A tool for prediction of risk of rehospitalisation and mortality in the hospitalised elderly: secondary analysis of clinical trial data

Development and external validation of a prognostic model for time to readmission or death in multimorbid patients

OBJECTIVE

To develop and externally validate a prognostic model built on important factors predisposing multimorbid patients to all-cause readmission and/or death. In addition to identify patients who may benefit most from a comprehensive clinical pharmacist intervention.

METHODS

A multivariable prognostic model was developed based on data from a randomised controlled trial investigating the effect of pharmacist-led medicines management on readmission rate in multimorbid, hospitalised patients. The derivation set comprised 386 patients randomised in a 1:1 manner to the intervention group, i.e. with a pharmacist included in their multidisciplinary treatment team, or the control group receiving standard care at the ward. External validation of the model was performed using data from an independent cohort, in which 100 patients were randomised to the same intervention, or standard care. The setting was an internal medicines ward at a university hospital in Norway.

RESULTS

The number of patients who were readmitted or had died within 18 months after discharge was 297 (76.9 %) in the derivation set, i.e. the randomized controlled trial, and 69 (71.1 %) in the validation set, i.e. the independent cohort. Charlson comorbidity index (CCI; low, moderate or high), previous hospital admissions within the previous six months and heart failure were the strongest prognostic factors and were included in the final model. The efficacy of the pharmaceutical intervention did not prove significant in the model. A prognostic index (PI) was constructed to estimate the hazard of readmission or death (low, intermediate or high-risk groups). Overall, the external validation replicated the result. We were unable to identify a subgroup of the multimorbid patients with better efficacy of the intervention.

CONCLUSIONS

A prognostic model including CCI, previous admissions and heart failure can be used to obtain valid estimates of risk of readmission and death in patients with multimorbidity.

Effectiveness of pharmacist-led medication reconciliation on medication errors at hospital discharge and healthcare utilization in the next 30 days: a pragmatic clinical trial

Transitions of care often lead to medication errors and unnecessary healthcare utilization. Medication reconciliation has been repeatedly shown to reduce this risk. However, the great majority of evidence is limited to the provision of medication reconciliation within clinical trials and countries with well-established clinical pharmacy. Thus, this pragmatic, prospective, controlled trial evaluated the effectiveness of routine pharmacist-led medication reconciliation compared to standard care on medication errors and unplanned healthcare utilization in adult general medical patients hospitalized in a teaching hospital in Slovenia. All patients hospitalized in a ward where medication reconciliation was integrated into routine clinical practice were included in the intervention group and received admission and discharge medication reconciliation, coupled with patient counselling. The control group consisted of randomly selected patients from the remaining medical wards. The primary study outcome was unplanned healthcare utilization within 30 days of discharge, and the secondary outcomes were clinically important medication errors at hospital discharge and serious unplanned healthcare utilization within 30 days of discharge. Overall, 414 patients (53.4% male, median 71 years) were included-225 in the intervention group and 189 in the control group. In the intervention group, the number of patients with clinically important medication errors at discharge was significantly lower (intervention vs control group: 9.3% vs 61.9%). Multiple logistic regression revealed that medication reconciliation reduced the likelihood of a clinically important medication error by 20-fold, while a higher number of medications on admission was associated with an increased likelihood. However, no significant differences were noted in any and serious unplanned healthcare utilization (intervention vs control group: 33.9% vs 27.8% and 20.3% vs 14.6%, respectively). The likelihood of serious healthcare utilization increased with the age of the patient, the number of medications on admission and being hospitalized for an acute medical condition. Our pragmatic trial confirmed that medication reconciliation, even when performed as part of routine clinical practice, led to a substantial reduction in the risk of clinically important medication errors at hospital discharge but not to a reduction in healthcare utilization. Medication reconciliation is a fundamental, albeit not sufficient, element to ensure patient safety after hospital discharge. Clinical Trial Registration: https://clinicaltrials.gov/search?id=NCT06207500, identifier NCT06207500.

Targeted care navigation to reduce hospital readmissions in 'at-risk' patients

BACKGROUND

Care navigation is commonly used to reduce preventable hospitalisation. The use of Electronic Health Record-derived algorithms may enable better targeting of this intervention for greater impact.

AIMS

To evaluate if community-based Targeted Care Navigation, supported by an Electronic Health Record-derived readmission risk algorithm, is associated with reduced rehospitalisation.

METHODS

A propensity score matching cohort (5 comparison to 1 intervention cohort ratio) study was conducted in an 850-bed Victorian public metropolitan health service, Australia, from May to November 2017. Admitted acute care patients with a non-surgical condition, identified as at-risk of hospital readmission using an Electronic Health Record-derived readmission risk algorithm provide by the state health department, were eligible. Targeted Care Navigation involved telephone follow-up support provided for 30 days post-discharge by a registered nurse. The hazard ratio for hospital readmission was calculated at 30, 60 and 90 days post-discharge using multivariable Cox Proportional Hazards regression.

RESULTS

Sixty-five recipients received care navigation and were matched to 262 people who did not receive care navigation. Excellent matching was achieved with standardised differences between groups being <0.1 for all 11 variables included in the propensity score, including the readmission risk score. The Targeted Care Navigation group had a significantly reduced hazard of readmission at 30 days (hazard ratio 0.34; 95% confidence interval: 0.12, 0.94) compared with the comparison group. The effect size was reduced at 60 and 90 days post-discharge.

CONCLUSION

We provide preliminary evidence that Targeted Care Navigation supported by an Electronic Health Record-derived readmission risk algorithm may reduce 30-day hospital readmissions.

