Using a State Birth Registry as a Quality Improvement Tool.

Background Birth registry data are universally collected, generating large administrative datasets. However, these data are typically not used for quality improvement (QI) initiatives in perinatal medicine because the quality and timeliness of the information is uncertain. Objective We sought to identify and address causes of inaccuracy in recording birth registry information so that birth registry data could support statewide obstetrical quality initiatives in Ohio. Study Design The Ohio Perinatal Quality Collaborative and the Ohio Department of Health Vital Statistics used QI techniques in 15 medium-sized maternity hospitals to identify and remove systemic sources of inaccuracy in birth registry data. The primary outcome was the rate of scheduled deliveries without medical indication between 370/7 and 386/7 weeks at participating hospitals from birth registry data. Results Inaccurate birth registry data most commonly resulted from limited communication between clinical and medical record staff. The rate of scheduled births between 370/7 and 386/7 weeks' gestation without a documented medical indication as recorded in the birth registry declined by 35%. Conclusion A QI initiative aimed at increasing the accuracy of birth registry information demonstrated the utility of these data for surveillance of perinatal outcomes and has led to ongoing efforts to support birth registrars in submitting accurate data.

A maturity grid assessment tool for learning networks.

BACKGROUND: The vision of learning healthcare systems (LHSs) is attractive as a more effective model for health care services, but achieving the vision is complex. There is limited literature describing the processes needed to construct such multicomponent systems or to assess development. METHODS: We used the concept of a capability maturity matrix to describe the maturation of necessary infrastructure and processes to create learning networks (LNs), multisite collaborative LHSs that use an actor-oriented network organizational architecture. We developed a network maturity grid (NMG) assessment tool by incorporating information from literature review, content theory from existing networks, and expert opinion to establish domains and components. We refined the maturity grid in response to feedback from network leadership teams. We followed NMG scores over time for nine LNs and plotted scores for each domain component with respect to SD for one participating network. We sought subjective feedback on the experience of applying the NMG to individual networks. RESULTS: LN leaders evaluated the scope, depth, and applicability of the NMG to their networks. Qualitative feedback from network leaders indicated that changes in NMG scores over time aligned with leaders' reports about growth in specific domains; changes in scores were consistent with network efforts to improve in various areas. Scores over time showed differences in maturation in the individual domains of each network. Scoring patterns, and SD for domain component scores, indicated consistency among LN leaders in some but not all aspects of network maturity. A case example from a participating network highlighted the value of the NMG in prompting strategic discussions about network development and demonstrated that the process of using the tool was itself valuable. CONCLUSIONS: The capability maturity grid proposed here provides a framework to help those interested in creating Learning Health Networks plan and develop them over time.

Using a network organisational architecture to support the development of Learning Healthcare Systems.

The US National Academy of Sciences has called for the development of a Learning Healthcare System in which patients and clinicians work together to choose care, based on best evidence, and to drive discovery as a natural outgrowth of every clinical encounter to ensure innovation, quality and value at the point of care. However, the vision of a Learning Healthcare System has remained largely aspirational. Over the last 13 years, researchers, clinicians and families, with support from our paediatric medical centre, have designed, developed and implemented a network organisational model to achieve the Learning Healthcare System vision. The network framework aligns participants around a common goal of improving health outcomes, transparency of outcome measures and a flexible and adaptive collaborative learning system. Team collaboration is promoted by using standardised processes, protocols and policies, including communication policies, data sharing, privacy protection and regulatory compliance. Learning methods include collaborative quality improvement using a modified Breakthrough Series approach and statistical process control methods. Participants observe their own results and learn from the experience of others. A common repository (a 'commons') is used to share resources that are created by participants. Standardised technology approaches reduce the burden of data entry, facilitate care and result in data useful for research and learning. We describe how this organisational framework has been replicated in four conditions, resulting in substantial improvements in outcomes, at scale across a variety of conditions.

Statewide Quality Improvement Initiative to Reduce Early Elective Deliveries and Improve Birth Registry Accuracy.

