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OBJECTIVES: To estimate the economic benefit of evidence-based patient-initiated virtual physical therapy (PIVPT) service among a nationally representative sample of commercially insured patients with musculoskeletal (MSK) conditions. STUDY DESIGN: Counterfactual simulation. METHODS: Using a nationally representative sample from the 2018 Medical Expenditure Panel Survey, we simulated the direct medical care savings and indirect cost savings from reduced absenteeism resulting from PIVPT among commercially insured working adults with self-reported MSK conditions. Model parameters of the impact of PIVPT are drawn from peer-reviewed literature. Four potential benefits of PIVPT are explored: (1) more rapid access to PT, (2) improved adherence to PT, (3) less expensive PT care per episode, and (4) reduced/avoided referral costs of PT. RESULTS: The mean medical care savings per person per year from PIVPT range between $1116 and $1523. Savings are mainly attributed to early initiation of PT (35%) and lower cost of PT (33%). The benefits of PIVPT result in a mean reduction of 6.6 hours in pain-related missed work per person per year. The return on investment of PIVPT is 2.0 (medical savings only) or 2.2 (medical savings plus reduced absenteeism). CONCLUSIONS: PIVPT service provides added value to MSK care by facilitating earlier access and better adherence to PT and lowering the cost of PT.
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Renta , Modalidades de Fisioterapia , Adulto , Humanos , Costos y Análisis de CostoRESUMEN
OBJECTIVE: To analyze economic savings and health impacts associated with a virtual digitally enhanced diabetes self-management education and support (DSMES) program. RESEARCH DESIGN AND METHODS: Participants (n = 1,494) were nonpregnant adults with diagnosed type 2 diabetes and baseline body mass index (BMI) of 25 kg/m2 (23 kg/m2 if of Asian descent) or higher who enrolled in virtual DSMES between February 2019 and April 2020 for at least 4 months. Participants' changes in glycated hemoglobin (A1C) and body weight were calculated as the difference between program start and last recorded values between months 4 and 6. Outcomes for all participants were analyzed; subanalyses were done on 628 participants with starting A1C >7% (53 mmol/mol), who could benefit most from DSMES. Markov-based microsimulation approach was used to model the potential reductions in diabetes sequalae and medical expenditures if observed improvements in A1C and BMI were maintained. RESULTS: DSMES participants with starting A1C >7% experienced average reductions of 0.9% A1C and 2.1 kg of body weight (-1.7% of BMI) within 6 months. If these improvements were maintained, simulated outcomes include reduced 5-year onset of ischemic heart disease by 9.2%, myocardial infarction by 10.6%, stroke by 12.1%, chronic kidney disease by 16.5%, and reduced onset of other sequelae. Simulated cumulative reduction in medical expenditures is $1160 after 1 year, $4150 after 3 years, $7790 after 5 years, and $18 020 after 10 years. CONCLUSIONS: Participation in virtual DSMES improves A1C and body weight, with the potential to slow onset of diabetes sequelae and reduce medical expenditures.
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Diabetes Mellitus Tipo 2 , Automanejo , Adulto , Glucemia , Peso Corporal , Diabetes Mellitus Tipo 2/epidemiología , Hemoglobina Glucada/análisis , HumanosRESUMEN
INTRODUCTION: In light of the need to expand the reach and access of clinically proven digital Diabetes Prevention Programs (d-DPPs) and the need for rigorous evidence of effectiveness, the purpose of this study was to determine the effectiveness of a digital Diabetes Prevention Program for improving weight, HbA1c, and cardiovascular risk factors among people with prediabetes compared to enhanced standard care plus waitlist control. STUDY DESIGN: This was a single-blind RCT among participants at risk of developing type 2 diabetes and included 12 months of follow-up. SETTING/PARTICIPANTS: A total of 599 volunteer patients with prediabetes were recruited primarily through electronic medical records and primary care practices. INTERVENTION: Participants were randomized to either a d-DPP (n=299) or a single-session small-group diabetes-prevention education class (n=300) focused on action planning for weight loss. The d-DPPs consisted of 52 weekly sessions, lifestyle coaching, virtual peer support, and behavior tracking tools. MAIN OUTCOME MEASURES: The primary outcome was a change in HbA1c from baseline to 12 months using intent-to-treat analyses. On the basis of multiple comparisons of endpoints, 95% CIs are presented and 2-sided p<0.025 was required for statistical significance. Secondary outcomes included body weight and cardiovascular disease risk factors. RESULTS: Among 599 randomized participants (mean age=55.4 years, 61.4% women), 483 (80%) completed the study. The d-DPPs produced significantly greater reductions in HbA1c (0.08%, 95% CI= -0.12, -0.03) and percentage change in body weight (-5.5% vs -2.1%, p<0.001) at 12 months. A greater proportion of the d-DPPs group achieved a clinically significant weight loss ≥5% (43% vs 21%, p<0.001), and more participants shifted from prediabetes to normal HbA1c range (58% vs 48%, p=0.04). Engagement in d-DPPs was significantly related to improved HbA1c and weight loss. CONCLUSIONS: This d-DPPs demonstrated clinical effectiveness and has significant potential for widespread dissemination and impact, particularly considering the growing demand for telemedicine in preventive healthcare services. TRIAL REGISTRATION: This study is registered at www. CLINICALTRIALS: gov (ClinicalTrials.gov Identifier: NCT03312764).
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Diabetes Mellitus Tipo 2 , Estado Prediabético , Telemedicina , Diabetes Mellitus Tipo 2/prevención & control , Femenino , Humanos , Masculino , Persona de Mediana Edad , Estado Prediabético/terapia , Método Simple Ciego , Pérdida de PesoRESUMEN
OBJECTIVE: Interactive patient care systems (IPCS) at the bedside are becoming increasingly common, but evidence is limited as to their potential for innovative clinical trial implementation. The objective of this study was to test the hypothesis that the IPCS could feasibly be used to automate recruitment and enrolment for a clinical trial. METHODS: In medical-surgical units, we used the IPCS to randomise, recruit and consent eligible subjects. For participants not interacting with IPCS study materials within 48 hours, study staff-initiated recruitment in-person. Eligible study population included all caregivers and any patients >6 years old admitted to medical-surgical units and oncology units September 2015 to January 2016. OUTCOMES: randomisation assessed using between-group comparisons of patient characteristics; recruitment success assessed by rates of consent; paperless implementation using successful acquisition of electronic signature and email address. We used χ2 analysis to assess success of randomisation and recruitment. RESULTS: Randomisation was successful (n=1012 randomised, p>0.05 for all between-group comparisons). For the subset of eligible, randomised patients who were recruited, IPCS-only recruitment (consented: 2.4% of n=213) was less successful than in-person recruitment (61.4% of n=87 eligible recruited, p<0.001). For those consenting (n=61), 96.7% provided an electronic signature and 68.9% provided email addresses. CONCLUSIONS: Our results suggest that as a tool at the bedside, the IPCS offers key efficiencies for study implementation, including randomisation and collecting e-consent and contact information, but does not offer recruitment efficiencies. Further research could assess the value that interactive technologies bring to recruitment when paired with in-person efforts, potentially focusing on more intensive user-interface testing for recruitment materials. TRIAL REGISTRATION NUMBER: NCT02491190.