The Impact of the Change in Payment System for German Psychiatric Clinics on Treatment Success: An Interrupted Time Series Analysis

2019 ◽  
Vol 82 (06) ◽  
pp. 559-567
Author(s):  
Christina Niedermeier ◽  
Andrea Barrera ◽  
Eva Esteban ◽  
Ivana Ivandic ◽  
Carla Sabariego
Keyword(s):  
Time Series ◽  
Negative Impact ◽  
Treatment Success ◽  
Interrupted Time Series ◽  
Sensitivity Analyses ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
Intervention Point ◽  
The Impact ◽  
New System

Abstract Background In Germany a new reimbursement system for psychiatric clinics was proposed in 2009 based on the § 17d KHG Psych-Entgeltsystem. The system can be voluntary implemented by clinics since 2013 but therapists are frequently afraid it might affect treatment negatively. Objectives To evaluate whether the new system has a negative impact on treatment success by analysing routinely collected data in a Bavarian clinic. Material and methods Aggregated data of 1760 patients treated in the years 2007–2016 was analysed with segmented regression analysis of interrupted time series to assess the effects of the system on treatment success, operationalized with three outcome variables. A negative change in level after a lag period was hypothesized. The robustness of results was tested by sensitivity analyses. Results The percentage of patients with treatment success tends to increase after the new system but no significant change in level was observed. The sensitivity analyses corroborate results for 2 outcomes but when the intervention point was shifted, the positive change in level for the third outcome became significant. Conclusions Our initial hypothesis is not supported. However, the sensitivity analyses disclosed uncertainties and our study has limitations, such as a short observation time post intervention. Results are not generalizable as data of a single clinic was analysed. Nevertheless, we show the importance of collecting and analysing routine data to assess the impact of policy changes on patient outcomes.

scholarly journals The impact of China’s lockdown policy on the incidence of CoVID-19: An Interrupted time series analysis

2020 ◽  
Author(s):  
Mooketsi Molefi ◽  
John Tlhakanelo ◽  
Thabo Phologolo ◽  
Shimeles G. Hamda ◽  
Tiny Masupe ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Effective Means ◽  
Interrupted Time Series ◽  
Ordinary Least Squares ◽  
World Health ◽  
Least Squares Regression ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
The Impact

Abstract BackgroundPolicy changes are often necessary to contain the detrimental impact of epidemics such as the coronavirus disease (COVID-19). China imposed strict restrictions on movement on January 23rd, 2020.Interrupted time series methods were used to study the impact of the lockdown on the incidence of COVID-19. MethodsThe number of cases of COVID-19 reported daily from January 12thto March 30th, 2020 were extracted from the World Health Organization (WHO) COVID-19 dashboard ArcGIS® and matched to China’s projected population of 1 408 526 449 for 2020 in order to estimate daily incidences. Data were plotted to reflect daily incidences as data points in the series. A deferred interruption point of 6thFebruary was used to allow a 14-day period of diffusion. The magnitude of change and linear trend analyses were evaluated using the itsafunction with ordinary least-squares regression coefficients in Stata® yielding Newey-West standard errors.ResultsSeventy-eight (78) daily incidence points were used for the analysis, with 11(14.10%) before the intervention. There was a daily increase of 163 cases (β=1.16*10-07, p=0.00) in the pre-intervention period. Although there was no statistically significant drop in the number of cases reported daily in the immediate period following 6thFebruary 2020 when compared to the counterfactual (p=0.832), there was a 241 decrease (β=-1.71*10-07, p=0.00) in cases reported daily when comparing the pre-intervention and post-intervention periods. A deceleration of 78(47%) cases reported daily. ConclusionThe lockdown policy managed to significantly decrease the incidence of CoVID-19 in China. Lockdown provides an effective means of curtailing the incidence of COVID-19.

scholarly journals LB-16. Association Between Universal Face Shield in a Quaternary Care Center and Reduction of SARS-COV2 Infections Among Healthcare Personnel and Hospitalized Patients

