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A pragmatic methodology for the evaluation of digital care management in the context of multimorbidity.
Lindemer, Emily; Jouni, Mohammad; Nikolaev, Nikolay; Reidy, Pat; Mattie, Heather; Rogers, Jameson K; Giangreco, LouAnne; Sherman, Michael; Bartels, Matthew; Panch, Trishan.
Affiliation
  • Lindemer E; Wellframe Inc, Boston, MA, USA.
  • Jouni M; Wellframe Inc, Boston, MA, USA.
  • Nikolaev N; Wellframe Inc, Boston, MA, USA.
  • Reidy P; Wellframe Inc, Boston, MA, USA.
  • Mattie H; Wellframe Inc, Boston, MA, USA.
  • Rogers JK; Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  • Giangreco L; Google Cloud Healthcare, Mountain View, CA, USA.
  • Sherman M; Cayuga Health System, Ithaca, NY, USA.
  • Bartels M; Harvard Pilgrim Healthcare, Wellesley, MA, USA.
  • Panch T; Blue Cross Blue Shield South Carolina, Columbia, SC, USA.
J Med Econ ; 24(1): 373-385, 2021.
Article in En | MEDLINE | ID: mdl-33588669
ABSTRACT
Multimorbidity is a defining challenge for health systems and requires coordination of care delivery and care management. Care management is a clinical service designed to remotely engage patients between visits and after discharge in order to support self-management of chronic and emergent conditions, encourage increased use of scheduled care and address the use of unscheduled care. Care management can be provided using digital technology - digital care management. A robust methodology to assess digital care management, or any traditional or digital primary care intervention aimed at longitudinal management of multimorbidity, does not exist outside of randomized controlled trials (RCTs). RCTs are not always generalizable and are also not feasible for most healthcare organizations. We describe here a novel and pragmatic methodology for the evaluation of digital care management that is generalizable to any longitudinal intervention for multimorbidity irrespective of its mode of delivery. This methodology implements propensity matching with bootstrapping to address some of the major challenges in evaluation including identification of robust outcome measures, selection of an appropriate control population, small sample sizes with class imbalances, and limitations of RCTs. We apply this methodology to the evaluation of digital care management at a U.S. payor and demonstrate a 9% reduction in ER utilization, a 17% reduction in inpatient admissions, and a 29% increase in the utilization of preventive medicine services. From these utilization outcomes, we drive forward an estimated cost saving that is specific to a single payor's payment structure for the study time period of $641 per-member-per-month at 3 months. We compare these results to those derived from existing observational approaches, 11 and 1n propensity matching, and discuss the circumstances in which our methodology has advantages over existing techniques. Whilst our methodology focuses on cost and utilization and is applied in the U.S. context, it is applicable to other outcomes such as Patient Reported Outcome Measures (PROMS) or clinical biometrics and can be used in other health system contexts where the challenge of multimorbidity is prevalent.
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Full text: 1 Database: MEDLINE Main subject: Self-Management / Multimorbidity Type of study: Clinical_trials / Prognostic_studies Limits: Humans Language: En Journal: J Med Econ Journal subject: SERVICOS DE SAUDE Year: 2021 Type: Article Affiliation country: United States

Full text: 1 Database: MEDLINE Main subject: Self-Management / Multimorbidity Type of study: Clinical_trials / Prognostic_studies Limits: Humans Language: En Journal: J Med Econ Journal subject: SERVICOS DE SAUDE Year: 2021 Type: Article Affiliation country: United States