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1.
J Pediatr ; 253: 292-296.e2, 2023 02.
Article in English | MEDLINE | ID: mdl-36088995

ABSTRACT

Two low-cost pragmatic interventions (change in the options in the electronic health record; change in the electronic health record plus education plus feedback comparing prescribing with peers) to improve prescribing of guideline-concordant short antibiotic durations for children 2 years and older with uncomplicated acute otitis media were highly effective and results were sustained 18 months after discontinuation of the active components of the interventions.


Subject(s)
Otitis Media , Practice Patterns, Physicians' , Child , Humans , Anti-Bacterial Agents/therapeutic use , Otitis Media/drug therapy , Guideline Adherence , Acute Disease
2.
JMIR Diabetes ; 4(2): e12985, 2019 Apr 15.
Article in English | MEDLINE | ID: mdl-30985289

ABSTRACT

BACKGROUND: To reach all 84.1 million US adults estimated to have prediabetes warrants need for low-cost and less burdensome alternatives to the National Diabetes Prevention Program (NDPP). In a previous randomized controlled trial, we demonstrated the efficacy of a 12-month short message service text message support program called SMS4PreDM amongst individuals with prediabetes. OBJECTIVE: The study aimed to evaluate the implementation and effectiveness of SMS4PreDM in a pragmatic study following dissemination in a safety net health care system. METHODS: English- and Spanish-speaking patients at risk for diabetes (eg, glycated hemoglobin 5.7-6.4) were referred by their providers and offered either NDPP classes, SMS4PreDM, or both. This analysis focuses on weight change among 285 SMS4PreDM-only participants who began the year-long intervention between October 2015 and April 2017 with accompanying pre- and postweights, as compared with 1233 usual-care control patients at risk for diabetes, who were identified from electronic health records during this time but not referred. Weight outcomes included time-related mean weight change and frequency of either ≥3% weight loss or gain. Mixed linear models adjusted for age, gender, race, ethnicity, preferred language, and baseline weight. A secondary analysis was stratified by language. We also assessed implementation factors, including retention and cost. RESULTS: SMS4PreDM participants had high retention (259 of 285 patients or 91.0% completion at 12-months, ) and a time-related mean weight loss of 1.3 pounds (SE 0.74), compared with the control group's slight mean weight gain of 0.25 pounds (SE 0.59; P=.004). Spanish-speaking SMS4PreDM participants (n=130) had a time-related mean weight loss of 1.11 pounds (SE 1.22) compared with weight gain of 0.96 pounds (SE 1.14) in Spanish-speaking controls (n=382, P<.001). English-speaking intervention participants (n=155) had a comparable time-related mean weight change (-0.89 pounds; SE 0.93) as English-speaking controls (n=828; 0.31 pounds gained; SE 0.62, P=.14). Overall, frequency of achieving ≥3% weight loss was comparable between groups (54 of 285 or 19.0% of SMS4PreDM participants [95% CI 14.8-23.9] vs 266 of 1233 or 21.6% of controls [95% CI 19.3-24.0]; P=.33). Nonetheless, more controls had ≥3% weight gain compared with intervention participants (337 of 1233 or 27.3% of controls [95% CI 24.9-29.9] vs 57 of 285 or 20.0% of SMS4PreDM participants [95% CI 16.8-25.1]; P=.01). SMS4PreDM delivery costs were US $100.92 per participant. CONCLUSIONS: Although SMS4PreDM was relatively low cost to deliver and demonstrated high retention, weight loss outcomes may not be sufficient to serve as a population health strategy.

