Skilled Nursing Facility Differences in Readmission Rates by the Diagnosis-Related Group Category of the Initial Hospitalization

Skilled Nursing Facility Differences in Readmission Rates by the Diagnosis-Related Group Category of the Initial Hospitalization

The US Health and Human Services Office of the Inspector General report on nursing homes found that skilled nursing facilities (SNFs) exhibit wide differences in overall hospital readmission rates. Because evidence has been found that hospital readmission rates can be lowered by discharging to specific SNFs, policy makers have started using hospital readmission rates by SNFs as a measure of quality of care patients receive at these facilities.

In a letter to the editor, a group of authors featuring HIP Investigator Dr. Maureen Smith, examined whether SNFs differed substantially in their readmission rates by the DRG category of the initial hospitalization (ie, medically uncomplicated, surgically uncomplicated, medically complicated, or surgically complicated). The authors’ results suggest considerable differences in readmission rates across SNFs by DRG category of the initial hospitalization, despite similar overall readmission rates.

Read the article

View the toolkit

Girl with Diabetes

Factors associated with health psychology use in pediatric type 1 diabetes

Factors associated with health psychology use in pediatric type 1 diabetes

For children with type 1 diabetes (T1D), self-management is complex and requires coordination between a child and his or her family multiple times every day to test blood sugars, determine and administer insulin doses, and adjust as needed. The consequences of suboptimal self-management are a combination of short- and long-term complications, some of which are life-threatening.

In this publication, HIP Investigator Dr. Elizabeth Cox et al. evaluated the prevalence of health psychology use in children with T1D and the association of this use with individual and contextual characteristics.

Read the article

View the toolkit

Doctor checking sugar level

Impact of family‐centered tailoring of pediatric diabetes self‐management resources

Impact of family‐centered tailoring of pediatric diabetes self‐management resources

Behavioral interventions to improve self‐management, glycemic control, or quality of life (QOL) for children with type 1 diabetes have small to moderate positive effects, but a host of challenges diminishes their effectiveness in practice. A group of authors including HIP Investigator, Dr. Elizabeth Cox evaluated the hypothesis that delivering self‐management resources in a family‐centered manner, using PRISM to guide resource selection, will result in better glycemic control and quality of life for children and their parents.

Authors found that tailored self‐management resources may improve outcomes among specific populations, suggesting the need to consider families' self‐management barriers and patient characteristics before implementing self‐management resources.

Read the article

View the toolkit

FCR

System Factors Influencing the Use of a Family-Centered Rounds Checklist

System Factors Influencing the Use of a Family-Centered Rounds Checklist

Checklists are used to operationalize care processes and enhance patient safety; however, checklist implementation is difficult within complex health systems. A family-centered rounds (FCR) checklist increased physician performance of key rounding activities, which were associated with improved parent engagement, safety perceptions, and behaviors. To inform FCR checklist implementation and dissemination, a team of authors including HIP Investigator, Dr. Elizabeth Cox assessed physician compliance with this checklist and factors influencing its use.

Authors found that multiple factors within hospital systems may influence FCR checklist use. Strategies, such as providing rounding schedules and mobile computers, may promote optimal engagement of families during rounds and promote pediatric patient safety.

Read the article

View the toolkit

Doctors in meeting room

Using Stakeholder Values to Promote Implementation of an Evidence-Based Mobile Health Intervention for Addiction Treatment in Primary Care Settings

Using Stakeholder Values to Promote Implementation of an Evidence-Based Mobile Health Intervention for Addiction Treatment in Primary Care Settings

Most evidence-based practices (EBPs) do not find their way into clinical use, including evidence-based mobile health (mHealth) technologies. The literature offers implementers little practical guidance for successfully integrating mHealth into health care systems. HIP Investigator, Dr. Andrew Quanbeck describes a novel decision-framing model that gives implementers a method of eliciting the considerations of different stakeholder groups when they decide whether to implement an EBP.

