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20200730_服薬アドヒアランスを評価する

d.sat0
October 24, 2021
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 20200730_服薬アドヒアランスを評価する

d.sat0

October 24, 2021
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  1. 服薬アドヒアランスを評価する 2020.07.30 d.sat0

  2. claimデータを使って 服薬アドヒアランスを評価しよう

  3. 服薬アドヒアランスとは (medication adherence )

  4. コンプライアンス 医療者が治療⽅針を決定し、患者がそれに従う⾏動をとること アドヒアランス 患者が治療に対して積極的・前向きな考えをもつこと コンコーダンス 患者の考えと医療者の考えが⼀致するように、両者の考えを尊重しあうこと Bond C.: Concordance: A

    partnership in medicine-taking(Concordance 1st Edition); Pharmaceutical Press, the publishing division of the Royal Pharmaceutical Society of Great Britain, London UK, 2004 /岩堀平 ⾨ ・ラリー・フラムソン( 訳 ):なぜ,患者は薬を 飲まないのか?,薬事⽇報社,東京 , 2010
  5. コンプライアンス 患者が医師の処⽅に従い、薬をきちんと飲むこと アドヒアランス ⾃ら納得した上で薬をきちんと飲むこと コンコーダンス 処⽅薬決定の段階から患者の意思が反映 Bond C.: Concordance: A

    partnership in medicine-taking(Concordance 1st Edition); Pharmaceutical Press, the publishing division of the Royal Pharmaceutical Society of Great Britain, London UK, 2004 /岩堀平 ⾨ ・ラリー・フラムソン( 訳 ):なぜ,患者は薬を 飲まないのか?,薬事⽇報社,東京 , 2010
  6. 服薬アドヒアランス 服薬コンプライアンス 厳密には違うけど、今回は・・

  7. アドヒアランス悪い⼈ そんなにいるの︖

  8. ADHERENCE TO LONG-TERM THERAPIES Evidence for action World Health Organization

    2003 慢性疾患に対する⻑期治療の良好な アドヒアランスは先進国で平均50% (発展途上国ではさらに低い)。 これはpopulation healthにおいて ⼤きな問題だ︕ “ADHERENCE TO LONG-TERM THERAPIES: EVIDENCE FOR ACTION” World Health Organization 2003
  9. ISPOR(International Society for Pharmacoeconomics and Outcomes Research)のHP https://www.ispor.org/member-groups/special-interest-groups/medication-adherence-and-persistence Special Interest

    GroupにMedication Adherenceあり
  10. なぜ患者は 服薬を遵守しないのか

  11. Understanding Medication Compliance and Persistence from an Economics Perspective Rachel

    A. Elliott, BPharm, MRPharmS, PhD,1 Judith A. Shinogle, PhD, MSc,2 Pamela Peele, PhD,3 Monali Bhosle, MS, PhD Candidate,4 Dyfrig A. Hughes, BPharm, MSc, PhD, MRPharmS5 1School of Pharmacy,The University of Nottingham, University Park, Nottingham, UK; 2Department of Health Services Administration, University of Maryland, College Park, MD, USA; 3UPMC Health Plan, Pittsburgh, PA, USA; 4Division of Pharmacy Practice and Administration, Ohio State University, Columbus, OH, USA; 5Centre for Economics and Policy in Health, Bangor University, Bangor, UK ABSTRACT Objectives: An increased understanding of the reasons for noncompliance and lack of persistence with prescribed medi- cation is an important step to improve treatment effective- ness, and thus patient health. Explanations have been attempted from epidemiological, sociological, and psycho- logical perspectives. Economic models (utility maximization, time preferences, health capital, bilateral bargaining, stated preference, and prospect theory) may contribute to the under- standing of medication-taking behavior. Methods: Economic models are applied to medication non- compliance. Traditional consumer choice models under a budget constraint do apply to medication-taking behavior in that increased prices cause decreased utilization. Neverthe- less, empiric evidence suggests that budget constraints are not the only factor affecting consumer choice around medicines. Examination of time preference models suggests that the retical relevance, but has not been applied to compliance. Bilateral bargaining may present an alternative model to concordance of the patient–prescriber relationship, taking account of game-playing by either party. Nevertheless, there is limited empiric evidence to test its usefulness. Stated pref- erence methods have been applied most extensively to medi- cines use. Results: Evidence suggests that patients’ preferences are con- sistently affected by side effects, and that preferences change over time, with age and experience. Prospect theory attempts to explain how new information changes risk perceptions and associated behavior but has not been applied empirically to medication use. Conclusions: Economic models of behavior may contribute to the understanding of medication use, but more empiric work is needed to assess their applicability. Volume 11 • Number 4 • 2008 V A L U E I N H E A L T H Table 1 The relationship of economic models to the various forms of (non)compliance Concordance Initial prescription fill Compliance Persistence Supply and demand    Bilateral bargaining  Human Capital Model    Prospect theory    Stated preference     Time preference    Applying Economic Models to Compliance 607 ISPORのworking groupが⾏動経済学の観点で考察
  12. アドヒアランスは どのように評価するのか

