Process Improvement and Information Technology: The Keys to Health Care Transformation.

Human beings are inherently resistant to change. In our technologically driven world, change happens fast, thereby regularly challenging us inherently change-averse humans to adjust. Only through rapid, effective, outcomes-driven change can we address the numerous challenges facing health care today. And as health care leaders, it is our responsibility to learn how to become the most effective change leader so that we can deliver the changes in systems, processes, and thinking required to deliver ever-improving quality, safety, and access to care while managing its cost.

Evaluating the Implementation of Project Re-Engineered Discharge (RED) in Five Veterans Health Administration (VHA) Hospitals.

BACKGROUND: Improving the process of hospital discharge is a critical priority. Interventions to improve care transitions have been shown to reduce the rate of early unplanned readmissions, and consequently, there is growing interest in improving transitions of care between hospital and home through appropriate interventions. Project Re-Engineered Discharge (RED) has shown promise in strengthening the discharge process. Although studies have analyzed the implementation of RED among private-sector hospitals, little is known about how hospitals in the Veterans Health Administration (VHA) have implemented RED. The RED implementation process was evaluated in five VHA hospitals, and contextual factors that may impede or facilitate the undertaking of RED were identified. METHODS: A qualitative evaluation of VHA hospitals' implementation of RED was conducted through semistructured telephone interviews with personnel involved in RED implementation. Qualitative data from these interviews were coded and used to compare implementation activities across the five sites. In addition guided by the Practical, Robust Implementation and Sustainability Model (PRISM), cross-site analyses of the contextual factors were conducted using a consensus process. RESULTS: Progress and adherence to the RED toolkit implementation steps and intervention components varied across study sites. A majority of contextual factors identified were positive influences on sites' implementation. CONCLUSION: Although the study sites were able to tailor and implement RED because of its adaptability, redesigning discharge processes is a significant undertaking, requiring additional support/resources to incorporate into an organization's existing practices. Lessons learned from the study should be useful to both VHA and private-sector hospitals interested in implementing RED and undertaking a care transition intervention.

Factors associated with internal medicine physician job attitudes in the Veterans Health Administration.

BACKGROUND: US healthcare organizations increasingly use physician satisfaction and attitudes as a key performance indicator. Further, many health care organizations also have an academically oriented mission. Physician involvement in research and teaching may lead to more positive workplace attitudes, with subsequent decreases in turnover and beneficial impact on patient care. This article aimed to understand the influence of time spent on academic activities and perceived quality of care in relation to job attitudes among internal medicine physicians in the Veterans Health Administration (VHA). METHODS: A cross-sectional survey was conducted with inpatient attending physicians from 36 Veterans Affairs Medical Centers. Participants were surveyed regarding demographics, practice settings, workplace staffing, perceived quality of care, and job attitudes. Job attitudes consisted of three measures: overall job satisfaction, intent to leave the organization, and burnout. Analysis used a two-level hierarchical model to account for the nesting of physicians within medical centers. The regression models included organizational-level characteristics: inpatient bed size, urban or rural location, hospital teaching affiliation, and performance-based compensation. RESULTS: A total of 373 physicians provided useable survey responses. The majority (72%) of respondents reported some level of teaching involvement. Almost half (46%) of the sample reported some level of research involvement. Degree of research involvement was a significant predictor of favorable ratings on physician job satisfaction and intent to leave. Teaching involvement did not have a significant impact on outcomes. Perceived quality of care was the strongest predictor of physician job satisfaction and intent to leave. Perceived levels of adequate physician staffing was a significant contributor to all three job attitude measures. CONCLUSIONS: Expanding opportunities for physician involvement with research may lead to more positive work experiences, which could potentially reduce turnover and improve system performance.

Quality improvement strategies and tools: A comparative analysis between Italy and the United States.

Italian and American hospitals, in two different periods, have been urged by external circumstances to extensively redesign their quality improvement strategies. This paper, through the use of a survey administered to chief quality officers in both countries, aims to identify commonalities and differences between the two systems and to understand which approaches are effective in improving quality of care. In both countries chief quality officers report quality improvement has become a strategic priority, clinical governance approaches, and tools-such as disease-specific quality improvement projects and clinical pathways-are commonly used, and there is widespread awareness that clinical decision making must be supported by protocols and guidelines. Furthermore, the study clearly outlines the critical importance of adopting a system-wide approach to quality improvement. To this extent Italy seems lagging behind compared to US in fact: (i) responsibilities for different dimensions of quality are spread across different organizational units; (ii) quality improvement strategies do not typically involve administrative staff; and (iii) quality performance measures are not disseminated widely within the organization but are reported primarily to top management. On the other hand, in Italy chief quality officers perceive that the typical hospital organizational structure, which is based on clinical directories, allows better coordination between clinical specialties than in the United States. In both countries, the results of the study show that it is not the single methodology/model that makes the difference but how the different quality improvement strategies and tools interact to each other and how they are coherently embedded with the overall organizational strategy.

