This dataset provides data for new prescription drugs introduced to market in California with a Wholesale Acquisition Cost (WAC) that exceeds the Medicare Part D specialty drug cost threshold. Prescription drug manufacturers submit information to HCAI within a specified time period after a drug is introduced to market. Key data elements include the National Drug Code (NDC) administered by the FDA, a narrative description of marketing and pricing plans, and WAC, among other information. Manufacturers may withhold information that is not in the public domain. Note that prescription drug manufacturers are able to submit new drug reports for a prior quarter at any time. Therefore, the data set may include additional new drug report(s) from previous quarter(s).

There are two types of New Drug data sets: Monthly and Annual. The Monthly data sets include the data in completed reports submitted by manufacturers for calendar year 2025, as of July 8, 2025. The Annual data sets include data in completed reports submitted by manufacturers for the specified year. The data sets may include reports that do not meet the specified minimum thresholds for reporting.

The program regulations are available here: https://hcai.ca.gov/wp-content/uploads/2024/03/CTRx-Regulations-Text.pdf

The data format and file specifications are available here: https://hcai.ca.gov/wp-content/uploads/2024/03/Format-and-File-Specifications-version-2.0-ada.pdf

DATA NOTES: Due to recent changes in Excel capabilities, it is not recommended that you save these files to .csv format. If you do, when importing back into Excel the leading zeros in the NDC number column will be dropped. If you need to save it into a different format other than .xlsx it must be .txt

The number of prescriptions dispensed in the U.S. has increased between 2009 and 2022. In 2009 the number of prescriptions dispensed was near **** billion, while in 2022 the number of prescriptions dispensed was around *** billion. The increase in the number of prescriptions dispensed has a multifactorial origin that includes health care sources, health insurance, and prescription drug benefits. However, the increase in prescription drug usage comes with a price tag as the price of drugs in the U.S. is also on the rise. Medication usage The total number of retail prescriptions filed annually in the United States is expected to also rise significantly by the year 2025. Medication usage varies depending on the population, for example, some data shows that prescription usage increases with age. Likewise, gender has an influence on prescription drug use. Females have a higher rate of prescription drug usage. Prescription drug costs The U.S. has some of the highest per capita drug spending in the world. That is largely because the prices of drugs in the U.S. are based solely on what the market can bear, rather than what the actual costs of production are. Personal health care expenditures in the U.S. have more than doubled since 2000. Estimates suggest that the cost of drugs will continue to increase. Estimated U.S. prescribed drug expenditures amounted to *** billion U.S. dollars by the end of 2021.

Graph and download economic data for Producer Price Index by Industry: Pharmacies and Drug Retailers: Retailing of Prescription Drugs (PCU4461104461101) from Jun 2000 to May 2025 about prescription drugs, medicines, retail, PPI, industry, inflation, price index, indexes, price, and USA.

Between the launch of Eliquis and 2024, the price of the drug in the United States increased by *** percent. This statistic illustrates the price increase of select top-selling drugs in the United States between their launch and 2024.

The Centers for Medicare and Medicaid Services estimate that prescription drug expenditure in the United States will reach around 460 billion U.S. dollars in 2024. This amount includes only retail drug spending, excluding nonretail. Estimations of drug spending can vary by investigating organization. For the U.S., among the most relevant drug spending calculations are provided by CMS, ASPE (Assistant Secretary for Planning and Evaluation), and pharmaceutical market researcher IQVIA. High drug prices in the U.S.The United States is the country with the highest total drug spending, and also with the highest per capita pharmaceuticals spending among developed countries. This is mostly connected to higher drug prices in the United States. For example, the price for the blockbuster drug Humira was almost three times higher in the United States than in Germany in 2017. But whereas in other countries, governments more or less directly control drug prices, the U.S. leaves drug pricing to market competition. As a consequence, the U.S. market is the most profitable for pharmaceutical companies. Where the money is spentNearly half of all Americans have taken at least one prescription medicine within the preceding month. The therapeutic areas where spending is the highest are ‘traditionally’ to be found among antidiabetics, oncologics, autoimmune, and respiratory diseases. Based on number of prescriptions filled, antihypertensives, pain reliever, and mental health drugs are the leading classes.

