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Research ArticleOriginal Research

Financial Incentives for Medical Assistants: A Mixed-Methods Exploration of Bonus Structures, Motivation, and Population Health Quality Measures

Stacie Vilendrer, Cati Brown-Johnson, Samantha M. R. Kling, Darlene Veruttipong, Alexis Amano, Bryan Bohman, William P. Daines, David Overton, Raj Srivastava and Steven M. Asch
The Annals of Family Medicine September 2021, 19 (5) 427-436; DOI: https://doi.org/10.1370/afm.2719
Stacie Vilendrer
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
MD, MBA, MS
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  • For correspondence: staciev@stanford.edu
Cati Brown-Johnson
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
PhD
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Samantha M. R. Kling
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
PhD, RD
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Darlene Veruttipong
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
MPH
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Alexis Amano
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
MS
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Bryan Bohman
2Department of Anesthesiology Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California
MD
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William P. Daines
3Internal Medicine Clinical Program, Intermountain Healthcare, Murray, Utah
MD
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David Overton
4University Healthcare Alliance, Newark, California
RN
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Raj Srivastava
5Intermountain Healthcare Delivery Institute, Intermountain Healthcare, Salt Lake City, Utah
MD, FRCP(C), MPH
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Steven M. Asch
1Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California
6Center for Innovation to Implementation, Veterans Affairs, Menlo Park, California
MD, MPH
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    Table 1.

    Sociodemographics of MA Participants (N = 59)

    Sociodemographic MeasureNo. (%)
    Age-group, y
        18-2914 (23.7)
        30-3926 (44.1)
        40-4911 (18.6)
        50-596 (10.2)
        60-692 (3.4)
    Sex
        Missing1 (1.7)
        Female54 (91.5)
        Male4 (6.8)
    Race
        Missing11 (18.6)
        American Indian1 (1.7)
        Asian9 (15.3)
        Native Hawaiian or1 (1.7)
    Pacific Islander
        White22 (37.3)
        Other or multirace15 (25.4)
    Hispanic
        No32 (54.2)
        Yes27 (45.8)
    Location
        Urban/suburban46 (78.0)
        Partially rural13 (22.0)
    Health system organizationa
        UHA16 (27.1)
        SHC20 (33.9)
        IHC23 (39.0)
    Years as MA
        <12 (3.4)
        1-411 (18.6)
        5-917 (28.8)
        ≥1029 (49.2)
    • IHC = Intermountain Healthcare; MA = medical assistant; SHC = Stanford Health Care; UHA= University Healthcare Alliance.

    • Notes: MAs reported that all clinics except for 1 SHC clinic predominately used an MA-to-physician 1:1 teamlet model, although other variations (eg, 3:3, 2:5, 3:2, and 2:1) were used across all institutions. MA work primarily consisted of tasks related to rooming patients and preparing them for seeing the physician. SHC MAs also rotated through checking patients in at the front desk.

    • ↵a These organizations represent diversity in payment structures and patient populations served: SHC is a large academic health system delivering a range of highly specialized care; UHA is a network of primary care practices closely affiliated with SHC that serve patients from diverse socioeconomic backgrounds in the San Francisco Bay Area; IHC is an integrated delivery system with its own health insurance and is the largest provider in its area.

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    Table 2.

    MA-Reported Mechanisms Whereby Financial Incentives May Improve Organizational Performance

    MechanismIllustrative Quotations
        Increased employee effort Consistent performance“Definitely different work ethics amongst all MAs, yes. You can be on top of it like OCD/type A or you could just exist I guess.” (MA 5, FG 7)
    Thorough follow-up in gathering outside records“We have [a] standard where when it’s slow, we’re supposed to create folders, but some people don’t follow up. Some people delete the whole thing when you’re not supposed to. You’re supposed to keep it for at least a month or 3.” (MA 2, FG 5)
    “I send messages to myself. I call myself on my phone…Because I’ll be home and I’ll remember something I forgot to do so I call myself.” (MA 2, FG 9)
        Equivalent population health care for non-panel patientsExpectations vary across clinics and institutions for whether MAs work to close population health gaps for patients not on their physicians’ panel. (Field notes)
    Signaling of organization priorities“We just had a report run on us last week about our blood pressure … everyone’s name was on there … we just passed it around in the huddle and you could see those ones that don’t do standard work … they only double-checked it [blood pressure] 1 time. This has been embedded in our heads for 2 months. ‘Why can’t you do your job?’” (MA 1, FG 5)
    • FG = focus group; MA = medical assistant; OCD = obsessive-compulsive disorder.

