Should management of pneumonia be an indicator of quality of care?

Incentivizing performance in health care: a rapid review, typology and qualitative study of unintended consequences

BACKGROUND

Health systems are increasingly implementing policy-driven programs to incentivize performance using contracts, scorecards, rankings, rewards, and penalties. Studies of these "Performance Management" (PM) programs have identified unintended negative consequences. However, no single comprehensive typology of the negative and positive unintended consequences of PM in healthcare exists and most studies of unintended consequences were conducted in England or the United States. The aims of this study were: (1) To develop a comprehensive typology of unintended consequences of PM in healthcare, and (2) To describe multiple stakeholder perspectives of the unintended consequences of PM in cancer and renal care in Ontario, Canada.

METHODS

We conducted a rapid review of unintended consequences of PM in healthcare (n = 41 papers) to develop a typology of unintended consequences. We then conducted a secondary analysis of data from a qualitative study involving semi-structured interviews with 147 participants involved with or impacted by a PM system used to oversee 40 care delivery networks in Ontario, Canada. Participants included administrators and clinical leads from the networks and the government agency managing the PM system. We undertook a hybrid inductive and deductive coding approach using the typology we developed from the rapid review.

RESULTS

We present a comprehensive typology of 48 negative and positive unintended consequences of PM in healthcare, including five novel unintended consequences not previously identified or well-described in the literature. The typology is organized into two broad categories: unintended consequences on (1) organizations and providers and on (2) patients and patient care. The most common unintended consequences of PM identified in the literature were measure fixation, tunnel vision, and misrepresentation or gaming, while those most prominent in the qualitative data were administrative burden, insensitivity, reduced morale, and systemic dysfunction. We also found that unintended consequences of PM are often mutually reinforcing.

CONCLUSIONS

Our comprehensive typology provides a common language for discourse on unintended consequences and supports systematic, comparable analyses of unintended consequences across PM regimes and healthcare systems. Healthcare policymakers and managers can use the results of this study to inform the (re-)design and implementation of evidence-informed PM programs.

Effect of β-Lactam Plus Macrolide Versus Fluoroquinolone on 30-Day Readmissions for Community-Acquired Pneumonia

BACKGROUND

Antibiotic therapy with a macrolide and β-lactam or a fluoroquinolone for the empirical treatment of community-acquired pneumonia (CAP) in an inpatient non-intensive care setting is recommended per guidelines. Studies show that these treatments have similar outcomes, including death, adverse effects, and bacterial eradication. However, a comparison of 30-day readmission rates between these treatments is limited.

STUDY QUESTION

To determine whether 30-day readmissions for patients treated for CAP in a regional hospital differed between a fluoroquinolone monotherapy and a β-lactam plus macrolide combination therapy.

STUDY DESIGN

Retrospective cohort study of patients aged ≥18 years with a CAP diagnosis who were admitted to the same regional hospital from December 1, 2011, through December 1, 2016.

MEASURES AND OUTCOMES

Patients receiving a third-generation cephalosporin plus macrolide were compared with those receiving a respiratory fluoroquinolone. Exclusion criteria were concurrent or recent use of the study antibiotics; death, transfer, or transition to hospice; and diagnosis of hospital-acquired pneumonia or health care-associated pneumonia. The collected data were 30-day readmission rates, antibiotic regimens, demographic characteristics, and pneumonia severity index and comorbidity scores. Association between treatment group and readmissions was assessed with logistic regression. Association between readmissions and individual data points between the 2 treatment groups was calculated with multivariate regression and odds ratio (95% confidence interval).

RESULTS

Of 432 patients, 171 met inclusion criteria (fluoroquinolone group, n = 101; β-lactam plus macrolide group, n = 70). Thirty-day readmissions were not significantly different between the fluoroquinolone group and β-lactam plus macrolide group (P = 0.58). Increased 30-day readmissions were independently associated with male sex and hospital length of stay (P < 0.05). Length of stay was approximately 3 days and did not differ between treatment groups.

CONCLUSIONS

No difference was seen in 30-day readmissions between CAP patients who received fluoroquinolone monotherapy and those who received β-lactam plus macrolide combination therapy.

Impact of the Joint Commission Pneumonia Core Measure on Antibiotic Use and Selection for Community-Acquired Pneumonia in the Emergency Room

Background

Prior to 2012, The Joint Commission (TJC) pneumonia core measure (PN-5) required antibiotic administration for suspected community-acquired pneumonia (CAP) within 6 hours of arrival to the emergency room (ER). In 2012, TJC issued PN-6 requiring antibiotic administration within 24 hours of presentation. Though PN-6 was anticipated to reduce overuse and inappropriate antibiotic use and improve appropriate antibiotic selection, the impact of PN-5 and PN-6 on optimizing care for CAP in the ER remains unknown.

Objective

To investigate the impact of TJC pneumonia core measures on antibiotic use in the ER for suspected CAP.

Methods

In this single-center study, medical records of patients 18 years old and older diagnosed with CAP in the ER during 2011 (PN-5) and 2012 (PN-6) and admitted for 1 day or longer were reviewed. Exclusion criteria included criteria for health care–associated pneumonia. Comparisons between groups were performed using descriptive statistics and contingency table analysis with chi-square or Fisher exact tests for categorical variables and t tests for continuous variables. Statistical analyses were performed using Microsoft Excel 2010 and SAS version 9.4.

Results

Antibiotic use was comparable between PN-5 and PN-6. Approximately half of patients in each group received an appropriate empiric CAP regimen (52% vs 54%; P = .807). Among inappropriate regimens, the most common reason was use of a beta-lactam alone (69% vs 83%; P = .26). More patients had an ultimate diagnosis of CAP with PN-6 (78% vs 86%; P = .3).

Conclusion

Changes in pneumonia core measure requirements did not have a significant impact on appropriate antibiotic use in the ER.

Readmission following hospitalization for pneumonia: the impact of pneumonia type and its implication for hospitals

BACKGROUND

Readmission rates following discharge after pneumonia are thought to represent the quality of care. Factors associated with readmission, however, remain poorly described. It is unclear if readmission rates vary based on pneumonia type.

METHODS

We retrospectively identified adults admitted to an index hospital with non-nosocomial pneumonia (January through December 2010) and who survived to discharge. We only included patients with bacterial evidence of infection. Readmission in the 30 days following discharge to any of 9 hospitals comprising the index hospital's healthcare system served as the primary end point. We recorded demographics, severity of illness, comorbidities, and infection-related factors. We noted whether the patient had healthcare-associated pneumonia (HCAP) versus community-acquired pneumonia. We utilized logistic regression analysis to determine factors independently associated with readmission.

RESULTS

The cohort included 977 subjects; 78.9% survived to discharge. The readmission rate equaled 20%. Neither disease severity nor the rate of initially inappropriate antibiotic therapy correlated with readmission. Subjects with HCAP were 7.5 (95% confidence interval [CI], 3.6-15.7) times more likely to be readmitted. Four HCAP criteria were independently associated with readmission: admission from long-term care (adjusted odds ratio [AOR], 2.2 [95% CI, 1.4-3.4]); immunosuppression (AOR, 1.9 [95% CI, 1.3-2.9]); prior antibiotics (AOR, 1.7 [95% CI, 1.2-2.6]); and prior hospitalization (AOR, 1.7 [95% CI, 1.1-2.5]).

CONCLUSIONS

Readmission for pneumonia is common but varies based on pneumonia type. The variables associated with readmission do not reflect factors that hospitals directly control. Use of one rule to guide payment that fails to account for HCAP and the HCAP criteria on readmission seems inappropriate.