Advance Care Planning in an Accountable Care Organization Is Associated with Increased Advanced Directive Documentation and Decreased Costs

Abstract

Background: Advance care planning (ACP) documents patient wishes and increases awareness of palliative care options.

Objective: To study the association of outpatient ACP with advanced directive documentation, utilization, and costs of care.

Design: This was a case-control study of cases with ACP who died matched 1:1 with controls. We used 12 months of data pre-ACP/prematch and predeath. We compared rates of documentation with logit model regression and conducted a difference-in-difference analysis using generalized linear models for utilization and costs.

Setting/subjects: Medicare beneficiaries attributed to a large rural-suburban-small metro multisite accountable care organization from January 2013 to April 2016, with cross reference to ACP facilitator logs to find cases.

Measurements: The presence of advance directive forms was verified by chart review. Cost analysis included all utilization and costs billed to Medicare.

Results: We matched 325 cases and 325 controls (51.1% female and 48.9% male, mean age 81). 320/325 (98.5%) ACP versus 243/325 (74.8%) of controls had a Healthcare Power of Attorney (odds ratio [OR] 21.6, 95% CI 8.6-54.1) and 172/325(52.9%) ACP versus 145/325 (44.6%) controls had Practitioner Orders for Life Sustaining Treatment (OR 1.40, 95% CI 1.02-1.90) post-ACP/postmatch. Adjusted results showed ACP cases had fewer inpatient admissions (-0.37 admissions, 95% CI -0.66 to -0.08), and inpatient days (-3.66 days, 95% CI -6.23 to -1.09), with no differences in hospice, hospice days, skilled nursing facility use, home health use, 30-day readmissions, or emergency department visits. Adjusted costs were $9,500 lower in the ACP group (95% CI -$16,207 to -$2,793).

Conclusions: ACP increases documentation and was associated with a reduction in overall costs driven primarily by a reduction in inpatient utilization. Our data set was limited by small numbers of minorities and cancer patients.

Keywords: advance care planning; advance directives; healthcare costs; healthcare power of attorney; healthcare utilization; practitioner orders for life sustaining treatment.

FIG. 1.

Patient cohort selection and matching.

FIG. 2.

Cost comparison. Costs were compared with a difference-in-difference method, using a generalized linear model with gamma distribution for expenditures (a) and a generalized linear model with gamma distribution adjusted by age, gender, race, CMS risk score, and comorbidities (CHF, COPD, ESRD, and cancer) (b). All expenditures were converted to 2016 U.S. dollars using the Medical Component of the Consumer Price Index. For patients (N = 190 and each group N = 95) who do not have a full 12-month period between ACP date and death date, we used a multiple imputation method. Ten imputed values were obtained for each missing observation with the mean used for the missing value. ACP, advance care planning; CHF, congestive heart failure; CMS, Center for Medicare and Medicaid Services; COPD, Chronic Obstructive Pulmonary Disease; ESRD, end-stage renal disease.

APPENDIX FIG. 1.

Matching algorithm details. We used a 1:1 matching algorithm and included the following variables: ACP date with the snapshot index date for controls, gender, race, age using nearest with maximum difference <3 years, Deyo adaptation of the Charlson Comorbidity Index (CCI) using diagnosis coding (nearest, maximum difference <2), and an internally developed utilization risk score (similar to Medicare's Hierarchical Condition Categories model). Both the CCI and the utilization risk score were calculated with information before the ACP date or snapshot index date for controls. This study's matching approach is further described in Appendix 2. The CMS risk score is presented in the demographics, but was not used for matching. CMS, Center for Medicare and Medicaid Services. ACP, advance care planning.

APPENDIX FIG. 2.

Conceptual map of matching process. We completed 1:1 matching with data visibility limited to that available as of the ACP date or snapshot index date for control patients. A custom data extraction program built a chronologically informed dataset for matching purposes. The program created snapshots of potential match patients, using only information available before the individual ACP dates. This provided views of all potential matches at all potential matching dates. The matching process then started at the first ACP date, used snapshots from that date in the dataset, determined the best control match based upon the matching criteria, and then removed the chosen match patient from all future snapshots. The process continued moving through all the ACP dates chronologically until all intervention patients were associated with a unique matching control patient.

APPENDIX FIG. 3.

In the twelve months prior to death, the proportion of Health Care Power of Attorney (HCPOA) and Practitioner Orders for Life Sustaining Treatment (POLST).