Importance: When an older adult is hospitalized, where they are discharged is of utmost importance. Fragmented readmissions, defined as readmissions to a different hospital than a patient was previously discharged from, may increase the risk of a nonhome discharge for older adults. However, this risk may be mitigated via electronic information exchange between the admission and readmission hospitals. Objective: To determine the association of fragmented hospital readmissions and electronic information sharing with discharge destination among Medicare beneficiaries. Design, Setting, and Participants: This cohort study retrospectively examined data from Medicare beneficiaries hospitalized for acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, syncope, urinary tract infection, dehydration, or behavioral issues in 2018 and their 30-day readmission for any reason. The data analysis was completed between November 1, 2021, and October 31, 2022. Exposures: Same hospital vs fragmented readmissions and presence of the same health information exchange (HIE) at the admission and readmission hospitals vs no information shared between the admission and readmission hospitals. Main Outcomes and Measures: The main outcome was discharge destination following the readmission, including home, home with home health, skilled nursing facility (SNF), hospice, leaving against medical advice, or dying. Outcomes were examined for beneficiaries with and without Alzheimer disease using logistic regressions. Results: The cohort included 275 189 admission-readmission pairs, representing 268 768 unique patients (mean [SD] age, 78.9 [9.0] years; 54.1% female and 45.9% male; 12.2% Black, 82.1% White, and 5.7% other race and ethnicity). Of the 31.6% fragmented readmissions in the cohort, 14.3% occurred at hospitals that shared an HIE with the admission hospital. Beneficiaries with same hospital/nonfragmented readmissions tended to be older (mean [SD] age, 78.9 [9.0] vs 77.9 [8.8] for fragmented with same HIE and 78.3 [8.7] years for fragmented without HIE; P < .001). Fragmented readmissions were associated with 10% higher odds of discharge to an SNF (adjusted odds ratio [AOR], 1.10; 95% CI, 1.07-1.12) and 22% lower odds of discharge home with home health (AOR, 0.78; 95% CI, 0.76-0.80) compared with same hospital/nonfragmented readmissions. When the admission and readmission hospital shared an HIE, beneficiaries had 9% to 15% higher odds of discharge home with home health (patients without Alzheimer disease: AOR, 1.09 [95% CI, 1.04-1.16]; patients with Alzheimer disease: AOR, 1.15 [95% CI, 1.01-1.32]) compared with fragmented readmissions where information sharing was not available. Conclusions and Relevance: In this cohort study of Medicare beneficiaries with 30-day readmissions, whether a readmission is fragmented was associated with discharge destination. Among fragmented readmissions, shared HIE across admission and readmission hospitals was associated with higher odds of discharge home with home health. Efforts to study the utility of HIE for care coordination for older adults should be pursued.
Background: Although electronic health information sharing is expanding nationally, it is unclear whether electronic health information sharing improves patient outcomes, particularly for patients who are at the highest risk of communication challenges, such as older adults with Alzheimer disease. Objective: To determine the association between hospital-level health information exchange (HIE) participation and in-hospital or postdischarge mortality among Medicare beneficiaries with Alzheimer disease or 30-day readmissions to a different hospital following an admission for one of several common conditions. Methods: This was a cohort study of Medicare beneficiaries with Alzheimer disease who had one or more 30-day readmissions in 2018 following an initial admission for select Hospital Readmission Reduction Program conditions (acute myocardial infarction, congestive heart failure, chronic obstructive pulmonary disease, and pneumonia) or common reasons for hospitalization among older adults with Alzheimer disease (dehydration, syncope, urinary tract infection, or behavioral issues). Using unadjusted and adjusted logistic regression, we examined the association between electronic information sharing and in-hospital mortality during the readmission or mortality in the 30 days following the readmission. Results: A total of 28,946 admission-readmission pairs were included. Beneficiaries with same-hospital readmissions were older (aged 81.1, SD 8.6 years) than beneficiaries with readmissions to different hospitals (age range 79.8-80.3 years, P<.001). Compared to admissions and readmissions to the same hospital, beneficiaries who had a readmission to a different hospital that shared an HIE with the admission hospital had 39% lower odds of dying during the readmission (adjusted odds ratio [AOR] 0.61, 95% CI 0.39-0.95). There were no differences in in-hospital mortality observed for admission-readmission pairs to different hospitals that participated in different HIEs (AOR 1.02, 95% CI 0.82-1.28) or to different hospitals where one or both hospitals did not participate in HIE (AOR 1.25, 95% CI 0.93-1.68), and there was no association between information sharing and postdischarge mortality. Conclusions: These results indicate that information sharing between unrelated hospitals via a shared HIE may be associated with lower in-hospital, but not postdischarge, mortality for older adults with Alzheimer disease. In-hospital mortality during a readmission to a different hospital was higher if the admission and readmission hospitals participated in different HIEs or if one or both hospitals did not participate in an HIE. Limitations of this analysis include that HIE participation was measured at the hospital level, rather than at the provider level. This study provides some evidence that HIEs can improve care for vulnerable populations receiving acute care from different hospitals.