Medication review in hospitalised patients to reduce morbidity and mortality

BACKGROUND

A medication review can be defined as a structured evaluation of a patient's medication conducted by healthcare professionals with the aim of optimising medication use and improving health outcomes. Optimising medication therapy though medication reviews may benefit hospitalised patients.

OBJECTIVES

We examined the effects of medication review interventions in hospitalised adult patients compared to standard care or to other types of medication reviews on all-cause mortality, hospital readmissions, emergency department contacts and health-related quality of life.

SEARCH METHODS

In this Cochrane Review update, we searched for new published and unpublished trials using the following electronic databases from 1 January 2014 to 17 January 2022 without language restrictions: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform (ICTRP). To identify additional trials, we searched the reference lists of included trials and other publications by lead trial authors, and contacted experts.

SELECTION CRITERIA

We included randomised trials of medication reviews delivered by healthcare professionals for hospitalised adult patients. We excluded trials including outpatients and paediatric patients.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected trials, extracted data and assessed risk of bias. We contacted trial authors for data clarification and relevant unpublished data. We calculated risk ratios (RRs) for dichotomous data and mean differences (MDs) or standardised mean differences (SMDs) for continuous data (with 95% confidence intervals (CIs)). We used the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach to assess the overall certainty of the evidence.

MAIN RESULTS

In this updated review, we included a total of 25 trials (15,076 participants), of which 15 were new trials (11,501 participants). Follow-up ranged from 1 to 20 months. We found that medication reviews in hospitalised adults may have little to no effect on mortality (RR 0.96, 95% CI 0.87 to 1.05; 18 trials, 10,108 participants; low-certainty evidence); likely reduce hospital readmissions (RR 0.93, 95% CI 0.89 to 0.98; 17 trials, 9561 participants; moderate-certainty evidence); may reduce emergency department contacts (RR 0.84, 95% CI 0.68 to 1.03; 8 trials, 3527 participants; low-certainty evidence) and have very uncertain effects on health-related quality of life (SMD 0.10, 95% CI -0.10 to 0.30; 4 trials, 392 participants; very low-certainty evidence).

AUTHORS' CONCLUSIONS

Medication reviews in hospitalised adult patients likely reduce hospital readmissions and may reduce emergency department contacts. The evidence suggests that mediation reviews may have little to no effect on mortality, while the effect on health-related quality of life is very uncertain. Almost all trials included elderly polypharmacy patients, which limits the generalisability of the results beyond this population.

Detection tools for prediction and identification of adverse drug reactions in older patients: a systematic review and meta-analysis

Tools to accurately predict and detect adverse drug reactions (ADR) in elderly patients have not been developed. We aimed to identify and evaluate reports on tools that predict and detect ADR in elderly patients (≥ 60 years). In this review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Databases were searched until January 2022 using key terms “elderly,” “adverse drug reaction,” and “detection instruments.” Eighteen studies met the inclusion criteria, and they examined assorted interventions: STOPP/START version 1/2 (n = 10), Beers Criteria 2012 or 2015 (n = 4), Systematic Tool to Reduce Inappropriate Prescribing (STRIP) (n = 2), Tool to Reduce Inappropriate Medications (TRIM) (n = 1), Medication Risk Score (MERIS) (n = 1), Computerized alert systems (n = 1), and Norwegian General Practice-Nursing Home criteria (n = 1). The interventions affected the number of potential prescription omissions (OR, 0.50 [0.37–0.69]; p < 0.0001; four studies). No apparent reduction in the number of drug interactions within 2 months (OR, 0.84 [0.70–1.02]; p = 0.08; two studies) and mortality (OR, 0.92 [0.76–1.12]; p = 0.41; three studies) was observed. In conclusion, there is no definitive and validated assessment tool for detecting and predicting ADR in elderly patients. Thus, more research on refining existing tools or developing new ones is warranted.

Is a High Medication Risk Score Associated With Increased Risk of 30-Day Readmission? A Population-Based Cohort Study From CROSS-TRACKS

OBJECTIVES

The primary aim of this study was to evaluate whether a high Medication Risk Score (MERIS) upon admission to an emergency department is associated with increased risk of 30-day readmission in patients discharged directly home. Mortality, visit to general practitioner, and drug changes within 30 days were included as secondary outcomes.

METHODS

This is a historical cohort study with data from the Danish population-based open-cohort CROSS-TRACKS. Cox regression analyses were used to determine whether a high MERIS score was associated with increased risk of 30-day readmission and mortality. Visit to general practitioner and drug changes were tested with χ2 test and Wilcoxon rank sum test.

RESULTS

A total of 2106 patients were eligible: 2017 had a MERIS score lower than 14 (low-risk group), and 89 had a score of 14 or higher (high-risk group). The proportion of patients in the high-risk group who were readmitted was 21.3% compared with 16.3% in the low-risk group, resulting in a hazard ratio for readmission of 1.43 (95% confidence interval, 0.9-1.3). The hazard ratio for mortality was 8.3 (95% confidence interval, 3.0-22.8). No statistical significant difference was found in general practitioner visits; however, significantly more drug changes were observed in the high-risk group.

CONCLUSIONS

A high MERIS score was associated with increased risk of readmissions and can potentially assist healthcare professionals in the prioritizing of patients who may benefit from further exam, for example, additional medication review in acute care setting. Further investigation of MERIS and exploration of causal inferences between medication-related harm and medication-related readmissions are warranted.

Readmission to an Acute Care Hospital During Inpatient Rehabilitation After Stroke

OBJECTIVE

The aim of the study was to identify causes for readmission to acute care of patients admitted to inpatient rehabilitation facility after stroke.

DESIGN

The institutional Uniform Data System for Medical Rehabilitation database was used to identify stroke patients who experienced readmission to acute care and an equal number of age-/sex-matched group of patients who successfully completed their inpatient rehabilitation facility stay during 2005-2018. Retrospective chart review was used to extract clinical data. The two study groups were compared using univariate and multivariate analyses.

