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EFFICACY: Hopewell Hospitalist: A Video Game Intervention to Increase Advance Care Planning by Hospitalists

Hopewell Hospitalist: A Video Game Intervention to Increase Advance Care Planning Conversations by Hospitalists With Older Adults

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT04557930
Enrollment
163
Registered
2020-09-22
Start date
2020-07-01
Completion date
2021-08-31
Last updated
2023-04-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Advance Care Planning

Keywords

advance care planning, physician performance, serious games, narrative engagement

Brief summary

Hopewell Hospitalist is a theory-based adventure video game designed to increase the likelihood that a physician will engage in an advance care planning (ACP) conversation with a patient over the age of 65. Drawing on the theory of narrative engagement, players assume the persona of a hospitalist and navigate a series of clinical encounters with seriously-ill patients over the age of 65. Players experience the consequences of having (or not having) ACP conversations in a timely fashion. The planned study is a pragmatic stepped-wedge crossover phase III trial testing the efficacy of Hopewell Hospitalist for increasing ACP rates measured by ACP billing frequency.

Detailed description

Introduction: Fewer than half of all people in the U.S. have a documented advance care plan, such as an advance directive, despite their importance in ensuring high-quality care at the end-of-life. Hospitalization offers an opportunity for physicians to initiate advance care planning (ACP) conversations. Despite expert recommendations, hospital-based physicians (hospitalists) do not routinely engage in these conversations, reserving them for the critically ill. The objective of this study is to test the effect of a novel behavioral intervention on the incidence of ACP conversations by hospitalists practicing at a stratified random sample of hospitals drawn from 220 US acute care hospitals staffed by a large, nationwide acute care physician practice with an ongoing ACP quality improvement initiative. Methods and analysis: We developed Hopewell Hospitalist, a theory-based adventure video game, to modify physicians' attitudes towards ACP conversations, and to increase their motivation for engaging in them. Drawing on the theory of narrative engagement, players assume the persona of Andy Jordan, a hospitalist who accepts a new job in a small town. Through a series of clinical encounters with seriously-ill patients over the age of 65, players experience the consequences of having (or not having) ACP conversations in a timely fashion. The planned study is a pragmatic stepped-wedge crossover phase III trial, testing the efficacy of Hopewell Hospitalist for increasing ACP conversations. We will randomize 40 hospitals to the month (step) in which they receive the intervention. We aim to recruit 30 hospitalists from up to 8 hospitals each step to complete the intervention, playing Hopewell Hospitalist for at least 2 hours on an iPad pre-loaded with the game. The primary outcome is ACP billing for patients age 65 and older managed by participating hospitalists. We hypothesize that the intervention will increase ACP billing in the quarter after dissemination, and have 80% power to detect a 1% absolute increase and 99% power to detect a 3.5% absolute increase. Ethics and dissemination: Dartmouth's Committee for the Protection of Human Subjects has approved the study protocol, which is registered on clinicaltrials.gov. We will disseminate the results through manuscripts and the trials website. Hopewell Hospitalist will be made available on the iOS Application Store for download, free of cost, at the conclusion of the trial.

Interventions

Hopewell Hospitalist is a customized theory-based adventure video game that uses narrative engagement to educate physician players on advance care planning to increase physicians' likelihood of engaging in and billing for ACP conversations.

Sponsors

Sound Physicians
CollaboratorOTHER
National Institute on Aging (NIA)
CollaboratorNIH
Dartmouth-Hitchcock Medical Center
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Outcomes Assessor)

Masking description

A hospital's treatment assignment was masked during analysis.

Intervention model description

A stepped wedge crossover trial randomizing physician participants at the group level (i.e., hospital). Each hospital group 'crossed over' from control to intervention at a randomized time point.

