The impact of transforming healthcare delivery on cystic fibrosis outcomes: a decade of quality improvement at Cincinnati Children's Hospital

Predicting lung function decline in cystic fibrosis: the impact of initiating ivacaftor therapy

BACKGROUND

Modulator therapies that seek to correct the underlying defect in cystic fibrosis (CF) have revolutionized the clinical landscape. Given the heterogeneous nature of lung disease progression in the post-modulator era, there is a need to develop prediction models that are robust to modulator uptake.

METHODS

We conducted a retrospective longitudinal cohort study of the CF Foundation Patient Registry (N = 867 patients carrying the G551D mutation who were treated with ivacaftor from 2003 to 2018). The primary outcome was lung function (percent predicted forced expiratory volume in 1 s or FEV1pp). To characterize the association between ivacaftor initiation and lung function, we developed a dynamic prediction model through covariate selection of demographic and clinical characteristics. The ability of the selected model to predict a decline in lung function, clinically known as an FEV1-indicated exacerbation signal (FIES), was evaluated both at the population level and individual level.

RESULTS

Based on the final model, the estimated improvement in FEV1pp after ivacaftor initiation was 4.89% predicted (95% confidence interval [CI]: 3.90 to 5.89). The rate of decline was reduced with ivacaftor initiation by 0.14% predicted/year (95% CI: 0.01 to 0.27). More frequent outpatient visits prior to study entry and being male corresponded to a higher overall FEV1pp. Pancreatic insufficiency, older age at study entry, a history of more frequent pulmonary exacerbations, lung infections, CF-related diabetes, and use of Medicaid insurance corresponded to lower FEV1pp. The model had excellent predictive accuracy for FIES events with an area under the receiver operating characteristic curve of 0.83 (95% CI: 0.83 to 0.84) for the independent testing cohort and 0.90 (95% CI: 0.89 to 0.90) for 6-month forecasting with the masked cohort. The root-mean-square errors of the FEV1pp predictions for these cohorts were 7.31% and 6.78% predicted, respectively, with standard deviations of 0.29 and 0.20. The predictive accuracy was robust across different covariate specifications.

CONCLUSIONS

The methods and applications of dynamic prediction models developed using data prior to modulator uptake have the potential to inform post-modulator projections of lung function and enhance clinical surveillance in the new era of CF care.

Built environment factors predictive of early rapid lung function decline in cystic fibrosis

BACKGROUND

The extent to which environmental exposures and community characteristics of the built environment collectively predict rapid lung function decline, during adolescence and early adulthood in cystic fibrosis (CF), has not been examined.

OBJECTIVE

To identify built environment characteristics predictive of rapid CF lung function decline.

METHODS

We performed a retrospective, single-center, longitudinal cohort study (n = 173 individuals with CF aged 6-20 years, 2012-2017). We used a stochastic model to predict lung function, measured as forced expiratory volume in 1 s (FEV1 ) of % predicted. Traditional demographic/clinical characteristics were evaluated as predictors. Built environmental predictors included exposure to elemental carbon attributable to traffic sources (ECAT), neighborhood material deprivation (poverty, education, housing, and healthcare access), greenspace near the home, and residential drivetime to the CF center.

MEASUREMENTS AND MAIN RESULTS

The final model, which included ECAT, material deprivation index, and greenspace, alongside traditional demographic/clinical predictors, significantly improved fit and prediction, compared with only demographic/clinical predictors (Likelihood Ratio Test statistic: 26.78, p < 0.0001; the difference in Akaike Information Criterion: 15). An increase of 0.1 μg/m3 of ECAT was associated with 0.104% predicted/yr (95% confidence interval: 0.024, 0.183) more rapid decline. Although not statistically significant, material deprivation was similarly associated (0.1-unit increase corresponded to additional decline of 0.103% predicted/year [-0.113, 0.319]). High-risk regional areas of rapid decline and age-related heterogeneity were identified from prediction mapping.

CONCLUSION

Traffic-related air pollution exposure is an important predictor of rapid pulmonary decline that, coupled with community-level material deprivation and routinely collected demographic/clinical characteristics, enhance CF prognostication and enable personalized environmental health interventions.

