Organization of Cancer Specialists in US Physician Practices and Health Systems.

PURPOSE: To describe the supply of cancer specialists, the organization of cancer care within versus outside of health systems, and the distance to multispecialty cancer centers. METHODS: Using the 2018 Health Systems and Provider Database from the National Bureau of Economic Research and 2018 Medicare data, we identified 46,341 unique physicians providing cancer care. We stratified physicians by discipline (adult/pediatric medical oncologists, radiation oncologists, surgical/gynecologic oncologists, other surgeons performing cancer surgeries, or palliative care physicians), system type (National Cancer Institute [NCI] Cancer Center system, non-NCI academic system, nonacademic system, or nonsystem/independent practice), practice size, and composition (single disciplinary oncology, multidisciplinary oncology, or multispecialty). We computed the density of cancer specialists by county and calculated distances to the nearest NCI Cancer Center. RESULTS: More than half of all cancer specialists (57.8%) practiced in health systems, but 55.0% of cancer-related visits occurred in independent practices. Most system-based physicians were in large practices with more than 100 physicians, while those in independent practices were in smaller practices. Practices in NCI Cancer Center systems (95.2%), non-NCI academic systems (95.0%), and nonacademic systems (94.3%) were primarily multispecialty, while fewer independent practices (44.8%) were. Cancer specialist density was sparse in many rural areas, where the median travel distance to an NCI Cancer Center was 98.7 miles. Distances to NCI Cancer Centers were shorter for individuals living in high-income areas than in low-income areas, even for individuals in suburban and urban areas. CONCLUSION: Although many cancer specialists practiced in multispecialty health systems, many also worked in smaller-sized independent practices where most patients were treated. Access to cancer specialists and cancer centers was limited in many areas, particularly in rural and low-income areas.

Using Consistently Low Performance to Identify Low-Quality Physician Groups.

Importance: There has been a growth in the use of performance-based payment models in the past decade, but inherently noisy and stochastic quality measures complicate the assessment of the quality of physician groups. Examining consistently low performance across multiple measures or multiple years could potentially identify a subset of low-quality physician groups. Objective: To identify low-performing physician groups based on consistently low performance after adjusting for patient characteristics across multiple measures or multiple years for 10 commonly used quality measures for diabetes and cardiovascular disease (CVD). Design, Setting, and Participants: This cross-sectional study used medical and pharmacy claims and laboratory data for enrollees ages 18 to 65 years with diabetes or CVD in an Aetna health insurance plan between 2016 and 2019. Each physician group's risk-adjusted performance for a given year was estimated using mixed-effects linear probability regression models. Performance was correlated across measures and time, and the proportion of physician groups that performed in the bottom quartile was examined across multiple measures or multiple years. Data analysis was conducted between September 2020 and May 2021. Exposures: Primary care physician groups. Main Outcomes and Measures: Performance scores of 6 quality measures for diabetes and 4 for CVD, including hemoglobin A1c (HbA1c) testing, low-density lipoprotein testing, statin use, HbA1c control, low-density lipoprotein control, and hospital-based utilization. Results: A total of 786 641 unique enrollees treated by 890 physician groups were included; 414 655 (52.7%) of the enrollees were men and the mean (SD) age was 53 (9.5) years. After adjusting for age, sex, and clinical and social risk variables, correlations among individual measures were weak (eg, performance-adjusted correlation between any statin use and LDL testing for patients with diabetes, r = -0.10) to moderate (correlation between LDL testing for diabetes and LDL testing for CVD, r = .43), but year-to-year correlations for all measures were moderate to strong. One percent or fewer of physician groups performed in the bottom quartile for all 6 diabetes measures or all 4 cardiovascular disease measures in any given year, while 14 (4.0%) to 39 groups (11.1%) were in the bottom quartile in all 4 years for any given measure other than hospital-based utilization for CVD (1.1%). Conclusions and Relevance: A subset of physician groups that was consistently low performing could be identified by considering performance measures across multiple years. Considering the consistency of group performance could contribute a novel method to identify physician groups most likely to benefit from limited resources.

Association Between Clinical Practice Group Adherence to Quality Measures and Adverse Outcomes Among Adult Patients With Diabetes.