Background: Given financial and clinical implications of readmissions after total hip arthroplasty (THA) and the potential for varied expenditures related to a hospital's teaching status, this study sought to characterize 90-day hospital readmission patterns and assess likelihood of readmission based on teaching designation of a Medicare beneficiaries’ (MB's) index THA hospital. Methods: Retrospective analysis of 2016-2018 Centers for Medicare and Medicaid Services-linked data identified primary THA hospitalizations and readmissions within 90 days. Hospitals were categorized as teaching or nonteaching (Council of Teaching Hospitals and Health Systems). Chi-squared analysis and Fisher exact test assessed differences between readmission hospitals and the index hospital teaching status. Multivariate logistic regression models estimated risk-adjusted probability of experiencing at least one 90-day readmission. Results: Analysis identified 433,959 index THA admissions with an all-cause 90-day readmission rate of 9.12%. Most readmissions were to the same hospital regardless of index THA hospital teaching status (67.5% index teaching; 68.2% index nonteaching). Crossover in hospital teaching status from the index procedure to readmission location was more common for those with index THA at a teaching hospital (18.9%) than for MBs with index THA performed at a nonteaching hospital (6.2%). Controlling for patient characteristics, no significant relationship was found between 90-day readmission and index hospital teaching status (odds ratio 0.98, confidence interval 0.947–1.011). Conclusions: Overall, while certain patterns of readmission after the index THA were observed, after controlling for patient characters and comorbidities, there was no significant association between 90-day all-cause readmission and index hospital teaching status.
PURPOSE
Practice facilitation is widely recognized as a promising method for achieving large-scale practice redesign. Little is known, however, about the cost of providing practice facilitation to small primary practices from the prospective of an organization providing facilitation activities.
METHODS
We report practice facilitation costs on 19 practices in South Texas that were randomized to receive facilitation activities. The study design assured that each practice received at least 6 practice facilitation visits during the intervention year. We examined only the variable cost associated with practice facilitation activities. Fixed or administrative costs of providing facilitation actives were not captured. All facilitator activities (time, mileage, and materials) were self-reported by the practice facilitators and recorded in spreadsheets.
RESULTS
The median total variable cost of all practice facilitation activities from start-up through monitoring, including travel and food, was $9,670 per practice (ranging from $8,050 to $15,682). Median travel and food costs were an additional $2,054 but varied by clinic. Approximately 50% of the total cost is attributable to practice assessment and start-up activities, with another 31% attributable to practice facilitation visits. Sensitivity analysis suggests that a 24-visit practice facilitation protocol increased estimated median total variable costs of all practice facilitation activities only by $5,428, for a total of $15,098.
CONCLUSIONS
We found that, depending on the facilitators wages and the intensity of the intervention, the cost of practice facilitation ranges between $9,670 and $15,098 per practice per year and have the potential to be cost-neutral from a societal prospective if practice facilitation results in 2 fewer hospitalizations per practice per year.
