FINANCING AND AVAILABILITY OF ESSENTIAL MEDICINES …pharm-school.uonbi.ac.ke/sites/default/files/chs/pharm... · · 2014-12-19financing and availability of essential medicines

FINANCING AND AVAILABILITY OF ESSENTIAL MEDICINES

BEFORE AND AFTER INTRODUCTION OF THE NATIONAL

HOSPITAL INSURANCE FUND CIVIL SERVANTS AND

DISCIPLINED SERVICES MEDICAL SCHEME: A CASE STUDY

OF WEBUYE DISTRICT HOSPITAL, WESTERN KENYA

BY

LUCY WINKIE MECCA, BPHARM

U51/63523/2013

A thesis submitted in partial fulfillment of the requirements for the award of

the degree of Master of Pharmacy in Pharmacoepidemiology &

Pharmacovigilance

DEPARTMENT OF PHARMACOLOGY AND PHARMACOGNOSY

UNIVERSITY OF NAIROBI

NOVEMBER, 2014

i

DECLARATION

This thesis is my original work and has not been presented for a degree in any other university

Mecca Lucy Winkie Signature………………………. Date………………………

This thesis has been submitted with our approval as university supervisors.

Dr. Eric M. Guantai Signature………………………. Date………………………

Department of Pharmacology and Pharmacognosy

School of Pharmacy

College of Health Sciences

University of Nairobi

Dr. James Riungu Signature………………………. Date………………………

Senior Technical Advisor- Commodity Security

Jhpiego – Affiliate of Johns Hopkins University

KURHI/Tupange program

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DECLARATION OF ORIGINALITY FORM

Name of student: Mecca, Lucy Winkie

Registration number: U51/63523/2013

College: Health Sciences

Faculty: Pharmacy

Department: Pharmacology and Pharmacognosy

Course Name: Master of Pharmacy- Pharmacovigilance and Pharmacoepidemiology

Title of work: Financing and availability of essential medicines before and after introduction of the

National Hospital Insurance Fund Civil servants and Disciplined services medical scheme: a case

study of Webuye District Hospital

DECLARATION

1. I understand what plagiarism is and I am aware of the University’s policy in this regard.

2. I declare that this thesis is my original work and has not been submitted elsewhere for

examination, award of a degree or publication. Where other people’s work or my work has been

used, this has properly been acknowledged and referenced in accordance with the University of

Nairobi’s requirements.

3. I have not sought or used the services of any professional agencies to produce this work.

4. I have not allowed, and shall not allow anyone to copy my work with the intention of passing it

off as his/her own work

5. I understand that any false claim in respect of this work shall result in disciplinary action, in

accordance with University Plagiarism Policy

Signature…………………...

Date.............................

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ACKNOWLEDGEMENT

I would like first and foremost like to thank God who performs all things for me.

I would like to thank my supervisors Dr. Eric M. Guantai and Dr. James Riungu for their invaluable

and gracious input.

I would also like to thank the staff at Webuye District Hospital, particularly the Medical

Superintendent-Dr. Caesar Bitta, pharmacists-Dr. Martha Mandale, Dr. Lidya Anyanzwa, Dr.

Ferdinand Ndubi and all pharmacy staff for their selfless assistance.

I am also grateful to my friend Mercy Mulaku for her generous input.

I would also like to acknowledge my classmates who were instrumental in bringing this thesis to

completion.

I would also like to appreciate my employer who gave me leave to do this work.

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Table of Contents

DECLARATION ........................................................................................................................................... i

DECLARATION OF ORIGINALITY FORM ............................................................................................. ii

ACKNOWLEDGEMENT ........................................................................................................................... iii

LIST OF TABLES ...................................................................................................................................... vii

LIST OF FIGURES ................................................................................................................................... viii

LIST OF APPENDICES.............................................................................................................................. ix

OPERATIONAL DEFINITION OF TERMS............................................................................................... x

ABBREVIATIONS .................................................................................................................................... xii

ABSTRACT................................................................................................................................................xiii

CHAPTER 1: INTRODUCTION .................................................................................................................1

1.1 BACKGROUND ................................................................................................................................1

1.2 PROBLEM STATEMENT .................................................................................................................5

1.3 JUSTIFICATION ...............................................................................................................................6

1.4 RESEARCH QUESTIONS.................................................................................................................6

1.5 NULL HYPOTHESES .......................................................................................................................7

1.6 OBJECTIVES ..................................................................................................................................... 7

1.6.1 Main Objective.............................................................................................................................7

1.6.2 Specific Objectives ......................................................................................................................7

CHAPTER 2: LITERATURE REVIEW ...................................................................................................... 8

2.1 INTRODUCTION ..............................................................................................................................8

2.2 HEALTH INSURANCE.....................................................................................................................8

2.2.1 Health Insurance and medicines .................................................................................................. 9

2.2.2 Moral Hazard ...............................................................................................................................9

2.3 CASE STUDIES OF INSURANCE SCHEMES AND IMPACT ON MEDICINES ......................10

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2.3.1 China ..........................................................................................................................................10

2.3.2 Thailand .....................................................................................................................................10

2.3.3 Mexico .......................................................................................................................................11

2.3.4 Tanzania .....................................................................................................................................12

2.3.5 Nigeria........................................................................................................................................12

2.3.6 Ghana .........................................................................................................................................13

2.3.7 Kenya .........................................................................................................................................13

2.3 CONCEPTUAL FRAMEWORK .....................................................................................................14

CHAPTER 3: METHODOLOGY ..............................................................................................................16

3.1 STUDY DESIGN..............................................................................................................................16

3.2 LOCATION OF STUDY..................................................................................................................16

3.3 DATA COLLECTION .....................................................................................................................16

3.4 DATA ANALYSIS...........................................................................................................................20

3.5 LIMITATIONS .................................................................................................................................21

3.6 ASSUMPTION .................................................................................................................................21

3.7 ETHICAL CONSIDERATIONS AND APPROVAL ......................................................................22

CHAPTER 4: RESULTS ............................................................................................................................23

4.1 Allocation of FIF before and after the introduction of the NHIF civil servants scheme ..................23

4.1.1. Quarterly allocation of funds for purchase of medicines from the FIF (Absolute amounts) ....23

4.1.2 Proportion of total FIF allocated quarterly for purchase of medicines ......................................25

4.2 Contributors to the Essential Medicines Budget ...............................................................................25

4.2.1 Proportion of essential medicines procured through KEMSA, FIF and Other Facility .............26

4.2.2 Expenditure on essential medicines procured through KEMSA, FIF and Other Facility ..........28

4.2.3 Efficiency ...................................................................................................................................30

4.3 Availability of essential medicines ...................................................................................................31

4.3.1 Monthly stock-out time (%) .......................................................................................................31

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4.3.2 Stock-out rate per essential medicine.........................................................................................34

4.4 Analysis for factors that influence stock-out rate .............................................................................36

4.4.1 Monthly data- Autoregressive Integrated Moving Average ......................................................36

4.4.2 Total days out of stock- Negative binomial regression..............................................................37

CHAPTER 5: DISCUSSION......................................................................................................................39

CONCLUSION...........................................................................................................................................45

RECOMMENDATIONS ............................................................................................................................45

REFERENCES ...........................................................................................................................................46

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LIST OF TABLES

Table 3.1 : Summary table for methods……………………………………………………..…....….17

Table 4.1: Quarterly Percentage allocation of FIF for purchase of medicines……………............…25

Table 4.2: Results from within-source comparison of proportion of essential medicine procured….27

Table 4.3: Results from within- source comparison (expenditure).……………………………….…29

Table 4.4: Efficiency in number of units per Ksh - Summary statistics……………..…………...….30

Table 4.5: Monthly stock-out time (%) - Summary statistics……………………………….........….31

Table 4.6: Results from comparison of stock out rate of different months in a quarter…..……...….33

Table 4.7: Significant p-values for Wilcoxon Signed Rank Test for differences in stock out rates for

different classes of essential medicines………………………………………….……..……...…….33

Table 4.8: 20 essential medicines with highest and lowest stock-out rates in 2010-2013….………..35

Table 4.9: Significant p values for independent variables regressed with log of monthly % stock-out

time…………………………………………………..…………………………………..…...….…..37

Table 4.10 Significant p-values for independent variables regressed with total days out of

stock………………………………………………………………………………………………….38

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LIST OF FIGURES

Figure 1.1 The Access Framework…………….……………………………………………..…….…2

Figure 4.1 Quarterly FIF allocation for purchase of medicines-summary statistics ………..……….24

Figure 4.2 Mean proportion (%) of essential medicines procured and source……………...……….26

Figure 4.3 Mean expenditure on essential medicines by source………..………..………….……….28

Figure 4.4 Monthly average stock-out time (%)…………………………………….……….………32

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LIST OF APPENDICES

APPENDIX I- Data Collection Forms…………………………..……………………...……………52

APPENDIX II- Letter of Ethical Approval………………………………………………….………60

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OPERATIONAL DEFINITION OF TERMS

Essential Medicines- as defined by the World Health Organization are those medicines that satisfy

the priority health care need of the population. They are selected with due regard to disease

prevalence, evidence on efficacy and safety, and comparative cost-effectiveness.

