Pay-for-performance programmes reduce stroke risks in patients with type 2 diabetes: a national cohort study

Pay-for-performance in Taiwan: A systematic review and meta-analysis of the empirical literature

OBJECTIVES

This study aimed to assess the impact of pay-for-performance (P4P) programmes on healthcare in Taiwan.

STUDY DESIGN

This was a systematic review and meta-analysis.

METHODS

A systematic literature search was performed using the PubMed, Medline, Embase, Cochrane review, Scopus, Web of Science and PsycINFO databases up to July 2023. Meta-analysis of the available outcomes was conducted using a random-effects model.

RESULTS

The search yielded 85 studies, of which 58 investigated the programme for diabetes mellitus (DM), eight looked at the programme for chronic kidney disease (CKD), and the remaining studies examined programmes for breast cancer, tuberculosis, schizophrenia and chronic obstructive pulmonary disease. The DM P4P programme was a cost-effective strategy associated with reduced hospitalisation and subsequent complications. The CKD P4P was associated with a lower risk of dialysis initiation. The P4P programme also improved outcomes in breast cancer, cure rates in tuberculosis, reduced admissions for schizophrenia and reduced acute exacerbation in chronic obstructive pulmonary disease. The meta-analysis revealed that the P4P programme for DM (odds ratio [OR] = 0.59; 95% confidence interval [CI] = 0.48-0.73) and CKD (OR = 0.73; 95% CI = 0.67-0.81) significantly reduced mortality risk. However, participation rate in the DM P4P programme was only 19% in 2014.

CONCLUSIONS

P4P programmes in Taiwan improve quality of care. However, participation was voluntary and the participation rate was very low, raising the concern of selective enrolment of participants (i.e. 'cherry-picking' behaviour) by physicians. Future programme reforms should focus on well-designed features with the aim of reducing healthcare disparities.

Educational attainment affects the diagnostic time in type 2 diabetes mellitus and the mortality risk of those enrolled in the diabetes pay-for-performance program

Most patients are diagnosed as having diabetes only after experiencing diabetes complications. Educational attainment might have a positive relationship with diabetes prognosis. The diabetes pay-for-performance (P4P) program-providing comprehensive, continuous medical care-has improved diabetes prognosis in Taiwan. This retrospective cohort study investigated how educational attainment affects the presence of diabetes complications at diabetes diagnosis and mortality risk in patients with diabetes enrolled in the P4P program. From the National Health Insurance Research Database, we identified patients aged >45 years who had received a new diagnosis of type 2 diabetes during 2002-2015; they were followed up until the end of 2017. We next used logistic regression analysis to explore whether the patients with different educational attainments had varied diabetic complication risks at diabetes diagnosis. The Cox proportional hazard model was employed to examine the association of different educational attainments in people with diabetes with mortality risk after their enrollment in the P4P program. The results indicated that as educational attainment increased, the risk of diabetes complications at type 2 diabetes diagnosis decreased gradually. When type 2 diabetes with different educational attainments joined the P4P program, high school education had the highest effect on reducing mortality risk; however, those with ≤ 6th grade education had the lowest impact.

Impact of a diabetes pay-for-performance program on nonincentivized mental disorders: a panel study based on claims database analysis

BACKGROUND

Diabetes is one of the most prevalent chronic diseases with subsequent complications. The positive effects of diabetes pay-for-performance (P4P) programs on treatment outcomes have been reported. The program provides financial incentives based on physiological care indicators, but common mental disorder complications such as depression are not covered.

METHODS

This study employed a natural experimental design to examine the spillover effects of diabetes P4P program on patients with nonincentivized depressive symptoms. The intervention group consisted of diabetes patients enrolled in the DM P4P program from 2010 to 2015. Unenrolled patients were selected by propensity score matching to form the comparison group. Difference-in-differences analyses were conducted to evaluate the effects of P4P programs. We employed generalized estimating equation (GEE) models, difference-in-differences analyses and difference-in-difference-in-differences analyses to evaluate the net effect of diabetes P4P programs. Changes in medical expenses (outpatient and total health care costs) over time were analysed for the treatment and comparison groups.

RESULTS

The results showed that enrolled patients had a higher incidence of depressive symptoms than unenrolled patients. The outpatient and total care expenses of diabetes patients with depressive symptoms were lower in the intervention group than in the comparison group. Diabetes patients with depressive symptoms enrolled in the DM P4P program had lower expenses for depression-related care than those not enrolled in the program.

