Evaluation of Physician Network-Based Measures of Care Coordination Using Medicare Patient-Reported Experience Measures

A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research

Social network analysis is the study of the structure of relationships between social entities. Access to health care administrative datasets has facilitated use of "patient-sharing networks" to infer relationships between health care providers based on the extent to which they have encounters with common patients. The structure and nature of patient-sharing relationships can reflect observed or latent aspects of health care delivery systems, such as collaboration and influence. We conducted a scoping review of peer-reviewed studies that derived patient-sharing network measure(s) in the analyses. There were 134 papers included in the full-text review. We identified and created a centralized resource of 118 measures and uncovered three major themes captured by them: Influential and Key Players, Care Coordination and Teamwork, and Network Structure and Access to Care. Researchers may use this review to inform their use of patient-sharing network measures and to guide the development of novel measures.

Rural-Urban Differences in Patient-Sharing by Clinicians Caring for Children with Medical Complexity: Network Analysis of the Pediatric Workforce in Three States

OBJECTIVE

To examine rural-urban differences in the clinician workforce caring for children with medical complexity (CMC) in ambulatory settings and to determine how measures of clinician patient-sharing differ for rural- and urban-residing CMC.

STUDY DESIGN

We analyzed Massachusetts, New Hampshire, and Colorado all-payer claims data from 2012 through 2017 to identify CMC and their clinicians. We assembled patient-sharing networks in which clinicians were connected on the basis of having encounters with common pediatric patients. We evaluated rural-urban differences in CMC care team size, composition (ie, which specialists were included), and care density (ie, extent to which a CMC's care team shared patients) and network measures of primary care clinician (PCC) centrality (eg, number of patient-sharing relationships).

RESULTS

Analysis included 107 692 CMC, of whom 7065 (7.0%) were rural-residing and 100 627 (93.0%) were urban-residing. Rural-residing CMC had lower relative risk of having a PCC specialized in pediatrics (relative risk 0.81, 95% CI 0.73-0.89) compared with urban-residing CMC. Despite having similarly sized care teams, rural-residing CMC had substantially lower care density (median [IQR] = 21.6 [7.9, 72.8]) compared with urban-residing CMC (median [IQR] = 48.3 [13.0, 158.7]). Rural PCC were less central in the networks and had a greater percentage of connections with advanced practice providers compared with their urban counterparts (median [IQR] = 19.2 [14.3, 24.5] vs 14.3 [7.5, 23.4]).

CONCLUSIONS

Our study provides new insight into the clinicians and teams caring for CMC. Rural-residing CMC were more likely to receive care from clinicians with fewer connections and lower care density, reflecting fewer shared patients within the team. Programs supporting care of CMC may benefit from recognizing rural-urban differences in team composition and relationships between clinicians.

Within-Physician Differences in Patient Sharing Between Primary Care Physicians and Cardiologists Who Treat White and Black Patients With Heart Disease

BACKGROUND

Black-White disparities in heart disease treatment may be attributable to differences in physician referral networks. We mapped physician networks for Medicare patients and examined within-physician Black-White differences in patient sharing between primary care physicians and cardiologists.

METHODS AND RESULTS

Using Medicare fee-for-service files for 2016 to 2017, we identified a cohort of Black and White patients with heart disease and the primary care physicians and cardiologists treating them. To ensure the robustness of within-physician comparisons, we restricted the sample to regional health care markets (ie, hospital referral regions) with at least 10 physicians sharing ≥3 Black and White patients. We used claims to construct 2 race-specific physician network measures: degree (number of cardiologists with whom a primary care physician shares patients) and transitivity (network tightness). Measures were adjusted for Black-White differences in physician panel size and calculated for all settings (hospital and office) and for office settings only. Of 306 US hospital referral regions, 226 and 145 met study criteria for all settings and office setting analyses, respectively. Black patients had more cardiology encounters overall (6.9 versus 6.6; P<0.001) and with unique cardiologists (3.0 versus 2.6; P<0.001), but fewer office encounters (31.7% versus 41.1%; P<0.001). Primary care physicians shared Black patients with more cardiologists than White patients (mean differential degree 23.4 for all settings and 3.6 for office analyses; P<0.001 for both). Black patient-sharing networks were less tightly connected in all but office settings (mean differential transitivity -0.2 for all settings [P<0.001] and near 0 for office analyses [P=0.74]).

CONCLUSIONS

Within-physician Black-White differences in patient sharing exist and may contribute to disparities in cardiac care.

Density of Patient-Sharing Networks: Impact on the Value of Parkinson Care

BACKGROUND

Optimal care for Parkinson's disease (PD) requires coordination and collaboration between providers within a complex care network. Individual patients have personalised networks of their own providers, creating a unique informal network of providers who treat ('share') the same patient. These 'patient-sharing networks' differ in density, ie, the number of identical patients they share. Denser patient-sharing networks might reflect better care provision, since providers who share many patients might have made efforts to improve their mutual care delivery. We evaluated whether the density of these patient-sharing networks affects patient outcomes and costs.