For the purpose of the study, essential medicines are those that are common to the hospital draft

formulary and the Kenya Essential Medicines List.

Capitation-a fixed sum per person paid in advance of the coverage period to a healthcare entity in

consideration of its providing, or arranging to provide, contracted healthcare services to the eligible

person for the specified period

Cost Sharing- that portion of health care costs not borne by the funding agency (the government). It

includes all contributions, including cash, which a recipient makes towards health care.

District Hospital - A public hospital gazetted as such by the government, also known as a level 4 or

5 hospital. It is usually the referral hospital in a district.

Facility Improvement Fund - Cost sharing revenues which are additional to budget allocations

from the Treasury.

Fee-for-service: separate payment to a health-care provider for each medical service rendered to a

patient.

Fill-rate: Percentage of total order (by cost) that was supplied

Low, Middle and High Income Country-Economies are divided according to 2012 Gross National

Income per capita, calculated using the World Bank Atlas method. The groups are: low income,

$1,035 or less; lower middle income, $1,036 - $4,085; upper middle income, $4,086 - $12,615; and

high income,$12,616 or more.

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Out-of-pocket payments-include any direct payments made by patients to health care providers at

the point of use. These are also amounts which users are required to pay for health care that are

separate from any contributions to voluntary or mandatory insurance or through general taxation

Quarterly Pharmacy Budget: A quarterly expenditure plan for both non essential and essential

medicines at a district hospital.

Universal coverage-usually refers to a health care system which provides health care and financial

protection to all its citizens. It is organized around providing a specified package of benefits to all

members of a society with the end goal of providing financial risk protection, improved access to

health services, and improved health outcomes

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ABBREVIATIONS

AIE- Authority to Incur Expenditure

DDD-Daily defined dose

EEC- Executive expenditure committee

FIF-Facility Improvement Fund (Cost sharing)

HMT- Hospital Management Team

KEML- Kenya Essential Medicines List

KEMSA-Kenya Medical Supplies Agency

KSHS- Kenya Shillings

LMIC-Low and Middle Income Countries

MDG- Millennium Development Goal

MEDS- Mission For Essential Drugs and Supplies

MOH-Ministry of Health

NGO-Non-governmental organization

NHIF- National Hospital Insurance Fund

NHIS- National Hospital Insurance Scheme

NSHI-National Social Health Insurance Fund

UN-United Nations

WHO- World Health Organization

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ABSTRACT

Introduction

About 30% of the world’s population is estimated not to have access to essential medicines. Studies

done in Kenya have shown that public facilities experience stock-outs of basic essential medicines

for about 46 days per year.

One of the determinants of access to essential medicines is financing. Introduction of the National

Hospital Insurance Fund Civil Servants and Disciplined Services Medical Scheme affords additional

funding for a district hospital. Following this, it is expected that the stock-out rate of essential

medicines at Webuye District Hospital would reduce.

Main Objective: The study aimed to compare availability of essential medicines and funding of

essential medicines before and after implementation of the National Hospital Insurance Fund Civil

Servants and Disciplined Services Medical Scheme.

Methods: This was a retrospective longitudinal before-after study of four years; the latter two of

which the National Hospital Insurance Fund Civil Servants and Disciplined Services Medical

Scheme package was in operation. The study period was January 2010 – December 2013. Stock

control cards from the pharmacy store and accounting records were the main sources of data. Data

was extracted into various data collection forms. Data was analyzed using MS Excel, SPSS and

STATA. Results were statistically significant when p<0.05.

Results: The period after introduction of the scheme experienced a significantly higher allocation for

the medicines budget from the Facility Improvement Fund (p=0.008). Actual expenditure on

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essential medicines was also higher. There was less funding from the government supplier of

medicines, KEMSA after introduction of the new scheme (p<0.0001). There was a change in stock-

out rate after introduction of the new scheme, falling from 21.75% in 2010/11 to 19.47% in 2012/13.

The change was however not statistically significant (p=0.099). Regression analysis found that an

increase in the amount of Facility Improvement Fund spent on essential medicines was a significant

independent predictor of a reduction in stock-out rate, and that a higher rate of unfilled KEMSA

orders for a particular medicine predicted a higher stock-out rate.

Conclusion

Even though financing of medicines through the Facility Improvement Fund increased after

introduction of the new scheme, there was no change in the stock-out rate due to prevailing

contextual factors.

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CHAPTER 1: INTRODUCTION

1.1 BACKGROUND

Along with skilled and dedicated healthcare providers, medicines are the most significant means that

society possesses to prevent, alleviate, and cure disease (UN, 2005)

Essential medicines are those medicines that satisfy the priority health care needs of the population.

Essential medicines are intended to be available within the context of functioning health systems at

all times, in adequate amounts, in the appropriate dosage forms, with assured quality and adequate

information, and at a price the individual and the community can afford (WHO, 2002).

The following criteria are used by the WHO Expert Committee on the Selection and Use of Essential

Medicine: Adequate evidence of efficacy and safety in a variety of settings, relative cost-

effectiveness, suitability of pharmacokinetic properties and formulation as single compounds.

No health system can afford to supply all medicines that are available on the market. Lists of

essential medicines guide the procurement and supply of medicines in the public sector, schemes that

reimburse medicine costs, medicine donations, and local medicine production. The selection of the

medicines should be done with regard to evidence-based standard clinical guidelines. The Kenya

Essential Medicines List (KEML) 2010 was developed by The National Medicines & Therapeutics

Committee (NMTC) in consultation with WHO (KEML). It is planned that a new edition of the

KEML will be produced at least once every 2-3 years.

A hospital formulary is a list of medicines consisting of the most cost-effective, safe, locally

available medicines of assured quality that will satisfy the health care needs of the majority of the

patients. It is formulated by the Hospital Drugs and Therapeutic Committee using agreed upon

criteria (based on WHO criteria for selection of essential medicines).

Access is defined as having medicines continuously available and affordable at public or private

health facilities or medicine outlets that are within one hour’s walk from the homes of the population

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(UN, 2003). Access to medicines depends on four factors as illustrated by the framework below

(Figure 1.1).

Figure 1.1: The Access Framework (Adapted from WHO Policy Perspectives on Medicines, 2004)

One of the ways hospitals can ensure rational selection and use of medicines is by coming up with

national essential medicines lists and hospital formulary lists that guide procurement and use of

medicines. Mechanisms that make medicines affordable include promoting bulk procurement,

implementing generics policies, eliminating duties, tariffs and taxes on essential medicines and

encouraging local production of essential medicines of assured quality. Reliable supply systems can

be realized by public-private-NGO partnerships in supply delivery, proper regulatory control and

exploring various purchasing schemes

In many high income countries, over 70% of pharmaceuticals are publicly funded whereas in low

and middle income countries (LMIC) public medicine expenditure does not cover the basic needs of

the majority of the population. In these countries 50-90% of the medicines are paid for by patients

themselves (WHO 2004b). Kenya is classified as a middle income country by the World Bank.

