30-Day Readmission Among Elderly Medicare Beneficiaries with Type 2 Diabetes

Digitally Enabled Transitional Care Management in Oncology

PURPOSE

Improving care transitions for patients with cancer discharged from the hospital is considered an important component of quality care. Digital monitoring has the potential to better the delivery of transitional care through improved patient-provider communication and enhanced symptom management. However, remote patient monitoring (RPM) interventions have not been widely implemented for oncology patients after discharge, an innovative setting in which to apply this technology.

METHODS

We implemented a RPM intervention which identifies medical oncology patients at discharge, monitors their symptoms for 10 days, and intervenes as necessary to manage symptoms. We evaluated the feasibility (>50% patient engagement with symptom assessment), appropriateness (symptom alerts), and acceptability (net promoter score >0.7) of the intervention and the initial effect on acute care visits and return on investment.

RESULTS

During the study period, January 1, 2021, to December 31, 2022, we evaluated 2,257 medical oncology discharges representing 1,857 unique patients. We found that 65.9% of patients discharged (N = 1,489) completed at least one symptom assessment postdischarge and of them, 45.5% (n = 678) generated a severe symptom alert that we helped to manage. Patients expressed high satisfaction with the intervention with a net promoter score of 84%. In preliminary analysis of patients with GI malignancies (n = 449), we found a nonsignificant decrease in 30-day readmissions for the intervention cohort (n = 269) by 5.8% as compared with the control (n = 180; from 33.3% to 27.5%; P = .22).

CONCLUSION

Digital transitional care management was feasible and demonstrated that patients transitioning from the hospital to home have a substantial symptom burden. The intervention was associated with high patient satisfaction but will require further refinement and evaluation to increase its impact on 30-day readmission.

Improvement of scoring system used before discharge to predict 30-day all-cause unplanned readmission in geriatric population: a prospective cohort study

BACKGROUND

Data taken from tertiary referral hospitals in Indonesia suggested readmission rate in older population ranging between 18.1 and 36.3%. Thus, it is crucial to identify high risk patients who were readmitted. Our previous study found several important predictors, despite unsatisfactory discrimination value.

METHODS

We aimed to investigate whether comprehensive geriatric assessment (CGA) -based modification to the published seven-point scoring system may increase the discrimination value. We conducted a prospective cohort study in July-September 2022 and recruited patients aged 60 years and older admitted to the non-surgical ward and intensive coronary care unit. The ROC curve was made based on the four variables included in the prior study. We conducted bivariate and multivariate analyses, and derived a new scoring system with its discrimination value.

RESULTS

Of 235 subjects, the incidence of readmission was 32.3% (95% CI 26-38%). We established a new scoring system consisting of 4 components. The scoring system had maximum score of 21 and incorporated malignancy (6 points), delirium (4 points), length of stay ≥ 10 days (4 points), and being at risk of malnutrition or malnourished (7 points), with a good calibration test. The C-statistic value was 0.835 (95% CI 0.781-0.880). The optimal cut-off point was ≥ 8 with a sensitivity of 90.8% and a specificity of 54.7%.

CONCLUSIONS

Malignancy, delirium, length of stay ≥ 10 days, and being at risk of malnutrition or malnourished are predictors for 30-day all-cause unplanned readmission. The sensitive scoring system is a strong model to identify whether an individual is at higher risk for readmission. The new CGA-based scoring system had higher discrimination value than that of the previous seven-point scoring system.

Consensus methodology to investigate the crucial referral criteria to pharmacist-led counseling clinics in Makkah City

Aim

Identifying and prioritizing criteria for referring patients to a counseling clinic managed by hospital pharmacists in the tertiary care setting in Saudi Arabia (SA).

Method

A two-phase consensus Delphi methodological approach was adopted in this study. Data was collected from physicians and pharmacists from different specialties working in different hospitals in Makkah City. In Phase 1, semi-structured interviews were conducted with physicians and pharmacists to discuss and develop the initial list of potential referral criteria for post-discharge counseling. Phase 2 consisted of two rounds of online surveys where participants were asked to independently rank the referral criteria using a 5-point Likert Scale.

Results

In Phase 1, four participants undertook the interviews (two physicians and two pharmacists). Overall, no major comments were given on the suggested criteria. In Phase 2, most suggested referral criteria to the counseling clinic reached participants' consensus agreement of >70 % in both rounds for all three domains. Among all criteria that achieved consensus agreement, two demographic criteria were top-ranked by the participants; the elderly patients (100 %) and those who needed help with their devices (96 %). These were followed by five medication-related criteria, which are medication-related problems, polypharmacy, medication that needs monitoring, high-risk medication, and medication with special formulations. All had a consensus agreement of 96 %.

Conclusion

This study suggests that a counseling clinic led by pharmacists is particularly advisable for the elderly, individuals requiring assistance with their devices, and those encountering medication issues. It is essential to prioritize specific patient demographics when contemplating the extensive establishment and integration of such clinics across various hospitals in SA.

Associations Between Postdischarge Care and Cognitive Impairment-Related Hospital Readmissions for Ketoacidosis and Severe Hypoglycemia in Adults With Diabetes

OBJECTIVE

Patients with severe hypoglycemia (SH) or diabetic ketoacidosis (DKA) experience high hospital readmission after being discharged. Cognitive impairment (CI) may further increase the risk, especially in those experiencing an interruption of medical care after discharge. This study examined the effect modification role of postdischarge care (PDC) on CI-associated readmission risk among U.S. adults with diabetes initially admitted for DKA or SH.

RESEARCH DESIGN AND METHODS

We used the Nationwide Readmissions Database (NRD) (2016-2018) to identify individuals hospitalized with a diagnosis of DKA or SH. Multivariate Cox regression was used to compare the all-cause readmission risk at 30 days between those with and without CI identified during the initial hospitalization. We assessed the CI-associated readmission risk in the patients with and without PDC, an effect modifier with the CI status.