Background: There are limited data on factors associated with 30-day readmissions and the frequency of avoidable readmissions among patients with stroke and other cerebrovascular disease. Methods: University HealthSystem Consortium (UHC) database records were used to identify patients discharged with a diagnosis of stroke or other cerebrovascular disease at a university hospital from January 1, 2007 to December 31, 2009 and readmitted within 30 days to the index hospital. Logistic regression models were used to identify patient and clinical characteristics associated with 30-day readmission. Two neurologists performed chart reviews on readmissions to identify avoidable cases. Results: Of 2706 patients discharged during the study period, 174 patients had 178 readmissions (6.4%) within 30 days. The only factor associated with 30-day readmission was the index length of stay >10 days (vs <5 days; odds ratio [OR] 2.3, 95% CI [1.4, 3.7]). Of 174 patients readmitted within 30 days (median time to readmission 10 days), 92 (53%) were considered avoidable readmissions including 38 (41%) readmitted for elective procedures within 30 days of discharge, 27 (29%) readmitted after inadequate outpatient care coordination, 15 (16%) readmitted after incomplete initial evaluations, 8 (9%) readmitted due to delayed palliative care consultation, and 4 (4%) readmitted after being discharged with inadequate discharge instructions. Only 5% of the readmitted patients had outpatient follow-up recommended within 1 week. Conclusions: More than half of the 30-day readmissions were considered avoidable. Coordinated timing of elective procedures and earlier outpatient follow-up may prevent the majority of avoidable readmissions among patients with stroke and other cerebrovascular disease.
Background:
Practice facilitation (PF) is an implementation strategy now commonly used in primary care settings for improvement initiatives. PF occurs when a trained external facilitator engages and supports the practice in its change efforts. The purpose of this group-randomized trial is to assess PF as an intervention to improve the delivery of chronic illness care in primary care.
Methods:
A randomized trial of 40 small primary care practices who were randomized to an initial or a delayed intervention (control) group. Trained practice facilitators worked with each practice for one year to implement tailored changes to improve delivery of diabetes care within the Chronic Care Model framework. The Assessment of Chronic Illness Care (ACIC) survey was administered at baseline and at one-year intervals to clinicians and staff in both groups of practices. Repeated-measures analyses of variance were used to assess the main effects (mean differences between groups) and the within-group change over time.
Results:
There was significant improvement in ACIC scores (p < 0.05) within initial intervention practices, from 5.58 (SD 1.89) to 6.33 (SD 1.50), compared to the delayed intervention (control) practices where there was a small decline, from 5.56 (SD 1.54) to 5.27 (SD 1.62). The increase in ACIC scores was sustained one year after withdrawal of the PF intervention in the initial intervention group, from 6.33 (SD 1.50) to 6.60 (SD 1.94), and improved in the delayed intervention (control) practices during their one year of PF intervention, from 5.27 (SD 1.62) to 5.99 (SD 1.75).
Conclusions:
Practice facilitation resulted in a significant and sustained improvement in delivery of care consistent with the CCM as reported by those involved in direct patient care in small primary care practices. The impact of the observed change on clinical outcomes remains uncertain.
Trial registration:
This protocol followed the CONSORT guidelines and is registered per ICMJE guidelines: Clinical Trial Registration Number: NCT00482768.
Background
Most patients with type 2 diabetes have suboptimal control of their glucose, blood pressure (BP), and lipids – three risk factors for diabetes complications. Although the chronic care model (CCM) provides a roadmap for improving these outcomes, developing theoretically sound implementation strategies that will work across diverse primary care settings has been challenging. One explanation for this difficulty may be that most strategies do not account for the complex adaptive system (CAS) characteristics of the primary care setting. A CAS is comprised of individuals who can learn, interconnect, self-organize, and interact with their environment in a way that demonstrates non-linear dynamic behavior. One implementation strategy that may be used to leverage these properties is practice facilitation (PF). PF creates time for learning and reflection by members of the team in each clinic, improves their communication, and promotes an individualized approach to implement a strategy to improve patient outcomes.
Specific objectives
The specific objectives of this protocol are to: evaluate the effectiveness and sustainability of PF to improve risk factor control in patients with type 2 diabetes across a variety of primary care settings; assess the implementation of the CCM in response to the intervention; examine the relationship between communication within the practice team and the implementation of the CCM; and determine the cost of the intervention both from the perspective of the organization conducting the PF intervention and from the perspective of the primary care practice.
Intervention
The study will be a group randomized trial conducted in 40 primary care clinics. Data will be collected on all clinics, with 60 patients in each clinic, using a multi-method assessment process at baseline, 12, and 24 months. The intervention, PF, will consist of a series of practice improvement team meetings led by trained facilitators over 12 months. Primary hypotheses will be tested with 12-month outcome data. Sustainability of the intervention will be tested using 24 month data. Insights gained will be included in a delayed intervention conducted in control practices and evaluated in a pre-post design.
