Leveraging healthcare utilization to explore outcomes from musculoskeletal disorders: methodology for defining relevant variables from a health services data repository.

BACKGROUND: Large healthcare databases, with their ability to collect many variables from daily medical practice, greatly enable health services research. These longitudinal databases provide large cohorts and longitudinal time frames, allowing for highly pragmatic assessment of healthcare delivery. The purpose of this paper is to discuss the methodology related to the use of the United States Military Health System Data Repository (MDR) for longitudinal assessment of musculoskeletal clinical outcomes, as well as address challenges of using this data for outcomes research. METHODS: The Military Health System manages care for approximately 10 million beneficiaries worldwide. Multiple data sources pour into the MDR from multiple levels of care (inpatient, outpatient, military or civilian facility, combat theater, etc.) at the individual patient level. To provide meaningful and descriptive coding for longitudinal analysis, specific coding for timing and type of care, procedures, medications, and provider type must be performed. Assumptions often made in clinical trials do not apply to these cohorts, requiring additional steps in data preparation to reduce risk of bias. The MDR has a robust system in place to validate the quality and accuracy of its data, reducing risk of analytic error. Details for making this data suitable for analysis of longitudinal orthopaedic outcomes are provided. RESULTS: Although some limitations exist, proper preparation and understanding of the data can limit bias, and allow for robust and meaningful analyses. There is the potential for strong precision, as well as the ability to collect a wide range of variables in very large groups of patients otherwise not captured in traditional clinical trials. This approach contributes to the improved understanding of the accessibility, quality, and cost of care for those with orthopaedic conditions. CONCLUSION: The MDR provides a robust pool of longitudinal healthcare data at the person-level. The benefits of using the MDR database appear to outweigh the limitations.

Predictors of chronic prescription opioid use after orthopedic surgery: derivation of a clinical prediction rule.

BACKGROUND: Prescription opioid use at high doses or over extended periods of time is associated with adverse outcomes, including dependency and abuse. The aim of this study was to identify mediating variables that predict chronic opioid use, defined as three or more prescriptions after orthopedic surgery. METHODS: Individuals were ages between 18 and 50 years and undergoing arthroscopic hip surgery between 2004 and 2013. Two categories of chronic opioid use were calculated based on individuals (1) having three or more unique opioid prescriptions within 2 years and (2) still receiving opioid prescriptions > 1 year after surgery. Univariate elationships were identified for each predictor variable, then significant variables (P > 0.15) were entered into a multivariate logistic regression model to identify the most parsimonious group of predictor variables for each chronic opioid use classification. Likelihood ratios were derived from the most robust groups of variables. RESULTS: There were 1642 participants (mean age 32.5 years, SD 8.2, 54.1% male). Nine predictor variables met the criteria after bivariate analysis for potential inclusion in each multivariate model. Eight variables: socioeconomic status (from enlisted rank family), prior use of opioid medication, prior use of non-opioid pain medication, high health-seeking behavior before surgery, a preoperative diagnosis of insomnia, mental health disorder, or substance abuse were all predictive of chronic opioid use in the final model (seven variables for three or more opioid prescriptions; four variables for opioid use still at 1 year; all< 0.05). Post-test probability of having three or more opioid prescriptions was 93.7% if five of seven variables were present, and the probability of still using opioids after 1 year was 69.6% if three of four variables were present. CONCLUSION: A combination of variables significantly predicted chronic opioid use in this cohort. Most of these variables were mediators, indicating that modifying them may be feasible, and the potential focus of interventions to decrease the risk of chronic opioid use, or at minimum better inform opioid prescribing decisions. This clinical prediction rule needs further validation.

Comparison of Downstream Health Care Utilization, Costs, and Long-Term Opioid Use: Physical Therapist Management Versus Opioid Therapy Management After Arthroscopic Hip Surgery.