CONCLUSIONS

The DM P4P program benefits diabetes patients by screening for depressive symptoms and lowering accompanying health care expenses. These positive spillover effects may be an important aspect of physical and mental health in patients with chronic disease enrolled in disease management programs while contributing to the control of health care expenses for chronic diseases.

Effects of colchicine use on ischemic and hemorrhagic stroke risk in diabetic patients with and without gout

This study aimed to determine the effect of colchicine use on the risk of stroke among patients with diabetes mellitus (DM). We retrospectively enrolled patients with DM between 2000 and 2013 from the Longitudinal Health Insurance Database and divided them into a colchicine cohort (n = 8761) and noncolchicine cohort (n = 8761) by using propensity score matching (PSM). The event of interest was a stroke, including ischemic stroke and hemorrhagic stroke. The incidence of stroke was analyzed using multivariate Cox proportional hazards models between the colchicine cohort and the comparison cohort after adjustment for several confounding factors. The subdistribution hazard model was also performed for examination of the competing risk. The colchicine cohort had a significantly lower incidence of stroke [adjusted hazard ratios (aHR), 95% confidence intervals (95%CI)] (aHR = 0.61, 95%CI = 0.55–0.67), ischemic stroke (aHR = 0.59, 95%CI = 0.53–0.66), and hemorrhagic stroke (aHR = 0.66, 95%CI = 0.53–0.82) compared with the noncolchicine cohort. Drug analysis indicated that patients in the colchicine cohort who received colchicine of cumulative daily defined dose (cDDD) > 14 and duration > 28 days had a lower risk of stroke and ischemic stroke compared with nonusers. The colchicine cohort (cDDD > 150, duration > 360 days) also had a lower risk of stroke, ischemic stroke, and hemorrhagic stroke. The cumulative incidence of stroke, ischemic stroke, and hemorrhagic stroke in the colchicine cohort was significantly lower than that in the noncolchicine cohort (log-rank P < 0.001). However, the subdistribution hazard model reveal the colchicine was not associated with the hemorrhagic stroke in DM patients without gout (aHR = 0.69, 95%CI = 0.47–1.00). Colchicine use with cDDD > 14 and duration > 28 days was associated with lower risk of stroke and ischemic stroke, and colchicine use with cDDD > 150 and duration > 360 days played an auxiliary role in the prevention of stroke, ischemic stroke, and hemorrhagic stroke in patients with DM. The colchicine for the hemorrhagic stroke in DM patients without gout seem to be null effect.

Relationships Between Bronchodilators, Steroids, Antiarrhythmic Drugs, Antidepressants, and Benzodiazepines and Heart Disease and Ischemic Stroke in Patients With Predominant Bronchiectasis and Asthma

Objective

We investigated the effects of medication on heart disease and ischemic stroke (HDS) risk in patients with predominant bronchiectasis-asthma combination (BCAS).

Methods

BCAS and non-BCAS cohorts (N = 588 and 1,118, respectively) were retrospectively enrolled. The cumulative incidence of HDS was analyzed using Cox proportional regression; propensity scores were estimated using non-parsimonious multivariable logistic regression. Adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for HDS were calculated, adjusting for sex, age, comorbidities, and medication {long- and short-acting β2 agonists and muscarinic antagonists (LABAs/SABAs and LAMAs/SAMAs), steroids [inhaled corticosteroid steroids (ICSs), oral steroids (OSs)], antiarrhythmics, antidepressants (fluoxetine), benzodiazepines (alprazolam, fludiazepam), statins and antihypertensive drugs (diuretics, cardioselective beta blockers, calcium channel blockers (CCBs) and angiotensin converting enzyme inhibitors (ACEi), angiotensin II blockers)}.

