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The American Journal of Managed Care May 2019
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Evaluation of Value-Based Insurance Design for Primary Care
Qinli Ma, PhD; Gosia Sylwestrzak, MA; Manish Oza, MD; Lorraine Garneau; and Andrea R. DeVries, PhD
Clarification of References to Medication Adherence Scale
Open Doors to Primary Care Should Add a “Screen” to Reduce Low-Value Care
Betsy Q. Cliff, MS; and A. Mark Fendrick, MD
From the Editorial Board: Daniel B. Wolfson, MHSA
Daniel B. Wolfson, MHSA
Cost-Effectiveness of DPP-4 Inhibitor and SGLT2 Inhibitor Combination Therapy for Type 2 Diabetes
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Michael Adelberg, MA, MPP; Austin Frakt, PhD; Daniel Polsky, PhD; and Michelle Kitchman Strollo, DrPH, MHS
Electronic Consults for Improving Specialty Care Access for Veterans
David E. Winchester, MD, MS; Anita Wokhlu, MD; Juan Vilaro, MD; Anthony A. Bavry, MD, MPH; Ki Park, MD; Calvin Choi, MD; Mark Panna, MD; Michael Kaufmann, MD; Matthew McKillop, MD; and Carsten Schmalfuss, MD
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Leah L. Zullig, PhD; Bradi B. Granger, PhD; Helene Vilme, DrPH; Megan M. Oakes, MPA; and Hayden B. Bosworth, PhD
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Maria de Jesus Diaz-Perez, PhD; Rita Hanover, PhD; Emilie Sites, MPH; Doug Rupp, BS; Jim Courtemanche, MS; and Emily Levi, MPH
Beyond Satisfaction Scores: Exploring Emotionally Adverse Patient Experiences
Laura M. Holdsworth, PhD; Dani L. Zionts, MScPH; Karen Marie De Sola-Smith, PhD; Melissa Valentine, PhD; Marcy D. Winget, PhD; and Steven M. Asch, MD
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Joel F. Farley, PhD; Arun Kumar, PharmD, MS; Benjamin Y. Urick, PharmD, PhD; and Marisa E. Domino, PhD
Pilot of Urgent Care Center Evaluation for Acute Coronary Syndrome
Ryan P. Radecki, MD, MS; Kevin F. Foley, PhD; Timothy S. Elzinga, MD; Cynthia P. Horak, MD; Thomas E. Gant, MS; Heather M. Papp, BA; Adam J. Morris, BS; Natalie R. Hauser, BA; and Briar L. Ertz-Berger, MD, MPH

Evaluation of Value-Based Insurance Design for Primary Care

Qinli Ma, PhD; Gosia Sylwestrzak, MA; Manish Oza, MD; Lorraine Garneau; and Andrea R. DeVries, PhD
The removal of cost sharing increased primary care access and did not negatively affect total cost of care.
Outcome Measures

The primary outcomes measured the utilization rate of physician office visits and the annual total healthcare spending. The total spending was the sum of plan-paid amounts, out-of-pocket amounts, and amounts paid by other insurances for all medical services, including hospitalizations, ED visits, physician office visits, and other outpatient services (ie, services occurring in an outpatient setting that are not physician office visits, such as laboratory tests, imaging, and procedures), for all causes. Other types of all-cause healthcare utilization, including hospitalizations, ED visits, and other outpatient services, were assessed for exploratory purposes. Furthermore, several specific utilization types, such as hospital admissions due to ambulatory care–sensitive conditions and ED visits for primary care–treatable conditions (defined by the New York University Emergency Department Algorithm), were also examined.18,19 Average annual utilization and spending for the preintervention and postintervention periods were calculated respectively and compared across the cohorts. All spending was adjusted to 2015 values using the Consumer Price Index.20

Statistical Analyses

Multivariate logistic regression was used to estimate the association of having PCP cost sharing removed (ie, being in the VBID cohort) with covariates of baseline characteristics, including age, gender, health plan type, residence region, metropolitan statistical area, enhanced Elixhauser Comorbidity Index (ECI) score, comorbid conditions, and healthcare utilization and expenditures during 2008.21,22 The VBID and comparison cohorts with similar estimated likelihood (maximum permitted difference of 0.0001) were selected using a greedy algorithm, to ensure the baseline comparability of the 2 cohorts after matching.23 For outcome measures, a DID analysis was conducted to compare changes from the preintervention to postintervention period between the 2 cohorts. A generalized estimating equation approach was used with a zero-inflated Poisson distribution and a log link for utilization, and a γ distribution with log link for spending, at the conventional significance level of α <.05. Analyses were also performed on the 3 age subgroups.


