SBIR-STTR Award

The long-range goal of this fast-track research application is to improve healthcare quality and reduce healthcare costs nationwide among those at risk for medication-related hospitalization. The specific objective of this proposed research is to develop an algorithm that uses existing electronic health information to efficiently identify patients at risk of medication-related hospitalization so that they can be referred for medication management services. The project will design, program, and test an algorithm to accurately identify patients at risk of medication-related hospitalization. The algorithm will be tested against a pharmacist review of cases to confirm that the algorithm accurately identified patients at risk of medication-related hospitalization using evidence-based criteria and based on a Receiver Operating Characteristic (ROC) curve analysis. The algorithm will also be tested in terms of user acceptance. For each user group, the algorithm will be deployed, and the user's satisfaction with and use of the information provided about each patient will be assessed.

Public Health Relevance Statement:
This project will advance the ability of healthcare providers to avoid medication problems in high risk patients, most of whom are older adults. It will also contribute to the sustainability of the healthcare system by improving efficiency and reducing medication-related hospitalizations.

Project Terms:
Adoption; Elderly; senior citizen; older person; older adult; later life; late life; geriatric; elders; advanced age; Algorithms; drug/agent; Pharmaceutic Preparations; Medication; Drugs; Pharmaceutical Preparations; Environment; Goals; Hawaii; Health; Health Care Systems; Healthcare Systems; treatment provider; medical personnel; healthcare personnel; health workforce; health provider; health care worker; health care personnel; Healthcare worker; Healthcare Providers; Health Care Providers; Health Personnel; Hospital Admission; Hospitalization; Hospitals; Insurance; Investments; heavy metal lead; heavy metal Pb; Pb element; Lead; Logic; lifespan; life span; Length of Life; Longevity; Manuals; Medical Records; Medicine; Patients; Pharmacies; Pharmacy facility; Pharmacists; Production; Public Health; healthcare quality; health care quality; Receiver Operator Characteristics; Receiver Operating Characteristics; Research; Retirement; Risk; social role; Role; Testing; United States Department of Health and Human Services; Department of Health and Human Services; United States Dept. of Health and Human Services; Universities; Healthcare Costs; Health Costs; Health Care Costs; health care; Healthcare; medication therapy management; Pharmacologic Management; Analgesic Management; Medication Management; Caring; base; improved; Phase; satisfaction; Funding; programs; Clinic; System; interest; college; collegiate; Services; Medicare/Medicaid; Structure; member; payment; Code; Coding System; Modeling; Provider; Address; Data; Data Element; Older Population; Process; National Institute on Aging; National Institute of Aging; burden of illness; years of life lost to disease; years of life lost to disability; disease burden; burden of disease; design; designing; Population; innovation; innovative; innovate; commercialization; high risk; evidence base; health information technology; multiple chronic conditions; multimorbidity; Algorithm Design; algorithmic composition; algorithm engineering; Algorithmic Engineering; Algorithmic Design; senior faculty; full professor; health plan; health plans; hospitalization rates

The long-range goal of this fast-track research application is to improve healthcare quality and reduce healthcare costs nationwide among those at risk for medication-related hospitalization. The specific objective of this proposed research is to develop an algorithm that uses existing electronic health information to efficiently identify patients at risk of medication-related hospitalization so that they can be referred for medication management services. The project will design, program, and test an algorithm to accurately identify patients at risk of medication-related hospitalization. The algorithm will be tested against a pharmacist review of cases to confirm that the algorithm accurately identified patients at risk of medication-related hospitalization using evidence-based criteria and based on a Receiver Operating Characteristic (ROC) curve analysis. The algorithm will also be tested in terms of user acceptance. For each user group, the algorithm will be deployed, and the user's satisfaction with and use of the information provided about each patient will be assessed.

Public Health Relevance Statement:
This project will advance the ability of healthcare providers to avoid medication problems in high risk patients, most of whom are older adults. It will also contribute to the sustainability of the healthcare system by improving efficiency and reducing medication-related hospitalizations.

Project Terms:
Adoption; Elderly; advanced age; elders; geriatric; late life; later life; older adult; older person; senior citizen; Algorithms; Pharmaceutical Preparations; Drugs; Medication; Pharmaceutic Preparations; drug/agent; Environment; Goals; Hawaii; Health; Healthcare Systems; Health Care Systems; Health Personnel; Health Care Providers; Healthcare Providers; Healthcare worker; health care personnel; health care worker; health provider; health workforce; healthcare personnel; medical personnel; treatment provider; Hospitalization; Hospital Admission; Hospitals; Insurance; Investments; Lead; Pb element; heavy metal Pb; heavy metal lead; Logic; Longevity; Length of Life; life span; lifespan; Manuals; Medical Records; Medicine; Patients; Pharmacies; Pharmacy facility; Pharmacists; Production; Public Health; healthcare quality; health care quality; Research; Retirement; Risk; ROC Analyses; receiver operating characteristic analyses; receiver operating characteristic curve; ROC Curve; social role; Role; Testing; United States Dept. of Health and Human Services; Department of Health and Human Services; United States Department of Health and Human Services; Universities; Health Care Costs; Health Costs; Healthcare Costs; Healthcare; health care; Medication Management; Analgesic Management; Pharmacologic Management; medication therapy management; Caring; base; improved; Phase; satisfaction; Funding; programs; Clinic; System; interest; collegiate; college; Services; Medicare/Medicaid; Structure; member; payment; Coding System; Code; Modeling; Provider; Address; Data; Data Element; Older Population; Process; National Institute on Aging; National Institute of Aging; burden of illness; burden of disease; disease burden; years of life lost to disability; years of life lost to disease; design; designing; Population; innovation; innovate; innovative; commercialization; high risk; evidence base; health information technology; multiple chronic conditions; multimorbidity; Algorithm Design; Algorithmic Design; Algorithmic Engineering; algorithm engineering; algorithmic composition; senior faculty; full professor; health plan; health plans; hospitalization rates