Intensification of diabetes medication and risk for 30-day readmission

A health promotion model-based intervention to enhance treatment adherence in patients with type 2 diabetes

BACKGROUND

The present study aimed to determine the effect of an intervention based on Pender's health promotion model (HPM) on treatment adherence in patients with type 2 diabetes (T2D).

METHODS

The present quasi-experimental study with a 3-month follow-up was conducted in Bandar Abbas, a city in the south of Iran in 2023. The intervention group (IG) with a total number of 95 T2D patients was selected from Hormuz diabetes clinic and the control group (CG) with 95 T2D patients was selected from comprehensive health centers through a clustering sampling method. The educational intervention was implemented in 10 sessions to improve patients' treatment adherence. The teaching methods in training sessions were lectures, joint discussions, Q&A, role-play and peer training. The participants were evaluated using a researcher-made questionnaire including the constructs of Pender's HPM about T2D treatment adherence, hemoglobin A1C (HbA1C), and BMI. Independent-samples t-test, paired-samples t-test, covariance analysis and stepwise regression analysis were used. Data analysis was done in SPSS 26.

FINDINGS

Three months after the intervention, in comparison to the CG, the mean and standard deviation of treatment adherence benefits (p = 0.002), treatment adherence self-efficacy (p = 0.010), treatment adherence related affect (p = 0.001), interpersonal influences (p = 0.012), commitment to plan of action (p < 0.001), treatment adherence behavior (p = 0.022), treatment adherence experiences (p = 0.001) was higher in the IG. The mean and standard deviation of situational influences (p < 0.001), immediate competing demands and preferences (p = 0.018) were lower than the CG. The results obtained from the analysis of covariance proved the effectiveness of the intervention in the constructs of Pender's HPM and HbA1C in participants of the IG (p < 0.001). The regression analysis showed, after the intervention, for every 1 unit of change in commitment to behavior planning, action related affect and perceived self-efficacy, compared to before the intervention, there were 0.22 units, 0.16 units and 0.26 units of change in the behavior score in the IG.

CONCLUSION

The findings proved the effectiveness of the educational intervention in improving the constructs in Pender's HPM and the blood sugar level of T2D patients. As the results of the educational intervention showed, the use of a suitable educational approach as well as the development of appropriate educational content for the target population can significantly improve the treatment adherence behavior.

TRIAL REGISTRATION

This study is registered on the Iranian Registry of Clinical Trials (IRCT20211228053558N1: https://www.irct.ir/trial/61741 ) and first release date of 17th March 2022.

Impact of medication intensification on 30-day hospital readmissions in a geriatric trauma population: A multicenter cohort study

BACKGROUND

Fall-related injuries are a significant health issue that occur in 25% of older adults and account for a significant number of trauma-related hospitalizations. Although medication intensification may increase the risk of hospital readmissions in non-trauma patients, data on a geriatric trauma population are lacking.

OBJECTIVE

The primary objective was to evaluate the effect of medication intensification on 30-day hospital readmissions in geriatric patients hospitalized for fall-related injuries.

METHODS

This multicenter, retrospective cohort study included patients with geriatric who presented to one of three trauma centers within a large, health-system between January 1, 2018 and December 31, 2020. Patients at least 65 years old admitted with a fall-related injury were eligible for inclusion. Patients were grouped according to medication changes at discharge, which included intensified and non-intensified groups. Medication intensification included increased dose(s) or initiation of new agents. The primary outcome was the 30-day hospital readmission rate.

RESULTS

Of the 870 patients included (median [interquartile range, IQR] age, 82 [74-89] years, 522 (60%) female, and 220 (25%) with a previous fall), there were 471 (54%) and 399 (46%) patients in the intensified and non-intensified groups, respectively. The intensified group had a higher 30-day hospital readmission rate (21% intensified vs. 16% non-intensified, p = 0.043; number needed to harm 20) based on an unweighted analysis. According to a weighted propensity score logistic regression, medication intensification was associated with higher 30-day hospital readmissions (24% [95% confidence interval [CI] 19-31%] intensified vs. 15% [95% CI 11-20%] non-intensified, p = 0.018). These results were consistent within competing risk models accounting for death (cause-specific model: hazard ratio [HR] 1.63 [95% CI 1.07-2.49], p = 0.023; Fine-Gray model: HR 1.64 [95% CI 1.07-2.50], p = 0.022).

CONCLUSIONS

In a geriatric trauma population hospitalized after a fall, intensification of medications may pose an increased risk of 30-day hospital readmission.

Early intervention model of inpatient diabetes care improves glycemia following hospitalization

Admission to hospital provides an opportunity to optimize long-term diabetes management, but clinical inertia is common. We previously reported the randomized study of a proactive inpatient diabetes service (RAPIDS), investigating an early intervention model of care and demonstrated improved in-hospital glycemia and clinical outcomes. This follow-up study assessed whether proactive care in hospital improved postdischarge HbA1c. In a subgroup of 298 RAPIDS trial participants with type 2 diabetes, age <80 years, and admission HbA1c ≥ 7.0%, diabetes treatment intensification occurred more often in early intervention versus usual care groups (37% vs. 19% [p = .001]), adjusted odds ratio 3.2 (95% confidence interval [CI]: 1.7-6.0). There was a greater change in HbA1c in the early intervention group (mean -0.9% [95% CI -1.3 to -0.4]) versus the usual care group (-0.3% [-0.6 to -0.1]), p = .029. The value of acute care by dedicated inpatient diabetes teams can extend beyond improving inpatient clinical outcomes and can lead to sustained improvement in glycemia.

Predicting readmission due to severe hyperglycemia after a hyperglycemic crisis episode

AIM

This study aimed to investigate the readmission pattern and risk factors for patients who experienced a hyperglycemic crisis.

METHODS

Patients admitted to MacKay Memorial Hospital for diabetic ketoacidosis (DKA) or hyperglycemic hyperosmolar state (HHS) between January 2016 and April 2019 were studied. The timing of the first readmission for hyperglycemia and other causes was recorded. Kaplan-Meier analysis was used to compare patients with hyperglycemia and all-cause readmissions. Cox regression was used to identify independent predictors for hyperglycemia and all-cause readmission post-discharge.

RESULTS

The study cohort included 410 patients, and 15.3 % and 46.3 % of them had hyperglycemia and all-cause readmissions, respectively. The DKA and HHS group showed a similar incidence for hyperglycemia, with the latter group showing a higher incidence of all-cause readmissions. The significant predictors of hyperglycemia readmissions included young age, smoking, hypoglycemia, higher effective osmolality, and hyperthyroidism in the DKA group and higher glycated hemoglobin level in the HHS group.

