened patient morbidity and mortality [ [10] , [11] , [12] ]. Because of anecdotal and such clinical data suggesting that December and its associated holiday season may impact medical and surgical outcomes, analyzing the impact of the month of December specifically on in-hospital outcomes after TJA is needed to identify potential unique risk factors, which may uncover addressable opportunities for better risk stratification and improved postsurgical outcomes.…”

Aging underlies heterogeneity between comorbidity and multimorbidity frameworks

“…In the SMAC study, adult patients admitted to our internal medicine unit were included, regardless of the cause of admission. The details of the enrolment have already been described elsewhere [17]. Demographic (i.e., age, gender) and clinical data (i.e., polypharmacy, body mass index [BMI], frailty according to the Edmonton Frail Scale [18], length of stay, in-hospital and 30-day mortalities, 30-day readmission) were collected, including the Cumulative Illness Rating Scale (CIRS) [19], a common tool for assessing MCC in clinical studies [20].…”