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Rethinking clinical outcome markers in multimorbidity

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Rethinking clinical outcome markers in multimorbidity

Posted on
13 January 2020
by Andrea Gaspar

Last year, I worked on Pine Ridge Indian Reservation, where I had the privilege of providing medical care to members of the Oglala Lakota Tribe. The people there were culturally rich, but living in poverty. They also suffered from poor health, particularly chronic illnesses. Most of the time, they had not just one but multiple chronic diseases, a state called multimorbidity.

As a hospitalist, I witnessed how drastically the complications of these diseases can change lives. When a patient in their thirties with a family and a job undergoes an amputation because of a diabetic foot infection, their life is permanently altered. It is likely that their ability to comply with their medical regimen was already difficult. After the amputation, it would only become more challenging, as they would have to manage their new physical limitation on top of their daily responsibilities and medical routines. This concept – the idea that the work of being a patient can have lasting effects on the lives of individuals – is called burden of treatment (BOT).

On Pine Ridge, BOT was high for many reasons. The geographic isolation, extreme climate, and sparse job opportunities were just some of the things that made everyday life challenging. Things took more work, time, and energy, which meant that good medical adherence was not a priority for many. In addition, patients had to grapple with a medical system that was under-resourced, disorganized, and far from being able to provide them with the required support – increasing BOT and impacting adherence.

As I came to understand these challenges, I realized that these patients needed medical care that would actually help them engage in their treatment plans in order to effectively treat their chronic conditions. For example, simply trying to follow medication guidelines for diabetes wouldn’t suffice. It resulted in them simply feeling overwhelmed, causing them to neglect all or part of it. This led to worse outcomes. It was a perpetual cycle that couldn’t just be broken by medications but required education, psychosocial support, therapeutic patient-physician relationships, and more streamlined medical care.

The Cumulative Complexity Model (CuCoM) is a theoretical framework that helps explain this. There are two fundamental components of the CuCoM: patient workload and patient capacity. Patient workload is defined as the patient’s life demands and medical care demands, including from BOT. Patient capacity refers to their resources and abilities that allow them to take part in their medical care. The CuCoM proposes that in order for patients to successfully participate in their medical care, there must be a balance between workload and capacity (Figure 1) [1].

Figure 1. The Cumulative Complexity Model and minimally disruptive medicine (inspired from Spencer-Bonilla et al., 2017 [1]).

One of the ways in which to potentially establish this balance is called minimally disruptive medicine (MDM). It aims to decrease BOT by minimizing workload and increasing capacity through greater consideration of the patient’s life goals and well-being [1]. The four principles of MDM include identifying patients with high BOT, incorporating multimorbidity into clinical guidelines, considering patient perspectives, and encouraging coordination of care [2]. Things that decrease workload include streamlining appointments, decreasing administrative work, and minimizing polypharmacy. Things that improve patient capacity include bolstering social services or supporting caregivers with classes and trainings [3].

Like other things, however, ensuring proper implementation of MDM requires quality indicators to monitor effectiveness. Measuring BOT, the target of MDM, is one promising way to do this. Currently, there are two validated surveys that measure BOT in patients with multimorbidity. These include the Treatment Burden Questionnaire and the Patient Experience with Treatment and Self-Management.  Although both of these tools have both shown good reliability and validity, they have rarely been used as clinical outcome markers to evaluate healthcare quality. It is time, however, to change our approach and to start evaluating BOT as a routine part of clinical management of patients with multimorbidity. If BOT is high, patients won’t adhere. As in Pine Ridge, outcomes will be suboptimal, and quality of care can’t improve.

Multimorbidity is increasing throughout the globe, and its burden is highest in low- or middle-income populations such as Pine Ridge, where there is poverty, poor infrastructure, and disorganized healthcare systems. If we do not change our approach, multimorbidity will only continue to take its toll on individuals, communities, healthcare systems, and economies. Managing multimorbidity better than we currently are doing is imperative, and using BOT as a clinical outcome marker should be a part of this change.

 

References

1. Spencer-Bonilla G, Ana R. Quiñones, Victor M Montori. Assessing the Burden of Treatment. J Gen Intern Med. 2017;32(10):1141-1145.

2. May C, Montori V, Mair F. We need minimally disruptive medicine. BMJ. 2009;339:b2803.

3. Shippee ND et. al. Attaining minimally disruptive medicine: context, challenges and a roadmap for implementation. J R Coll Physicians Edinb. 2015;45:118-122.

Global HealthIndigenous People tags: Cumulative complexity model / Indigenous health / Minimally disruptive medicine / Multimorbidity

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