  13. と、その前に⽤語の整理

  14. Raebel MA, Schmittdiel J, Karter AJ, Konieczny JL, Steiner JF.

    Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases. Med Care. 2013;51(8 Suppl 3):S11-S21. 新しい処⽅がされてから、あらかじめ定義した 期間までに薬を受けとるかどうか Primary Adherence 初回調剤後、定められた⽇数以内に次の処⽅を 充填したかどうか(いわゆるアドヒアランス) Secondary Adherence Adherence ※ 論⽂によって表現はいろいろ。
  15. ⽇本における処⽅箋の有効期限は 発⾏⽇を含めて4⽇間(⽇曜⽇や祝⽇を含む) 保険医療機関及び保険医療養担当規則(療担規則)第20条の3(⻭科の場合は第21条の3) 【カナダ ブリティッシュコロンビア州】 • ⼀般的な処⽅箋︓1年間 • 特定の⿇薬処⽅箋︓5⽇間 •

    経⼝避妊薬︓2年間有効 もちろん、国により異なります
  16. • Cramer JA, Roy A, Burrell A, et al. Medication

    compliance and persistence: terminology and definitions. Value Health. 2008;11(1):44-47. doi:10.1111/j.1524-4733.2007.00213. • Peterson AM, Nau DP, Cramer JA, Benner J, Gwadry-Sridhar F, Nichol M. A checklist for medication compliance and persistence studies using retrospective databases. Value Health. 2007;10(1):3-12. • Parker MM, Moffet HH, Adams A, Karter AJ. An algorithm to identify medication nonpersistence using electronic pharmacy databases. J Am Med Inform Assoc. 2015;22(5):957-961. “ the duration of time from initiation to discontinuation of therapy ” Medication persistence 処⽅が終了してからどの程度間が空いたら中断したかという定義 (permissible gap)をあらかじめ設定しなければならない。 許容できる⽇数は病態によるので、⾃分で決める。 ※ 58件の研究のレビューでは、 permissible gapは7⽇から180⽇までと⾮常にばらつきがあり、中央値は30⽇であった。
  17. アドヒアランスは どのように評価するのか

  18. Direct Measures Osterberg L, Blaschke T. Adherence to medication. N

    Engl J Med. 2005;353(5):487-497. drug therapy Table 1. Methods of Measuring Adherence. Test Advantages Disadvantages Direct methods Directly observed therapy Most accurate Patients can hide pills in the mouth and then discard them; impracti- cal for routine use Measurement of the level of medicine or metabolite in blood Objective Variations in metabolism and “white- coat adherence” can give a false impression of adherence; ex- pensive Measurement of the biologic marker in blood Objective; in clinical trials, can also be used to measure placebo Requires expensive quantitative as- says and collection of bodily fluids Indirect methods Patient questionnaires, patient self-reports Simple; inexpensive; the most useful method in the clinical setting Susceptible to error with increases in time between visits; results are easily distorted by the patient Pill counts Objective, quantifiable, and easy to perform Data easily altered by the patient (e.g., pill dumping)
  19. Indirect Measures Adherence to medication. N Engl J Med. 2005;353(5):487-497.

