Diagnostic and antibiotic stewardship lessons: an outpatient assessment of symptomatic reflex urinalysis ordering accuracy using an electronic best-practice alert.

BACKGROUND: It is not well known how reliably clinicians order reflex urinalysis to microscopy and culture (rUA-cx) for outpatient urinary tract infection (UTI) workup. Antibiotic appropriateness cannot be fully appreciated until the prevalence of UTIs and asymptomatic bacteriuria (ASB) are realized. OBJECTIVE: This quality improvement study has two major aims, first to determine UTI symptom accuracy for rUA-cx ordering and second, to confirm UTI and ASB cases by integrating rUA-cx and cascaded urinalysis results. Antibiotic utilization and diagnostic coding were secondarily linked to UTIs and ASB. METHODS: An electronic best-practice alert informed the ordering of two rUA-cx options: symptomatic- rUA-cx specifically for dysuria, frequency, urgency, costovertebral pain, suprapubic pain or fever versus non-specific-rUA-cx for vague complaints. UTI symptoms were verified by chart review. Confirmed UTI was defined as a significant culture with UTI symptoms and ASB as a significant culture without UTI symptoms. RESULTS: rUA-cx (2065) were prospectively collected over 6 months from female patients at risk for uncomplicated UTIs. Symptomatic-rUA-cx and non-specific-rUA-cx were associated with UTI symptoms for 53% (809/1527) and 20% (107/538), respectively. Overall, 44% (916/2065) of all rUA-cx had UTI symptoms. rUA-cx were overordered by a factor of 9 (2065/225) for every confirmed UTI. The UTI-to-ASB relative ratio was 2.6 (225/86). Regarding UTI-relevant antibiotics, 39% (214/553) were appropriately associated with UTI whereas only 22% (74/339) of inappropriate antibiotics were captured by the ASB definition, underestimating the problem 4-fold. CONCLUSIONS: UTI and ASB remain challenging to categorize despite a meticulous method that applied acceptable criteria.

The Feasibility of Automating Assessment of Concordance Between Advance Care Preferences and Care Received Near the End of Life.

BACKGROUND: End-of-life care is patient centered when it is concordant with patient preferences. Concordance has been frequently assessed by interview, chart review, or both. These time-consuming methods can constrain sample sizes, precluding population-level quality assessment. Concordance between preferences and care as measured by automated methods is described. METHODS: Automated processes extracted and analyzed electronic health record (EHR) data to assess concordance between 15 advance care planning preference domains and 232 related end-of-life care events for 388 patients aged 65 years or older with an inpatient encounter at Kaiser Permanente Southern California who died during or after the encounter. Patient preferences were recorded in advance directives or physician orders or reflected in hospital code status. Concordance, assessed in relation to the most recent documents, orders, or code status, occurred when patients received care they preferred or did not receive nonpreferred care. Discordance occurred when patients received care they did not prefer or did not receive care they preferred. RESULTS: Overall concordance for 12,592 observed end-of-life care events was 97.7%. A total of 55 of 4,154 (1.3%) received care events were nonpreferred, according to patient preferences in the EHR. Automated methods could not distinguish between medically nonbeneficial treatments, those that were not medically indicated, and potential undertreatment. CONCLUSION: Automating assessment of concordance between care near the end of life and preferences is feasible but requires model refinement and discrete care preference data. Automated methods may be most valuable as a screening tool to identify potential overtreatment and undertreatment, with chart review to verify discordance.

Impact of a Care Directives Activity Tab in the Electronic Health Record on Documentation of Advance Care Planning.

CONTEXT: To ensure patient-centered end-of-life care, advance care planning (ACP) must be documented in the medical record and readily retrieved across care settings. OBJECTIVE: To describe use of the Care Directives Activity tab (CDA), a single-location feature in the electronic health record for collecting and viewing ACP documentation in inpatient and ambulatory care settings, and to assess its association with ACP documentation rates. DESIGN: Retrospective pre- and postimplementation analysis in 2012 and 2013 at Kaiser Permanente Southern California among 113,309 patients aged 65 years and older with ACP opportunities during outpatient or inpatient encounters. MAIN OUTCOME MEASURES: Providers' CDA use rates and documentation rates of advance directives and physician orders for life-sustaining treatments stratified by CDA use. RESULTS: Documentation rates of advance directives and physician orders for life-sustaining treatments among patients with outpatient and inpatient encounters were 3.5 to 9.6 percentage points higher for patients with CDA use vs those without it. The greatest differences were for orders for life-sustaining treatments among patients with inpatient encounters and for advance directives among patients with outpatient encounters; both were 9.6 percentage points higher among those with CDA use than those without it. All differences were significant after controlling for yearly variation (p < 0.001). CONCLUSION: Statistically significant differences in documentation rates between patients with and without CDA use suggest the potential of a standardized location in the electronic health record to improve ACP documentation. Further research is required to understand effects of CDA use on retrieval of preferences and end-of-life care.