Health care in Kenya is relatively costly, as a result of the widespread user fees at government health

facilities together with other out-of-pocket payments at NGO and other private health facilities (Xu

3

et al., 2006). Households are the largest contributors of health funds (35.9%) followed by donors

(31%), and then the government (29.3%) (Luoma et al., 2010). The total government health

expenditure as a percent of total government expenditures has continued to decline, from a high of

8.6 percent in 2001/02 to 4.6 percent in 2009/10 (MOMS & MOPHS 2011)

Currently, the public health system in Kenya relies on four main sources of financing: General

government revenues (taxes), donor funds, user fees and the National Hospital Insurance Fund

(NHIF), a government-sponsored health insurance scheme.

Total pharmaceutical expenditure accounts for 1.65 % of GDP and makes up 36.64 % of the total

health expenditure. Government expenditure on pharmaceuticals represents 9.03 % of the total

expenditure on pharmaceuticals in the Kenya (MOMS, 2010). Before the devolution of health

services, the government procured medicines through Kenya Medical Supplies Agency. KEMSA’s

2010/2011 Government budget (not counting donor contributions) for the procurement of essential

medicines for public hospitals was US$ 19.8 million; Out of 343 items on the Essential Drug List

(EDL), KEMSA procured only about 117 selected items, based on available funds. Many EDL

medicines could not be purchased because of budgetary constraints (UNIDO, 2010). The Ministry of

Health allocated hospitals with yearly drawing rights depending on various factors including

workload, and the poverty index of the area. Hospitals ordered from KEMSA on quarterly basis

using standard order forms. The total value of the order would not surpass the quarterly drawing

rights for the hospital. The order forms contained a limited number of essential medicines and supply

of orders was characterized by a low fill rate (The World Bank, 2009).

A large proportion of donor contributions to the health sector (78%) went to funding HIV/AIDS

related programs (Chuma and Okungu, 2011)

Beginning July 2013, health services in the country were devolved. Finances for essential medicines

were sent to the counties. The discretion of where to procure medicines from fell to the counties,

leaving KEMSA handling only medicines financed by donors (KEMSA, 2013).

User fees (cost-sharing), which were introduced in 1989, also pay for a portion of health services at

public facilities. NHIF reimbursements, free maternity reimbursements from the government and

4

cash collected from user fees are aggregated into one fund known as the Facility Improvement Fund

(FIF). This fund is used to supplement the government budget in areas such as purchase of essential

medicines, food, payment of salaries for casual workers and utility bills. Budgeting for FIF is usually

done on quarterly basis. Medicines can be purchased from local suppliers, NGO’s such as Mission

for Essential Drugs and Supplies and from the KEMSA Supplementary Supplies Division.

Revenue from the cost-sharing system has increased exponentially over the years. However, the

revenue’s overall share of total health expenditure for Fiscal 2005/06 was just 6.4% of the Ministry

of Health’s total spending (Wamai, 2009).

The NHIF derives its mandate from the NHIF Act no. 9 of 1998 which establishes the Fund as an

autonomous state corporation. Overall coverage levels for formal and informal sector populations

have reached 4.5 million people (11% of the Kenyan population) (USAID, 2014). The NHIF is only

compulsory for the formal sector workers and until 2012, only covered part of inpatient health care

costs (UNIDO, 2010). The beneficiaries still needed to pay out-of-pocket fees for treatment,

diagnosis and pharmaceuticals (Xu et al., 2006).

There are plans to restructure NHIF in order to increase financing for health. In 2005, legislation for

a National Social Health Insurance (NSHI) was passed with the objective of covering 60 per cent of

the population by 2015 (UNIDO, 2010). The plan is to systematically enroll all of the Kenyan

population, starting with workers and civil servants, followed by the self-employed and informal

sector workers, into the new NSHI Fund.

In 2012, the NHIF introduced a Civil Servants and Disciplined Services Medical Scheme for civil

servants and disciplined services (police officers, prison officers and National Youth Service). Civil

servants and Discipline Services were allocated hospitals which were funded via capitated payment

for outpatient services and other payment policies for inpatient care. Several hospitals including

public hospitals were contracted to provide services towards the new scheme. The hospitals were

required to provide effective quality services and treatments of therapeutic value to the beneficiaries

according to evidence-based standards and treatment guidelines as provided by the Ministry of

Health.

Webuye District hospital is a public hospital situated in Webuye town, Bungoma East district in

Bungoma County along the Mombasa-Kampala highway. The hospital has an immediate catchment

5

area of 500,000 people. The hospital has a bed capacity of 217 beds and bed occupancy of up to 150

%. On average 200-300 patients seek medical services from the casualty department daily.

In January 2012, The Director of Medical Services via circular (Ref.MMS/ADM/1/1/16) instructed

the management of the hospital to begin offering primary health care and treatment services to civil

servants and disciplined forces who had been allocated to the hospital as per the new NHIF scheme.

The hospital also entered into a formal contract with National Hospital Insurance Fund. The hospital

received a capitation premium of Kshs 3500 per year for every member on the scheme. This

capitation was channeled through the FIF account. In return for this capitation, the hospital agreed to

provide outpatient services to all members of the health plan, regardless of what the actual cost of

these services ended up being. In addition, the hospital was reimbursed in-patient charges at a flat

rate per day depending on the job group of the member. These rates were generally higher than for

the general NHIF scheme.

The NHIF provides a list of essential drugs required to be present during accreditation as a minimum

requirement. After accreditation NHIF expected that all prescribed drugs be filled at the hospital

regardless of whether they were essential or not.

1.2 PROBLEM STATEMENT

Stock-outs of essential medicines are common in public hospitals. It is expected that once new NHIF

scheme is introduced, there would be an improvement of services due to increased funding, and also

in order to meet the expectations of the clients. It is therefore expected that stock-outs of essential

medicines will be reduced.

On the other hand, insurance cover is generally associated with a greater demand for services and

this may include non-essential services and goods (Moral Hazard). The hospital may therefore stock

non-essential medicines even when there are stock-outs of essential medicines. This could lead to an

increased stock-out rate of essential medicines.

All out-patients are served from the same pharmacy, regardless of whether they are on the NHIF

scheme or not. This means that when a medicine is out of stock at the hospital pharmacy, NHIF

beneficiaries have to make out-of-pocket purchases from private pharmacies.

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1.3 JUSTIFICATION

Webuye District Hospital signed a contract with NHIF to provide both in-patient and out-patient

services by a capitated system. Essential services should therefore be provided adequately. It is

important that systematic studies be carried out to assess the availability of essential medicines after

implementation of the NHIF Civil Servants and Disciplined Services Medical Scheme. This is

particularly important considering that there is a possibility that the introduction of the scheme may

paradoxically compromise the availability of essential medicines.

To the best of our knowledge no studies have been done in Kenya on the effect of introduction of the

NHIF Civil Servants and Disciplined Services Medical Scheme.

Factors that may affect availability of medicines also need to be explored. These include the

KEMSA supply and amount of FIF allocated to purchase medicines.

The findings of this study will be essential in providing the management of the hospital with

information on the status of essential medicine availability before and after implementation of NHIF

and making recommendations on how to improve availability of these medicines.

1.4 RESEARCH QUESTIONS

The study aims to answer the following questions:

1. Has the funding for the budget for medicines changed since the introduction of the NHIF Civil

Servants and Disciplined Services Medical Scheme?

2. Are stock-outs of essential medicines reduced since the introduction of NHIF Civil Servants and

Disciplined Services Medical Scheme?

3. What are the factors that affect availability of essential medicines in a hospital pharmacy?

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1.5 NULL HYPOTHESES

1. The average amount and proportion of FIF allocated in the years 2010/2011 = years 2012/2013.

2. The percentage quantity contribution and expenditure on essential medicines for each of the

sources of essential medicines years 2010/2011= years 2012/2013

3. The frequency and duration of stock-outs of essential medicines in years 2010/2011= years

2012/2013

4. Availability of essential medicines is not influenced by any factor.

1.6 OBJECTIVES

1.6.1 Main Objective

The main objective of this study was to compare the availability and funding for essential medicines

before and after introduction of National Health Insurance Fund Civil Servants and Disciplined

Services Medical Scheme at Webuye District Hospital.

1.6.2 Specific Objectives

1. To compare the proportion of FIF allocated for procurement of medicines before and after

implementation of the NHIF Civil Servants and Disciplined Services Medical Scheme.

