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Collection and analysis of longitudinal pharmacy refill data from manual registers: Experiences from Ugandan public health systems Joshua Kayiwa INRUD-IAA, Uganda

Joshua Kayiwa INRUD-IAA, Uganda

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Collection and analysis of longitudinal pharmacy refill data from manual registers: Experiences from Ugandan public health systems. Joshua Kayiwa INRUD-IAA, Uganda. Session Objectives. - PowerPoint PPT Presentation

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Page 1: Joshua  Kayiwa INRUD-IAA, Uganda

Collection and analysis of longitudinal pharmacy refill data

from manual registers: Experiences from Ugandan public health

systems

Joshua KayiwaINRUD-IAA, Uganda

Page 2: Joshua  Kayiwa INRUD-IAA, Uganda

Session Objectives

Narrate the experience of the Uganda INRUD-IAA team in collecting, cleaning, summarizing and analyzing manually recorded pharmacy refill data for longitudinal research

Make recommendations for similar longitudinal studies in the African health systems context

Page 3: Joshua  Kayiwa INRUD-IAA, Uganda

Brief BackgroundMost public health systems in low and middle

income countries maintain patients’ treatment data in manual registers

Mainly due to constraints in technological, financial and human resource capacity to design and maintain appropriate Electronic Medical Record Systems (EMRs)

Has implications for data security, availability, accessibility, accuracy, completeness, and the ease of using such data to study policy impacts

Page 4: Joshua  Kayiwa INRUD-IAA, Uganda

Background to INRUD-IAA StudyDesigned as a longitudinal staggered entry interventional

study among six public health facilities in Uganda

Aim was to investigate the extent to which low-cost interventions meant to reduce clinic congestion, implemented at health facility level would improve patients’ individual-level adherence to antiretroviral therapy (ART) Results in press and also presented elsewhere in this ICIUM

meeting

Collected pharmacy-refill information for evaluation Appointment dates, actual visit dates, numbers of pills dispensed 720 ART-experienced and 761 patients newly initiating ART for

six months pre-intervention and nine months post-intervention

Page 5: Joshua  Kayiwa INRUD-IAA, Uganda

Where Were Raw Data Found?

• Longitudinal patient-level data in clinical records, diaries, pharmacy, appointment registers

• Manually filled and kept at facility or with patients

Page 6: Joshua  Kayiwa INRUD-IAA, Uganda

What Were We Trying to Measure? Key study outcomes :

% of experienced patients with >30 days of dispensed medication

% of experienced patients missing any scheduled visit

% of experienced patients with 3 or more days without medication

Time until newly-treated patients experienced a medication gap of >7 or >14 days during first 120 days of treatment

Page 7: Joshua  Kayiwa INRUD-IAA, Uganda

Challenges with Collecting Data from Manual Registers and Diaries

Data availabilityHealth workers only record what they think they need to

administer today’s treatmentData often missing, e.g., # of pills dispensed, patients’ CD4 and

viral load history

Data accessibility and securityHard to access, especially for patient diariesDiaries prone to wear and tear due to mishandlingPages may tear out or be destroyed by cockroaches / mould

Data accuracy and reliabilityData not protected against entry errors Cannot be verified against secondary sources.

Page 8: Joshua  Kayiwa INRUD-IAA, Uganda

Managing Longitudinal Data Collected from Manual Registers

Data collected and recorded using a standard tool by trained research assistants

Data entry and validationCustomized double entry data input and validation using MS ExcelFurther quality checks in Stata before analysis

Page 9: Joshua  Kayiwa INRUD-IAA, Uganda

Summarizing the DataUsing appointment

and visit dates and days of medication dispensed, we computed: % of patients receiving

more than 30 days of medication

Number of days by which patient missed any visit (see graph)

Gaps medication availability between appointments

Page 10: Joshua  Kayiwa INRUD-IAA, Uganda

Key Findings (manuscript in press)Among experienced patients,

interventions led to Significant two-fold increase in

patients receiving >30 days of dispensed medication

Significant 33% reductions of missed appointments

Significant 31% reductions of experiencing a medication gap of 3+ days

Among newly treated patients, interventions associated with Significant 44% reduction in

hazard of experiencing medication gap of >7 days (see graph)

Significant 38% reduction medication gap of >14 days

Page 11: Joshua  Kayiwa INRUD-IAA, Uganda

Aim Achieved?We aimed to

determine whether interventions to reduce clinic congestion, improve patient flow and if this would translate into better ART adherence.

Using routine data from manual clinic records, we were able to measure increases in days of medication dispensed, reductions in missed visits, and fewer medication gaps among ART patients.

Page 12: Joshua  Kayiwa INRUD-IAA, Uganda

Lessons Learnt and RecommendationsIt is possible to collect pharmacy refill records from

manual registers in African health facilitiesMany challenges: especially data completeness,

accuracy, security and reliability

RecommendationsManual pharmacy registers and clinical records safer

when kept at the health facility than with patientsMore attention to staff training in record keepingUnless staff see data used for clinical care, management,

or research, they have no incentive to record accuratelyPharmacy refill records should ideally be kept

electronically, whenever resources (human and financial) allow

Page 13: Joshua  Kayiwa INRUD-IAA, Uganda

Thanks Very Much