Comparing the quality of care in physician networks to usual care for elderly patients in three German regions: a quasi-experimental cohort study.

OBJECTIVES: Patients in Germany have free choice of physicians in the ambulatory care sector and can consult them as often as they wish without a referral. This can lead to inefficiencies in treatment pathways. In response, some physicians have formed networks to improve the coordination and quality of care. This study aims to investigate whether the care provided by these networks results in better health and process outcomes than usual care. STUDY DESIGN: This was a quasi-experimental cohort study. METHODS: We analysed claims data from 2017 to 2018 in Bavaria, Brandenburg, and Westphalia-Lippe. Our study population includes patients aged 65 years or older with heart failure (n = 267,256), back pain (n = 931,672), or depression (n = 483,068). We compared condition-specific and generic quality indicators between patients treated in physician networks and usual care. Ambulatory care-sensitive emergency department cases were used as a primary outcome measure. Imbalances between the groups were minimized using propensity score matching. RESULTS: Rates of ambulatory care-sensitive emergency department cases yielded insignificant differences between networks and usual care in the depression and heart failure subgroups. For back pain patients, rates were 0.17 percentage points higher (P < 0.01) in network patients compared with usual care. Among network patients, generic indicators for prevention and coordination showed significantly better performance. For instance, the rate of completed vaccination against influenza is 3.03 percentage points higher (P < 0.01), and the rate of specialist visits after referral is 1.6 percentage points higher (P < 0.01) in heart failure patients, who are treated in physician networks. This is accompanied by higher rates of polypharmacy. Furthermore, the results for condition-specific indicators suggest that for most indicators, a greater proportion of the care provided by physician networks adhered to national treatment guidelines. CONCLUSIONS: Our findings suggest that physician networks in Germany do not reduce rates of ambulatory care-sensitive emergency department cases but perform better than usual care in terms of care coordination and prevention. Further research is needed to confirm our findings and explore the implications of the potentially higher rates of polypharmacy seen in physician networks.

The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation.

Black-White disparities in cardiac care may be related to physician referral network segregation. We developed and tested new geographic physician network segregation measures. We used Medicare claims to identify Black and White Medicare heart disease patients and map physician networks for 169 hospital referral regions (HRRs) with over 1000 Black patients. We constructed two network segregation indexes ranging from 0 (integration) to 100 (total segregation): Dissimilarity (the unevenness of Black and White patient distribution across physicians [Dn]) and Absolute Clustering (the propensity of Black patients' physicians to have closer ties with each other than with other physicians [ACLn]). We employed conditional logit models to estimate the probability of using the best (lowest mortality) geographically available hospital for Black and White patients undergoing coronary artery bypass grafting (CABG) surgery in 126 markets with sufficient sample size at increasing levels of network segregation and for low vs. high HRR Black patient population. Physician network segregation was lower than residential segregation (Dissimilarity 21.9 vs. 48.7, and Absolute Clustering 4.8 vs. 32.4) and positively correlated with residential segregation (p < .001). Network segregation effects differed by race and HRR Black patient population. For White patients, higher network segregation was associated with a higher probability of using the best available hospitals in HRRs with few black patients but unchanged (ACLn) or lower (Dn) probability of best hospital use in HRRs with many Black patients. For Black patients, higher network segregation was not associated with a substantial change in the probability of best hospital use regardless of the HRR Black patient population size. Measuring physician network segregation is feasible and associated with nuanced effects on Black-White differences in high-quality hospital use for heart disease. Further work is needed to understand underlying mechanisms and potential uses in health equity policy.

Tiered network health plans and changes in physician practice intensity.

