Specific Aims and Hypotheses

This section presents the proposed aims and hypotheses of this research.

Specific Aim 1

1A: Identify and categorize reasons for ED use in community-dwelling older adults.

1B: Identify and categorize reasons for problems that occur during the transition from ED back to residence in community-dwelling older adults.

1C: Describe the predisposing (e.g. age, gender, ethnicity/race, education level), enabling (e.g.

insurance type, PCP, years of residence in apartment building, social network, transportation source, telephone access, use of assistive devices, Activities of Daily Living), and need (e.g.

number of medications, type and number of chronic conditions, type and number of mental health conditions, substance abuse history) characteristics and use of health services or health behaviors (e.g. ED visits, hospitalizations, PCP visits, use of RHWP clinic) of the RHWP participants. Describe RHWP clinic use and reason for visits (e.g. number of clinic visits per patient, main patient reasons for clinic use (chief complaint)), problems identified (e.g.

potentially inappropriate medication use or care transition problem), and services or care coordination provided. Describe patient self-report of ED use (e.g. number of ED visits per patient, main reasons for ED visit, care provided in the ED, and outcome of ED visit), patient’s

scores on validated tools (e.g. Geriatric Depression Scale), and modified tools (e.g. Care Coordination Measurement Tool).

1D: Examine the association between predisposing, enabling, and need characteristics and health behaviors of the RHWP participants with the occurrence of care transition problems.

HA1: Patients with a higher number of medications will be more likely to experience a care transition problem.

HA2: Patients with a lack of follow-up with their PCP will be more likely to experience a care transition problem.

HA3: Patients with a higher number of chronic conditions will be more likely to experience a care transition problem.

HA4: Patients who have help or aid in the home will be less likely to experience a care transition problem.

HA5: Patients with the ability to drive will be less likely to experience a care transition problem.

HA6: Patients with higher levels of independence will be less likely to experience a care transition problem.

H07: There will be no difference between other predisposing (age, gender, race/ethnicity, education level), enabling (insurance type, years of residence, telephone access, use of assistive devices), need (mental health conditions, substance abuse history), and health behavior characteristics (RHWP use, hospitalizations, ED visits) with the presence of a care transition problem.

1E: Examine the association between predisposing, enabling, and need characteristics and health behaviors of the RHWP participants with ED use.

HA8: Patients with a hospitalization within the past six months will be more likely to have an ED visit than those who were not hospitalized.

HA9: Patients with diabetes will be more likely to have an ED visit than those without diabetes.

HA10: Patients with heart disease will be more likely to have an ED visit than those without heart disease.

HA11: Older patients without a PCP are more likely to have an ED visit than those with a PCP.

HA12: Patients without help or aid in the home will be more likely to have an ED visit than those who do.

HA13: Older patients will be more likely to have an ED visit than younger patients.

HA14: Patients with a higher GDS score will be more likely to have an ED visit than those with a lower GDS score.

H015: There will be no difference between other predisposing (gender, race/ethnicity, education level), enabling (insurance type, years of residence, transportation source, telephone access, use of assistive devices, Activities of Daily Living score), need (number of medications, substance abuse history), and health behavior characteristics (PCP visit, RHWP use) and the presence of an ED visit.

Specific Aim 2

2A: Describe the demographics (age, race, gender) and use characteristics (location of

ambulance pick-up, location of transport destination, reason for transport (destination code), date and time of transport, urgent vs. non-urgent) of all ambulance transports in the Richmond area and for all ambulance transports from the low-income, subsidized housing apartment building.

2B: Compare ambulance use before and after the start of the RHWP for older adults at the low-income, subsidized housing apartment building.

HA16: The number of ambulance transports from this apartment building will be lower after the start of RHWP.

H017: Demographics (age, race, gender) will have no effect on the number of ambulance transports after the start of RHWP.

H018: Day of transport will have no effect on the number of ambulance transports after the start of the RHWP.

H019: Time of transport will have no effect on the number of ambulance transports after the start of the RHWP.

H020: There will be no change of the number of urgent ambulance transports from this apartment building after the start of the RHWP.

HA21: The number of non-urgent ambulance transports will be lower after the start of the RHWP.

2C: Compare use of ambulance services by older adults by zip code to identify areas of high utilization in the Richmond area.

2D: Examine the relationship between demographic (age, race, gender) and utilization variables (reason for transport, date, and time of transport) with non-urgent ambulance transports to the ED.

HA22: Older patients will have increased use of non-urgent ambulance transports to the ED.

