Table 1.
Outcome Measures with High Pragmatic Characteristics
| Primary Outcomes Measures with High Pragmatic Characteristics (n=9) | |||
| Outcome | ACP Domain | Key Pragmatic Characteristics | Reference |
| ACP conversation & documentation | Action | Variable, potentially highly pragmatic if a standardized EHR embedded tool is utilized (e.g., ACPWise tool); low data extract burden, can be completed with ease, no associated cost, and <50 items. | Tilburgs (2020), Gabbard (2021), Sævareid (2019), Sampson (2011) |
| Social engagement and withdrawal | Healthcare | High, since routinely measured and collected in Minimum Data Set, low data capture burden, and only 6 items. | Hilgeman (2014) |
| Burdensome Treatment | Healthcare | High, since using existing EHR data. | Moyo (2021) |
| Depression-Patient Health Questionnaire (PHQ-9) scale | Healthcare | High, since routinely collected and embedded in most EHRs along with only 9 items. | Reinhardt (2014) |
| ED visits and hospitalizations | Healthcare | High, since using existing EHR data. | Martin (2019) |
| Hospital-Length of stay | Healthcare | High, since using existing EHR data. | Lamppu (2021) |
| Hospital transfer | Healthcare | High, since using existing EHR data. | Moyo (2021) Loomer (2021) Mitchell (2020) |
| Late transitions | Healthcare | High, since using existing EHR data. | Moyo (2021) |
| Satisfaction with care | Quality of Care | High, since simple to score & interpret, commonly collected by healthcare systems. | Reinhardt (2014) |
| Secondary Outcome Measures with High Pragmatic Characteristics (n=15) | |||
| Documentation of Surrogate Decision Maker | Action | High, since routinely collected and embedded in most EHRs. | Gabbard (2021) Overbeek (2018) Saevareid (2019) |
| Documentation of Preferences for Life Sustaining treatments | Action | Variable, potentially highly pragmatic if a standardized EHR embedded tool is utilized | Reinhardt (2014) Sævareid (2019) Loizeau (2019) |
| Documentation of Preferences for Comfort | Action | Variable, potentially highly pragmatic if a standardized EHR embedded tool is utilized | Mitchell (2018) |
| ACP conversation & documentation | Action | Variable, potentially highly pragmatic if a standardized EHR embedded tool is utilized | Mitchell (2018) Saevareid (2019) |
| Use of ACP billing codes | Action | High, since using existing EHR data. | Gabbard (2021) |
| % of patients who reported having feeding tube discussions | Action | Variable, potentially highly pragmatic if a standardized EHR embedded tool is utilized | Hanson (2011) |
| Rates of burdensome treatment | Healthcare | High, since using existing EHR data. | Mitchell (2018,2020) Loomer (2021) Saevareid (2019) |
| Rates of Hospital Transfers | Healthcare | High, since using existing EHR data. | Mitchell (2020) Hanson (2017) |
| Rates of Hospice Enrollment | Healthcare | Variable, embedded in some EHR data, though some only have referral rates. | Mitchell (2020) Hanson (2017) |
| Rates of Hospitalization and ED visits | Healthcare | High, since using existing EHR data. | Loomer (2021) Martin (2019) Brazil (2018) Lamppu (2021) Saevareid (2019) |
| Hospital-Length of stay | Healthcare | High, since using existing EHR data. | Martin (2019) |
| DNR Orders | Healthcare | High, since using existing EHR data. | Brazil (2018) |
| Feeding tube placement | Healthcare | High, since routinely embedded in most EHRs. | Hanson (2011) |
| Medical Care Use (hospital care, procedures, medical interventions) | Healthcare | High, since using existing EHR data. | Overbeek (2018) |
| Mortality Rate (in-hospital and nursing home) | Healthcare | High, since using existing EHR data. | Martin (2019) |