Accelerating Virtual Health Implementation Following the COVID-19 Pandemic: Questionnaire Study.

BACKGROUND: The COVID-19 pandemic accelerated drivers for virtual health adoption and triggered the US federal government to implement regulatory changes to reduce barriers to virtual health implementation. Consequently, virtual health solutions have been increasingly adopted, and health systems in the United States have been reorganizing their care delivery process with unprecedented speed. OBJECTIVE: This study aimed to assess and make recommendations on the strategy, business model, implementation, and future considerations for scaling and sustaining virtual health solutions based on the views of executives from the largest health systems in the United States. METHODS: In September 2020 and October 2020, the Health Management Academy conducted 29 quantitative surveys and 23 qualitative interviews involving 58 executives from 41 of the largest health systems in the United States. Participating health systems were approximately equally distributed across size categories (small, medium, and large, defined as annual total operating revenue US $2-3 billion, $3-6 billion, and >$6 billion, respectively) and US Census Bureau regions (Northeast, Midwest, South, and West). RESULTS: Based on the Health Management Academy's assessment of approaches to governance, financing, data infrastructure, and clinical integration of virtual health, most participating health systems (13/24, 54%) had a mid-stage level of maturity in virtual health implementation. Executives reported the pandemic is forcing health systems to re-examine strategic priorities; the most commonly raised key impacts were increased access (15/21, 71%) and flexibility (10/21, 48%) as well as lower costs of care delivery (9/21, 43%). Most executives (16/28, 57%) reported their organization had a defined budget for virtual health, and many noted that virtual health is best supported through value-based payment models. Irrespective of health system maturity, reimbursement was consistently rated as a key challenge to virtual health scaling, along with patient access to and understanding of virtual health technology. The success of virtual health implementation was most commonly measured by patient satisfaction, health care provider engagement, and proportion of health care providers using virtual health solutions (reported by 7/8, 88%; 6/8, 75%; and 7/8, 75% of information technology executives, respectively). Almost all health systems (27/29, 93%) expect to continue growing their virtual health offerings for the foreseeable future, with user-friendliness and ease of integration into the electronic medical record as key factors in making go-forward decisions on virtual health solutions (each selected by 9/10, 90% executives). CONCLUSIONS: The increased demand for virtual health solutions during the COVID-19 pandemic is expected to continue postpandemic. Consequently, health systems are re-evaluating their current platforms, processes, and strategy to develop a sustainable, long-term approach to virtual health. To ensure future success, health system leaders need to proactively build on their virtual health solutions; advocate for payment, site flexibility, and reimbursement parity for virtual health; and demonstrate continued engagement and boldness to evolve care beyond established models.

One size does not fit all: evaluating an intervention to reduce antibiotic prescribing for acute bronchitis.

BACKGROUND: Overuse of antibiotics for upper respiratory tract infections (URIs) and acute bronchitis is a persistent and vexing problem. In the U.S., more than half of all patients with upper respiratory tract infections and acute bronchitis are treated with antibiotics annually, despite the fact that most cases are viral in etiology and are not responsive to antibiotics. Interventions aiming to reduce unnecessary antibiotic prescribing have had mixed results, and successes have been modest. The objective of this evaluation is to use mixed methods to understand why a multi-level intervention to reduce antibiotic prescribing for acute bronchitis among primary care providers resulted in measurable improvement in only one third of participating clinicians. METHODS: Clinician perspectives on print-based and electronic intervention strategies, and antibiotic prescribing more generally, were elicited through structured telephone surveys at high and low performing sites after the first year of intervention at the Geisinger Health System in Pennsylvania (n = 29). RESULTS: Compared with a survey on antibiotic use conducted 10 years earlier, clinicians demonstrated greater awareness of antibiotic resistance and how it is impacted by individual prescribing decisions-including their own. However, persistent perceived barriers to reducing prescribing included patient expectations, time pressure, and diagnostic uncertainty, and these factors were reported as differentially undermining specific intervention components' effectiveness. An exam room poster depicting a diagnostic algorithm was the most popular strategy. CONCLUSIONS: Future efforts to reduce antibiotic prescribing should address multi-level barriers identified by clinicians and tailor strategies to differences at individual clinician and group practice levels, focusing in particular on changing how patients and providers make decisions together about antibiotic use.

