INTRODUCTION
Patients seen in preoperative testing clinics are at an increased risk of surgical complications and most are incapacitated for during anesthesia. Advance directives (ADs) are important to guide care in the event of emergencies when patients are unable to speak for themselves. The goal of this study was to determine the frequency with which ADs are completed for patients seen in preoperative clinics prior to elective surgery and identify demographic and clinical characteristics associated with having ADs available in the electronic medical record (EMR).
METHODS
Study Design
A retrospective EMR chart review was conducted on 400 consecutive patients who underwent a preoperative evaluation in a preoperative clinic from February 1 through early March 2017 at two high-volume hospitals in a midwestern urban academic tertiary referral center.
Data Collection
All raters first completed chart reviews of the same 30 patients to calculate interrater reliability.
We collected demographic variables, elevated perioperative risk of surgery,1 Revised Cardiac Risk Index (RCRI) > 1%,2 and presence of revised Charleston comorbid conditions.3 Functional capacity was reported in the EMR as either metabolic equivalents (METS) scale (1 through 4) or as “good,” “borderline,” or “poor.” We dichotomized patients’ functional capacity as “good” or 4 METS versus and “other” or 1–3 METS.
Reviewers assessed the presence of AD documents scanned into the EMR, including an SDM, a living will, or either (any AD). The study was approved by the Indiana University Institutional Review Board.
Statistical Analysis
Patient characteristics were compared based upon the presence of having either type of AD documents in the EMR using two sample t tests for the continuous variables and Fisher’s exact tests for the categorical variables. All preoperative patient clinical and demographic variables significant in the univariate model at the alpha = 0.15 level were included in multiple logistic regression modeling of the AD outcome. Both stepwise and backward methods were used to identify a final parsimonious model with all variables significant at the alpha = 0.05 level.
RESULTS
Interrater reliability for the Charlson3 score showed interclass correlations from 0.76–0.97. The range for Cohen’s kappa coefficients on categorical data ranged from 0.37 to 1, and percentage agreement ranged from 67 to 100% for pairwise comparisons.
We found 64 (16.0%) of patients had evidence of either AD scanned into the EMR, 43 (10.8%) had an SDM, and 46 (11.5%) had a living will. In a bivariate analysis, age 54.7 vs. 31.3%, p = 0.0005) and higher functional status (17.7 vs. 7.0%, p = 0.0118) were associated with the presence of any AD. There were no differences between those with and without ADs with complications or death (Table 1).
Table 1.
Comparison of Patient Characteristics and Hospital Events by Presence of any Advance Directive (Surrogate Decision Maker or Living Will) in the Electronic Medical Record
| Advance directive in EMR | ||||
|---|---|---|---|---|
| Total | Yes | No | p value | |
| N = 400 | N = 64 (16.0%) | N = 336 (84.0%) | ||
| Preoperative patient characteristics | ||||
| Age ≥ 65, n (%) | 140 (35.0) | 35 (54.7) | 105 (31.3) | 0.0005 |
| Sex, male n (%) | 193 (48.3) | 24 (37.5) | 169 (50.3) | 0.0756 |
| Race, white vs. non-white, n (%) | 339 (84.8) | 56 (87.5) | 283 (84.2) | 0.5744 |
| Hospital 1 vs. hospital 2, n (%) | 199 (49.8) | 36 (56.3) | 163 (48.5) | 0.2772 |
| Insurance: Medicaid, n (%) | 46 (11.5) | 7 (10.9) | 39 (11.6) | 1.0000 |
| Perioperative risk of surgery elevated, n (%) | 347 (86.8) | 57 (89.1) | 290 (86.3) | 0.6886 |
| Revised cardiac risk index > 1%, n (%) | 158 (39.5) | 28 (43.8) | 130 (38.7) | 0.4865 |
| Reason for surgery: cancer, n (%) | 122 (30.5) | 20 (31.3) | 102 (30.4) | 0.8831 |
| Revised Charlson comorbidity index, mean (SD) | 1.9 (2.2) | 1.9 (2.1) | 1.9 (2.3) | 0.9629 |
| Myocardial infarction, n (%) | 25 (6.3) | 1 (1.6) | 24 (7.1) | 0.1527 |
| Congestive heart failure, n (%) | 22 (5.5) | 8 (12.5) | 14 (4.2) | 0.0139 |
| Peripheral vascular disease, n (%) | 18 (4.5) | 0 (0.0) | 18 (5.4) | 0.0911 |
| Cerebrovascular disease, n (%) | 33 (8.3) | 4 (6.3) | 29 (8.6) | 0.6285 |
| Dementia, n (%) | 4 (1.0) | 0 (0.0) | 4 (1.2) | 1.0000 |
| Chronic pulmonary disease, n (%) | 60 (15.0) | 11 (17.2) | 49 (14.6) | 0.5702 |