This data package contains a national benchmark that is reflective of the prices paid by retail community pharmacies to acquire prescription and over-the-counter covered outpatient drugs and offers an access to all changes of National Average Drug Acquisition Cost (NADAC) rates since end of 2013.

This dataset provides data for new prescription drugs introduced to market in California with a Wholesale Acquisition Cost (WAC) that exceeds the Medicare Part D specialty drug cost threshold. Prescription drug manufacturers submit information to HCAI within a specified time period after a drug is introduced to market. Key data elements include the National Drug Code (NDC) administered by the FDA, a narrative description of marketing and pricing plans, and WAC, among other information. Manufacturers may withhold information that is not in the public domain. Note that prescription drug manufacturers are able to submit new drug reports for a prior quarter at any time. Therefore, the data set may include additional new drug report(s) from previous quarter(s). There are two types of New Drug data sets: Monthly and Annual. The Monthly data sets include the data in completed reports submitted by manufacturers for calendar year 2025, as of February 7, 2025. The Annual data sets include data in completed reports submitted by manufacturers for the specified year. The data sets may include reports that do not meet the specified minimum thresholds for reporting. The program regulations are available here: https://hcai.ca.gov/wp-content/uploads/2024/03/CTRx-Regulations-Text.pdf The data format and file specifications are available here: https://hcai.ca.gov/wp-content/uploads/2024/03/Format-and-File-Specifications-version-2.0-ada.pdf DATA NOTES: Due to recent changes in Excel capabilities, it is not recommended that you save these files to .csv format. If you do, when importing back into Excel the leading zeros in the NDC number column will be dropped. If you need to save it into a different format other than .xlsx it must be .txt

The Medicare Part D by Drug dataset presents information on spending for drugs prescribed to Medicare beneficiaries enrolled in Part D by physicians and other healthcare providers. Drugs prescribed in the Medicare Part D program are drugs patients generally administer themselves. The dataset focuses on average spending per dosage unit and change in average spending per dosage unit over time. It also includes spending information for manufacturer(s) of the drugs as well as consumer-friendly information of drug uses and clinical indications. Drug spending metrics for Part D drugs are based on the gross drug cost, which represents total spending for the prescription claim, including Medicare, plan, and beneficiary payments. The Part D spending metrics do not reflect any manufacturers’ rebates or other price concessions as CMS is prohibited from publicly disclosing such information.

The National Average Drug Acquisition Cost (NADAC) is designed to create a national benchmark that is reflective of the prices paid by retail community pharmacies to acquire prescription and over-the-counter covered outpatient drugs. This dataset shows this data.

Data on delay or nonreceipt of needed medical care, nonreceipt of needed prescription drugs, or nonreceipt of needed dental care during the past 12 months due to cost by selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Health Interview Survey, Family Core, Sample Child, and Sample Adult questionnaires. Data for level of difficulty are from the 2010 Quality of Life, 2011-2017 Functioning and Disability, and 2018 Sample Adult questionnaires. For more information on the National Health Interview Survey, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

Dataset Description: This dataset provides comprehensive information on medicines available in Egyptian pharmacies. It includes drug names, prices, and additional attributes such as form, company, region, and category. The data was collected through web scraping from a reputable Egyptian pharmaceutical website, covering a variety of drugs sold in the local market. The dataset can be valuable for price tracking, market analysis, or healthcare-related research in Egypt.

Columns: Drugname: The name of the medication. Price: The price of the drug in Egyptian pounds (EGP). Search Query: Search terms used for scraping, based on two-letter combinations. Date: The timestamp when the data was scraped. Form: The form of the medication (e.g., tablet, syrup), randomly generated for this dataset. Company: The company manufacturing the drug, randomly generated for this dataset. Region: Placeholder for the region where the drug is commonly available. Category: The category or type of drug (e.g., antibiotic, analgesic), randomly generated for this dataset. Price Changed: Indicates whether the price has changed compared to the previous scrape. Use Cases: This dataset is suitable for:

Pharmaceutical pricing analysis: Understanding trends in drug prices across pharmacies. Healthcare research: Investigating the availability of specific drugs. Economic studies: Monitoring inflation or price fluctuations in medicines. Supply chain analysis: Assessing the market distribution of pharmaceutical companies in Egypt. Acknowledgements: This dataset was generated using web scraping techniques from a public Egyptian pharmaceutical website.