Results

Compared with the non-BCAS cohort, the BCAS cohort taking LABAs, SABAs, SAMAs, ICSs, OSs, antiarrhythmics, and alprazolam had an elevated HDS risk [aHRs (95% CIs): 2.36 (1.25–4.33), 2.65 (1.87–3.75), 2.66 (1.74–4.05), 2.53 (1.61–3.99), 1.76 (1.43–2.18), 9.88 (3.27–30.5), and 1.73 (1.15–2.58), respectively except fludiazepam 1.33 (0.73–2.40)]. The aHRs (95% CIs) for LABAs ≤ 30 days, DDDs &lt;415, ICSs ≤ 30 days were 1.10 (0.38–3.15), 2.95 (0.22–38.8), 1.45 (0.76–2.77). The aHRs (95% CIs) for current and recent alprazolam were 1.78 (1.09–2.93) and 777.8 (1.34–451590.0); for current and past fludiazepam were 1.39 (0.75–2.59) and 1.29 (0.42–4.01) and for past alprazolam was 1.57 (0.55–4.46); respectively. The aHRs (95% CIs) for alprazolam &gt;30 DDDs, fludiazepam &gt;20 DDDs, ICSs ≦415 DDDs, and OSs DDDs ≦15 were 1.60 (0.78–3.29), 2.43 (0.90–6.55), 5.02 (1.76–14.3), and 2.28 (1.43–3.62), respectively.

Conclusion

The bronchodilators, steroids, and antiarrhythmics were associated with higher risk of HDS, even low dose use of steroids. However, the current use of LABAs/ICSs were not associated with HDS. Benzodiazepines were relatively safe, except for current or recent alprazolam use. Notably, taking confounders into account is crucial in observational studies.

Trends in all-cause mortality and major causes of death between 2007 and 2018 among patients with diabetes in Taiwan

Optimal control of diabetes and relevant risk factors substantially reduce the risks of chronic complications and mortality. We investigated all-cause mortality rate and major causes of death between 2007 and 2018 in patients with diabetes in Taiwan. This study was conducted using data from Taiwan National Health Insurance Research Database. We selected patients with diabetes diagnosed between 2007 and 2017 (grouped according to the year of diabetes diagnosis 2007-2010 vs. 2011-2017). Information on mortality and causes of death by the end of 2018 was confirmed through linking to the National Death Registry. Standardized mortality rate (SMR) were calculated by weighting the World Health Organization (WHO) standard population (WHO 2000-2025). More than 2.7 million of patients with diabetes were analyzed and a total of 566121 deaths were identified. Overall, the SMR was 11.72 per 1000 person-years. Patients with diabetes diagnosed in 2011-2017 had a lower SMR (8.42 vs. 12.92 per 1000 person-years) than those diagnosed in 2007-2010. Similar finding were noted regarding the major causes of death (cancer, diabetes, heart disease, hypertensive disease, and cerebrovascular disease). Compared with patients who were diagnosed in 2008-2010, those who were diagnosed in 2011-2014 and 2015-2018 had a higher 3-year survival rate (0.9356 vs. 0.9438 vs. 0.946, log-rank test p<0.001) after the diagnosis of diabetes. Patients who were diagnosed with diabetes after 2011 had a lower rate of all-cause mortality and major causes of death, compared with those who were diagnosed before 2010 in Taiwan.

Adding Pay-for-Performance Program to Routine Care Was Related to a Lower Risk of Depression Among Type 2 Diabetes Patients in Taiwan

Background: Patients with type 2 diabetes (T2DM) often experience depression during treatment, negatively influencing their treatment compliance and clinical outcomes. Recently, the pay-for-performance (P4P) program for chronic diseases, with high-cost and high-risk feature, such as T2DM, has been implemented and has been operational for several years. Nevertheless, its effect on the risk of developing depression among T2DM cases is unknown. This study aims to explore the association of P4P use with the subsequent risk of developing depression among these patients. Methods: This cohort study used a nationwide health insurance database to identify patients 20-70 years of age newly diagnosed with T2DM who enrolled in the P4P program between 2001 and 2010. From this group, we enrolled 17,022 P4P users and then 17,022 non-P4P users who were randomly selected using propensity-score-matching. Enrolled patients were followed until the end of 2012 to record the occurrence of depression. The Cox proportional hazards regression was utilized to obtain the adjusted hazard ratio (aHR) for P4P use. Results: During the study period, a total of 588 P4P users and 1,075 non-P4P users developed depression at incidence rates of 5.89 and 8.41 per 1,000 person-years, respectively. P4P users had a lower depression risk than did non-P4P users (aHR, 0.73; 95% Confidence Interval, 0.65-0.80). This positive effect was particularly prominent in those receiving high-intensity use of the P4P program. Conclusion: Integrating P4P into routine care for patients with T2DM may have beneficial effects on curtailing the subsequent risk of depression.

