Risk calculators can be of great value in guiding clinical decision making, patient-centered precision medicine, and resource allocation.1 Several perioperative risk prediction models have emerged in recent decades that estimate specific hazards (eg, cardiovascular complications after noncardiac surgery) with varying accuracy and utility. In the perioperative sphere, the time windows are often limited to an index hospitalization or 30 days following surgery or discharge.2-9 Although longer periods are of interest to patients, families, and health systems, few widely used or validated models are designed to look beyond this very narrow window.10,11 In addition, perioperative risk prediction models do not routinely incorporate parameters of a wide variety of health or demographic domains, such as patterns of health care, health care utilization, or medication use.
In 2013, in response to the need for near real-time information to guide delivery of enhanced care management services, the Veterans Health Administration (VHA) Office of Informatics and Analytics developed automated risk prediction models that used detailed electronic health record (EHR) data. These models were used to report Care Assessment Need (CAN) scores each week for all VHA enrollees and include data from a wide array of health domains. These CAN scores predict the risk for hospitalization, death, or either event within 90 days and 1 year.12,13 Each score is reported as both a predicted probability (0-1) and as a percentile in relation to all other VHA enrollees (a value between 1 and 99).13 The data used to calculate CAN scores are listed in Table 1.12
Surgical procedures or admissions would not be differentiated from nonsurgical admissions or other procedural clinic visits, and as such, it is not possible to isolate the effect of undergoing a surgical procedure from another health-related event on the CAN score. At the same time though, a short-term increase in system utilization caused by an elective surgical procedure such as a total knee replacement (TKR) would presumably be reflected in a change in CAN score, but this has not been studied.
Since their introduction, CAN scores have been routinely accessed by primary care teams and used to facilitate care coordination for thousands of VHA patients. However, these CAN scores are currently not available to VHA surgeons, anesthesiologists, or other perioperative clinicians. In this study, we examine the distributions of preoperative CAN scores and explore the relationships of preoperative CAN 1-year mortality scores with 1-year survival following discharge and length of stay (LOS) during index hospitalization in a cohort of US veterans who underwent TKR, the most common elective operation performed within the VHA system.
Methods
Following approval of the Durham Veterans Affairs Medical Center Institutional Review Board, all necessary data were extracted from the VHA Corporate Data Warehouse (CDW) repository.14 Informed consent was waived due to the minimal risk nature of the study.
We used Current Procedural Terminology codes (27438, 27446, 27447, 27486, 27487, 27488) and International Classification of Diseases, 9th edition clinical modification procedure codes (81.54, 81.55, 81.59, 00.80-00.84) to identify all veterans who had undergone primary or revision TKR between July 2014 and December 2015 in VHA Veterans Integrated Service Network 1 (Maine, Vermont, New Hampshire, Massachusetts, Connecticut, Rhode Island, New York, Pennsylvania, West Virginia, Virginia, North Carolina). Because we focused on outcomes following hospital discharge, patients who died before discharge were excluded from the analysis. Preoperative CAN 1-year mortality score was chosen as the measure under the assumption that long-term survival may be the most meaningful of the 4 possible CAN score measures.
Our primary objective was to determine distribution of preoperative CAN scores in the study population. Our secondary was to study relationships among the preoperative CAN 1-year mortality scores and 1-year mortality and hospital LOS.
Study Variables
For each patient, we extracted the date of index surgery. The primary exposure or independent variable was the CAN score in the week prior to this date. Because prior study has shown that CAN scores trajectories do not significantly change over time, the date-stamped CAN scores in the week before surgery represent what would have been available to clinicians in a preoperative setting.15 Since CAN scores are refreshed and overwritten every week, we extracted archived scores from the CDW.