The effect of the Iranian health transformation plan on hospitalization rate: insights from an interrupted time series analysis.
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SUBMITTER: Beiranvand S
PROVIDER: S-EPMC7168862 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
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The effect of the Iranian health transformation plan on hospitalization rate: insights from an interrupted time series analysis.
Beiranvand Siavash S Saki Mandana M Behzadifar Meysam M Bakhtiari Ahad A Behzadifar Masoud M Keshvari Mohammad M Bragazzi Nicola Luigi NL
BMC health services research 20200419 1
<h4>Background</h4>Healthcare policy- and decision-makers make efforts to build and maintain high-performing and effective health systems, implementing effectiveness programs and health reforms. In May 2014, the Iranian Ministry of Health and Medical Education has launched a series of ambitious reforms, known as the Health Transformation Plan (HTP). This study aimed to determine the effect of the HTP on hospitalization rate in Iranian public hospitals affiliated to the Ministry of Health and Med ...[more]
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Project description:BackgroundHealth transformation plan (HTP) implemented in Iran since 2014 to improve accessibility and financial protection of patients. This study aimed to assess the impact of HTP on health spending in Iran.MethodsThis was a quasi-experimental design using Interrupted Time Series. All registered impatient records in Iran health insurance organization (IHIO) for the population of Mazandaran province (1,628,919 population in 2011), north of Iran from March 2010 to February 2019 were included. Data for three depended variables: hospitalization rate, average inpatient cost and inpatient expenditure per capita was extracted in 96 monthly observations. Segmented regression analysis was done in R version 3.6.1.ResultsHospitalization rate in 2010 was 6.6 in 1000 people and its level change was 0/799 immediately after HTP (P < 001). Post-reform level and trend changes for monthly average inpatient cost of registered admissions in IHIO were also significant (P < 001). IHIO inpatient expenditure per capita for 1,628,919 population in Mazandaran province was 24,436 Rials in 2011 and increased significantly immediately following HTP as 34,459 Rials (P < 001).ConclusionsThree important components of health spending including hospitalization rate, average inpatient cost and inpatient expenditure per capita were increased dramatically after HTP. Cost containment strategies and strengthening the preventive care initiatives is required to control the escalating trends of inpatient expenditure in Iran.
| S-EPMC8173793 | biostudies-literature
Project description:OBJECTIVE:Discharge against medical advice (DAMA) is a critical problem in hospitals and has several consequences for healthcare systems. The aim of this study was to determine and compare the rate of DAMA and its related factors before and after executing the healthcare transformation plan (HTP) in Iran. METHODS:In a two-phase, cross-sectional study, the DAMA information of 200 patients in 2016 (after HTP) and the patients of a previous study in 2012 (before HTP) was compared. Samples were randomly selected from the main referral centre in the north-west of Iran. Data were collected using a validated and reliable questionnaire and analysed using the SPSS V.16 software. RESULTS:In the post-HTP plan period, the rate of DAMA was 3.9%, while this rate was 5.49% in 2012 (p=0.029). A total of 15% (108 out of 721) of patients in the postreform group and 13.5% (101 out of 747) in the prereform group were rehospitalised (p=0.411). The three main categories of reasons for DAMA in 2012 and 2016 were as follows: patient-related factors, 27% vs 45%; staff-related factors, 33% vs 30%; and hospital-related factors (basic amenities), 40% vs 25%. In both periods, the average scores of patient satisfaction were almost the same; however, satisfaction regarding environmental and human factors in hospitals had changed significantly after HTP (p<0.05). CONCLUSIONS:There was a decrease in the rate of DAMA after HTP in Iran. Considering DAMA as a multifactorial phenomenon, this might be due to the higher relative satisfaction after HTP, indicating an increase in public confidence in general hospitals.