The NHS Business Services Authority (NHSBSA) publishes Secondary Care Medicines Data on behalf of NHS England (NHSE). This dataset provides 'Provisional' Secondary Care Medicines data for all NHS Acute, Teaching, Specialist, Mental Health, and Community Trusts in England. It provides information on pharmacy stock control, reflecting processed medicines data. RX Info is responsible for refreshing the Provisional data at the close of each financial year to include backtracking adjustments. The data is 'Finalised' to provide validated and complete figures for each reporting period, incorporating any updates and corrections throughout the year. The Finalised dataset serves as the definitive record for each month and year, offering the most accurate information on medicines issued. While we do not analyse changes, users can compare the finalised data with provisional data to identify any discrepancies. Key Components of the Data Quantities of Medicines Issued: Details the total quantities of medicines stock control via NHS Secondary Care services. Indicative Costs: Actual costs cannot be displayed in the dataset as NHS Hospital pricing contracts and NICE Patient Access Schemes are confidential. The indicative cost of medicines is derived from current medicines pricing data held in NHSBSA data systems (Common Drug Reference and dm+d), calculated to VMP level. Indicative costs are calculated using: Community pharmacy reimbursement prices for generic medicines. List prices for branded medicines. Care should be taken when interpreting and analysing this indicative cost as it does not reflect the net actual cost of NHS Trusts, which will differ due to the application of confidential discounts, rebates, or procurement agreements paid by hospitals when purchasing medicines. Standardisation with SNOMED CT and dm+d: SNOMED CT (Systematised Nomenclature of Medicine - Clinical Terms) is used to enhance the dataset’s compatibility with electronic health record systems and clinical decision support tools. SNOMED CT is a globally recognised coding system that provides precise definitions for clinical terms, ensuring interoperability across healthcare systems. Trust-Level Data: Data is broken down by individual NHS Trusts, enabling regional comparisons, benchmarking, and targeted analysis of specific Trusts. Medicine Identification: Medicines in the dataset are identified using Virtual Medicinal Product (VMP) codes from the Dictionary of Medicines and Devices (dm+d): VMP_PRODUCT_NAME: The name of the Virtual Medicinal Product (VMP) as defined by the dm+d, which includes key details about the product. For example: Paracetamol 500mg tablets. VMP_SNOMED_CODE: The code for the Virtual Medicinal Product (VMP), providing a unique identifier for each product. For example: 42109611000001109 represents Paracetamol 500mg tablets. You can access the finalised files in our Finalised Secondary Care Medicines Data (SCMD) with indicative price dataset. Dataset Details Service Overview Information about our NHSBSA Prescriptions Data service can be found here - Prescription data | NHSBSA The NHS Business Services Authority (NHSBSA) publishes this dataset, provided by RX Info, which contains information about pharmacy stock control in NHS Secondary Care settings across England on behalf of NHS England. It includes data from NHS Trusts and is in a standardised dm+d format (Dictionary of medicines and devices (dm+d) | NHSBSA). For further context about the Secondary Care Medicines Data, you can explore the following resources: Secondary Care Medicines Data Release Guidance v0.5 (Word: 78.3KB) RX Info: RX Info is the provider of the data related to pharmacy stock control medicines issued in NHS Secondary Care settings, which is made available by NHSBSA. Visit RX Info's website for more details. Data Source The data is sourced from NHS Trusts' pharmacy stock control systems which capture detailed records of medicines issued, including quantities. The data is provided to NHSBSA by RX Info, a data provider that supplies records on medicines issued in NHS Secondary Care settings. Data quality controls are in place to exclude transactions flagged as outliers, non-standardised items and zero activity. No personal or patient-identifiable information is included, ensuring compliance with data protection regulations. Rx-Info will provide a complete annual refresh of the data two months after the close of a financial year, planned for the end May, which will then be the fixed data set accounting for backtracking. The data for the finalised view is provided to NHSBSA. Data Collection Data is from NHS England sites only and provided under the agreement entered into by Trusts and Rx-Info (Define) facilitated by NHS England. The data owners and data controllers are the respective NHS Trusts. Time Periods Publication frequency: Data is uploaded on a monthly basis and is published retrospectively with a two-month delay. For example, January data is published in March. Historical Data: Data is available from April 2021 onwards. Geography NHS Trusts in England. Statistical Classification This is not an official statistic. A related official statistic can be found in our Prescribing Costs in Hospitals and the Community publication, which includes Secondary Care Medicines data with actual cost, broken down by British National Formulary (BNF) Section. Caveats Information: Interpreting 'Cost' Data Cost Limitations and Interpretation Indicative Costs: The costs in this dataset are indicative and do not reflect the net actual cost (including discounts and rebates) paid by hospitals when purchasing medicines. Due to confidential procurement agreements, the indicative costs will overestimate total NHS hospital expenditure. These figures are most useful for trend analysis rather than precise cost predictions.

