Can Claims Data Algorithms Identify the Physician of Record?

BACKGROUND: Claims-based algorithms based on administrative claims data are frequently used to identify an individual's primary care physician (PCP). The validity of these algorithms in the US Medicare population has not been assessed. OBJECTIVE: To determine the agreement of the PCP identified by claims algorithms with the PCP of record in electronic health record data. DATA: Electronic health record and Medicare claims data from older adults with diabetes. SUBJECTS: Medicare fee-for-service beneficiaries with diabetes (N=3658) ages 65 years and older as of January 1, 2008, and medically housed at a large academic health system. MEASURES: Assignment algorithms based on the plurality and majority of visits and tie breakers determined by either last visit, cost, or time from first to last visit. RESULTS: The study sample included 15,624 patient-years from 3658 older adults with diabetes. Agreement was higher for algorithms based on primary care visits (range, 78.0% for majority match without a tie breaker to 85.9% for majority match with the longest time from first to last visit) than for claims to all visits (range, 25.4% for majority match without a tie breaker to 63.3% for majority match with the amount billed tie breaker). Percent agreement was lower for nonwhite individuals, those enrolled in Medicaid, individuals experiencing a PCP change, and those with >10 physician visits. CONCLUSIONS: Researchers may be more likely to identify a patient's PCP when focusing on primary care visits only; however, these algorithms perform less well among vulnerable populations and those experiencing fragmented care.

Apples and Oranges: Four Definitions of Multiple Chronic Conditions and their Relationship to 30-Day Hospital Readmission.

OBJECTIVES: To determine the extent of agreement between four commonly used definitions of multiple chronic conditions (MCCs) and compare each definition's ability to predict 30-day hospital readmissions. DESIGN: Retrospective cohort study. SETTING: National Medicare claims data. PARTICIPANTS: Random sample of Medicare beneficiaries discharged from the hospital from 2005 to 2009 (n = 710,609). MEASUREMENTS: Baseline chronic conditions were determined for each participant using four definitions of MCC. The primary outcome was all-cause 30-day hospital readmission. Agreement between MCC definitions was measured, and sensitivities and specificities for each definition's ability to identify patients experiencing a future readmission were calculated. Logistic regression was used to assess the ability of each MCC definition to predict 30-day hospital readmission. RESULTS: The sample prevalence of hospitalized Medicare beneficiaries with two or more chronic conditions ranged from 18.6% (Johns Hopkins Adjusted Clinical Groups (ACG) Case-Mix System software) to 92.9% (Medicare Chronic Condition Warehouse (CCW)). There was slight to moderate agreement (kappa = 0.03-0.44) between pair-wise combinations of MCC definitions. CCW-defined MCC was the most sensitive (sensitivity 95.4%, specificity 7.4%), and ACG-defined MCC was the most specific (sensitivity 32.7%, specificity 83.2%) predictor of being readmitted. In the fully adjusted model, the risk of readmission was higher for those with chronic condition Special Needs Plan (c-SNP)-defined MCCs (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.47-1.52), Charlson Comorbidity Index-defined MCCs (OR = 1.45, 95% CI = 1.42-1.47), ACG-defined MCCs (OR = 1.22, 95% CI = 1.19-1.25), and CCW-defined MCCs (OR = 1.15, 95% CI = 1.11-1.19) than for those without MCCs. CONCLUSION: MCC definitions demonstrate poor agreement and should not be used interchangeably. The two definitions with the greatest agreement (CCI, c-SNP) were also the best predictors of 30-day hospital readmissions.

Trajectories and Prognosis of Older Patients Who Have Prolonged Mechanical Ventilation After High-Risk Surgery.

