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Background As adolescents gain autonomy, it remains important for parents to be involved with diabetes management to avoid deterioration in glycemic control. Technologies for self‐monitoring of blood glucose (SMBG) allow for remote monitoring in real‐time by parents. This research compared 3 strategies for improving SMBG and diabetes self‐care in the short‐term. These strategies were: (1) health information technology (HIT)‐enhanced blood glucose meter that shared blood glucose data among patients, their parent, and care providers, and allowed for text messaging; (2) family‐centered goal setting; and (3) a combination of (1) and (2). Methods One hundred twenty‐eight participants enrolled; 97 adolescent‐parent pairs attended clinic at 3‐month intervals during the 6‐month intervention. Differences between treatment groups were evaluated using analysis of variance (ANOVAs) for continuous variables and χ2 tests for frequencies. Within patient changes were evaluated using paired t tests. Results Participants in the HIT‐enhanced SMBG group had no change in mean glycosylated hemoglobin (HbA1c). Participants assigned to family‐centered goal setting had a non‐significant decrease in HbA1c of −0.3% (P = .26) from baseline to 6 months. Participants in the combined approach had a significant decrease in HbA1c of −0.6% (P = .02) from baseline to 3 months, but the decrease of −0.4% at 6 months was non‐significant (P = .51). The change in HbA1c from baseline to 3 months was greater for the combined approach than for the HIT‐enhanced SMBG (P = .05) or family‐centered goal setting (P = .01). Conclusions Our data suggest that utilizing the family‐centered goal setting strategy when implementing HIT‐enhanced diabetes technology deserves further study.

BackgroundTime-sensitive alerts are among the many types of clinical notifications delivered to physicians’ secure InBaskets within commercial electronic health records (EHRs). A delayed alert review can impact patient safety and compromise care.ObjectiveTo characterize factors associated with opening of non-interruptive time-sensitive alerts delivered into primary care provider (PCP) InBaskets.Design and ParticipantsWe analyzed data for 799 automated alerts. Alerts highlighted actionable medication concerns for older patients post-hospital discharge (2010–2011). These were study-generated alerts sent 3 days post-discharge to InBaskets for 75 PCPs across a multisite healthcare system, and represent a subset of all urgent InBasket notifications.Main MeasuresUsing EHR access and audit logs to track alert opening, we performed bivariate and multivariate analyses calculating associations between patient characteristics, provider characteristics, contextual factors at the time of alert delivery (number of InBasket notifications, weekday), and alert opening within 24 h.Key ResultsAt the time of alert delivery, the PCPs had a median of 69 InBasket notifications and had received a median of 379.8 notifications (IQR 295.0, 492.0) over the prior 7 days. Of the 799 alerts, 47.1% were opened within 24 h. Patients with longer hospital stays (>4 days) were marginally more likely to have alerts opened (OR 1.48 [95% CI 1.00–2.19]). Alerts delivered to PCPs whose InBaskets had a higher number of notifications at the time of alert delivery were significantly less likely to be opened within 24 h (top quartile >157 notifications: OR 0.34 [95% CI 0.18–0.61]; reference bottom quartile ≤42). Alerts delivered on Saturdays were also less likely to be opened within 24 h (OR 0.18 [CI 0.08–0.39]).ConclusionsThe number of total InBasket notifications and weekend delivery may impact the opening of time-sensitive EHR alerts. Further study is needed to support safe and effective approaches to care team management of InBasket notifications.