Adjustment of drug prices after the change of their clinical status in the current drug pricing system in Japan functions as an appropriate allocation mechanism for drug expenditures under the universal health insurance system. However, the failure to incorporate a drug’s value when determining its price decreases pharmaceutical companies’ motivation to develop and launch novel drugs in Japan. In this study, we applied the value-based pricing framework MARIE to drugs with new clinical status. We estimated drug prices at the time of approval for the initial indication and new clinical status, with a total of 32 drugs by using MARIE. To estimate maximum number of patients for the new clinical status, we referred to the market expansion rate and calculated it backwards. As a result, the median change of MARIE-estimated price under new clinical status against those under initial indication was −50.24% (range, −80.36% to 16.39%). For the initial indication, the median ratio of the drug price estimated with MARIE to the initial list price was 122.12% (range, 15.57% to 2237.38%); the median ratio of actual to estimated drug price were similar to those in our previous study (125.65%). We proposed the versatile, practical, convenient, multiple criteria, qualitative VBP framework MARIE for the new clinical status. Under the MARIE system, price would only be changed when the “box” (category of the maximum number of patients) in the conversion table of the maximum number of the patients changes as the environment changes.

The National Prescribed Drug Register provides the basis for the official statistics about prescribed drugs in Sweden.

The National Prescribed Drug Register with personal identity numbers was established in July 2005 and contains all prescribed drugs dispensed at pharmacies. About 67 percent (6.8 million) of the population were prescribed a pharmaceutical at least once 2019. Each row in the register corresponds to one dispensation at a pharmacy. The number of rows in the register amounts to more than 100 million per year. This level has remained almost unchanged for several years.

The purpose of the Swedish Prescribed Drug Register is to increase the patient safety in the pharmaceutical area. The register is used by researchers, media, analysts in the regions and authorities as well as by the pharmaceutical industry. The register can be linked to other health data registers, for example the National Patient Register or the National Medical Birth Register. Increased knowledge of the effects and safety of different drugs may be of benefit to each individual patient in the long run.

The register is updated each month with new data from the Swedish eHealth Agency based on the monthly billing of the pharmacies. The register contains all prescribed drugs that are dispensed at pharmacies as well as information on dispensed medical devices and medical consumables within the pharmaceutical benefits scheme, such as ostomy products and foods for nutritional use by children under 16 years.

Drugs administered at hospital settings or nursing homes are not included in the register. Vaccines and over-the-counter medicines are not included in the register. In the register it is not possible to identify individual prescribers or the individual prescriber’s workplace.

The register contains information about

• patient (gender, age, place of residence)
• product (for example ATC code, drug name, strength, pack size, included/not included in the pharmaceutical benefits scheme)
• the prescription (for example prescribed quantity/number of packages, strength, date of prescription, date of purchase and type of ordination.)
• the costs (total cost, patient cost, region’s cost and additional patient cost)
• the prescriber (work title, kind of care according to the work-place, education code and specialist education code).

For a complete list of all variables see the variable list (xlsx).

Reporting

All data in the National Prescribed Drug Register comes from the Swedish eHealth Agency. Pharmacies, retailers and wholesalers are obligated to report their sales to the Swedish eHealth Agency. In addition, pharmacies must submit additional information to the Swedish eHealth Agency when a prescribed drug is dispensed. The Swedish eHealth Agency in turn submits information on prescription dispensations to the National Board of Health and Welfare.

The quality of the National Prescribed Drug Register is overall very good. The risk of measurement errors is small since the collection process is largely automated and is based on administrative systems. The Swedish eHealth Agency checks the quality of the sales data that the pharmacies deliver before it is included in the register, but errors and incompletions cannot be completely avoided.