2. To measure and compare the proportional contribution of the following sources of funding to the

essential medicines budget before and after implementation of the NHIF Civil Servants and

Disciplined Services Medical Scheme: FIF, KEMSA and miscellaneous sources.

3. To determine the frequency and duration of stock-outs of essential medicines before and after

implementation of the NHIF Civil Servants and Disciplined Services Medical Scheme.

4. To explore some factors that could affect the stock-out rate of essential medicines.

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CHAPTER 2: LITERATURE REVIEW

2.1 INTRODUCTION

Millennium Development Goal 8, Target 8.E states as follows ― “In cooperation with

pharmaceutical companies, provide access to affordable essential medicines in developing countries”

(UN, 2003)

About 30% of the world’s population, or between 1.3 and 2.1 billion people, are estimated not to

have access to the essential medicines. In India, an estimated 499–649 million people (50% to 65%

of the population) do not have regular access to essential medicines. Throughout Africa, a further

267 million people (almost half the population or 15% of the world total) also lack access (WHO,

2004a).

A study conducted in health facilities in Kenya found that public facilities experienced stock-outs of

basic essential medicines for about 46 days per year. The public sector supply chain was

particularly prone to significant interruptions and critical stock outs, extending beyond 30 or

even 90 consecutive days (MOMS & MOPHS, 2009).

The WHO created a framework for expanding access to medicines, which consists of four

components: rational selection and use of medicines, affordable prices, sustainable financing, and

reliable supply system.

One way to create access is by ensuring essential medicines are always available.

2.2 HEALTH INSURANCE

Health Insurance is a mechanism for spreading the risks of potential healthcare costs over a group of

individuals or households, with the goal of protecting the individual from a catastrophic financial

loss in the event of serious illness.

By pooling financial contributions from many people, insurance plans can cover the hospital

expenses of those experiencing catastrophic events, such as near−fatal illness or injury. Without

access to such insurance, many people are unable to obtain treatment or must incur debts to pay

hospital bills. Insurance mechanisms can also generate large volumes of revenue for health services.

9

Many African governments in theory have been providing "health insurance" to their populations for

years in the form of free services, financed by tax. However, rising costs, limited funding, and

increasing inefficiency have greatly weakened the ability of public systems to provide effective care

and universal coverage. (Shaw, 1995)

2.2.1 Health Insurance and medicines

There are few studies on effects of health insurance on medicine use in LMIC. Most of the studies

are observational studies whose results must be cautiously interpreted. These studies also have

different outcomes.

Results from the World Health Survey as cited by Faden et al., (2011a) suggest that insurance hardly

improves access to medicines. However, this could be because many insurance schemes in

developing countries lack a comprehensive medicines benefit or require substantial cost-sharing for

medicines (Faden et al., 2011a).

There is evidence that health insurance reduces financial barriers to access in LMIC. It has been

shown that providing health insurance can improve consumer access to and utilization of

pharmaceuticals as well as health outcomes (Faden et al., 2011b). Studies either compare the insured

to the uninsured within a population, or they compare utilization before and after insurance was

implemented. It has been shown that providing insurance was associated with an increased use of

medicines with one study finding that insurance to be most important factor for explaining utilization

of medicine (Faden et al., 2011b).

Health insurance schemes are known to have great potential to improve the cost-effective use of

medicines by incentivizing better provider prescribing, more cost-effective use by consumers, and

lower prices from pharmaceutical companies (Faden et al., 2011b).

2.2.2 Moral Hazard

Moral hazard refers to the change in behavior induced by insurance coverage. In other words, if

people do not experience consequences they will behave irresponsibly. This means that low out-of-

pocket cost will lead to waste. Health insurers attempt to mitigate this through the introduction of co-

payments by users. It is assumed that if users are required to make a payment towards their health

care at the point of service, more prudent utilization will be encouraged (Shung-King, 2011).

10

However, there is a concern that out-of-pocket payments, of which co-payments is one kind, may

have unintended negative consequences on the economy of households and in the context of poorer

households, may deepen their level of poverty (Shung-King, 2011).

2.3 CASE STUDIES OF INSURANCE SCHEMES AND IMPACT ON

MEDICINES

2.3.1 China

The Shenzhen labor health insurance in China is a capitated social health insurance system for

migrant workers.

A study showed that the insurance had improved accessibility to essential medicines for migrant

workers (Zhu et al., 2008). Insurance indicators within two periods before and after 1st June 2006

were compared.

Percentage costs of essential medicines procured increased from 43.1% to 46.1%. This indicator

reflects the application of National Essential Medicines List as the base for purchasing of medicines,

and hence rational use of medicines. It was calculated as the costs of purchased Essential Medicines

in a period divided by the total costs of medicines purchased in that period; costs of medicines per

outpatient visit decreased from 24.94 Renminbi to 22.20 Renminbi. Percentage costs of medicine per

outpatient visit decreased, and number of outpatient visits increased. Only the decrease in costs of

medicines per outpatient visit was statistically significant (p = 0.010).

The popularization of this insurance was recommended to other provinces in the country.

2.3.2 Thailand

In 2001, Thailand implemented the Universal Coverage Scheme (UCS), a public insurance system.

This was in order to achieve universal access to healthcare.

A study was conducted to evaluate the impact of the UCS on utilization of medicines in Thailand for

three non-communicable diseases: cancer, cardiovascular disease and diabetes. Although the

majority of increases in sales were for essential medicines, there were also post-policy increases in

sales of non-essential medicines (Garabedian et al., 2012).

11

The policy was associated with a 39% increase in antidiabetic product sales 5 years after

implementation. One year after the policy, the sale of insulin was 35% higher and at 5 years 174%

higher than what would have been expected in the absence of the UCS.

There appears to have been a mixed impact on sales of cardiovascular medicines. Five years after

the policy, the sale of lipid-lowering agents was nearly double (108%) what would have been

expected in the absence of the scheme. The increase was primarily due to sales of branded generic

Simvastatin and Gemfibrozil products, which are on the National List of Essential Medicines

(NLEM), and a slight increase in sales of originator atorvastatin products, which were not on the

NLEM until 2004. For antihypertensives and cardiac medicines there was no statistically significant

change..

The results were also mixed for cancer medicines. There was no significant 1-year or 5-year impact

on the sale of antineoplastics or cytostatic hormones. However, there was an immediate reduction in

sales of immunostimulating agents to a sharp reduction in sales of interferon α-2b, a non-NLEM

medicine, around the time of UCS implementation, following recall of the product (Garabedian et

al., 2012).

2.3.3 Mexico

In a move towards universal coverage, the Sistema de Protección Social en Salud (System of Social

Protection in Health) was approved by law in 2003. Poor families could now enroll in the Seguro

Popular (People’s Insurance) which assured access to comprehensive health care.

During the reform period, regular external measurements of the availability of drugs in public

institutions were carried out. There was improved availability of drugs after the reform. In 2002,

only 55% of the prescriptions issued in Ministry of Health outpatient clinics were fully filled. By

2006, this percentage of fully filled prescriptions had increased from 55% in 2002 to 79% in

Ministry of Health outpatient clinics in general and to 89% in Ministry of Health outpatient clinics

serving Seguro Popular beneficiaries. In some states, 97% of the prescriptions issued in outpatient

clinics serving Seguro Popular beneficiaries were fully filled. In 2006, the percentage of

prescriptions issued in social security institute outpatient clinics that were fully filled was

consistently above 90, as opposed to less than 70 in 2002 (Frenk et al., 2009).

12

2.3.4 Tanzania

A survey was carried out in Tanzania to collect information on medicines coverage and health

insurance programs in the country. The National Health Insurance Scheme for public servants covers

more than 5% of the total population. It became apparent that medicines were covered by insurance

but medicines availability in the treatment facilities was an area which needed to be addressed

(Ministry Of Health And Social Services, 2008).

In another study, increasing enrolment in the government’s existing health insurance schemes was

frequently cited as one of the most promising solutions for addressing stock-out problems (Wales et

al., 2014). In the case that medicines needed by health facilities were stocked out by Medical Stores

Department, these funds could be used to supplement. At that time however, the amount of funds

available through these schemes was relatively small in comparison with the budget for purchasing

drugs from the medical stores department.

