Citations

OBJECTIVE Spinal procedures are increasingly conducted as outpatient procedures, with a growing proportion conducted in ambulatory surgery centers (ASCs). To date, studies reporting outcomes and cost analyses for outpatient spinal procedures in the US have not distinguished the various outpatient settings from each other. In this study, the authors used a state-level administrative database to compare rates of overnight stays and nonroutine discharges as well as index admission charges and cumulative 7-, 30-, and 90-day charges for patients undergoing outpatient lumbar decompression in freestanding ASCs and hospital outpatient (HO) settings. METHODS For this project, the authors used the Florida State Ambulatory Surgery Database (SASD), offered by the Healthcare Cost and Utilization Project (HCUP), for the years 2013 and 2014. Patients undergoing outpatient lumbar decompression for degenerative diseases were identified using CPT (Current Procedural Terminology) and ICD-9 codes. Outcomes of interest included rates of overnight stays, rate of nonroutine discharges, index admission charges, and subsequent admission cumulative charges at 7, 30, and 90 days. Multivariable analysis was performed to assess the impact of outpatient type on index admission charges. Marginal effect analysis was employed to study the difference in predicted dollar margins between ASCs and HOs for each insurance type. RESULTS A total of 25,486 patients were identified; of these, 7067 patients (27.7%) underwent lumbar decompression in a freestanding ASC and 18,419 (72.3%) in an HO. No patient in the ASC group required an overnight stay compared to 9.2% (n = 1691) in the HO group (p < 0.001). No clinically significant difference in the rate of nonroutine discharge was observed between the two groups. The mean index admission charge for the ASC group was found to be significantly higher than that for the HO group ($35,017.28 ± $14,335.60 vs $33,881.50 ± $15,023.70; p < 0.001). Patients in ASCs were also found to have higher mean 7-day (p < 0.001), 30-day (p < 0.001), and 90-day (p = 0.001) readmission charges. ASC procedures were associated with increased charges compared to HO procedures for patients on Medicare or Medicaid (mean index admission charge increase $4049.27, 95% CI $2577.87–$5520.67, p < 0.001) and for patients on private insurance ($4775.72, 95% CI $4171.06–$5380.38, p < 0.001). For patients on self-pay or no charge, a lumbar decompression procedure at an ASC was associated with a decrease in index admission charge of −$10,995.38 (95% CI −$12124.76 to −$9866.01, p < 0.001) compared to a lumbar decompression procedure at an HO. CONCLUSIONS These “real-world” results from an all-payer statewide database indicate that for outpatient spine surgery, ASCs may be associated with higher index admission and subsequent 7-, 30-, and 90-day charges. Given that ASCs are touted to have lower overall costs for patients and better profit margins for physicians, these analyses warrant further investigation into whether this cost benefit is applicable to outpatient spine procedures.

OBJECTIVE Sustained postoperative opioid use after elective surgery is a matter of growing concern. Herein, the authors investigated incidence and predictors of long-term opioid use among patients undergoing elective lumbar spine surgery, especially as a function of opioid prescribing practices at postoperative discharge (dose in morphine milligram equivalents [MMEs] and type of opioid). METHODS The OptumLabs Data Warehouse (OLDW) was queried for postdischarge opioid prescriptions for patients undergoing elective lumbar decompression and discectomy (LDD) or posterior lumbar fusion (PLF) for degenerative spine disease. Only patients who received an opioid prescription at postoperative discharge and those who had a minimum of 180 days of insurance coverage prior to surgery and 180 days after surgery were included. Opioid-naive patients were defined as those who had no opioid fills in 180 days prior to surgery. The following patterns of long-term postoperative use were investigated: additional fills (at least one opioid fill 90–180 days after surgery), persistent fills (any span of opioid use starting in the 180 days after surgery and lasting at least 90 days), and Consortium to Study Opioid Risks and Trends (CONSORT) criteria for persistent use (episodes of opioid prescribing lasting longer than 90 days and 120 or more total days’ supply or 10 or more prescriptions in 180 days after the index fill). Multivariable logistic regression was performed to identify predictors of long-term use. RESULTS A total of 25,587 patients were included, of whom 52.7% underwent PLF (n = 13,486) and 32.5% (n = 8312) were opioid-naive prior to surgery. The rates of additional fills, persistent fills, and CONSORT use were 47%, 30%, and 23%, respectively, after PLF and 35.4%, 19%, and 14.2%, respectively, after LDD. The rates among opioid-naive patients were 18.9%, 5.6%, and 2.5% respectively, after PLF and 13.3%, 2.0%, and 0.8%, respectively, after LDD. Using multivariable logistic regression, the following were identified to be significantly associated with higher risk of long-term opioid use following PLF: discharge opioid prescription ≥ 500 MMEs, prescription of a long-acting opioid, female sex, multilevel surgery, and comorbidities such as depression and drug abuse (all p < 0.05). Elderly (age ≥ 65 years) and opioid-naive patients were found to be at lower risk (all p < 0.05). Similar results were obtained on analysis for LDD with the following significant additional risk factors identified: discharge opioid prescription ≥ 400 MMEs, prescription of tramadol alone at discharge, and inpatient surgery (all p < 0.05). CONCLUSIONS In an analysis of pharmacy claims from a national insurance database, the authors identified incidence and predictors of long-term opioid use after elective lumbar spine surgery.

