Barnett ML, Gray J, Zink A, Jena AB.
Coupling Policymaking with Evaluation — The Case of the Opioid Crisis.
New England Journal of Medicine. 2017;377 (24) :2306-2309.
Publisher's Version Barnett ML, Sommers BD.
A National Survey of Medicaid Beneficiaries’ Experiences and Satisfaction With Health Care.
JAMA Intern Med. 2017;177 :1378-81.
Publisher's VersionAbstractIn the current debate over the Affordable Care Act (ACA), some policymakers have argued that Medicaid is a broken program that provides enrollees with inadequate access to physicians. While numerous studies demonstrate that Medicaid increases access to care,
1,2 the literature has less frequently focused on patient satisfaction among Medicaid enrollees themselves. We analyzed a newly released government survey examining Medicaid beneficiaries’ experiences in the program.
Fernández-Gracia J, Onnela J-P, Barnett ML, Eguíluz VM, Christakis NA.
Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections.
Scientific Reports. 2017;7 :2930.
Publisher's VersionAbstractAntibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems. We construct a network defined by the transfer of Medicare patients across US inpatient facilities using a 100% sample of inpatient discharge claims from 2006-2007. We show the association between network structure and C. difficile incidence, with a 1% increase in a facility's C. difficile incidence being associated with a 0.53% increase in C. difficile incidence of neighboring facilities. Finally, we used network science methods to determine the facilities to monitor to maximize surveillance efficiency. An optimal surveillance strategy for selecting "sensor" hospitals, based on their network position, detects 80% of the C. difficile infections using only 2% of hospitals as sensors. Selecting a small fraction of facilities as "sensors" could be a cost-effective mechanism to monitor emerging nosocomial infections.
Ray KN, Martsolf GR, Mehrotra A, Barnett ML.
Trends in Visits to Specialist Physicians Involving Nurse Practitioners and Physician Assistants, 2001 to 2013.
JAMA Intern Med. 2017;177 :1213-6.
Publisher's VersionAbstractNurse practitioners (NPs) and physician assistants (PAs) play key roles in expanding access to primary care,
1,2 but their involvement in specialty care is not well described. Given concerns about the limited supply of specialist physicians,
3 increasing incorporation of NPs and PAs into collaborative specialist practices could be a strategy for improving access. Prior studies described the frequency of NPs and PAs practicing in specialty practices,
4,5 and quantified the volume of care by NPs and PAs for surgical outpatients.
6 However, to our knowledge, no study has described trends in specialist physician visits in which NPs and PAs provide care. We hypothesized that NPs and PAs increasingly are providing care to specialist physicians’ patients, and that this growth is primarily for routine follow-up.
Barnett ML, Song Z, Rose S, et al. Insurance transitions and changes in physician and emergency department utilization: An observational study.
Journal of General Internal Medicine. 2017;32 (10) :1146-55.
Publisher's VersionAbstractBackground
Shopping for health insurance is encouraged as a way to find the most affordable coverage that best meets an enrollee’s needs. However, the extent to which individuals switch insurance and subsequent changes in health care utilization that might arise, particularly new physician visits, are not well understood.
Objective
To examine the relationship between insurance switching and new physician and emergency department visits around the time of a switch.
Design
Observational study using a difference-in-differences design to compare those switching insurance carriers with propensity score-matched controls who did not switch, stratified based on whether individuals initially had private or Medicaid insurance coverage. All analyses adjusted for individual and insurance characteristics.
Participants
Continuously insured, non-elderly individuals with private or Medicaid insurance coverage in Massachusetts from 2010 to 2013.
Main Measures
Rates of new primary care and specialist physician visits, as well as rates of emergency department visits.
Key Results
Before matching, among 1,628,057 continuously insured individuals, 418,231 (26%) switched insurance carriers during a 2-year period. Characteristics of switchers and non-switchers were similar after matching (n = 316,343 in each group). After matching, switching plans was associated with a 203% and 47.5% increase in the rate of new primary care physician visits following switching for those initially with Medicaid or private coverage, respectively (both p < 0.001), with a large short-term increase, diminishing over time. Among those with Medicaid coverage, switching was associated with a 14.9% higher rate of ED visits during the month of switching (p < 0.001), but otherwise decreased modestly after switching.
Conclusions
Insurance switching is common, and is associated with increased new physician visits and temporarily increased ED use among the publicly insured. As insurance markets become more volatile in the current policy environment, understanding changes in utilization after insurance switching may become increasingly important.
Barnett ML, Linder JA, Clark CR, Sommers BD.
Low-Value Medical Services in the Safety-Net Population.
JAMA Internal Medicine. 2017;177 (6) :829–837.