OBJECTIVE: To examine whether physicians in tiered physician networks where tier assignments are based on "intensity" of care, which is the quantity of resources used per-episode of care, change their intensity after learning detailed information about how their intensity compares to their peers. DATA SOURCES: Administrative data on intensity and quality at the physician-episode level for all physicians included in a tiered physician network offered through the Massachusetts Group Insurance Commission (GIC) in 2010-2015. Data on physicians' share of revenue from GIC patients from the 2012 Massachusetts All-Payer Claims Database. STUDY DESIGN: For 21,086 physicians in seven specialties, we estimate the impact of the dissemination of detailed intensity performance information in 2014 on physician intensity per episode of care overall and decomposed into physician services, facility, and pharmaceutical subcomponents. Intensity outcomes were measured using a standardized price schedule. Using a difference-in-differences regression, we compared physicians with high exposure to the tiered network via a large share of their revenue coming from GIC patients ("GIC share") to physicians who were less exposed. Measures of intensity of care and GIC share were log-transformed, and models controlled for physician-episode type fixed effects. DATA EXTRACTION METHODS: We linked GIC share to administrative data using National Provider Identifier. PRINCIPAL FINDINGS: There were no statistically significant differences in total intensity of care with the informational intervention for physicians in procedure-based specialties (-0.12 elasticity of intensity per episode with respect to GIC patient share, 95% CI -0.30 to 0.06) or in relationship-based specialties (0.09, 95% CI -0.15 to 0.33). There were also no differences in intensity of subcomponents of care following the intervention. CONCLUSIONS: Tiered network incentives had no detectable impact on intensity of care that physicians provided to patients.

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.

Can peer effects explain prescribing appropriateness? a social network analysis.

BACKGROUND: Optimizing prescribing practices is important due to the substantial clinical and financial costs of polypharmacy and an increasingly aging population. Prior research shows the importance of social relationships in driving prescribing behaviour. Using social network analysis, we examine the relationship between a physician practices' connectedness to peers and their prescribing performance in two German regions. METHODS: We first mapped physician practice networks using links established between two practices that share 8 or more patients; we calculated network-level (density, average path length) and node-level measures (degree, betweenness, eigenvector). We defined prescribing performance as the total number of inappropriate medications prescribed or appropriate medications not prescribed (PIMs) to senior patients (over the age of 65) during the calendar year 2016. We used FORTA (Fit fOR The Aged) algorithm to classify medication appropriateness. Negative binomial regression models estimate the association between node-level measures and prescribing performance of physician practices controlling for patient comorbidity, provider specialization, percentage of seniors in practice, and region. We conducted two sensitivity analyses to test the robustness of our findings - i) limiting the network mapping to patients younger than 65; ii) limiting the network ties to practices that share more than 25 patients. RESULTS: We mapped two patient-sharing networks including 436 and 270 physician practices involving 28,508 and 20,935 patients and consisting of 217,126 and 154,274 claims in the two regions respectively. Regression analyses showed a practice's network connectedness as represented by degree, betweenness, and eigenvector centrality, is significantly negatively associated with prescribing performance (degree-bottom vs. top quartile aRR = 0.04, 95%CI: 0.035,0.045; betweenness-bottom vs. top quartile aRR = 0.063 95%CI: 0.052,0.077; eigenvector-bottom vs. top quartile aRR = 0.039, 95%CI: 0.034,0.044). CONCLUSIONS: Our study provides evidence that physician practice prescribing performance is associated with their peer connections and position within their network. We conclude that practices occupying strategic positions at the edge of networks with advantageous access to novel information are associated with better prescribing outcomes, whereas highly connected practices embedded in insulated information environments are associated with poor prescribing performance.

Organization and quality of care in patient-sharing networks.

Healthcare systems seek to provide continuous and coordinated care of high quality. However, patient pathways in the ambulatory sector may differ and result in various provider units. Our aim was to analyze whether health outcomes and the quality of care differ between different types of patient-sharing physician networks. We analyzed administrative data on patients with diagnosed heart failure in Germany. We investigated distinct networks of ambulatory physicians by using a modular-based optimization algorithm and characterized each network as having either a key physician at its center or some other kind of configuration. We subsequently conducted multilevel regression analyses to estimate the impact a network's configuration has on hospitalization rates and guideline-based process indicators. We identified 1,847 networks, of which 27% had a key physician at their center. Compared to physician networks with other configurations, networks that had a key physician at their center were associated in our regression analysis with (a) somewhat lower hospitalization rates, and (b) heart failure treatment that was more frequently in concordance with the German national treatment guideline. Organizing healthcare for people with chronic disease into units that have a key physician at their center and include the relevant specialists may foster treatment that is effective and of higher quality.

Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations.

BACKGROUND: Coordinating health care within and among sectors is crucial to improving quality of care and avoiding undesirable negative health outcomes, such as avoidable hospitalizations. Quality circles are one approach to strengthening collaboration among health care providers and improving the continuity of care. However, identifying and including the right health professionals in such meetings is challenging, especially in settings with no predefined patient pathways. Based on the Accountable Care in Germany (ACD) project, our study presents a framework for and investigates the feasibility of applying social network analysis (SNA) to routine data in order to identify networks of ambulatory physicians who can be considered responsible for the care of specific patients. METHODS: The ACD study objectives predefined the characteristics of the networks. SNA provides a methodology to identify physicians who have patients in common and ensure that they are involved in health care provision. An expert panel consisting of physicians, health services researchers, and data specialists examined the concept of network construction through informed decisions. The procedure was structured by five steps and was applied to routine data from three German states. RESULTS: In total, 510 networks of ambulatory physicians met our predefined inclusion criteria. The networks had between 20 and 120 physicians, and 72% included at least ten different medical specialties. Overall, general practitioners accounted for the largest proportion of physicians in the networks (45%), followed by gynecologists (10%), orthopedists, and ophthalmologists (5%). The specialties were distributed similarly across the majority of networks. The number of patients this study allocated to the networks varied between 95 and 45,268 depending on the number and specialization of physicians per network. CONCLUSIONS: The networks were constructed according to the predefined characteristics following the ACD study objectives, e.g., size of and specialization composition in the networks. This study shows that it is feasible to apply SNA to routine data in order to identify groups of ambulatory physicians who are involved in the treatment of a specific patient population. Whether these doctors are also mainly responsible for care and if their active collaboration can improve the quality of care still needs to be examined.

Physician network connections to specialists and HIV quality of care.

OBJECTIVE: To estimate novel measures of generalist physicians' network connectedness to HIV specialists and their associations with two dimensions of HIV quality of care. DATA SOURCES: Medicare and Medicaid claims and the American Medical Association Masterfile data on people living with HIV (PLWH) and the physicians providing their HIV care in California between 2007 and 2010. STUDY DESIGN: I construct regional patient-sharing physician networks from the shared treatment of PLWH and calculate (a) measures of network connectedness to all physician types and (b) specialty-weighted measures to describe connectedness to HIV specialists. Two HIV quality of care outcomes are then evaluated: medication quality (prescribing antiretroviral drugs from at least two drug classes) and monitoring quality (at least two annual HIV virus monitoring scans). Linear probability models estimate the associations between network statistics and the two dimensions of HIV quality of care, and a policy simulation demonstrates the importance of these statistical relationships. These analyses include 16 124 PLWH, 3240 generalists, and 1031 HIV specialists. DATA COLLECTION/EXTRACTION METHODS: PLWH are identified from claims for patients with any indication of HIV using an existing algorithm from the literature. PRINCIPAL FINDINGS: Generalists' network connectedness to HIV specialists is positively related with their own HIV medication quality; one additional HIV specialist connection is associated with a 1.46 percentage point (SE 0.42, P < .01) increase in generalist's medication quality. Based on the estimated associations, a simulated policy that increases connectedness between generalists and HIV specialists reduces the annual rate of HIV infections by up to 6%, roughly 290 fewer infections per year. Only network connectedness to all physician types is associated with improved monitoring quality. CONCLUSIONS: Network connectedness to HIV specialists is positively associated with generalists' HIV medication quality, which suggests that specialists provide clinical support through patient-sharing for complex treatment protocol.

Prices for Physicians' Services in Medicare Advantage and Commercial Plans.

The prices that insurers pay physicians ultimately affect beneficiaries' health insurance premiums. Using 2014 claims data from three major insurers, we analyzed the prices insurers paid in their Medicare Advantage (MA) and commercial plans for 20 physician services, in and out of network, and compared those prices with estimated amounts that Medicare's fee-for-service (FFS) program would pay for the same service. MA prices paid by those insurers were close to Medicare FFS prices, varied minimally, and were similar in and out of network. In contrast, commercial prices paid by the same insurers were substantially higher than FFS, varied widely, and were up to three times higher out of network than in network. Those results suggest that insurers can use statutory limits on out-of-network charges in MA to negotiate lower in-network prices in those plans. In contrast, without those limits on out-of-network prices, in-network prices in commercial plans are much higher.

