Policy Spotlight Effect In Critical Time-Sensitive Diseases

Background: Categorization of hospital emergency capability (CHEC) is a policy implemented worldwide to regionalize critical emergent care. The CHEC policy mainly uses time-based indicators as emergency care quality measurements. Objectives: We aimed to explore the CHEC policy spotlight effect on critical time-sensitive diseases with and without the inuence of time-based surveillance indicators and guidelines. Research Design: We conducted a nationwide retrospective cohort study between 2005–2011. Regarding critical time-sensitive diseases, our study targeted acute ischemic stroke (AIS), ST-segment elevation myocardial infarction (STEMI), septic shock, and major trauma. We selected diagnosis and treatment guideline adherence as process quality measures and dened medical utilization, upward transfer rate, and short-term mortality rate as outcome indicators. Subjects: The Taiwan National Health Insurance 2005 Longitudinal Health Insurance Database contains one million random cases, including medical records and hospital information. Results: During this 7-year study AIS, STEMI, septic shock, and major trauma, respectively. AIS and STEMI cohorts had signicantly higher rates of guideline adherence and better process quality than those of septic shock and major trauma cohorts. Furthermore, AIS and STEMI cohorts had a signicant increase in diagnosis costs. Conclusion: The CHEC policy spotlight effect exists in critical time-sensitive diseases with time-based quality indicators. Importantly, disease entities without these indicators may experience decreases in diagnosis and treatment guideline adherence, indirectly jeopardizing their outcomes. the contribution of each predictor to the overall explanatory power of the model conducting a subgroup analysis for each stratum of sex, age group, income, living area, occupation, CCI score, and emergency medical resource area using the multivariate logistic regression model without stratication and with one dichotomous independent variable, i.e. whether denite diagnosis and treatment were implemented. Adjusted odds ratios (aOR) with 95% condence intervals (CI) were obtained using a logistic regression analysis adjusted for risk factors. All analyses were performed using Statistical Analysis Software version 9.4 (SAS Institute Inc., Cary, NC, USA). A p-value <0.05 was considered statistically signicant. the best our knowledge, this was the rst nationwide retrospective cohort study using data on different critical time-sensitive diseases and following the QUERI framework [11] to explore emergency care providers’ behaviors under time constraints and how they interacted with strict time-based quality surveillance indicators and GWTG adherence. Our study explored a new paradigm in emergency care provider’s behavior research. Our ndings applied the concept of Hawthorne’s effect to the policy spotlight effect and its unintended consequences.


Introduction
remaining critical time-sensitive diseases. The proportion of male patients was signi cantly higher than that of female patients in all cohorts (supplementary table 1). Major trauma cases had a biphasic age distribution in which the age groups ≥ 65 years and ≤ 39 years were the most representative and had signi cantly lower CCI scores than the remaining age groups. The proportion of manual workers was higher than that of other occupations in all cohorts.
Nearly 80% of critical time-sensitive diseases were treated at hospitals categorized as moderate or severe levels. Approximately 20% of patients resided in a region with insu cient emergency care resources.

Principal ndings
We observed the CHEC policy implementation impact on the quality of diagnoses, treatments, and short-term mortality outcomes of critical time-sensitive diseases from several perspectives. (1) The proportion of patients with acute ischemic stroke who received diagnostic brain structural imaging examination, intravenous thrombolytic treatment (intravenous tissue plasminogen activator, IV-tPA), antiplatelet drugs usage, diagnosis cost and total cost increased signi cantly after policy implementation (supplementary tables 3 and 4). Conversely, upward transfer and 30-day mortality rates remained unchanged. (2) The proportion of patients with STEMI as well as the rate of electrocardiography (EKG), percutaneous coronary intervention (PCI), antiplatelet drugs usage and diagnosis cost increased signi cantly after policy implementation (supplementary tables 5 and 6). Furthermore, the 7-day and 30-day mortality rate decreased signi cantly after CHEC policy implementation and the upward transfer rate showed a downward trend. Conversely, IV-tPA increase signi cantly. (3) The proportions of patients with septic shock who diagnosis using bacterial cultures, antipathogen drug administration, diagnosis cost and total cost did not change signi cantly after policy implementation (supplementary tables 7 and 8). Conversely, the use of lactic acid tests increased while the use of central venous catheters decreased after CHEC policy implementation. The 30-day mortality rate was signi cantly higher during the trial period than before the policy was implemented. Though not statistically signi cant, the upward transfer rate decreased after policy implementation. (4) Among major trauma cohort, we also observed a non-signi cant decrease in total cost, upward transfer, rescue surgery and short-term mortality rates, after treatment policy implementation (supplementary tables 9 and 10). Furthermore, the diagnosis cost decreased signi cantly after policy mplementation.

Sensitivity analysis
In order to test the length of stay effect over diagnosis, treatment and outcome characteristics of time-sensitive disease. We adjusted length of stay in acute ischemic stroke cohort. The diagnosis, treatment and outcome of acute stroke patients did not differ signi cantly pre-and post-intervention (supplementary   table 15).

Methodology and principal ndings
Our ndings indicated that the implementation of CHEC policy resulted in improved treatment guideline adherence rates and process quality for both acute ischemic stroke and STEMI cohorts. In contrast, the lack of surveillance indicators for septic shock and major trauma may have resulted in a decrease in process quality, indirectly worsening the septic shock short-term mortality rate. Furthermore, all disease cohorts signi cantly increased their diagnosis-related costs without signi cant bene ts to short-term mortality outcomes (Table 5).

Limitations
Because the study data were retrieved from a secondary dataset of insurance claims not a randomized controlled trial, this study has the following limitations: (1) our analysis lacked detailed information on time-related quality indicators, such as door-to-evaluation and door-to-treatment times; (2) we only assessed short-term CHEC policy effects, which may not re ect its long-term impact on emergency care quality, to prevent the interference of other emergency care policies; (3) we need more qualitative research to elucidate the psychological mechanisms through which the policy spotlight effect in uences emergency care providers' behaviour; and (4) future qualitative research studies should focus on the well-being of emergency care providers to compensate for quantitative research inadequacies.
In conclusion, our study used real-world evidence to demonstrate that CHEC policy implementation generated a policy spotlight effect resulting in a disproportional improvement in disease guideline adherence rates and process quality of critical time-sensitive diseases with time-based surveillance indicators. In contrast, disease entities not fully encompassed in the surveillance may be jeopardized with a decrease in diagnosis and treatment processes, indirectly worsening the quality of outcomes. This study approved by Institutional Review Board of National Yang-Ming University-YM107035E on May, 5 2018. In accordance with regulations of the National Health Research Institutes, patient identi cation information was anonymized, such that informed consent was not required.

Availability of Data and Materials
The data that support the ndings of this study are available from the Taiwan National Health Insurance Research Database, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Data are however available from the authors upon academic request and with permission of the Taiwan National Health Insurance Administration.

Competing Interests
The authors declare that they have no competing interests.