Assessment of treatment burden and complexity in cystic fibrosis: A quality improvement project

BACKGROUND

Treatment regimens for cystic fibrosis (CF) continue to evolve and grow in complexity. Treatment regimen burden, and associated sequelae, are incompletely understood.

OBJECTIVE

Quality improvement (QI) methods were used to investigate treatment burden of CF care, family and care team partnerships, and potential interventions to reduce burden.

METHODS

Patients 6-24 years with CF and caregivers of patients 6-13 years were surveyed. Portions of validated tools and existing surveys measured burden and family-care team partnership. An automated report calculated treatment complexity. Plan-do-study-act cycles tested survey administration during CF visits and run charts tracked progress. Interventions to reduce burden were tracked, and bidirectional assessments explored partnerships among patients, families and clinicians.

RESULTS

Over 6 months, 110 patients and 62 caregivers completed assessments. Caregivers reported lower burden/higher quality of life (74.0, range 22.2-100) than patients (66.5, range 16.7-100). The mean treatment complexity score was 17.2 (range 6-34). Treatment complexity and burden increased with patient age (p < .05 and p < .01 respectively). Lower lung function correlated with higher patient-reported burden (p < .01) and higher treatment complexity (p < .0001). As burden increased, providers more often performed select interventions (discussed combining treatments, simplified regimens, or involved other team members (p < .05 for each)). Families reported high partnership (mean scores 4.7-4.8, 5 = high), and providers reported high utilization of partnership tools (tool used in 77% of encounters).

CONCLUSION

We assessed, quantified, and responded to treatment burden and complexity in real-time during outpatient CF visits. Systematic and individualized assessments of treatment complexity and burden may enhance treatment adherence while preserving quality of life.

Seasonal variation of lung function in cystic fibrosis: longitudinal modeling to compare a Midwest US cohort to international populations

Characterizing seasonal trend in lung function in individuals with chronic lung disease may lead to timelier treatment of acute respiratory symptoms and more precise distinction between seasonal exposures and variability. Limited research has been conducted to assess localized seasonal fluctuation in lung function decline in individuals with cystic fibrosis (CF) in context with routinely collected demographic and clinical data. We conducted a longitudinal cohort study of 253 individuals aged 6-22 years with CF receiving care at a pediatric Midwestern US CF center with median (range) of follow-up time of 4.7 (0-9.95) years, implementing two distinct models to estimate seasonality effects. The outcome, lung function, was measured as percent-predicted of forced expiratory volume in 1 second (FEV₁). Both models showed that older age, being male, using Medicaid insurance and having Pseudomonas aeruginosa infection corresponded to accelerated FEV₁ decline. A sine wave model for seasonality had better fit to the data, compared to a linear model with categories for seasonality. Compared to international cohorts, seasonal fluctuations occurred earlier and with greater volatility, even after adjustment for ambient temperature. Average lung function peaked in February and dipped in August, and FEV1 fluctuation was 0.81 % predicted (95% CI: 0.52 to 1.1). Adjusting for temperature shifted the peak and dip to March and September, respectively, and decreased FEV₁ fluctuation to 0.45 % predicted (95% CI: 0.08 to 0.82). Understanding localized seasonal variation and its impact on lung function may allow researchers to perform precision public health for lung diseases and disorders at the point-of-care level.

An Animated Functional Data Analysis Interface to Cluster Rapid Lung Function Decline and Enhance Center-Level Care in Cystic Fibrosis

Identifying disease progression through enhanced decision support tools is key to chronic management in cystic fibrosis at both the patient and care center level. Rapid decline in lung function relative to patient level and center norms is an important predictor of outcomes. Our objectives were to construct and utilize center-level classification of rapid decliners to develop an animated dashboard for comparisons within patients over time, multiple patients within centers, or between centers. A functional data analysis technique known as functional principal components analysis was applied to lung function trajectories from 18,387 patients across 247 accredited centers followed through the United States Cystic Fibrosis Foundation Patient Registry, in order to cluster patients into rapid decline phenotypes. Smaller centers (<30 patients) had older patients with lower baseline lung function and less severe rates of decline and had maximal decline later, compared to medium (30-150 patients) or large (>150 patients) centers. Small centers also had the lowest prevalence of early rapid decliners (17.7%, versus 24% and 25.7% for medium and large centers, resp.). The animated functional data analysis dashboard illustrated clustering and center-specific summaries of the rapid decline phenotypes. Clinical scenarios and utility of the center-level functional principal components analysis (FPCA) approach are considered and discussed.