RESULTS

The rate of readmission to acute care was 4.7% (n = 89; age = 65 ± 14 yrs; 37% female; 65% White; 73% ischemic stroke). The most common indications for transfer were neurological (31%) and cardiovascular (28%). Compared with control group, the readmission to acute care group had statistically higher rates of comorbid conditions, lower median (interquartile range) Functional Independence Measure score on inpatient rehabilitation facility admission (55 [37-65] vs. 64 [51-78], P < 0.001), and a higher rate of sedative/hypnotic prescription (82% vs. 23%, P < 0.001).

CONCLUSIONS

Readmission to acute care is not common in our cohort. Patients who experienced readmission to acute care had higher medical complexity and were prescribed more sedative/hypnotic medications than the control group. Practitioners should be vigilant in patients who meet these criteria.

Safety of Elderly Fallers: Identifying Associated Risk Factors for 30-Day Unplanned Readmissions Using a Clinical Data Warehouse

BACKGROUND

Hospital readmissions are a major problem in the older people as they are frequent, costly, and life-threatening. Falls among older adults are the leading cause of injury, deaths, and emergency department visits for trauma.

OBJECTIVE

The main objective was to determine risk factors associated with a 30-day readmission after index hospital admission for fall-related injuries.

METHODS

A retrospective nested case-control study was conducted. Data from elderly patients initially hospitalized for fall-related injuries in 2019, in 11 of the Greater Paris University Hospitals and discharged home, were retrieved from the clinical data warehouse. Cases were admission of elderly patients who subsequently experienced a readmission within 30 days after discharge from the index admission. Controls were admission of elderly patients who were not readmitted to hospital.

RESULTS

Among 670 eligible index admissions, 127 (18.9%) were followed by readmission within 30 days after discharge. After multivariate analysis, men sex (odds ratio [OR] = 2.29, 95% confidence interval [CI] = 1.45-3.61), abnormal concentration of C-reactive protein, and anemia (OR = 2.22, 95% CI = 1.28-3.85; OR = 1.85, 95% CI = 1.11-3.11, respectively) were associated with a higher risk of readmission. Oppositely, having a traumatic injury at index admission decreased this risk (OR = 0.47, 95% CI = 0.28-0.81).

CONCLUSIONS

Reducing early unplanned readmission is crucial, especially in elderly patients susceptible to falls. Our results indicate that the probability of unplanned readmission is higher for patients with specific characteristics that should be taken into consideration in interventions designed to reduce this burden.

Discharge Planning of Older Persons from Hospital: Comparison of Observed Practice to Recommended Best Practice

Older people are particularly vulnerable to hospital re-presentation following discharge. Ideal discharge planning processes facilitate the transition from hospital to home and prevent subsequent re-presentations to hospital. The objective of this study was to examine discharge planning processes in two Australian hospitals, compare them between sites and to best-practice recommendations. An ethnographic observational study of discharge planning processes was conducted at two general medical inpatient wards at a large tertiary hospital and a smaller regional hospital in Brisbane, Australia. Participants were patients and ward staff involved in discharge planning during a hospital admission. A literature review was conducted to elicit best-practice recommendations for discharge planning. Data for this study (duration: 112 h) were collected directly using field notes by a research assistant embedded in the ward. A directed qualitative content analysis approach was used for data analysis. Results were compared to best-practice recommendations. Findings indicate that both hospitals implemented various best-practice interventions to enhance communication, collaboration, coordination and patient/family engagement for optimal discharge planning. Strategies used were context specific and effective to varying degrees. Clear responsibilities and goals within the multidisciplinary team helped to create cohesive, well-functioning teams. More work is needed to engage patients and families in discharge planning, and to encourage health professionals to consider patients and family as active team members in the discharge planning process.

External validation of the PAR-Risk Score to assess potentially avoidable hospital readmission risk in internal medicine patients

BACKGROUND

Readmission prediction models have been developed and validated for targeted in-hospital preventive interventions. We aimed to externally validate the Potentially Avoidable Readmission-Risk Score (PAR-Risk Score), a 12-items prediction model for internal medicine patients with a convenient scoring system, for our local patient cohort.

METHODS

A cohort study using electronic health record data from the internal medicine ward of a Swiss tertiary teaching hospital was conducted. The individual PAR-Risk Score values were calculated for each patient. Univariable logistic regression was used to predict potentially avoidable readmissions (PARs), as identified by the SQLape algorithm. For additional analyses, patients were stratified into low, medium, and high risk according to tertiles based on the PAR-Risk Score. Statistical associations between predictor variables and PAR as outcome were assessed using both univariable and multivariable logistic regression.

RESULTS

The final dataset consisted of 5,985 patients. Of these, 340 patients (5.7%) experienced a PAR. The overall PAR-Risk Score showed rather poor discriminatory power (C statistic 0.605, 95%-CI 0.575-0.635). When using stratified groups (low, medium, high), patients in the high-risk group were at statistically significant higher odds (OR 2.63, 95%-CI 1.33-5.18) of being readmitted within 30 days compared to low risk patients. Multivariable logistic regression identified previous admission within six months, anaemia, heart failure, and opioids to be significantly associated with PAR in this patient cohort.

CONCLUSION

This external validation showed a limited overall performance of the PAR-Risk Score, although higher scores were associated with an increased risk for PAR and patients in the high-risk group were at significantly higher odds of being readmitted within 30 days. This study highlights the importance of externally validating prediction models.