CONCLUSIONS

Patients who experienced DKA and HHS had similar hyperglycemia readmission rates; however, predictors in the DKA group were not applicable to the HHS group. Designing different strategies for different types of hyperglycemic crisis is necessary for preventing readmission.

Acceptance and Effect of Continuous Glucose Monitoring on Discharge From Hospital in Patients With Type 2 Diabetes: Open-label, Prospective, Controlled Study

Background

Continuous glucose monitors (CGM) can provide detailed information on glucose excursions. There is little information on safe transitioning from hospital back to the community for patients who have had diabetes therapies adjusted in hospital and it is unclear whether newer technologies may facilitate this process.

Objective

Our aim was to determine whether offering CGM on discharge would be acceptable and if CGM initiated on hospital discharge in people with type 2 diabetes (T2DM) would reduce hospital re-presentations at 1 month.

Methods

This was an open-label study. Adult inpatients with T2DM, who were to be discharged home and required postdischarge glycemic stabilization, were offered usual care consisting of clinic review at 2 weeks and at 3 months. In addition to usual care, participants in the intervention arm were provided with a Libre flash glucose monitoring system (Abbott Australia). An initial run-in phase for the first 20 participants was planned, where all consenting participants were enrolled in an active arm. Subsequently, all participants were to be randomized to the active arm or usual care control group.

Results

Of 237 patients screened during their hospital admission, 34 had comorbidities affecting cognition that prevented informed consent and affected their ability to learn to use the CGM device. In addition, 21 were not able to be approached as the material was only in English. Of 101 potential participants who fulfilled eligibility criteria, 19 provided consent and were enrolled. Of the 82 patients who declined to participate, 31 advised that the learning of a new task toward discharge was overwhelming or too stressful and 26 were not interested, with no other details. Due to poor recruitment, the study was terminated without entering the randomization phase to determine whether CGM could reduce readmission rate.

Conclusions

These results suggest successful and equitable implementation of telemedicine programs requires that any human factors such as language, cognition, and possible disengagement be addressed. Recovery from acute illness may not be the ideal time for introduction of newer technologies or may require more novel implementation frameworks.

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.

Intensification of Diabetes Medications at Hospital Discharge and Clinical Outcomes in Older Adults in the Veterans Administration Health System

IMPORTANCE

Transient elevations of blood glucose levels are common in hospitalized older adults with diabetes and may lead clinicians to discharge patients with more intensive diabetes medications than they were using before hospitalization.

OBJECTIVE

To investigate outcomes associated with intensification of outpatient diabetes medications at discharge.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study assessed patients 65 years and older with diabetes not taking insulin who were hospitalized in the Veterans Health Administration Health System between January 1, 2011, and September 28, 2016, for common medical conditions. Data analysis was performed from January 1, 2020, to March 31, 2021.

EXPOSURE

Discharge with intensified diabetes medications, defined as filling a prescription at hospital discharge for a new or higher-dose medication than was being used before hospitalization. Propensity scores were used to construct a matched cohort of patients who did and did not receive diabetes medication intensifications.

MAIN OUTCOMES AND MEASURES

Coprimary outcomes of severe hypoglycemia and severe hyperglycemia were assessed at 30 and 365 days using competing risk regressions. Secondary outcomes included all-cause readmissions, mortality, change in hemoglobin A1c (HbA1c) level, and persistent use of intensified medications at 1 year after discharge.

RESULTS

The propensity-matched cohort included 5296 older adults with diabetes (mean [SD] age, 73.7 [7.7] years; 5212 [98.4%] male; and 867 [16.4%] Black, 47 [0.9%] Hispanic, 4138 [78.1%] White), equally split between those who did and did not receive diabetes medication intensifications at hospital discharge. Within 30 days, patients who received medication intensifications had a higher risk of severe hypoglycemia (hazard ratio [HR], 2.17; 95% CI, 1.10-4.28), no difference in risk of severe hyperglycemia (HR, 1.00; 95% CI, 0.33-3.08), and a lower risk of death (HR, 0.55; 95% CI, 0.33-0.92). At 1 year, no differences were found in the risk of severe hypoglycemia events, severe hyperglycemia events, or death and no difference in change in HbA1c level was found among those who did vs did not receive intensifications (mean postdischarge HbA1c, 7.72% vs 7.70%; difference-in-differences, 0.02%; 95% CI, -0.12% to 0.16%). At 1 year, 48.0% (591 of 1231) of new oral diabetes medications and 38.5% (548 of 1423) of new insulin prescriptions filled at discharge were no longer being filled.

CONCLUSIONS AND RELEVANCE

In this national cohort study, among older adults hospitalized for common medical conditions, discharge with intensified diabetes medications was associated with an increased short-term risk of severe hypoglycemia events but was not associated with reduced severe hyperglycemia events or improve HbA1c control. These findings indicate that short-term hospitalization may not be an effective time to intervene in long-term diabetes management.

Use of Endocrine Consultation for HbA1c ≥ 9.0% as a Standardized Practice in an Emergency Department Observation Unit

OBJECTIVE

Severely uncontrolled Diabetes Mellitus (DM) is associated with poor long-term outcomes, and may remain unrecognized. A high frequency of uncontrolled DM has been identified in the acute care setting, including the Emergency Department Observation Unit (EDOU). We assess the use of standardized endocrine consultation in the EDOU for Hemoglobin A1c (HbA1c) ≥ 9%.

MATERIALS AND METHODS

Standard practice in our EDOU includes universal HbA1c screening and endocrine consultation for HbA1c ≥ 9.0%. As part of a quality improvement program, EDOU patients with HbA1c ≥ 9.0% had an endocrinology consult. One month follow up phone calls assessed effects of consultation after discharge.

RESULTS

3,688 (95.7%) of 3,853 EDOU patients received an HbA1c test. 7.0% (n=258) were found to have HbA1c ≥ 9% (Mean HbA1c 11.7 ±1.8%; range 9 - 16.6%). Endocrine consults were completed for 190/258 (73.6%) patients with severely uncontrolled DM. Among the 190 patients, 92.1% (n=175) had discharge DM medication adjustments. Known DM patients (n=142) injectable diabetes medication prescriptions increased from 47.2% (67/142) on EDOU arrival to 78.2% (111/142) on discharge. Newly diagnosed DM injectable prescriptions increased from 0% (0/48) on arrival to 72.9% (35/48) on discharge. A total of 72.6% (n=138) were contacted at one-month and 94.9% (n=131) reported taking DM medications compared to 68.2% (n=94) prior to consult.