2.3.5 Nigeria

In 2005, Nigeria introduced the Formal Sector Social Health Insurance component of National

Health Insurance Scheme. Before 2005, the prescription pattern at a Nigerian military hospital was

reported as irrational with high drugs per encounter, low use of generic prescriptions and high level

of injection use (Adebayo et al., 2013). The average number of drugs per prescription after

implementation of the scheme was lower than recorded in before (2.6 vs. 3.0). It was inferred that

moral hazard may have been avoided (Adebayo et al., 2013). This could be due to the use of

capitation payments for drugs dispensed at the general outpatient clinics. There were far fewer

injections in the after than before (8.9% vs 23.9%) (Adebayo et al., 2013).

There was evidence of moral hazard shown by slight increase in antibiotic prescription more patients

encountered antibiotics in this present after than before (35.0% vs 27.8%) (Adebayo et al., 2013).

Studies have found that in general, fee-for-service payment systems provide implicit financial

incentives to increase service quantity whereas fixed reimbursement systems, such as capitation and

fixed salaries, give doctors incentive to contain costs (Faden et al., 2011b).

13

2.3.6 Ghana

In 2005, Ghana took a step toward providing universal coverage by introducing the National

Hospital Insurance Scheme (NHIS). The beneficiaries of the scheme receive free health care,

including a drug benefit package covering a wide range of treatments.

At the end of 2008, 61% of the population was covered by the NHIS (USAID Health Systems).

Membership in the NHIS is mandatory unless individuals obtain private health insurance (less than

1% of the population). (McIntyre et al., 2008)

In one study, the NHIS is observed to impact negatively on the ability of health facilities to acquire

medicines both in terms of quality and quantity (SEND-Ghana, 2010).This was reported in about

92% of facilities. Reasons cited were high market prices of some drugs/medicines, delayed claims

reimbursement and the exclusion of some effective drugs from the medicines list.

Increased financing for drugs caused by the rollout of the National Health Insurance Scheme resulted

in an increase in demand for drugs as evidenced by a tripled turnover at the level of regional medical

stores in two years (Seiter, 2010). The central medical stores were however unable to respond in

time. Private wholesalers stepped in. The NHIS contracts with the both public and private providers,

including private pharmacies.

Additional financing in combination with partial privatization of the supply chain appears to have

increased access to medicines for patients in Ghana.

2.3.7 Kenya

In the year 2012, the National Hospital Insurance Fund introduced a Civil Servants and Disciplined

Services Medical Scheme. Beneficiaries of the scheme were allocated hospitals and hospitals were

funded via capitated payment for outpatient services and other payment policies for inpatient care.

The effects of this system on availability of medicines are yet to be studied. With greater insurance

coverage, the demand for medicines is naturally expected to rise although the impact is difficult to

quantify (UNIDO, 2010).

In conclusion, although local data is scarce, it is evident that insurance has varied effects on

availability of medicines. It is to be expected that there will be an increase in demand for drugs

following introduction of an insurance model. Moral hazard is an adverse phenomenon in insurance

that has the potential to reduce availability of essential medicines.

14

2.3 CONCEPTUAL FRAMEWORK

Availability of essential medicines is partly determined by financing. Sources of financing for the

essential medicines budget for the district hospital are described in the conceptual framework below.

What would happen to efficiency in utilization of funds and availability of essential medicines if the

hospital received additional funding? Other factors may also have an effect on availability of

essential medicines.

15

Denotes a dependent relationship; the head of the arrow points to the dependent variable.

Denotes a linkage between concepts

Process-FIF Allocation for Pharmacy Budget (Local

Purchase Orders to suppliers)

Essential Medicines in hospital formulary: Analgesics, Antibiotics & Anti-fungal, Antimalarials,

Cardiovascular drugs, Gastrointestinal drugs, Drugs for Metabolic Disorders, topical drugs, others

Number of days out of stock for

Essential Medicines (before and after

NHIF)

Efficiency in utilization of funds (funds

spent per unit) before and after NHIF

Determinant of Access to Medicines

Rational Selection

Affordable prices

Reliable health and supply

systemsSustainable financing

-KEMSA Fill rate

-Irrational selection (non-essentials)

-Consumption rate

-Other factors

Sources of financing for essential medicines in a district hospital

-Cash paid by patients as user fees

-NHIF inpatient reimbursements

-Maternity reimbursements FIF

- NHIF capitation for civil servants (January 2012)

KEMSA quarterly supply of medicines- from the government

Miscellaneous sources such as medicine donations, other facilities.

16

CHAPTER 3: METHODOLOGY

3.1 STUDY DESIGN

A retrospective longitudinal before-after study of four years; the latter two of which the NHIF Civil

Servants and Disciplined Services Medical Scheme was in operation. The study period was 1st

January 2010 – 31st December 2013. The new NHIF scheme came into operation on 1st January

2012.

3.2 LOCATION OF STUDY

The study was conducted at Webuye District Hospital because of ease of access to past records. This

is because the hospital pharmacy is computerized. The hospital provides services to members of the

NHIF Civil Servants and Disciplined Services Medical Scheme. Webuye District hospital is situated

in Webuye town, Bungoma East district in Bungoma County along the Mombasa-Kampala highway.

The hospital is centrally placed with an immediate catchment area of 500,000 people.

3.3 DATA COLLECTION

A list of essential medicines for evaluation had been prepared by merging the Webuye District

Hospital draft formulary list of 2010 and the KEML 2010, then selecting all medicines common to

both lists (i.e. by complete enumeration/no sampling). The resulting list had 145 essential medicines.

Table 3.1 outlines the various types of data that were collected for each objective, and indicates the

various records from which the data was collected. The data was extracted into various data

collection forms that had been pre-tested and validated.

17

Table 3.1: Summary for data collection methods

Specific Objective Variables Indicator Method/tool Source of Data

1. Compare the proportion of FIF

allocated for procurement of

pharmaceuticals

FIF Amount allocated, Total Amount for each

quarter from 2010-2013

Difference in

Proportion

allocated for

period 2010-2011

and 2012-2013

Extracted data

into Form 1

(Appendix I)

Quarterly

Authority to

Incur

expenditure

from accounts

department

2. To measure the proportional

contribution of the various

sources of funding to the

essential medicines budget

Quantity and Cost of each essential medicine

procured sorted by source of funding (KEMSA, FIF,

Other facility)for each quarter from 2010-2013

Difference

between the

proportion of

medicine

procured, by

quantity and cost,

for period 2010-

2011 and 2012-

2013, sorted by

source of funding

Extracted data

into Form 3

(Appendix I)

KEMSA orders,

Local Purchase

orders and

invoices from

suppliers, S3

cards, Pharmacy

Summary

budgets from

Supplies office

and Pharmacy

department

18

3.To determine the frequency

and duration of stock-outs of

essential medicines

Number of days out of stock for each essential

medicine for each month from 2010-2013

Total number of

days out of stock

for period 2010-

2011 and 2012-

2013

Extracted

data into

Form 2

(Appendix I)

Stock Control

Cards

(electronic and

manual) from

pharmacy

department

4.To explore some factors that

could affect the stock-out rate of

essential medicines

a)KEMSA fill rate Total value of KEMSA order placed and supplied

quarterly

Value of supplies

as a proportion of

total order

Extracted

data to Form

4 (Appendix

I)

KEMSA orders

and Invoices

b)Presence on KEMSA Standard

Order Form

Presence of essential medicine on KEMSA order

form for the period 2010-2013

Yes/No Extracted data

to Form

4(Appendix I)

KEMSA

standard Order

Forms

c)Nature of medicines procured

by FIF

Cost of Non essential drugs procured quarterly, Total

cost of medicines procured by FIF

Proportion of

expenditure on

non-essentials

Extracted

data to Form

5 (Appendix

I)

Pharmacy

Summary

Budgets

19

d) Consumption rate of essential

medicines

Adjusted consumption rate of essential medicine in

Daily Defined Dose, Average cost per Daily Defined

Dose

Cost of Adjusted

Consumption rate

Extract to

Form 6

(Appendix I)

Pharmacy Stock-

Control cards

e) Monthly workload In-patient and out-patient workload Number of bed

days, Number of

patients

Extract to

Form7

(Appendix I)

Health Records

20

Unless listed differently in the formulary, medicines with the same formulation and active ingredient

but different strengths were considered to be the same; the quantity was adjusted to be equivalent to

the one in the formulary.