RESULTS

We identified 23,775 SH patients (53.3% women, mean age 65.9 ± 15.3 years) and 140,490 DKA patients (45.8% women, mean age 40.3 ± 15.4 years), and 2,675 (11.2%) and 1,261 (0.9%), respectively, had a CI diagnosis during their index hospitalization. For SH and DKA patients discharged without PDC, CI was associated with a higher readmission risk of 23% (adjusted hazard ratio [aHR] 1.23, 95% confidence interval 1.08-1.40) and 35% (aHR 1.35, 95% confidence interval 1.08-1.70), respectively. However, when patients were discharged with PDC, we found PDC was an effect modifier to mitigate CI-associated readmission risk for both SH and DKA patients (P < 0.05 for all).

CONCLUSIONS

Our results suggest that PDC can potentially mitigate the excessive readmission risk associated with CI, emphasizing the importance of postdischarge continuity of care for medically complex patients with comorbid diabetes and CI.

Multimorbidity and prior falls correlate with risk of 30-day hospital readmission in aged 80+: A prospective cohort study

BACKGROUND/PURPOSE

Thirty-day hospital readmission rate significantly raised with advanced age. The performance of existing predictive models for readmission risk remained uncertain in the oldest population. We aimed to examine the effect of geriatric conditions and multimorbidity on readmission risk among older adults aged 80 and over.

METHODS

This prospective cohort study enrolled patients aged 80 and older discharged from a geriatric ward at a tertiary hospital, with phone follow-up for 12 months. Demographics, multimorbidity, and geriatric conditions were assessed before hospital discharge. Logistic regression models were conducted to analyse risk factors for 30-day readmission.

RESULTS

Patients readmitted had higher Charlson comorbidity index scores, and were more likely to have falls, frailty, and longer hospital stay, compared to those without 30-day readmission. Multivariate analysis revealed that higher Charlson comorbidity index score was associated with readmission risk. Older patients with a fall history within 12 months had a near 4-fold increase in readmission risk. Severe frailty status before index admission was associated with a higher 30-day readmission risk. Functional status at discharge was not associated with readmission risk.

CONCLUSION

In addition to multimorbidity, history of falls and frailty were associated with higher hospital readmission risk in the oldest.

Rates and predictors of 30-day hospital readmissions in adults for drug-induced acute pancreatitis: A retrospective study from the United States National Readmission Database

BACKGROUND AND AIM

Drug-induced acute pancreatitis (DIAP) linked to several medications is a diagnosis of exclusion and is associated with significant morbidity and mortality, contributing to the US healthcare cost burden. Existing studies on DIAP focus on the drug classes that can cause acute pancreatitis. Hence, our retrospective study aims to determine the rates and predictors for 30-day readmissions (30-DR) in patients with index hospitalization for DIAP.

METHODS

From the Nationwide Readmissions Database, we followed adults admitted for DIAP who were discharged alive for 30 days. During 30-DR, we evaluated the rates, predictors, and outcomes of DIAP.

RESULTS

Of the 4457 DIAP patients surviving at discharge, 12.5% were readmitted at 30 days. During readmissions, the predictors of 30-DR for DIAP were young age, the Charlson-Deyo Comorbidity Index of 2 and 3, protein-energy malnutrition, and dyslipidemia. During 30-DR, DIAP had a higher mortality rate (2.4% vs. 0.7%; P < 0.020), extended hospital stays (5.6 days vs. 4 days, 0.000), and higher hospital charges ($12 983.6 vs. $8 255.6; P 0.000).

CONCLUSIONS

DIAP has high 30-DR rates and poorer outcomes.

Development and validation of predictive model for long-term hospitalization, readmission, and in-hospital death of patients over 60 years old

Objective

To develop and validate a high-risk predictive model that identifies, at least, one common adverse event in older population: early readmission (up to 30 days after discharge), long hospital stays (10 days or more) or in-hospital deaths.

Methods

This was a retrospective cohort study including patients aged 60 years or older (n=340) admitted at a 630-beds tertiary hospital, located in the city of São Paulo, Brazil. A predictive model of high-risk indication was developed by analyzing logistical regression models. This model prognostic capacity was assessed by measuring accuracy, sensitivity, specificity, and positive and negative predictive values. Areas under the receiver operating characteristic curve with 95% confidence intervals were also obtained to assess the discriminatory power of the model. Internal validation of the prognostic model was performed in a separate sample (n=168).

Results

Statistically significant predictors were identified, such as current Barthel Index, number of medications in use, presence of diabetes mellitus, difficulty chewing or swallowing, extensive surgery, and dementia. The study observed discrimination model acceptance in the construction sample 0.77 (95% confidence interval: 0.71-0.83) and good calibration. The characteristics of the validation samples were similar, and the receiver operating characteristic curve area was 0.687 (95% confidence interval: 0.598-0.776). We could assess an older patient’s adverse health events during hospitalization after admission.

Conclusion

A predictive model with acceptable discrimination was obtained, with satisfactory results for early readmission (30 days), long hospital stays (10 days), or in-hospital death.

Sex differences in glycemic measures, complications, discharge disposition, and postdischarge emergency room visits and readmission among non-critically ill, hospitalized patients with diabetes

INTRODUCTION

The purpose of this prospective observational cohort study was to examine sex differences in glycemic measures, diabetes-related complications, and rates of postdischarge emergency room (ER) visits and hospital readmissions in non-critically ill, hospitalized patients with diabetes.

RESEARCH DESIGN AND METHODS

Demographic data including age, body mass index, race, blood pressure, reason for admission, diabetes medications at admission and discharge, diabetes-related complications, laboratory data (hematocrit, creatinine, hemoglobin A1c, point-of-care blood glucose measures), length of stay (LOS), and discharge disposition were collected. Patients were followed for 90 days following hospital discharge to obtain information regarding ER visits and readmissions.

RESULTS

120 men and 100 women consented to participate in this study. There were no sex differences in patient demographics, diabetes duration or complications, or LOS. No differences were observed in the percentage of men and women with an ER visit or hospital readmission within 30 (39% vs 33%, p=0.40) or 90 (60% vs 49%, p=0.12) days of hospital discharge. More men than women experienced hypoglycemia prior to discharge (18% vs 8%, p=0.026). More women were discharged to skilled nursing facilities (p=0.007).

CONCLUSIONS

This study demonstrates that men and women hospitalized with an underlying diagnosis of diabetes have similar preadmission glycemic measures, diabetes duration, and prevalence of diabetes complications. More men experienced hypoglycemia prior to discharge. Women were less likely to be discharged to home. Approximately 50% of men and women had ER visits or readmissions within 90 days of hospital discharge.

