Optimizing Post Acute Referrals and Effect on Patient Outcomes The Centers for Medicare and Medicaid's vision for post acute care in the 21st century is a system that is patient centered and organized around the individual's needs rather than around the setting in which the care is received. Each year clinicians make more than 13 million decisions about the need for post acute services following hospital discharge of Medicare beneficiaries;yet, there are no empirically derived, clinical guidelines to assist in making these common and important decisions. The post acute care referral process has multiple steps that require careful, comprehensive assessment to determine patients'present needs, anticipate future needs, make appropriate decisions, and coordinate follow-up services. This proposal focuses on the first three steps of this process to achieve the CMS goal of getting the right care for every person every time. The findings of this research team and others have consistently shown that the quality of post acute referral decision making is negatively impacted by shortened lengths of stay, inconsistent assessment, poor communication, and varying levels of expertise and risk tolerance in decision-making. Our team's recently completed NINR study (RO1-NR007674) revealed that experts, given high quality information and the time to deliberate, refer 52% more patients for post acute care than were referred by clinicians. The proposed competing renewal will advance these findings in several important ways. Using over 1200 patient scenarios obtained from the electronic records at 4 hospitals, large numbers of patient characteristics will be analyzed from a socio-demographic and clinically representative sample of elderly patients. In addition, a large group of clinical and scholarly experts will assure multidisciplinary perspectives. The model, labeled as the "expert discharge decision support system" (D2S2), will be embedded in the electronic record and field tested for its effects on patient outcomes.
The specific aims are: 1) To identify the patient characteristics (factors) that are significantly correlated with experts'decisions to refer hospitalized elders for post acute care. 2) To define and validate the most significantly predictive model of factors to mimic experts'referral decisions. 3) To evaluate the effects of the D2S2 on decision making and patient outcomes. Study findings will identify and make available the knowledge of experts to standardize and facilitate the identification of older patients in need of post acute care. Results will improve the quality and consistency of post acute referral decisions, reduce the time required for referrals to occur, and decrease the costs associated with poor outcomes related to unmet post discharge needs. In addition to addressing gaps in knowledge and care quality, the proposed study meets recommended strategies for improving quality and safety outlined by the Institute of Medicine reports and the National Quality Forum where matching patient needs with service delivery is a high priority.

Public Health Relevance

Currently the decision to refer older adults for post hospital care, such as home care, is made by a variety of clinicians using a variety of criteria. This study will develop and test a computerized system that will provide advice to clinicians about these important decisions. The goal is to improve the identification of who needs post acute care, to get them to the most appropriate care, and to prevent rehospitalization.

Agency
National Institute of Health (NIH)
Institute
National Institute of Nursing Research (NINR)
Type
Research Project (R01)
Project #
5R01NR007674-06
Application #
8290448
Study Section
Nursing Science: Adults and Older Adults Study Section (NSAA)
Program Officer
Huss, Karen
Project Start
2001-09-15
Project End
2016-06-30
Budget Start
2012-07-01
Budget End
2014-06-30
Support Year
6
Fiscal Year
2012
Total Cost
$530,238
Indirect Cost
$157,369
Name
University of Pennsylvania
Department
Other Health Professions
Type
Schools of Nursing
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
Bowles, Kathryn H; Ratcliffe, Sarah; Potashnik, Sheryl et al. (2016) Using Electronic Case Summaries to Elicit Multi-Disciplinary Expert Knowledge about Referrals to Post-Acute Care. Appl Clin Inform 7:368-79
Bowles, Kathryn H; Chittams, Jesse; Heil, Eric et al. (2015) Successful electronic implementation of discharge referral decision support has a positive impact on 30- and 60-day readmissions. Res Nurs Health 38:102-14
Bowles, Kathryn H; Dykes, Patricia; Demiris, George (2015) The use of health information technology to improve care and outcomes for older adults. Res Gerontol Nurs 8:5-10
Topaz, Maxim; Kang, Youjeong; Holland, Diane E et al. (2015) Higher 30-day and 60-day readmissions among patients who refuse post acute care services. Am J Manag Care 21:424-33
Hechenbleikner, Elizabeth; Makary, Martin; Samarov, Daniel et al. (2015) Decision support tool use in colorectal surgery: what is the role? J Surg Res 194:69-76
Bowles, Kathryn H; Hanlon, Alexandra; Holland, Diane et al. (2014) Impact of discharge planning decision support on time to readmission among older adult medical patients. Prof Case Manag 19:29-38
Bowles, Kathryn H; Heil, Eric (2014) From unmet clinical need to entrepreneurship: taking your informatics solution to market. Stud Health Technol Inform 201:315-20
Bowles, Kathryn H (2014) Developing evidence-based tools from EHR data. Nurs Manage 45:18-20
Topaz, Maxim; Rao, Aditi; Masterson Creber, Ruth et al. (2013) Educating clinicians on new elements incorporated into the electronic health record: theories, evidence, and one educational project. Comput Inform Nurs 31:375-9; quiz 380-1
Holland, Diane E; Knafl, George J; Bowles, Kathryn H (2013) Targeting hospitalised patients for early discharge planning intervention. J Clin Nurs 22:2696-703

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