An out-of-stock situation was when the quantity of medicine remaining at a specified point in time

was zero, and was not replenished immediately. 1 day out of stock therefore means the remaining

quantity fell to zero and was replenished the next day.

Prices of medicines procured through FIF were obtained from invoices or S3 card. Prices of

medicines from KEMSA were obtained from the standard order form. Where the cost data was not

available, such as in the case of borrowing from other health facilities, KEMSA prices were used.

Where KEMSA price was not available, the current contract price was used.

3.4 DATA ANALYSIS

The quantitative data was entered into Microsoft Excel. The data entered was then checked for

accuracy and completeness before being exported to STATA Software version 10.0 and SPSS

version 20 for statistical analysis.

Stock out rate was calculated in two ways

i) Percentage Monthly Stock-Out Time –for 145 medicines

=%∗

ii) Stock out rate per medicine

=100%∗Total number of stock−out days in the periodTotal number of days in the period∗

*1461 days for entire period

Because the different medicines had different units, quantity received from the different sources was

converted to a percentage. The total amount received for a certain medicine was used as the

21

denominator when calculating the percentage quantity of medicine provided by KEMSA, FIF or

other facility.

Inferential and descriptive analysis was carried out. Inferential tests were selected according to the

nature of the data. Paired comparisons were done using Wilcoxon Signed Rank Test where

assumptions of the paired t-test had not been met. Friedman test was used to compare related data of

more than one group.

Time series data was tested for autocorrelation. In the event of autocorrelation Auto-regressive

Integrated Moving Average (ARIMA) modelling was used. Lagged values of the variables were

taken into account during regression of the time series.

Negative binomial regression analysis was used for count data that did not meet assumptions of

Poisson regression.

Results were considered statistically significant if the p-value is less than 0.05 or confidence level of

more than 95%.

3.5 LIMITATIONS

1. There was a potential risk of missing data since the study was retrospective. Every effort was

made to obtain missing data, for example, electronic records were corroborated and/or

supplemented with manual records.

2. Anti-Retroviral drugs, anti-tuberculosis drugs and contraceptives which were not directly under

the hospital were not studied.

3. This being an observational study at one hospital, the data should be interpreted cautiously if it is

to be applied in a broader setting.

4. There were some non-essential drugs on the hospital formulary.

3.6 ASSUMPTION

It was assumed that an out of stock in the pharmacy store meant an out of stock even at the point of

use.

22

3.7 ETHICAL CONSIDERATIONS AND APPROVAL

Ethical approval was sought and obtained from the Kenyatta National Hospital/University of Nairobi

Ethics and Research Committee (Ref-KNH-ERC/A/83). A copy of the letter is at Appendix II.

Approval was also obtained from the administration of Webuye District Hospital.

The information obtained from records was kept confidential and was only used for purposes of this

study.

23

CHAPTER 4: RESULTS

4.1 Allocation of FIF before and after the introduction of the NHIF civil servants

scheme

4.1.1. Quarterly allocation of funds for purchase of medicines from the FIF

(Absolute amounts)

At the beginning of every quarter, the Hospital Management Team meets and discusses various

budget proposals that have been forwarded from the departments. The FIF collections of the

previous quarter are then allocated for various purposes, including purchase of medicines, according

to the final approved budget.

Data on amount allocated for purchase of medicines from FIF was collected for the 8 quarters

before and after the implementation of the NHIF civil servants scheme.

Summary statistics for amount of money allocated for purchase of medicines are listed in Figure 4.1

below

24

Figure 4.1 Quarterly FIF allocations for purchase of medicines-summary statistics

The mean and median of the quarterly FIF allocation for purchase of medicines was greater in the

period after introduction of the new NHIF scheme (Ksh1.20 million vs. 0.73million and Ksh 1.04

million vs. 0.70million respectively). The highest quarterly FIF allocation in 2012/13 was Ksh 2.41

million compared to Ksh 0.85 million in 2010/11. The lowest quarterly allocation in 2012/13 was

Ksh 0.75 million. This is greater than the minimum quarterly allocation in 2010/11 which was Ksh

0.55 million.

0.73

1.20

0.0000

0.5000

1.0000

1.5000

2.0000

2.5000

3.0000

Mean

Qua

rter

ly F

IF A

lloca

tion

in m

illio

n ks

hs

24







0.55 million.

0.55

0.850.700.75

2.41

1.04

Minimum Maximum 50th (Median)

24







0.55 million.

year 2010-2011

year 2012-2013

25

Bivariate analysis: Comparison of amount of FIF allocate before and after new NHIF scheme

Quarterly FIF allocation for purchase of medicines in the period 2012/13 was compared to the

allocation in 2010/2011.The Wilcoxon Signed Rank Test was used because the data was paired but

did not fit the assumption of normality required for the paired t-test.

There is evidence of a significant median difference in FIF allocation for purchase of medicines

between period 2012/13 and 2010/11 (p=0.008). This suggests a significantly higher FIF allocation

for purchase of medicines in the period 2012/13 than 2010/11.

4.1.2 Proportion of total FIF allocated quarterly for purchase of medicines

The mean quarterly amount of FIF allocated for purchase of medicines as a percentage of the total

amount available to the hospital for budgeting was calculated for each period (Table 4.1)

Table 4.1: Quarterly Percentage allocation of FIF for purchase of medicines

Mean Minimum Maximum

Year 2010 to 2011 7.55 5.14 10.66Year 2012 to 2013 9.12 6.95 12.36

The mean proportion of FIF allocated quarterly for purchase of medicines was slightly higher in the

period after introduction of the new scheme. However the paired t-test, appropriate here because the

data was paired and satisfied the assumption of normality, suggested that the difference in these

means was not statistically significant (p=0.0502).

4.2 Contributors to the Essential Medicines Budget

Three sources were found to contribute to the essential medicines budget: KEMSA, which consisted

of the supply of medicines funded by the MOH allocation/donors; FIF which entails the purchase of

medicines from local suppliers and is funded by cash collected from user fees as well as NHIF and

other government reimbursements; and other facilities, which involves direct donations to the facility

and the supply of medicines obtained from other hospitals. Of note is that the period 2010-2013

26

experienced an average KEMSA fill rate of 42.7% (by total value) for essential medicines, i.e.

KEMSA honored 42.7% of orders for essential medicines.

4.2.1 Proportion of essential medicines procured through KEMSA, FIF and

Other Facility

To account for the fact that different medicines are supplied in different units, the quantity of each

medicine received from each of the different sources was calculated as a proportion (percentage) of

the total quantity of that medicine received during that period. These proportions were then

averaged to yield the reported mean percentages. This was done for both periods, i.e. 2010-11 and

2012-13 (Figure 4.2).

Figure 4.2 Mean proportion(%) of essential medicines procured and source

0

10

20

30

40

50

60

2010/11 2012/13 2010/11 2012/13 2010/11 2012/13

KEMSA FIF Other Facility

%

SOURCE

27

KEMSA contributed the largest average proportion of essential medicines (48.9%) in the period

before the new scheme was introduced. In the second period, FIF contributed the largest average

proportion of essential medicines (45.5%) (Figure 4.2).

Bivariate analysis: Cross-comparison of the different sources of medicines

Bivariate analysis was carried out to compare the proportions of essential medicines obtained

through the different sources of medicines. The Wilcoxon Signed Rank Tests was appropriate as the

data was paired but non-normal.

In the period 2010/11 the proportion of essential medicines from both KEMSA and FIF was found to

be significantly higher than that from other facilities i.e. KEMSA>Other Facility and FIF> Other

Facility (p=0.000). However, the study did not find a significant difference between the proportions

from KEMSA and FIF for this period (p=0.050).

In the period 2012/13, the proportion of essential medicines from the different sources was as

follows FIF>KEMSA> Other facility (p <0.017).

Bivariate analysis: Within-source comparison

For each source, Wilcoxon Signed Rank Tests were also used to compare proportions of essential

medicines procured in 2010/11 to those procured in 2012/13. The results are shown in Table 4.2.