A cluster randomized trial of decision support strategies for reducing antibiotic use in acute bronchitis.

BACKGROUND: National quality indicators show little change in the overuse of antibiotics for uncomplicated acute bronchitis. We compared the effect of 2 decision support strategies on antibiotic treatment of uncomplicated acute bronchitis. METHODS: We conducted a 3-arm cluster randomized trial among 33 primary care practices belonging to an integrated health care system in central Pennsylvania. The printed decision support intervention sites (11 practices) received decision support for acute cough illness through a print-based strategy, the computer-assisted decision support intervention sites (11 practices) received decision support through an electronic medical record-based strategy, and the control sites (11 practices) served as a control arm. Both intervention sites also received clinician education and feedback on prescribing practices, as well as patient education brochures at check-in. Antibiotic prescription rates for uncomplicated acute bronchitis in the winter period (October 1, 2009, through March 31, 2010) following introduction of the intervention were compared with the previous 3 winter periods in an intent-to-treat analysis. RESULTS: Compared with the baseline period, the percentage of adolescents and adults prescribed antibiotics during the intervention period decreased at the printed decision support intervention sites (from 80.0% to 68.3%) and at the computer-assisted decision support intervention sites (from 74.0% to 60.7%) but increased slightly at the control sites (from 72.5% to 74.3%). After controlling for patient and clinician characteristics, as well as clustering of observations by clinician and practice site, the differences for the intervention sites were statistically significant from the control sites (P = .003 for control sites vs printed decision support intervention sites and P = .01 for control sites vs computer-assisted decision support intervention sites) but not between themselves (P = .67 for printed decision support intervention sites vs computer-assisted decision support intervention sites). Changes in total visits, 30-day return visit rates, and proportion diagnosed as having uncomplicated acute bronchitis were similar among the study sites. CONCLUSIONS: Implementation of a decision support strategy for acute bronchitis can help reduce the overuse of antibiotics in primary care settings. The effect of printed vs computer-assisted decision support strategies for providing decision support was equivalent. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00981994.

Unintended consequences of a quality measure for acute bronchitis.

OBJECTIVES: To determine whether diagnostic coding shifts might undermine apparent improvements resulting from the 2007 Healthcare Effectiveness Data and Information Set (HEDIS) measure on avoidance of antibiotics for the treatment of adults with acute bronchitis (International Classification of Diseases, Ninth Revision, Clinical Modification code 466.0). STUDY DESIGN: Time series analysis within a primary care network for 3 successive winter seasons from 2006 to 2009. METHODS: All initial adult visits with a primary diagnosis code of 466.0 or 490 (bronchitis, not otherwise specified) were analyzed. Multivariable analysis accounted for clustering of observations by physician. RESULTS: The percentage of visits treated with antibiotics declined significantly for code 466.0 (76.8% to 74.4% to 27.0% of visits over the 3-year study period; P <.0001 for trend) but did not decline for code 490 (86.6% to 87.6% to 82.1% of visits; P = .33 for trend). Use of the 490 code rose significantly over the study period, from 1.5% of total bronchitis visits in year 1 to 84.6% of total bronchitis visits in year 3. As a result, the odds of an antibiotic prescription for codes 466 and 490 combined decreased slightly in year 3 compared with year 1 (odds ratio 0.88; 95% confidence interval 0.78-0.99). CONCLUSIONS: While performance on the specific HEDIS measure improved dramatically during this study period, overall antibiotic prescribing did not decline substantially. Quality measures that assess performance on specific diagnosis codes are imperfect and do not account for shifts in diagnosis coding.