TRIAL REGISTRATION NUMBER

NCT03279627.

Exploration of risk factors for high-risk adverse events in elderly patients after discharge and comparison of discharge planning screening tools

OBJECTIVES

Discharge planning is an effective strategy to prevent adverse health events and reduce medical expenditures. The high-risk target populations of discharged elderly patients and important predictors for the occurrence of adverse events are still not clear. Therefore, the purposes of this study were to examine the validity of discharge planning screening tools in sufficiently identifying high-risk adverse events to health after discharge and to compare two screening tools with our study model.

DESIGN

We conducted a prospective study and recruited elderly patients who had had no hospitalization within 3 months before admission to 13 general wards of a medical center in northern Taiwan from November 2018 to May 2020.

METHODS

Elderly patients were randomly selected during the study period. Within 24 h of admission, patients were asked to consent to join this study. After the patient was discharged, the patient's health and hospitalization for the next year were tracked by telephone interviews.

RESULTS

In total, 300 participants were recruited for this study. Incidences of high-risk adverse events within 30 days, 60 days, and 12 months after discharge were 20.3%, 25.7%, and 48.7% respectively. A logistic regression showed that an increased age, physical or mental disabilities or a major illness, a low body-mass index, and having been hospitalized in the past year were significantly related to the occurrence of high-risk events among elderly discharge patients. The pooled sensitivity of the P_ra was 52% and the specificity was 72%; the pooled sensitivity of the LACE index was 67% and the specificity was 36%. The predictive model of this study had a higher discriminatory power than the P_ra and LACE index for high-risk events after discharge.

CONCLUSIONS

Elderly patients are more vulnerable to high-risk adverse events after discharge. Both the LACE index and P_ra are useful discharge planning screening tools to screen for high-risk adverse events after discharge. Elderly patients need more-active and complete continuity of care plans and discharge planning services to ensure that the overall quality of patient care can be improved and readmissions and mortality reduced.

CLINICAL RELEVANCE

The findings of this study can provide information for discharge planning managers to identify high-risk elderly patients during hospitalization and promptly offer care education or resources to improve care management.

Timing of Home Health Care Initiation and 30-Day Rehospitalizations among Medicare Beneficiaries with Diabetes by Race and Ethnicity

Older adults with diabetes are at elevated risk of complications following hospitalization. Home health care services mitigate the risk of adverse events and facilitate a safe transition home. In the United States, when home health care services are prescribed, federal guidelines require they begin within two days of hospital discharge. This study examined the association between timing of home health care initiation and 30-day rehospitalization outcomes in a cohort of 786,734 Medicare beneficiaries following a diabetes-related index hospitalization admission during 2015. Of these patients, 26.6% were discharged to home health care. To evaluate the association between timing of home health care initiation and 30-day rehospitalizations, multivariate logistic regression models including patient demographics, clinical and geographic variables, and neighborhood socioeconomic variables were used. Inverse probability-weighted propensity scores were incorporated into the analysis to account for potential confounding between the timing of home health care initiation and the outcome in the cohort. Compared to the patients who received home health care within the recommended first two days, the patients who received delayed services (3-7 days after discharge) had higher odds of rehospitalization (OR, 1.28; 95% CI, 1.25-1.32). Among the patients who received late services (8-14 days after discharge), the odds of rehospitalization were four times greater than among the patients receiving services within two days (OR, 4.12; 95% CI, 3.97-4.28). Timely initiation of home health care following diabetes-related hospitalizations is one strategy to improve outcomes.

Association between glycosylated haemoglobin and outcomes for patients discharged from hospital with diabetes: A health informatics approach

Aims/Objectives

Extensive research considers associations between inpatient glycaemic control and outcomes during hospital admission; this cautions against overly tight glycaemic targets. Little research considers glycaemic control following hospital discharge. This is despite a clear understanding that people with diabetes are at increased risk of negative outcomes, following discharge. We evaluate absolute and relative Hba1c values, and frequency of Hba1c monitoring, on readmission and mortality rates for people discharged from hospital with diabetes.

Methods

All discharges (n = 46,357) with diabetes from a major tertiary referral centre over 3 years were extracted, including biochemistry data. We conducted an evaluation of association between Hba1c, mortality and readmission, statistical significance and standardised Cohen's D effect size calculations.

Results

399 patients had a Hba1c performed during their admission. 3,138 patients had a Hba1c within 1 year of discharge. Mean average Hba1c for readmissions was 57.82 vs 60.39 for not readmitted (p = 0.009, Cohen's D 0.28). Mean average number of days to Hba1c testing in readmitted was 97 vs 113 for those not readmitted (p = 0.00006, Cohen's D 0.39). Further evaluation of mortality outcomes, cohorts of T1DM and T2DM and association of relative change in Hba1c was performed.

Conclusions

Lower Hba1c values following discharge from hospital are significantly associated with increased risk of readmission, as is a shorter duration until testing. Similar patterns observed for mortality. Findings particularly prominent for T1DM. Further research needed to consider underlying causation and design of appropriate risk stratification models.

Flash CGM Is Associated With Reduced Diabetes Events and Hospitalizations in Insulin-Treated Type 2 Diabetes

Purpose

Suboptimal glycemic control among individuals with diabetes is a leading cause of hospitalizations and emergency department utilization. Use of flash continuous glucose monitoring (flash CGM) improves glycemic control in type 1 and type 2 diabetes, which may result in lower risk for acute and chronic complications that require emergency services and/or hospitalizations.

Methods

In this retrospective, real-world study, we analyzed IBM MarketScan Commercial Claims and Medicare Supplemental databases to assess the impact of flash CGM on diabetes-related events and hospitalizations in a cohort of 2463 individuals with type 2 diabetes who were on short- or rapid-acting insulin therapy. Outcomes were changes in acute diabetes-related events (ADE) and all-cause inpatient hospitalizations (ACH), occurring during the first 6 months after acquiring the flash CGM system compared with event rates during the 6 months prior to system acquisition. ICD-10 codes were used to identify ADE for hypoglycemia, hypoglycemic coma, hyperglycemia, diabetic ketoacidosis, and hyperosmolarity.