Table 4.2: Results from within-source comparison of proportion of essential medicine procured

Source Hypothesis p-value

KEMSA KEMSA 2012/13 < KEMSA 2010/11 0.000

FIF FIF 2012/13 > FIF 2010/11 0.000

Other Facility Other facility 2012/13 > Otherfacility2010/11 0.029

There is evidence of a significant median difference in proportion of essential medicines received

from KEMSA between the period 2012/13 and 2010/11 (p=0.000). This suggests the proportion of

essential medicines procured through KEMSA was significantly less after implementation of the

NHIF civil servants scheme.

28

Conversely, the results suggest that the proportion of essential medicines procured through FIF was

significantly greater after the implementation of the NHIF civil servants scheme (p=0.000). A

similar deduction was made for other facilities, whereby the proportion of essential medicines

received was also significantly greater after implementation of the NHIF civil servants scheme

(p=0.029).

4.2.2 Expenditure on essential medicines procured through KEMSA, FIF and

Other Facility

For this analysis, for each of the essential medicines, the quantity of medicines received from each

source was converted to monetary terms (Kenya Shillings). Summary statistics were calculated for

the 145 medicines and mean expenditure per essential medicine determined for the period before and

after implementation of the NHIF civil servants scheme (Figure 4.3).

Figure 4.3 Mean expenditure on essential medicines by source

0.0000

0.2000

0.4000

0.6000

0.8000

1.0000

1.2000

1.4000

1.6000

2010/11 2012/13 2010/11 2012/13 2010/11 2012/13

KEMSA FIF Other Facility

Exp

endi

ture

in '0

0000

ksh

s

29

As can be seen from Figure 4.3, the highest expenditure on essential medicines appears to be

incurred by KEMSA followed by FIF and while the least expenditure is by other facilities. In

2010/11 KEMSA recorded the highest expenditure per essential medicine at Ksh 111,380 followed

by FIF at Ksh 29,798. In the period after implementation of the new scheme FIF expenditure per

essential medicine rose and almost equaled that of KEMSA (Kshs 48,201 vs. Ksh 51,523).

Expenditure per essential medicine for other facilities decreased in the period after implementation

of the new scheme.

Bivariate analysis: Cross comparison of different sources’ expenditure on essential medicines

The Wilcoxon Signed Rank Tests were used to compare the different sources’ expenditure on

essential medicines.

In the period 2010/11, the expenditure on essential medicines from the different sources was found

to be significantly different, i.e. KEMSA>FIF>Other Facility (p=0.000).

In the period 2012/13, FIF>Other Facility (p=0.000) and KEMSA> Other facility (p=0.000) but

the study did not find a significant difference between FIF and KEMSA expenditure on essential

medicines (p=0.338).

Bivariate analysis: Within-source comparison: Expenditure in 2010/11 and Expenditure 2012/13

For each source, Wilcoxon Signed Rank Tests were also used to compare expenditure on essential

medicines in 2010/11 to expenditure in 2012/13. The mean expenditure per essential medicine for

each source before and after implementation of the NHIF civil servants scheme was compared

(Table 4.3)

Table 4.3: Results from within-source comparison (expenditure)

Source Hypothesis P value

KEMSA KEMSA 2012/13 < KEMSA2010/11 0.000

FIF FIF 2012/13 > FIF 2010/11 0.000

Other Facility Other facility 2012/13 < Other facility 2010/11 0.122

There is evidence of a significant median difference in expenditure on essential medicines by

KEMSA between the period 2012/13 and 2010/11 (p=0.000). This suggests a significantly lower

30

expenditure on essential medicines by KEMSA after implementation of the NHIF civil servants

scheme. Conversely, the results suggest that there was a significantly higher expenditure on essential

medicines by FIF after implementation of the NHIF civil servants scheme (p=0.000).

However, there was no evidence of a significant difference in expenditure on essential medicines by

other facilities between the period 2012/13 and 2010/11 (p=0.122).

4.2.3 Efficiency

Efficiency is a ratio of output vs. input (resources used). A higher efficiency indicates that for the

same output, less units of resource were used, while a lower efficiency indicates wastage in that

more units of resource were used to produce the same output. A higher efficiency in this case means

less expenditure per unit of essential medicine procured; the reverse is true.

Efficiency was compared for the two periods. For each period, efficiency was calculated for each

essential medicine as follows

Efficiency =

Summary statistics for efficiency calculated for each essential medicine for each period are outlined

below (Table 4.4)

Table 4.4: Efficiency in number of units per Ksh - Summary statistics

N Mean 50th

(Median)

Efficiency 2010to2011 128 1.18 .11

Efficiency 2012to2013 128 1.03 .08

17 essential medicines that did not have receipts in 2010-11 and/or 2012-13 were not included in the

analysis. Analysis using the Wilcoxon Signed Rank test yielded evidence of a significantly higher

efficiency before introduction of the NHIF civil servants scheme (p<0.0001).

31

4.3 Availability of essential medicines

4.3.1 Monthly stock-out time (%)

Percentage monthly stock-out time was computed for both periods as follows

Percentage Monthly Stock-Out Time =%∗

Summary statistics are outlined in Table 4.5 below

Table 4.5: Monthly Stock-out time (%) - Summary statistics

N Mean Std. Deviation Minimum Maximum Median

Year 2010to2011 24 21.75 3.54 15.12 29.08 21.45Year 2012to2013 24 19.47 6.54 11.26 38.26 19.04

The average monthly stock-out time reduced from 21.75% in 2010/11 to 19.47% in 2012/13. This

means that on average for period 2010/11, essential medicines were stocked-out 21.75% of the time.

In 2012/13, there was a decrease in stock-out rate in that essential medicines were stocked-out

19.47% of the time.

However, Wilcoxon Signed Rank Test analysis showed that the median difference in monthly stock-

out time between the two periods was not significant (p= 0.099). This suggests that there was no

significant change in stock-out rate after introduction of the new scheme.

Figure 4.4 below displays the plot of mean percentage stock-out time versus time (in months).

32

Figure 4.4 Monthly average stock-out time (%)

There are monthly variations in the percentage stock-out time. Visual inspection of the plot reveals a

notable reduction in percentage stock-out time from June 2012 up to March 2013. Actually this

period records some of the lowest stock-out rates.

Bivariate analysis of monthly stock-out time for different months of the quarter

It appears in Figure 4.4 that there may be variation in monthly stock-out rate depending on the

position of the month in the quarter (i.e. first, second or third month of the quarter). The monthly

stock-out time for each essential medicine was therefore sorted into 3 groups- first month of quarter,

second month and third month. For each essential medicine, the total number of days out of stock for

all the first months of the quarter was computed, then converted to percentage stock-out time

according to the total number of days for the first months. The same applied to the second and third

months. Wilcoxon Signed Rank Tests were used to compare the stock-out rates of the groups. The

results are outlined in Table 4.6 below.

0

5

10

15

20

25

30

35

40

45

Jan-

10

Mar

-10

May

-10

Jul-

10

Sep-

10

Nov

-10

Jan-

11

Mar

-11

May

-11

Jul-

11

Sep-

11

Nov

-11

Jan-

12

Mar

-12

May

-12

Jul-

12

Sep-

12

Nov

-12

Jan-

13

Mar

-13

May

-13

Jul-

13

Sep-

13

Nov

-13

%

NE

WN

HIF

SC

HE

ME

33

Table 4.6: Results from comparison of stock-out rate of different months in a quarter

Ha: p-value

Mean Stock-out time month 1> Month 2 0.0002

Mean Stock-out time month 2> Month 3 0.0004

Mean Stock-out time month 1> Month 3 <0.0001

The results suggest that there were significant differences in the different months of the quarter.

Percentage stock-out time for Month 1>Month2>Month3 (p<0.017)

Class differences in stock-out rate

The Wilcoxon signed rank test was applied to compare the monthly stock-out time for each class of

essential medicines over the two periods. Only five classes had statistically significant median

differences in monthly stock-out time (Table 4.7).

