Breadth and Exclusivity of Hospital and Physician Networks in US Insurance Markets.

Importance: Little is known about the breadth of health care networks or the degree to which different insurers' networks overlap. Objective: To quantify network breadth and exclusivity (ie, overlap) among primary care physician (PCP), cardiology, and general acute care hospital networks for employer-based (large group and small group), individually purchased (marketplace), Medicare Advantage (MA), and Medicaid managed care (MMC) plans. Design, Setting, and Participants: This cross-sectional study included 1192 networks from Vericred. The analytic unit was the network-zip code-clinician type-market, which captured attributes of networks from the perspective of a hypothetical patient seeking access to in-network clinicians or hospitals within a 60-minute drive. Exposures: Enrollment in a private insurance plan. Main Outcomes and Measures: Percentage of in-network physicians and/or hospitals within a 60-minute drive from a hypothetical patient in a given zip code (breadth). Number of physicians and/or hospitals within each network that overlapped with other insurers' networks, expressed as a percentage of the total possible number of shared connections (exclusivity). Descriptive statistics (mean, quantiles) were produced overall and by network breadth category, as follows: extra-small (<10%), small (10%-25%), medium (25%-40%), large (40%-60%), and extra-large (>60%). Networks were analyzed by insurance type, state, and insurance, physician, and/or hospital market concentration level, as measured by the Hirschman-Herfindahl index. Results: Across all US zip code-network observations, 415 549 of 511 143 large-group PCP networks (81%) were large or extra-large compared with 138 485 of 202 702 MA (68%), 191 918 of 318 082 small-group (60%), 60 425 of 149 841 marketplace (40%), and 21 781 of 66 370 MMC (40%) networks. Large-group employer networks had broader coverage than all other network plans (mean [SD] PCP breadth: large-group employer-based plans, 57.3% [20.1]; small-group employer-based plans, 45.7% [21.4]; marketplace, 36,4% [21.2]; MMC, 32.3% [19.3]; MA, 47.4% [18.3]). MMC networks were the least exclusive (a mean [SD] overlap of 61.3% [10.5] for PCPs, 66.5% [9.8] for cardiology, and 60.2% [12.3] for hospitals). Networks were narrowest (mean [SD] breadth 42.4% [16.9]) and most exclusive (mean [SD] overlap 47.7% [23.0]) in California and broadest (79.9% [16.6]) and least exclusive (71.1% [14.6]) in Nebraska. Rising levels of insurer and market concentration were associated with broader and less exclusive networks. Markets with concentrated primary care and insurance markets had the broadest (median [interquartile range {IQR}], 75.0% [60.0%-83.1%]) and least exclusive (median [IQR], 63.7% [52.4%-73.7%]) primary care networks among large-group commercial plans, while markets with least concentration had the narrowest (median [IQR], 54.6% [46.8%-67.6%]) and most exclusive (median [IQR], 49.4% [41.9%-56.9%]) networks. Conclusions and Relevance: In this study, narrower health care networks had a relatively large degree of overlap with other networks in the same geographic area, while broader networks were associated with physician, hospital, and insurance market concentration. These results suggest that many patients could switch to a lower-cost, narrow network plan without losing in-network access to their PCP, although future research is needed to assess the implications for care quality and clinical integration across in-network health care professionals and facilities in narrow network plans.

A survey to assess the extent of public-private mix DOTS in the management of tuberculosis in Zambia.

BACKGROUND: Involving all relevant healthcare providers in tuberculosis (TB) management through public-private mix (PPM) approaches is a vital element in the World Health Organization's (WHO) Stop TB Strategy. The control of TB in Zambia is mainly done in the public health sector, despite the high overall incidence rates. AIM: We conducted a survey to determine the extent of private-sector capacity, participation, practices and adherence to national guidelines in the control of TB. SETTING: This survey was done in the year 2012 in 157 facilities in three provinces of Zambia where approximately 85% of the country's private health facilities are found. METHODS: We used a structured questionnaire to interview the heads of private health facilities to assess the participation of the private health sector in TB diagnosis, management and prevention activities. RESULTS: Out of 157 facilities surveyed, 40.5% were from the Copperbelt, 4.4% from Central province and 55.1% from Lusaka province. Only 23.8% of the facilities were able to provide full diagnosis and management of TB patients. Although 47.4% of the facilities reported that they do notify their cases to the National TB control programme, the majority (62.7%) of these facilities did not show evidence of notifications. CONCLUSION: Our results show that the majority of the facilities that diagnose and manage TB in the private sector do not report their TB activities to the National TB Control Programme (NTP). There is a need for the NTP to improve collaboration with the private sector with respect to TB control activities and PPM for Directly Observed Treatment, Short Course (DOTS).