HA23: Male patients will have higher use of non-urgent ambulance transport to the ED.

H024: Race will have no effect on the use of non-urgent ED ambulance transports.

H025: Day of the week will have no effect on the use of non-urgent ED ambulance transports.

H026: Time of transport will have no effect on the use of non-urgent ED ambulance transports.

Specific Aim 3

3A: Describe demographics and ED visit characteristics for older adults in an urban, safety-net hospital.

3B: Examine the relationship between demographics and ED visit characteristics and zip code of patient residence.

For non-emergent ED visits:

HA27: Patients who live in zip code 23220 with a non-emergent ED visit will be older than those who do not live in zip code 23220.

HA28: Patients who live in zip code 23220 with a non-emergent ED visit will have higher CCI scores than those who do not live in zip code 23220.

HA29: Patients who live in zip code 23220 with a non-emergent ED visit will be more likely to arrive via ambulance than those who do not live in zip code 23220.

HA30: Patients who live in zip code 23220 with a non-emergent ED visit will have higher total costs than those who do not live in zip code 23220.

HA31: Patients who live in zip code 23220 with a non-emergent ED visit will have a higher disease count than those who do not live in zip code 23220.

H032: There will be no effect of gender, race/ethnicity, payment source, visit diagnosis, visit procedures, disposition, and number of prescribed medications in a non-emergent ED visit by patients who live in zip code 23220.

For emergent but primary-care treatable ED visits:

HA33: Patients who live in zip code 23220 with an emergent, but primary care treatable ED visit will be older than those who do not live in zip code 23220.

HA34: Patients who live in zip code 23220 with an emergent, but primary care treatable ED visit will have higher CCI scores than those who do not live in zip code 23220.

HA35: Patients who live in zip code 23220 with an emergent, but primary care treatable ED visit will be more likely to arrive via ambulance than those who do not live in zip code 23220.

HA36: Patients who live in zip code 23220 with an emergent, but primary care treatable ED visit will have higher total costs than those who do not live in zip code 23220.

HA37: Patients who live in zip code 23220 with an emergent, but primary care treatable ED visit will have a higher disease count than those who do not live in zip code 23220.

H038: There will be no effect of gender, race/ethnicity, payment source, visit diagnosis, visit procedures, disposition, and number of prescribed medications in an emergent, but primary care treatable ED visit by patients who live in zip code 23220.

For emergent, ED care needed, but preventable/avoidable ED visits:

HA39: Patients who live in zip code 23220 with an emergent, ED care needed, but preventable/avoidable ED visit will be older than those who do not live in zip code 23220.

HA40: Patients who live in zip code 23220 with an emergent, ED care needed, but preventable/avoidable ED visit will have higher CCI scores than those who do not live in zip code 23220.

HA41: Patients who live in zip code 23220 with an emergent, ED care needed, but preventable/avoidable ED visit will be more likely to arrive via ambulance than those who do not live in zip code 23220.

HA42: Patients who live in zip code 23220 with an emergent, ED care needed, but preventable/avoidable ED visit will have higher total costs than those who do not live in zip code 23220.

HA43: Patients who live in zip code 23220 with an emergent, ED care needed, but preventable/avoidable ED visit will have a higher disease count than those who do not live in zip code 23220.

H044: There will be no effect of gender, race/ethnicity, payment source, visit diagnosis, visit procedures, disposition, and number of prescribed medications in an emergent, ED care needed, but preventable/avoidable ED visit by patients who live in zip code 23220.

3C: Examine the relationship between demographics, ED visit characteristics, and billing costs.

All patients aged ≥ 65 years old using VCUHS ED:

HA45: Living in the 23220 zip code area will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA46: Increasing age will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA47: Larger CCI scores will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA48: Arrival to the ED via ambulance will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA49: Higher total disease count will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA50: Higher total visit procedures will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

H051: There will be no effect of gender, race/ethnicity, payment source, visit diagnosis, disposition, and number of prescribed medications on total ED billing costs.

Only patients living in zip code 23220 using VCUHS ED:

HA52: Participation in RHWP will be a significant negative predictor of total ED billing costs, while controlling for all other variables in the model.

HA53: Increasing age will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA54: Larger CCI scores will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA55: Arrival to the ED via ambulance will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA56: Higher total disease count will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

HA57: Higher total visit procedures will be a significant positive predictor of higher total ED billing costs, while controlling for all other variables in the model.

H058: There will be no effect of gender, race/ethnicity, payment source, visit diagnosis, disposition, NYU ED algorithm category, and number of prescribed medications on total ED billing costs.