Results

ADE rates decreased from 0.180 to 0.072 events/patient-year (hazard ratio [HR]: 0.39 [0.30, 0.51]; P < 0.001) and ACH rates decreased from 0.420 to 0.283 events/patient-year (HR: 0.68 [0.59 0.78]; P < 0.001). ADE reduction occurred regardless of age or gender.

Conclusions

Acquisition of the flash CGM system was associated with reductions in ADE and ACH. These findings provide support for the use of flash CGM in type 2 diabetes patients treated with short- or rapid-acting insulin therapy to improve clinical outcomes and potentially reduce costs.

Common sampling and modeling approaches to analyzing readmission risk that ignore clustering produce misleading results

Background

There is little consensus on how to sample hospitalizations and analyze multiple variables to model readmission risk. The purpose of this study was to compare readmission rates and the accuracy of predictive models based on different sampling and multivariable modeling approaches.

Methods

We conducted a retrospective cohort study of 17,284 adult diabetes patients with 44,203 discharges from an urban academic medical center between 1/1/2004 and 12/31/2012. Models for all-cause 30-day readmission were developed by four strategies: logistic regression using the first discharge per patient (LR-first), logistic regression using all discharges (LR-all), generalized estimating equations (GEE) using all discharges, and cluster-weighted (CWGEE) using all discharges. Multiple sets of models were developed and internally validated across a range of sample sizes.

Results

The readmission rate was 10.2% among first discharges and 20.3% among all discharges, revealing that sampling only first discharges underestimates a population’s readmission rate. Number of discharges was highly correlated with number of readmissions (r = 0.87, P < 0.001). Accounting for clustering with GEE and CWGEE yielded more conservative estimates of model performance than LR-all. LR-first produced falsely optimistic Brier scores. Model performance was unstable below samples of 6000–8000 discharges and stable in larger samples. GEE and CWGEE performed better in larger samples than in smaller samples.

Conclusions

Hospital readmission risk models should be based on all discharges as opposed to just the first discharge per patient and utilize methods that account for clustered data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-020-01162-0.

The Early Impact of the Centers for Medicare & Medicaid Services State Innovation Models Initiative on 30-Day Hospital Readmissions Among Adults With Diabetes

BACKGROUND

The Centers for Medicare & Medicaid Services (CMS) State Innovation Models (SIM) Initiative funds states to accelerate delivery system and payment reforms. All SIM states focus on improving diabetes care, but SIM's effect on 30-day readmissions among adults with diabetes remains unclear.

METHODS

A quasi-experimental research design estimated the impact of SIM on 30-day hospital readmissions among adults with diabetes in 3 round 1 SIM states (N=671,996) and 3 comparison states (N=2,719,603) from 2010 to 2015. Difference-in-differences multivariable logistic regression models that incorporated 4-group propensity score weighting were estimated. Heterogeneity of SIM effects by grantee state and for CMS populations were assessed.

RESULTS

In adjusted difference-in-difference analyses, SIM was associated with an increase in odds of 30-day hospital readmission among patients in SIM states in the post-SIM versus pre-SIM period relative to the ratio in odds of readmission among patients in the comparison states post-SIM versus pre-SIM (ratio of adjusted odds ratio=1.057, P=0.01). Restricting the analyses to CMS populations (Medicare and Medicaid beneficiaries), resulted in consistent findings (ratio of adjusted odds ratio=1.057, P=0.034). SIM did not have different effects on 30-day readmissions by state.

CONCLUSIONS

We found no evidence that SIM reduced 30-day readmission rates among adults with diabetes during the first 2 years of round 1 implementation, even among CMS beneficiaries. It may be difficult to reduce readmissions statewide without greater investment in health information exchange and more intensive use of payment models that promote interorganizational coordination.

Predictors of 30-day unplanned hospital readmission among adult patients with diabetes mellitus: a systematic review with meta-analysis

Adult patients with diabetes mellitus (DM) represent one-fifth of all 30-day unplanned hospital readmissions but some may be preventable through continuity of care with better DM self-management. We aim to synthesize evidence concerning the association between 30-day unplanned hospital readmission and patient-related factors, insurance status, treatment and comorbidities in adult patients with DM. We searched full-text English language articles in three electronic databases (MEDLINE, Embase and CINAHL) without confining to a particular publication period or geographical area. Prospective and retrospective cohort and case-control studies which identified significant risk factors of 30-day unplanned hospital readmission were included, while interventional studies were excluded. The study participants were aged ≥18 years with either type 1 or 2 DM. The random effects model was used to quantify the overall effect of each factor. Twenty-three studies published between 1998 and 2018 met the selection criteria and 18 provided information for the meta-analysis. The data were collected within a period ranging from 1 to 15 years. Although patient-related factors such as age, gender and race were identified, comorbidities such as heart failure (OR=1.81, 95% CI 1.67 to 1.96) and renal disease (OR=1.69, 95% CI 1.34 to 2.12), as well as insulin therapy (OR=1.45, 95% CI 1.24 to 1.71) and insurance status (OR=1.41, 95% CI 1.22 to 1.63) were stronger predictors of 30-day unplanned hospital readmission. The findings may be used to target DM self-management education at vulnerable groups based on comorbidities, insurance type, and insulin therapy.

A randomized clinical trial of a collaborative home-based diabetes intervention to reduce emergency department visits and hospitalizations in black individuals with diabetes

The prevalence of diabetes mellitus (DM) in black individuals (blacks) is twice that of white individuals (whites), and blacks are more likely to have worse glycemic control, less optimal medication regimens, and higher levels of mistrust in the medical system. These three factors account for higher rates of acute medical care use in blacks with DM. To address this disparity, we developed DM I-TEAM (Diabetes Interprofessional Team to Enhance Adherence to Medical Care), a home-based multidisciplinary behavioral intervention that integrates care from a community health worker (CHW), the participant's primary care physician (PCP), a DM nurse educator, and a clinical pharmacist. Treatment is delivered during 9 sessions over 1 year, and includes diabetes education and goal setting, telehealth visits with participants' PCP and a DM nurse educator, and comprehensive medication reviews by a pharmacist. We describe the rationale and methods for a randomized controlled trial to test the efficacy of DM I-TEAM to reduce emergency department (ED) visits and hospitalizations. We are enrolling 200 blacks with DM during an ED visit. Participants are randomized to DM I-TEAM or Usual Medical Care (UMC). Follow-up assessments are conducted at 6 and 12 months. The primary outcome is the number of ED visits and hospitalizations over 12 months, and is measured by participant self-report and medical record review. Secondary outcomes include hemoglobin A1c (HbA1c), number of potentially inappropriate medications (PIMs), and trust in health care.

