Susan E. Hickman
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Professor Susan Hickman (Professor, School of Nursing, Community & Health Systems) is committed to optimizing the quality of life for older adults in life’s final chapter through informed, values-based decision-making and effective communication about their treatment preferences. A primary focus of her research is the Physician Orders for Life-Sustaining Treatment (POLST) program, which improves the continuity of care by communicating patients’ treatment preferences as actionable medical orders. Findings from her research have been widely disseminated and are used across the country to support programs based on the POLST model.
Hickman co-founded the Indiana Patient Preferences Coalition, a group of individuals and organizational representatives from law, medicine, nursing, senior care, and ethics. The coalition created the Indiana POST (Physician Orders for Scope of Treatment), which is based on the national POLST model. Dr. Hickman provides education and facilitation skills-training for POST to health care providers around the state. The National Institutes of Health recently awarded her a second grant to study the quality of POLST decisions. She also serves as the Palliative Care Core lead on a Centers for Medicare and Medicaid Services innovations grant where POLST is used to reduce avoidable hospitalizations and improve care in 19 Indianapolis area nursing facilities. Her collaboration with colleagues at IU Health resulted in the launch of the Encompass Initiative, which will provide education to improve primary palliative care throughout the academic health system.
Professor Hickman’s work to improve the quality of life for older adults in life’s final chapter is another example of how IUPUI faculty are TRANSLATING RESEARCH INTO PRACTICE.
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Item Re-opening nursing facilities to visitors during a pandemic: An early look at experiences(2022) Petrovic, Marija; Hickman, Susan E.; Mack, Laramie; Unroe, Kathleen T.; School of NursingItem Age-specific rates of hospital transfers in long-stay nursing home residents(Oxford Academic, 2022-01) Tu, Wanzhu; Li, Ruohong; Stump, Timothy E.; Fowler, Nicole R.; Carnahan, Jennifer L.; Blackburn, Justin; Sachs, Greg A.; Hickman, Susan E.; Unroe, Kathleen T.; Biostatistics, School of Public HealthIntroduction hospital transfers and admissions are critical events in the care of nursing home residents. We sought to determine hospital transfer rates at different ages. Methods a cohort of 1,187 long-stay nursing home residents who had participated in a Centers for Medicare and Medicaid demonstration project. We analysed the number of hospital transfers of the study participants recorded by the Minimum Data Set. Using a modern regression technique, we depicted the annual rate of hospital transfers as a smooth function of age. Results transfer rates declined with age in a nonlinear fashion. Rates were the highest among residents younger than 60 years of age (1.30-2.15 transfers per year), relatively stable between 60 and 80 (1.17-1.30 transfers per year) and lower in those older than 80 (0.77-1.17 transfers per year). Factors associated with increased risk of transfers included prior diagnoses of hip fracture (annual incidence rate ratio or IRR: 2.057, 95% confidence interval (CI): [1.240, 3.412]), dialysis (IRR: 1.717, 95% CI: [1.313, 2.246]), urinary tract infection (IRR: 1.755, 95% CI: [1.361, 2.264]), pneumonia (IRR: 1.501, 95% CI: [1.072, 2.104]), daily pain (IRR: 1.297, 95% CI: [1.055,1.594]), anaemia (IRR: 1.229, 95% CI [1.068, 1.414]) and chronic obstructive pulmonary disease (IRR: 1.168, 95% CI: [1.010,1.352]). Transfer rates were lower in residents who had orders reflecting preferences for comfort care (IRR: 0.79, 95% CI: [0.665, 0.936]). Discussion younger nursing home residents may require specialised interventions to reduce hospital transfers; declining transfer rates with the oldest age groups may reflect preferences for comfort-focused care.Item POLST Is More Than a Code Status Order Form: Suggestions for Appropriate POLST Use in Long-Term Care(Elsevier, 2021-08) Hickman, Susan E.; Steinberg, Karl; Carney, John; Lum, Hillary D.; School of NursingPOLST (Physician Orders for Life-Sustaining Treatment) is a medical order form used to document preferences about cardiopulmonary resuscitation (CPR), medical interventions such as hospitalization, care in the intensive care unit, and/or ventilation, as well as artificial nutrition. Programs based on the POLST paradigm are used in virtually every state under names that include POST (Physician Orders for Scope of Treatment), MOLST (Medical Orders for Life-Sustaining Treatment), and MOST (Medical Orders for Scope of Treatment), and these forms are used in the care of hundreds of thousands of geriatric patients every year. Although POLST is intended for persons who are at risk of a life-threatening clinical event due to a serious life-limiting medical condition, some nursing homes and residential care settings use POLST to document CPR preferences for all residents, resulting in potentially inappropriate use with patients who are ineligible because they are too healthy. This article focuses on