3.
Med Care ; 56(1): e1-e9, 2018 01.
Article in English | MEDLINE | ID: mdl-27632768

ABSTRACT

BACKGROUND: Patients with repeated hospitalizations represent a group with potentially avoidable utilization. Recent publications have begun to highlight the heterogeneity of this group. Latent class analysis provides a novel methodological approach to utilizing administrative data to identify clinically meaningful subgroups of patients to inform tailored intervention efforts. OBJECTIVE: The objective of the study was to identify clinically distinct subgroups of adult superutilizers. RESEARCH DESIGN: Retrospective cohort analysis. SUBJECTS: Adult patients who had an admission at an urban safety-net hospital in 2014 and 2 or more admissions within the preceding 12 months. MEASURES: Patient-level medical, mental health (MH) and substance use diagnoses, social characteristics, demographics, utilization and charges were obtained from administrative data. Latent class analyses were used to determine the number and characteristics of latent subgroups that best represented these data. RESULTS: In this cohort (N=1515), a 5-class model was preferred based on model fit indices, clinical interpretability and class size: class 1 (16%) characterized by alcohol use disorder and homelessness; class 2 (14%) characterized by medical conditions, MH/substance use disorders and homelessness; class 3 (25%) characterized primarily by medical conditions; class 4 (13%) characterized by more serious MH disorders, drug use disorder and homelessness; and class 5 (32%) characterized by medical conditions with some MH and substance use. Patient demographics, utilization, charges and mortality also varied by class. CONCLUSIONS: The overall cohort had high rates of multiple chronic medical conditions, MH, substance use disorders, and homelessness. However, the patterns of these conditions were different between subgroups, providing important information for tailoring interventions.


Subject(s)
Hospitalization/statistics & numerical data , Hospitals, Urban/statistics & numerical data , Medical Overuse/statistics & numerical data , Models, Statistical , Safety-net Providers/statistics & numerical data , Adult , Colorado , Female , Humans , Male , Middle Aged , Retrospective Studies
5.
Diabetes Care ; 39(8): 1364-70, 2016 Aug.
Article in English | MEDLINE | ID: mdl-26861922

ABSTRACT

OBJECTIVE: Although the benefits of in-person Diabetes Prevention Program (DPP) classes for diabetes prevention have been demonstrated in trials, effectiveness in clinical practice is limited by low participation rates. This study explores whether text message support enhances weight loss in patients offered DPP classes. RESEARCH DESIGN AND METHODS: English- and Spanish-speaking patients with prediabetes (n = 163) were randomized to the control group, which only received an invitation to DPP classes as defined by the Centers for Disease Control and Prevention, or to the text message-augmented intervention group, which also received text messages adapted from the DPP curriculum for 12 months. RESULTS: Mean weight decreased 0.6 pounds (95% CI -2.7 to 1.6) in the control group and 2.6 pounds (95% CI -5.5 to 0.2) in the intervention group (P value 0.05). Three percent weight loss was achieved by 21.5% of participants in the control group (95% CI 12.5-30.6), compared with 38.5% in the intervention group (95% CI 27.7-49.3) (absolute difference 17.0%; P value 0.02). Mean glycated hemoglobin (HbA1c) increased by 0.19% or 2.1 mmol/mol (95% CI -0.1 to 0.5%) and decreased by 0.09% or 1.0 mmol/mol (95% CI -0.2 to 0.0%) in the control group and intervention participants, respectively (absolute difference 0.28%; P value 0.07). Stratification by language demonstrated a significant treatment effect in Spanish speakers but not in English speakers. CONCLUSIONS: Text message support can lead to clinically significant weight loss in patients with prediabetes. Further study assessing effect by primary language and in an operational setting is warranted.


Subject(s)
Prediabetic State/therapy , Text Messaging , Weight Loss , Adult , Body Mass Index , Female , Follow-Up Studies , Glycated Hemoglobin/metabolism , Humans , Male , Middle Aged , Prediabetic State/psychology , Sensitivity and Specificity , Treatment Outcome
6.
EGEMS (Wash DC) ; 3(1): 1181, 2015.
Article in English | MEDLINE | ID: mdl-26290884

ABSTRACT

CONTEXT: The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health's (DH) integrated, safety net health care system $19.8 million to implement a "population health" approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner's Chronic Care Model (CCM) to achieve the "Triple Aim": improved health for populations, care to individuals, and lower per capita costs. CASE DESCRIPTION: This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. FINDINGS: In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. CONCLUSIONS: We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