CONCLUSIONS

HbA1c screening coupled with endocrine consultation for HbA1c ≥ 9.0% was assessed as a performance improvement study and shown to have valuable results. Further study is recommended to determine long-term clinical impact and cost analysis of this novel approach.

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.

Effects of Recommendations for Diabetes Management at Hospital Discharge on Long-Term Diabetes Control

OBJECTIVE

To determine the impact of diabetes-specific recommendations at 1 year after hospital discharge on glycemic control and diabetes care in an outpatient setting.

METHODS

A total of 139 patients with type 2 diabetes on a basal-bolus insulin regimen during hospitalization were included in the statistical analysis. We gathered data on treatment regimens after 12 to 16, 26 to 30, and 52 to 56 weeks following discharge as well as glycosylated hemoglobin (HbA1c) levels for all patients. Prescriptions for diabetes therapy were retrieved. All changes in insulin or oral/noninsulin injectable drug regimens were recorded.

RESULTS

Half of the patients (n = 69) were discharged on their preadmission regimen (no change), and a change in the home treatment was recommended in the other half (n = 70). In the group of patients whose preadmission therapy was adjusted, HbA1c decreased from 9.6% (80 mmol/mol) to 8.5% (69 mmol/mol) (P = .0004) 1 year after discharge. In the group of patients discharged on their preadmission regimen, no significant changes in HbA1c levels during the study were observed. At follow-ups occurring 12 to 16 weeks after discharge, 52% (95% CI: 37.4%-66.3%) of patients in the change group had their treatment modified, compared with 18.6% (95% CI: 9.7%-30.9%) in the no-change group. In the group of patients discharged on their preadmission regimen, no significant change was observed. At the beginning of the study, patients in the change treatment group had higher HbA1c levels than patients in the no-change group (9.6 ± 2.0 vs 8.6 ± 1.7, P < .001). At the end of the study, no significant changes in terms of HbA1c levels were found between the groups (8.8 ± 1.9 vs 8.5 ± 1.9, P = .2).

CONCLUSIONS

Significant improvement in diabetes control occurred 1 year after hospital discharge in patients who underwent modifications in their treatment. This supports the relevance of providing and implementing proper care recommendations at transition.

Application of the Ottawa Charter Five Priority Areas of Action for Public Health to an Institution-Wide Diabetes Care Promotion

This study was the first institution-wide health promotion program in Taiwan to apply the five priority areas for taking action in public health highlighted in the Ottawa Charter for diabetes patients. We aimed to improve the quality of home care received by diabetic patients by training health care professionals in health promotion. This program consisted of developing personal skills, reorienting health services, strengthening community actions, creating supportive environments, and building healthy public policy. It was applied in the Yunlin Christian Hospital located in central Taiwan from August 2011 to November 2011. A health-promoting education course consisting of weight control, diabetes care, and quality management for diabetes was developed and applied to all 323 hospital staff. Then, hospital staff volunteers and diabetes patients were recruited to participate in the program. A total of 61 staff volunteers and 90 diabetes patients were involved in this study. Staff volunteers were trained to participate in communities to provide care and guidance to patients with diabetes. The World Health Organization Quality of Life(WHOQOL)-BREF-Taiwan Version questionnaires were investigated before and after implementation of this program for the patients. A health-promoting lifestyle profile questionnaire was filled by the staff. The investigation data were then analyzed by statistical methods. The diabetes patients experienced a significant increase in their satisfaction with health and health-related quality of life as well as significant improvements in health-promotion and self-management behaviors (p < 0.05). In addition, staff volunteers significantly consumes food from the five major groups than the other staff (p < 0.05). Various improvements in health-promoting behaviors were observed amongst the hospital staff and the diabetic patients. Our project could be a reference for other medical organizations to implement an institution-wide health-promotion program for diabetic patients.

Inpatient Hyperglycemia and Transitions of Care: A Systematic Review

OBJECTIVE

The transition of diabetes care from home to hospital, within the hospital, and upon discharge is fraught with gaps that can adversely affect patient safety and length of stay. We aimed to highlight the variability in care during these transitions and point out areas where research is needed.

METHODS

A PubMed search was performed with a combination of search terms that pertained to diabetes, hyperglycemia, hospitalization, locations in the hospital, discharge to home or a nursing facility, and diabetes medications. Studies with at least 50 patients that were written in the English language were included.

RESULTS

With the exception of transitioning from intravenous insulin infusion to subcutaneous insulin and perhaps admission to the regular floors, few studies pointedly focused on transitions of care, leading us to extrapolate recommendations based on data from disparate areas of care in the hospital. There is evidence at every stage of care, starting from the entry into the hospital and ending with discharge home or to a facility, that patients benefit from having protocols in place guiding overall care.

CONCLUSION

Pockets of care exist in hospitals where methods of effective diabetes management have been studied and implemented. However, there is no sustained continuum of care. Protocols and care teams that follow patients from one physical location to the other may result in improved clinical outcomes during and following a hospital stay.

Clinical profiles, outcomes and risk factors among type 2 diabetic inpatients with diabetic ketoacidosis and hyperglycemic hyperosmolar state: a hospital-based analysis over a 6-year period

OBJECTIVE

Diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS) are the two most common hyperglycemic emergencies (HEs) associated with diabetes mellitus. Individuals with HEs can present with combined features of DKA and HHS. The objective of this study is to assess the clinical characteristics, therapeutic outcomes, and associated predisposing factors of type 2 diabetic patients with isolated or combined HEs in China.

METHODS

We performed a retrospective analysis of 158 patients with type 2 diabetes (T2DM), complicated with DKA, HHS, or DKA combined with HHS (DKA-HHS) in Shanghai Tongji Hospital, China from 2010 to 2015. Admission clinical features, therapeutic approaches and treatment outcomes of those patients were extracted and analyzed.

RESULTS

Of the 158 patients with T2DM, 65 (41.1%) patients were DKA, 74 (46.8%) were HHS, and 19 (12.0%) were DKA-HHS. The most common precipitants were infections (111, 70.3%), newly diagnosed diabetes (28,17.7%) and non-compliance to medications (9, 5.7%). DKA patients were divided into mild, moderate and severe group, based on arterial blood gas. Spearman correlation analysis revealed that C-reaction protein (CRP) was positively correlated with severity of DKA, whereas age and fasting C peptide were inversely correlated with severity of DKA (P < 0.05). The mortality was 10.8% (17/158) in total and 21.6% (16/74) in the HHS group, 5.9% (1/17) in DKA-HHS. Spearman correlation analysis indicated that death in patients with HHS was positively correlated to effective plasma osmolality (EPO), renal function indicators and hepatic enzymes, while inversely associated with the continuous subcutaneous insulin infusion (CSII) therapy. Logistic regression analysis suggested that elevated blood urea nitrogen (BUN) on admission was an independent predisposing factor of mortality in HHS, while CSII might be a protective factor for patients with HHS. Furthermore, the receiver-operating characteristic (ROC) curve analysis indicated that BUN had the largest area under the ROC curves for predicting death in patients with HHS.

