Background and Purpose—Risk-standardized hospital readmission rates are used as publicly reported measures reflecting quality of care. Valid risk-standardized models adjust for differences in patient-level factors across hospitals. We conducted a systematic review of peer-reviewed literature to identify models that compare hospital-level poststroke readmission rates, evaluate patient-level risk scores predicting readmission, or describe patient and process-of-care predictors of readmission after stroke. Methods—Relevant studies in English published from January 1989 to July 2010 were identified using MEDLINE, PubMed, Scopus, PsycINFO, and all Ovid Evidence-Based Medicine Reviews. Authors of eligible publications reported readmission within 1 year after stroke hospitalization and identified ≥1 predictors of readmission in risk-adjusted statistical models. Publications were excluded if they lacked primary data or quantitative outcomes, reported only composite outcomes, or had <100 patients. Results—Of 374 i...

Predictors of Hospital Readmission After Stroke A Systematic Review

Background. Chronic upper extremity impairment due to stroke has significant medical, psychosocial, and financial consequences, but few studies have examined the effectiveness of rehabilitation therapy during the chronic stroke period. Objective. To test the safety and efficacy of the MIT-Manus robotic device for chronic upper extremity impairment following stroke. Methods. The VA Cooperative Studies Program initiated a multicenter, randomized, controlled trial in November 2006 (VA ROBOTICS). Participants with upper extremity impairment ≥6 months poststroke were randomized to robot-assisted therapy (RT), intensive comparison therapy (ICT), or usual care (UC). RT and ICT consisted of three 1-hour treatment sessions per week for 12 weeks. The primary outcome was change in the Fugl-Meyer Assessment upper extremity motor function score at 12 weeks relative to baseline. Secondary outcomes included the Wolf Motor Function Test and the Stroke Impact Scale. Results. A total of 127 participants were randomized: 49...

/pdf/multicenter-randomized-trial-of-robot-assisted-53orv18nik.pdf

Multicenter Randomized Trial of Robot-Assisted Rehabilitation for Chronic Stroke: Methods and Entry Characteristics for VA ROBOTICS:

Background and Purpose— Stroke is the fourth-leading cause of death and a leading cause of long-term major disability in the United States. Measuring outcomes after stroke has important policy implications. The primary goals of this consensus statement are to (1) review statistical considerations when evaluating models that define hospital performance in providing stroke care; (2) discuss the benefits, limitations, and potential unintended consequences of using various outcome measures when evaluating the quality of ischemic stroke care at the hospital level; (3) summarize the evidence on the role of specific clinical and administrative variables, including patient preferences, in risk-adjusted models of ischemic stroke outcomes; (4) provide recommendations on the minimum list of variables that should be included in risk adjustment of ischemic stroke outcomes for comparisons of quality at the hospital level; and (5) provide recommendations for further research.

Methods and Results— This statement gives an overview of statistical considerations for the evaluation of hospital-level outcomes after stroke and provides a systematic review of the literature for the following outcome measures for ischemic stroke at 30 days: functional outcomes, mortality, and readmissions. Data on outcomes after stroke have primarily involved studies conducted at an individual patient level rather than a hospital level. On the basis of the available information, the following factors should be included in all hospital-level risk-adjustment models: age, sex, stroke severity, comorbid conditions, and vascular risk factors. Because stroke severity is the most important prognostic factor for individual patients and appears to be a significant predictor of hospital-level performance for 30-day mortality, inclusion of a stroke severity measure in risk-adjustment models for 30-day outcome measures is recommended. Risk-adjustment models that do not include stroke severity or other recommended variables must provide comparable classification of hospital performance as models that include these variables. Stroke severity and other variables that are included in risk-adjustment models should be standardized across sites, so that their reliability and accuracy are equivalent. There is a pressing need for research in multiple areas to better identify methods and metrics to evaluate outcomes of stroke care.

Conclusions— There are a number of important methodological challenges in undertaking risk-adjusted outcome comparisons to assess the quality of stroke care in different hospitals. It is important for stakeholders to recognize these challenges and for there to be a concerted approach to improving the methods for quality assessment and improvement.

Risk adjustment of ischemic stroke outcomes for comparing hospital performance: a statement for healthcare professionals from the American Heart Association/American Stroke Association.