Dynamic predictive probabilities to monitor rapid cystic fibrosis disease progression

Cystic fibrosis (CF) is a progressive, genetic disease characterized by frequent, prolonged drops in lung function. Accurately predicting rapid underlying lung‐function decline is essential for clinical decision support and timely intervention. Determining whether an individual is experiencing a period of rapid decline is complicated due to its heterogeneous timing and extent, and error component of the measured lung function. We construct individualized predictive probabilities for “nowcasting” rapid decline. We assume each patient's true longitudinal lung function, S(t), follows a nonlinear, nonstationary stochastic process, and accommodate between‐patient heterogeneity through random effects. Corresponding lung‐function decline at time t is defined as the rate of change, S′(t). We predict S′(t) conditional on observed covariate and measurement history by modeling a measured lung function as a noisy version of S(t). The method is applied to data on 30 879 US CF Registry patients. Results are contrasted with a currently employed decision rule using single‐center data on 212 individuals. Rapid decline is identified earlier using predictive probabilities than the center's currently employed decision rule (mean difference: 0.65 years; 95% confidence interval (CI): 0.41, 0.89). We constructed a bootstrapping algorithm to obtain CIs for predictive probabilities. We illustrate real‐time implementation with R Shiny. Predictive accuracy is investigated using empirical simulations, which suggest this approach more accurately detects peak decline, compared with a uniform threshold of rapid decline. Median area under the ROC curve estimates (Q1‐Q3) were 0.817 (0.814‐0.822) and 0.745 (0.741‐0.747), respectively, implying reasonable accuracy for both. This article demonstrates how individualized rate of change estimates can be coupled with probabilistic predictive inference and implementation for a useful medical‐monitoring approach.

Identifying exceptional cystic fibrosis care services: combining statistical process control with focus groups

Background

The Cystic Fibrosis (CF) Registry collects clinical data on all patients attending specialist CF centres in the UK. These data have been used to make comparisons between centres on key outcomes such as forced expiratory volume in 1 second (FEV1) using simple rankings, which promote the assumption that those with the highest measures provide ‘better’ care.

Objectives

To explore whether or not using statistical ‘process control’ charts that move away from league tables and adjusting for case mix (age, where appropriate; sex; CF genotype; pancreatic sufficiency; and socioeconomic status) could identify exceptional CF care services in terms of clinically meaningful outcomes. Then, using insight from patients and clinicians on what structures, processes and policies are necessary for delivering good CF care, to explore whether or not care is associated with observed differences in outcomes.

Design

Cross-sectional analyses.

Setting

Specialist CF centres in the UK.

Participants

Patients aged ≥ 6 years attending specialist CF centres and clinicians at these centres.

Main outcome measures

FEV1% predicted.

Data sources

Annual reviews taken from the UK CF Registry (2007–15).

Results

We studied FEV1 in many different ways and in different periods. In our analyses of both adult and paediatric centres, we observed that some centres showed repeated evidence of ‘special-cause variation’, with mean FEV1 being greater than the mean in some cases and lower than the mean in others. Some of these differences were explained by statistical adjustment for different measures of case mix, such as age, socioeconomic status, genotype and pancreatic sufficiency. After adjustment, there was some remaining evidence of special-cause variation for some centres. Our data at these centres suggest that there may be an association with the use of intravenous antibiotics. Workshops and focus groups with clinicians at paediatric and adult centres identified a number of structures, processes and policies that were felt to be associated with good care. From these, questionnaires for CF centre directors were developed and disseminated. However, the response rate was low, limiting the questionnaires’ use. Focus groups with patients to gain their insights into what is necessary for the delivery of good care identified themes similar to those identified by clinicians, and a patient questionnaire was developed based on these insights.

Limitations

Our data analyses suggest that differences in intravenous antibiotic usage may be associated with centre-level outcomes; this needs to be explored further in partnership with the centres. Our survey of centre directors yielded a low response, making it difficult to gain useful knowledge to inform further discussions with sites.

Conclusions

Our findings confirm that the CF Registry can be used to identify differences in clinical outcomes between centres and that case mix might explain some of these differences. As such, adjustment for case mix is essential when trying to understand how and why centres differ from the mean.