CONCLUSIONS

Our findings showed elevated CRP and decreased fasting C-peptide might serve as indicator for severe DKA. Elevated BUN might be an independent predictor of mortality in patients with HHS, whereas CSII might be a protective factor against death in HHS.

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.

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.

Patterns and predictors of antihyperglycemic intensification at hospital discharge for type 2 diabetic patients not on home insulin

BACKGROUND

Diabetes mellitus is a prevalent condition among hospitalized patients and the inpatient setting presents an opportunity for providers to review and adjust antihyperglycemic medications. We sought to describe practice patterns and predictors of antihyperglycemic intensification (AHI) at hospital discharge for type 2 diabetes mellitus (T2DM) patients not on home insulin.

METHODS

We conducted a retrospective study of adult patients with T2DM receiving either non-insulin antihyperglycemic (NIA) or no antihyperglycemic medications prior to admission who were hospitalized within two hospitals in the Johns Hopkins Health System from December 2015 to September 2016. Mean hospital glucose values and observed vs. individualized target hemoglobin A1C values (based on risk of mortality score) were used to define an indication for AHI. Multivariable logistic regression was used to identify predictors of AHI.

RESULTS

A total of 554 discharges of 475 unique patients were included. An indication for AHI was present in 104 (18.8%) of discharges, and AHI occurred in 30 (28.8%) of these discharges. Higher mean admission BG values and A1C, fewer pre-admission antihyperglycemic agents, involvement of the diabetes service, and admitting service were associated with AHI, while no association was observed with age, sex, race, risk of mortality and severity of illness scores, or length of stay. AHI was not associated with 30-day readmission.

CONCLUSION

An indication for AHI occurs relatively infrequently among hospitalized patients, but when present, AHI occurs in approximately 1 in 3 discharges. AHI appears to be related largely to the degree of hyperglycemia, and diabetes service involvement. Further studies are needed to understand the implications of AHI at hospital discharge on short and long-term outcomes in this population.

Thirty-day readmission, length of stay and self-management behaviour among patients with acute coronary syndrome and type 2 diabetes mellitus: A scoping review

AIMS AND OBJECTIVES

To summarise the current evidence on comorbid type 2 diabetes mellitus (T2DM) related to 30-day readmission and hospital length of stay (LOS) among patients with acute coronary syndrome (ACS) and evidence on the effectiveness of self-management programmes for patients with both conditions.

BACKGROUND

Acute coronary syndrome and T2DM remain two major diseases leading to serious consequences. Thirty-day readmission and LOS were considered indicators of the quality of care, with the understanding that the potential significant effects of these outcomes could be varied.

DESIGN

This scoping review followed the methodology described by Arksey and O'Malley.

METHODS

Five databases including PubMed, Embase, Cochrane Library, Web of Science and CINAHL were searched, and a total of 20 articles involving 913,807 patients were included. Results were reported in accordance with PRISMA-ScR guidelines.

RESULTS

The results indicated that patients with both ACS and T2DM have prolonged LOS and increased 30-day readmission rates. The findings supported that improvements in patient self-management behaviour for optimal health outcomes were partially successful by effective self-management programmes; however, few articles on intervention programmes specifically designed for patients with two conditions were found.

CONCLUSION

Prolonged LOS and increased 30-day readmission rates are found among patients with ACS and T2DM. Based on few pilot studies building on each other, the effectiveness of self-management programmes in promoting self-care behaviour, self-efficacy and knowledge for patients with ACS and T2DM cannot be concluded.

RELEVANCE TO CLINICAL PRACTICE

Findings from this review provide valuable information on and a better understanding of readmissions and LOS among patients with ACS and T2DM for healthcare providers. Future developments and implementations of effective self-management programmes should target patients with dual diagnoses to improve health behaviour and reduce readmission and LOS.

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.

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.

Recurrent hospitalizations for severe hypoglycemia and hyperglycemia among U.S. adults with diabetes

AIMS

Examine 30-day readmissions for recurrent hypoglycemia and hyperglycemia in a national cohort of adults with diabetes.

METHODS

Retrospective analysis of data from OptumLabs Data Warehouse for all adults with diabetes hospitalized January 1, 2009 to December 31, 2014 with a principal diagnosis of hypoglycemia or hyperglycemia. We examined the rates and risk factors of 30-day readmissions for hypoglycemia and hyperglycemia.

RESULTS

After 6419 index hypoglycemia hospitalizations, 1.2% were readmitted for recurrent hypoglycemia, 0.2% for hyperglycemia, and 8.6% for other causes. Multimorbidity was the strongest predictor of recurrent hypoglycemia. After 6872 index hyperglycemia hospitalizations, 4.0% were readmitted for recurrent hyperglycemia, 0.4% for hypoglycemia, and 5.4% for other causes. Recurrent hyperglycemia was less likely in older patients (OR 0.6, 95% CI 0.5-0.9 for 45-64 vs. <45 years) and with the addition of a new glucose-lowering medication at index discharge (OR 0.40; 95% CI 0.2-0.7). New hypoglycemia readmissions were most likely among patients ≥75 years (OR 13.3, 95% CI 2.4-73.4, vs. <45 years).

CONCLUSIONS

Patients hospitalized for hyperglycemia are often readmitted for recurrent hyperglycemia, while patients hospitalized for hypoglycemia are generally readmitted for unrelated causes. Early recognition of high risk patients may identify opportunities to improve post-discharge management and reduce these events.

Perspective Review: Type 2 Diabetes and Readmission for Heart Failure

Heart failure is a leading cause for hospitalisation and for readmission, especially in patients over the age of 65. Diabetes is an increasingly common companion to heart failure. The presence of diabetes and its associated comorbidity increases the risk of adverse outcomes and premature mortality in patients with heart failure. In particular, patients with diabetes are more likely to be readmitted to hospital soon after discharge. This may partly reflect the greater severity of heart disease in these patients. In addition, agents that reduce the chances of readmission such as β-blockers, renin-angiotensin-aldosterone system blockers, and mineralocorticoid receptor antagonists are underutilised because of the perceived increased risks of adverse drug reactions and other limitations. In some cases, readmission to hospital is precipitated by acute decompensation of heart failure (re-exacerbation) leading to pulmonary congestion and/or refractory oedema. However, it appears that for most of the patients admitted and then discharged with a primary diagnosis of heart failure, most readmissions are not due to heart failure, but rather due to comorbidity including arrhythmia, infection, adverse drug reactions, and renal impairment/reduced hydration. All of these are more common in patients who also have diabetes, and all may be partly preventable. The many different reasons for readmission underline the critical value of multidisciplinary comprehensive care in patients admitted with heart failure, especially those with diabetes. A number of new strategies are also being developed to address this area of need, including the use of SGLT2 inhibitors, novel nonsteroidal mineralocorticoid antagonists, and neprilysin inhibitors.