reasons that POLST is used as a default code status order form, the risks associated with this practice, and recommendations for nursing homes to implement appropriate use of POLST.Item Preparation Matters: What We Can Learn From an Olympic Swimmer About the Value of Advance Care Planning Interventions(ACP, 2021-11) Hickman, Susan E.; Lum, Hillary D.; School of NursingItem Facility and resident characteristics associated with variation in nursing home transfers: evidence from the OPTIMISTIC demonstration project(BMC, 2021-05-24) Blackburn, Justin; Balio, Casey P.; Carnahan, Jennifer L.; Fowler, Nicole R.; Hickman, Susan E.; Sachs, Greg A.; Tu, Wanzhu; Unroe, Kathleen T.; Health Policy and Management, School of Public HealthBackground: Centers for Medicare and Medicaid Services (CMS) funded demonstration project to evaluate financial incentives for nursing facilities providing care for 6 clinical conditions to reduce potentially avoidable hospitalizations (PAHs). The Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) site tested payment incentives alone and in combination with the successful nurse-led OPTIMISTIC clinical model. Our objective was to identify facility and resident characteristics associated with transfers, including financial incentives with or without the clinical model. Methods: This was a longitudinal analysis from April 2017 to June 2018 of transfers among nursing home residents in 40 nursing facilities, 17 had the full clinical + payment model (1726 residents) and 23 had payment only model (2142 residents). Using CMS claims data, the Minimum Data Set, and Nursing Home Compare, multilevel logit models estimated the likelihood of all-cause transfers and PAHs (based on CMS claims data and ICD-codes) associated with facility and resident characteristics. Results: The clinical + payment model was associated with 4.1 percentage points (pps) lower risk of all-cause transfers (95% confidence interval [CI] - 6.2 to - 2.1). Characteristics associated with lower PAH risk included residents aged 95+ years (- 2.4 pps; 95% CI - 3.8 to - 1.1), Medicare-Medicaid dual-eligibility (- 2.5 pps; 95% CI - 3.3 to - 1.7), advanced and moderate cognitive impairment (- 3.3 pps; 95% CI - 4.4 to - 2.1; - 1.2 pps; 95% CI - 2.2 to - 0.2). Changes in Health, End-stage disease and Symptoms and Signs (CHESS) score above most stable (CHESS score 4) increased the risk of PAH by 7.3 pps (95% CI 1.5 to 13.1). Conclusions: Multiple resident and facility characteristics are associated with transfers. Facilities with the clinical + payment model demonstrated lower risk of all-cause transfers compared to those with payment only, but not for PAHs.Item Identifying the Implementation Conditions Associated With Positive Outcomes in a Successful Nursing Facility Demonstration Project(Oxford Academic, 2020-11-23) Hickman, Susan E.; Miech, Edward J.; Stump, Timothy E.; Fowler, Nicole R.; Unroe, Kathleen T.; Emergency Medicine, School of MedicineBackground and objectives: To identify the implementation barriers, facilitators, and conditions associated with successful outcomes from a clinical demonstration project to reduce potentially avoidable hospitalizations of long-stay nursing facility residents in 19 Indiana nursing homes. Research design and methods: Optimizing Patient Transfers, Impacting Medical quality, Improving Symptoms-Transforming Institutional Care (OPTIMISTIC) is a multicomponent intervention that includes enhanced geriatric care, transition support, and palliative care. The configurational analysis was used to analyze descriptive and quantitative data collected during the project. The primary outcome was reductions in hospitalizations per 1,000 eligible resident days. Results: Analysis of barriers, facilitators, and conditions for success yielded a model with 2 solution pathways associated with a 10% reduction in potentially avoidable hospitalizations per 1,000 resident days: (a) lower baseline hospitalization rates and investment of senior management; or (b) turnover by the director of nursing during the observation period. Conditions for success were similar for a 20% reduction, with the addition of increased resident acuity. Discussion and implications: Key conditions for successful implementation of the OPTIMISTIC intervention include strong investment by senior leadership and an environment in which baseline hospitalization rates leave ample room for improvement. Turnover in the position of director of nursing also linked to successful implementation; this switch in leadership may represent an opportunity for culture change by bringing in new perspectives and viewpoints. These findings help define the conditions for the successful implementation of the OPTIMISTIC model and have implications for the successful implementation of interventions in the nursing facility more generally.Item Long-Stay Nursing Facility Resident Transfers: Who Gets Admitted to the Hospital?