7.
Am J Manag Care ; 18(2): e42-7, 2012 Feb 01.
Article in English | MEDLINE | ID: mdl-22435883

ABSTRACT

OBJECTIVES: To assess the feasibility of engaging adults with diabetes in self management behaviors between clinic visits by using cell phone text messaging to provide blood sugar measurement prompts and appointment reminders. STUDY DESIGN: Quasi-experimental pilot among adult diabetic patients with cell phones who receive regular care at a federally qualified community health center in Denver, Colorado, which serves a population that is predominantly either uninsured (41%) or on Medicaid or Medicare (56%). METHODS: Patients (N = 47) received text message prompts over a 3-month period. Blood sugar readings were requested 3 times per week (Monday, Wednesday, and Friday). Reminders were sent 7, 3, and 1 day(s) before each scheduled appointment. Acknowledgments were returned for all patient-sent messages. Focus groups were conducted in English and Spanish with selected patients (n = 8). RESULTS: Patients of all ages were active participants. Correctly formatted responses were received for 67.3% of 1585 prompts. More than three-fourths (79%) of the cohort responded to more than 50% of their prompts. The appointment analysis was underpowered to detect significant changes in attendance. Participants reported increased social support, feelings that the program "made them accountable," and increased awareness of health information. Two-thirds (66%) of patients provided glucose readings when prompted during the study, compared with 12% at 2 preceding clinic visits. CONCLUSIONS: For certain patients, cell phone-based text messaging may enhance chronic disease management support and patient-provider communications beyond the clinic setting.


Subject(s)
Diabetes Mellitus/therapy , Disease Management , Self Care/methods , Text Messaging/statistics & numerical data , Adult , Aged , Blood Glucose Self-Monitoring , Colorado , Female , Focus Groups , Hispanic or Latino , Humans , Male , Middle Aged , Patient Satisfaction , Pilot Projects , Poverty , Reminder Systems/statistics & numerical data , Self Care/statistics & numerical data
8.
Am J Manag Care ; 18(2): 77-84, 2012 02.
Article in English | MEDLINE | ID: mdl-22435835

ABSTRACT

BACKGROUND: There is a need for randomized, prospective trials of case management interventions with resource utilization analyses. OBJECTIVES: To determine whether algorithm-driven telephone care by nurses improves lipid control in patients with diabetes. DESIGN: Prospective, randomized, controlled trial. PARTICIPANTS: Adults with diabetes at a federally funded community health center were randomly assigned to intervention (n = 381) or usual-care (n = 381) groups. INTERVENTIONS: Nurses independently initiated and titrated lipid therapy and promoted behavioral change through motivational interviewing and self-management techniques. Other parameters of diabetes care were addressed based on time constraints. MAIN MEASURES: The primary outcome was the proportion of patients with a low-density lipoprotein (LDL) less than 100 mg/dL. Secondary outcomes included the number of hospital admissions, total hospital charges per patient, and the proportion of patients meeting other lipid, glycemic, and blood pressure guidelines. KEY RESULTS: The percent of patients with an LDL < 100 mg/dL increased from 52.0% to 58.5% in the intervention group and decreased from 55.6% to 46.7% in the control group (P < .01). Average cost per patient to the healthcare system was less for the intervention group ($6600 vs $9033, P = .03). Intervention patients trended toward fewer hospital admissions (P = .06). The intervention did not affect glycemic and blood pressure outcomes. CONCLUSIONS: Nurses can improve lipid control in patients with diabetes in a primarily indigent population through telephone care using moderately complex algorithms, but a more targeted approach is warranted. Telephone-based outreach may decrease resource utilization, but more study is needed.


Subject(s)
Case Management/organization & administration , Diabetes Mellitus/blood , Lipoproteins, LDL/blood , Nursing Care/methods , Patient Admission/statistics & numerical data , Telemedicine/methods , Adult , Case Management/economics , Case Management/standards , Colorado , Cost-Benefit Analysis , Diabetes Mellitus/economics , Electronic Health Records/statistics & numerical data , Humans , Medically Uninsured , Motivation , Patient Admission/economics , Prospective Studies , Self Care/methods , Telemedicine/economics
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