Composite Measures of Health Care Provider Performance: A Description of Approaches.

CONTEXT: Since the Institute of Medicine's 2001 report Crossing the Quality Chasm, there has been a rapid proliferation of quality measures used in quality-monitoring, provider-profiling, and pay-for-performance (P4P) programs. Al-though individual performance measures are useful for identifying specific processes and outcomes for improvement and tracking progress, they do not easily provide an accessible overview of performance. Composite measures aggregate individual performance measures into a summary score. By reducing the amount of data that must be processed, they facilitate (1) benchmarking of an organization's performance, encouraging quality improvement initiatives to match performance against high-performing organizations, and (2) profiling and P4P programs based on an organization's overall performance. METHODS: We describe different approaches to creating composite measures,discuss their advantages and disadvantages, and provide examples of their use. FINDINGS: The major issues in creating composite measures are (1) whether to aggregate measures at the patient level through all-or-none approaches or the facility level, using one of the several possible weighting schemes; (2) when combining measures on different scales, how to rescale measures (using z scores,range percentages, ranks, or 5-star categorizations); and (3) whether to use shrinkage estimators, which increase precision by smoothing rates from smaller facilities but also decrease transparency. CONCLUSIONS: Because provider rankings and rewards under P4P programs may be sensitive to both context and the data, careful analysis is warranted before deciding to implement a particular method. A better understanding of both when and where to use composite measures and the incentives created by composite measures are likely to be important areas of research as the use of composite measures grows.

Do pneumonia readmissions flagged as potentially preventable by the 3M PPR software have more process of care problems? A cross-sectional observational study.

BACKGROUND: In the USA, administrative data-based readmission rates such as the Centers for Medicare and Medicaid Services' all-cause readmission measures are used for public reporting and hospital payment penalties. To improve this measure and identify better quality improvement targets, 3M developed the Potentially Preventable Readmissions (PPRs) measure. It matches clinically related index admission and readmission diagnoses that may indicate readmissions resulting from admission- or post-discharge-related quality problems. OBJECTIVE: To examine whether PPR software-flagged pneumonia readmissions are associated with poorer quality of care. METHODS: Using a retrospective observational study design and Veterans Health Administration (VA) data, we identified pneumonia discharges associated with 30-day readmissions, and then flagged cases as PPR-yes or PPR-no using the PPR software. To assess quality of care, we abstracted electronic medical records of 100 random readmissions using a tool containing explicit care processes organised into admission work-up, in-hospital evaluation/treatment, discharge readiness and post-discharge period. We derived quality scores, scaled to a maximum of 25 per section (maximum total score=100) and compared cases by total and section-specific mean scores using t tests and effect size (ES) to characterise the clinical significance of findings. RESULTS: Our abstraction sample was selected from 11,278 pneumonia readmissions (readmission rate=16.5%) during 1 October 2005-30 September 2010; 77% were flagged as PPR-yes. Contrary to expectations, total and section mean quality scores were slightly higher, although non-significantly, among PPR-yes (N=77) versus PPR-no (N=23) cases (respective total scores, 71.2±8.7 vs 65.8±11.5, p=0.14); differences demonstrated ES >0.30 overall and for admission work-up and post-discharge period sections. CONCLUSIONS: Among VA pneumonia readmissions, PPR categorisation did not produce the expected quality of care findings. Either PPR-yes cases are not more preventable, or preventability assessment requires other data collection methods to capture poorly documented processes (eg, direct observation).

Use of quality improvement interventions and the link to performance on percutaneous intervention for acute myocardial infarction.