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

BACKGROUND: There is significant promise in analyzing physician patient-sharing networks to indirectly measure care coordination, yet it is unknown whether these measures reflect patients' perceptions of care coordination. OBJECTIVE: To evaluate the associations between network-based measures of care coordination and patient-reported experience measures. DESIGN: We analyzed patient-sharing physician networks within group practices using data made available by the Centers for Medicare and Medicaid Services. SUBJECTS: Medicare beneficiaries who provided responses to the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Survey in 2016 (data aggregated by physician group practice made available through the Physician Compare 2016 Group Public Reporting). MAIN MEASURES: The outcomes of interest were patient-reported experience measures reflecting aspects of care coordination (CAHPS). The predictor variables of interests were physician group practice density (the number of physician pairs who share patients adjusting for the total number of physician pairs) and clustering (the extent to which sets of three physicians share patients). KEY RESULTS: Four hundred seventy-six groups had patient-reported measures available. Patients' perception of "Clinicians working together for your care" was significantly positively associated with both physician group practice density (Est (95 % CI) = 5.07(0.83, 9.33), p = 0.02) and clustering (Est (95 % CI) = 3.73(1.01, 6.44), p = 0.007). Physician group practice clustering was also significantly positively associated with "Getting timely care, appointments, and information" (Est (95 % CI) = 4.63(0.21, 9.06), p = 0.04). CONCLUSIONS: This work suggests that network-based measures of care coordination are associated with some patient-reported experience measures. Evaluating and intervening on patient-sharing networks may provide novel strategies for initiatives aimed at improving quality of care and the patient experience.

An empiric approach to identifying physician peer groups from claims data: An example from breast cancer care.

OBJECTIVE: To develop an empiric approach for evaluating the performance of physician peer groups based on patient-sharing in administrative claims data. DATA SOURCES: Surveillance, Epidemiology and End Results-Medicare linked dataset. STUDY DESIGN: Applying social network theory, we constructed physician peer groups for patients with breast cancer. Under different assumptions of key parameter values-minimum patient volume for physician inclusion and minimum number of patients shared between physicians for a connection-we compared agreement in group membership between split samples during 2004-2006 (T1) (reliability) and agreement in group membership between T1 and 2007-2009 (T2) (stability). We also compared the results with those derived from randomly generated groups and to hospital affiliation-based groups. PRINCIPAL FINDINGS: The sample included 142 098 patients treated by 43 174 physicians in T1 and 136 680 patients treated by 51 515 physicians in T2. We identified parameter values that resulted in a median peer group reliability of 85.2 percent (Interquartile range (IQR) [0 percent, 96.2 percent]) and median stability of 73.7 percent (IQR [0 percent, 91.0 percent]). In contrast, stability of randomly assigned peer groups was 6.2 percent (IQR [0 percent, 21.0 percent]). Median overlap of empirical groups with hospital groups was 32.2 percent (IQR [12.1 percent, 59.2 percent]). CONCLUSIONS: It is feasible to construct physician peer groups that are reliable, stable, and distinct from both randomly generated and hospital-based groups.

Comparison of physician networks constructed from thresholded ties versus shared clinical episodes.

OBJECTIVE: To compare standard methods for constructing physician networks from patient-physician encounter data with a new method based on clinical episodes of care. DATA SOURCE: We used data on 100% of traditional Medicare beneficiaries from 51 nationally representative geographical regions for the years 2005-2010. STUDY DESIGN: We constructed networks of physicians based on their shared patients. In the fixed-threshold networks and adaptive-threshold networks, we included data on all patient-physician encounters to form the physician-physician ties, and then subsequently thresholded some proportion of the strongest ties. In contrast, in the episode-based approach, only those patient-physician encounters that occurred within shared clinical episodes treating specific conditions contributed towards physician-physician ties. DATA COLLECTION/EXTRACTION METHODS: We extracted clinical episodes in the Medicare data and investigated structural properties of the patient-sharing networks of physicians, temporal dynamics of their ties, and temporal stability of network communities across the two approaches. PRINCIPAL FINDINGS: The episode-based networks accentuated ties between primary care physicians (PCPs) and medical specialists, had ties that were more likely to reappear in the future, and appeared to have more fluid community structure. CONCLUSIONS: Constructing physician networks around shared episodes of care is a clinically sound alternative to previous approaches to network construction that does not require arbitrary decisions about thresholding. The resulting networks capture somewhat different aspects of patient-physician encounters.

