Adoption of medication alert systems in hospital outpatient departments in Taiwan

Advanced Medication Alert System Decreased Hospital-Based Outpatient Duplicated Medications: A Longitudinal Hospital Cohort Study

OBJECTIVES

This study aimed to examine the associations between adoption of an advanced medication alert system and decreases in hospital-based outpatient duplicated medication rates in Taiwan.

METHODS

The unit of analysis was the hospital. We merged the hospital medication alert system adoption survey data and Taiwan National Health Insurance outpatient claims data. The observation time was 1998 to 2011, divided into 5 periods (T1-T5). The analysis included 216 hospitals, and outcome variable was hospital-based outpatient duplicated medication rates. The system adoption time frame, hospital accreditation level, and number of drugs per prescription were defined as predicted variables. A generalized estimating equation regression model was used.

RESULTS

Adoption of the advanced medication alert system gradually increased, such that 100% of medical centers and 84% of regional hospitals, but less than 50% of district hospitals, had systems by T5. The hospital-based outpatient duplicated medication rate continually decreased, from 29.8% to 11.2%. The generalized estimating equation model showed rates of duplicated medications of b = -8.44 at T2 and b = -17.88 at T5 (P < 0.001) compared with T1. Medical centers and regional hospitals demonstrated much lower duplication rates (b = -13.71, b = -6.82; P < 0.001) compared with district hospitals. Hospitals with more medications per prescription had higher duplication rates than did hospitals with fewer items.

CONCLUSIONS

Hospitals accredited at higher levels tended to have advanced medication alert systems. Hospitals that implemented advanced systems decreased hospital-based outpatient duplicated medications, avoiding a potential risk due to inappropriate medication use.

Improved diagnosis-medication association mining to reduce pseudo-associations

BACKGROUND AND OBJECTIVE

Association rule mining has been adopted to medical fields to discover prescribing patterns or relationships among diseases and/or medications; however, it has generated unreasonable associations among these entities. This study aims to identify the real-world profile of disease-medication (DM) associations using the modified mining algorithm and assess its performance in reducing DM pseudo-associations.

METHODS

We retrieved data from outpatient records between January 2011 and December 2015 in claims databases maintained by the Health and Welfare Data Science Center, Ministry of Health and Welfare, Taiwan. The association rule mining's lift (Q-value) was adopted to quantify DM associations, referred to as Q₁ for the original algorithm and as Q₂ for the modified algorithm. One thousand DM pairs with positive Q₁-values (Q₁⁺) and negative or no Q₂-values (Q₂^- or Q₂^∅) were selected as the validation dataset, in which two pharmacists assessed the DM associations.

RESULTS

A total of 3,120,449 unique DM pairs were identified, of which there were 333,347 Q₁⁺Q₂^- pairs and 429,931 Q₁⁺Q₂^∅ pairs. Q₁⁺Q₂^- rates were relatively high in ATC classes C (29.91%) and R (30.24%). Classes L (69.91%) and V (52.52%) demonstrated remarkably high Q₁⁺Q₂^∅ rates. For the 1000 pairs in the validation, 93.7% of the Q₁⁺Q₂^- or Q₁⁺Q₂^∅ DM pairs were assessed as pseudo-associations. However, classes M (5.3%), H (4.5%), and B (4.1%) showed the highest rates of plausible associations falsely given Q₂^- or Q₂^∅ by the modified algorithm.

CONCLUSIONS

The modified algorithm demonstrated high accuracy to identify pseudo-associations regarded as positive associations by the original algorithm and would potentially be applied to improve secondary databases to facilitate research on real-world prescribing patterns and further enhance drug safety.

The Impact of a National Health Information Exchange Program Under a Single-payer System

OBJECTIVE

This study aimed to evaluate the impact of the PharmaCloud program, a health information exchange program implemented in 2013, on medication duplication under a single-payer, universal health insurance program in Taiwan.

STUDY DESIGN

This study employed a retrospective pre-post study design and used nationwide health insurance claim data from 2013 to 2015. A difference-in-difference analysis was conducted to evaluate the effects of inquiry rate on the probability of receiving duplicate medications and on the number of days of overlapping medication prescriptions after implementation of the PharmaCloud program.

RESULTS

The study subjects included patients receiving medications in 7 categories: antihypertension drugs, 217,200; antihyperlipidemic drugs, 69,086; hypoglycemic agents, 103,962; antipsychotic drugs, 15,479; antidepressant drugs, 12,057; sedative and hypnotic drugs, 56,048; and antigout drugs, 18,250. Up to 2015, the overall PharmaCloud inquiry rate has increased to 55.36%-69.16%. Compared with subjects in 2013, subjects in 2014 and 2015 had a significantly lower likelihood of receiving duplicate medication in all 7 medication groups; for instance, for antihypertension drug users, the odds ratio (OR) was 0.91 with 95% confidence interval (CI)=0.90-0.92 in 2014, and the OR was 0.81 with 95% confidence interval=0.81-0.82 in 2015. However, a higher inquiry rate led to a lower likelihood of receiving duplicate medication and shorter periods of overlapping medications only in some of the medication groups.

CONCLUSIONS

The health information exchange program has reduced medication duplication, yet the reduction was not entirely associated with record inquiries. The hospitals have responded to the challenge of medication duplication by enhancing internal prescription control via a prescription alert system, which may have contributed to the reduction in duplicate medications and is a positive, unintended consequence of the intervention.

The impact of a medication record sharing program among diabetes patients under a single-payer system: The role of inquiry rate

OBJECTIVE

Taiwan's single health insurer introduced a medication record exchange platform, the PharmaCloud program, in 2013. This study aimed to evaluate the effects of the medication record inquiry rate on medication duplication among patients with diabetes.

MATERIALS AND METHODS

A retrospective pre-post design with a comparison group was conducted using nationwide health insurance claim data of diabetic patients from 2013 to 2014. Patients whose medication record inquiry rate fell within the upper 25th percentile were classified as the high-inquiry group, and the others as the low-inquiry group. The dependent variables were the likelihood of receiving duplicated medication and the overlapped medication days of the study subjects. Generalized estimation equations with difference-in-difference analysis were calculated to examine the net effect of the PharmaCloud inquiry rate for a matched sub-sample.

RESULTS

In total, 106,508 patients with diabetes were randomly selected. From 2013 to 2014, the medication duplication rate was reduced 7.76 percentile (54.12%-46.36%) for the high-inquiry group and 9.58 percentile (63.72%-54.14%) for the low-inquiry group; the average medication overlap periods were shortened 4.36 days (8.49-4.13) and 6.29 days (11.28-4.99), respectively. The regression models showed patients in the high-inquiry group were more likely to receive duplicated medication (OR = 1.11, 95% C.I. = 1.07-1.16) and with longer overlapped days (7.53%, P = 0.0081) after the program.

CONCLUSION

The medication record sharing program has reduced medication duplication among diabetes patients. However, higher inquiry rate did not lead to greater reduction in medication duplication; the overall effect might be due to enhanced internal control via prescription alert system in hospitals rather physician's review of the records.