Patient Characteristics

Among members in the VBID cohort, 25,725 (53%) met the population inclusion criteria. The main reason for exclusion was lack of continuous eligibility, which accounted for 45% of the population drop. The members who were not included were slightly younger (average age of 31.0 vs 33.5 years), more likely to be from the South region (27.6% vs 15.2%), and more likely to have a mental disorder (3.0% vs 2.2%; all P <.0001) compared with those included in the study (eAppendix B). However, they did not differ in other characteristics. After matching, the VBID and comparison cohorts each had 25,725 subjects with comparable baseline characteristics in 2008—all standardized differences were less than 20% (Table 1). Both cohorts had a mean age of 33.4 to 33.5 years, and most were aged 19 to 50 years. A slight majority of the subjects were men (51.2%-51.3%) and lived in the Midwest or Northeast regions. Both cohorts had the same mean (SD) ECI scores (0.5 [0.9]); more than 68% of subjects had an ECI score of 0. The most common comorbidity was hyperlipidemia (9.7% in VBID cohort vs 10.3% in comparison cohort), followed by hypertension (7.4% vs 7.8%, respectively). All subjects were followed for the entire 6-year study period.

Physician Office Visits

Physician office visits increased in both cohorts from the preintervention to the postintervention period (Table 2): 3588 to 3681 visits per 1000 members per year in the VBID cohort and 3792 to 3866 visits per 1000 members per year in the comparison cohort. However, the magnitudes of increase were similar between the VBID and comparison cohorts (2.6% increase vs 1.7% increase; DID, 0.9%; P = .25).

The plan-paid amount for physician visits had the same trend as utilization. Both cohorts had increased plan-paid amounts in the postintervention period, but the VBID cohort had a relatively greater increase compared with the comparison cohort (DID, 9.4%; P = .03). Not surprisingly, out-of-pocket amounts for physician visits decreased annually by 12.8% in the VBID cohort, driven by the removal of cost sharing for PCP visits, compared with a 9.8% annual increase in the comparison cohort (DID, –22.6%; P <.0001). As the sum of plan-paid and out-of-pocket amounts, the total spending for physician office visits in the VBID cohort had a relative but marginal increase (DID, 2.1%; P = .09).

Overall Healthcare Spending

Trends of overall healthcare spending, including the total and out-of-pocket amounts, were favorable for the VBID cohort. Total medical spending for the VBID cohort increased annually by 12.2% compared with a 17.3% annual increase for the comparison cohort (DID, –5.1%; P = .02) (Figure). This difference in trend translates to a $12.0 relative reduction in total spent per member per month (PMPM) for the VBID cohort. ED visits and other outpatient services significantly contributed to the trend toward lower spending for the VBID cohort (Table 3), with $1.3 (DID, –10.0%; P = .03) and $7.6 (DID, –5.8%; P = .02) relative reductions in PMPM spending, respectively. No significant relative reduction was observed for hospitalization expenses ($4.2 PMPM relative reduction; DID, –10.0%; P = .17). The aforementioned total spending for physician office visits stayed relatively stable (DID, 2.1%; P = .09).

There was a relative reduction of $5.5 in out-of-pocket PMPM spending that favored the VBID cohort (DID, –11.1%; P <.0001). Significant relative reductions in out-of-pocket amount were seen for other outpatient services (13.2% increase for VBID vs 24.3% increase for comparison cohort; DID, –11.2%; P = .004). The change in overall plan-paid amount was similar between the 2 cohorts (DID, –2.3%; P = .39), but VBID had favorable decreasing trends of plan-paid amounts for ED visits (DID, –9.2%; P = .001) and other outpatient services (DID, –3.4%; P = .003).

Overall Healthcare Utilization

The utilization trend aligned with the trend of spending (Table 418). The VBID cohort experienced a statistically significant relative reduction in use of other outpatient visits compared with the comparison cohort (DID, –4.1%; P = .004). Both cohorts experienced similar flat trends in all-cause hospitalizations and ED visits, so these results did not reach statistical significance (hospitalizations: DID, –4.7%; P = .33; ED visits: DID, –4.5%; P = .07). Another statistically significant relative reduction for the VBID cohort was observed in ED visits for primary care–treatable conditions (DID, –7.4%; P = .01).

Subgroup Analysis

Both cohorts had similar baseline characteristics among each age category subgroup. The most favorable trend for total medical spending was found in younger adults (aged 19-50 years) (DID, –9.2%; P = .02) (Table 3), and the trend mainly was driven by other outpatient visits—average annual decrease of $117 (6.5%) in the VBID cohort versus increase of $63 (4.3%) in the comparison cohort (DID, –10.7%; P = .002)—followed by ED visits: $35 (23.0%) increase versus $66 (40.5%) increase, respectively (DID, –17.5%; P = .01). The increase in physician office visits occurred most often among older adults (aged 51-64 years) in both cohorts (6.4% increase in VBID cohort vs 4.8% increase in comparison cohort) in a similar magnitude (DID, 1.6%; P = .34) (eAppendix C). Notably, the same subgroup had a statistically significant positive finding for ED visits that favored the VBID group (all-cause ED visits: DID, –16.5%; P = .0003; ED visits for primary care–treatable conditions: DID, –16.1%; P = .02).

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