Publisher's VersionAbstract\textlessh3\textgreaterImportance\textless/h3\textgreater\textlessp\textgreaterNational patterns of low-value and high-value care delivered to patients without insurance or with Medicaid could inform public policy but have not been previously examined.\textless/p\textgreater\textlessh3\textgreaterObjective\textless/h3\textgreater\textlessp\textgreaterTo measure rates of low-value care and high-value care received by patients without insurance or with Medicaid, compared with privately insured patients, and provided by safety-net physicians vs non–safety-net physicians.\textless/p\textgreater\textlessh3\textgreaterDesign, Setting, and Participants\textless/h3\textgreater\textlessp\textgreaterThis multiyear cross-sectional observational study included all patients ages 18 to 64 years from the National Ambulatory Medical Care Survey (2005-2013) and the National Hospital Ambulatory Medical Care Survey (2005-2011) eligible for any of the 21 previously defined low-value or high-value care measures. All measures were analyzed with multivariable logistic regression and adjusted for patient and physician characteristics.\textless/p\textgreater\textlessh3\textgreaterExposures\textless/h3\textgreater\textlessp\textgreaterComparison of patients by insurance status (uninsured/Medicaid vs privately insured) and safety-net physicians (seeing >25% uninsured/Medicaid patients) vs non–safety-net physicians (seeing 1%-10%).\textless/p\textgreater\textlessh3\textgreaterMain Outcomes and Measures\textless/h3\textgreater\textlessp\textgreaterDelivery of 9 low-value or 12 high-value care measures, based on previous research definitions, and composite measures for any high-value or low-value care delivery during an office visit.\textless/p\textgreater\textlessh3\textgreaterResults\textless/h3\textgreater\textlessp\textgreaterOverall, 193 062 office visits were eligible for at least 1 measure. Mean (95% CI) age for privately insured patients (n = 94 707) was 44.7 (44.5-44.9) years; patients on Medicaid (n = 45 123), 39.8 (39.3-40.3) years; and uninsured patients (n = 19 530), 41.9 (41.5-42.4) years. Overall, low-value and high-value care was delivered in 19.4% (95% CI, 18.5%-20.2%) and 33.4% (95% CI, 32.4%-34.3%) of eligible encounters, respectively. Rates of low-value and high-value care delivery were similar across insurance types for the majority of services examined. Among Medicaid patients, adjusted rates of use were no different for 6 of 9 low-value and 9 of 12 high-value services compared with privately insured beneficiaries, whereas among the uninsured, rates were no different for 7 of 9 low-value and 9 of 12 high-value services. Safety-net physicians provided similar care compared with non–safety-net physicians, with no difference for 8 out of 9 low-value and for all 12 high-value services.\textless/p\textgreater\textlessh3\textgreaterConclusions and Relevance\textless/h3\textgreater\textlessp\textgreaterOveruse of low-value care is common among patients without insurance or with Medicaid. Rates of low-value and high-value care were similar among physicians serving vulnerable patients and other physicians. Overuse of low-value care is a potentially important focus for state Medicaid programs and safety-net institutions to pursue cost savings and improved quality of health care delivery.\textless/p\textgreater
Barnett ML, Olenski AR, Jena AB.
Patient Mortality During Unannounced Accreditation Surveys at US Hospitals.
JAMA Internal Medicine. 2017;177 (5) :693–700.
Publisher's VersionAbstract\textlessh3\textgreaterImportance\textless/h3\textgreater\textlessp\textgreaterIn the United States, hospitals receive accreditation through unannounced on-site inspections (ie, surveys) by The Joint Commission (TJC), which are high-pressure periods to demonstrate compliance with best practices. No research has addressed whether the potential changes in behavior and heightened vigilance during a TJC survey are associated with changes in patient outcomes.\textless/p\textgreater\textlessh3\textgreaterObjective\textless/h3\textgreater\textlessp\textgreaterTo assess whether heightened vigilance during survey weeks is associated with improved patient outcomes compared with nonsurvey weeks, particularly in major teaching hospitals.\textless/p\textgreater\textlessh3\textgreaterDesign, Setting, and Participants\textless/h3\textgreater\textlessp\textgreaterQuasi-randomized analysis of Medicare admissions at 1984 surveyed hospitals from calendar year 2008 through 2012 in the period from 3 weeks before to 3 weeks after surveys. Outcomes between surveys and surrounding weeks were compared, adjusting for beneficiaries’ sociodemographic and clinical characteristics, with subanalyses for major teaching hospitals. Data analysis was conducted from January 1 to September 1, 2016.\textless/p\textgreater\textlessh3\textgreaterExposures\textless/h3\textgreater\textlessp\textgreaterHospitalization during a TJC survey week vs nonsurvey weeks.\textless/p\textgreater\textlessh3\textgreaterMain Outcomes and Measures\textless/h3\textgreater\textlessp\textgreaterThe primary outcome was 30-day mortality. Secondary outcomes were rates of\textitClostridium difficileinfections, in-hospital cardiac arrest mortality, and Patient Safety Indicators (PSI) 90 and PSI 4 measure events.\textless/p\textgreater\textlessh3\textgreaterResults\textless/h3\textgreater\textlessp\textgreaterThe study sample included 244 787 and 1 462 339 admissions during survey and nonsurvey weeks with similar patient characteristics, reason for admission, and in-hospital procedures across both groups. There were 811 598 (55.5%) women in the nonsurvey weeks (mean [SD] age, 72.84 [14.5] years) and 135 857 (55.5%) in the survey weeks (age, 72.76 [14.5] years). Overall, there was a significant reversible decrease in 30-day mortality for admissions during survey (7.03%) vs nonsurvey weeks (7.21%) (adjusted difference, −0.12%; 95% CI, −0.22% to −0.01%). This observed decrease was larger than 99.5% of mortality changes among 1000 random permutations of hospital survey date combinations, suggesting that observed mortality changes were not attributable to chance alone. Observed mortality reductions were largest in major teaching hospitals, where mortality fell from 6.41% to 5.93% during survey weeks (adjusted difference, −0.38%; 95% CI, −0.74% to −0.03%), a 5.9% relative decrease. We observed no significant differences in admission volume, length of stay, or secondary outcomes.\textless/p\textgreater\textlessh3\textgreaterConclusions and Relevance\textless/h3\textgreater\textlessp\textgreaterPatients admitted to hospitals during TJC survey weeks have significantly lower mortality than during nonsurvey weeks, particularly in major teaching hospitals. These results suggest that changes in practice occurring during periods of surveyor observation may meaningfully affect patient mortality.\textless/p\textgreater