Importance: Clinical practice group performance on quality measures associated with chronic disease management has become central to reimbursement. Therefore, it is important to determine whether commonly used process and disease control measures for chronic conditions correlate with utilization-based outcomes, as they do in acute disease. Objective: To examine the associations among clinical practice group performance on diabetes quality measures, including process measures, disease control measures, and utilization-based outcomes. Design, Setting, and Participants: This retrospective, cross-sectional analysis examined commercial claims data from a national health insurance plan. A cohort of eligible beneficiaries with diabetes aged 18 to 65 years who were enrolled for at least 12 months from January 1, 2010, through December 31, 2014, was defined. Eligible beneficiaries were attributed to a clinical practice group based on the plurality of their primary care or endocrinology office visits. Data were analyzed from October 1, 2018, through April 30, 2019. Main Outcomes and Measures: For each clinical practice group, performance on current diabetes quality measures included 3 process measures (2 testing measures [hemoglobin A1c {HbA1c} and low-density lipoprotein {LDL} testing] and 1 drug use measure [statin use]) and 2 disease control measures (HbA1c <8% and LDL level <100 mg/dL). The rates of utilization-based outcomes, including hospitalization for diabetes and major adverse cardiovascular events (MACEs), were also measured. Results: In this cohort of 652 258 beneficiaries with diabetes from 886 clinical practice groups, 42.9% were aged 51 to 60 years, and 52.6% were men. Beneficiaries lived in areas that were predominantly white (68.1%). At the clinical practice group level, except for high correlation between the 2 testing measures, correlations among different quality measures were weak (r range, 0.010-0.244). Rate of HbA1c of less than 8% had the strongest correlation with hospitalization for MACE (r = -0.046; P = .03) and diabetes (r = -0.109; P < .001). Rates of HbA1c control at the clinical practice group level were not significantly associated with likelihood of hospitalization at the individual level. Performance on the process and disease control measures together explained 3.9% of the variation in the likelihood of hospitalization for a MACE or diabetes at the individual level. Conclusions and Relevance: In this study, performance on utilization-based measures-intended to reflect the quality of chronic disease management-was only weakly associated with direct measures of chronic disease management, namely, disease control measures. This correlation should be considered when determining the degree of financial emphasis to place on hospitalization rates as a measure of quality in treatment of chronic diseases.

Social Risk Adjustment of Quality Measures for Diabetes and Cardiovascular Disease in a Commercially Insured US Population.

Importance: Patients' social risk factors may be associated with physician group performance on quality measures. Objective: To examine the association of social risk with change in physician group performance on diabetes and cardiovascular disease (CVD) quality measures in a commercially insured population. Design, Setting, and Participants: In this cross-sectional study using claims data from 2010 to 2014 from a US national health insurance plan, the performance of 1400 physician groups (physicians billing under the same tax identification number) was estimated. After base adjustments for age and sex, changes in variation across groups and reordering of rankings resulting from additional adjustments for clinical, social, or both clinical and social risk factors were analyzed. In all models, only within-group associations were adjusted to distinguish the association of patients' social risk factors with outcomes while excluding physician groups' distinct characteristics that could also change observed performance. Data analysis was conducted between April and July 2018. Main Outcomes and Measures: Process measures (hemoglobin A1c [HbA1c] testing, low-density lipoprotein cholesterol [LDL-C] testing, and statin use), disease control measures (HbA1c and LDL-C level control), and use-based outcome measures (hospitalizations for ambulatory-sensitive conditions) were calculated with base adjustment (age and sex), clinical adjustment, social risk factor adjustment, and both clinical and social adjustments. Quality variance in physician group performance and changes in rankings following these adjustments were measured. Results: This study identified 1 684 167 enrollees (859 618 [51%] men) aged 18 to 65 years (mean [SD] age, 50 [10.7] years) with diabetes or CVD. Performance rates were high for HbA1c and LDL-C level testing (mean ranged from 79.5% to 87.2%) but lower for statin use (54.7% for diabetes cohort and 44.2% for CVD cohort) and disease control measures (57.9% on LDL-C control for diabetes cohort and 40.0% for CVD cohort). On average, only 8.8% of enrollees with diabetes and 1.0% of enrollees with CVD in a group were hospitalized. The addition of clinical and social risk factors to base adjustment reduced variance across physician groups for most measures (percentage change in SD ranged from -13.9% to 1.6%). Although overall agreement between performance scores with base vs full adjustment was high, there was still substantial reordering for some measures. For example, social risk adjustment resulted in reordering for disease control in the diabetes cohort. Of the 1400 physician groups, 330 (23.6%) had performance rankings for HbA1c control that increased or decreased by at least 10 percentile points after adding social risk factors to age and sex. Both clinical and social risk adjustment affected rankings on hospital admissions. Conclusions and Relevance: Accounting for social risk may be important to mitigate adverse consequences of performance-based payments for physician groups serving socially vulnerable populations.