Background: Blood pressure (BP) measurement is a national core quality measure for hypertension care and hypertension control rates remain a major performance measure. It remains unclear whether improving measurement directly results in better control rates in hypertension management. Purpose: To utilize electronic medical records to explore the relationship between measurement of blood pressure and hypertension control rates among 4 eligible primary care providers groups - Primary Care Internal Medicine (PCIM), Family medicine (FM), General Internal Medicine (GIM), Preventive Medicine (PREV) - and 2 eligible specialist groups - Cardiology (CARD), Nephrology (NEPH) at an academic group medical practice. Methods: A two year cross sectional study involving adults seen by eligible primary or specialist providers at 2 or more office visits with a hypertension ICD-9 code in two years with at least one office visit in the measurement year. We measured the proportion of patients who had their BP measured at their last hypertension visit (LHV) in 2009 and 2010. We compared measurement rates with control rates as defined by the proportion of hypertension patients with BP < 140/90 mmHg at their LHV. Results: In 2009, 84.2% of 17989 patients (95% CI 83.6 - 84.7%) had their BP measured at their LHV compared to 85.3% (95% CI 84.8 - 85.8%) of 17992 patients in 2010, an increase of 1.2% (p=0.0026). Measurement rates varied widely across the different provider groups. PCIM, a high performing group, had significant improvement in measurement rates from 2009 to 2010 and demonstrated improvement in control rates. Lower performing groups, Nephrology and GIM, had significant improvement in measurement but did not see a direct translation to improved control rates. There was an associated worsening of the control rates for Preventive medicine along with a decrease in the measurement rates from 2009 to 2010. Conclusion: High BP measurement rates are associated with high hypertension control rates. Prioritizing BP measurement may result in improved intermediate outcomes in hypertension management.

Background: The diagnosis of hypertension requires systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg on at least 2 different occasions. Therefore, there is the possibility of patients with elevated BP remaining undiagnosed if not seen by the same provider. Purpose: To utilize electronic medical records (EMR) to identify patients not previously diagnosed with hypertension that have elevated blood pressure meeting criteria for a diagnosis of hypertension using a threshold of SBP ≥ 140mmHg or DBP ≥ 90 mmHg (high BP) on 2 or more occasions. Methods: This was a cross sectional design utilizing retrospective multi-year billing and clinical data from a large multi-specialty center in the Midwest. Using electronic records of all outpatient visits in each year from 2009 - 2011, patients with at least 2 visits with SBP ≥ 140mmHg or DBP ≥ 90 mmHg (2HBP) in the measurement year were identified. These patients were compared with previously identified cohorts of known hypertension patients (Known HTN) compiled using the EMR problem list. A sensitivity analysis was done using patients with high BP at 2 consecutive visits (2CHBP) and also those with high BP at 3 consecutive visits (3CHBP). We compared proportions of patients with high BP without a prior diagnosis of hypertension (UDHTN). Results: The proportion of patients with SBP ≥ 140mmHg or DBP ≥ 90 mmHg without a prior diagnosis of hypertension (UDHTN) when compared to the cohort of known patients with a diagnosis of hypertension (Known HTN) was 25% in 2009, 26% in 2010, and 28% in 2011 in the 2CHBP cohort compared to 27% in 2009, 28% in 2010, and 30% in 2011 in the 2HBP cohort and 18% in 2009, 19% in 2010 and 23% in 2011 in the 3CHBP cohort. Conclusion: About a quarter of patients meeting current thresholds on multiple and consecutive visits did not have a known diagnosis of hypertension. The use of EMR can identify these patients for commencement of appropriate management. Table 1

