Fidelity of implementation: development and testing of a measure

<p>Abstract</p> <p>Background</p> <p>Along with the increasing prevalence of chronic illness has been an increase in interventions, such as nurse case management programs, to improve outcomes for patients with chronic illness. Evidence supports the effectiveness of such interventions in reducing patient morbidity, mortality, and resource utilization, but other studies have produced equivocal results. Often, little is known about how implementation of an intervention actually occurs in clinical practice. While studies often assume that interventions are used in clinical practice exactly as originally designed, this may not be the case. Thus, fidelity of an intervention's implementation reflects how an intervention is, or is not, used in clinical practice and is an important factor in understanding intervention effectiveness and in replicating the intervention in dissemination efforts. The purpose of this paper is to contribute to the understanding of implementation science by (a) proposing a methodology for measuring fidelity of implementation (FOI) and (b) testing the measure by examining the association between FOI and intervention effectiveness.</p> <p>Methods</p> <p>We define and measure FOI based on organizational members' level of commitment to using the distinct components that make up an intervention as they were designed. Semistructured interviews were conducted among 18 organizational members in four medical centers, and the interviews were analyzed qualitatively to assess three dimensions of commitment to use--satisfaction, consistency, and quality--and to develop an overall rating of FOI. Mixed methods were used to explore the association between FOI and intervention effectiveness (inpatient resource utilization and mortality).</p> <p>Results</p> <p>Predictive validity of the FOI measure was supported based on the statistical significance of FOI as a predictor of intervention effectiveness. The strongest relationship between FOI and intervention effectiveness was found when an alternative measure of FOI was utilized based on individual intervention components that had the greatest variation across medical centers.</p> <p>Conclusions</p> <p>In addition to contextual factors, implementation research needs to consider FOI as an important factor in influencing intervention effectiveness. Our proposed methodology offers a systematic means for understanding organizational members' use of distinct intervention components, assessing the reasons for variation in use across components and organizations, and evaluating the impact of FOI on intervention effectiveness.</p

Supplement 1: Spectral multiphoton effects and quantum anharmonicities in dissipative cavity-QED systems via off-resonant coherent excitation

Originally published in Optica on 20 August 2015 (optica-2-8-689

Despite variation in volume, Veterans Affairs hospitals show consistent outcomes among patients with non-postoperative mechanical ventilation

OBJECTIVE: To assess the relationship between volume of nonoperative mechanically ventilated patients receiving care in a specific Veterans Health Administration hospital and their mortality. DESIGN: Retrospective cohort study. SETTING: One-hundred nineteen Veterans Health Administration medical centers. PATIENTS: We identified 5,131 hospitalizations involving mechanically ventilated patients in an intensive care unit during 2009, who did not receive surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We extracted demographic and clinical data from the VA Inpatient Evaluation Center. For each hospital, we defined volume as the total number of nonsurgical admissions receiving mechanical ventilation in an intensive care unit during 2009. We examined the hospital contribution to 30-day mortality using multilevel logistic regression models with a random intercept for each hospital. We quantified the extent of interhospital variation in 30-day mortality using the intraclass correlation coefficient and median odds ratio. We used generalized estimating equations to examine the relationship between volume and 30-day mortality and risk-adjusted all models using a patient-level prognostic score derived from clinical data representing the risk of death conditional on treatment at a high-volume hospital. Mean age for the sample was 65 (SD 11) yrs, 97% were men, and 60% were white. The median VA hospital cared for 40 (interquartile range 19-62) mechanically ventilated patients in 2009. Crude 30-day mortality for these patients was 36.9%. After reliability and risk adjustment to the median patient, adjusted hospital-level mortality varied from 33.5% to 40.6%. The intraclass correlation coefficient for the hospital-level variation was 0.6% (95% confidence interval 0.1, 3.4%), with a median odds ratio of 1.15 (95% confidence interval 1.06, 1.38). The relationship between hospital volume of mechanically ventilated and 30-day mortality was not statistically significant: each 50-patient increase in volume was associated with a nonsignificant 2% decrease in the odds of death within 30 days (odds ratio 0.98, 95% confidence interval 0.87-1.10). CONCLUSIONS: Veterans Health Administration hospitals caring for lower volumes of mechanically ventilated patients do not have worse mortality. Mechanisms underlying this finding are unclear, but, if elucidated, may offer other integrated health systems ways to overcome the disadvantages of small-volume centers in achieving good outcomes.Supported, in part, by U.S. Department of Veterans Affairs Health Services Research & Development Services IIR 11–109 (TJI). The opinions expressed here are those of the authors and do not represent those of the Department of Veterans AffairsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93629/1/12.Cooke.CCM.VA.Volume.Outcomes.pd