This paper presents a model implementers may use to elicit stakeholders' considerations when deciding to adopt a new technology, considerations that may then be used to adapt the intervention and tailor implementation, potentially increasing the likelihood of implementation success.

Read the article

View the toolkit

D&I

Building Capacity for Dissemination and Implementation to Maximize Research Impact in a CTSA: The University of Wisconsin Story

Building Capacity for Dissemination and Implementation to Maximize Research Impact in a CTSA: The University of Wisconsin Story

The publication reports results of an 8-year process of stakeholder engagement aimed at buildingcapacity in Dissemination and Implementation (D&I) research at the University of Wisconsin as part of the National Institutes of Health’s Clinical and Translational Science Award (CTSA). HIP Investigators, Dr. Andrew Quanbeck and Dr. Maureen Smith et al. describe how CTSA leaders at UW built a comprehensive system designed to improve the health of the communities statewide by incorporating D&I concepts across the translational research spectrum.

The team also developed a toolkit on HIPxChange that describes resources and activities developed to build D&I capacity at UW’s Institute for Clinical and Translational Research.

Read the article

View the toolkit

HIP Model

A practical model for research with learning health systems: Building and implementing effective complex case management

A practical model for research with learning health systems: Building and implementing effective complex case management

For researchers to contribute meaningfully to the creation of learning health systems, practical tools are required to operationalize existing conceptual frameworks. A team of authors including HIP Investigators, Dr. Maureen Smith and Dr. Menggang Yu describe a model currently in use by the University of Wisconsin Health Innovation Program (HIP). The HIP model consolidates and enhances existing learning health system frameworks by defining specific steps needed to create sustainable change based on research conducted within the health system.

Read the article

View the HIP Model and Tools for Research with Learning Health Systems

View the Case Management Case Management Benefit Scoring System Toolkit

Big Data Word Scramble

The Importance of Health Insurance Claims Data in Creating Learning Health Systems: Evaluating Care for High-Need High-Cost Patients Using the National Patient-Centered Clinical Research Network (PCORNet)

The Importance of Health Insurance Claims Data in Creating Learning Health Systems: Evaluating Care for High-Need High-Cost Patients Using the National Patient-Centered Clinical Research Network (PCORNet)

Case management programs for high-need high-cost patients are spreading rapidly among health systems. PCORNet has substantial potential to support learning health systems in rapidly evaluating these programs, but access to complete patient data on health care utilization is limited as PCORNet is based on electronic health records not health insurance claims data. Because matching cases to comparison patients on baseline utilization is often a critical component of high-quality observational comparative effectiveness research for high-need high-cost patients, limited access to claims may negatively affect the quality of the matching process. A team of authors including HIP Investigators Dr. Maureen Smith and Dr. Menggang Yu sought to determine whether the evaluation of programs for high-need high-cost patients required claims data to match cases to comparison patients.

Read the article

View the toolkit

NNT vs number referred

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits

Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits

Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. HIP Investigator, Dr. Brian Patterson et al. examined the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department visits. This study evaluated several machine learning methodologies for the creation of a risk stratification algorithm using electronic health record data and estimated the effects of a resultant intervention based on algorithm performance in test data.

Read the article

View the toolkit

Patient using tablet

Inpatients Sign On: An Opportunity to Engage Hospitalized Patients and Caregivers Using Inpatient Portals

Inpatients Sign On: An Opportunity to Engage Hospitalized Patients and Caregivers Using Inpatient Portals

Inpatient portals are online patient portals linked to electronic health records that provide hospitalized patients and caregivers secure access to real-time clinical information and tools to enhance their communication with providers and hospital experience. HIP Investigator, Dr. Ryan Coller et al. provided a perspective that inpatient portals are innovative tools poised to engage patients and caregivers during hospitalization and, thus, enhance patient-centered care. This article highlights the potential of using inpatient portals to engage hospitalized patients and caregivers and proposes next steps to evaluate this emerging technology.

Read the article

View the Toolkit

Pages