BACKGROUND: Despite numerous calls for hospitals to employ quality improvement (QI) interventions to improve emergency department (ED) performance, their impact has not been explored in multi-site investigations. OBJECTIVE: We investigated the association between use of QI interventions (patient flow strategies, ED electronic dashboards, and five-level triage systems) and hospital performance on receipt of percutaneous intervention (PCI) within 90 min for acute myocardial infarction patients, a publicly available quality measure. METHODS: This was an exploratory, cross-sectional analysis of secondary data from 292 hospitals. Data were drawn from the Quality Improvement Activities Survey, the American Hospital Association's Annual Survey, and Hospital Compare. Linear regression models were used to detect differences in PCI performance scores based on whether hospitals employed one or more QI interventions. RESULTS: Fifty-three percent of hospitals reported widespread use of patient flow strategies, 62% reported using a dashboard, and 74% reported using a five-level triage system. Time to PCI performance scores were 3.5 percentage points higher (i.e., better) for hospitals that used patient flow strategies and 6.2 percentage points higher for hospitals that used a five-level triage system. Scores were 10.4 percentage points higher at hospitals that employed two quality improvement interventions and 12.8 percentage points higher at hospitals that employed three. CONCLUSION: Employing QI interventions was associated with better PCI scores. More research is needed to explore the direction of this relationship, but results suggest that hospitals should consider adopting patient flow strategies, electronic dashboards, and five-level triage systems to improve PCI scores.

Nurse practitioner and physician assistant scope of practice in 118 acute care hospitals.

BACKGROUND: Advanced practice providers (APPs), including nurse practitioners (NPs) and physician assistants (PAs) are cost-effective substitutes for physicians, with similar outcomes in primary care and surgery. However, little is understood about APP roles in inpatient medicine. OBJECTIVE: Describe APPs role in inpatient medicine. DESIGN: Observational cross-sectional cohort study. SETTING: One hundred twenty-four Veterans Health Administration (VHA) hospitals. PARTICIPANTS: Chiefs of medicine (COMs) and nurse managers. MEASUREMENTS: Surveys included inpatient medicine scope of practice for APPs and perceived healthcare quality. We conducted bivariate unadjusted and multivariable adjusted analyses. RESULTS: One hundred eighteen COMs (95.2%) and 198 nurse managers (75.0%) completed surveys. Of 118 medicine services, 56 (47.5%) employed APPs; 27 (48.2%) used NPs only, 15 (26.8%) PAs only, and 14 (25.0%) used both. Full-time equivalents for NPs was 0.5 to 7 (mean = 2.22) and PAs was 1 to 9 (mean = 2.23). Daily caseload was similar at 4 to 10 patients (mean = 6.5 patients). There were few significant differences between tasks. The presence of APPs was not associated with patient or nurse manager satisfaction. Presence of NPs was associated with greater overall inpatient and discharge coordination ratings by COMs and nurse managers, respectively; the presence of PAs was associated with lower overall inpatient coordination ratings by nurse managers. CONCLUSIONS: NPs and PAs work on half of VHA inpatient medicine services with broad, yet similar, scopes of practice. There were few differences between their roles and perceptions of care. Given their very different background, regulation, and reimbursement, this has implications for inpatient medicine services that plan to hire NPs or PAs.

Impact of provider coordination on nurse and physician perceptions of patient care quality.

The objective of this study was to assess the role of provider coordination on nurse manager and physician perceptions of care quality, while controlling for organizational factors. Findings indicated that nurse-nurse coordination was positively associated with nurse manager perceptions of care quality; neither physician-physician nor physician-nurse coordination was associated with physician perceptions. Organizational factors associated with positive perceptions of care quality included facility support of education for nurses and physicians, and the use of multidisciplinary rounding.

Organizational predictors of coordination in inpatient medicine.

BACKGROUND: As the care of hospitalized patients becomes more complex, intraprofessional coordination among nurses and among physicians, and interprofessional coordination between these groups are likely to play an increasingly important role in the provision of hospital care. PURPOSE: The purpose of this study was to identify the independent effects of organizational factors on provider ratings of overall coordination in inpatient medicine (OCIM). METHODOLOGY/APPROACH: This was an exploratory cross-sectional, descriptive study. Primary data were collected between June 2010 and September 2011 through surveys of inpatient medicine nurse managers, physicians, and chiefs of medicine at 36 Veterans Health Administration medical centers. Secondary data from the 2011 Veterans Health Administration national survey of nurses were also used. Individual-level data were aggregated and analyzed at the facility level. Multivariate linear regression models were used to assess the relationship between 55 organizational factors and provider ratings of OCIM. FINDINGS: Organizational factors that were common across models and associated with better provider ratings of OCIM included provider perceptions that the goals of senior leadership are aligned with those of the inpatient service and that the facility is committed to the highest quality of patient care, having resources and staff that enable clinicians to do their jobs, and use of strategies that enhance interactions and communication among and between nurses and physicians. PRACTICE IMPLICATIONS: To improve intraprofessional and interprofessional coordination and, consequently, patient care, facilities should consider making patient care quality a more important strategic organizational priority; ensuring that providers have the staffing, training, supplies, and other resources they need to do their jobs; and implementing strategies that improve interprofessional communication and working relationships, such as multidisciplinary rounding.