Intelligent therapeutic decision support for 30 days readmission of diabetic patients with different comorbidities

The significance of medication therapy in managing comorbid diabetes is vital for maintaining the overall wellness of patients and reducing the cost of healthcare. Thus, using appropriate medication or medication combinations will be necessary for improved person-centred care and reduce complications associated with diagnosis and treatment. This study explains an intelligent decision support framework for managing 30 days unplanned readmission (30_URD) of comorbid diabetes using the Random Forest (RF) algorithm and Bayesian Network (BN) model. After the analysis of the medical records of 101,756 de-identified diabetic patients treated with 21 medications for 28 comorbidity combinations, the optimal medications for minimizing the likelihood of early readmissions were determined. This approach can help for identifying and managing most vulnerable patients thereby giving room to enhance post-discharge monitoring through clinical specialist supports to build critical-self management skills that will minimize the cost of diabetes care.

Readmission of older acutely admitted medical patients after short-term admissions in Denmark: a nationwide cohort study

Background

Knowledge of unplanned readmission rates and prognostic factors for readmission among older people after early discharge from emergency departments is sparse. The aims of this study were to examine the unplanned readmission rate among older patients after short-term admission, and to examine risk factors for readmission including demographic factors, comorbidity and admission diagnoses.

Methods

This cohort study included all medical patients aged ≥65 years acutely admitted to Danish hospitals between 1 January 2013 and 30 June 2014 and surviving a hospital stay of ≤24 h. Data on readmission within 30 days, comorbidity, demographic factors, discharge diagnoses and mortality were obtained from the Danish National Registry of Patients and the Danish Civil Registration System. We examined risk factors for readmission using a multivariable Cox regression to estimate adjusted hazard ratios (aHR) with 95% confidence intervals (CI) for readmission.

Results

A total of 93,306 patients with a median age of 75 years were acutely admitted and discharged within 24 h, and 18,958 (20.3%; 95% CI 20.1 - 20.6%) were readmitted with a median time to readmission of 8 days (IQR 3 - 16 days). The majority were readmitted with a new diagnosis. Male sex (aHR 1.15; 1.11 - 1.18) and a Charlson Comorbidity Index ≥3 (aHR 2.28; 2.20 - 2.37) were associated with an increased risk of readmission. Discharge diagnoses associated with increased risk of readmission were heart failure (aHR 1.26; 1.12 - 1.41), chronic obstructive pulmonary disease (aHR 1.33; 1.25 - 1.43), dehydration (aHR 1.28; 1.17 - 1.39), constipation (aHR 1.26; 1.14 - 1.39), anemia (aHR 1.45; 1.38 - 1.54), pneumonia (aHR 1.15; 1.06 - 1.25), urinary tract infection (aHR 1.15; 1.07 - 1.24), suspicion of malignancy (aHR 1.51; 1.37 - 1.66), fever (aHR 1.52; 1.33 - 1.73) and abdominal pain (aHR 1.12; 1.05 - 1.19).

Conclusions

One fifth of acutely admitted medical patients aged ≥65 were readmitted within 30 days after early discharge. Male gender, the burden of comorbidity and several primary discharge diagnoses were risk factors for readmission.

Patient-Reported Quality of Hospital Discharge Transitions: Results from the SILVER-AMI Study

BACKGROUND

Transitions from hospital to home in older patients are a high-risk period for adverse outcomes in a population that may have more challenges navigating the healthcare system. There is little information about the association of patient-reported quality of hospital discharge processes with clinical outcomes.

OBJECTIVES

We evaluated whether patient-reported quality of hospital discharge processes was associated with emergency department utilization and rehospitalization within 30 days of discharge after hospitalization for acute myocardial infarction (AMI) in older adults.

DESIGN

Multi-center, prospective cohort study.

PATIENTS

The ComprehenSIVe Evaluation of Risk Factors in Older Patients with Acute Myocardial Infarction (SILVER-AMI) study was a longitudinal study of 3006 adults age 75 and older hospitalized with AMI recruited from 94 academic and community hospitals from across the USA.

INTERVENTION

N/A MAIN MEASURES: Patients answered a subset of questions from the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. Readmissions and emergency department utilization within 30 days of discharge were ascertained through medical record review.

KEY RESULTS

A total of 2132 patients were included in the study. Patients' median age was 81 years and the response rate to the survey of discharge quality was 87%. Patients who reported being asked about having the help they needed at home were significantly less likely to have emergency room utilization within 30 days of discharge in both the unadjusted (0.65, 95% CI 0.43-0.99) and adjusted (0.65, 95% CI 0.42-0.997) models, though there was no significant association with readmission.

CONCLUSION

Report of an assessment of help needed at home during hospitalization was associated with lower post-discharge emergency department utilization. Efforts to improve outcomes after hospital discharge in older patients may benefit from greater focus on assessing need of help at home.

Association between potentially inappropriate medications at discharge and unplanned readmissions among hospitalised elderly patients at a single centre in Japan: a prospective observational study

OBJECTIVE

To determine the prevalence of potentially inappropriate medication (PIM) use at admission and discharge among hospitalised elderly patients and evaluate the association between PIMs at discharge and unplanned readmission in Japan.

DESIGN

A prospective observational study conducted by using electronic medical records.

PARTICIPANTS

All consecutive patients aged 65 years or older who were admitted to the internal medicine ward were included. Patients who were electively admitted for diagnostic procedures were excluded.

MAIN OUTCOME MEASURES

The primary outcome was 30-day unplanned readmissions. The secondary outcome was the prevalence of any PIM use at admission and discharge. PIMs were defined based on the Beers Criteria. The association between any PIM use at discharge and the primary outcome was evaluated by using logistic regression.