An information model for automated assessment of concordance between advance care preferences and care delivered near the end of life.

OBJECTIVE: To develop an information model for automating evaluation of concordance between patient preferences and end-of-life care. METHODS: We modeled and validated 15 end-of-life care preference option domains, to which we mapped preferences recorded in standardized advance care planning documents and 232 end-of-life care events defined by procedure and medication codes. Patient preferences and end-of-life care events were available in electronic health records. Data from Kaiser Permanente Southern California modeling and testing populations were evaluated for concordance between patients' preferences and the end-of-life care events they experienced. RESULTS: The information model successfully assessed concordance between patient preferences and end-of-life care events. Among 388 expired patients in the modeling population, 4164 care events occurred, 4100 (98%) of which were preference-concordant, and 64 (2%) of which were preference-discordant. Including end-of-life care events that did not occur increased the number of observations to 6029; 99% were preference-concordant. At the level of individuals, 72% (278) of patients experienced only preference-concordant care events, 13% (50) experienced at least one preference-discordant care event, and 15% (60) experienced no preference-related care events. DISCUSSION: Model limitations pertain to assumptions that are required to match advance care planning documents with patient preference options and exclusion of preferred care that did not occur. Further research is required to apply the model to larger populations and to investigate the need for additional preference options. CONCLUSION: An information model for automating the assessment of the concordance between patients' advance care planning preferences and the end-of-life care they received was effective in a small population and has the potential to assess population-level preference-concordance on an ongoing basis.

Race/ethnicity, personal health record access, and quality of care.

OBJECTIVES: To estimate the impact of race/ethnicity and written language preference on registration for a personal health record (PHR) that included emailing providers, viewing lab results, refilling prescriptions, and other functionalities, and the impact of PHR use on quality across racial/ethnic groups with comparable access. STUDY DESIGN AND METHODS: Retrospective observational design among 3,173,774 adults. Factors affecting registration were assessed using logistic regression, and propensity score matching techniques assessed the impact of language preference on registration and PHR use on quality of care. Difference-in-differences methods assessed the significance of between-group changes in Healthcare Effectiveness Data and Information Set (HEDIS) scores, such as glycated hemoglobin and lipid screening and control. RESULTS: Race/ethnicity most strongly predicted PHR registration. After adjusting for multiple factors, Asian American, Latino American, and African American members remained 23%, 55%, and 62% less likely to register, respectively, than non-Hispanic white members. Preference for Spanish as a written language predicted poor PHR adoption. The probability of registration was 0.451 (95% CI, 0.449-0.453) for English language-preferring Latinos and 0.174 (95% CI, 0.173-0.176) for Spanish language-preferring Latinos. For non- Hispanic whites, Latinos, and African Americans using the PHR, HEDIS scores increased after PHR use by 1.3 to 12.7 percentage points, compared with differences of -1.1 to 8.1 percentage points among nonusers. All but 2 difference-in-differences between PHR users and nonusers were statistically significant. CONCLUSIONS: Nonwhite race/ethnicity and Spanish language preference independently predict poor PHR adoption. PHR use is associated with higher quality healthcare, and when PHR use is equivalent across racial/ethnic groups, so is quality of care.

Nurses' use of an integrated electronic health record: results of a case site analysis.