Background: Physical therapy and opioid prescriptions are common after hip surgery, but are sometimes delayed or not used. Objective: The objective of this study was to compare downstream health care utilization and opioid use following hip surgery for different patterns of physical therapy and prescription opioids. Design: The design of this study was an observational cohort. Methods: Health care utilization was abstracted from the Military Health System Data Repository for patients who were 18 to 50 years old and were undergoing arthroscopic hip surgery between 2004 and 2013. Patients were grouped into those receiving an isolated treatment (only opioids or only physical therapy) and those receiving both treatments on the basis of timing (opioid first or physical therapy first). Outcomes included overall health care visits and costs, hip-related visits and costs, additional surgeries, and opioid prescriptions. Results: Of 1870 total patients, 76.8% (n = 1437) received physical therapy, 71.6% (n = 1339) received prescription opioids, and 1073 (56.1%) received both physical therapy and opioids. Because 24 patients received both opioids and physical therapy on the same day, they were eventually removed the final timing-of-care analysis. Adjusted hip-related mean costs were the same in both groups receiving isolated treatments (${\$}$11,628 vs ${\$}$11,579), but the group receiving only physical therapy had significantly lower overall total health care mean costs (${\$}$18,185 vs ${\$}$23,842) and fewer patients requiring another hip surgery. For patients receiving both treatments, mean hip-related downstream costs were significantly higher in the group receiving opioids first than in the group receiving physical therapy first (${\$}$18,806 vs ${\$}$16,955) and resulted in greater opioid use (7.83 vs 4.14 prescriptions), greater total days' supply of opioids (90.17 vs 44.30 days), and a higher percentage of patients with chronic opioid use (69.5% vs 53.2%). Limitations: Claims data were limited by the accuracy of coding, and observational data limit inferences of causality. Conclusions: Physical therapy first was associated with lower hip-related downstream costs and lower opioid use than opioids first; physical therapy instead of opioids was associated with less total downstream health care utilization. These results need to be validated in prospective controlled trials.

Does Health Care Utilization Before Hip Arthroscopy Predict Health Care Utilization After Surgery in the US Military Health System? An Investigation Into Health-Seeking Behavior.

BACKGROUND: The influence of prior patterns of health care utilization on future health care utilization has had minimal investigation in populations with musculoskeletal disorders. OBJECTIVES: The purpose of this study was to explore the relationship between presurgical health care utilization and postsurgical health care utilization in a population of patients undergoing hip surgery in the US Military Health System. METHODS: In this observational cohort study, person-level data were collected for patients undergoing hip arthroscopy in the Military Health System from 2003 to 2015, capturing all encounters 12 months before and 24 months after surgery for every individual. Cluster analysis was used to categorize individuals with high and low health care utilization, based on preoperative health care visits. Unadjusted and adjusted Poisson and generalized linear models were generated. Health care utilization outcomes were targeted, including costs, visits, and medication use. RESULTS: There were 1850 individuals in the final cohort (mean age, 32.18 years; 55.4% male). The high health care utilization group averaged 57.69 ± 25.87 visits, compared to 20.43 ± 8.36 visits in the low utilization group. There were significant differences between groups for total health care visits (58.17; 95% confidence interval [CI]: 57.39, 58.58), total health care costs ($11 539.71; 95% CI: $10 557.26, $12 595.04), hip-related visits (12.77; 95% CI: 12.59, 12.96), hip-related costs ($3325.07; 95% CI: $2886.43, $3804.51), days' supply of pain medications (752.67; 95% CI: 751.24, 754.11), opioid prescriptions (48.83; 95% CI: 48.47, 49.21), and cost of pain medications ($1074.80; 95% CI: $1011.91, $1137.68). CONCLUSION: Presurgical patterns of health care utilization were associated with postsurgical patterns of health care utilization, indicating that those patients who used more care before surgery also used more care after surgery. Clinicians should consider prior patterns of health care utilization, including utilization unrelated to the index condition, when determining care plans and prognosis. J Orthop Sports Phys Ther 2018;48(11):878-886. Epub22 Jul 2018. doi:10.2519/jospt.2018.8259.