    40 Measurement of the level of medicine or metabolite in blood Objective Variations in metabolism and “white- coat adherence” can give a false impression of adherence; ex- pensive Measurement of the biologic marker in blood Objective; in clinical trials, can also be used to measure placebo Requires expensive quantitative as- says and collection of bodily fluids Indirect methods Patient questionnaires, patient self-reports Simple; inexpensive; the most useful method in the clinical setting Susceptible to error with increases in time between visits; results are easily distorted by the patient Pill counts Objective, quantifiable, and easy to perform Data easily altered by the patient (e.g., pill dumping) Rates of prescription refills Objective; easy to obtain data A prescription refill is not equivalent to ingestion of medication; re- quires a closed pharmacy system Assessment of the patient’s clinical response Simple; generally easy to perform Factors other than medication adher- ence can affect clinical response Electronic medication monitors Precise; results are easily quantified; tracks patterns of taking medication Expensive; requires return visits and downloading data from medica- tion vials Measurement of physiologic markers (e.g., heart rate in patients taking beta-blockers) Often easy to perform Marker may be absent for other rea- sons (e.g., increased metabol- ism, poor absorption, lack of response) Patient diaries Help to correct for poor recall Easily altered by the patient When the patient is a child, question- naire for caregiver or teacher Simple; objective Susceptible to distortion drug therapy Table 1. Methods of Measuring Adherence. Test Advantages Disadvantages Direct methods Directly observed therapy Most accurate Patients can hide pills in the mouth and then discard them; impracti- cal for routine use Measurement of the level of medicine or metabolite in blood Objective Variations in metabolism and “white- coat adherence” can give a false impression of adherence; ex- pensive Measurement of the biologic marker in blood Objective; in clinical trials, can also be used to measure placebo Requires expensive quantitative as- says and collection of bodily fluids Indirect methods Patient questionnaires, patient self-reports Simple; inexpensive; the most useful method in the clinical setting Susceptible to error with increases in time between visits; results are easily distorted by the patient Pill counts Objective, quantifiable, and easy to perform Data easily altered by the patient (e.g., pill dumping) Rates of prescription refills Objective; easy to obtain data A prescription refill is not equivalent to ingestion of medication; re- quires a closed pharmacy system Assessment of the patient’s clinical response Simple; generally easy to perform Factors other than medication adher- ence can affect clinical response Electronic medication monitors Precise; results are easily quantified; Expensive; requires return visits and secondary databaseを利⽤
  20. secondary databaseでの アドヒアランス指標は︖

  21. Primary Adherence Secondary Adherence Based on Medication Possession • Medication

    Possession Ratio (MPR) • Proportion of Days Covered (PDC) Based on Medication Gaps • New Prescription Medication Gap (NPMG) • Continuous measure of Medication Gaps (CMG) 調剤された処⽅数/観察期間中の新規処⽅数 ※これ以外にもいくつかあります。
  22. Medication Possession Ratio (MPR) 𝑴𝑷𝑹 = 𝑻𝒐𝒕𝒂𝒍 𝑫𝒂𝒚!𝒔 𝑺𝒖𝒑𝒑𝒍𝒚 𝒊𝒏

    𝑷𝒆𝒓𝒊𝒐𝒅 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑫𝒂𝒚𝒔 𝒊𝒏 𝑷𝒆𝒓𝒊𝒐𝒅 観察期間中の処⽅⽇数合計 観察期間(本来内服すべき⽇数) • 分⼦が処⽅⽇数の合計なので、早めに処⽅を受けた場合は100% を超える可能性あり。ただ、過剰使⽤を検出することはできる。 • 複数の薬剤が処⽅されている場合、各薬剤の平均値で求めるので、 MPRが⾼いものに引っ張られる。
  23. • 処⽅がカバーされていた⽇を分⼦にしているので、早めに処⽅さ れた場合、その分は別で考える。 • 「カバーされているかどうか」を⾒るので100%は超えない。 • 複数薬剤レジメンの場合、平均値ではなく、全ての薬剤がカバー されている⽇のみを有効と考える。 Proportion of