EXTERNAL VALIDATION OF THE DIABETES EARLY RE-ADMISSION RISK INDICATOR (DERRI™)

OBJECTIVE

The Diabetes Early Re-admission Risk Indicator (DERRI^™) was previously developed and internally validated as a tool to predict the risk of all-cause re-admission within 30 days of discharge (30-day re-admission) of hospitalized patients with diabetes. In this study, the predictive performance of the DERRI^™ with and without additional predictors was assessed in an external sample.

METHODS

We conducted a retrospective cohort study of adult patients with diabetes discharged from two academic medical centers between January 1, 2000 and December 31, 2014. We applied the previously developed DERRI^™, which includes admission laboratory results, sociodemographics, a diagnosis of certain comorbidities, and recent discharge information, and evaluated the effect of adding metabolic indicators on predictive performance using multivariable logistic regression. Total cholesterol and hemoglobin A1c (A1c) were selected based on clinical relevance and univariate association with 30-day re-admission.

RESULTS

Among 105,974 discharges, 19,032 (18.0%) were followed by 30-day re-admission for any cause. The DERRI^™ had a C-statistic of 0.634 for 30-day re-admission. Total cholesterol was the lipid parameter most strongly associated with 30-day re-admission. The DERRI^™ predictors A1c and total cholesterol were significantly associated with 30-day re-admission; however, their addition to the DERRI^™ did not significantly change model performance (C-statistic, 0.643 [95% confidence interval, 0.638 to 0.647]; P = .92).

CONCLUSION

Performance of the DERRI^™ in this external cohort was modest but comparable to other re-admission prediction models. Addition of A1c and total cholesterol to the DERRI^™ did not significantly improve performance. Although the DERRI^™ may be useful to direct resources toward diabetes patients at higher risk, better prediction is needed.

ABBREVIATIONS

A1c = hemoglobin A1c; CI = confidence interval; DERRI^™ = Diabetes Early Re-admission Risk Indicator; GEE = generalized estimating equation; HDL-C = high-density-lipoprotein cholesterol; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; LDL-C = low-density-lipoprotein cholesterol.

Correction to: Hospital Readmission of Patients with Diabetes

This article was originally published with errors that were introduced during the editing process. The corrected version of this article appears below.

Effect of follow-up by a hospital diabetes care team on diabetes control at one year after discharge from the hospital

AIM

This study was conducted to evaluate the effect of continued follow-up by a hospital diabetes team on HbA1c at 1-year after discharge.

METHODS

Adults with HbA1c ≥8% (64mmol/mol), undergoing an elective surgery, were treated in the perioperative period and randomized to continued care (CC) or the usual care (UC) after discharge. Patients in the CC group received weekly to monthly phone calls from a diabetes specialist nurse practitioner (NP) to review their home blood glucose values, diet, exercise, and medications. Patients in the UC group followed with their diabetes care providers.

RESULTS

Out of 151 patients, 77 were randomized to the CC group and 74 to the UC group. HbA1c (%) at 1-year was 8.2±1.4 in the CC group and 8.5±1.5 in the UC group (p=NS). Change in HbA1c from baseline was similar between the groups; -0.7±1.4 in the CC versus -0.7±1.5 in the UC group (p=NS). A higher number of calls was not associated with lower HbA1c or reduction in HbA1c. There were 41 insulin-treated patients in the CC group and 53 in the UC group and among them, HbA1c reduction was 0.5±1.5 and 0.6±1.3 respectively (p=NS).

CONCLUSIONS

Optimal perioperative treatment of diabetes is associated with an improvement in HbA1c but continued follow-up by a hospital diabetes team after discharge does not have an additional impact on long-term glycemic control. ClinicalTrials.gov identifier NCT02065050.

Practical Recommendations for Transitioning Patients with Type 2 Diabetes from Hospital to Home

PURPOSE OF REVIEW

The purpose of this review is to provide practical evidence-based recommendations for transitioning hospitalized patients with type 2 diabetes (T2DM) to home.

RECENT FINDINGS

Hospitalized patients who have newly diagnosed or poorly controlled T2DM require initiation or intensification of their outpatient diabetes regimen. Potential barriers to medication access and continuity of care should be identified early in the hospitalization. Throughout hospitalization, patients should receive diabetes education focused on basic survival skills and tailored to learning needs. Patients should leave the hospital with personalized discharge instructions that include a list of all medications and follow-up appointments with both the outpatient diabetes provider and a diabetes educator whenever possible. An approach to transitioning patients with T2DM from hospital to home that focuses on optimizing the patient's discharge diabetes regimen, anticipating patients' needs during the immediate post-discharge period, providing survival skills education, and ensuring continuation of diabetes care and education following hospital discharge has the potential to improve glycemic control and reduce emergency department visits and hospital readmissions.

The Case for Diabetes Population Health Improvement: Evidence-Based Programming for Population Outcomes in Diabetes

PURPOSE OF REVIEW

The goal of this review is to describe diabetes within a population health improvement framework and to review the evidence for a diabetes population health continuum of intervention approaches, including diabetes prevention and chronic and acute diabetes management, to improve clinical and economic outcomes.

RECENT FINDINGS

Recent studies have shown that compared to usual care, lifestyle interventions in prediabetes lower diabetes risk at the population-level and that group-based programs have low incremental medial cost effectiveness ratio for health systems. Effective outpatient interventions that improve diabetes control and process outcomes are multi-level, targeting the patient, provider, and healthcare system simultaneously and integrate community health workers as a liaison between the patient and community-based healthcare resources. A multi-faceted approach to diabetes management is also effective in the inpatient setting. Interventions shown to promote safe and effective glycemic control and use of evidence-based glucose management practices include provider reminder and clinical decision support systems, automated computer order entry, provider education, and organizational change. Future studies should examine the cost-effectiveness of multi-faceted outpatient and inpatient diabetes management programs to determine the best financial models for incorporating them into diabetes population health strategies.