Primary and secondary outcomes
To test hypotheses, the unit of randomization will be the clinic. The unit of analysis will be the repeated measure of each risk factor for each patient, nested within the clinic. The repeated measure of glycosylated hemoglobin A1c will be the primary outcome, with BP and Low Density Lipoprotein (LDL) cholesterol as secondary outcomes. To study change in risk factor level, a hierarchical or random effect model will be used to account for the nesting of repeated measurement of risk factor within patients and patients within clinics.
This protocol follows the CONSORT guidelines and is registered per ICMJE guidelines:
Background
Schizophrenia is often a persistent and costly illness that requires continued treatment with antipsychotics. Differences among antipsychotics on efficacy, safety, tolerability, adherence, and cost have cost-effectiveness implications for treating schizophrenia. This study compares the cost-effectiveness of oral olanzapine, oral risperidone (at generic cost, primary comparator), quetiapine, ziprasidone, and aripiprazole in the treatment of patients with schizophrenia from the perspective of third-party payers in the U.S. health care system.
Methods
A 1-year microsimulation economic decision model, with quarterly cycles, was developed to simulate the dynamic nature of usual care of schizophrenia patients who switch, continue, discontinue, and restart their medications. The model captures clinical and cost parameters including adherence levels, relapse with and without hospitalization, quality-adjusted life years (QALYs), treatment discontinuation by reason, treatment-emergent adverse events, suicide, health care resource utilization, and direct medical care costs. Published medical literature and a clinical expert panel were used to develop baseline model assumptions. Key model outcomes included mean annual total direct cost per treatment, cost per stable patient, and incremental cost-effectiveness values per QALY gained.
Results
The results of the microsimulation model indicated that olanzapine had the lowest mean annual direct health care cost ($8,544) followed by generic risperidone ($9,080). In addition, olanzapine resulted in more QALYs than risperidone (0.733 vs. 0.719). The base case and multiple sensitivity analyses found olanzapine to be the dominant choice in terms of incremental cost-effectiveness per QALY gained.
Conclusion
The utilization of olanzapine is predicted in this model to result in better clinical outcomes and lower total direct health care costs compared to generic risperidone, quetiapine, ziprasidone, and aripiprazole. Olanzapine may, therefore, be a cost-effective therapeutic option for patients with schizophrenia.
Aim: Persons with concomitant heart failure (HF) and diabetes mellitus (DM) have complicated, competing, self-care expectations and treatment regimens that may reduce quality of life (QOL). This randomized controlled trial tested an integrated self-care intervention on outcomes of HF and DM QOL, physical function and physical activity (PA).
Methods: Participants with HF and DM (n=134, mean age 57.4 ± 11 years, 66% men, 69% minority) were randomized to usual care attention control (control) or intervention groups. The control group received standard HF and DM educational brochures with follow up phone contact; Intervention received education/counseling on combined HF and DM self-care (diet, medications, self-monitoring, symptoms, and PA) with follow up home visit and phone counseling. Measures including questionnaires for HF and DM-specific, and overall QOL; Physical activity frequency; and physical function (6 minute walk test; 6MWT) were obtained at baseline, 3 and 6 months. Analysis included mixed models with a priori post-hoc tests.
Results: Adjusting for age, body mass index, and comorbidity, the intervention group improved HF total (p=.002) and physical (p<.001) QOL scores at 3 months with retention of improvements at 6 months, improved emotional QOL scores compared to control at 3 months (p=.04), and improved health status ratings (p=.04) at 6 Months compared to baseline. The intervention group improved 6MWT distance (924 feet vs 952 feet, p=. 03) while control declined (834 vs 775 feet) (F1, 63=6.86, p=.01). The intervention group increased self-reported PA between baseline and 6M (p=.01).
Conclusions: An integrated HF and DM self-care intervention improved perceived HF and general QOL but not DM QOL. Improved physical functioning and self-reported PA were also observed with the integrated self-care intervention. Further study of the HF and DM integrated self-care intervention on other outcomes such as hospitalization and cost is warranted.