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    Table 3.

    MAs’ Perceptions of Control Over Population Health Measures (N = 57)

    Population Health MeasureaNo Control, No.A Little Control, No.Moderate Control, No.A Lot of Control, No.Complete Control, No.
    Eye examination in diabetic patients  71625  5  3
    BMI screening  2  313  632
    Controlling high blood pressure  4  824  910
    Screening for depression  2  4  51925
    Use of imaging for low back pain35  7  7  5  0
    Influenza vaccination  0  3  82421
    Tobacco screening  0  2  42229
    Breast cancer screening  6102014  6
    Colorectal cancer screening  3142311  5
    Pneumococcal vaccination for adultsb  0  3142118
    Good control of A1c in diabetic patients  51618  9  8
    • BMI = body mass index; MA = medical assistant.

    • Note: Values are numbers of MAs.

    • ↵a These measures were selected because of their inclusion in a national pay-for-performance program, ready measurability using the population health software at 2 organizations (Healthy Planet, Epic Systems), relative commonality across institutions, and diversity in associated disease and clinician roles involved in improving the measure. For example, physicians are expected to control placing imaging orders for low back pain,35 so this measure is included as a comparator.

    • ↵b Although pneumococcal vaccination guidelines call for multiple doses,36,37 achieving the national measurement is based on a single dose; thus, vaccinations can also be considered a specific type of same-day measure, although they are analyzed independently.

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    Table 4.

    Differences in MA-Perceived Control Between Health Measures by Timing and Activity Type (Screening, Vaccination)

    ComparisonOverall Perceived Control, Mean (SD)aEffect Size (95% CI)P Value
    Same day vs vaccination
        Same day3.18 (0.83)–0.14 (–0.42 to 0.14).45
        Vaccination3.04 (0.82)
    Same day vs multiday
        Same day3.18 (0.83)1.21 (0.93 to 1.48)<.001
        Multiday1.99 (0.82)
    Vaccination vs multiday
        Vaccination3.04 (0.82)1.07 (0.79 to 1.34)<.001
        Multiday1.99 (0.82)
    • ↵a On a scale from 0 (no control) to 4 (complete control). Degrees of freedom = 111 for all comparisons.

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    Table 5.

    Barriers MAs Face When Trying to Improve Population Health Measures

    BarrierIllustrative Quotation
    Time pressure including inability to work overtime“There’s a lot of [population health] questions and there’s a lot of pressure for us to do a lot within a certain time frame, and so I think asking [all] the questions is kind of out of the question. It’s too much to do.” (MA 1, FG 4)
    “We can’t have overtime, but we can’t do our job. We can’t do everything we need to do in the amount of the time we have.” (MA 3, FG 8)
    “I have my little [population health] folders at my desk, all paper, all wanting to be done.” (MA 2, FG 5)
    Poor patient compliance (multifactorial)“They go home, they’re the ones that have to take that pill, go to the pharmacy and get it. Pay for it. A lot of our patients, it’s ‘why aren’t you taking your diabetes med?’ ‘I can’t afford it.’ … It’s heartbreaking.” (MA 2, FG 9)
    “I think there’s a patient assumption that they assume that the doctor is going to always take care of them and do those refills, but the system’s not set up for that.” (MA 1, FG 7)
    Patient declines care“Sometimes patients don’t want to do colonoscopies and even patients that are due for colonoscopy will be like, ‘I don’t care, I’m not going to do that till the day I die.’ So that is challenging.” (MA 1, FG 3)
    An exchange from FG 8:
    • “I know it gets frustrating when someone’s coming in and they’re sick and we’re like, ‘Let me go over the depression questionnaire with you.’” (MA 4)

