Difficult hospital discharges in internal medicine wards

Collection and Use of Social Determinants of Health Data in Inpatient General Internal Medicine Wards: A Scoping Review

BACKGROUND

There is growing interest in incorporating social determinants of health (SDoH) data collection in inpatient hospital settings to inform patient care. However, there is limited information on this data collection and its use in inpatient general internal medicine (GIM). This scoping review sought to describe the current state of the literature on SDoH data collection and its application to patient care in inpatient GIM settings.

METHODS

English-language searches on MedLine, Embase, Web of Science, CINAHL, Cochrane, and PsycINFO were conducted from 2000 to April 2021. Studies reporting systematic data collection or use of at least three SDoH, sociodemographic, or social needs variables in inpatient hospital GIM settings were included. Four independent reviewers screened abstracts, and two reviewers screened full-text articles.

RESULTS

A total of 8190 articles underwent abstract screening and eight were included. A range of SDoH tools were used, such as THRIVE, PRAPARE, WHO-Quality of Life, Measuring Health Equity, and a biopsychosocial framework. The most common SDoH were food security or malnutrition (n=7), followed by housing, transportation, employment, education, income, functional status and disability, and social support (n=5 each). Four of the eight studies applied the data to inform patient care, and three provided community resource referrals.

DISCUSSION

There is limited evidence to guide the collection and use of SDoH data in inpatient GIM settings. This review highlights the need for integrated care, the role of the electronic health record, and social history taking, all of which may benefit from more robust SDoH data collection. Future research should examine the feasibility and acceptability of SDoH integration in inpatient GIM settings.

Perceived discharge quality and associations with hospital readmissions and emergency department use: a prospective cohort study

Background

At hospital discharge, care is handed over from providers to patients. Discharge encounters must prepare patients to self-manage their health, but have been found to be suboptimal. Our study objectives were to describe and determine the correlates of perceived discharge quality and to explore the association between perceived discharge quality and postdischarge outcomes.

Methods

We conducted a prospective cohort study in medical inpatients admitted to a tertiary care hospital in Calgary, Canada. Perceived discharge quality was measured by the Care Transitions Measure (CTM). Linkage to administrative databases provided data for the composite outcome—90-day hospital readmission or emergency department visit. Logistic regression modelling was used to determine the association between global CTM scores, and the individual CTM components, and the composite outcome.

Results

A total of 316 patients were included in the analysis. The median CTM score was 80.0 (IQR 66.6–100.0). The distribution of CTM scores were significantly different based on comorbidity burden, with the median and maximum CTM scores being lower and the IQR being narrower, for those with six or more comorbidities compared with those with fewer comorbidities. CTM scores were not associated with the composite outcome, though a single CTM item—not understanding warning signs and symptoms—was (adjusted OR 3.46 (95% CI 1.02 to 11.73)).

Conclusion

Perceived quality of discharge varies based on patient burden of comorbidities. While global perceived discharge quality was not associated with postdischarge outcomes, lack of patient understanding of warning symptoms was. Discharging healthcare teams should pay special attention to these priority patient groups and specific discharge process components.

Organizational determinants of hospital stay: establishing the basis of a widespread action on more efficient pathways in medical units

Given the high hospital costs, the increasing clinical complexity and the overcrowding of emergency departments, it is crucial to improve the efficiency of medical admissions. We aimed at isolating organizational drivers potentially targetable through a widespread improvement action. We studied all medical admissions in a large tertiary referral hospital from January 1st to December 31st, 2018. Data were retrieved from the administrative database. Available information included age, sex, type (urgent or elective) and Unit of admission, number of internal transfers, main ICD-9 diagnosis, presence of cancer among diagnoses, surgical or medical code, type of discharge, month, day and hour of admission and discharge. National Ministry of Health database was used for comparisons. 8099 admissions were analyzed. Urgent admissions (80.5% of the total) were responsible for longer stays and were the object of the multivariate analysis. The variables most influencing length-of-stay (LOS) were internal transfers and assisted discharge: they contributed, respectively, to 62% and 40% prolongation of LOS. Also, the daily and weekly kinetics of admission accounted for a significant amount of variation in LOS. Long admissions (≥ 30 days) accounted for the 15.5% of total bed availability. Type of discharge and internal transfers were again among the major determinants. A few factors involved in LOS strictly depend on the organizational environment and are potentially modifiable. Re-engineering should be focused on making more efficient internal and external transitions and at ensuring continuity of the clinical process throughout the day and the week.

Causas de atraso na alta hospitalar no cliente adulto: scoping review

Resumo OBJETIVO Mapear a evidência existente sobre as causas de atraso na alta hospitalar no cliente adulto. MÉTODOS Efetuada revisão da literatura do tipo scoping review. Pesquisou-se na plataforma informática da Ebscohost, na PubMed e na literatura cinzenta, consultando-se as referências bibliográficas desses documentos. RESULTADOS Dos 22 artigos analisados verificou-se que o atraso na alta hospitalar se deve a causas relacionadas com os recursos da comunidade, designadamente a falta de vagas em unidades de saúde e motivos sociais; a causas organizacionais relacionadas com os cuidados de saúde; a causas individuais, destacando-se as questões familiares e financeiras; culminando nas causas organizacionais relacionadas com a gestão hospitalar. CONCLUSÃO O atraso na alta hospitalar é multifatorial, tornando-se necessário monitorizar o processo de internação, apostando-se num planejamento de alta antecipado.