| S-EPMC6731801 | biostudies-literature
Project description:BackgroundImplementation of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in the U.S. on October 1, 2015 was a significant policy change with the potential to affect established injury morbidity trends. This study used data from a single state to demonstrate 1) the use of a statistical method to estimate the effect of this coding transition on injury hospitalization trends, and 2) interpretation of significant changes in injury trends in the context of the structural and conceptual differences between ICD-9-CM and ICD-10-CM, the new ICD-10-CM-specific coding guidelines, and proposed ICD-10-CM-based framework for reporting of injuries by intent and mechanism. Segmented regression analysis was used for statistical modeling of interrupted time series monthly data to evaluate the effect of the transition to ICD-10-CM on Kentucky hospitalizations' external-cause-of-injury completeness (percentage of records with principal injury diagnoses supplemented with external-cause-of-injury codes), as well as injury hospitalization trends by intent or mechanism, January 2012-December 2017.ResultsThe segmented regression analysis showed an immediate significant drop in external-cause-of-injury completeness during the transition month, but returned to its pre-transition levels in November 2015. There was a significant immediate change in the percentage of injury hospitalizations coded for unintentional (3.34%) and undetermined intent (- 3.39%). There were immediate significant changes in the level of injury hospitalization rates due to poisoning, suffocation, struck by/against, other transportation, unspecified mechanism, and other specified not elsewhere classifiable mechanism. Significant change in slope after the transition (without immediate level change) was identified for assault, firearm, cut/pierce, and motor vehicle traffic injury rates. The observed trend changes reflected structural and conceptual features of ICD-10-CM coding (e.g., poisoning and suffocations are now captured via diagnosis codes only), new coding guidelines (e.g., requiring coding of injury intent as "accidental" if it is unknown or unspecified), and CDC proposed external-cause-of-injury code groupings by injury intent and mechanism. Researchers can replicate this methodology assessing trends in injuries or other ICD-10-CM-coded conditions using administrative billing data sets.ConclusionsThe CDC 's Proposed Framework for Presenting Injury Data Using ICD-10-CM External Cause of Injury Codes provided a logical transition from the ICD-9-CM-based matrix on injury hospitalization trends by intent and mechanism. Our findings are intended to raise awareness that changes in the ICD-10-CM coding system must be understood to assure accurate interpretation of injury trends.
| S-EPMC6165830 | biostudies-literature
Project description:BackgroundHealth systems reform is inevitable due to the never-ending changing nature of societal health needs and policy dynamism. Today, the Health Transformation Plan (HTP) remains the major tool to facilitate the achievements of universal health coverage (UHC) in Iran. It was initially implemented in hospital-based setting and later expanded to primary health care (PHC). This study aimed to analyze the HTP at the PHC level in Iran.MethodsQualitative data were collected through document analysis, round-table discussion, and semi-structured interviews with stakeholders at the micro, meso and macro levels of the health system. A tailored version of Walt & Gilson's policy triangle model incorporating the stages heuristic model was used to guide data analysis.ResultsThe HTP emerged through a political process. Although the initiative aimed to facilitate the achievements of UHC by improving the entire health system of Iran, little attention was given to PHC especially during the first phases of policy development - a gap that occurred because politicians were in a great haste to fulfil a campaign promise.ConclusionsHealth reforms targeting UHC and the health-related Sustainable Development Goals require the political will to improve PHC through engagements of all stakeholders of the health system, plus improved fiscal capacity of the country and financial commitments to implement evidence-informed initiatives.
| S-EPMC6751681 | biostudies-literature
Project description:BackgroundJapan has one of the highest percentages of persons with dementia and hospital deaths in the world. Hospitals are often not equipped to handle the care complexity required for persons with dementia at the end of life. The National Dementia Orange plan aimed to decrease hospital deaths by expanding time in the community.ObjectiveThe aim of this study is to evaluate whether the National Dementia Orange Plan is associated with a decrease in hospitals deaths for persons with dementia.MethodsWe used quarterly, cross-sectional, national death certificate data consisting of the total Japanese dementia population 65 years and older, spanning a period from 2009 to 2016. The primary outcome was quarterly adjusted relative risk rates (aRRR) of dying in hospital, nursing home, home, or elsewhere. An interrupted time series analysis was performed to study the slope change over time. Analyses were adjusted for sex and seasonality.Results149,638 died with dementia. With the implementation of the Orange Plan, death in nursing home (aRRR 1.08, [1.07-1.08], p < 0.001) and elsewhere (aRRR 1.05, [1.05-1.06], p < 0.001) increased over time compared to hospital death. No changes were found in death at home.ConclusionThis study provides evidence that the National Dementia Orange plan was associated with a small increase in death in nursing home and elsewhere. Hospital death remained the primary location of death. End-of-life strategies should be expanded in national dementia policies to increase aging in the community until death.
| S-EPMC8543253 | biostudies-literature
Project description:BackgroundMost private drug plans in Canada do not use a formulary, which leads to suboptimal drug use. We studied the impact of the adoption of the public formulary by a large private health benefits plan in British Columbia.MethodsWe studied the impact of a change by members of the BC Hospital Employees' Union to have their private drug plan mirror the public formulary as of June 2013. With data from Pacific Blue Cross, we conducted a before-and-after descriptive study using interrupted time-series analysis to study changes in covered drug costs and use for 18 months preceding and following the change.ResultsOur cohort averaged 66 000 plan members and dependents over our study period. Following the implementation of the formulary, the number of prescriptions covered by the plan declined by 0.46 prescriptions per member per month (95% confidence interval -0.50 to -0.42), a decline of 23.8% at 1 year. This decreased plan spending by $1.32 million over the 18 months after the coverage change, a 49.7% decline.InterpretationThe adoption of the public formulary by a large private drug plan in BC substantially reduced drug plan expenditures and the volume of prescriptions paid for by the plan. Overall, these results suggest that carefully designed formulary changes could substantially reduce spending by private-sector drug plans on drugs that have more cost-effective therapeutic alternatives.