Background: Hypertension (HTN) control rate is a core clinical quality measure. It is presently assessed by manual review of a random sample of patients with HTN billing claims. There is an increasing push by regulators towards the use of electronic medical records (EMR) to assess quality of care. Purpose: To use EMR to obtain a more in-depth assessment of quality of hypertension care. Methods: Cross sectional study involving adults with HTN seen at 2 or more office visits in 2009 by eligible primary or specialist providers at a large medical group practice. We measured the proportion of HTN patients with blood pressure (BP) at goal (BP < 140/90 mm Hg) at their last hypertension visit (LHV). Results: Of a total of 10,401 patients, 5970 (57%) were controlled and 1959 (19%) were uncontrolled at their LHV. Control could not be assessed in 2472 (24%) as BP values were unavailable from the vital signs section of the visit notes in the EMR. Of a random sample of 250 patients with unavailable BP, only 94 (37.6%) had BP values documented in other parts of the visit note. In 29 patients (11.6%) billing for HTN was done without adequate evidence that it was addressed at that visit. Control rates were highest for primary care providers where measurement and documentation of BP was a focus - Family Medicine 77% controlled, 1% unavailable; Primary Care Internal Medicine 71% controlled, 4% unavailable. A considerable proportion of patients in the other four provider groups did not have BP available from their last hypertension visit - Cardiology 59% controlled, 22% unavailable; Nephrology 38% controlled, 47% unavailable; Preventive Medicine 48% controlled, 39% unavailable; General Internal Medicine 41% controlled, 45% unavailable. Control rates were similar across provider groups when patients with unavailable BP were excluded: Family Medicine 78%, Primary Care 74%, Cardiology 75%, Nephrology 73%, Preventive Medicine 79%, and General Medicine 75%. Conclusions: Up to a quarter of HTN patients did not have properly documented BP in the EMR at their LHV. For those with measurements recorded, control rates were similar across primary care and specialty clinics, but measurement rates were higher for primary care practices. Use of the EMR facilitates efficient and granular assessment of the measurement process and control rates for HTN among various provider groups.

Abstract Objective We aimed to develop a model for accurate prediction of general care inpatient deterioration. Materials and Methods Training and internal validation datasets were built using 2-year data from a quaternary hospital in the Midwest. Model training used gradient boosting and feature engineering (clinically relevant interactions, time-series information) to predict general care inpatient deterioration (resuscitation call, intensive care unit transfer, or rapid response team call) in 24 hours. Data from a tertiary care hospital in the Southwest were used for external validation. C-statistic, sensitivity, positive predictive value, and alert rate were calculated for different cutoffs and compared with the National Early Warning Score. Sensitivity analysis evaluated prediction of intensive care unit transfer or resuscitation call. Results Training, internal validation, and external validation datasets included 24 500, 25 784 and 53 956 hospitalizations, respectively. The Mayo Clinic Early Warning Score (MC-EWS) demonstrated excellent discrimination in both the internal and external validation datasets (C-statistic = 0.913, 0.937, respectively), and results were consistent in the sensitivity analysis (C-statistic = 0.932 in external validation). At a sensitivity of 73%, MC-EWS would generate 0.7 alerts per day per 10 patients, 45% less than the National Early Warning Score. Discussion Low alert rates are important for implementation of an alert system. Other early warning scores developed for the general care ward have achieved lower discrimination overall compared with MC-EWS, likely because MC-EWS includes both nursing assessments and extensive feature engineering. Conclusions MC-EWS achieved superior prediction of general care inpatient deterioration using sophisticated feature engineering and a machine learning approach, reducing alert rate.

Background: Managing the safety climate in health care is a promising tool for improving employee and patient safety in the health care work environment. Gaps in the theoretical and conceptual underpinnings of safety climate, as well as the evidence base for its practical application in health care remain. The purpose of this study was to evaluate the number of work injuries occurring in health care work units and associated safety climate beliefs. Methods: A retrospective analysis was conducted utilizing organizational staff survey data collected by a large medical hospital in the Midwest in 2015. Employees ( n = 32,327) were invited to identify safety climate perceptions via survey. Injuries, days restricted, and days absent were identified through the Hospital’s Occupational Safety and Health Administration (OSHA) log. Zero inflated negative binomial regressions used injuries as dependent variables and safety climate perceptions as independent variables. Findings: In all, 23,599 employees completed the survey (73% response rate) across 1,805 employee work units which were defined as groupings of employees reporting to a single supervisor. We found that there was an association between fewer injuries and health care workers indicating that they share responsibility for compliance with safety rules and procedures (relative risk [RR] = 0.98, 95% confidence interval [CI] = [0.98, 0.99]). Conclusion/Application to Practice: This study supports the use of a safety climate measure to assess working units’ perceptions of employee safety. A continued focus on the health and safety of employees who interact directly with patients is warranted, as well as employees who do not provide direct patient care.