Developing a Prediction Model for 7-Year and 10-Year All-Cause Mortality Risk in Type 2 Diabetes Using a Hospital-Based Prospective Cohort Study

Leveraging easily accessible data from hospitals to identify high-risk mortality rates for clinical diabetes care adjustment is a convenient method for the future of precision healthcare. We aimed to develop risk prediction models for all-cause mortality based on 7-year and 10-year follow-ups for type 2 diabetes. A total of Taiwanese subjects aged ≥18 with outpatient data were ascertained during 2007-2013 and followed up to the end of 2016 using a hospital-based prospective cohort. Both traditional model selection with stepwise approach and LASSO method were conducted for parsimonious models' selection and comparison. Multivariable Cox regression was performed for selected variables, and a time-dependent ROC curve with an integrated AUC and cumulative mortality by risk score levels was employed to evaluate the time-related predictive performance. The prediction model, which was composed of eight influential variables (age, sex, history of cancers, history of hypertension, antihyperlipidemic drug use, HbA1c level, creatinine level, and the LDL /HDL ratio), was the same for the 7-year and 10-year models. Harrell's C-statistic was 0.7955 and 0.7775, and the integrated AUCs were 0.8136 and 0.8045 for the 7-year and 10-year models, respectively. The predictive performance of the AUCs was consistent with time. Our study developed and validated all-cause mortality prediction models with 7-year and 10-year follow-ups that were composed of the same contributing factors, though the model with 10-year follow-up had slightly greater risk coefficients. Both prediction models were consistent with time.

Diabetes, Vascular Aging and Stroke: Old Dogs, New Tricks?

BACKGROUND

Stroke remains a leading cause of death and disability throughout the world. It is well established that Diabetes Mellitus (DM) is a risk factor for stroke, while other risk factors include dyslipidaemia and hypertension. Given that the global prevalence of diabetes steadily increases, the need for adequate glycaemic control and prevention of DM-related cardiovascular events remains a challenge for the medical community. Therefore, a re-examination of the latest data related to this issue is of particular importance.

OBJECTIVE

This review aims to summarise the latest data on the relationship between DM and stroke, including epidemiology, risk factors, pathogenesis, prevention and biomarkers.

METHODS

For this purpose, comprehensive research was performed on the platforms PubMed, Google Scholar and EMBASE with a combination of the following keywords: diabetes mellitus, stroke, macrovascular complications, diabetic stroke, cardiovascular disease.

CONCLUSIONS

Much progress has been made in stroke in people with DM in terms of prevention and early diagnosis. In the field of prevention, the adaptation of the daily habits and the regulation of co-morbidity of individuals play a particularly important role. Simultaneously, the most significant revolution has been brought by the relatively new treatment options that offer protection to the cardiovascular system. Moreover, many prognostic and diagnostic biomarkers have been identified, paving the way for early and accurate diagnoses. However, to date, there are crucial points that remain controversial and need further clarification.

Performance of ICD-10-CM Diagnosis Codes for Identifying Acute Ischemic Stroke in a National Health Insurance Claims Database

Purpose

The validity of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding for the identification of acute ischemic stroke (AIS) in Taiwan’s National Health Insurance claims database has not been investigated. This study aimed to construct and validate the case definition algorithms for AIS based on ICD-10-CM diagnostic codes.

Patients and Methods

This study identified all hospitalizations with ICD-10-CM code of I63* in any position of the discharge diagnoses from the inpatient claims database and all patients with a final diagnosis of AIS from the stroke registry between Jan 2018 and Dec 2019. Hospitalizations in the claims data that could be successfully linked to those in the registry data were regarded as true episodes of AIS. Otherwise, their electronic medical records and images were manually reviewed to ascertain whether they were true episodes of AIS. Using the true episodes of AIS as the reference standard, the positive predictive value (PPV) and sensitivity of various case definition algorithms for AIS were calculated.

Results

A total of 1227 hospitalizations were successfully linked. Among the 155 hospitalizations that could not be linked, 54 were determined to be true episodes of AIS. Using ICD-10-CM code of I63* in any position of the discharge diagnoses to identify AIS yielded a PPV and sensitivity of 92.7% and 99.4%, respectively. The PPV increased to 99.8% with >12% decrease in the sensitivity when AIS was restricted to those with I63* as the primary diagnosis. When AIS was defined to be I63* as the primary, first secondary, or second secondary diagnosis, both PPV and sensitivity were greater than 97%.

Conclusion

This study demonstrated the validity of various case definition algorithms for AIS based on ICD-10-CM coding and can provide a reference for future claims-based stroke research.