RESULTS

Seven hundred thirty-nine eligible patients were included in this study. The median patient age was 82 years (IQR 74-88); 389 (52.6%) were women, and the median Charlson Comorbidity Index was 2 (IQR 0-3). The proportions of patients taking any PIMs at admission and discharge were 47.2% and 32.2%, respectively. Of all the patients, 39 (5.3%) were readmitted within 30 days after discharge for the index hospitalisation. The use of PIMs at discharge was not associated with an increased risk of 30-day readmission (OR 0.93; 95% CI 0.46 to 1.87). This result did not change after adjusting for patient age, sex, number of medications, duration of hospital stay and comorbidities (OR 0.78; 95% CI 0.36 to 1.66).

CONCLUSION

The prevalence of any PIM use at discharge was high among hospitalised elderly patients in a Japanese hospital. Although the use of PIMs at discharge was not associated with an increased risk of unplanned readmission, given a lack of power of this study due to a low event rate, further studies investigating this association are needed.

TRIAL REGISTRATION NUMBER

UMIN000027189.

The association between polypharmacy and adverse health consequences in elderly type 2 diabetes mellitus patients; a systematic review and meta-analysis

AIM

To summarize the existing literature concerning the association between polypharmacy and adverse health consequences in elderly patients with type 2 diabetes mellitus.

METHODS

We searched four literature databases (PubMed/Medline, ScienceDirect and Web of Science) through April 2019. We included all studies that addressed the association between polypharmacy and all-cause of mortality, glycemic control, macrovacular complications, hospitalization, potentially inappropriate medicines, drug-drug interactions and fall. A statistical program OpenMeta [Analyst] was used. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with a random effects model. I² statistics was performed to assess heterogeneity.

RESULTS

Out of sixteen studies, three studies were used for meta-analysis. A statistically significant association was found between polypharmacy and all-cause mortality (OR = 1.622, 95% CI (1.606-1.637) P < 0.001), and myocardial infarction (OR = 1.962, 95% CI (1.942-1.982), P < 0.001. Non-statistically significant association with evidence of moderate heterogeneity was found between polypharmacy and stroke (OR = 1.335; 95% CI (0.532-3.346), P = 0.538, I² = 45%), and hospitalization (OR = 1.723; 95% CI (0.983-3.021), P = 0.057, I² = 57%).

CONCLUSIONS

Pooled risk estimates reveal that polypharmacy is associated with increased all-cause mortality, macrovacular complications and hospitalization using categorical definitions. These findings assert the need for interventions that optimize the balance of benefits and harms in medicines prescribing.

Risk factors for readmission of inpatients with diabetes: A systematic review

AIM

We have limited understanding of which risk factors contribute to increased readmission rates amongst people discharged from hospital with diabetes. We aim to complete the first review of its kind, to identify, in a systematic way, known risk factors for hospital readmission amongst people with diabetes, in order to better understand this costly complication.

METHOD

The review was prospectively registered in the PROSPERO database. Risk factors were identified through systematic review of literature in PubMed, EMBASE & SCOPUS databases, performed independently by two authors prior to data extraction, with quality assessment and semi-quantitative synthesis according to PRISMA guidelines.

RESULTS

Eighty-three studies were selected for inclusion, predominantly from the United States, and utilising retrospective analysis of local or regional data sets. 76 distinct statistically significant risk factors were identified across 48 studies. The most commonly identified risk factors were; co-morbidity burden, age, race and insurance type. Few studies conducted power calculations; unstandardized effect sizes were calculated for the majority of statistically significant risk factors.

CONCLUSION

This review is important in assessing the current state of the literature and in supporting development of interventions to reduce readmission risk. Furthermore, it provides an important foundation for development of rigorous, pre-specified risk prediction models.

Integrative review: Patient safety among older people with diabetes in home care services

AIMS

To identify diabetes specific patient safety domains that need to be addressed to improve home care of older people; to assess research from primary studies to review evidence on patient safety in home care services for older people with diabetes.

DESIGN

An integrative review.

DATA SOURCES

Domains for patient safety in diabetes home care settings were identified by conducting two searches. We performed searches in: CINAHL, Medline, Embase, and Cochrane Library for the years 2000-2017.

REVIEW METHODS

The first search identified frameworks or models on patient safety in home care services published up to October 2017. The second search identified primary studies about older people with diabetes in the home care setting published between 2000-2017.

RESULTS

Data from the 21 articles populated and refined 13 predetermined domains of patient safety in diabetes home care. These were used to explore how the domains interact to either increase or reduce risk. The domains constitute a model of associations between aspects of diabetes home care and adverse events. The results highlight a knowledge gap in safety for older persons with diabetes, influenced by e.g. hypoglycaemia, falls, pain, foot ulcers, cognitive impairment, depression, and polypharmacy. Moreover, providers' inadequate diabetes-specific knowledge and assessment skills contribute to the risk of adverse events.

CONCLUSION

Older persons with diabetes in home care are at risk of adverse events due to their reduced ability to self-manage their condition, adverse medication effects, the family's ability to take responsibility or home care service's suboptimal approaches to diabetes care.

Improving Care Transitions for Hospitalized Veterans Discharged to Skilled Nursing Facilities: A Focus on Polypharmacy and Geriatric Syndromes

Geriatric syndromes and polypharmacy are common in older patients discharged to skilled nursing facilities (SNFs) and increase 30-day readmission risk. In a U.S.A. Department of Veterans Affairs (VA)-funded Quality Improvement study to improve care transitions from the VA hospital to area SNFs, Veterans (N = 134) were assessed for geriatric syndromes using standardized instruments as well as polypharmacy, defined as five or more medications. Warm handoffs were used to facilitate the transfer of this information. This paper describes the prevalence of geriatric syndromes, polypharmacy, and readmission rates. Veterans were prescribed an average of 14.7 medications at hospital discharge. Moreover, 75% of Veterans had more than two geriatric syndromes, some of which began during hospitalization. While this effort did not reduce 30-day readmissions, the high prevalence of geriatric syndromes and polypharmacy suggests that future efforts targeting these issues may be necessary to reduce readmissions among Veterans discharged to SNF.