A small proportion of the rows in the National Prescribed Drug Register have negative values for the variables antal, tkost, lankost, patkost, merkost and fddd. This is not a lack of quality but rather how the register is corrected. This may be due to the fact that a drug has been registered in the system but has not been retrieved or that a pharmacy has accepted a repurchase of medicines (e.g. in case of product failure). There may also be misreported transactions that need to be corrected for some reason. The minus rows are used for the register to match when aggregating and summing.

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In 2011, Bristol-Myers Squibb set the price of its newly approved melanoma drug ipilimumab— brand name Yervoy—at $120,000 for a course of therapy. The drug was associated with an incremental increase in life expectancy of four months. Drugs like ipilimumab have fueled the perception that the launch prices of new anticancer drugs and other drugs in the so-called "specialty" pharmaceutical market have been increasing over time and that increases are unrelated to the magnitude of the expected health benefits. In this paper, we discuss the unique features of the market for anticancer drugs and assess trends in the launch prices for 58 anticancer drugs approved between 1995 and 2013 in the United States. We restrict attention to anticancer drugs because the use of median survival time as a primary outcome measure provides a common, objective scale for quantifying the incremental benefit of new products. We find that the average launch price of anticancer drugs, adjusted for inflation and health benefits, increased by 10 percent annually—or an average of $8,500 per year—from 1995 to 2013. We argue that the institutional features of the market for anticancer drugs enable manufacturers to set the prices of new products at or slightly above the prices of existing therapies, giving rise to an upward trend in launch prices. Government-mandated price discounts for certain classes of buyers may have also contributed to launch price increases as firms sought to offset the growth in the discount segment by setting higher prices for the remainder of the market.

This dataset tracks the updates made on the dataset "Prescription Drug Wholesale Acquisition Cost (WAC) Increases" as a repository for previous versions of the data and metadata.

United States CPI U: sa: Medical Care: CO: MD: Prescription Drugs data was reported at 534.538 1982-1984=100 in Jun 2018. This records an increase from the previous number of 532.693 1982-1984=100 for May 2018. United States CPI U: sa: Medical Care: CO: MD: Prescription Drugs data is updated monthly, averaging 224.950 1982-1984=100 from Jan 1969 (Median) to Jun 2018, with 594 observations. The data reached an all-time high of 534.538 1982-1984=100 in Jun 2018 and a record low of 46.300 1982-1984=100 in Feb 1969. United States CPI U: sa: Medical Care: CO: MD: Prescription Drugs data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I006: Consumer Price Index: Urban: sa.

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Generic Drugs Market Size 2025-2029

The generic drugs market size is forecast to increase by USD 217.4 billion, at a CAGR of 7.6% between 2024 and 2029.

The market is driven by the increasing demand for low-cost alternatives to branded medicines. This trend is particularly pronounced in developing economies where affordability is a significant factor in healthcare access. However, the market faces challenges, including the advent of Robotic Process Automation (RPA) in the pharmaceutical industry, which could potentially reduce the cost advantage of generic drugs. Additionally, rising credibility issues related to generic drugs pose a significant challenge, as consumers and healthcare providers increasingly demand assurance of quality and safety. Companies in the market must navigate these challenges by focusing on ensuring the highest standards of quality and safety, while also leveraging technological advancements to maintain cost competitiveness.
Strategic partnerships, mergers and acquisitions, and collaborations could also provide opportunities for market expansion and growth. Overall, the market presents both opportunities and challenges, requiring a strategic approach from market participants to capitalize on the former and mitigate the latter.

What will be the Size of the Generic Drugs Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, shaped by various factors that impact its dynamics. Patient education plays a crucial role in ensuring the effective utilization of medications, with dosage forms varying from capsules to tablets and liquids. Clinical trials and pharmacokinetic studies contribute to regulatory approval, ensuring therapeutic equivalence and drug safety. Pharmaceutical manufacturing involves GMP compliance and stability testing to maintain quality, while patent expiration triggers increased competition and price reductions. Drug interactions necessitate diligent monitoring and education, with regulatory bodies such as the EMA and FDA overseeing approvals. Value-based healthcare and market access strategies prioritize cost-effectiveness analysis, influencing pricing and distribution channels.