Potentially inappropriate prescriptions according to explicit and implicit criteria in patients with multimorbidity and polypharmacy. MULTIPAP: A cross-sectional study

Background

Multimorbidity is a global health challenge that is associated with polypharmacy, increasing the risk of potentially inappropriate prescribing (PIP). There are tools to improve prescription, such as implicit and explicit criteria.

Objective

To estimate the prevalence of PIP in a population aged 65 to 74 years with multimorbidity and polypharmacy, according to American Geriatrics Society Beers Criteria^® (2015, 2019), the Screening Tool of Older Person’s Prescription -STOPP- criteria (2008, 2014), and the Medication Appropriateness Index -MAI- criteria in primary care.

Methods

This was an observational, descriptive, cross-sectional study. The sample included 593 community-dwelling elderly aged 65 to 74 years, with multimorbidity and polypharmacy, who participated in the MULTIPAP trial. Socio-demographic, clinical, professional, and pharmacological-treatment variables were recorded. Potentially inappropriate prescribing was detected by computerized prescription assistance system, and family doctors evaluated the MAI. The MAI-associated factors were analysed using a logistic regression model.

Results

A total of 4,386 prescriptions were evaluated. The mean number of drugs was 7.4 (2.4 SD). A total of 94.1% of the patients in the study had at least one criterion for drug inappropriateness according to the MAI. Potentially inappropriate prescribing was detected in 57.7%, 43.6%, 68.8% and 71% of 50 patients according to the explicit criteria STOPP 2014, STOPP 2008, Beers 2019 and Beers 2015 respectively. For every new drug taken by a patient, the MAI score increased by 2.41 (95% CI 1.46; 3.35) points. Diabetes, ischaemic heart disease and asthma were independently associated with lower summated MAI scores.

Conclusions

The prevalence of potentially inappropriate prescribing detected in the sample was high and in agreement with previous literature for populations with multimorbidity and polypharmacy. The MAI criteria detected greater inappropriateness than did the explicit criteria, but their application was more complex and difficult to automate.

Medication-related hospital admissions and readmissions in older patients: an overview of literature

Background The number of medication related hospital admissions and readmissions are increasing over the years due to the ageing population. Medication related hospital admissions and readmissions lead to decreased quality of life and high healthcare costs. Aim of the review To assess what is currently known about medication related hospital admissions, medication related hospital readmissions, their risk factors, and possible interventions which reduce medication related hospital readmissions. Method We searched PubMed for articles about the topic medication related hospital admissions and readmissions. Overall 54 studies were selected for the overview of literature. Results Between the different selected studies there was much heterogeneity in definitions for medication related admission and readmissions, in study population and the way studies were performed. Multiple risk factors are found in the studies for example: polypharmacy, comorbidities, therapy non adherence, cognitive impairment, depending living situation, high risk medications and higher age. Different interventions are studied to reduce the number of medication related readmission, some of these interventions may reduce the readmissions like the participation of a pharmacist, education programmes and transition-of-care interventions and the use of digital assistance in the form of Clinical Decision Support Systems. However the methods and the results of these interventions show heterogeneity in the different researches. Conclusion There is much heterogeneity in incidence and definitions for both medication related hospital admissions and readmissions. Some risk factors are known for medication related admissions and readmissions such as polypharmacy, older age and additional diseases. Known interventions that could possibly lead to a decrease in medication related hospital readmissions are spare being the involvement of a pharmacist, education programs and transition-care interventions the most mentioned ones although controversial results have been reported. More research is needed to gather more information on this topic.

Screening Tools Used by Clinical Pharmacists to Identify Elderly Patients at Risk of Drug-Related Problems on Hospital Admission: A Systematic Review

None of the models met the four key stages required to create a quality risk prediction model. Further research is needed to either refine the tools developed to date or develop new ones that have good performance and have been externally validated before considering the potential impact and implementation of such tools.

Comparing Potentially Inappropriate Prescribing Tools and Their Association With Patient Outcomes

OBJECTIVE

To assess the agreement of several different measures of potentially inappropriate prescribing (PIP) in older people and compare their relationship with patient-reported outcomes.

DESIGN

Prospective cohort study including participants in The Irish Longitudinal Study on Ageing (TILDA).

SETTING

Waves 1 and 2 of TILDA, a nationally representative aging cohort study.

PARTICIPANTS

A total of 1753 community-dwelling TILDA participants with linked administrative pharmacy claims data on medications.

MEASUREMENTS

Potentially inappropriate medications were assessed using the Screening Tool of Older Persons' Potentially Inappropriate Prescriptions (STOPP) v1, American Geriatrics Society (AGS) Beers Criteria® 2012, and relevant Assessing Care of Vulnerable Elders (ACOVE) v3 indicators. Potential prescribing omissions were assessed using the Screening Tool to Alert Doctors to the Right Treatment (START) v1 and ACOVE v3 indicators. Their agreement was assessed via κ statistics, and multivariate regression was used to assess relationships with emergency department visits, general practitioner (GP) visits, quality of life, and functional decline (increased assistance needed for activities of daily living).

RESULTS

There was slight agreement between STOPP and AGS Beers Criteria® (κ = 0.20) and ACOVE indicators (κ = 0.15), while agreement between AGS Beers Criteria® and ACOVE indicators was fair (κ = 0.31). Agreement was fair between START and ACOVE indicators (κ = 0.34). All measures of inappropriate medications were significantly associated with increased GP visits. Only exposure to two or more START indicators was associated with reduced quality of life (adjusted mean difference = -1.12; 95% confidence interval [CI] = -1.92 to -0.33), and only two or more AGS Beers Criteria® were associated with functional decline (adjusted odds ratio = 2.11; 95% CI = 1.37-3.28). For omissions, both measures were associated with functional decline, but only ACOVE indicators were associated with increased GP visits.