The association of hospital characteristics and quality improvement activities in inpatient medical services.

BACKGROUND: Quality of U.S. health care has been the focus of increasing attention, with deficiencies in patient care well recognized and documented. However, relatively little is known about the extent to which hospitals engage in quality improvement activities (QIAs) or factors influencing extent of QIAs. OBJECTIVE: To identify 1) the extent of QIAs in Veterans Administration (VA) inpatient medical services; and 2) factors associated with widespread adoption of QIAs, in particular use of hospitalists, non-physician providers, and extent of goal alignment between the inpatient service and senior managers on commitment to quality. DESIGN: Cross-sectional, descriptive study of QIAs using a survey administered to Chiefs of Medicine (COM) at all 124 VA acute care hospitals. We conducted hierarchical regression, regressing QIA use on facility contextual variables, followed by use of hospitalists, non-physician providers, and goal alignment/quality commitment. MAIN MEASURES: Outcome measures pertained to use of a set of 27 QIAs and to three dimensions--infrastructure, prevention, and information gathering--that were identified by factor analysis among the 27 QIAs overall. KEY RESULTS: Survey response rate was 90 % (111/124). Goal alignment/quality commitment was associated with more widespread use of all four QIA categories [infrastructure (b = 0.42; p < 0.001); prevention (b = 0.24; p < 0.001); information gathering (b = 0.28; p = <0.001); and overall QIA (b = 0.31; p < 0.001)], as was greater use of hospitalists [infrastructure (b = 0.55; p = 0.03); prevention (b = 0.61; p < 0.001); information gathering (b = 0.75; p = 0.01); and overall QIAs (b = 0.61; p < 0.001)]; higher occupancy rate was associated with greater infrastructure QIAs (b = 1.05, p = 0.02). Non-physician provider use, hospital size, university affiliation, and geographic region were not associated with QIAs. CONCLUSION: As hospitals respond to changes in healthcare (e.g., pay for performance, accountable care organizations), this study suggests that practices such as use of hospitalists and leadership focus on goal alignment/quality commitment may lead to greater implementation of QIAs.

System-level factors affecting clinicians' perceptions and use of interpreter services in California public hospitals.

Professional language interpreters are skilled in the nuances of interpretation and are less likely to make errors of clinical significance but clinicians infrequently use them. We examine system-level factors that may shape clinicians' perceptions and use of professional interpreters. Exploratory qualitative study in 12 California public hospitals. We conducted in-person key informant interviews with hospital leadership, clinical staff, and administrative staff. Five emergent themes highlight system-level factors that may influence clinicians' perceptions and use of professional interpreters in hospitals: (1) organization-wide commitment to improving language access for LEP patients; (2) organizational investment in remote interpreter technologies to increase language access; (3)training clinicians on how to access and work with interpreters; (4) hospital supports the training and certification of bilingual staff to serve as interpreters to expand in-person, on-site, interpreter capacity; and (5)organizational investment in readily accessible telephonic interpretation. Multiple system-level factors underlie clinicians' use of professional interpreters. Interventions that target these factors could improve language services for patients with limited English proficiency.

Hospital implementation of health information technology and quality of care: are they related?

BACKGROUND: Recently, there has been considerable effort to promote the use of health information technology (HIT) in order to improve health care quality. However, relatively little is known about the extent to which HIT implementation is associated with hospital patient care quality. We undertook this study to determine the association of various HITs with: hospital quality improvement (QI) practices and strategies; adherence to process of care measures; risk-adjusted inpatient mortality; patient satisfaction; and assessment of patient care quality by hospital quality managers and front-line clinicians. METHODS: We conducted surveys of quality managers and front-line clinicians (physicians and nurses) in 470 short-term, general hospitals to obtain data on hospitals' extent of HIT implementation, QI practices and strategies, assessments of quality performance, commitment to quality, and sufficiency of resources for QI. Of the 470 hospitals, 401 submitted complete data necessary for analysis. We also developed measures of hospital performance from several publicly data available sources: Hospital Compare adherence to process of care measures; Medicare Provider Analysis and Review (MEDPAR) file; and Hospital Consumer Assessment of Healthcare Providers and Systems HCAHPS® survey. We used Poisson regression analysis to examine the association between HIT implementation and QI practices and strategies, and general linear models to examine the relationship between HIT implementation and hospital performance measures. RESULTS: Controlling for potential confounders, we found that hospitals with high levels of HIT implementation engaged in a statistically significant greater number of QI practices and strategies, and had significantly better performance on mortality rates, patient satisfaction measures, and assessments of patient care quality by hospital quality managers; there was weaker evidence of higher assessments of patient care quality by front-line clinicians. CONCLUSIONS: Hospital implementation of HIT was positively associated with activities intended to improve patient care quality and with higher performance on four of six performance measures.