Future work

Future work will involve exploring with clinicians how care is delivered so that we can understand associations between care and outcomes. Patients will also be asked for their perspectives on the care they receive.

Funding

The National Institute for Health Research Health Services and Delivery Research programme.

Health outcomes measurement and organizational readiness support quality improvement: a systematic review

BACKGROUND

Using outcome measures to advance healthcare continues to be of widespread interest. The goal is to summarize the results of studies which use outcome measures from clinical registries to implement and monitor QI initiatives. The second objective is to identify a) facilitators and/or barriers that contribute to the realization of QI efforts, and b) how outcomes are being used as a catalyst to change outcomes over time.

METHODS

We searched the PubMed, EMBASE and Cochrane databases for relevant articles published between January 1995 and March 2017. We used a standardized data abstraction form. Studies were included when the following three criteria were fulfilled: 1) they relied on structural data collection, 2) when a structural and comprehensive QI intervention had been implemented and evaluated, and 3) impact on improving clinical and/or patient-reported outcomes was described. Data on QI strategies, QI initiatives and the impact on outcomes was extracted using standardized assessment tools.

RESULTS

We included 21 articles, of which eight showed statistically significant improvements on outcomes using data from clinical registries. Out of these eight studies, the Chronic Care Model, IT application as feedback, benchmarking and the Collaborative Care Model were used as QI methods. Encouraging trends in realizing improved outcomes through QI initiatives were observed, ranging from improving teamwork, implementation of clinical guidelines, implementation of physician alerts and development of a decision support system. Facilitators for implementing QI initiatives included a high quality database, audits, frequent reporting and feedback, patient involvement, communication, standardization, engagement, and leadership.

CONCLUSION

This review suggests that outcomes collected in clinical registries are supportive to realize QI initiatives. Organizational readiness and an active approach are key in achieving improved outcomes.

Improving Detection of Rapid Cystic Fibrosis Disease Progression-Early Translation of a Predictive Algorithm Into a Point-of-Care Tool

The clinical course of cystic fibrosis (CF) lung disease is marked by acute drops of lung function, defined clinically as rapid decline. As such, lung function is monitored routinely through pulmonary function testing, producing hundreds of measurements over the lifespan of an individual patient. Point-of-care technologies aimed at improving detection of rapid decline have been limited. Our aim in this early translational study is to develop and translate a predictive algorithm into a prototype prognostic tool for improved detection of rapid decline. The predictive algorithm was developed, validated and checked for 6-month, 1-year, and 2-year forecast accuracies using data on demographic and clinical characteristics from 30 879 patients aged 6 years and older who were followed in the U.S. Cystic Fibrosis Foundation Patient Registry from 2003 to 2015. Predictions of rapid decline based on the algorithm were compared to a detection algorithm currently being used at a CF center with 212 patients who received care between 2012-2017. The algorithm was translated into a prototype web application using RShiny, which resulted from an iterative development and refinement based on clinician feedback. The study showed that the algorithm had excellent predictive accuracy and earlier detection of rapid decline, compared to the current approach, and yielded a prototype platform with the potential to serve as a viable point-of-care tool. Future work includes implementation of this clinical prototype, which will be evaluated prospectively under real-world settings, with the aim of improving the pre-visit planning process for CF point of care. Likely extensions to other point-of-care settings are discussed.

Involvement of patients and parents in research undertaken by the Australian and New Zealand Fontan Registry

Research that is closely connected with the population it is studying and in which the translational value to healthcare is high is a laudable goal, but it is not often achieved. The Australian and New Zealand Fontan Registry has developed a model for involving patients and parents of children with a Fontan circulation in its research. The model involves consumer participation in the overarching Steering Committee, and has set in place multiple channels of communication allowing the early dissemination of research findings before peer-reviewing, and consumer feedback at all levels of the research. Our focus was not only to provide information but also to give a voice to this community and include them as researchers. These communication channels are a part of a larger network involving the practitioner community, support groups, funding agencies, and health authorities. This close connection with the target research population has multiple benefits: safeguarding the project; controlling and adjusting both the messages conveyed and the investigations; building a community; raising new ideas for research; increasing our research participation rate; increasing the weight of our endeavours; and, above all, increasing our own satisfaction in our research undertakings. In conclusion, the interactions with patients and their families within Australia and New Zealand provide one potential model for the involvement of patients and parents that may result in research that is more relevant, focussed, and practically applicable in a healthcare setting.