PURPOSE: To explore how nurses use an integrated Electronic Health Record (EHR) in practice. METHODS: A multi-site case study across two hospitals in Kaiser Permanente Northern California. Non-participant observation was used to explore nurses' use of the EHR, while semi-structured interviews with nurses and managers explored their perceptions of the EHR and how it affected their practice. Data were analyzed thematically using codes derived deductively from the literature and inductively from the data. RESULTS: Key themes arising from the analysis suggest that the EHR changed various elements of the way nurses practiced. Introducing the EHR was thought to have improved communication, ease of access to information and the safety of medication administration processes. At an organizational level, there was variability in how the EHR was used to support care documentation and initiatives to improve the quality of care provided by nurses. CONCLUSION: The EHR was perceived to improve efficiency, safety and communication by the majority of nurses who were interviewed. However, it is likely that a number of other factors such as individual nurse's characteristics and organizational culture influence how an EHR can be used effectively to improve outcomes for patients.

Effects of proactive population-based nephrologist oversight on progression of chronic kidney disease: a retrospective control analysis.

BACKGROUND: Benefits of early nephrology care are well-established, but as many as 40% of U.S. patients with end-stage renal disease (ESRD) do not see a nephrologist before its onset. Our objective was to evaluate the effect of proactive, population-based nephrologist oversight (PPNO) on chronic kidney disease (CKD) progression. METHODS: Retrospective control analysis of Kaiser Permanente Hawaii members with CKD using propensity score matching methods. We matched 2,938 control and case pairs of individuals with stage 3a CKD for the pre-PPNO period (2001-2004) and post-PPNO period (2005-2008) that were similar in other characteristics: age, gender, and the presence of diabetes and hypertension. After three years, we classified the stage outcomes for all individuals. We assessed the PPNO effect across all stages of progression with a χ2-test. We used the z-score test to assess the proportional differences in progression within a stage. RESULTS: The progression within the post-PPNO period was less severe and significantly different from the pre-PPNO period (p = 0.027). Within the stages, there were 2.6% more individuals remaining in 3a in the post-period (95% confidence interval [CI], 1.5% to 3.8%; P value < 0.00001). Progression from 3a to 3b was 2.2% less in the post-period (95% [CI], 0.7% to 3.6%; P value = 0.0017), 3a to 4/5 was 0.2% less (95% CI, 0.0% to 0.87%; P value = 0.26), and 3a to ESRD was 0.24% less (95% CI, 0.0% to 0.66%, P value = 0.10). CONCLUSIONS: Proactive, population-based nephrologist oversight was associated with a statistically significant decrease in progression. With enabling health information technology, risk stratification and targeted intervention by collaborative primary and specialty care achieves population-level care improvements. This model may be applicable to other chronic conditions.

Association between personal health record enrollment and patient loyalty.

OBJECTIVES: To examine the association between patient loyalty, as measured by member retention in the health plan, and access to My Health Manager (MHM), Kaiser Permanente's PHR, which is linked to its electronic health record, KP HealthConnect. DESIGN: We conducted a retrospective cohort observational quality improvement project from the third quarter of 2005 to the fourth quarter of 2008 for approximately 394,000 Kaiser Permanente Northwest members. METHODS: To control for self-selection bias, we used propensity scores to perform exact 1-to-1 matching without replacement between MHM users and nonusers. We estimated retention rates of the matched data and assessed the association between MHM use and retention versus voluntary termination. We also estimated odds ratios of significant variables impacting member retention. RESULTS: The probability of remaining a member or being involuntarily terminated versus voluntary termination was 96.7% for users (95% confidence interval [CI], 96.6%-96.7%) and 92.2% for nonusers (95% CI, 92.1%-92.4%; P <.001). In the logistic model, MHM use was a significant predictor; only tenure and illness burden were stronger predictors. Users were 2.578 (95% CI, 2.487%-2.671%) times more likely to choose to remain members than were nonusers. The impact was more substantial among newer members. CONCLUSIONS: MHM use was significantly associated with voluntary membership retention. An indicator of patient loyalty, retention is critical to healthcare organizations.

The impact of an electronic health record on nurse sensitive patient outcomes: an interrupted time series analysis.