| S-EPMC6639096 | biostudies-literature
Project description:Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China. We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models. Compared with the expected level, there was an estimated decrease of -22.60% (95% confidence interval (CI): -27.53%, -17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (-62.25%; 95% CI: -65.62%, -58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%). Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.
| S-EPMC8135444 | biostudies-literature
Project description:IntroductionInterrupted Time Series (ITS) studies may be used to assess the impact of an interruption, such as an intervention or exposure. The data from such studies are particularly amenable to visual display and, when clearly depicted, can readily show the short- and long-term impact of an interruption. Further, well-constructed graphs allow data to be extracted using digitizing software, which can facilitate their inclusion in systematic reviews and meta-analyses.AimWe provide recommendations for graphing ITS data, examine the properties of plots presented in ITS studies, and provide examples employing our recommendations.Methods and resultsGraphing recommendations from seminal data visualization resources were adapted for use with ITS studies. The adapted recommendations cover plotting of data points, trend lines, interruptions, additional lines and general graph components. We assessed whether 217 graphs from recently published (2013-2017) ITS studies met our recommendations and found that 130 graphs (60%) had clearly distinct data points, 100 (46%) had trend lines, and 161 (74%) had a clearly defined interruption. Accurate data extraction (requiring distinct points that align with axis tick marks and labels that allow the points to be interpreted) was possible in only 72 (33%) graphs.ConclusionWe found that many ITS graphs did not meet our recommendations and could be improved with simple changes. Our proposed recommendations aim to achieve greater standardization and improvement in the display of ITS data, and facilitate re-use of the data in systematic reviews and meta-analyses.
| S-EPMC7818488 | biostudies-literature
Project description:Following the introduction of unprecedented "stay-at-home" national policies, the COVID-19 pandemic recently started declining in Europe. Our research aims were to characterize the changepoint in the flow of the COVID-19 epidemic in each European country and to evaluate the association of the level of social distancing with the observed decline in the national epidemics. Interrupted time series analyses were conducted in 28 European countries. Social distance index was calculated based on Google Community Mobility Reports. Changepoints were estimated by threshold regression, national findings were analyzed by Poisson regression, and the effect of social distancing in mixed effects Poisson regression model. Our findings identified the most probable changepoints in 28 European countries. Before changepoint, incidence of new COVID-19 cases grew by 24% per day on average. From the changepoint, this growth rate was reduced to 0.9%, 0.3% increase, and to 0.7% and 1.7% decrease by increasing social distancing quartiles. The beneficial effect of higher social distance quartiles (i.e., turning the increase into decline) was statistically significant for the fourth quartile. Notably, many countries in lower quartiles also achieved a flat epidemic curve. In these countries, other plausible COVID-19 containment measures could contribute to controlling the first wave of the disease. The association of social distance quartiles with viral spread could also be hindered by local bottlenecks in infection control. Our results allow for moderate optimism related to the gradual lifting of social distance measures in the general population, and call for specific attention to the protection of focal micro-societies enriching high-risk elderly subjects, including nursing homes and chronic care facilities.
| S-EPMC7288252 | biostudies-literature
Project description:BackgroundInterrupted time series (ITS) analysis is a time series regression model that aims to evaluate the effect of an intervention on an outcome of interest. ITS analysis is a quasi-experimental study design instrumental in situations where natural experiments occur, gaining popularity, particularly due to the Covid-19 pandemic. However, challenges, including the lack of a control group, have impeded the quantification of the effect size in ITS. The current paper proposes a method and develops a user-friendly R package to quantify the effect size of an ITS regression model for continuous and count outcomes, with or without seasonal adjustment.ResultsThe effect size presented in this work, together with its corresponding 95% confidence interval (CI) and P-value, is based on the ITS model-based fitted values and the predicted counterfactual (the exposed period had the intervention not occurred) values. A user-friendly R package to fit an ITS and estimate the effect size was developed and accompanies this paper. To illustrate, we implemented a nation population-based ITS study from January 2001 to May 2021 covering the all-cause mortality of Israel (n = 9,350 thousand) to quantify the effect size of Covid-19 exposure on mortality rates. In the period unexposed to the Covid-19 pandemic, the mortality rate decreased over time and was expected to continue decreasing had Covid-19 not occurred. In contrast, the period exposed to the Covid-19 pandemic was associated with an increased all-cause mortality rate (relative risk = 1.11, 95% CI = 1.04, 1.18, P < 0.001).ConclusionFor the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure.
| S-EPMC9652048 | biostudies-literature