Trans-Atlantic collaboration: applying lessons learned from the US CF Foundation quality improvement initiative

Background

Between 2002 and 2006 France launched a national cystic fibrois (CF) newborn screening program; organized a network of specialized CF care centers; and issued CF diagnostic and treatment standards. To continue to build on this success in 2007 the Cystic Fibrosis Center of Expertise for Rare Diseases (CF CERD) of Nantes-Roscoff in partnership with the French CF Society, the French CF Association (Vaincre la Mucoviscidose), and all CF center leaders from across the country agreed to pursue center-level improvement in medical outcomes for people with CF by adapting the U.S. Cystic Fibrosis Foundation’s (US CFF) national initiative, Accelerating the Rate of Improvement in CF Care. To launch the Program to Improve Results and Expertise in CF (le Programme d’Amélioration des Résultats et de l’Expertise en Mucoviscidose - PHARE-M), French leaders pursued mentorship and guidance from leaders at the US CFF, the Dartmouth Institute (TDI), and clinical care teams at CF centers across the U.S.

Methods

The following activities enabled the Nantes-Roscoff CF CERD team members and a parent, involved with the French CF Association board and a quality engineer by training, to gain the leadership and quality improvement knowledge and skills necessary to implement the PHARE-M program: 1) regularly attending national meetings, tracking publications, and leveraging existing partnerships; 2) completing two sabbaticals to visit U.S. CF centers and enrolling in academic and professional training courses; and, 3) inviting US CFF and TDI leaders to France to meet key opinion leaders and frontline teams.

Conclusions

The Nantes-Roscoff CF CERD team successfully adapted the US CFF’s initiative to accelerate improvement in CF care by establishing a partnership with U.S. leaders to communicate and exchange strategies and lessons learned; intentionally studying and adapting the Clinical Microsystems approach to quality improvement; and learning directly from the experience of frontline teams in the U.S. They continue to partner with U.S. leaders and are seeking to collaborate with European colleagues to continue to improve care for individuals with CF and their families across Europe.

Implementation of cystic fibrosis clinical pathways improved physician adherence to care guidelines

INTRODUCTION

There is significant variability in clinical outcomes, including growth and lung function, between the various cystic fibrosis (CF) centers. No specific or unique therapeutic practices have been identified to account for these differences. However, more uniform care within centers was associated with better outcomes. The objective of this study was to implement clinical pathways for diagnosis and treatment of nutritional failure and lung inflammation in order to achieve better health care provider adherence to center-specific, agreed-on practices.

METHODS

Agreed-on clinical pathway treatment plans for both nutrition and lower airway inflammation were implemented on January 1, 2010. The primary outcome measure was to evaluate if patients' diagnoses and treatments were consistent with the agreed-on clinical pathways.

RESULTS

The proportion of clinic visits from baseline to 18 months post-intervention where the provider completely followed nutrition clinical pathway increased from 57.72% to 79.49% (P = 0.049) and the proportion for lower airway inflammation clinical pathway increased from 65.85% to 86.32% (P = 0.035). The use of nutritional diagnosis and documentation of associated clinical pathway in the clinical plan increased from 16.26% to 61.54% and 56.10% to 94.87%, respectively. Similarly, diagnosis of lower airway inflammation and documentation related to their treatment plans increased from 1.63% to 43.59% and 30.08% to 87.18%, respectively.

CONCLUSION

Implementation of clinical pathways for nutrition and lower airway inflammation issues resulted in more uniform care of CF patients. Having objective criteria for diagnoses and agreed-on treatment plans for each of those diagnoses allowed for monitoring and individual feedback. Increases in utilization of correct diagnoses and discussion of specific therapeutic interventions in the clinic notes were associated with increased adherence to clinical pathways. Pediatr Pulmonol. 2017;52:175-181. © 2016 Wiley Periodicals, Inc.