Importance Primary care services based at home have the potential to reduce the likelihood of hospitalization among older adults with multiple chronic diseases. Objective To characterize the association between enrollment in Home-Based Primary Care (HBPC), a national home care program operated by the US Department of Veterans Affairs (VA), and hospitalizations owing to an ambulatory care–sensitive condition among older veterans with diabetes mellitus. Design and Setting Retrospective cohort study. Patients admitted to VA and non-VA hospitals were followed up from January 1, 2006, through December 31, 2010. Participants Veterans 67 years or older who were fee-for-service Medicare beneficiaries, were diagnosed as having diabetes mellitus and at least 1 other chronic disease, and had at least 1 admission to a VA or non-VA hospital in 2005 or 2006. Exposures Enrollment in HBPC, defined as a minimum of 2 HBPC encounters during the study period. Main Outcomes and Measures Admission to VA and non-VA hospitals owing to an ambulatory care–sensitive condition, as measured by the Agency for Healthcare Research and Quality’s Prevention Quality Indicators in VA medical records and Medicare claims. Outcomes were analyzed using distance from the veteran’s residence to a VA facility that provides HBPC as an instrumental variable. Results Among 56 608 veterans, 1978 enrolled in HBPC. These patients were older (mean age, 79.1 vs 77.1 years) and had more chronic diseases (eg, 59.2% vs 53.5% had congestive heart failure). Multivariable predictors for HBPC enrollment included paralysis (odds ratio [OR], 2.11; 95% CI, 1.63-2.74), depression (OR, 1.99; 95% CI, 1.70-2.34), congestive heart failure (OR, 1.36; 95% CI, 1.17-1.58), and distance from the nearest HBPC-providing VA facility (OR, 0.59; 95% CI, 0.50-0.70 for >10-30 vs Conclusions and Relevance Home-Based Primary Care is associated with a decreased probability of ambulatory care–sensitive condition hospitalization among elderly veterans with diabetes mellitus. In accountable care models, HBPC may have an important role in the management of older adults with multiple chronic diseases.

https://jamanetwork.com/journals/jamainternalmedicine/articlepdf/1904760/ioi140089.pdf

Home-based primary care and the risk of ambulatory care-sensitive condition hospitalization among older veterans with diabetes mellitus.

Interhospital fragmentation of care occurs when patients are admitted to different, disconnected hospitals. It has been hypothesized that this type of care fragmentation decreases the quality of care received and increases hospital costs and healthcare utilization. This systematic review aims to synthesize the existing literature exploring the association between interhospital fragmentation of care and patient outcomes. MEDLINE, the Cochrane Library, EMBASE, and the Science Citation Index were systematically searched for studies published up to April 30, 2018 reporting the association between interhospital fragmentation of care and patient outcomes. We included peer-reviewed observational studies conducted in adults that reported measures of association between interhospital care fragmentation and one or more of the following patient outcomes: mortality, hospital length of stay, cost, and subsequent hospital readmission. Seventy-nine full texts were reviewed and 22 met inclusion criteria. Nearly all studies defined fragmentation of care as a readmission to a different hospital than the patient was previously discharged from. The strongest association reported was that between a fragmented readmission and in-hospital or short-term mortality (adjusted odds ratio range 0.95–3.62). Over half of the studies reporting length-of-stay showed longer length of stay in fragmented readmissions. All three studies that investigated healthcare utilization suggested an association between fragmented care and odds of subsequent readmission. The study populations and exposures were too heterogenous to perform a meta-analysis. Our review suggests that fragmented hospital readmissions contribute to increased mortality, longer length-of-stay, and increased risk of readmission to the hospital.

/pdf/patient-outcomes-following-interhospital-care-fragmentation-2c9vc4quk8.pdf

Patient Outcomes Following Interhospital Care Fragmentation: A Systematic Review

Background and Purpose— Many Veteran Health Administration (VHA) enrollees receive health services outside the VHA system. However, limited information is available about poststroke utilization and mortality by veterans who used multiple sources of health care. This study assessed the likelihood of 12-month poststroke rehospitalization and mortality of veterans who used VHA only versus those who used multiple sources of care. Methods— Our retrospective observational study examined veterans living in Florida and diagnosed with acute stroke. We categorized users into 4 groups: VHA-only, VHA-Medicare, VHA-Medicaid, and VHA-Medicare-Medicaid based on their use of each health care program. Logistic regression models were fitted for 12-month poststroke general rehospitalization, recurrent stroke readmission, and mortality, adjusting for sociodemographic and clinical factors. Results— The sample consisted of 29% VHA-only users, 61% VHA-Medicare users, 3% VHA-Medicaid users, and 7% VHA-Medicare-Medicaid triple us...

Multiple System Utilization and Mortality for Veterans With Stroke

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Multiple System Utilization and Mortality for Veterans With Stroke