OBJECTIVES: Surgical patients often receive routine postoperative mechanical ventilation with excellent outcomes. However, older patients who receive prolonged mechanical ventilation may have a significantly different long-term trajectory not fully captured in 30-day postoperative metrics. The objective of this study is to describe patterns of mortality and hospitalization for Medicare beneficiaries 66 years old and older who have major surgery with and without prolonged mechanical ventilation. DESIGN: Retrospective cohort study. SETTING: Hospitals throughout the United States. PATIENTS: Five percent random national sample of elderly Medicare beneficiaries (age ≥ 66 yr) who underwent 1 of 227 operations previously defined as high risk during an inpatient stay at an acute care hospital between January 1, 2005, and November 30, 2009. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified 117,917 episodes for older patients who had high-risk surgery; 4% received prolonged mechanical ventilation during the hospitalization. Patients who received prolonged mechanical ventilation had higher 1-year mortality rate than patients who did not have prolonged ventilation (64% [95% CI, 62-65%] vs 17% [95% CI, 16.4-16.9%]). Thirty-day survivors who received prolonged mechanical ventilation had a 1-year mortality rate of 47% (95% CI, 45-48%). Thirty-day survivors who did not receive prolonged ventilation were more likely to be discharged home than patients who received prolonged ventilation 71% versus 10%. Patients who received prolonged ventilation and were not discharged by postoperative day 30 had a substantially increased 1-year mortality (adjusted hazard ratio, 4.39 [95% CI, 3.29-5.85]) compared with patients discharged home by day 30. Hospitalized 30-day survivors who received prolonged mechanical ventilation and died within 6 months of their index procedure spent the majority of their remaining days hospitalized. CONCLUSIONS: Older patients who require prolonged mechanical ventilation after high-risk surgery and survive 30 days have a significant 1-year risk of mortality and high burdens of treatment. This difficult trajectory should be considered in surgical decision making and has important implications for surgeons, intensivists, and patients.

Medication oversupply in patients with diabetes.

BACKGROUND: Studies in integrated health systems suggest that patients often accumulate oversupplies of prescribed medications, which is associated with higher costs and hospitalization risk. However, predictors of oversupply are poorly understood, with no studies in Medicare Part D. OBJECTIVE: The aim of this study was to describe prevalence and predictors of oversupply of antidiabetic, antihypertensive, and antihyperlipidemic medications in adults with diabetes managed by a large, multidisciplinary, academic physician group and enrolled in Medicare Part D or a local private health plan. METHODS: This was a retrospective cohort study. Electronic health record data were linked to medical and pharmacy claims and enrollment data from Medicare and a local private payer for 2006-2008 to construct a patient-quarter dataset for patients managed by the physician group. Patients' quarterly refill adherence was calculated using ReComp, a continuous, multiple-interval measure of medication acquisition (CMA), and categorized as <0.80 = Undersupply, 0.80-1.20 = Appropriate Supply, >1.20 = Oversupply. We examined associations of baseline and time-varying predisposing, enabling, and medical need factors to quarterly supply using multinomial logistic regression. RESULTS: The sample included 2519 adults with diabetes. Relative to patients with private insurance, higher odds of oversupply were observed in patients aged <65 in Medicare (OR = 3.36, 95% CI = 1.61-6.99), patients 65+ in Medicare (OR = 2.51, 95% CI = 1.37-4.60), patients <65 in Medicare/Medicaid (OR = 4.55, 95% CI = 2.33-8.92), and patients 65+ in Medicare/Medicaid (OR = 5.73, 95% CI = 2.89-11.33). Other factors associated with higher odds of oversupply included any 90-day refills during the quarter, psychotic disorder diagnosis, and moderate versus tight glycemic control. CONCLUSIONS: Oversupply was less prevalent than in previous studies of integrated systems, but Medicare Part D enrollees had greater odds of oversupply than privately insured individuals. Future research should examine utilization management practices of Part D versus private health plans that may affect oversupply.

Determining breast cancer axillary surgery within the surveillance epidemiology and end results-Medicare database.

BACKGROUND: Use of sentinel lymph node biopsy (SLNB) is under-reported by cancer registries' "Scope of Regional Lymph Node Surgery" variable. In 2011, the Surveillance Epidemiology and End Results (SEER) Program recommended against its use to determine extent of axillary surgery, leaving a gap in the utilization of claims data for breast cancer research. The objective was to develop an algorithm using SEER registry and claims data to classify extent of axillary surgery for breast cancer. METHODS: We analyzed data for 24,534 breast cancer patients. CPT codes and number of examined lymph nodes classified the extent of axillary surgery. The final algorithm was validated by comparing the algorithm derived extent of axillary surgery to direct chart review for 100 breast cancer patients treated at our breast center. RESULTS: Using the algorithm, 13% had no axillary surgery, 56% SLNB and 31% axillary lymph node dissection (ALND). SLNB was performed in 77% of node negative patients and ALND in 72% of node positive. In our validation study, concordance between algorithm and direct chart review was 97%. CONCLUSIONS: Given recognized inaccuracies in cancer registries' "Scope of Regional Lymph Node Surgery" variable, these findings have high utility for health services researchers studying breast cancer treatment.

Patient demographic and tumor characteristics influencing oncologist follow-up frequency in older breast cancer survivors.