Online pharmacies and retail pharmacies adapt to evolving market trends, offering convenience and accessibility. Intellectual property rights and pharmacy dispensing regulations shape the competitive landscape. Bioequivalence studies and drug utilization reviews facilitate generic substitution, while pharmacy dispensing and capsule filling processes ensure accurate and efficient prescription fulfillment. The continuous unfolding of market activities necessitates ongoing attention to drug safety, regulatory compliance, and pricing strategies.

How is this Generic Drugs Industry segmented?

The generic drugs industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Route Of Administration

  Oral
  Injectables
  Topical
  Inhalers


Type

  Small-molecule generics
  Biosimilars


Application

  Anti-infectives
  CNS
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

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By Route Of Administration Insights

The oral segment is estimated to witness significant growth during the forecast period

The oral route of administration is the most commonly used. Oral administration is the ingestion of a drug through the mouth into the gastrointestinal tract. The oral drug delivery system market segment includes drugs that can be administered in the form of capsules, tablets, syrups, solutions, and suspensions. The growth of the segment is accelerating at a moderate pace due to the ease of usage and an increasing number of companies investing in research and development for oral treatment. The advantages provided by the oral route, such as better availability, rapid drug delivery, and high efficacy, are further expected to propel the growth of the oral segment, which, in turn, will drive the growth of the market during the forecast period.

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The Oral segment was valued at USD 232.00 billion in 2019 and showed a gradual increase during the forecast period.

Regional Analysis

North America is estimated to contribute 33% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

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The market in North America is experiencing significant growth,

BackgroundChina’s National Essential Medicines Policy (NEMP) has been implemented for over 15 years; yet empirical evidence on its long-term impacts is lacking, particularly in remote and rural regions. This study aims to assess the short-and long-term effects of NEMP on the drug availability, price, and usage in a deprived rural county in southwestern China.MethodsA quasi-experimental design was employed, featuring a single-group pre-and-post comparison. We gathered 74,436 procurement records spanning from 2009 to 2016 from the drug warehouses of local medical institutions. Pharmaceutical data were analyzed quarterly, considering various policy and therapeutic attributes. Fisher’s Drug Price Index (DPI-F) was calibrated for the retail and wholesale prices of a consistent collection of 405 medications. We conducted interrupted time-series analysis to examine the immediate and enduring impacts of NEMP’s initial (commencing in January 2011) and second (starting from December 2015) stages.ResultsAfter initiation of NEMP, the number of available essential medicines surged by 115 but subsequently faced a steady quarterly decline (−9.1) in township healthcare centers (THCs, primary care). Conversely, county hospitals (secondary care) initially saw a reduction of 40 in drug availability but later exhibited a steady increase (+4.2 per quarter) up to the second-stage NEMP. Regarding price, THCs encountered abrupt (−26.1%/−15.9% in retail/wholesale price) and sustained (−0.2%/−0.3% per quarter) price drops after NEMP. The immediate price change after NEMP in county hospitals were milder but significant in non-essential medicines, and long-term declines were also observed in all drugs. As for total sales, a significant long-term disparity emerged between THCs (+0.9% per quarter) and county hospitals (+3.3% per quarter). Following the second-stage NEMP, retail prices in county hospitals further decreased, although wholesale prices did not; however, following price upward trends were observed in both THCs and county hospitals. Lastly, the influences of NEMP varied across different therapeutical categories of medicines.ConclusionNEMP has successfully regulated drug prices in primary and secondary healthcare facilities in remote and rural areas, both short-term and long-term. However, a remarkable disparity in medicine availability and utilization was observed between different levels of facilities over time. Continuous monitoring is essential, with increased attention needed on the uneven impacts of the policy on diverse drugs, facilities, regions, and demographics.

United States CPI U: AW: Medical Care: CO: MD: Prescription Drugs data was reported at 1.443 % in 2017. This records an increase from the previous number of 1.434 % for 2016. United States CPI U: AW: Medical Care: CO: MD: Prescription Drugs data is updated yearly, averaging 1.333 % from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 1.443 % in 2017 and a record low of 1.253 % in 2010. United States CPI U: AW: Medical Care: CO: MD: Prescription Drugs data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s USA – Table US.I011: Consumer Price Index: Urban: Weights (Annual).