Eligibility

Sex/Gender
ALL
Healthy volunteers
Yes

Inclusion criteria

Hospital Inclusion Criteria: * Value-based delivery model of care (Bundled Payment Care Initiative) * Staffed by Sound Physicians for at least 2 quarters * Advance care planning billing rate in prior quarter greater than 0 percent * Employs a nurse liaison * Hospitalist chief approval to approach hospitalists Hospital

Exclusion criteria

* Sound Physicians no longer staffing the hospital * Not staffed by Sound Physicians for at least 2 quarters * Advance care planning billing rate in prior quarter of 0 percent * Does not employ a nurse liaison * Hospitalist chief disapproval to approach hospitalists * Hospitalist chief does not provide contact information for hospitalists * Target number of hospitalists for the step has been met or exceeded Hospitalist Inclusion Criteria: * Employed by Sound for at least 2 quarters and staffing an eligible hospital for at least 1 quarter * ACP billing rate in prior quarter greater than 0 percent or answers eligibility question affirming use of ACP billing codes * Provides informed consent * Name matches a name in the contact list for the sample; OR is verified by communication through an employer-based email address * Receipt of a functional iPad within study step time frame Hospitalist

Design outcomes

Primary

MeasureTime frameDescription
Percentage of Patients With Advance Care Planning Bills11 monthsPercentage of advance care planning bills submitted by physicians in the trial for patients over the age of 65 in the period before and after the roll-out of the video game intervention at their hospital. Advance care planning bills are defined as the presence/absence of ACP charges (Medicare billing codes 99497 or 99498) during a patient's hospitalization.

Secondary

MeasureTime frameDescription
Percentage of Patients Who Died While in Hospital11 monthsNumber of patients who died in the pre-intervention and post-intervention period/total number of patients for both periods
Percentage of Patients Readmitted in 7 Days11 monthsNumber of patients readmitted within 7 days/Total number of patients treated in the pre-intervention and post-intervention periods
Percentage of Patients Readmitted Within 30-days11 monthsNumber of patients readmitted within 30-days/Total number of patients in the pre-intervention and post-intervention periods
Percentage of Patients Who Received Critical Care11 monthsNumber of patients who received critical care while admitted/total number of patients admitted in the pre-intervention and post-intervention periods
Length of Stay11 monthsDuration of hospitalization for patients treated in the pre-intervention and post-intervention periods

Countries

United States

Participant flow

Recruitment details

Dates: July 2020-May 2021 Types of location: acute care hospitals

Pre-assignment details

There was a minimum three month (maximum 7-month) run-in period prior to the exposure of patients to the physicians enrolled in the intervention. We distinguish below between physician participants who enrolled in the trial, and patient participants who were treated by physicians in the trial. The latter group were unconsented.

Participants by arm

ArmCount
Intervention
The control arm occurs prior to receipt of the video game intervention. Each hospital group 'crosses over' from control to intervention at a randomized time point.
163
Total163

Baseline characteristics

CharacteristicIntervention
Age, Continuous40 years
STANDARD_DEVIATION 7
Ethnicity (NIH/OMB)
Hispanic or Latino
9 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
154 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants
How frequently do you use the Advance Care Planning [ACP] billing codes
Always
54 Participants
How frequently do you use the Advance Care Planning [ACP] billing codes
Often
74 Participants
How frequently do you use the Advance Care Planning [ACP] billing codes
Rarely
7 Participants
How frequently do you use the Advance Care Planning [ACP] billing codes
Sometimes
28 Participants
Physician Experience in Years of Practice6.7 years
STANDARD_DEVIATION 5
Race (NIH/OMB)
American Indian or Alaska Native
0 Participants
Race (NIH/OMB)
Asian
75 Participants
Race (NIH/OMB)
Black or African American
15 Participants
Race (NIH/OMB)
More than one race
0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants
Race (NIH/OMB)
Unknown or Not Reported
21 Participants
Race (NIH/OMB)
White
52 Participants
Region of Enrollment
United States
163 participants
Sex: Female, Male
Female
55 Participants
Sex: Female, Male
Male
108 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
0 / 1630 / 163
other
Total, other adverse events
0 / 1630 / 163
serious
Total, serious adverse events
0 / 1630 / 163

Outcome results

Primary

Percentage of Patients With Advance Care Planning Bills

Percentage of advance care planning bills submitted by physicians in the trial for patients over the age of 65 in the period before and after the roll-out of the video game intervention at their hospital. Advance care planning bills are defined as the presence/absence of ACP charges (Medicare billing codes 99497 or 99498) during a patient's hospitalization.