BACKGROUND: Although recommendations for breast cancer follow-up frequency exist, current follow-up guidelines are standardized, without consideration of individual patient characteristics. Some studies suggest oncologists are using these characteristics to tailor follow-up recommendations, but it is unclear how this is translating into practice. The objective of this study was to examine current patterns of oncologist breast cancer follow-up and determine the association between patient and tumor characteristics and follow-up frequency. METHODS: The Surveillance, Epidemiology, and End Results (SEER)-Medicare database was used to identify stage I-III breast cancer patients diagnosed 2000-2007 (n = 39,241). Oncologist follow-up visits were defined using Medicare specialty provider codes and the linked AMA Masterfile. Multinomial logistic regression determined the association between patient and tumor characteristics and oncologist follow-up visit frequency. RESULTS: Younger age (p < 0.001), positive nodes (p < 0.001), estrogen receptor/progesterone receptor positivity (p < 0.001), and increasing treatment intensity (p < 0.001) were most strongly associated with more frequent follow-up. However, after accounting for these characteristics, significant variation in follow-up frequency was observed. In addition to patient factors, the number and types of oncologists involved in follow-up were associated with follow-up frequency (p < 0.001). Types of oncologists providing follow-up varied, with medical oncologists the sole providers of follow-up for 19-51 % of breast cancer survivors. Overall, 58 % of patients received surgical oncology, and 51 % undergoing radiation received radiation oncology follow-up, usually in combination with medical oncology. CONCLUSIONS: Significant variation in breast cancer follow-up frequency exists. Developing follow-up guidelines tailored for patient, tumor, and treatment characteristics while also providing guidance on who should provide follow-up has the potential to increase clinical efficiency.

Coordinated primary and specialty care for type 2 diabetes mellitus, guidelines, and systems: an educational needs assessment.

OBJECTIVE: To determine knowledge, competence, and attitudinal issues among primary care providers (PCPs) and diabetes specialists regarding the use and application of evidence-based clinical guidelines and the coordination of care between PCPs and diabetes specialists specifically related to referral practices for patients with diabetes. METHODS: A survey tool was completed by 491 PCPs and 249 diabetes specialists. Data were collected from specialists online and from PCP attendees at live symposia across the United States. Results were analyzed for frequency of response and evaluation of significant relationships among the variables. RESULTS: Suboptimal practice patterns and interprofessional communication as well as gaps in diabetes-related knowledge and processes were identified. PCPs reported a lack of clarity about who, PCP or specialist, should assume clinical responsibility for the management of diabetes after a specialty referral. PCPs were most likely to refer patients to diabetes specialists for management issues relating to insulin therapy and use of advanced treatment strategies, such as insulin pens and continuous glucose monitoring. A minority of PCPs and even fewer specialists reported the routine use of clinical guidelines in practice. CONCLUSION: This research-based assessment identified critical educational needs and gaps related to coordinated care for patients with diabetes as well as the need for quality- and performance-based educational interventions.

Usage patterns of devices designed to support diabetes management: an educational needs assessment.

OBJECTIVE: To determine knowledge, competence, and attitudinal issues among diabetes specialists and primary care providers (PCPs) regarding the use of insulin delivery devices such as insulin pens and insulin pumps and the role of glucose monitoring devices and systems in the care of patients with diabetes. METHODS: A quantitative survey tool was developed that contained 51 questions directed to diabetes specialists and 49 questions directed to PCPs. A 5-point, Likert-type scale or multiple-choice format was used. Data were collected from attendees at live symposia across the United States. Results were analyzed for frequency of response and significant relationships among the variables. RESULTS: The survey was completed by 136 specialists and 418 PCPs. There were higher usage rates for insulin pens among specialists than PCPs, although there were higher usage rates among more experienced PCPs. Regarding glucose monitoring, most specialists and PCPs did not recommend "block checking," which has been commonly thought of as a reasonable compromise checking schedule for patients with type 2 diabetes not using insulin. PCPs who were more experienced and used outside educational resources, such as a certified diabetes educator, and specialists who saw more patients on a weekly basis were more likely to prescribe the use of continuous glucose monitoring. There was a general underuse of continuous glucose monitoring in eligible patients. CONCLUSIONS: These findings underscore the discordance between PCPs and specialists with regard to advanced knowledge and confidence required for the use of newer technologies for glucose monitoring and insulin replacement. We have identified important remedial opportunities for quality- and performance-based educational interventions.