CONCLUSION

Prevalence of PIP and relationships with outcomes can differ substantially between tools with little agreement. Choice of PIP measure for research or practice should be considered in light of the circumstances and requirements in each case. J Am Geriatr Soc 68:526-534, 2020.

Risk scores identifying elderly inpatients at risk of 30-day unplanned readmission and accident and emergency department visit: a systematic review

OBJECTIVES

The aim of this systematic review was to describe and analyse the performance statistics of validated risk scores identifying elderly inpatients at risk of early unplanned readmission.

DATA SOURCES

We identified potentially eligible studies by searching MEDLINE, EMBASE, COCHRANE and Web of Science. Our search was restricted to original studies, between 1966 and 2018.

ELIGIBILITY CRITERIA

Original studies, which internally or externally validated the clinical scores of hospital readmissions in elderly inpatients.

DATA EXTRACTION AND SYNTHESIS

A data extraction grid based on Strengthening the Reporting of Observational Studies in Epidemiology and Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis statements was developed and completed by two reviewers to collect general data. The same process was used to extract metrological data of the selected scores.

QUALITY ASSESSMENT OF THE INCLUDED STUDIES

Assessment of the quality and risk of bias in individual studies was performed by two reviewers, using the validated Effective Public Health Practice Project quality assessment tool.

PARTICIPANTS

Elderly inpatients discharged to home from hospital or returning home after an accident and emergency department visit.

RESULTS

A total of 12 studies and five different scores were included in the review. The five scores present area under the receiving operating characteristic curve between 0.445 and 0.69. Identification of Senior At Risk (ISAR) and Triage  Risk Screening Tool (TRST) scores were the more frequently validated scores with ISAR being more sensitive and TRST more specific.

CONCLUSIONS

The TRST and ISAR scores have been extensively studied and validated. The choice of the most suitable score relies on available patient data, patient characteristics and the foreseen clinical care intervention. In order to pair the intervention with the appropriate clinical score, further studies of external validation of clinical scores, identifying elderly patients at risk of early unplanned readmission, are needed.

PROSPERO REGISTRATION NUMBER

CRD42017054516.

Do the 2015 Beers Criteria predict medication-related harm in older adults? Analysis from a multicentre prospective study in the United Kingdom

PURPOSE

To investigate whether inappropriate prescribing, defined by the Beers Criteria, is associated with medication-related harm (MRH), hospital admission, and mortality in older adults in England.

METHODS

A multicentre, prospective cohort study recruited 1280 patients (median age 82 years) at hospital discharge. Patients were followed-up in the community by pharmacists for 8 weeks to identify MRH (harm from adverse drug reactions, non-adherence, and medication errors) and hospital admissions. One-year mortality was determined using hospital records. Potentially inappropriate medications (PIMs) were determined using the 2015 version of the Beers criteria. Logistic regression was used to investigate the relationship between patients prescribed PIMs and adverse outcomes.

RESULTS

Two hundred and seventy-six patients (22%) were prescribed one or more PIMs at hospital discharge. The main PIM classes prescribed at hospital discharge were benzodiazepines and related drugs (30%) and antidepressants (27%). 1116 out of 1280 patients completed follow-up and 413 (37%) experienced MRH. In 51 cases (12%), MRH was attributable to a PIM. There was no significant relationship between patients prescribed PIMs and overall MRH, hospital readmission or all-cause one-year mortality. Multiple PIMs at discharge was independently associated with an increased risk of ADR (OR 2.32, 95% CI 1.03-5.23).

CONCLUSION

The prescribing of PIMs is common at hospital discharge of older adults in England. The 2015 Beers criteria have a limited clinical value to predict adverse outcomes following hospital discharge in this setting.

Development of a predictive score for potentially avoidable hospital readmissions for general internal medicine patients

BACKGROUND

Identifying patients at high risk of hospital preventable readmission is an essential step towards selecting those who might benefit from specific transitional interventions.

OBJECTIVE

Derive and validate a predictive risk score for potentially avoidable readmission (PAR) based on analysis of readmissions, with a focus on medication.

DESIGN/SETTING/PARTICIPANTS

Retrospective analysis of all hospital admissions to internal medicine wards between 2011 and 2014. Comparison between patients readmitted within 30 days and non-readmitted patients, as identified using a specially designed algorithm. Univariate and multivariate regression analyses of demographic data, clinical diagnoses, laboratory results, and the medication data of patients admitted during the first period (2011-2013), to identify factors associated with PAR. Using these, derive a predictive score with a regression coefficient-based scoring method. Subsequently, validate this score with a second cohort of patients admitted in 2013-2014. Variables were identified at hospital discharge.

RESULTS

The derivation cohort included 7,317 hospital stays. Multivariate logistic regressions found significant associations with PAR for: [adjusted OR (95% CI)] hospital length of stay > 4 days [1.3 (1.1-1.7)], admission in previous 6 months [2.3 (1.9-2.8)], heart failure [1.3 (1.0-1.7)], chronic ischemic heart disease [1.7 (1.2-2.3)], diabetes with organ damage [2.2 (1.3-3.8)], cancer [1.4 (1.0-1.9)], metastatic carcinoma [1.9 (1.3-3.0)], anemia [1.2 (1.0-1.5)], hypertension [1.3 (1.1-1.7)], arrhythmia [1.3 (1.0-1.6)], hyperkalemia [1.4 (1.0-1.7)], opioid drug prescription [1.3 (1.1-1.6)], and acute myocardial infarction [0.6 (0.4-0.9)]. The PAR-Risk Score, derived from these results, demonstrated fair discriminatory and calibration power (C-statistic = 0.699; Brier Score = 0.069). The results for the validation cohort's operating characteristics were similar (C-statistic = 0.687; Brier Score = 0.064).