Immobilisation predicts adverse outcomes in patients in the surgical intensive care unit (SICU). Attempts to mobilise critically ill patients early after surgery are frequently restricted, but we tested whether early mobilisation leads to improved mobility, decreased SICU length of stay, and increased functional independence of patients at hospital discharge. We did a multicentre, international, parallel-group, assessor-blinded, randomised controlled trial in SICUs of five university hospitals in Austria (n=1), Germany (n=1), and the USA (n=3). Eligible patients (aged 18 years or older, who had been mechanically ventilated for <48 h, and were expected to require mechanical ventilation for ≥24 h) were randomly assigned (1:1) by use of a stratified block randomisation via restricted web platform to standard of care (control) or early, goal-directed mobilisation using an inter-professional approach of closed-loop communication and the SICU optimal mobilisation score (SOMS) algorithm (intervention), which describes patients’ mobilisation capacity on a numerical rating scale ranging from 0 (no mobilisation) to 4 (ambulation). We had three main outcomes hierarchically tested in a prespecified order: the mean SOMS level patients achieved during their SICU stay (primary outcome), and patient's length of stay on SICU and the mini-modified functional independence measure score (mmFIM) at hospital discharge (both secondary outcomes). This trial is registered with ClinicalTrials.gov (NCT01363102). Between July 1, 2011, and Nov 4, 2015, we randomly assigned 200 patients to receive standard treatment (control; n=96) or intervention (n=104). Intention-to-treat analysis showed that the intervention improved the mobilisation level (mean achieved SOMS 2·2 [SD 1·0] in intervention group vs 1·5 [0·8] in control group, p<0·0001), decreased SICU length of stay (mean 7 days [SD 5–12] in intervention group vs 10 days [6–15] in control group, p=0·0054), and improved functional mobility at hospital discharge (mmFIM score 8 [4–8] in intervention group vs 5 [2–8] in control group, p=0·0002). More adverse events were reported in the intervention group (25 cases [2·8%]) than in the control group (ten cases [0·8%]); no serious adverse events were observed. Before hospital discharge 25 patients died (17 [16%] in the intervention group, eight [8%] in the control group). 3 months after hospital discharge 36 patients died (21 [22%] in the intervention group, 15 [17%] in the control group). Early, goal-directed mobilisation improved patient mobilisation throughout SICU admission, shortened patient length of stay in the SICU, and improved patients’ functional mobility at hospital discharge. Jeffrey and Judy Buzen.

Background Lower mammography screening rates among minority and low income women contribute to increased morbidity and mortality from breast cancer. Objective To evaluate the effect of a patient navigation intervention on adherence rates to biennial screening mammography among women engaged in primary care at an inner-city academic medical center. Design Quality improvement intervention with a concurrent control group, conducted from February to November of 2008. Study Subjects All women in a hospital-based primary care practice aged 51–70 years. Subjects were randomized at the level of their primary care provider, such that half of the patients in the practice received the intervention, while the other half received usual care. Interventions Intervention subjects whose last mammogram was >18 months prior received a combination of telephone calls and reminder letters from patient navigators trained to identify barriers to care. Navigators were integrated into primary care teams and interacted directly with patients, providers, and radiology to coordinate care. Navigators utilized an electronic report to track subjects. Adherence rates to biennial mammography were assessed in intervention and control groups at baseline and post-intervention. Key Results A total of 3,895 women were randomized to intervention (n = 1,817) and control (n = 2,078) groups. Mean age was 60, 71% were racial/ethnic minorities, 23% were non-English speaking, and 63% had public or no health insurance. At baseline, there was no difference in mammography adherence between the control and intervention groups (78%, respectively, p = 0.55). After the 9-month intervention, mammogram adherence was higher in the intervention group compared with the control group (87% vs. 76%, respectively, p < 0.001). Except among Hispanic women who demonstrated high rates in both the intervention and control groups (85% and 83%, respectively), all racial/ethnic and insurance groups demonstrated higher adherence in the intervention group. Conclusions Patient navigation improves biennial mammography rates for inner city, low income, minority populations.

Background Delirium is a common and serious condition, which affects many of our older hospitalised patients. It is an indicator of severe underlying illness and requires early diagnosis and prompt treatment, associated with poor survival, functional outcomes with increased risk of institutionalisation following the delirium episode in the acute care setting. We describe a new model of delirium care in the acute care setting, titled Geriatric Monitoring Unit (GMU) where the important concepts of delirium prevention and management are integrated. We hypothesize that patients with delirium admitted to the GMU would have better clinical outcomes with less need for physical and psychotropic restraints compared to usual care. Methods/Design GMU models after the Delirium Room with adoption of core interventions from Hospital Elder Life Program and use of evening bright light therapy to consolidate circadian rhythm and improve sleep in the elderly patients. The novelty of this approach lies in the amalgamation of these interventions in a multi-faceted approach in acute delirium management. GMU development thus consists of key considerations for room design and resource planning, program specific interventions and daily core interventions. Assessments undertaken include baseline demographics, comorbidity scoring, duration and severity of delirium, cognitive, functional measures at baseline, 6 months and 12 months later. Additionally we also analysed the pre and post-GMU implementation knowledge and attitude on delirium care among staff members in the geriatric wards (nurses, doctors) and undertook satisfaction surveys for caregivers of patients treated in GMU. Discussion This study protocol describes the conceptualization and implementation of a specialized unit for delirium management. We hypothesize that such a model of care will not only result in better clinical outcomes for the elderly patient with delirium compared to usual geriatric care, but also improved staff knowledge and satisfaction. The model may then be transposed across various locations and disciplines in the acute hospital where delirious patients could be sited. Trial Registration Current Controlled Trials ISRCTN52323811