(AGS, 2020-09) Unroe, Kathleen T.; Caterino, Jeffrey M.; Stump, Timothy E.; Tu, Wanzhu; Carnahan, Jennifer L.; Vest, Joshua R.; Sachs, Greg A.; Hickman, Susan E.; Medicine, School of MedicineBACKGROUND/OBJECTIVES The Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) project is a successful, multicomponent demonstration project to reduce potentially avoidable hospitalizations of long-stay nursing facility residents. To continue to reduce hospital transfers, a more detailed understanding of these transfer events is needed. The purpose of this study was to describe differences in transfer events that result in treatment in the hospital versus emergency department (ED) only. DESIGN OPTIMISTIC project nurses collected data on residents who transferred. Transfer events that resulted in treatment in ED versus hospitalization were compared using t-tests and chi-square tests. A generalized estimating equations regression model was used to assess the associations between hospital admission and transfer characteristics. PARTICIPANTS A total of 867 long-stay nursing facility residents enrolled in OPTIMISTIC, January 2015 to June 2016. MEASUREMENTS Resident and transfer characteristics from Minimum Data Set and project REDCap (Research Electronic Data Capture) database, including demographics, cognitive status, comorbidities, symptoms at time of transfer, and diagnoses. RESULTS The most common symptoms associated with treatment in the ED only were falls, trauma, or fracture (38% vs 10% admitted). Residents with cognitive impairment were more likely to be admitted to the hospital (odds ratio (OR) = 1.47; 95% confidence interval (CI) = 1.09–1.98; P = .011). Residents with respiratory complaints were more likely to be admitted (OR = 2.098; 95% CI = 1.198–3.675; P = .009); residents with hematological/bleeding (nongastrointestinal) (OR = 0.23; 95% CI = 0.107–0.494; P = .0002), pain (OR = 0.421; 95% CI = 0.254–0.698; P = .0008), or fall/trauma/fracture (OR = 0.181; 95% CI = 0.12–0.272; P < .001) were less likely to be admitted to the hospital. CONCLUSION Some presenting symptoms and other characteristics are more associated with ED only treatment versus hospitalization. A knowledge of who is likely to receive ED only care could prompt adoption of targeted resources and protocols to further reduce these types of transfer events. Opportunity may exist in the ED as well to reduce hospitalizations and increase discharges back to the facility.Item Attitudes and Experiences of Frontline Nursing Home Staff Towards Coronavirus Testing(2020) Hofschulte-Beck, Spencer L.; Hickman, Susan E.; Blackburn, Justin L.; Mack, Laramie M.; Unroe, Kathleen; Medicine, School of MedicineItem Reducing the Risk of Hospitalization for Nursing Home Residents: Effects and Facility Variation From OPTIMISTIC(Elsevier, 2020-04) Blackburn, Justin; Stump, Timothy E.; Carnahan, Jennifer L.; Hickman, Susan E.; Tu, Wanzhu; Fowler, Nicole R.; Unroe, Kathleen T.; Health Policy and Management, School of Public HealthObjectives The Optimizing Patient Transfers, Impacting Medical Quality, and Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) project led to significant decreases in potentially avoidable hospitalizations of long-stay nursing facility residents in external evaluation. The purpose of this study was to quantify hospitalization risk from the start of the project and describe the heterogeneity of the enrolled facilities in order to better understand the context for successful implementation. Design Pre-post analysis design of a prospective intervention within a single group. Setting and Participants A total of 4320 residents in the 19 facilities were included from admission until time to the first hospitalization. Measures Data were extracted from Minimum Data Set assessments and linked with facility-level covariates from the LTCFocus.org data set. Kaplan-Meier and Cox proportional hazards regression were used to assess risk of hospitalization during the preintervention period (2011-2012), a “ramp-up” period (2013-2014), and an intervention period (2015-2016). Results The cohort consisted of 4230 long-stay nursing facility residents. Compared with the preintervention period, residents during the intervention period had an increased probability of having no hospitalizations within 1 year, increasing from 0.51 to 0.57, which was statistically significant ( P < .001). In adjusted Cox models, the risk of hospitalization was lower in the ramp-up period compared to the pre-period [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.75-0.95] and decreased further during the intervention period (HR 0.74, 95% CI 0.65-0.84). Conclusions and Implications As part of a large multisite demonstration project, OPTIMISTIC has successfully reduced hospitalizations. However, this study highlights the magnitude and extent to which results differ across facilities. Implementing the OPTIMISTIC program was associated with a 16% risk reduction after the first 18 months and continued to a final risk reduction of 26% after 5½ years. Although this model of care reduces hospitalizations overall, facility variation should be expected.Item Attitudes and Experiences of Frontline Nursing Home Staff Towards Coronavirus Testing(Elsevier, 2020-11-05) Hofschulte-Beck, Spencer L.; Hickman, Susan E.; Blackburn, Justin L.; Mack, Laramie M.; Unroe, Kathleen T.; Medicine, School of MedicineThe Indiana State Department of Health tested nursing home staff for COVID-19 in June 2020. A survey of staff found many felt physical discomfort, some questioned testing the asymptomatic, but a majority agreed testing is important.