CONCLUSION

This study identified routinely-available factors that were significantly associated with PAR. A predictive score was derived and internally validated.

Hospital Discharge Decisions Concerning Older Patients: Understanding the Underlying Process

ABSTRACTWe aimed to understand clinical decision-making processes that influence the orientation of older patients after hospital discharge. We compared discharge decisions (i.e., discharge home, or nursing home stay) of the hospital team with those of an expert panel. Both panel and hospital team made their decisions independently. The blind study included 102 patients (mean age: 83.13 ± 6.74). There is a statistically significant difference between expert and hospital team decisions (p &lt; .001; kappa coefficient: 0.468). Panel decisions were more closely associated with isolation (p = .018), reliable caregivers (p = .004), social problems (p = .001), and behavioural symptoms perceived as aggressive (p = .001). Both decision processes considered refusal of care (p = 0,025 and 0.016 respectively) and social problems (p = .001 and &lt; 0.001 respectively). Discharge planning models differ depending on the country, team and patient's condition. Our study suggests more precise evaluation of patients' needs.

Predictive models for hospital readmission risk: A systematic review of methods

OBJECTIVES

Hospital readmission risk prediction facilitates the identification of patients potentially at high risk so that resources can be used more efficiently in terms of cost-benefit. In this context, several models for readmission risk prediction have been proposed in recent years. The goal of this review is to give an overview of prediction models for hospital readmission, describe the data analysis methods and algorithms used for building the models, and synthesize their results.

METHODS

Studies that reported the predictive performance of a model for hospital readmission risk were included. We defined the scope of the review and accordingly built a search query to select the candidate papers. This query string was used as input for the chosen search engines, namely PubMed and Google Scholar. For each study, we recorded the population, feature selection method, classification algorithm, sample size, readmission threshold, readmission rate and predictive performance of the model.

RESULTS

We identified 77 studies that met the inclusion criteria, out of 265 citations. In 68% of the studies (n = 52) logistic regression or other regression techniques were utilized as the main method. Ten (13%) studies used survival analysis for model construction, while 14 (18%) used machine learning techniques for classification, of which decision tree-based methods and SVM were the most utilized algorithms. Among these, only four studies reported the use of any class imbalance addressing technique, of which resampling is the most frequent (75%). The performance of the models varied significantly among studies, with Area Under the ROC Curve (AUC) values in the ranges between 0.54 and 0.92.

CONCLUSION

Logistic regression and survival analysis have been traditionally the most widely used techniques for model building. Nevertheless, machine learning techniques are becoming increasingly popular in recent years. Recent comparative studies suggest that machine learning techniques can improve prediction ability over traditional statistical approaches. Regardless, the lack of an appropriate benchmark dataset of hospital readmissions makes a comparison of models' performance across different studies difficult.

The Effect of Computerized Physician Order Entry Template Modifications on the Administration of High-Risk Medications in Older Adults in the Emergency Department

BACKGROUND

Older adults are more susceptible to adverse events when administered certain medications at doses appropriate for younger adults.

OBJECTIVE

The aim of this study was to investigate the effect of default geriatric dosing on computerized physician order entry (CPOE) templates on the subsequent administration of recommended starting doses of opioids, benzodiazepines (BZDs) and non-steroidal anti-inflammatory drugs (NSAIDs) to older adults in the emergency department (ED).

METHODS

This was a before-after comparison of the frequency of the recommended starting doses of high-risk medications to adults aged 65 years and older. Computerized records were queried for the administration of the above medication classes in two academic EDs over two similar 4-month periods in 2015 and 2016. Between study periods, the doses of high-risk medications on ED CPOE templates were adjusted for older adults based on established pharmacy guidelines and expert consensus.

RESULTS

There was a significant improvement in the rate of recommended dose administration of all medications of interest (27.3 vs. 32.5%, p < 0.001). Not surprisingly, the medications that were maximally impacted were also those most frequently prescribed, with a significant increase in the recommended dosing of opioids (29.0 vs. 35.2%, p < 0.001) accounting for the majority of the change. Although there were no differences in BZDs as a group, there were significant differences in selected BZDs such as midazolam and diazepam. Changes in the recommended dosing of NSAIDs could not be determined due to low numbers of administered doses in both phases of the study.

CONCLUSION

Simple changes in the CPOE template resulted in increased administration of the recommended starting doses of high-risk medications to older adults in the ED.

Iatrogenic risk factors associated with hospital readmission of elderly patients: A matched case-control study using a clinical data warehouse

WHAT IS KNOWN

Hospital readmission within 30 days of patient discharge has become a standard to judge the quality of hospitalizations. It is estimated that 14% of the elderly, people over 75 years old or those over 65 with comorbidities, are at risk of readmission, of which 23% are avoidable. It may be possible to identify elderly patients at risk of readmission and implement steps to reduce avoidable readmissions.

OBJECTIVE

The aim of this study was to identify iatrogenic risk factors for readmission. The secondary objective was to evaluate the rate of drug-related readmissions (DRRs) among all readmissions and compare it to the rate of readmissions for other reasons.

METHODS

We conducted a retrospective, matched, case-control study to identify non-demographic risk factors for avoidable readmission, specifically DRRs. The study included patients hospitalized between 1 September 2014 and 31 October 2015 in an 800-bed university hospital. We included patients aged 75 and over. Cases consisted of patients readmitted to the emergency department within 30 days of initial discharge. Controls did not return to the emergency department within 30 days. Cases and controls were matched on sex and age because they are known as readmissions risk factors. After comparison of the mean or percentage between cases and controls for each variable, we conducted a conditional logistic regression.