| Rheumatologic disease, n (%) | 13 (3.3) | 4 (6.3) | 9 (2.7) | 0.1380 |
| Peptic ulcer disease, n (%) | 0 (0.0) | 0 (0.0) | 0 (0.0) | N/A |
| Mild liver disease, n (%) | 10 (2.5) | 0 (0.0) | 10 (3.0) | 0.3756 |
| Diabetes without chronic complications, n (%) | 57 (14.3) | 4 (6.3) | 53 (15.8) | 0.0505 |
| Diabetes with chronic complications, n (%) | 37 (9.3) | 6 (9.4) | 31 (9.2) | 1.0000 |
| Hemiplegia or paraplegia, n (%) | 9 (2.3) | 2 (3.1) | 7 (2.1) | 0.6407 |
| Renal disease, n (%) | 44 (11.0) | 7 (10.9) | 37 (11.0) | 1.0000 |
| Any malignancy, n (%) | 129 (32.3) | 22 (34.4) | 107 (31.9) | 0.7706 |
| Moderate or severe liver disease, n (%) | 16 (4.0) | 1 (1.6) | 15 (4.5) | 0.4859 |
| Metastatic solid tumor, n (%) | 28 (7.0) | 3 (4.7) | 25 (7.4) | 0.5954 |
| AIDS/HIV, n (%) | 6 (1.5) | 2 (3.1) | 4 (1.2) | 0.2466 |
| Functional capacity, n (%) good | 184 (46.0) | 11 (17.7) | 23 (7.0) | 0.0118 |
| Hospital events | ||||
| PC consult, n (%) | 7 (1.8) | 3 (4.7) | 4 (1.2) | 0.0849 |
| Underwent planned surgery, n (%) | 386 (96.5) | 62 (96.9) | 324 (96.4) | 1.0000 |
| Length of surgery, mean (SD)* | 2.9 (2.1) | 2.7 (1.7) | 2.9 (2.2) | 0.2396 |
| ICU stay, n (%)† | 56 (14.1) | 13 (20.3) | 43 (12.9) | 0.1199 |
| Postop complications | ||||
| Yes vs. none | 54 (13.6) | 12 (18.8) | 42 (12.6) | 0.2303 |
| Death, n (%) | 3 (0.8) | 1 (1.6) | 2 (0.6) | 0.4081 |
| Length of stay, mean (SD)‡ | 4.3 (5.8) | 4.5 (3.9) | 4.3 (6.2) | 0.7445 |
| Location of discharge, n (%) | 0.0002 | |||
| Home | 342 (87.69) | 44 (71.0) | 298 (90.9) | |
| Rehab | 41 (10.5) | 16 (25.8) | 25 (7.6) | |
| Other | 7 (1.8) | 2 (3.2) | 5 (1.5) | |
| Functional status on discharge, ambulatory n (%) | 356 (91.3) | 51 (82.3) | 305 (93.0) | 0.0118 |
*Length of surgery was calculated in hours from anesthesia records
†Patients who required any length of ICU stay
‡Length of stay was days spent in hospital
Multiple logistic regression examining preoperative characteristics associated with any AD found patients age 65 and older (odds ratio (OR), 2.85; 95% confidence interval (CI), 1.63, 4.98) and those with congestive heart failure (OR, 4.04; 95% CI, 1.55, 10.54) had significantly higher odds of having ADs. Men had significantly lower odds of having AD than females (OR, 0.56; 95% CI, (0.32, 0.99).
There were 14 (3.5%; n = 10 SDM/8 living will) patients who had not reported having an AD at the clinic visit but had one documented in the EMR prior to surgery and 66 (16.5%) who reported having an AD at the clinic visit but did not have one documented in the EMR prior to surgery (Table 2).
Table 2.
Frequency of Advance Directive (AD) Reported to Exist by Patient Compared to Scanned to Electronic Medical Record (EMR), n (%)
| AD reported to exist by patient | AD scanned to EMR | ||
|---|---|---|---|
| Yes | No | Total | |
| Yes | 50 (12.5) | 66 (16.5) | 116 (29.0) |
| No | 14 (3.5) | 270 (67.5) | 284 (71.0) |
| Total | 64 (16.0) | 336 (84.0) | 400 (100.0) |
DISCUSSION
Patients undergoing elective surgery and evaluated in a PAT had a low prevalence of AD, a finding similar to reports that identify low levels of ACP completion in other settings,1,4 and studies finding that the integration of ACP conversations into the preoperative clinic process is not an established norm.5 Lack of AD documentation places a burden on family members to make decisions on their loved one’s behalf without patient guidance and can lead to care that does not comport with the patient’s preference. Also, some ADs that patients report completing are not available in the EMR where clinicians could access them when needed. A limitation of this study was that it included only one health system. Local practice patterns may differ at other hospitals. Our findings suggest that there is a significant opportunity for improvement in ACP in this clinical setting. Future research should focus on processes to make ACP more available to high-risk patient populations.6
Acknowledgements
The authors would like to acknowledge Greg Sachs and Richard M. Frankel for their mentorship through the IUSM ASPIRE program.
Funding
Dr. Torke was supported by a Midcareer Investigator Award in Patient-Oriented Research (K24 AG053794).
Compliance with Ethical Standards
Conflict of Interest
The authors declare that they do not have a conflict of interest.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
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