Time frame: 11 months

Population: We analyzed outcomes for patients over 65 admitted for an acute illness, and treated by a trial participant in the pre- and post-intervention periods.

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Pre-interventionPercentage of Patients With Advance Care Planning Bills5,298 Participants
Post-interventionPercentage of Patients With Advance Care Planning Bills4,920 Participants
Comparison: We tested the association between exposure to the intervention and the incidence of ACP billing in the pre- and post-intervention periods using a mixed effects logistic regression model, adjusting for time, patient and hospital covariates.p-value: 0.4195% CI: [0.88, 1.06]Mixed Models Analysis
p-value: 0.7495% CI: [0.89, 1.19]Mixed Models Analysis
Comparison: Sensitivity analysis of the association between the intervention and ACP billing, adjusted for time, patient characteristics, hospital characteristics, and the interaction between step of the trial and the intervention.p-value: 0.0995% CI: [0.98, 1.36]Mixed Models Analysis
Comparison: Sensitivity analysis of the association between the intervention and ACP billing, adjusted for time, patient characteristics, hospital characteristics, and the interaction between step of the trial and the intervention.p-value: 0.1195% CI: [0.97, 1.33]Mixed Models Analysis
Comparison: Sensitivity analysis of the association between the intervention and ACP billing, adjusted for time, patient characteristics, hospital characteristics, and the interaction between step of the trial and the intervention.p-value: <0.00195% CI: [0.57, 0.76]Mixed Models Analysis
Comparison: Sensitivity analysis of the association between the intervention and ACP billing, adjusted for time, patient characteristics, hospital characteristics, and the interaction between step of the trial and the intervention.p-value: 0.4995% CI: [0.89, 1.19]Mixed Models Analysis
Secondary

Length of Stay

Duration of hospitalization for patients treated in the pre-intervention and post-intervention periods

Time frame: 11 months

ArmMeasureValue (MEAN)Dispersion
Pre-interventionLength of Stay6.5 DaysStandard Deviation 5.3
Post-interventionLength of Stay6.4 DaysStandard Deviation 5
Secondary

Percentage of Patients Readmitted in 7 Days

Number of patients readmitted within 7 days/Total number of patients treated in the pre-intervention and post-intervention periods

Time frame: 11 months

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Pre-interventionPercentage of Patients Readmitted in 7 Days756 Participants
Post-interventionPercentage of Patients Readmitted in 7 Days750 Participants
Secondary

Percentage of Patients Readmitted Within 30-days

Number of patients readmitted within 30-days/Total number of patients in the pre-intervention and post-intervention periods

Time frame: 11 months

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Pre-interventionPercentage of Patients Readmitted Within 30-days2,065 Participants
Post-interventionPercentage of Patients Readmitted Within 30-days2,190 Participants
Secondary

Percentage of Patients Who Died While in Hospital

Number of patients who died in the pre-intervention and post-intervention period/total number of patients for both periods

Time frame: 11 months

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Pre-interventionPercentage of Patients Who Died While in Hospital1625 Participants
Post-interventionPercentage of Patients Who Died While in Hospital1862 Participants
Secondary

Percentage of Patients Who Received Critical Care

Number of patients who received critical care while admitted/total number of patients admitted in the pre-intervention and post-intervention periods

Time frame: 11 months

ArmMeasureValue (COUNT_OF_PARTICIPANTS)
Pre-interventionPercentage of Patients Who Received Critical Care1,065 Participants
Post-interventionPercentage of Patients Who Received Critical Care1,034 Participants

Source: ClinicalTrials.gov · Data processed: Feb 15, 2026