Reporting information on emergency department crowding to the hospital board and delivery of time-sensitive care.

BACKGROUND: Hospital governing boards influence the quality of care that hospitals provide by holding senior leaders and managers accountable. A study was conducted to determine whether reporting data on emergency department (ED) crowding to hospital boards was associated with better performance on a time-sensitive quality measure for patients with acute myocardial infarction (AMI): Primary PCI [percutaneous intervention] Within 90 Minutes of Hospital Arrival. METHODS: In a survey, hospital chief quality officers were asked whether the following data were reported to the hospital governing board: ED wait times, the percentage of ED patients who left without being seen (LWBS), and the percentage of admitted ED patients who are boarded in the ED. Responses were paired with Centers for Medicare & Medicaid Services (CMS) data on the percentage of eligible AMI patients who received PCI within 90 minutes of arrival, which served as the hospitals' PCI score. RESULTS: In the sample of 261 hospitals, 133 (51%) of hospital governing boards received data on wait times, 125 (48%) received data on LWBS, and 63 (24%) received data on ED boarding. After hospital characteristics were controlled for, hospitals that reported data on ED boarding to the governing board had PCI scores that were 5.5 percentage points higher (that is, better); p < .05. There was no association between reporting wait times or LWBS to the board and PCI scores. CONCLUSION: Reporting data on the incidence of ED boarding to hospital governing boards was associated with better performance for PCI. More research is needed to explore the direction of this relationship, but the results suggest that hospitals should consider reporting data on ED boarding to their boards as a low/no-cost quality improvement activity.

Bringing responsibility for small area variations in hospitalization rates back to the hospital: the propensity to hospitalize index and a test of the Roemer's Law.

OBJECTIVE: To assign responsibility for variations in small area hospitalization rates to specific hospitals and to evaluate the Roemer's Law in a way that does not artificially induce correlation between bed supply and utilization. DATA SOURCES/STUDY SETTING: We used data on hospitalizations and outpatient treatment for 15 medical conditions of nonmanaged care Part B eligible Medicare enrollees of 65 years and older in Massachusetts in 2000. STUDY DESIGN: We used a Bayesian model to estimate each hospital's pool of potential patients and the fraction of the pool hospitalized (its propensity to hospitalize, PTH). To evaluate the Roemer's Law, we calculated the correlation between hospitals' PTH and beds per potential patient. Patient severity was measured using All Patient Refined Diagnosis Related Groups. RESULTS: We show that our approach does not artificially induce a correlation between beds and utilization whereas the traditional approach does. Nevertheless, our approach indicates a strong relationship between PTH and beds (r=0.56). Eighteen (of 66) hospitals had a high PTH that differed significantly from 16 hospitals with a low PTH. Average patient severity in the high PTH hospitals was lower than in the low PTH hospitals. Although the difference was not statistically significant (P=0.12), there was a medium effect size (0.58). DISCUSSION: Variation across hospitals in the PTH index, the strong relationship between beds and the PTH, and the lack of relationship between severity and the PTH suggest the importance of policies that limit bed growth of high PTH hospitals and create incentives for high PTH hospitals to reduce hospitalizations.

How well can we identify the high-performing hospital?

Sharing lessons from high-performing hospitals facilitates quality improvement. High-performing hospitals have usually been identified using a small number of performance measures. The objective was to analyze how well 1,006 hospitals performed across a broader range of measures. Five measures were developed from publicly available data: adherence to processes of care, 30-day readmission rates, in-hospital mortality, efficiency, and patient satisfaction. For a subset of hospitals, the authors included two survey-based assessments of patient care quality, one by chief quality officers and one by frontline clinicians. In general, there was little correlation among the publicly available measures (r ≤ .10), though there was notable correlation between objective measures and survey-based measures (r = .23). Hospitals that performed well on a composite measure calculated from the publicly available measures were often not in the top quintile on most individual measures. This highlights the challenge in identifying high-performing hospitals to learn organizational-level best practices.