Most Marketplace Plans Included At Least 25 Percent Of Local-Area Physicians, But Enrollment Disparities Remained.

The Affordable Care Act allows commercial insurers participating in the Marketplaces to vary the size of their provider networks as long as the providers are "sufficient" in numbers and types. Concerns have been growing over the increasing use of restricted-provider or narrow networks in Marketplace plans because of their implications for reduced access to care, but little is known about the breadth and stability of these networks over time or what types of enrollees choose such plans. Using national data, we found that in 2016, 60 percent of provider networks in plans offered in the federally facilitated Marketplaces included at least one-quarter of local-area physicians, and that consumers' access to broad-network plans remained stable between 2015 and 2016. Hispanic and low-income people made up a disproportionate share of enrollees in smaller-network plans (those with fewer than one-quarter of local-area physicians). It will be important to monitor the impact of narrow networks on access to and quality of care as well as on health outcomes.

Building Physician Networks as Part of the Zika Response.

The global community needs to easily identify and respond to new and reemerging threats, such as H1N1, Ebola, and most recently Zika. Clinicians are often the first-line providers to recognize these threats, but yet have few opportunities to learn from each other in real time. In this concept article, we describe the ways clinical information is traditionally shared during a public health emergency and then introduce new mechanisms to facilitate physician communication and learning as a part of the response to Zika. (Disaster Med Public Health Preparedness. 2017;11:259-261).

Who joins the network? Physicians' resistance to take budgetary co-responsibility.

Managed Care (MC) is expected to provide health care at a lower cost than conventional provision. Therefore, Switzerland intends to promote MC by forcing health insurers to write MC contracts and introducing budgetary co-responsibility for ambulatory care physicians. A discrete choice experiment conducted in 2011 including 872 physicians reveals a strong preference heterogeneity with respect to network participation and alternative remuneration schemes. The number of physicians working in networks is unlikely to rise on a voluntary basis, while general practitioners are more likely to join networks than specialists with surgical activities. For physicians considering joining networks, cost savings are predicted to be higher than the estimated willingness-to-accept payments.

Mapping physician Twitter networks: describing how they work as a first step in understanding connectivity, information flow, and message diffusion.

BACKGROUND: Twitter is becoming an important tool in medicine, but there is little information on Twitter metrics. In order to recommend best practices for information dissemination and diffusion, it is important to first study and analyze the networks. OBJECTIVE: This study describes the characteristics of four medical networks, analyzes their theoretical dissemination potential, their actual dissemination, and the propagation and distribution of tweets. METHODS: Open Twitter data was used to characterize four networks: the American Medical Association (AMA), the American Academy of Family Physicians (AAFP), the American Academy of Pediatrics (AAP), and the American College of Physicians (ACP). Data were collected between July 2012 and September 2012. Visualization was used to understand the follower overlap between the groups. Actual flow of the tweets for each group was assessed. Tweets were examined using Topsy, a Twitter data aggregator. RESULTS: The theoretical information dissemination potential for the groups is large. A collective community is emerging, where large percentages of individuals are following more than one of the groups. The overlap across groups is small, indicating a limited amount of community cohesion and cross-fertilization. The AMA followers' network is not as active as the other networks. The AMA posted the largest number of tweets while the AAP posted the fewest. The number of retweets for each organization was low indicating dissemination that is far below its potential. CONCLUSIONS: To increase the dissemination potential, medical groups should develop a more cohesive community of shared followers. Tweet content must be engaging to provide a hook for retweeting and reaching potential audience. Next steps call for content analysis, assessment of the behavior and actions of the messengers and the recipients, and a larger-scale study that considers other medical groups using Twitter.