RESULTS

The risk factors identified were an emergency admission at the index hospitalization, returning home after discharge, a history of unplanned readmissions and prescription of nervous system drugs. Otherwise, 11.4% of the readmissions were DRRs, of which 30% were caused by an overdose of antihypertensive. The number of drugs at readmission was higher, and potentially inappropriate medications were more widely prescribed for DRRs than for readmissions for other reasons.

WHAT IS NEW AND CONCLUSION

In this matched case-control retrospective study, after controlling for gender and age, we identified the typical profile of elderly patients at risk of readmission. These patients had an unplanned admission at the index hospitalization and prescribed nervous system drugs at discharge from the index admission; they have a history of unplanned readmission within 30 days and return home after discharge.

Older adults and high-risk medication administration in the emergency department

BACKGROUND

Older adults are susceptible to adverse effects from opioids, nonsteroidal anti-inflammatory drugs (NSAIDs), and benzodiazepines (BZDs). We investigated factors associated with the administration of elevated doses of these medications of interest to older adults (≥65 years old) in the emergency department (ED).

PATIENTS AND METHODS

ED records were queried for the administration of medications of interest to older adults at two academic medical center EDs over a 6-month period. Frequency of recommended versus elevated ("High doses" were defined as doses that ranged between 1.5 and 3 times higher than the recommended starting doses; "very high doses" were defined as higher than high doses) starting doses of medications, as determined by geriatric pharmacy/medicine guidelines and expert consensus, was compared by age groups (65-69, 70-74, 75-79, 80-84, and ≥85 years), gender, and hospital.

RESULTS

There were 17896 visits representing 11374 unique patients >65 years of age (55.3% men, 44.7% women). A total of 3394 doses of medications of interest including 1678 high doses and 684 very high doses were administered to 1364 different patients. Administration of elevated doses of medications was more common than that of recommended doses. Focusing on opioids and BZDs, the 65-69-year age group was much more likely to receive very high doses (1481 and 412 doses, respectively) than the ≥85-year age groups (relative risk [RR] 5.52, 95% CI 2.56-11.90), mainly reflecting elevated opioid dosing (RR 8.28, 95% CI 3.69-18.57). Men were more likely than women to receive very high doses (RR 1.47, 95% CI 1.26-1.72), primarily due to BZDs (RR 2.12, 95% CI 2.07-2.16).

CONCLUSION

Administration of elevated doses of opioids and BZDs in the older population occurs frequently in the ED, especially to the 65-69-year age group and men. Further attention to potentially unsafe dosing of high-risk medications to older adults in the ED is warranted.

Early rehospitalizations of frail elderly patients - the role of medications: a clinical, prospective, observational trial

BACKGROUND AND OBJECTIVE

Early readmissions of frail elderly patients after an episode of hospital care are common and constitute a crucial patient safety outcome. Our purpose was to study the impact of medications on such early rehospitalizations.

PATIENTS AND METHODS

This is a clinical, prospective, observational study on rehospitalizations within 30 days after an acute hospital episode for frail patients over the age of 75 years. To identify adverse drug reactions (ADRs), underuse of evidence-based treatment and avoidability of rehospitalizations, the Naranjo score, the Hallas criteria and clinical judgment were used.

RESULTS

Of 390 evaluable patients, 96 (24.6%) were rehospitalized. The most frequent symptoms and conditions were dyspnea (n = 25) and worsened general condition (n = 18). The most frequent diagnoses were heart failure (n = 17) and pneumonia/acute bronchitis (n = 13). By logistic regression analysis, independent risk predictors for rehospitalization were heart failure (odds ratio [OR] = 1.8; 95% CI = 1.1-3.1) and anemia (OR = 2.3; 95% CI = 1.3-4.0). The number of rehospitalizations due to probable ADRs was 13, of which two were assessed as avoidable. The number of rehospitalizations probably due to underuse of evidence-based drug treatment was 19, all of which were assessed as avoidable. The number of rehospitalizations not due to ADRs or underuse of evidence-based drug treatment was 64, of which none was assessed as avoidable.

CONCLUSION

One out of four frail elderly patients discharged from hospital was rehospitalized within 1 month. Although ADRs constituted an important cause of rehospitalization, underuse of evidence-based drug treatment might be an even more frequent cause. Potentially avoidable rehospitalizations were more frequently associated with underuse of evidence-based drug treatment than with ADRs. Efforts to avoid ADRs in frail elderly patients must be balanced and combined with evidence-based drug therapy, which can benefit these patients.

Utility of models to predict 28-day or 30-day unplanned hospital readmissions: an updated systematic review

OBJECTIVE

To update previous systematic review of predictive models for 28-day or 30-day unplanned hospital readmissions.

DESIGN

Systematic review.

SETTING/DATA SOURCE

CINAHL, Embase, MEDLINE from 2011 to 2015.

PARTICIPANTS

All studies of 28-day and 30-day readmission predictive model.

OUTCOME MEASURES

Characteristics of the included studies, performance of the identified predictive models and key predictive variables included in the models.

RESULTS

Of 7310 records, a total of 60 studies with 73 unique predictive models met the inclusion criteria. The utilisation outcome of the models included all-cause readmissions, cardiovascular disease including pneumonia, medical conditions, surgical conditions and mental health condition-related readmissions. Overall, a wide-range C-statistic was reported in 56/60 studies (0.21-0.88). 11 of 13 predictive models for medical condition-related readmissions were found to have consistent moderate discrimination ability (C-statistic ≥0.7). Only two models were designed for the potentially preventable/avoidable readmissions and had C-statistic >0.8. The variables 'comorbidities', 'length of stay' and 'previous admissions' were frequently cited across 73 models. The variables 'laboratory tests' and 'medication' had more weight in the models for cardiovascular disease and medical condition-related readmissions.