BackgroundCessation counseling and pharmacotherapy are recommended for hospitalized smokers, but better coordination between cessation counselors and providers might improve utilization of pharmacotherapy and enhance smoking cessation.ObjectiveTo compare smoking cessation counseling combined with care coordination post-hospitalization to counseling alone on uptake of pharmacotherapy and smoking cessation.DesignUnblinded, randomized clinical trialParticipantsHospitalized smokers referred from primarily rural hospitalsInterventionsCounseling only (C) consisted of telephone counseling provided during the hospitalization and post-discharge. Counseling with care coordination (CCC) provided similar counseling supplemented by feedback to the smoker’s health care team and help for the smoker in obtaining pharmacotherapy. At 6 months post-hospitalization, persistent smokers were re-engaged with either CCC or C.Main MeasuresUtilization of pharmacotherapy and smoking cessation at 3, 6, and 12 months post-discharge.Key ResultsAmong 606 smokers randomized, 429 (70.8%) completed the 12-month assessment and 580 (95.7%) were included in the primary analysis. Use of any cessation pharmacotherapy between 0 and 6 months (55.2%) and between 6 and 12 months (47.1%) post-discharge was similar across treatment arms though use of prescription-only pharmacotherapy between months 6–12 was significantly higher in the CCC group (30.1%) compared with the C group (18.6%) (RR, 1.61 (95% CI, 1.08, 2.41)). Self-reported abstinence rates of 26.2%, 20.3%, and 23.4% at months 3, 6, and 12, respectively, were comparable across the two treatment arms. Of those smoking at month 6, 12.5% reported abstinence at month 12. Validated smoking cessation at 12 months was 19.3% versus 16.9% in the CCC and C groups, respectively (RR, 1.13 (95% CI, 0.80, 1.61)).ConclusionSupplemental care coordination, provided by counselors outside of the health care team, failed to improve smoking cessation beyond that achieved by cessation counseling alone. Re-engagement of smokers 6 months post-discharge can lead to new quitters, at which time care coordination might facilitate use of prescription medications.Trial RegistrationNCT01063972

ABSTRACT BACKGROUND Rehospitalizations within 30 days of discharge are responsible for a large portion of healthcare spending. One approach to preventing rehospitalizations is early follow-up, usually defined as an office visit with a primary care physician within 7 days of discharge—an approach that is being incentivized by health plans. However, evidence regarding its effectiveness is limited. OBJECTIVE We aimed to determine whether an office visit with a primary care physician within 7 days after discharge is associated with 30-day rehospitalization. DESIGN This was an observational study set within a randomized trial. PARTICIPANTS The study included patients age 65 and older receiving care from a multi-specialty group practice and discharged from hospital to home between 26 August 2010 and 25 August 2011. To control for confounding, we identified characteristics of patients and hospital stays that are predictive of rehospitalization, and also developed high-dimensional propensity scores. Analyses used Cox proportional hazards models and took into account varying amounts of opportunity time for office visits. MAIN MEASURES We looked at 30-day rehospitalizations at any hospital. KEY RESULTS Of 3,661 patients discharged to home during the study year, 707 (19.3 %) were rehospitalized within 30 days. Patients receiving an office visit within 7 days numbered 1,808 (49.4 %), and of these, 1,000 (27.3 %) were with a primary care physician. In models predicting rehospitalization, stratified on deciles of propensity score and controlling for additional confounders, the hazard ratios associated with office visits with a primary care physician within 7 days were 0.98 (95 % CI 0.80, 1.21); for visits with any physician, the hazard ratio was HR 1.04, (95 % CI 0.87, 1.25). CONCLUSIONS We found no protective effect for office visits within 7 days. Such visits may need to be specifically focused on a range of issues related to the specific reasons why patients are rehospitalized. It is likely that outpatient visits will need to be set within comprehensive transition programs.