The effect of diabetes case management and Diabetes Resource Nurse program on readmissions of patients with diabetes mellitus

AIMS

Patients with diabetes have higher readmission rates than those without diabetes, yet limited data on efforts to reduce their readmissions are available. We describe a novel model of inpatient diabetes care, expanding the role of diabetes educators to include case management, and establishment of a Diabetes Resource Nurse program, aimed at increasing the knowledge of staff nurses, and evaluate the impact of this program on readmission rates.

METHODS

We performed retrospective analysis of 30-day readmission rates of patients with diabetes before (July 2010-December 2011), and after (January 2012-June 2013) starting the implementation of this tiered inpatient diabetes care delivery model.

RESULTS

We analyzed 34,472 discharged patient records from the 18-month pre-intervention period, and 32,046 records from the 18-month post-intervention period. The overall 30-day readmission rate for patients with diabetes decreased significantly from 20.1% (pre) to 17.6% (post) intervention (p < 0.0001). Patients seen by diabetes educators had the lowest 30-day readmission rates (∼15% during the whole study), a rate approaching the overall hospital readmission rates in those without diabetes in our institution.

CONCLUSION

The Diabetes Resource Nurse program is effective in decreasing readmission rates. Patients seen by the diabetes educators have the lowest rates of readmission.

Understanding 30-day re-admission after hospitalisation of older patients for diabetes: identifying those at greatest risk

OBJECTIVE

To identify factors that contribute to older Australians admitted to hospital with diabetes being re-hospitalised within 30 days of discharge.

DESIGN, SETTING AND PARTICIPANTS

A retrospective cohort study of Department of Veterans' Affairs administrative data for all patients hospitalised for diabetes and discharged alive during the period 1 January - 31 December 2012.

MAIN OUTCOME MEASURES

Causes of re-hospitalisation and prevalence of clinical factors associated with re-hospitalisation within 30 days of discharge.

METHODS

Multivariate logistic regression analysis (backward stepwise) was used to identify characteristics predictive of 30-day re-hospitalisation.

RESULTS

848 people were hospitalised for diabetes; their median age was 87 years (interquartile range, 77-89 years) and 60% were men. 209 patients (24.6%) were re-hospitalised within 30 days of discharge, of whom 77.5% were re-admitted within 14 days of discharge. 51 re-hospitalisations (24%) were for diabetes-related conditions; 41% of those re-admitted within 14 days had not seen their general practitioner between discharge and re-admission. Factors predictive of re-hospitalisation included comorbid heart failure (adjusted odds ratio [aOR], 1.49; 95% confidence interval [CI], 1.03-2.17; P = 0.036), numbers of prescribers in previous year (aOR [for each additional prescriber], 1.06; 95% CI, 1.01-1.08; P = 0.031), and two or more hospitalisations in the 6 months before the index admission (aOR, 1.79; 95% CI 1.15-2.78; P = 0.009).

CONCLUSION

Older people hospitalised for diabetes who have comorbid heart failure, multiple recent hospitalisations, and multiple prescribers involved in their care are at greatest risk of being re-admitted to hospital within 30 days. Targeted follow-up during the initial 14 days after discharge may facilitate appropriate interventions that avert re-admission of these at-risk patients.

Medication use and potentially high-risk prescribing in older patients hospitalized for diabetes: a missed opportunity to improve care?

AIMS

To examine the appropriateness of medicine use and potentially high-risk prescribing before and after hospitalization for diabetes.

METHODS

A retrospective cohort study of patients hospitalized for diabetes was conducted using administrative data from the Australian Government Department of Veterans' Affairs for the period between 1 January 2012 and 31 December 2012. The appropriateness of medicine use and potentially high-risk prescribing, including hyper-polypharmacy and associated treatment conflicts, were examined for the 120-day periods before and after hospitalization.

RESULTS

A total of 876 patients were hospitalized for a diabetes-related complication. Of these, 25% were not dispensed an antidiabetic medicine 4 months before hospitalization and 25% had not had their HbA_1c levels measured in the preceding 6 months. The use of antidiabetic medicines increased to 85% after hospitalization, with a 25.6% relative increase (95% CI 10.9-42.1) in the proportion of those dispensed insulin. The prevalence of high-risk prescribing before hospital admission was high; 70% had > 10 medicines dispensed, a third had at least one treatment conflict and half were dispensed a potentially inappropriate medicine. The use of long-acting sulphonylureas and corticosteroids had relative decreases of 46.0% (95% CI 17.0-64.9) and 29.9% (95% CI 8.8-46.0), respectively. Few changes in other high-risk prescribing patterns were observed after discharge.

CONCLUSIONS

This study has identified poor medication-related care and, in particular, high-risk-prescribing in people subsequently hospitalized for diabetes. While diabetes medicine use improved after hospitalization, there was little change in potentially inappropriate medicine use, which suggests that an opportunity to improve medication use in this older vulnerable population has been missed.

Using decision trees to explore the association between the length of stay and potentially avoidable readmissions: A retrospective cohort study

BACKGROUND

There is a growing concern that reduction in hospital length of stay (LOS) may raise the rate of hospital readmission. This study aims to identify the rate of avoidable 30-day readmission and find out the association between LOS and readmission.

METHODS

All consecutive patient admissions to the internal medicine services (n = 5,273) at King Abdullah University Hospital in Jordan between 1 December 2012 and 31 December 2013 were analyzed. To identify avoidable readmissions, a validated computerized algorithm called SQLape was used. The multinomial logistic regression was firstly employed. Then, detailed analysis was performed using the Decision Trees (DTs) model, one of the most widely used data mining algorithms in Clinical Decision Support Systems (CDSS).

RESULTS

The potentially avoidable 30-day readmission rate was 44%, and patients with longer LOS were more likely to be readmitted avoidably. However, LOS had a significant negative effect on unavoidable readmissions.

CONCLUSIONS

The avoidable readmission rate is still highly unacceptable. Because LOS potentially increases the likelihood of avoidable readmission, it is still possible to achieve a shorter LOS without increasing the readmission rate. Moreover, the way the DT model classified patient subgroups of readmissions based on patient characteristics and LOS is applicable in real clinical decisions.

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.

Predictors of Recurrent Hospital Admission for Patients Presenting With Diabetic Ketoacidosis and Hyperglycemic Hyperosmolar State

Background

Diabetic ketoacidosis (DKA) and hyperglycemic hyperosmolar state (HHS) are two serious, preventable complications of diabetes mellitus. Analysis of variables associated with recurrent DKA and HHS admission has the potential to improve patient outcomes by identifying possible areas for intervention. The aim of this study was to evaluate potential predictors of recurrent DKA or HHS admission.