OBJECTIVE: To evaluate the success of a quality improvement initiative to reduce early elective deliveries at less than 39 weeks of gestation and improve birth registry data accuracy rapidly and at scale in Ohio. METHODS: Between February 2013 and March 2014, participating hospitals were involved in a quality improvement initiative to reduce early elective deliveries at less than 39 weeks of gestation and improve birth registry data. This initiative was designed as a learning collaborative model (group webinars and a single face-to-face meeting) and included individual quality improvement coaching. It was implemented using a stepped wedge design with hospitals divided into three balanced groups (waves) participating in the initiative sequentially. Birth registry data were used to assess hospital rates of nonmedically indicated inductions at less than 39 weeks of gestation. Comparisons were made between groups participating and those not participating in the initiative at two time points. To measure birth registry accuracy, hospitals conducted monthly audits comparing birth registry data with the medical record. Associations were assessed using generalized linear repeated measures models accounting for time effects. RESULTS: Seventy of 72 (97%) eligible hospitals participated. Based on birth registry data, nonmedically indicated inductions at less than 39 weeks of gestation declined in all groups with implementation (wave 1: 6.2-3.2%, P<.001; wave 2: 4.2-2.5%, P=.04; wave 3: 6.8-3.7%, P=.002). When waves 1 and 2 were participating in the initiative, they saw significant decreases in rates of early elective deliveries as compared with wave 3 (control; P=.018). All waves had significant improvement in birth registry accuracy (wave 1: 80-90%, P=.017; wave 2: 80-100%, P=.002; wave 3: 75-100%, P<.001). CONCLUSIONS: A quality improvement initiative enabled statewide spread of change strategies to decrease early elective deliveries and improve birth registry accuracy over 14 months and could be used for rapid dissemination of other evidence-based obstetric care practices across states or hospital systems.

A modified healthy steps model to improve resident training in behavioral and developmental care.

OBJECTIVE: To assess whether implementing a modified Healthy Steps (HS) for young children program in residency clinics could improve resident education and their perception of the quality of care provided for common behavioral and developmental (B/D) issues. METHODS: Residents and faculty blinded to study intent were surveyed to assess perceptions of resident preparedness and the quality of behavioral and developmental (B/D) care at 4 pediatric residency training sites in North Carolina. Initially, Program 1 (with an established HS program) was compared with 3 sites without established programs at baseline (Programs 2, 3, and 4), and then the results before and after implementation at Programs 2 to 4 were compared. RESULTS: Initially, subjects at Program 1 were more likely than those at Programs 2 to 4 to rate residents as "well" or "very well" prepared to provide B/D care (63% vs 20% respectively, 95% confidence interval of the difference, 25-61%) and more likely to rate the overall quality of B/D care at their clinic as "high" or "extremely high" (94% and 47% respectively, 95% confidence interval for the difference, 34-59%). After implementation of HS at Programs 2 to 4, the mean percentage of subjects rating residents as "well" or "very well" prepared and the ratings of the care provided increased dramatically. CONCLUSION: A modified HS model focusing on resident B/D education substantially increased attending and resident ratings of residents' preparedness to deliver B/D care and increased the ratings of the quality of B/D care provided.

Assisting primary care practices in using office systems to promote early childhood development.

OBJECTIVE: The aim of this study was to use family-centered measures to estimate the effect of a collaborative quality improvement program designed to help practices implement systems to promote early childhood development services. METHODS: A cohort study was conducted in pediatric and family practices in Vermont and North Carolina. Eighteen collaborative education practices and 17 comparison practices participated in a 12-month program to assist practices in implementing improved systems to provide anticipatory guidance and parental education. The main outcome measures were change over time in parent-reported measures of whether children received each of 4 aspects of recommended care, documentation of developmental and psychosocial screening, and practice-reported care delivery systems. RESULTS: The number of care delivery systems increased from a mean of 12.9 to 19.4 of 27 in collaborative practices and remained the same in comparison practices (P=.0002). The proportion of children with documented developmental and psychosocial screening among intervention practices increased from 78% to 88% (P<.001) and from 22% to 29% (P=.002), respectively. Compared with control practices, there was a trend toward improvement in the proportion of parents who reported receiving at least 3 of 4 areas of care. CONCLUSION: The learning collaborative was associated with an increase in the number of practice-based systems and tools designed to elicit and address parents' concerns about their child's behavior and development and a modest improvement in parent-reported measures of the quality of care.