Veterans Affairs patient database (VAPD 2014–2017): building nationwide granular data for clinical discovery

Abstract Background To study patient physiology throughout a period of acute hospitalization, we sought to create accessible, standardized nationwide data at the level of the individual patient-facility-day. This methodology paper summarizes the development, organization, and characteristics of the Veterans Affairs Patient Database 2014–2017 (VAPD 2014–2017). The VAPD 2014–2017 contains acute hospitalizations from all parts of the nationwide VA healthcare system with daily physiology including clinical data (labs, vitals, medications, risk scores, etc.), intensive care unit (ICU) indicators, facility, patient, and hospitalization characteristics. Methods The VA data structure and database organization represents a complex multi-hospital system. We define a single-site hospitalization as one or more consecutive stays with an acute treating specialty at a single facility. The VAPD 2014–2017 is structured at the patient-facility-day level, where every patient-day in a hospital is a row with separate identification variables for facility, patient, and hospitalization. The VAPD 2014–2017 includes daily laboratory, vital signs, and inpatient medication. Such data were validated and verified through lab value range and comparison with patient charts. Sepsis, risk scores, and organ dysfunction definitions were standardized and calculated. Results We identified 565,242 single-site hospitalizations (SSHs) in 2014; 558,060 SSHs in 2015; 553,961 SSHs in 2016; and 550,236 SSHs in 2017 at 141 VA hospitals. The average length of stay was four days for all study years. In-hospital mortality decreased from 2014 to 2017 (1.7 to 1.4%), 30-day readmission rates increased from 15.3% in 2014 to 15.6% in 2017; 30-day mortality also decreased from 4.4% in 2014 to 4.1% in 2017. From 2014 to 2017, there were 107,512 (4.8%) of SSHs that met the Center for Disease Control and Prevention’s Electronic Health Record-based retrospective definition of sepsis. Conclusion The VAPD 2014–2017 represents a large, standardized collection of granular data from a heterogeneous nationwide healthcare system. It is also a direct resource for studying the evolution of inpatient physiology during both acute and critical illness

Interpretability, credibility, and usability of hospital-specific template matching versus regression-based hospital performance assessments; a multiple methods study

Abstract Background Hospital-specific template matching (HS-TM) is a newer method of hospital performance assessment. Objective To assess the interpretability, credibility, and usability of HS-TM-based vs. regression-based performance assessments. Research design We surveyed hospital leaders (January-May 2021) and completed follow-up semi-structured interviews. Surveys included four hypothetical performance assessment vignettes, with method (HS-TM, regression) and hospital mortality randomized. Subjects Nationwide Veterans Affairs Chiefs of Staff, Medicine, and Hospital Medicine. Measures Correct interpretation; self-rated confidence in interpretation; and self-rated trust in assessment (via survey). Concerns about credibility and main uses (via thematic analysis of interview transcripts). Results In total, 84 participants completed 295 survey vignettes. Respondents correctly interpreted 81.8% HS-TM vs. 56.5% regression assessments, p < 0.001. Respondents “trusted the results” for 70.9% HS-TM vs. 58.2% regression assessments, p = 0.03. Nine concerns about credibility were identified: inadequate capture of case-mix and/or illness severity; inability to account for specialized programs (e.g., transplant center); comparison to geographically disparate hospitals; equating mortality with quality; lack of criterion standards; low power; comparison to dissimilar hospitals; generation of rankings; and lack of transparency. Five concerns were equally relevant to both methods, one more pertinent to HS-TM, and three more pertinent to regression. Assessments were mainly used to trigger further quality evaluation (a “check oil light”) and motivate behavior change. Conclusions HS-TM-based performance assessments were more interpretable and more credible to VA hospital leaders than regression-based assessments. However, leaders had a similar set of concerns related to credibility for both methods and felt both were best used as a screen for further evaluation.http://deepblue.lib.umich.edu/bitstream/2027.42/173789/1/12913_2022_Article_8124.pd