Methods

This was a retrospective case-control study of 367 patients presenting during a 5-year period with DKA or HHS at a US tertiary academic medical center. Six potential readmission risk factors identified via literature review were coded as “1” if present and “0” if absent. Readmission odds ratios (ORs) for each risk factor and for the combined score of significant risk factors were calculated by logistic regression.

Results

Readmission odds were significantly increased for patients with age < 35, history of depression or substance/alcohol abuse, and self-pay/publicly funded insurance. HbA1C > 10.6% on admission and ethnic minority status did not significantly increase readmission odds, with inadequate study power for these variables. A total “ABCD” score, based on Age (< 35 years), Behavioral health (depression), insurance Coverage (self-pay/publicly funded insurance), and Drug/alcohol abuse, also had a significant effect on readmission odds.

Conclusions

Consideration of individual risk factors and the use of a scoring system based on objective predictors of recurrent DKA and HHS admission could be of value in helping identify patients with high readmission risk, allowing interventions to be targeted most effectively to reduce readmission rates, associated morbidity, and mortality.

A Real-World Observational Study of Time to Treatment Intensification Among Elderly Patients with Inadequately Controlled Type 2 Diabetes Mellitus

BACKGROUND

Among elderly patients, the management of type 2 diabetes mellitus (T2DM) is complicated by population heterogeneity and elderly-specific complexities. Few studies have been done to understand treatment intensification among elderly patients failing multiple oral antidiabetic drugs (OADs).

OBJECTIVE

To examine the association between time to treatment intensification of T2DM and elderly-specific patient complexities.

METHODS

In this observational, retrospective cohort study, elderly (aged ≥ 65 years) Medicare beneficiaries (n = 16,653) with inadequately controlled T2DM (hemoglobin A1c ≥ 8.0% despite 2 OADs) were included. Based on the consensus statement for diabetes care in elderly patients published by the American Diabetes Association and the American Geriatric Society, elderly-specific patient complexities were defined as the presence or absence of 5 geriatric syndromes: cognitive impairment; depression; falls and fall risk; polypharmacy; and urinary incontinence.

RESULTS

Overall, 48.7% of patients received intensified treatment during follow-up, with median time to intensification 18.5 months (95% CI = 17.7-19.3). Median time to treatment intensification was shorter for elderly patients with T2DM with polypharmacy (16.5 months) and falls and fall risk (12.7 months) versus those without polypharmacy (20.4 months) and no fall risk (18.6 months). Elderly patients with urinary incontinence had a longer median time to treatment intensification (18.6 months) versus those without urinary incontinence (14.6 months). The median time to treatment intensification did not significantly differ by the elderly-specific patient complexities that included cognitive impairment and depression. However, after adjusting for demographic, insurance, clinical characteristics, and health care utilization, we found that only polypharmacy was associated with time to treatment intensification (adjusted hazard ratio, 1.10; 95% CI = 1.04-1.15; P = 0.001).

CONCLUSIONS

Less than half of elderly patients with inadequately controlled T2DM received treatment intensification. Elderly-specific patient complexities were not associated with time to treatment intensification, emphasizing a positive effect of the integrated health care delivery model. Emerging health care delivery models that target integrated care may be crucial in providing appropriate treatment for elderly T2DM patients with complex conditions.

Glycemic control after hospital discharge in insulin-treated type 2 diabetes: a randomized pilot study of daily remote glucose monitoring

OBJECTIVE

Little is known about glycemic control in type 2 diabetes patients treated with insulin in the high-risk period between hospital discharge and follow-up. We sought to assess the impact of remote glucose monitoring on postdischarge glycemic control and insulin titration.

METHODS

We randomly assigned 28 hospitalized type 2 diabetes patients who were discharged home on insulin therapy to routine specialty care (RSC) or RSC with daily remote glucose monitoring (RGM). We compared the primary outcome of mean blood glucose and exploratory outcomes of hypoglycemia/hyperglycemia rates, change in hemoglobin A1c and glycated albumin, and insulin titration frequency between groups.

RESULTS

Mean blood glucose was not significantly different between the treatment arms (144 ± 34 mg/dL in the RSC group and 172 ± 41 mg/dL in the RGM group; not significant), nor were there significant differences in any of the other measures of glycemia during the month after discharge. Hypoglycemia (glucometer reading <60 mg/dL) was common, occurring in 46% of subjects, with no difference between groups. In as-treated analysis, insulin dose adjustments (29% with an increase and 43% with decrease in insulin dose) occurred more frequently in the patients who used RGM (average of 2.8 vs. 1.2 dose adjustments; P = .03).

CONCLUSION

In this pilot trial in insulin-treated type 2 diabetes, RGM did not affect glycemic control after hospital discharge; however, the high rate of hypoglycemia in the postdischarge transition period and the higher frequency of insulin titration in patients who used RGM suggest a safety role for such monitoring in the transition from hospital to home.

Incidence, Risk Factors, and Causes for Thirty-Day Unplanned Readmissions Following Primary Lower-Extremity Amputation in Patients with Diabetes

BACKGROUND

The Centers for Medicare & Medicaid Services targeted thirty-day readmissions as a quality-of-care measure. Hospitals can be penalized on unplanned readmissions. Given the frequency of amputation in diabetic patients and our changing health-care system, the purpose of this study was to determine the incidence, risk factors, and causes for unplanned thirty-day readmissions following primary lower-extremity amputation in diabetic patients.

METHODS

Patients with a diagnosis of diabetes undergoing primary lower-extremity amputation between 2002 and 2013 were retrospectively identified in a single-center patient database. Chart review determined patient factors including comorbidities, hemoglobin A1c level, amputation level, and demographic characteristics. Patients were divided into groups with and without unplanned readmission within thirty days postoperatively. Univariate and multivariate logistic regression analyses were used to compare cohorts and to identify variables associated with readmission.

RESULTS

Overall, forty-six (10.5%) of 439 diabetic patients undergoing primary lower-extremity amputation had an unplanned thirty-day readmission. The top reason for readmission was a major surgical event requiring reoperation (37.0%), followed by medical events (28.3%) and minor surgical events (28.3%). In the univariate analysis, discharge on antibiotics (p = 0.002), smoking (p = 0.003), chronic kidney disease (p = 0.002), peripheral vascular disease (p = 0.002), and higher Charlson Comorbidity Index (p = 0.001) were each associated with readmission. In the multivariate analysis, diagnosis of gangrene (odds ratio [OR], 2.95 [95% confidence interval (95% CI), 1.37 to 6.35]), discharge on antibiotics (OR, 4.48 [95% CI, 1.71 to 11.74]), smoking (OR, 3.22 [95% CI, 1.40 to 7.36]), chronic kidney disease (OR, 2.82 [95% CI, 1.30 to 6.15]), and peripheral vascular disease (OR, 2.47 [95% CI, 1.08 to 5.67]) were independently associated with readmission.