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S851-S851
Author(s):  
Vagesh Hemmige ◽  
Becky Winterer ◽  
Todd Lasco ◽  
Bradley Lembcke
Keyword(s):  
Time Series ◽  
Care Center ◽  
Interrupted Time Series ◽  
Hospitalized Patients ◽  
Healthcare Personnel ◽  
Segmented Regression ◽  
Intervention Period ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
The Impact

Abstract Background SARS-COV2 transmission to healthcare personnel (HCP) and hospitalized patients is a significant challenge. Our hospital is a quaternary healthcare system with more than 500 beds and 8,000 HCP. Between April 1 and April 17, 2020, we instituted several infection prevention strategies to limit transmission of SARS-COV2 including universal masking of HCP and patients, surveillance testing every two weeks for high-risk HCP and every week for cluster units, and surveillance testing for all patients on admission and prior to invasive procedures. On July 6, 2020, we implemented universal face shield for all healthcare personnel upon entry to facility. The aim of this study is to assess the impact of face shield policy on SARS-COV2 infection among HCP and hospitalized patients. Figure 1- Interrupted time series Methods The preintervention period (April 17, 2020-July 5, 2020) included implementation of universal face masks and surveillance testing of HCP and patients. The intervention period (July 6, 2020-July 26, 2020) included the addition of face shield to all HCP (for patient encounters and staff-to-staff encounters). We used interrupted time series analysis with segmented regression to examine the effect of our intervention on the difference in proportion of HCP positive for SARS-COV2 (using logistic regression) and HAI (using Poisson regression). We defined significance as p values < 0.05. Results Of 4731 HCP tested, 192 tested positive for SARS-COV2 (4.1%). In the preintervention period, the weekly positivity rate among HCP increased from 0% to 12.9%. During the intervention period, the weekly positivity rate among HCP decreased to 2.3%, with segmented regression showing a change in predicted proportion positive in week 13 (18.0% to 3.7%, p< 0.001) and change in the post-intervention slope on the log odds scale (p< 0.001). A total of 14 HAI cases were identified. In the preintervention period, HAI cases increased from 0 to 5. During the intervention period, HAI cases decreased to 0. There was a change between pre-intervention and post-intervention slope on the log scale was significant (p< 0.01). Conclusion Our study showed that the universal use of face shield was associated with significant reduction in SARS-COV2 infection among HCP and hospitalized patients. Disclosures All Authors: No reported disclosures

scholarly journals Assessing the impact of SIGN 136 on opioid prescribing rates in Scotland: An interrupted time series analysis

2021 ◽  
Author(s):  
Harry L. Hébert ◽  
Daniel R. Morales ◽  
Nicola Torrance ◽  
Blair H. Smith ◽  
Lesley A. Colvin
Keyword(s):  
Chronic Pain ◽  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Relative Reduction ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
Opioid Prescribing ◽  
Prescribing Trends ◽  
The Impact

AbstractBackgroundOpioids are used to treat patients with chronic pain, but their long-term use is associated with harms. In December 2013, SIGN 136 was published, providing a comprehensive evidence-based guideline for the assessment and management of chronic pain in ScotlandAimsThis study aimed to examine the impact of SIGN 136 on opioid prescribing trends and costs across the whole of Scotland.MethodsOpioid prescribing data and average cost per item were obtained from Public Health Scotland. An interrupted time series analysis examined the effects of SIGN 136 publication on the number of items prescribed per 1,000 population per quarter for 29 opioids (or opioid-containing combinations) from 2005 to 2019 inclusive. Exploratory analysis was conducted in NHS Tayside and NHS Fife combined and then up-scaled to all 14 NHS Scotland health boards. A similar approach was also used to assess the effect of SIGN 136 on estimated gross ingredient costs per quarter.ResultsAt six years post-intervention there was a relative reduction in opioid prescribing of 18.8% (95% CI: 16.0-21.7) across Scotland. There was also a relative reduction of 22.8% (95%: 14.9-30.1) in gross ingredient cost nationally. Opioid prescribing increased significantly pre-intervention across all 14 NHS Scotland health boards (2.19 items per 1000 population per quarter), followed by a non-significant change in level and a significant negative change in trend post-intervention (−2.69 items per 1000 population per quarter). Similar findings were observed locally in NHS Tayside and NHS Fife.ConclusionsThe publication of SIGN 136 coincided with a statistically significant reduction in opioid prescribing rates in Scotland and suggests that changes in clinical policy are having a positive effect on prescribing practices in primary care. These prescribing trends appear to be in contrast to the UK as a whole.

