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Mindsets play an important role in motivating and shaping health behavior and outcomes. For example, when patients have the mindset that a treatment will work, they are more likely to adhere to treatment medications and the treatment itself becomes more effective as a result of this mindset. Providers have an opportunity to shape important patient mindsets as part of clinical care, and these mindsets may influence patients' adherence to medication, screening and vaccination recommendations, and diet, exercise, and treatment recommendations that can help patients manage chronic illness. To help care teams capitalize on the potential of leveraging mindsets in medicine and improve patient health behavior and outcomes, we developed and implemented the Medicine Plus Mindset Training as part of Primary Care 2.0. Built on more than two decades of research, this training program (a) Informs Primary Care teams about the power of patient mindsets in shaping treatment outcomes (b) Provides care teams with a language and framework to identify which patient mindsets may be at play (i.e. patient mindsets about illness, treatment, their body, and the provider/care team) and (c) Equips care teams with skills and techniques to effectively shape patient mindsets to improve health outcomes. By motivating care teams to recognize patient mindsets that may be hindering health behavior change (such as "this illness is a catastrophe") or medication adherence (such as "this medication is going to cause side effects"), care teams become better equipped to help their patients adopt more useful mindsets (such as "this treatment will work," "this illness is manageable," "my body is capable," and "I am in good hands").
Full description
Healthcare providers at four Stanford clinic sites will be the investigators' main participants and the study will follow a wait-list control design. The investigators will track patient health outcomes.
The intervention described in this study will only be for the healthcare team. The investigators will track both provider outcomes (using self-report survey measures) and patient outcomes (using health information already being collected by the clinic). Although the investigators will be tracking the outcomes of all physicians at the clinics, only select patient outcomes will be included as part of the study.
The study will begin with the care team filling out baseline self-report surveys online and/or in person.
Prior to delivering the intervention, the clinics will be split, and half of the clinic sites will be assigned to be wait-list control clinics, while the other half of sites will receive the mindset training.
The intervention for the care team will be delivered in person by members of the research team. The care team will be told that the investigators are assessing the impact of a novel training program for providers.The care team will truthfully be informed that the training they are receiving is designed to enhance their interactions with patients.
Questionnaires:
The care team: Physicians will be asked to fill out an initial brief survey about their mindsets about connecting with patients, burnout, job satisfaction, and their efficacy using harnessing mindsets in clinical practice. Care team members will then be asked to fill out the same survey after receiving their training.
Charts will be reviewed to assess patient health outcomes. Data from the electronic medical record will be used to assess patient health outcomes at all clinics.
Overview of Expected Outcomes: This training was designed to improve care teams' ability to shape patient mindsets in clinical care, and therefore influence patient outcomes in the following ways:
Outcome Computation Plans for Requested Data:
To assess the impact of the training, we will review patient-level primary care data from January 1, 2016-June 1, 2020. Using the data requested, we will compute outcomes for each of the three broad categories as follows. We will compare outcomes within each clinic before and after the training was implemented, and will also compare outcomes at the two initial intervention clinics to outcomes at the two initial-wait list clinics during the time period in which two of the clinics had received the training and two had not.
Increase Adherence
Prescription fills, refills, & discontinuations Refill requests will serve as a proxy measure for whether patients are taking their medications as prescribed.
• Medications of interest:
Prescriptions fills, refills, & discontinuations for medications for chronic disease management medications such as:
o Antidepressants
• SSRIs & SNIs
Statins
Hypertension medication
• Beta blockers
Diabetic medications
• Variable(s) we will compute:
We will compute the percentage of patients who re-fill new prescriptions.
If possible, we will also use pharmacy data to assess the number of patients who fill the new prescription initially.
If possible, we will also assess the number of patients whose medication is discontinued because the patient stopped taking the medication.
Follow-up lab visit for patients with diabetes Patients with uncontrolled diabetes are recommended to have lab work every 3 months, and patients with controlled diabetes are recommended to have lab work every 6 months. Completion of such lab visits is an indication of adherence.
• Variables we will compute:
We will compute the percentage of patients with uncontrolled diabetes (defined as A1c > 8 or A1c > 9) coming in for lab work follow ups within 5 months after clinic visit.
We will compute the percentage of patients with controlled diabetes (defined as 6.5 < A1c < 8 or 6.5 < A1c < 9) coming in for lab work follow ups within 12 months after clinic visit.
Referral adherence When providers refer patients for diagnostic screenings such as Colonoscopy, Fit or Mammograms, completion of these referrals is a sign of adherence.
Variables we will compute:
o We will compute the percentage of patients following through with recommended screening referrals.
Denominator: Patients who are referred for Colonoscopy, Fit, or Mammogram.
Numerator: Patients from the above group who completed their screening within 6 months of order date
Vaccine adherence Pneummococcol vaccinations are recommended to patients ages 65 and older. Completed pneummococcol vaccinations are an indication of patient adherence to provider recommendations.
Variables we will compute:
o We will compute the percentage of patients 65 and older who received the pneumococcol vaccination.
Denominator: Patients in the clinic who are 65 and older
Numerator: Patients from the above group who completed the pneumococcol vaccination within 6 months of visit
o We will compute the percentage of patients aged 65-67, who are newly eligible to receive the pneumococcol vaccination, who received the pneumococcol vaccination.
Denominator: Patients in the clinic who are between 65 and 67 years of age
Numerator: Patients from the above group who completed the pneumococcol vaccination within 6 months of visit
Reduce antibiotic use
Reduction in antibiotic prescriptions While in most cases we hope to increase adherence to medication prescriptions, there are many cases in which antibiotics are unnecessary. For example, antibiotics are often unnecessarily prescribed for common colds, bronchitis, chest colds, flu, and sore throats. A 2016 CDC report found that an estimated 30% of antibiotics prescribed in outpatient settings are unnecessary. In order to combat antibiotic resistant bacteria, the CDC set a 2015 goal to reduce inappropriate antibiotic use in outpatient settings by 50% by 2020. Thus, reduction in overall antibiotic use is a desirable outcome.
● Variable(s) we will compute:
We will compute overall antibiotic prescriptions by looking at the number of patients prescribed antibiotics at clinic visits.
We will compute antibiotic prescriptions for respiratory illness by looking at the number of patients with respiratory illnesses prescribed antibiotics at clinic visits.
Improve health outcomes
Reduction in patient BMI Reduction in BMI for patients who are overweight is an indication of improved health outcomes.
● Variable(s) we will compute:
Overall reduction in BMI for patients who are overweight
▪ First we will select patients with a BMI > 25
▪ Then we will compute change in BMI between visits for these patients.
Reduction in BMI for patients with diabetes
Reduction in patient blood pressure Reduction in blood pressure for patients with hypertension is an indication of improved health outcomes.
Variable(s) we will compute:
Reduction in patient A1c levels Improved A1c control for patients with diabetes is an indication of improved health outcomes.
● Variables we will compute:
Overall reduction in A1c for patients with diabetes
▪ First we will select patients with a diagnosis of diabetes
▪ Then we will compute change in A1c between visits for the above
Reduction in A1c for patients with uncontrolled diabetes ▪ First we will select patients with uncontrolled diabetes (A1c > 8 or A1c > 9) ▪ Then we will compute change in A1c between visits for the above patients
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78,128 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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