Burden of Illness in Type 2 Diabetes Mellitus

An estimated 30.2 million Americans have diabetes, and this number is expected to increase based on trends over recent decades and compounded by an aging U.S.

POPULATION

As reviewed in this article, type 2 diabetes mellitus (T2DM) is associated with impaired health-related quality of life (HRQoL) and with a substantial socioeconomic burden. Compared with individuals without T2DM, those with T2DM have worse HRQoL, greater decrements in HRQoL over time, and possibly greater depressive symptomology. Diabetes-related complications and comorbidities (e.g., obesity and cardiovascular disease) are associated with worse HRQoL. Hypoglycemic episodes are associated with reduced HRQoL and greater levels of depression; they can also interfere with social and occupational activities. In turn, low HRQoL can be a driver for poor glycemic control. In 2012, the total estimated cost associated with diagnosed diabetes in the United States was $245 billion. Factors contributing to increased health care resource utilization and costs in patients with T2DM include medical comorbidities, diabetes-related complications, inadequate glycemic control, and hypoglycemic episodes. Readmission is a key driver of hospital-related costs and is more common among elderly patients with T2DM. Elderly patients with T2DM represent a particularly vulnerable population given that these patients may have varying degrees of physical and mental comorbidities that can increase their risk of hypoglycemia, falls, and depression. This review demonstrates that T2DM imposes a considerable burden on both the individual and society. Treatment strategies should consider the effects of treatment on HRQoL and on outcomes (e.g., complications and hypoglycemia) that affect both HRQoL and costs. Management strategies that maximize HRQoL while minimizing the risk of hypoglycemia and other treatment-related complications are particularly critical in the elderly.

DISCLOSURES

This supplement was funded by Novo Nordisk. Cannon reports speaker fees and owns stock in Novo Nordisk. Handelsman reports research grants from Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer Ingelheim, Grifols, Janssen, Lexicon, Merck, Novo Nordisk, Regeneron, and Sanofi; speaker fees from Amarin, Amgen, AstraZeneca, Boehringer Ingelheim-Lilly, Janssen, Merck, Novo Nordisk, Regeneron, and Sanofi; and has served in advisory capacity to Amarin, Amgen, AstraZeneca, Boehringer Ingelheim, Eisai, Intarcia, Janssen, Lilly, Merck, Merck-Pfizer, Novo Nordisk, Regeneron, and Sanofi. Heile reports speaker fees from and has served as advisor to Novo Nordisk. Shannon reports consultant and speaker fees from Novo Nordisk and Boehringer Ingelheim-Lilly Alliance.

Predischarge and Postdischarge Risk Factors for Hospital Readmission Among Patients With Diabetes

BACKGROUND

Hospital readmission within 30 days of discharge (30-d readmission) is an undesirable outcome. Readmission of patients with diabetes is common and costly. Most of the studies that have examined readmission risk factors among diabetes patients did not include potentially important clinical data.

OBJECTIVES

To provide a more comprehensive understanding of 30-day readmission risk factors among patients with diabetes based on predischarge and postdischarge data.

RESEARCH DESIGN

In this retrospective cohort study, 48 variables were evaluated for association with readmission by multivariable logistic regression.

SUBJECTS

In total, 17,284 adult diabetes patients with 44,203 hospital discharges from an urban academic medical center between January 1, 2004 and December 1, 2012.

MEASURES

The outcome was all-cause 30-day readmission. Model performance was assessed by c-statistic.

RESULTS

The 30-day readmission rate was 20.4%, and the median time to readmission was 11 days. A total of 27 factors were statistically significant and independently associated with 30-day readmission (P<0.05). The c-statistic was 0.82. The strongest risk factors were lack of a postdischarge outpatient visit within 30 days, hospital length-of-stay, prior discharge within 90 days, discharge against medical advice, sociodemographics, comorbidities, and admission laboratory values. A diagnosis of hypertension, preadmission sulfonylurea use, admission to an intensive care unit, sex, and age were not associated with readmission in univariate analysis.

CONCLUSIONS

There are numerous risk factors for 30-day readmission among patients with diabetes. Postdischarge factors add to the predictive accuracy achieved by predischarge factors. A better understanding of readmission risk may ultimately lead to lowering that risk.

Supporting Transitions in Care for Older Adults With Type 2 Diabetes Mellitus and Obesity

The aim of the current study was to compare outcomes for older adults with type 2 diabetes mellitus and obesity following participation in a transitional care intervention that included diabetes self-management education (DSME) and homecare. The three groups analyzed comprised an inpatient DSME plus homecare group (n = 35); an inpatient DSME only group (n = 100); and a group who received usual care (n = 45). Outcomes of interest included rehospitalization rates and hemoglobin A1C (A1C) for up to 1-year post hospital discharge. Rates of rehospitalization and A1C improved for older adults who received nurse-led inpatient DSME and homecare during transitions of care from hospital to home. Rehospitalization rates up to 90 days were decreased for the DSME plus homecare group (10%) compared to DSME only (20%) and usual care groups (26.7%) (p < 0.05). A decrease of -0.4 and -2.3 A1C units was observed for the DSME group and DSME plus homecare group, respectively, at 90 days. These results support a transitional care educational intervention for older adults with type 2 diabetes mellitus and obesity.

TARGETS

Older adults with type 2 diabetes mellitus and obesity.

INTERVENTION DESCRIPTION

Transitional care intervention including diabetes self-management education and homecare.

MECHANISMS OF ACTION

Inpatient diabetes education and homecare helps improve rates of rehospitalization and hemoglobin A1C during care transitions from hospital to home.

OUTCOMES

Rehospitalization rates, glycemic control (i.e., A1C level). [Res Gerontol Nurs. 2018; 11(2):71-81.].

Hospital Readmissions among Commercially Insured and Medicare Advantage Beneficiaries with Diabetes and the Impact of Severe Hypoglycemic and Hyperglycemic Events

BACKGROUND

Hospital readmission is common among patients with diabetes. Some readmissions, particularly for hypoglycemia and hyperglycemia, may be avoidable with better care transitions and post-discharge management.

OBJECTIVE

To ascertain the most common reasons and risk factors for readmission among adults with diabetes, with specific consideration of severe dysglycemia.

