Trends in hospital coding for people experiencing homelessness in Canada, 2015-2020: a descriptive study.

BACKGROUND: In 2018, hospitals were mandated to record homelessness using International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA code Z59.0). We sought to answer whether the coding mandate affected the volume of patients identified as experiencing homelessness in acute inpatient hospitalizations and if there was any geographic variation. METHODS: We conducted a serial cross-sectional study describing 6 fiscal years (2015/16 to 2020/21) of hospital administrative data from the Hospital Morbidity Database. We reported frequencies and percentages of hospitalizations with a Z59.0 diagnostic code and disaggregated by several types of Canadian geographies. Controlling for fiscal quarter (coded Q1 to Q4) and province or territory, adjusted logistic regression models quantified the odds of Z59.0 being coded during hospital stays. RESULTS: The frequency and percentage of people experiencing homelessness in hospitalization records across Canada increased from 6934 (0.12%) in 2015/16 to 21 529 (0.41%) in 2020/21. Trends varied by province and territory. Recording of the Z59.0 code increased following the mandate (adjusted odds ratio 2.29, 95% confidence interval 2.25-2.32), relative to the pre-mandate period. INTERPRETATION: The 2018 coding mandate coincided with an increase in the use of the Z59.0 code to document homelessness in health care administrative data; however, trends varied by jurisdiction. The ICD-10-CA code Z59.0 presents a promising opportunity for standardized and routinely collected data to identify people experiencing homelessness in hospital administrative data.

A Personalized Medicine Approach for the Management of Spinal Metastases with Cord Compression: Development of a Novel Clinical Prediction Model for Postoperative Survival and Quality of Life.

Surgery should be considered for patients with metastatic epidural spinal cord compression (MESCC) with a life expectancy of ≥3 months. Given the heterogeneity of the clinical presentation and outcomes, clinical prognostic models (CPMs) can assist in tailoring a personalized medicine approach to optimize surgical decision-making. We aimed to develop and internally validate the first CPM of health-related quality of life (HRQoL) and a novel CPM to predict the survival of patients with MESCC treated surgically. Using data from 258 patients (AOSpine North America MESCC study and Nottingham MESCC registry), we created 1-year survival and HRQoL CPMs using a Cox model and logistic regression analysis with manual backward elimination. The outcome measure for HRQoL was the minimal clinical important difference in EuroQol 5-dimension questionnaire scores. Internal validation involved 200 bootstrap iterations, and calibration and discrimination were evaluated. Longer survival was associated with a higher SF-36 physical component score (hazard ratio [HR], 0.96). In contrast, primary tumor other than breast, thyroid, or prostate (unfavorable: HR, 2.57; other: HR, 1.20), organ metastasis (HR, 1.51), male sex (HR, 1.58), and preoperative radiotherapy (HR, 1.53) were not (c-statistic, 0.69; 95% confidence interval, 0.64-0.73). Karnofsky performance status <70% (odds ratio [OR], 2.50), living in North America (OR, 4.06), SF-36 physical component score (OR, 0.95) and SF-36 mental component score (OR, 0.96) were associated with the likelihood of achieving a minimal clinical important difference improvement in the EuroQol 5-Dimension Questionnaire score at 3 months (c-statistic, 0.74; 95% confidence interval, 0.68-0.79). The calibration for both CPMs was very good. We developed and internally validated the first CPMs of survival and HRQoL at 3 months postoperatively in patients with MESCC using the TRIPOD (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis) guidelines. A web-based calculator is available (available at: http://spine-met.com) to assist with clinical decision-making.

Utilizing Patient E-learning in an Intervention Study on Preoperative Smoking Cessation.

BACKGROUND: Patients who smoke put themselves at increased risk for serious surgical complications, yet it is not currently routine practice to educate patients about the risk of complications due to smoking. Computer-based smoking cessation programs are increasingly being utilized in the general population and may overcome some of the barriers such as lack of time, knowledge, and training to provide interventions. Our objective was to develop and implement a patient e-learning program designed for surgical patients as part of a multifaceted program aimed at assisting them to quit smoking and to determine the factors cross-sectionally and longitudinally associated with abstinence. METHODS: In this prospective multicenter study, smokers undergoing elective noncardiac surgery participated in a preoperative smoking cessation program consisting of a patient e-learning program, brief advice, educational pamphlet, tobacco quitline referral, letter to the primary care physician, and pharmacotherapy. The patient e-learning program described (1) the benefits of quitting smoking before surgery; (2) how to quit smoking; and (3) how to cope while quitting. The 7-day point prevalence (PP) abstinence on the day of surgery and at 1, 3 and 6 six months after surgery was separately assessed, and factors most associated with abstinence were identified using multivariable logistic regression analysis. Generalized estimating equation methods were used to estimate effect of the factors associated with abstinence longitudinally. The reach of the program was assessed with the number of smokers who participated in the program versus the number of patients who were referred to the program. RESULTS: A total of 459 patients (68.9% of eligible patients) participated. The 7-day PP abstinence at day of surgery, 1 month, 3 months, and 6 months was 22%, 29%, 25%, and 22%, respectively. The variables predicting abstinence at 6 months were use of pharmacotherapy (odds ratio [OR], 7.32; 95% confidence interval [CI], 3.71-14.44; P < .0001) and number of contacts with a tobacco quitline (OR, 1.60; 95% CI, 1.35-1.90; P < .0001). Presence of other smokers in the household (OR, 0.39; 95% CI, 0.21-0.72; P = .0030) and amount spent on cigarettes weekly at baseline (per $10 increase) (OR, 0.73; 95% CI, 0.61-0.87; P = .0004) were barriers to abstinence. CONCLUSIONS: Our preoperative smoking cessation program resulted in a 7-day PP abstinence of 22% at 6 months. A multifaceted intervention including a patient e-learning program may be a valuable tool to overcome some of the barriers to help surgical patients quit smoking.