Applying the Chronic Care Model to Improve Care and Outcomes at a Pediatric Medical Center

BACKGROUND

Cincinnati Children's Hospital Medical Center launched the Condition Outcomes Improvement Initiative in 2012 to help disease-based teams use the principles of improvement science to implement components of the Chronic Care Model and improve outpatient care delivery for populations of children with chronic and complex conditions. The goal was to improve outcomes by 20% from baseline.

METHODS

Initiative activities included review of the evidence to choose and measure outcomes, development of condition-specific patient registries and tools for data collection, patient stratification, planning and coordinating care before and after visits, and self-management support.

RESULTS

Eighteen condition teams, in sequenced cohorts, fully participated in the three-year initiative. As of October 1, 2015, data from 27,221 active patients with chronic conditions were entered into registries within the electronic health record and being used to inform quality improvement and population management. Overall, 13,601 of these children had an improved outcome. Seven of the teams had implemented their evidence-based interventions with ≥ 90% reliability, 83% of teams were regularly using an electronic template to plan care for a child's condition before an encounter, 89% had stratified their population by severity of medical/psychosocial needs, 56% were using registry care gap data for population management, and 72% were doing self-management assessments. Eleven teams achieved the numeric goal of 20% improvement in their chosen outcome.

CONCLUSION

The results suggest that, by implementing quality improvement methods with multidisciplinary support, clinical teams can manage chronic condition populations and improve clinical, functional, and patient-reported outcomes. This work continues to be spread across the institution.

Value co-creation in healthcare through positive deviance

PURPOSE

To explore how converging fields of co-creation and positive deviance may increase value in healthcare.

METHODS

Informed by research in positive deviance, patient engagement, value co-creation, and quality improvement, we propose a positive deviance approach to co-creation of health.

RESULTS

Co-creation has shown to improve health outcomes with regard to multiple health conditions. Positive deviance has also shown to improve outcomes in multiple healthcare and patient community environments.

CONCLUSION

A positive deviance co-creation framework may aid in achieving improved outcomes for patients, care teams and their respective healthcare organizations.

Improvements in Cystic Fibrosis Quarterly Visits, Lung Function Tests, and Respiratory Cultures

BACKGROUND

The Cystic Fibrosis (CF) Foundation recommends patients attend clinic ≥4 times per year with 4 respiratory cultures and 2 pulmonary function tests (PFTs). However, nationally only 57.4% of patients met these guidelines in 2012. We used a quality improvement program with a goal of 75% of our patients meeting this care guideline by 2012.

METHODS

A 2-stage program was started in 2011. Stage 1: education of patients/caregivers on importance of quarterly visits. Stage 2: quarterly tracking system of patient appointments. Data on clinic visits, respiratory cultures, and PFTs were collected from the CF registry from January 2009 through December 2013. Statistical process control charts were used to track improvements.

RESULTS

The average number of clinic visits increased significantly from 4.6 ± 2.3 in 2009 to 6.3 ± 4.6 in 2013 (P < .0001). The percentage of patients ages 6 through 18 completing a clinic visit, PFT, and respiratory culture per quarter increased significantly from 76.2% during 2009 to 86.4% in 2013. The percentage of patients completing ≥4 clinic visits with 4 respiratory cultures and 2 PFTs improved significantly from 47.5% in 2009 to 71.0% in 2013 (P < .0001).

CONCLUSIONS

A tracking system of patient appointments significantly improved adherence to the care guidelines better than education alone. The multiple-stage quality improvement program we implemented may be modifiable and able to be integrated in other CF centers or other multiple disciplinary chronic illness care centers.

Tackling the increasing complexity of CF care

Health outcomes for individuals with cystic fibrosis (CF) have dramatically improved in parallel with better organization of clinical care systems, evolution of novel therapeutics, and improvements in diagnosis and screening for CF and CF-related complications. In parallel with these advances has come an increasing complexity and burden of care, leading to challenges with adherence to treatment regimens. As novel therapeutics continue to be developed and introduced to the CF care regimen, there are clear opportunities to refine and personalize care. This can be done by adding comparative effectiveness research to the CF clinical research paradigm and integrating novel technologies in drug delivery and remote monitoring that can facilitate adherence but also reduce the burden of treatment while maintaining efficacy. This review highlights both the challenges of the increasingly complex treatment regimens in CF and the opportunities to advance care by addressing adherence, implementation science, comparative effectiveness, and integration of novel technologies in CF care.