    Days Covered (PDC) 𝑷𝑫𝑪 = 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑫𝒂𝒚𝒔 𝒊𝒏 𝑷𝒆𝒓𝒊𝒐𝒅 ”𝒄𝒐𝒗𝒆𝒓𝒅” 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑫𝒂𝒚𝒔 𝒊𝒏 𝑷𝒆𝒓𝒊𝒐𝒅 処⽅⽇数がカバーしていた期間 観察期間(本来内服すべき⽇数)
  24. わかりにくいので 図で考えてみます。

  25. Drug A=30⽇×8 Drug B=30⽇×8 →480⽇ Drug AとDrug Bが処⽅されている =30⽇×6 →180⽇

    Challenges of achieving effective glycemic control in type 2 diabetes Vol 39, No. 3, 2017,132 Medicographia A Servier publication 1.0を超えた場合の取り 扱いは⾃分で決める
  26. 観察終了をいつまでにするかは⾃分で決める。PDCもそれで変わってくる。 最終処⽅⽇(この場合、day182)にするか、最終処⽅+処⽅⽇数にするかなど。 カバーされているので、 1.0は超えない 重複している⽇(⿊)を不⾜している⽇(グレー) に前倒しできる “Medica(on Adherence: Defini(ons, Calcula(ons,

    and Sta(s(cal Modeling Strategies” By Joshua Joseph DeClercq Thesis SubmiCed to the Faculty of the Graduate School of Vanderbilt University in par(al fulfillment of the requirements for the degree of MASTER OF SCIENCE in Biosta(s(cs August 10, 2018 Nashville, Tennessee
  27. Continuous measure of Medication Gaps (CMG) (観察期間総⽇数 - 累積処⽅⽇数)/ 観察期間総⽇数

    New Prescription Medication Gap (NPMG) • CMGの観察期間の考え⽅を拡張 • 最初に処⽅されてから追跡調査が終了するまでの期間、 別の治療法に切り替えるまでの期間、薬物療法が中⽌さ れるまでの期間 Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases. Med Care. 2013;51(8 Suppl 3):S11-S21.
  28. 結局、どれがいいの︖

  29. Volume 10 • Number 1 • 2007 V A L

    U E I N H E A L T H Blackwell Publishing IncMalden, USAVHEValue in Health1098-30152006 Blackwell Publishing2007101312Original ArticleChecklist for Medication Compliance StudiesPeterson et al. A Checklist for Medication Compliance and Persistence Studies Using Retrospective Databases Andrew M. Peterson, PharmD,1 David P. Nau, PhD,2 Joyce A. Cramer, BS,3 Josh Benner, PharmD, ScD,4 Femida Gwadry-Sridhar, PhD, RPh, MSc, BSc,5 Michael Nichol, PhD6 1University of the Sciences in Philadelphia, Philadelphia, PA, USA; 2University of Michigan, Ann Arbor, MI, USA; 3Yale University, West Haven, CT, USA; 4ValueMedics Research, LLC, Falls Church, VA, USA; 5McMaster University, London, ON, Canada; 6University of Southern California, Los Angeles, CA, USA ABSTRACT The increasing number of retrospective database studies related to medication compliance and persistence (C&P), and the inher- ent variability within each, has created a need for improvement in the quality and consistency of medication C&P research. This article stems from the International Society of Pharmacoeconom- ics and Outcomes Research (ISPOR) efforts to develop a check- list of items that should be either included, or at least considered, when a retrospective database analysis of medication compliance or persistence is undertaken. This consensus document outlines a systematic approach to designing or reviewing retrospective database studies of medication C&P. Included in this article are discussions on data sources, measures of C&P, results reporting, and even conflict of interests. If followed, this checklist should improve the consistency and quality of C&P analyses, which in turn will help providers and payers understand the impact of C&P on health outcomes. Keywords: compliance, guidelines, persistence, retrospective databases. ISPORのチェックリスト(2007年)には、 どれがベストかという記述はない。 「MPRやPDC、CMGなどがありますー」という書き⽅。 Peterson AM, Nau DP, Cramer JA, Benner J, Gwadry-Sridhar F, Nichol M. A checklist for medica(on compliance and persistence studies using retrospec(ve databases. Value Health. 2007;10(1):3-12. doi:10.1111/j.1524-4733.2006.00139.x
  30. Proportion of Days Covered (PDC) as a Preferred Method of