    • “They need a refuse button because I’ve had a patient that refuses to answer questions.” (MA 2)

    • “They do.” (MA 4)

    Lack of physician follow-through“Everybody’s doctor’s different. Some doctors are very good at being more meticulous in their record keeping and making sure things are ordered and stuff, where other doctors don’t order things as well and whatnot. … You may work twice as hard but your doctor didn’t make the metrics, so you’re not getting anything, yet you’re working just as hard as someone else.” (MA 6, FG 2)
    Poorly designed electronic health record“I think it’s remembering when the MAs are doing the remaining intake to get to that e-cigarette area because it’s a separate screen so you have to remember to take that extra step because vaping is such a new thing.” (MA 9, FG 1)
    “We scan that sucker [vaccination] it should autofill, without a doubt. That just doesn’t make any sense to me. Same with even just logging on … why does his [primary care physician] name not autofill? I use it 99% of the time?” (MA 3, FG 9)
    Inability to adequately address a positive depression screenFacilitator [follow-up question regarding the depression screen]: “Does anybody start crying?”
    An exchange from FG 2:
    • “Almost every other patient … They’re coming in for like a toe, foot problem. You’re asking them some depression questions and they break down.” (MA 7)

    • “That’s why it’s hard for the doctors too. When we were trying to add it to the workflow, it was hard for them, because they were like, ‘Okay. We’re here for foot pain and now we’re talking about depression.’ And of course, in all of this it expanded more than the 15 to the 30 or 40 [minutes].” (MA 4)


    An exchange from FG 9:
    • “You have no choice but to stare at a computer because you’ve got to hit all these dots, rather than, you know, sit there and when they’re crying at you …” (MA 2)

    • “And you only have that short window to get it done.” (MA 4)

    • “‘Stop crying for just a minute.’” (MA 2)

    • “And you have to hurry because the doctor’s on your butt.” (MA 4)

    Reluctance to irritate patient“I personally don’t like quizzing because if someone asked me every time I saw a provider, I would be annoyed, so I try to make a mark of that, like ‘when’s the last time I asked them?’ so I know if they’re not a generally depressed person so I’m not bothering them.” (MA 4, FG 7)
    “It is a lot of extra work, and we’re not harassing people, but sometimes it feels like we’re harassing them, making sure they’re doing what they need to do, but in the end it is saving [the health system] money. It is saving patients hospital visits. It is saving ER [emergency room visits]. So it is making a difference. It doesn’t always feel like it.” (MA 2, FG 7)
    Frequent role switching“It’s very important that same MA continues doing the [population health list] work for it, especially on admin time. That way you know where you left off, because someone else touches it, it ends up you have to start from the beginning to understand.” (MA 2, FG 5)
    • FG = focus group; MA = medical assistant.

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Financial Incentives for Medical Assistants: A Mixed-Methods Exploration of Bonus Structures, Motivation, and Population Health Quality Measures
Stacie Vilendrer, Cati Brown-Johnson, Samantha M. R. Kling, Darlene Veruttipong, Alexis Amano, Bryan Bohman, William P. Daines, David Overton, Raj Srivastava, Steven M. Asch
The Annals of Family Medicine Sep 2021, 19 (5) 427-436; DOI: 10.1370/afm.2719

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Financial Incentives for Medical Assistants: A Mixed-Methods Exploration of Bonus Structures, Motivation, and Population Health Quality Measures
Stacie Vilendrer, Cati Brown-Johnson, Samantha M. R. Kling, Darlene Veruttipong, Alexis Amano, Bryan Bohman, William P. Daines, David Overton, Raj Srivastava, Steven M. Asch
The Annals of Family Medicine Sep 2021, 19 (5) 427-436; DOI: 10.1370/afm.2719
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