CONCLUSIONS

Thirty-day readmission rates following primary lower-extremity amputation in patients with diabetes were high at >10%. Both medical and surgical complications, many of which were unavoidable, contributed to readmission. Quality-reporting metrics should include these risk factors to avoid undeservedly penalizing surgeons and hospitals caring for this patient population.

LEVEL OF EVIDENCE

Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Hospital readmission of patients with diabetes

Hospital readmission is a high-priority health care quality measure and target for cost reduction. Despite broad interest in readmission, relatively little research has focused on patients with diabetes. The burden of diabetes among hospitalized patients, however, is substantial, growing, and costly, and readmissions contribute a significant portion of this burden. Reducing readmission rates of diabetic patients has the potential to greatly reduce health care costs while simultaneously improving care. Risk factors for readmission in this population include lower socioeconomic status, racial/ethnic minority, comorbidity burden, public insurance, emergent or urgent admission, and a history of recent prior hospitalization. Hospitalized patients with diabetes may be at higher risk of readmission than those without diabetes. Potential ways to reduce readmission risk are inpatient education, specialty care, better discharge instructions, coordination of care, and post-discharge support. More studies are needed to test the effect of these interventions on the readmission rates of patients with diabetes.

Best Practices for Interdisciplinary Care Management by Hospital Glycemic Teams: Results of a Society of Hospital Medicine Survey Among 19 U.S. Hospitals

Objective. The Society for Hospital Medicine (SHM) conducted a survey of U.S. hospital systems to determine how nonphysician providers (NPPs) are utilized in interdisciplinary glucose management teams. Methods. An online survey grouped 50 questions into broad categories related to team functions. Queries addressed strategies that had proven successful, as well as challenges encountered. Fifty surveys were electronically distributed with an invitation to respond. A subset of seven respondents identified as having active glycemic committees that met at least every other month also participated in an in-depth telephone interview conducted by an SHM Glycemic Advisory Panel physician and NPP to obtain further details. The survey and interviews were conducted from May to July 2012. Results. Nineteen hospital/hospital system teams completed the survey (38% response rate). Most of the teams (52%) had existed for 1-5 years and served 90-100% of noncritical care, medical critical care, and surgical units. All of the glycemic control teams were supported by the use of protocols for insulin infusion, basal-bolus subcutaneous insulin orders, and hypoglycemia management. However, > 20% did not have protocols for discontinuation of oral hypoglycemic agents on admission or for transition from intravenous to subcutaneous insulin infusion. About 30% lacked protocols assessing A1C during the admission or providing guidance for insulin pump management. One-third reported that glycemic triggers led to preauthorized consultation or assumption of care for hyperglycemia. Institutional knowledge assessment programs were common for nurses (85%); intermediate for pharmacists, nutritionists, residents, and students (40-45%); and uncommon for fellows (25%) and attending physicians (20%). Many institutions were not monitoring appropriate use of insulin, oral agents, or insulin protocol utilization. Although the majority of teams had a process in place for post-discharge referrals and specific written instructions were provided, only one-fourth were supported with written protocols to standardize medication, education, equipment, and follow-up instructions. Conclusion. Inpatient glycemic control teams with NPPs often function in environments without a full set of measurement, education, standardization, transition, and order tools. Executive hospital leaders, community partners, and the glycemic control teams themselves need to address these deficiencies to optimize team effectiveness.

Effectively identifying the inpatient with hyperglycemia to increase patient care and lower costs

Recent years have seen an increased focus on merging quality care and financial results. This focus not only extends to the inpatient setting but also is of major importance in assuring effective transitions of care from hospital to home. Inducements to meld the 2 factors include tying payment to quality standards, investing in patient safety, and offering new incentives for providers who deliver high-quality and coordinated care. Once seen as the purview of primary care or specific surgical screening programs, identification of patients with hyperglycemia or undiagnosed diabetes mellitus now presents providers with opportunities to improve care. Part of the new focus will need to address the length of stay for patients with diabetes mellitus. These patients are proven to require longer hospital stays regardless of the admission diagnosis. With reducing length of stay as a major objective, efficiency combined with improved quality is the desired outcome. Even with the mounting evidence supporting the benefits of improving glycemic control in the hospital setting, institutions continue to struggle with inpatient glycemic control. Multiple national groups have provided recommendations for blood glucose assessment and glycated hemoglobin testing. This article identifies the key benefits in identifying patients with hyperglycemia and reviews possible ways to identify, monitor, and treat this potential problem area and thereby increase the level of patient care and cost-effectiveness.

Patient activation and 30-day post-discharge hospital utilization

BACKGROUND

Patient activation is linked to better health outcomes and lower rates of health service utilization. The role of patient activation in the rate of hospital readmission within 30 days of hospital discharge has not been examined.

METHODS

A secondary analysis using data from the Project RED-LIT randomized controlled trial conducted at an urban safety net hospital. Data from 695 English-speaking general medical inpatient subjects were analyzed. We used an adapted, eight-item version of the validated Patient Activation Measure (PAM). Total scores were categorized, according to standardized methods, as one of four PAM levels of activation: Level 1 (lowest activation) through Level 4 (highest activation). The primary outcome measure was total 30-day post-discharge hospital utilization, defined as total emergency department (ED) visits plus hospital readmissions including observation stays. Poisson regression was used to control for confounding.

RESULTS

Of the 695 subjects, 67 (9.6 %) were PAM Level 1, 123 (17.7 %) were Level 2, 193 (27.8 %) were Level 3, and 312 (44.9 %) were Level 4. Compared with highly activated patients (PAM Level 4), a higher rate of 30-day post-discharge hospital utilization was observed for patients at lower levels of activation (PAM Level 1, incident rate ratio [IRR] 1.75, 95 % CI,1.18 to 2.60) and (PAM Level 2, IRR 1.50, 95 % CI 1.06 to 2.13). The rate of returning to the hospital among patients at PAM Level 3 was not statistically different than patients with PAM Level 4 (IRR 1.30, 95 % CI, 0.94 to 1.80). The rate ratio for PAM Level 1 was also higher compared with Level 4 for ED use alone (1.68(1.07 to 2.63)) and for hospital readmissions alone (1.93 [1.22 to 3.06]).

CONCLUSION

Hospitalized adult medical patients in an urban academic safety net hospital with lower levels of Patient Activation had a higher rate of post-discharge 30-day hospital utilization.