    Measuring Medication Adherence By: David P. Nau, RPh, PhD, CPHQ Senior Director, Research & Performance Measurement Pharmacy Quality Alliance Source: http://www.pqaalliance.org/files/PDCvsMPRfinal.pdf Background The Pharmacy Quality Alliance (PQA) has developed, tested and endorsed numerous measures of medication-use quality. PQA members identified medication adherence as an important component of medication-use quality, and therefore PQA sought to endorse a standard method for calculation of medication adherence using data that would be widely available across prescription drug plans and pharmacies. After reviewing the extant literature and conducting tests of draft measure specifications, PQA chose to endorse the method known as Proportion of Days Covered (PDC). Review of Methods for Adherence Measurement N me o me hod ha e been ili ed o e ima e pa ien adhe ence to a medication regimen. Since PQA sought a method that could be derived from drug claims data, the review of methods focused on PQA(Pharmacy Quality Alliance)は PDCがアドヒアランス評価に良い指標と宣⾔した(2012年) 80%以上をアドヒアランス良好(レトロウイルス治療薬は90%以上)
  31. Fact Sheet - 2020 Part C and D Star Ratings

    ※ MA-PD︓Medicare Advantage with prescription drug coverage Star Ratingでアドヒアランスも評価対象 https://www.cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCovGenIn/Downloads/2020-Star-Ratings-Fact-Sheet-.pdf
  32. https://www.pharmacyquality.com/wp-content/uploads/2019/10/PQSMedicareStarRatingsUpdate2020.pdf PQS Summary of 2020 Medicare Part C and D

    Star Ratings Technical Notes PDCで評価している
  33. PDC が無難

  34. 他に注意する点は︖

  35. 薬を切り替えた場合 確⽴した回答はない。 同じ系統ならOKなのか(例︓スタチン間での変更)、ブランド変更時(先発 →後発)はOKとするかなど、あらかじめ定義しておく。 基本的に経⼝薬のみ ⾮経⼝薬や⽤量調整をする薬(例︓ワルファリン)では信頼性が落ちる。 Coming full circle in

    the measurement of medication adherence: opportunities and implications for health care. Patient Prefer Adherence. 2017;11:1009-1017. Published 2017 Jun 2.
  36. 基本的に慢性疾患を対象とする 6ヶ⽉あるいは12ヶ⽉以上継続している薬で評価をする。 Standardizing terminology and definitions of medication adherence and

    persistence in research employing electronic databases. Med Care. 2013;51(8 Suppl 3):S11-S21. 処⽅の出し⽅でアドヒアランスが変わることは理解しておく 30⽇処⽅を受けた患者は90⽇処⽅を受けた患者よりもMPRが14%低い。 Medication days' supply, adherence, wastage, and cost among chronic patients in Medicaid. Medicare Medicaid Res Rev. 2012;2(3):mmrr.002.03.a04. Published 2012 Sep 1 claimデータなので必ずしも内服しているとは限らない
  37. STATAやR、SASでできる︖