CONCLUSIONS

The predictive models which focused on general medical condition-related unplanned hospital readmissions reported moderate discriminative ability. Two models for potentially preventable/avoidable readmissions showed high discriminative ability. This updated systematic review, however, found inconsistent performance across the included unique 73 risk predictive models. It is critical to define clearly the utilisation outcomes and the type of accessible data source before the selection of the predictive model. Rigorous validation of the predictive models with moderate-to-high discriminative ability is essential, especially for the two models for the potentially preventable/avoidable readmissions. Given the limited available evidence, the development of a predictive model specifically for paediatric 28-day all-cause, unplanned hospital readmissions is a high priority.

Potentially inappropriate prescribing according to STOPP and START and adverse outcomes in community-dwelling older people: a prospective cohort study

AIMS

This study aims to determine if potentially inappropriate prescribing (PIP) is associated with increased healthcare utilization, functional decline and reduced quality of life (QoL) in a community-dwelling older cohort.

METHOD

This prospective cohort study included participants aged ≥65 years from The Irish Longitudinal Study on Ageing (TILDA) with linked administrative pharmacy claims data who were followed up after 2 years. PIP was defined by the Screening Tool for Older Persons Prescriptions (STOPP) and Screening Tool to Alert doctors to Right Treatment (START). The association with number of emergency department (ED) visits and GP visits reported over 12 months was analyzed using multivariate negative binomial regression adjusting for confounders. Marginal structural models investigated the presence of time-dependent confounding.

RESULTS

Of participants followed up (n = 1753), PIP was detected in 57% by STOPP and 41.8% by START, 21.7% reported an ED visit and 96.1% visited a GP (median 4, IQR 2.5-6). Those with any STOPP criterion had higher rates of ED visits (adjusted incident rate ratio (IRR) 1.30, 95% confidence interval (CI) 1.02, 1.66) and GP visits (IRR 1.15, 95%CI 1.06, 1.24). Patients with two or more START criteria had significantly more ED visits (IRR 1.45, 95%CI 1.03, 2.04) and GP visits (IRR 1.13, 95%CI 1.01, 1.27) than people with no criteria. Adjusting for time-dependent confounding did not affect the findings.

CONCLUSIONS

Both STOPP and START were independently associated with increased healthcare utilization and START was also related to functional decline and QoL. Optimizing prescribing to reduce PIP may provide an improvement in patient outcomes.

The Use of Opioid Analgesics following Common Upper Extremity Surgical Procedures: A National, Population-Based Study

BACKGROUND

The misuse of opioid analgesics is a major public health concern, and guidelines regarding postoperative opioid use are sparse. The authors examined the use of opioids following outpatient upper extremity procedures to discern the variation by procedure type and patient factors.

METHODS

The authors studied opioid prescriptions among 296,452 adults older than 18 years who underwent carpal tunnel release, trigger finger release, cubital tunnel release, or thumb carpometacarpal arthroplasty from 2009 to 2013 using insurance claims drawn from the Truven Health MarketScan Commercial Claims and Encounters, which encompasses over 100 health plans in the United States. Using multivariable regression, the authors compared the receipt of opioids, number of days supplied, indicators of inappropriate prescriptions, and number of refills by patient factors.

RESULTS

In this cohort, 59 percent filled a postoperative prescription for opioid medication, and 8.8 percent of patients had an indicator of inappropriate prescribing. The probability of filling an opioid prescription declined linearly with advancing age. On multivariate analysis, patients who had previously received opioids were more likely to fill a postoperative opioid prescription (66 percent versus 59 percent), receive longer prescriptions (24 versus 5 days), receive refills following surgery (24 percent versus 5 percent), and have at least one indicator of potentially inappropriate prescribing (19 percent versus 6 percent).

CONCLUSIONS

Current opioid users are more likely to require postoperative opioid analgesics for routine procedures and more likely to receive inappropriate prescriptions. More evidence is needed to identify patients who derive the greatest benefit from opioids to curb opioid prescriptions when alternative analgesics may be equally effective and available.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.

The Use of Opioid Analgesics following Common Upper Extremity Surgical Procedures: A National, Population-Based Study

BACKGROUND

The misuse of opioid analgesics is a major public health concern, and guidelines regarding postoperative opioid use are sparse. The authors examined the use of opioids following outpatient upper extremity procedures to discern the variation by procedure type and patient factors.

METHODS

The authors studied opioid prescriptions among 296,452 adults older than 18 years who underwent carpal tunnel release, trigger finger release, cubital tunnel release, or thumb carpometacarpal arthroplasty from 2009 to 2013 using insurance claims drawn from the Truven Health MarketScan Commercial Claims and Encounters, which encompasses over 100 health plans in the United States. Using multivariable regression, the authors compared the receipt of opioids, number of days supplied, indicators of inappropriate prescriptions, and number of refills by patient factors.

RESULTS

In this cohort, 59 percent filled a postoperative prescription for opioid medication, and 8.8 percent of patients had an indicator of inappropriate prescribing. The probability of filling an opioid prescription declined linearly with advancing age. On multivariate analysis, patients who had previously received opioids were more likely to fill a postoperative opioid prescription (66 percent versus 59 percent), receive longer prescriptions (24 versus 5 days), receive refills following surgery (24 percent versus 5 percent), and have at least one indicator of potentially inappropriate prescribing (19 percent versus 6 percent).

CONCLUSIONS

Current opioid users are more likely to require postoperative opioid analgesics for routine procedures and more likely to receive inappropriate prescriptions. More evidence is needed to identify patients who derive the greatest benefit from opioids to curb opioid prescriptions when alternative analgesics may be equally effective and available.

CLINICAL QUESTION/LEVEL OF EVIDENCE

Risk, III.