Predicting discharge to institutional long-term care following acute hospitalisation: a systematic review and meta-analysis

Background

moving into long-term institutional care is a significant life event for any individual. Predictors of institutional care admission from community-dwellers and people with dementia have been described, but those from the acute hospital setting have not been systematically reviewed. Our aim was to establish predictive factors for discharge to institutional care following acute hospitalisation.

Methods

we registered and conducted a systematic review (PROSPERO: CRD42015023497). We searched MEDLINE; EMBASE and CINAHL Plus in September 2015. We included observational studies of patients admitted directly to long-term institutional care following acute hospitalisation where factors associated with institutionalisation were reported.

Results

from 9,176 records, we included 23 studies (n = 354,985 participants). Studies were heterogeneous, with the proportions discharged to a care home 3–77% (median 15%). Eleven studies (n = 12,642), of moderate to low quality, were included in the quantitative synthesis. The need for institutional long-term care was associated with age (pooled odds ratio (OR) 1.02, 95% confidence intervals (CI): 1.00–1.04), female sex (pooled OR 1.41, 95% CI: 1.03–1.92), dementia (pooled OR 2.14, 95% CI: 1.24–3.70) and functional dependency (pooled OR 2.06, 95% CI: 1.58–2.69).

Conclusions

discharge to long-term institutional care following acute hospitalisation is common, but current data do not allow prediction of who will make this transition. Potentially important predictors evaluated in community cohorts have not been examined in hospitalised cohorts. Understanding these predictors could help identify individuals at risk early in their admission, and support them in this transition or potentially intervene to reduce their risk.

Identification of components of health complexity on internal medicine units by means of the INTERMED method

BACKGROUND

The INTERMED was developed for the early identification of biological, psychological, social and health system factors considered interacting in health complexity. This is defined as the interference with the achievement of expected or desired health and service use outcomes when patients are exposed to standard care.

OBJECTIVE

The aim of this study was to test the INTERMED's ability to identify 'case' and 'care' complexity, identifying patients that would especially benefit from integrated care.

METHODS

Observational longitudinal study of Internal medicine in patients in two National Health System hospitals in Spain using the INTERMED (patients scoring ≥ 21 were considered to be 'complex'); the Cumulative Illness Rating Scale (CIRS), a severity of illness assessment; and standard clinical variables.

RESULTS

Six hundred and fifteen consecutives were included, and the prevalence of health complexity was 27.6%. The greatest differences between patients with and without health complexity were observed in the non-biological domains. Eighty-five per cent of patients with health complexity had non-biological items considered to require timely (immediately or soon) assistance or intervention compared to 30% of those without, nearly a threefold difference. Complex patients had a significantly higher number of medical diagnoses (p = 0.002) and number of psychiatric referrals (p = 0.041), but there were no differences in CIRS scores or lengths of stay.

CONCLUSION

The INTERMED has the potential to identify a considerable subset of complex internal medicine inpatients for which timely corrective action related to non-biological risk factors not typically uncovered during standard medical evaluations would be considered beneficial.

Method for Assigning Priority Levels in Acute Care (MAPLe-AC) predicts outcomes of acute hospital care of older persons--a cross-national validation

BACKGROUND

Although numerous risk factors for adverse outcomes for older persons after an acute hospital stay have been : identified, a decision making tool combining all available information in a clinically meaningful way would be helpful for daily hospital practice. The purpose of this study was to evaluate the ability of the Method for Assigning Priority Levels for Acute Care (MAPLe-AC) to predict adverse outcomes in acute care for older people and to assess its usability as a decision making tool for discharge planning.

METHODS

Data from a prospective multicenter study in five Nordic acute care hospitals with information from admission to a one year follow-up of older acute care patients were compared with a prospective study of acute care patients from admission to discharge in eight hospitals in Canada. The interRAI Acute Care assessment instrument (v1.1) was used for data collection. Data were collected during the first 24 hours in hospital, including pre-morbid and admission information, and at day 7 or at discharge, whichever came first. Based on this information a crosswalk was developed from the original MAPLe algorithm for home care settings to acute care (MAPLe-AC). The sample included persons 75 years or older who were admitted to acute internal medical services in one hospital in each of the five Nordic countries (n = 763) or to acute hospital care either internal medical or combined medical-surgical services in eight hospitals in Ontario, Canada (n = 393). The outcome measures considered were discharge to home, discharge to institution or death. Outcomes in a 1-year follow-up in the Nordic hospitals were: living at home, living in an institution or death, and survival. Logistic regression with ROC curves and Cox regression analyses were used in the analyses.

RESULTS

Low and mild priority levels of MAPLe-AC predicted discharge home and high and very high priority levels predicted adverse outcome at discharge both in the Nordic and Canadian data sets, and one-year outcomes in the Nordic data set. The predictive accuracy (AUC's) of MAPLe-AC's was higher for discharge outcome than one year outcome, and for discharge home in Canadian hospitals but for adverse outcome in Nordic hospitals. High and very high priority levels in MAPLe-AC were also predictive of days to death adjusted for diagnoses in survival models.

CONCLUSION

MAPLe-AC is a valid algorithm based on risk factors that predict outcomes of acute hospital care. It could be a helpful tool for early discharge planning although further testing for active use in clinical practice is still needed.