METHODS

We analysed medical claims data from all PD patients in the Netherlands between 2012 and 2016. We focused on seven professional disciplines that are commonly involved in Parkinson care. We calculated for each patient the density score: the average number of patients that each patient's providers shared. Density scores could range from 1.00 (which might reflect poor collaboration) to 83.00 (which might reflect better collaboration). This score was also calculated at the hospital level by averaging the scores for all patients belonging to a specific hospital. Using logistic and linear regression analyses we estimated the relationship between density scores and health outcomes, healthcare utilization, and healthcare costs.

RESULTS

The average density score varied considerably (average 6.7, SD 8.2). Adjusted for confounders, higher density scores were associated with a lower risk of PD-related complications (odds ratio [OR]: 0.901; P<.001) and with lower healthcare costs (coefficients: -0.018, P=.005). Higher density scores were associated with more frequent involvement of neurologists (coefficient 0.068), physiotherapists (coefficient 0.052) and occupational therapists (coefficient 0.048) (P values all <.001).

CONCLUSION

Patient sharing networks showed large variations in density, which appears unwanted as denser networks are associated with better outcomes and lower costs.

The Effect of Interdependences of Referral Behaviors on the Quality of Ambulatory Care: Evidence from Taiwan

Purpose

The purpose of this study is to investigate the effect of interdependences of healthcare providers’ referral behaviors on the quality of ambulatory care. The significance of this study is to address the concern regarding the low quality of ambulatory care due to the lack of a compulsory referral system under Taiwan’s National Health Insurance system.

Methods

We applied the dynamic connectedness network analysis to estimate the total connectedness index of the referral behavior network, which was separated into the horizontal and vertical referral behavior components in order to measure the interdependences of horizontal and vertical referral behaviors across hospitals and local clinics, respectively.

Results

Our results suggest that the interdependences of referral behaviors increase the quality of ambulatory care. The harmful effect on the quality of ambulatory care from the interdependences of horizontal referral behaviors within the local clinics sector is more significant than that from the interdependences of horizontal referral behaviors within the hospital sector, and the negative effect on the overall and chronic composite measures of avoidable hospital admissions from the interdependences of vertical behaviors associated with local clinics is more substantial than that from the interdependences of vertical behaviors within the hospital sector.

Conclusion

These results not only highlight the significance of care collaboration between local clinics and hospitals to restrain avoidable hospital admissions of chronic diseases for a better overall quality of ambulatory care, but they also suggest that the surveillance system established for the quality of ambulatory care under the global budget payment scheme for the local clinics sector should target ambulatory care for patients with acute conditions.

Changes in patient experiences and assessment of gaming among large clinician practices in precursors of the Merit-Based Incentive Payment System

Question

Do clinician practices game pay-for-performance programs by selectively reporting measures on which they already perform well, and does mandating public reporting on patient experience measures improve care?

Findings

In this cross-sectional analysis of patient experience data from Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys, practices were more likely to voluntarily include CAHPS measures in a Medicare pay-for-performance program when they previously scored higher on these measures. However, mandatory public reporting of CAHPS measures was not associated with improved patient experiences with care.

Meaning

These findings support calls to end voluntary measure selection in public reporting and pay-for-performance programs, including Medicare’s Merit-Based Incentive Payment System, but also suggest that requiring practices to report on patient experiences may not produce gains.

Importance

Medicare’s Merit-Based Incentive Payment System (MIPS), a public reporting and pay-for-performance program, adjusts clinician payments based on publicly reported measures that are chosen primarily by clinicians or their practices. However, measure selection raises concerns that practices could earn bonuses or avoid penalties by selecting measures on which they already perform well, rather than by improving care—a form of gaming. This has prompted calls for mandatory reporting on a smaller set of measures including patient experiences.

Objective

To examine (1) practices’ selection of Consumer Assessment of Healthcare Providers and Systems (CAHPS) patient experience measures for quality scoring under the pay-for-performance program and (2) the association between mandated public reporting on CAHPS measures and performance on those measures within precursor programs of the MIPS.

Design, Setting, and Participants

This cross-sectional study included 2 analyses. The first analysis examined the association between the baseline CAHPS scores of large practices (≥100 clinicians) and practices’ selection of these measures for quality scoring under a pay-for-performance program up to 2 years later. The second analysis examined changes in patient experiences associated with a requirement that large practices publicly report CAHPS measures starting in 2014. A difference-in-differences analysis of 2012 to 2017 fee-for-service Medicare CAHPS data was conducted to compare changes in patient experiences between large practices (111-150 clinicians) that became subject to this reporting mandate and smaller unaffected practices (50-89 clinicians). Analyses were conducted between October 1, 2020, and July 30, 2021.

