SBIR-STTR Award

Hospital discharge planning is a frequently occurring and expensive hospital care process done annually for more than 13 million Medicare beneficiaries. The process has multiple steps that require careful, comprehensive assessment to adequately determine patients' present needs, anticipate future needs, make appropriate referral decisions, and coordinate follow-up services. Although the volume of decisions for hospitalized older adults is high, there are no nationally recognized, empirically derived decision support tools in use to assist discharge planners and others in making these important decisions. The completed National Institute of Nursing Research study (RO1- NR07674), and further development and testing, resulted in the patent pending invention called the Discharge Decision Support System (D2S2) 2,3 This invention is poised for commercialization by our company, RightCare Solutions. Based on a prediction model of patient symptoms and other characteristics, and referral decisions made by experts, the D2S2 is a valid and reliable decision tool that identifies which hospitalized patients should be considered for referral for post-acute care (PAC) such as home care or skilled nursing facility.3 The quality of these decisions determines whether older adults receive the PAC services they need, to return, and remain successfully in their homes. The proposed study purpose is to increase the commercial application of the D2S2 by increasing the speed of delivery, sophistication, and dissemination of the decision support through automation. A second aim will evaluate the implementation and impact on readmissions. The study involves technology development to assist clinicians in timely use and delivery of the D2S2 advice. These enhancements will guide clinicians to anticipate and better match services to patients' needs more quickly and accurately. Completion of these aims will result in successful production of a marketable, technologically innovative, and highly effective decision support tool that directs patients to the "right care".

Public Health Relevance:
This decision support software will enhance the referral decision making of hospital clinicians as they prepare patients for hospital discharge. Development of this product will improve identification of patients who would benefit from care after hospital discharge by providing expert advice and additional information about patients. Patients who have their needs met are more likely to have good outcomes.

Public Health Relevance Statement:
This decision support software will enhance the referral decision making of hospital clinicians as they prepare patients for hospital discharge. Development of this product will improve identification of patients who would benefit from care after hospital discharge by providing expert advice and additional information about patients. Patients who have their needs met are more likely to have good outcomes.

Project Terms:
Acute; Admission activity; Aftercare; Age; Agreement; Automation; base; beneficiary; Caring; Censuses; Characteristics; Clinical Trials; commercial application; commercialization; Computer software; Databases; Decision Making; Decision Support Systems; design; Development; Discipline of Nursing; Elderly; Ensure; follow-up; Future; Health system; high risk; Home environment; Hospitals; Hour; improved; innovation; Leadership; Learning; Legal patent; Length of Stay; Life; Marketing; Medical; Medicare; meetings; Mental Depression; Methodology; Methods; Modeling; models and simulation; National Institute of Nursing Research; Outcome; Paper; patient home care; Patients; Pennsylvania; Phase; predictive modeling; Process; product development; Production; Randomized; research study; Risk; Services; Side; Small Business Innovation Research Grant; Solutions; Speed (motion); success; Symptoms; System; Systems Integration; Techniques; Technology; technology development; Test Result; Testing; Time; tool; Training; University Hospitals; Walking; Work

Decreasing readmissions through better discharge planning (DP) and transitional care is a national healthcare priority. RightCare Solutions has leveraged over 10 years of interdisciplinary academic research led by a nurse researcher, and through our highly successful phase one SBIR grant demonstrated market value for the D2S2 product and the technical expertise of our team. The D2S2 is a six-item decision support tool installed by RightCare Solutions in the hospital EHR to assist discharge planners to identify high-risk patients upon admission allowing time and focus to target appropriate transitional and post-acute care to prevent readmissions. We have achieved outstanding outcomes from our phase 1 award and are proposing further technological developments to enhance our commercial launch. The market potential for the D2S2 tool is significant since discharge decision support is estimated to be applicable to roughly 6,500 U.S. hospitals with a census that is 60% older adults equaling 14 million discharges per year. The phase 1 results indicate a significant impact on 30 and 60 day readmissions giving us strong evidence as to the value of the product. However, the results and our experience using the software indicate there is opportunity to enhance the product's accruacy and functionality. We propose to enhance our predictive accuracy through innovative data mining and machine learning techniques and to improve the functionality by electronically connecting the acute and post-acute care settings. Due to implementation in the three hospitals of the University of Pennsylvania Health System we have data on over 6,000 patients and through the continued live implementation we will accumulate data on over 25,000 patients by the start of the phase 2 grant. Using existing, and new data generated from continued operations, this proposed SBIR grant will advance the product in two major ways to enhance the commercial benefit to its users. Aim 1: Develop, test, and scale SMART capabilities, a dynamic process for improving prediction accuracy, by using hospital-specific and patient level characteristics (D2S2 variables and additional clinical and non-clinical characteristics) and modern data mining/machine learning techniques. AIM 2: Operationalize the D2S2 recommendations by electronically connecting high-risk patients with post-acute care (PAC) providers and stakeholders, known as CONNECT capabilities. Called a 'learning health system' the end- product of this SBIR grant will provide continuous evaluation and improvement to the end-user measured against their goals. Our innovative design produces a closed-loop system that will use data from the D2S2 and hospital databases over time to 'get smarter.' Further, our enhanced product will link acute care to post-acute providers giving them advanced warning of patients who will shortly come to them for care.

Thesaurus Terms:
Acute;Admission Activity;Award;Base;Caring;Ccl4 Gene;Censuses;Characteristics;Clinical;Computer Software;Data;Data Mining;Data Set;Databases;Design;Development;Diagnosis;Elderly;Environment;Evaluation;Experience;Exposure To;Fall Risk;Goals;Grant;Health System;Healthcare;High Risk;Hospital Readmission;Hospitals;Improved;Infection;Innovation;Inpatients;Interest;Intervention;Learning;Length Of Stay;Life;Link;Machine Learning;Marketing;Measures;Medical Errors;Methodology;Metric;Nurses;Operation;Outcome;Patient Readmission;Patients;Pattern;Payment;Pennsylvania;Phase;Phase 1 Study;Population;Prevent;Process;Programs;Provider;Public Health Relevance;Recommendation;Relative (Related Person);Research;Research Personnel;Risk;Screening;Site;Small Business Innovation Research Grant;Solutions;Specificity;Statutes And Laws;System;Technical Expertise;Techniques;Technology;Testing;Time;Tool;Transitional Care Planning;Treatment As Usual;University Hospitals;