OBJECTIVES: To evaluate the impact of electronic health record (EHR) implementation on nursing care processes and outcomes. DESIGN: Interrupted time series analysis, 2003-2009. SETTING: A large US not-for-profit integrated health care organization. PARTICIPANTS: 29 hospitals in Northern and Southern California. INTERVENTION: An integrated EHR including computerized physician order entry, nursing documentation, risk assessment tools, and documentation tools. MAIN OUTCOME MEASURES: Percentage of patients with completed risk assessments for hospital acquired pressure ulcers (HAPUs) and falls (process measures) and rates of HAPU and falls (outcome measures). RESULTS: EHR implementation was significantly associated with an increase in documentation rates for HAPU risk (coefficient 2.21, 95% CI 0.67 to 3.75); the increase for fall risk was not statistically significant (0.36; -3.58 to 4.30). EHR implementation was associated with a 13% decrease in HAPU rates (coefficient -0.76, 95% CI -1.37 to -0.16) but no decrease in fall rates (-0.091; -0.29 to 0.11). Irrespective of EHR implementation, HAPU rates decreased significantly over time (-0.16; -0.20 to -0.13), while fall rates did not (0.0052; -0.01 to 0.02). Hospital region was a significant predictor of variation for both HAPU (0.72; 0.30 to 1.14) and fall rates (0.57; 0.41 to 0.72). CONCLUSIONS: The introduction of an integrated EHR was associated with a reduction in the number of HAPUs but not in patient fall rates. Other factors, such as changes over time and hospital region, were also associated with variation in outcomes. The findings suggest that EHR impact on nursing care processes and outcomes is dependent on a number of factors that should be further explored.

Detecting bimodality in plant size distributions and its significance for stand development and competition.

Bimodal distributions in plant size, with a major mode of small and minor mode of large-size plants, have been reported for a range of single species stands in different growing conditions. The occurrence of bimodality has implications for the dynamics of competition within a stand and potentially for stand productivity. However, deduction of the existence of bimodality has been by visual assessment of histograms of a single measure of plant size which can lead to differences of opinion about its existence. We show that the bivariate distribution of plant height and weight is more informative about stand structure than univariate distributions. We demonstrate how sub-populations of small- and large-size plants can be identified using a bivariate mixture distribution fitted using evolutionary computation. For the multiple datasets we analyse, a bimodal distribution fits in preference to unimodal or trimodal distributions. Small- and large-plant sub-populations, respectively, form a lower and upper canopy. The numbers of plants in these canopies change during stand development and vary with initial spacing, contrary to reports for other species. Early in stand development, large plants show spatial separation between themselves but spatial association with small plants, and as stands develop the number of large plants declines markedly but they remain spatially separated between each other. Bivariate analysis of height and weight, and spatial analysis of individuals of different sizes, provides a more comprehensive description of stand structure than that obtained in previous studies.

Use of electronic health records can improve the health care industry's environmental footprint.

Electronic health records have the potential to improve the environmental footprint of the health care industry. We estimate that Kaiser Permanente's electronic health record system, which covers 8.7 million beneficiaries, eliminated 1,000 tons of paper records and 68 tons of x-ray film, and that it has lowered gasoline consumption among patients who otherwise would have made trips to the doctor by at least three million gallons per year. However, the use of personal computers resulted in higher energy consumption and generated an additional 250 tons of waste. We conclude that electronic health records have a positive net effect on the environment, and that our model for evaluating their impact can be used to determine whether their use can improve communities' health.

Improving population care with an integrated electronic panel support tool.

This study measured the impact of an electronic Panel Support Tool (PST) on primary care teams' performance on preventive, monitoring, and therapeutic evidence-based recommendations. The PST, tightly integrated with a comprehensive electronic health record, is a dynamic report that identifies gaps in 32 evidence-based care recommendations for individual patients, groups of patients selected by a provider, or all patients on a primary care provider's panel. It combines point-of-care recommendations, disease registry capabilities, and continuous performance feedback for providers. A serial cross-sectional study of the PST's impact on care performance was conducted, retrospectively using monthly summary data for 207 teams caring for 263,509 adult members in Kaiser Permanente's Northwest region. Baseline care performance was assessed 3 months before first PST use and at 4-month intervals over 20 months of follow-up. The main outcome measure was a monthly care performance percentage for each provider, calculated as the number of selected care recommendations that were completed for all patients divided by the number of clinical indications for care recommendations among them. Statistical analysis was performed using the t test and multiple regression. Average baseline care performance on the 13 measures was 72.9% (95% confidence interval [CI], 71.8%-74.0%). During the first 12 months of tool use, performance improved to a statistically significant degree every 4 months. After 20 months of follow-up, it increased to an average of 80.0% (95% CI, 79.3%-80.7%).