Arrow
use cases

Improve Medication Adherence

Poor medication adherence causes 125k deaths, 10% hospital admissions, costs $300B yearly. AI can boost adherence, reduce risks.

Problem

The magnitude of poor adherence to medications for chronic conditions is striking. Of the approximately four billion prescriptions written each year, 20% are never filled and when they are, only 50% are taken correctly (1). The price of poor medication adherence is similarly staggering. It has been linked to an estimated 125,000 annual deaths, 10% of yearly hospital admissions, and up to $300 billion in annual economic impacts (2-4). However, this burden is not inevitable.

Why it matters

Improving adherence can have a significant impact on costs and outcomes. For commercial populations, every $1 spent on medications reduced medical costs between $3-10 (depending on the condition) and the impact was even greater (5). In Medicaid populations, high adherence drove 8–26% fewer admissions and 3–12% fewer ER visits, again depending on the condition (6). Research has also shown that the benefits of better adherence accrue well before crossing an 80% threshold (often used to designate ‘good adherence’). They actually begin much sooner (e.g., at 40%) and grow as adherence rises. The same study also demonstrated that helping patients to initiate medications could possibly have an equal if not greater impact.Medication adherence is a complex behavior influenced by several interacting factors that differ by patient, provider, medication, and condition (7,8). In fact, systematic reviews have concluded there is no “best” intervention that is singularly effective (9-11). Instead, success relied on being able to identify each patient’s needs and match them with the right intervention. Successful interventions varied, but common elements included face-to-face pharmacist consultations, addressing financial barriers, aiding habit formation (e.g., pill monitors and refill reminders), and using behavioral economic elements.

Solution

HCOs can leverage predictive analytics and AI to systematically promote adherence as a part of routine clinical practice. Exploiting AI-based models can enable clinicians to regularly assess each patient’s individual adherence, risk for specific adverse events, and barriers to care. This knowledge can facilitate personalized intervention efforts that address modifiable risk factors and account for the complexity and variable nature of medication adherence across different patients. Armed with predictive analytics, HCOs can readily identify the key opportunities in which improving adherence has the most potential to reduce risks and improve outcomes.AI equips clinicians and care managers with the power to determine which patients need extra attention when it comes to adhering to their medication routine. By providing accurate statistics, AI allows health workers to make an informed choice on who needs calling—and how best they should be approached in these conversations. They can provide personalized care tailored to meet the individual needs of their patients. Through programs that facilitate access and offer assistance, they are able to bridge gaps in medication availability- greatly improving health outcomes while optimizing resources. In doing so, these institutions truly empower those under their care by providing an environment where quality support is always at hand.

Datasources

  • Unstructured Clinical Notes: Data extracted from EHR clinical notes for conditions being diagnosed, monitored, or treated about important clinical concepts related to symptoms, test results, diagnoses and treatments.
  • Rx Claims: Data extracted from health insurance pharmacy claims with details about each medication and its type, fill dates, days supply, pharmacy location, and prescribing clinician.
  • Digital Health: Captures a wide variety of data, including digital biomarkers, symptom trackers, vital signs, diet and exercise, weight, adherence trackers, sleep monitoring, self-assessments.

Citations

  1. Neiman, Andrea B., et al. "CDC Grand Rounds: Mejora de la adherencia a los medicamentos para el manejo de enfermedades crónicas: innovaciones y oportunidades". MMWR. Informe Semanal de Morbilidad y Mortalidad, vol. 66, núm. 45, 17 de noviembre de 2017, págs. 1248-1251, doi:http://dx.doi.org/10.15585/mmwr.mm664522. Consultado el 24 de febrero de 2021.
  2. Brown, Marie T., Bussell, Jennifer K. "Adherencia a la medicación: ¿A QUIÉN le importa?" Actas de la Clínica Mayo, vol. 86, núm. 4, abril c2011, págs. 304-314, DO!:10.4065/mcp.2010.0575. Consultado el 24 de febrero de 2021.
  3. Kim, Jennifer y otros. Adherencia a la medicación: el elefante en la habitación”. Farmacéutico estadounidense, vol. 43, núm. 1, 19 de enero de 2018, págs. 30-34. Consultado el 24 de febrero de 2021.
  4. NEHI "En balance: Adherencia a la medicación del paciente y manejo de enfermedades crónicas”. Network for Excellence in Health Innovation, 10 de junio de 2020. Consultado el 24 de febrero de 2021.
  5. Roebuck MC, Liberman JN, Gemmill-Toyama M, Brennan TA. La adherencia a los medicamentos conduce a un menor uso y costos de atención médica a pesar del aumento del gasto en medicamentos. Asuntos de Salud. 2011:30(1):91-99. doi:10.1377/hlthaff.2009.1087
  6. Roebuck MC, Kaestner RJ, Dougherty JS. Impacto de la adherencia a los medicamentos en la utilización de los servicios de salud en Medicaid. Atención médica. 2018;56(3):1. doi:10.1097/mlr.0000000000000870
  7. BA Briesacher, et al; Pacientes en riesgo de falta de adherencia a la medicación relacionada con el costo: una revisión de la literatura. J Gen Intern Med. 2007,22:864-71.
  8. Pensando fuera del pastillero: un enfoque de todo el sistema para mejorar la adherencia a la medicación del paciente para enfermedades crónicas; Resumen de investigación del NEHI, agosto de 2009.
  9. Intervenciones de adherencia a la medicación: eficacia comparativa. Cerrando la Brecha de Calidad: Revisando el Estado de la Cienci; Informe de Evidencia No. 208 (Publicación AHRQ No. 12-E010-1)
  10. M. Viswanathan, et al; Intervenciones para mejorar la adherencia a los medicamentos autoadministrados; Ann Inter Med; septiembre de 2012.
  11. Conn VS, Ruppar TM, Enriquez M, Cooper P. Intervenciones de adherencia a medicamentos dirigidas a sujetos con problemas de adherencia: revisión sistemática y metanálisis. Investigación en Farmacia Social y Administrativa. 2016;12(2):218-246. doi:10.1016/j.sapharm.2015.06.001

Book a Free Consultation

Trusted by the world's top healthcare institutions