Background Insight in the natural course of care dependency of vulnerable older persons in long-term care facilities (LTCF) is essential to organize and optimize individual tailored care. We examined changes in care dependency in LTCF residents over two 6-month periods, explored the possible predictive factors of change and the effect of care dependency on mortality. Methods A prospective follow-up study in 21 Dutch long-term care facilities. 890 LTCF residents, median age 84 (Interquartile range 79–88) years participated. At baseline, 6 and 12 months, care dependency was assessed by the nursing staff with the Care Dependency Scale (CDS), range 15–75 points. Since the median CDS score differed between men and women (47.5 vs. 43.0, P  = 0.013), CDS groups (low, middle and high) were based on gender-specific 33% of CDS scores at baseline and 6 months. Results At baseline, the CDS groups differed in median length of stay on the ward, urine incontinence and dementia (all P  < 0.001); participants in the low CDS group stayed longer, had more frequent urine incontinence and more dementia. They had also the highest mortality rate (log rank 32.2; df = 2; P for trend <0.001). Per point lower in CDS score, the mortality risk increased with 2% (95% CI 1%-3%). Adjustment for age, gender, cranberry use, LTCF, length of stay, comorbidity and dementia showed similar results. A one point decrease in CDS score between 0 and 6 months was related to an increased mortality risk of 4% (95% CI 3%-6%). At the 6-month follow-up, 10% improved to a higher CDS group, 65% were in the same, and 25% had deteriorated to a lower CDS group; a similar pattern emerged at 12-month follow-up. Gender, age, urine incontinence, dementia, cancer and baseline care dependency status, predicted an increase in care dependency over time. Conclusion The majority of residents were stable in their care dependency status over two subsequent 6-month periods. Highly care dependent residents showed an increased mortality risk. Awareness of the natural course of care dependency is essential to residents and their formal and informal caregivers when considering therapeutic and end-of-life care options.

Background Efforts to improve primary care diabetes management have assessed strategies across heterogeneous groups of patients and practices. However, there is substantial variability in how well practices implement interventions and achieve desired outcomes. Objective To examine practice contextual features that moderate intervention effectiveness. Design Secondary analysis of data from a cluster randomized trial of three approaches for implementing the Chronic Care Model to improve diabetes care. Participants Forty small to mid-sized primary care practices participated, with 522 clinician and staff member surveys. Outcomes were assessed for 822 established patients with a diagnosis of type 2 diabetes who had at least one visit to the practice in the 18 months following enrollment. Main Measures The primary outcome was a composite measure of diabetes process of care, ascertained by chart audit, regarding nine quality measures from the American Diabetes Association Physician Recognition Program: HgA1c, foot exam, blood pressure, dilated eye exam, cholesterol, nephropathy screen, flu shot, nutrition counseling, and self-management support. Data from practices included structural and demographic characteristics and Practice Culture Assessment survey subscales (Change Culture, Work Culture, Chaos). Key Results Across the three implementation approaches, demographic/structural characteristics (rural vs. urban + .70(p = .006), +2.44(p < .001), −.75(p = .004)); Medicaid: <20 % vs. ≥20 % (−.20(p = .48), +.75 (p = .08), +.60(p = .02)); practice size: <4 clinicians vs. ≥4 clinicians (+.56(p = .02), +1.96( p < .001), +.02(p = .91)); practice Change Culture (high vs. low: −.86(p = .048), +1.71(p = .005), +.34(p = .22)), Work Culture (high vs. low: −.67(p = .18), +2.41(p < .001), +.67(p = .005)) and variability in practice Change Culture (high vs. low: −.24(p = .006), −.20(p = .0771), −.44(p = .0019) and Work Culture (high vs. low: +.56(p = .3160), −1.0(p = .008), −.25 (p = .0216) were associated with trajectories of change in diabetes process of care, either directly or differentially by study arm. Conclusions This study supports the need for broader use of methodological approaches to better examine contextual effects on implementation and effectiveness of quality improvement interventions in primary care settings.