  38. Paper 043-2007 Using Arrays to Calculate Medication Utilization R. Scott

    Leslie, MedImpact Healthcare Systems, Inc., San Diego, CA ABSTRACT Assessing duration of medication therapy involves managing a data set with multiple observations per subject. This paper offers an innovative approach to calculating medication utilization as the proportion of days supplied over a specified time period. In this paper, the TRANSPOSE procedure, ARRAY statements, and DO loops are used to create multiple indicator variables, which are then used to calculate medication utilization. Variations of this code can integrate gaps and overlaps in therapy and can be used in calculating concomitant medication utilization. INTRODUCTION Many health outcomes related to pharmacy utilization involve length of therapy measurements. The purpose of this paper is to offer code that calculates a patient’s medication utilization as the proportion of days medication is supplied over a time period. This code is a helpful start for building code to calculate additional outcome measures such as compliance, adherence, and persistence. EXAMPLE 1: PROPORTION OF DAYS MEDICATION SUPPLIED This example uses a pharmacy claims data set that has multiple observations per patient. The steps below calculate the number of days a single drug is supplied over a 180-day study period, with the date of first claim as the first day of study period. A cut of the data set shows 3 claims for a patient. SAS Global Forum 2007 Coders’ Corner SASのcodeはあるそうです。が、私にはわかりません。 https://support.sas.com/resources/papers/proceedings/proceedings/forum2007/043-2007.pdf
  39. R は AdhereR packageでできるそうです https://cran.r-project.org/web/packages/AdhereR/vignettes/AdhereR-overview.html CMA1-8 (continuous multiple interval measures

    of medication availability/gaps) をだせます。
  40. Study design and research setting We report data collected as

    part of a randomized clinical trial of members of the Northwest (KPNW) and Hawai‘i We compare eight alternative measures of adherence, which we label CMA1-CMA8 (Table 1). Some of these are classical CMA-type measures and some are derived Table 1 Summary of study measures Defn start of window to first dispensing last dispensing to end of window Timing^ Description of Measure CMA1 ignored ignored ignored (# days dispensed, excluding last) / (first to last dispensing) CMA2 ignored counted ignored (# days dispensed, including last) / (first dispensing to end of window) CMA3 ignored ignored ignored minimum (CMA1, 1) CMA4 ignored counted ignored minimum (CMA2, 1) CMA5 ignored ignored counted (# days theoretical use#) / (first to last dispensing) CMA6 ignored counted counted (# days theoretical use#) / (first dispensing to end of window) CMA7 counted counted counted (# days theoretical use#) / (start to end of observation window), includes in numerator meds carried into observation window CMA8 counted counted counted (# days theoretical use#) / (lagged* start of obs’n window to end of window), numerator and denominator ignore intial lag period ^refers to whether the timing of the dispensing (actual date dispensed) is taken into account in the calculations or is ignored. #assumes medications taken as directed and new medications “banked” until needed. *lag refers to initial period covered by medication supply on hand at start of observation window. Medications dispensed during lag interval are “banked” and counted starting with end of lag. 基本は累積処⽅⽇数/観察期間総⽇数 観察期間をどこまでにするか、100%を超えたら どうするかなどの違いでCMA1-8まである。 CMA (continuous multiple interval measures of medication availability/gaps) Vollmer WM, Xu M, Feldstein A, Smith D, Waterbury A, Rand C. Comparison of pharmacy-based measures of medication adherence. BMC Health Serv Res. 2012;12:155. Published 2012 Jun 12.
  41. Assessing Medication Adherence Using Stata Ariel Linden Linden Consulting Group,

    LLC San Francisco, CA, USA alinden@lindenconsulting.org Abstract. In this article I introduce the medadhere package, which computes medication adherence rates for two commonly-used measures in research and practice -- the medication possession ratio (MPR) and proportion of days covered (PDC). medadhere computes adherence rates for a single medication or multiple medications, and its options provide great flexibility to support the specific needs of the user. Keywords: medication adherence, medication compliance, medication possession ratio, proportion of days covered, pharmacy claims 1 Introduction While most patients leave the doctor’s office with a medication prescription, many fail to take their medication as prescribed. According to the World Health Organization, medication adherence (also referred to as compliance) rates in developed countries average only about 50 percent (Sabaté The Stata Journal. Volume: 19 issue: 4, page(s): 820-831 STATA Journalに載ってました
  42. A single patient on a single medication A single patient

    on multiple medications MPRとPDCを出してくれる
  43. Multiple patients on a single medication Multiple patients on multiple

    medications
  44. 閾値を決めて(80%)クロス集計も作れます

  45. 今⽇のまとめ

  46. 服薬アドヒアランスの指標はMPRとPDCがよく使われる PDCを使うのが無難 STATA、R、SASでcodeがある