DESIGN

Retrospective analysis of data from the OptumLabs Data Warehouse, an administrative data set of commercially insured and Medicare Advantage beneficiaries across the U.S.

PARTICIPANTS

Adults ≥18 years of age with diabetes, discharged from a hospital between January 1, 2009, and December 31, 2014 (N = 342,186).

MAIN MEASURES

Principal diagnoses and risk factors for 30-day unplanned readmissions, subset as being for severe dysglycemia vs. all other causes.

KEY RESULTS

We analyzed 594,146 index hospitalizations among adults with diabetes: mean age 68.2 years (SD, 13.0), 52.9% female, and 67.8% white. The all-cause 30-day readmission rate was 10.8%. Heart failure was the most common cause for index hospitalization (5.5%) and readmission (8.9%). Severe dysglycemia accounted for 2.6% of index hospitalizations (48.1% hyperglycemia, 50.4% hypoglycemia, 1.5% unspecified) and 2.5% of readmissions (38.3% hyperglycemia, 61.0% hypoglycemia, 0.7% unspecified). Younger patient age, severe dysglycemia at index or prior hospitalization, and the Diabetes Complications Severity Index (DCSI) were the strongest risk factors predisposing patients to severe dysglycemia vs. other readmissions. Prior episodes of severe dysglycemia and the DCSI were also independent risk factors for other-cause readmissions, irrespective of the cause of the index hospitalization.

CONCLUSIONS

Adults with diabetes are hospitalized and readmitted for a wide range of health conditions, and hospitalizations for severe hypoglycemia and hyperglycemia remain common, with high rates of recurrence. Severe dysglycemia is most likely to occur among younger patients with multiple diabetes complications and prior history of such events.

Predictors of all-cause 30 day readmission among Medicare patients with type 2 diabetes

OBJECTIVE

Readmission is costly among patients with type 2 diabetes (T2DM) in Medicare Advantage Prescription Drug Plans; identifying high-risk patients is necessary for targeting reduction programs. The objective of this study was to develop a claims-based algorithm to predict all-cause 30 day readmission among patients with T2DM.

METHODS

This study used administrative data from 1 January 2012 through 31 January 2014. The cohort included hospitalized T2DM patients, aged 18-90 with ≥12 months' continuous enrollment before an unplanned hospital admission and ≥1 month of enrollment post-discharge, excluding patients in long-term care >30 days pre-index. Multivariate logistic regression predicted the likelihood of readmission following hospitalization in 2013. The analytic file was randomly split into training and test datasets to build and validate the model. Candidate variables included physician and patient demographics, baseline clinical conditions, and healthcare utilization metrics. Clinical conditions were classified using the Healthcare Cost and Utilization Project clinical classification system for ICD-9-CM.

RESULTS

Of 63,237 individuals, 17.1% experienced a readmission. Of nearly 200 candidate variables, 14 were predictors of readmission, including total cumulative number of days for inpatient stays and the number of emergency department visits in the baseline period. Male gender, older age, and certain comorbidities were associated with higher likelihood of readmission. The final model demonstrated good discriminant ability (c-statistic = 0.82).

CONCLUSIONS

This study provided evidence that certain patient characteristics and healthcare utilization are predictive of readmission. An algorithm with good discriminant ability was developed which could be used to target readmission reduction programs. Physician gender, specialty, and ownership status did not appear to influence the likelihood of readmission.

Risk factors of adverse health outcomes after hospital discharge modifiable by clinical pharmacist interventions: a review with a systematic approach

The present review assessed the evidence on risk factors for the occurrence of adverse health outcomes after discharge (i.e. unplanned readmission or adverse drug event after discharge) that are potentially modifiable by clinical pharmacist interventions. The findings were compared with patient characteristics reported in guidelines that supposedly indicate a high risk of drug-related problems. First, guidelines and risk assessment tools were searched for patient characteristics indicating a high risk of drug-related problems. Second, a systematic PubMed search was conducted to identify risk factors significantly associated with adverse health outcomes after discharge that are potentially modifiable by a clinical pharmacist intervention. After the PubMed search, 37 studies were included, reporting 16 risk factors. Only seven of 34 patient characteristics mentioned in pertinent guidelines corresponded to one of these risk factors. Diabetes mellitus (n = 11), chronic obstructive lung disease (n = 9), obesity (n = 7), smoking (n = 5) and polypharmacy (n = 5) were the risk factors reported most frequently in the studies. Additionally, single studies also found associations of adverse health outcomes with different drug classes {e.g. warfarin [hazard ratio 1.50; odds ratio (OR) 3.52], furosemide [OR 2.25] or high beta-blocker starting doses [OR 3.10]}. Although several modifiable risk factors were found, many patient characteristics supposedly indicating a high risk of drug-related problems were not part of the assessed risk factors in the context of an increased risk of adverse health outcomes after discharge. Therefore, an obligatory set of modifiable patient characteristics should be created and implemented in future studies investigating the risk for adverse health outcomes after discharge.

Risk factors associated with 30-day readmission and length of stay in patients with type 2 diabetes

AIMS

Patients with type 2 diabetes mellitus (type 2 DM) are at greater risk of poor hospital outcomes. The purpose of this study was to determine the impact of type 2 DM on 30-day hospital readmission and length of stay (LOS).

METHODS

We studied all inpatient admissions in Pennsylvania during 2011 using data from the Pennsylvania Health Care Cost Containment Council. Outcomes included 30-day readmission and inpatient LOS. We estimated the impact of type 2 DM on readmission and LOS, and identified risk factors for readmission and prolonged LOS.

RESULTS

Among inpatient admissions, patients with diabetes were more likely to be readmitted (AOR=1.17, P<0.001) and have longer LOS (0.19days, P<0.001) compared to patients without diabetes. Among those with diabetes, several factors were associated with readmission, including demographics, source of admission, and comorbidities. Patients with diabetes were more likely to be readmitted for infectious complications (9.4% vs. 7.7%), heart failure (6.0% vs. 3.1%), and chest pain/MI (5.5% vs. 3.3%) than patients without diabetes.

CONCLUSIONS

Diabetes is associated with risk of 30-day readmission and LOS, and several patient-specific factors are associated with outcomes for patients with diabetes. Future studies may target risk factors to develop strategies to reduce readmissions and LOS.