Comparison of Approaches for Aggregating Quality Measures in Population-based Payment Models.

OBJECTIVE: To assess the impact of alternative methods of aggregating individual quality measures on Accountable Care Organization (ACO) overall scores. DATA SOURCE: 2014 quality scores for Medicare ACOs. STUDY DESIGN: We compare ACO overall scores derived using CMS' aggregation approach to those derived using alternative approaches to grouping and weighting measures. PRINCIPAL FINDINGS: Alternative grouping and weighting methods based on statistical criteria produced overall quality scores similar to those produced using CMS' approach (κ = 0.80 to 0.95). Scores derived from giving specific domains greater weight were less similar (κ = 0.51 to 0.93). CONCLUSIONS: How measures are grouped into domains and how these domains are weighted to generate overall scores can have important implications for ACO's shared savings payments.

Public Opinion Regarding Financial Incentives to Engage in Advance Care Planning and Complete Advance Directives.

BACKGROUND: The Centers for Medicare & Medicaid Services (CMS) recently instituted physician reimbursements for advance care planning (ACP) discussions with patients. AIM: To measure public support for similar programs. DESIGN: Cross-sectional online and in-person surveys. SETTING/PARTICIPANTS: English-speaking adults recruited at public parks in Philadelphia, Pennsylvania, from July to August 2013 and online through survey sampling international Web-based recruitment platform in July 2015. Participants indicated support for 6 programs designed to increase advance directive (AD) completion or ACP discussion using 5-point Likert scales. Participants also indicated how much money (US$0-US$1000) was appropriate to incentivize such behaviors, compared to smoking cessation or colonoscopy screening. RESULTS: We recruited 883 participants: 503 online and 380 in-person. The status quo of no systematic approach to motivate AD completion was supported by 67.0% of participants (63.9%-70.1%). The most popular programs were paying patients to complete ADs (58.0%; 54.5%-61.2%) and requiring patients to complete ADs or declination forms for health insurance (54.1%; 50.8%-57.4%). Participants more commonly supported paying patients to complete ADs than paying physicians whose patients complete ADs (22.6%; 19.8%-25.4%) or paying physicians who document ACP discussions (19.1%; 16.5%-21.7%; both P < .001). Participants supported smaller payments for AD completion and ACP than for obtaining screening colonoscopies or stopping smoking. CONCLUSIONS: Americans view payments for AD completion or ACP more skeptically than for other health behaviors and prefer that such payments go to patients rather than physicians. The current CMS policy of reimbursing physicians for ACP conversations with patients was the least preferred of the programs evaluated.

Stability of end-of-life preferences: a systematic review of the evidence.

IMPORTANCE: Policies and practices that promote advance care planning and advance directive completion implicitly assume that patients' choices for end-of-life (EOL) care are stable over time, even with changes in health status. OBJECTIVE: To systematically evaluate the evidence on the stability of EOL preferences over time and with changes in health status. EVIDENCE REVIEW: We searched for longitudinal studies of patients' preferences for EOL care in PubMed, EMBASE, and using citation review. Studies restricted to preferences regarding the place of care at the EOL were excluded. FINDINGS: A total of 296 articles were assessed for eligibility, and 59 met inclusion criteria. Twenty-four articles had sufficient data to extract or calculate the percentage of individuals with stable preferences or the percentage of total preferences that were stable over time. In 17 studies (71%) more than 70% of patients' preferences for EOL care were stable over time. Preference stability was generally greater among inpatients and seriously ill outpatients than among older adults without serious illnesses (P < .002). Patients with higher education and who had engaged in advance care planning had greater preference stability, and preferences to forgo therapies were generally more stable than preferences to receive therapies. Among 9 of the 24 studies (38%) assessing changes in health status, no consistent relationship with preference changes was identified. CONCLUSIONS AND RELEVANCE: Considerable variability among studies in the methods of preference assessment, the time between assessments, and the definitions of stability preclude meta-analytic estimates of the stability of patients' preferences and the factors influencing these preferences. Although more seriously ill patients and those who engage in advance care planning most commonly have stable preferences for future treatments, further research in real-world settings is needed to confirm the utility of advance care plans for future decision making.