Time Series Analysis as an Impact Analysis Method

2017 ◽  
Author(s):  
Youseop Shin
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Impact Analysis ◽  
Interrupted Time Series ◽  
Public Law ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Intervention Point ◽  
Three Strikes ◽  
The Impact

Chapter Seven explains interrupted time series analysis. This chapter includes the impact analysis of the Three-Strikes-Out law with October 1994 (when Public Law 103-322 was enacted) as the intervention point.

scholarly journals The impact of stringent prescription-only antimicrobial sale regulation (Schedule H1) in India: an interrupted time series analysis, 2008–18

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Habib Hasan Farooqui ◽  
Sakthivel Selvaraj ◽  
Aashna Mehta ◽  
Manu Raj Mathur
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Private Sector ◽  
Positive Impact ◽  
Interrupted Time Series ◽  
Control Group ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
Series Analysis ◽  
The Impact

Abstract Objectives To assess the impact of Schedule H1 regulation notified and implemented in 2014 under the amended rules of the Drugs and Cosmetics Act (DCA), 1940 on the sale of antimicrobials in the private sector in India. Methods The dataset was obtained from the Indian pharmaceutical sales database, PharmaTrac. The outcome measure was the sales volume of antimicrobials in standard units (SUs). A quasi-experimental research design—interrupted time series analysis—was used to detect the impact of the intervention. Results We observed a substantial rise in antimicrobial consumption during 2008–18 in the private sector in India, both for antimicrobials regulated under Schedule H1 as well as outside the regulation. Key results suggested that post-intervention there was an immediate reduction (level change) in use of Schedule H1 antimicrobials by 10% (P = 0.007), followed by a sustained decline (trend change) in utilization by 9% (P > 0.000) compared with the pre-intervention trend. Segregated analysis on different antimicrobial classes suggests a sharp drop (level changes) and sustained decline (trend changes) in utilization post-intervention compared with the pre-intervention trend. Our findings remained robust on carrying out sensitivity analysis with the oral anti-diabetics market as a control. Post-intervention, the average monthly difference between antimicrobials under Schedule H1 and the control group witnessed an immediate increase of 16.3% (P = 0.10) followed by a sustained reduction of 0.5% (P = 0.13) compared with the pre-intervention scenario. Conclusions Though the regulation had a positive impact in terms of reducing sales of antimicrobials notified under the regulation, optimizing the effectiveness of such stand-alone policies will be limited unless accompanied by a broader set of interventions.

scholarly journals Impact of the 2016 Policy Change on the Delivery of MedsCheck Services in Ontario: An Interrupted Time-Series Analysis

Pharmacy ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 115
Author(s):  
Shakeri ◽  
Dolovich ◽  
MacCallum ◽  
Gamble ◽  
Zhou ◽  
...  
Keyword(s):  
Time Series ◽  
Policy Change ◽  
Community Pharmacists ◽  
Professional Community ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Post Intervention ◽  
Term Care ◽  
The Government ◽  
The Impact

MedsCheck (MC) is an annual medication review service delivered by community pharmacists and funded by the government of Ontario since 2007 for residents taking three or more medications for chronic conditions. In 2010, MC was expanded to include patients with diabetes (MCD), home-bound patients (MCH), and residents of long-term care homes (MCLTC). The Ontario government introduced an abrupt policy change effective 1 October 2016 that added several components to all MC services, especially those completed in the community. We used an interrupted time series design to examine the impact of the policy change (24 months pre- and post-intervention) on the monthly number of MedsCheck services delivered. Immediate declines in all services were identified, especially in the community (47%–64% drop MC, 71%–83% drop MCD, 55% drop MCH, and 9%–14% drop MCLTC). Gradual increases were seen over 24 months post-policy change, yet remained 21%–76% lower than predicted for MedsCheck services delivered in the community, especially for MCD. In contrast, MCLTC services were similar or exceeded predicted values by September 2018 (from 5.1% decrease to 3.5% increase). A more effective implementation of health policy changes is needed to ensure the feasibility and sustainability of professional community pharmacy services.