Main Outcomes and Measures

The primary outcomes of the 2 analyses were (1) the association of baseline CAHPS scores of large practices with those practices’ selection of those measures for quality scoring under a pay-for-performance program; and (2) changes in patient experiences associated with a requirement that large practices publicly report CAHPS measures starting in 2014.

Results

Among 301 large practices that publicly reported patient experience measures, the mean (IQR) age of patients at baseline was 71.6 (70.4-73.2 ) years, and 55.8% of patients were women (IQR, 54.3%-57.7%). Large practices in the top vs bottom quintile of patient experience scores at baseline were more likely to voluntarily include these scores in the pay-for-performance program 2 years later (96.3% vs 67.9%), a difference of 28.4 percentage points (95% CI, 9.4-47.5 percentage points; P = .004). After 2 to 3 years of the reporting mandate, patient experiences did not differentially improve in affected vs unaffected practices (difference-in-differences estimate: −0.03 practice-level standard deviations of the composite score; 95% CI, −0.64 to 0.58; P = .92).

Conclusions and Relevance

In this cross-sectional study of US physician practices that participated in precursors of the MIPS, large practices were found to select measures on which they were already performing well for a pay-for-performance program, consistent with gaming. However, mandating public reporting was not associated with improved patient experiences. These findings support recommendations to end optional measures in the MIPS but also suggest that public reporting on mandated measures may not improve care.

A measure of local uniqueness to identify linchpins in a social network with node attributes

Network centrality measures assign importance to influential or key nodes in a network based on the topological structure of the underlying adjacency matrix. In this work, we define the importance of a node in a network as being dependent on whether it is the only one of its kind among its neighbors' ties. We introduce linchpin score, a measure of local uniqueness used to identify important nodes by assessing both network structure and a node attribute. We explore linchpin score by attribute type and examine relationships between linchpin score and other established network centrality measures (degree, betweenness, closeness, and eigenvector centrality). To assess the utility of this measure in a real-world application, we measured the linchpin score of physicians in patient-sharing networks to identify and characterize important physicians based on being locally unique for their specialty. We hypothesized that linchpin score would identify indispensable physicians who would not be easily replaced by another physician of their specialty type if they were to be removed from the network. We explored differences in rural and urban physicians by linchpin score compared with other network centrality measures in patient-sharing networks representing the 306 hospital referral regions in the United States. We show that linchpin score is uniquely able to make the distinction that rural specialists, but not rural general practitioners, are indispensable for rural patient care. Linchpin score reveals a novel aspect of network importance that can provide important insight into the vulnerability of health care provider networks. More broadly, applications of linchpin score may be relevant for the analysis of social networks where interdisciplinary collaboration is important.

Care coordination for severe mental health disorders: an analysis of healthcare provider patient-sharing networks and their association with quality of care in a French region

BACKGROUND

For patients with multiple and complex health needs, such as those suffering from mental health disorders, outcomes are determined by the combined actions of the care providers they visit and their interactions. Care coordination is therefore essential. However, little is known on links between hospitals providing psychiatric care and community-based care providers which could serve as a basis for the creation of formal mental care networks supported by recent policies. In this context, we first aimed to identify and characterize existing types of healthcare provider patient-sharing networks for severe mental health disorders in one French region. Second, we aimed to analyse the association between their characteristics and the quality of the care they provide.

METHODS

Patient flows among healthcare providers involved in treating severe mental health disorders in the Provence-Alpes-Côte-d'Azur region were extracted from the French national health data system, which contains all billing records from the social health insurance. Healthcare provider networks that have developed around public and private non-profit hospitals were identified based on shared patients with other providers (hospitals, community-based psychiatrists, general practitioners and nurses). Hierarchical clustering was conducted to create a typology of the networks. Indicators of quality of care, encompassing multiple complementary dimensions, were calculated across these networks and linked to their characteristics using multivariable methods.

RESULTS

Three main types of existing healthcare provider networks were identified. They were either networks strongly organized around the main hospital providing psychiatric care; scattered networks involving numerous and diverse healthcare providers; or medically-oriented networks involving mainly physician providers. Few significant associations between the structure and composition of healthcare provider networks and indicators of quality of care were found.

CONCLUSIONS

Our findings provide a basis to develop explicit structuring of mental care based on pre-existing working relationships but suggest that healthcare providers' patient-sharing patterns were not the main driver of optimal care provision in the context explored. The shift towards a stronger integration of health and social care in the mental health field might impact these results but is currently not observable in the administrative data available for research purpose which should evolve to include social care.