scholarly journals Does admission prevalence change after reconfiguration of inpatient services? An interrupted time series analysis of the impact of reconfiguration in five centres

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Joanne Martin ◽  
Edwin Amalraj Raja ◽  
Steve Turner
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Emergency Admission ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Emergency Admissions ◽  
Series Analysis ◽  
Inpatient Services ◽  
The Impact ◽  
Admission Prevalence

Abstract Background Service reconfiguration of inpatient services in a hospital includes complete and partial closure of all emergency inpatient facilities. The “natural experiment” of service reconfiguration may give insight into drivers for emergency admissions to hospital. This study addressed the question does the prevalence of emergency admission to hospital for children change after reconfiguration of inpatient services? Methods There were five service reconfigurations in Scottish hospitals between 2004 and 2018 where emergency admissions to one “reconfigured” hospital were halted (permanently or temporarily) and directed to a second “adjacent” hospital. The number of emergency admissions (standardised to /1000 children in the regional population) per month to the “reconfigured” and “adjacent” hospitals was obtained for five years prior to reconfiguration and up to five years afterwards. An interrupted time series analysis considered the association between reconfiguration and admissions across pairs comprised of “reconfigured” and “adjacent” hospitals, with adjustment for seasonality and an overall rising trend in admissions. Results Of the five episodes of reconfiguration, two were immediate closure, two involved closure only to overnight admissions and one with overnight closure for a period and then closure. In “reconfigured” hospitals there was an average fall of 117 admissions/month [95% CI 78, 156] in the year after reconfiguration compared to the year before, and in “adjacent” hospitals admissions rose by 82/month [32, 131]. Across paired reconfigured and adjacent hospitals, in the months post reconfiguration, the overall number of admissions to one hospital pair slowed, in another pair admissions accelerated, and admission prevalence was unchanged in three pairs. After reconfiguration in one hospital, there was a rise in admissions to a third hospital which was closer than the named “adjacent” hospital. Conclusions There are diverse outcomes for the number of emergency admissions post reconfiguration of inpatient facilities. Factors including resources placed in the community after local reconfiguration, distance to the “adjacent” hospital and local deprivation may be important drivers for admission pathways after reconfiguration. Policy makers considering reconfiguration might consider a number of factors which may be important determinants of admissions post reconfiguration.

Recession and risk of suicide in Denmark during the 2009 global financial crisis: an ecological register-based study

2021 ◽  
pp. 140349482110132
Author(s):  
Agnieszka Konieczna ◽  
Sarah Grube Jakobsen ◽  
Christina Petrea Larsen ◽  
Erik Christiansen
Keyword(s):  
Time Series ◽  
Financial Crisis ◽  
Time Series Analysis ◽  
Suicide Rate ◽  
Global Financial Crisis ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Prevention Programmes ◽  
The Impact

Aim: The aim of this study is to analyse the potential impact from the financial crisis (onset in 2009) on suicide rates in Denmark. The hypothesis is that the global financial crisis raised unemployment which leads to raising the suicide rate in Denmark and that the impact is most prominent in men. Method: This study used an ecological study design, including register data from 2001 until 2016 on unemployment, suicide, gender and calendar time which was analysed using Poisson regression models and interrupted time series analysis. Results: The correlation between unemployment and suicide rates was positive in the period and statistically significant for all, but at a moderate level. A dichotomised version of time (calendar year) showed a significant reduction in the suicide rate for women (incidence rate ratio 0.87, P=0.002). Interrupted time series analysis showed a significant decreasing trend for the overall suicide rate and for men in the pre-recession period, which in both cases stagnated after the onset of recession in 2009. The difference between the genders’ suicide rate changed significantly at the onset of recession, as the rate for men increased and the rate for women decreased. Discussion: The Danish social welfare model might have prevented social disintegration and suicide among unemployed, and suicide prevention programmes might have prevented deaths among unemployed and mentally ill individuals. Conclusions: We found some indications for gender-specific differences from the impact of the financial crises on the suicide rate. We recommend that men should be specifically targeted for appropriate prevention programmes during periods of economic downturn.

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