Table 4.7: Significant p-values for Wilcoxon Signed Rank test for differences in monthly

stock-out time for different classes of essential medicines

Class and Ha p-value

Central Nervous System: 2012/13<2010/11 0.000

Gastrointestinal: 2012/13>2010/11 0.001

Topical Drugs :2012/13<2010/11 0.023

Anti-Malarial :2012/13< 2010/11 0.035

Thyroid drugs :2012/13<2010/11 0.001

Four out of the eighteen classes registered a significant decrease in monthly stock-out time after

introduction of the NHIF civil servants scheme. These include medicines for the central nervous

system, Thyroid drugs, Anti-Malarial drugs and Topical Drugs. Gastrointestinal medicines are the

only class that had a statistically significant increase in monthly stock-out time after introduction of

the new scheme.

34

Further analysis of the stock-out rates across the different classes of medicines revealed that, for the

entire period, anti-helminthics had the highest percentage monthly stock-out time than all other

classes (p<0.0001).

4.3.2 Stock-out rate per essential medicine

The percentage stock-out rate for each essential medicine was calculated for the entire study period

as follows.

Stock out rate per medicine=100%∗Total number of stock−out days in the period1461

Results for twenty medicines with highest and lowest stock-out rates are listed in table 4.8 below

35

Table 4.8: Essential medicines with highest and lowest stock-out rates in 2010-2013

20 Medicines with lowest stock-out

Rates

% stock-

out rate

20 Medicines with highest

stock-out rates

% stock

out rate

Amoxicillin 250mg caps 0.00 Chloramphenical suspension 100.00

Cotrimoxazole 400:80 tabs 0.00 Clindamycin tablets 100.00

Insulin soluble human 0.00 Fluoxetine caps 100.00

Oral Rehydration Salts 0.00 Ibuprofen suspension 100.00

Sulfadoxine/pyrimethamine tabs 0.00 Praziquantel 600mg tablets 100.00

Aspirin 300mg tabs 0.07 Salicylic acid powder 100.00

Water for injections 10ml 0.07 Lignocaine spray 100.00

Diazepam injection 0.14 Erythromycin suspension 94.93

Insulin Isophane Biphasic human 30/70 0.62 Gentamicin injection 20mg/2ml 85.56

Nystatin suspension 0.75 Haloperidol decanoate injection 78.44

Magnesium sulphate injection 0.89 Ceftriaxone Inj 250mg 73.31

Suxamethonium injection 0.96 Phenytoin Injection 64.13

Ibuprofen 200mg tablets 1.03 Ciprofloxacin ear/eye drops 59.34

Sodium bicarbonate injection 1.03

Amoxicillin-clavulanic acid

228mg/5ml 52.09

Thiopentone injection 1.03 Valproic acid 200mg 45.11

Chlorpheniramine 4mg tabs 1.16 Paracetamol suppositories 44.28

Chlorpromazine 100mg tabs 1.44 Phenobarbitone injection 41.48

Amitryptilline 25mg tabs 1.78 Dexamethasone 0.5mg tabs 39.77

Neostigmine injection 2.12 Atropine Eye Drops 1% 39.29

Paracetamol 500mg tabs 2.26 Morphine Injection 39.29

Some products were never stocked-out during the entire four years. These include antibiotics such as

amoxicillin capsules and co-trimoxazole tablets. Medicines used in theatre had very low stock-out

rates (<2.5%). These include Neostigmine Injection, Thiopentone Injection, Suxamethonium

Injection. In contrast there were some products that were stocked-out throughout the entire period.

These include antibiotics such as Clindamycin tablets, Chloramphenicol suspension and the anti-

36

helminthic Praziquantel. Some pediatric preparations had high stock-out rates (>50%). These include

Amoxicillin-Clavulanic suspension, Erythromycin Suspension and Ibuprofen suspension. Topical

preparations also had high stock-out rates (Atropine eye drops, Ciprofloxacin eye/ear drops,

Lignocaine spray, Salicylic acid powder).

4.4 Analysis for factors that influence stock-out rate

Data on various factors that may influence the stock out rate was collected. This included KEMSA

fill rate, workload, FIF allocation and percentage of FIF expenditure on non essential medicines.

Two different modeling approaches were used for this analysis:

Autoregressive Integrated Moving Average based on monthly data.

Negative binomial regression based on total days out of stock for each essential medicine.

4.4.1 Monthly data- Autoregressive Integrated Moving Average

Time series analysis using an Autoregressive Integrated Moving Average (ARIMA) model was used

to model variation in monthly stock out over the study period. Monthly stock-out time was found to

be auto-correlated and at the first lag.

The monthly stock-out time data was log transformed and first differenced data was used because the

transformed data was found be non-stationary (Dicker Fuller test, p=0.0586)

The following independent variables and their first lags were tested: KEMSA expenditure, FIF

expenditure, Other Facility expenditure, % of total FIF expenditure on non-essential medicines,

outpatient workload and inpatient workload (as total bed days).

A forward stepwise approach was used and the most parsimonious model was retained.

37

Table 4.9 Significant p-values for independent variables regressed with log of monthly % stock-out

time

Independent variable Coefficient P

value

95% Confidence

Interval

FIF expenditure on essential medicines( in Kshs

100000)

-0.0337 0.025 (-0.0633,-0.0042)

One month’s lag of FIF expenditure on essential

medicines( in Kshs 100000)

-0.0280 0.022 (-0.0521,-0.0040)

The model obtained from the time series regression analysis of monthly stock-out rate showed that

the amount of money provided by FIF and its first lag (1 month) significantly influences the monthly

stock-out time. The previous month’s stock-out time also influences the stock-out time. The money

received from KEMSA and other facilities appears not to influence the monthly stock-out time. The

model was statistically significant with a probability > (chi) =0.0014.

All other factors remaining constant, a unit increase in FIF expenditure (in Kshs 100,000) for the

month will result in a decrease in monthly stock-out time by 3.31% of the original stock-out time (95

% confidence interval of 0.42% to 6.13%).

Similarly, all other factors remaining constant, a unit increase in the previous months FIF

expenditure(in Kshs 100,000) for the month will result in a decrease in percentage monthly stock-

out time by 2.76% of the original stock-out time( confidence interval 0.40% to 5.08%)

The constant in the model was significant (p=0.010) suggesting other factors may also be

influencing monthly stock-out time.

4.4.2 Total days out of stock- Negative binomial regression

This model was based on the individual medicines and the dependent variable was number of days

out of stock for the whole four years. Since number of days is count data, negative binomial

regression was found to be most appropriate. The data did not meet assumptions for Poisson

regression.

Independent variables explored included: number of times a medicine was ordered and not received

or was not on the KEMSA list, the number of times it was procured by FIF and cost of adjusted

consumption rate (in WHO daily defined dose).

38

Table 4.10 Significant p-values for independent variables regressed with total days out of stock

Independent variable Coefficient P

value

95% confidence

interval

Number of times medicine was supplied by FIF -0.1102 0.000 (-0.1478,-0.0726)

Number of times medicine was not supplied by

KEMSA when ordered or not on KEMSA list 0.1146 0.000 (0.0863,0.1430)

All other factors remaining constant, a unit increase in number of quarters an essential medicine was

received through FIF would result in a decrease in total days out of stock by 10.43 % of the original

total days out of stock (confidence interval of 7.00% to 13.74%).

All other factors remaining constant, a unit increase in the number of times an essential medicine

was not received from KEMSA when ordered or not on KEMSA list would result in an increase in

the total days out of stock by 12.15% of the original days out of stock confidence interval (9.01% to

15.37%).

The constant in the model was significant (p=0.000) suggesting other factors may also be

influencing the total days out of stock.

39

CHAPTER 5: DISCUSSION

Health insurance is one of several medicines financing strategies (WHO 2012). The actual amount of

money allocated for purchase of medicines increased significantly after the implementation of the

new NHIF scheme. NHIF capitation and reimbursement monies are channeled through the FIF

account. The increase was most probably due to additional funding from NHIF. The introduction of

free maternity and subsequent government reimbursements towards the end of the year 2013 may

also have contributed to this increase.

Up until implementation of devolution of health in late 2013, KEMSA was established by law as the

primary public procurement agency of essential medicines for public facilities (UNIDO, 2010). Until

June 2013, KEMSA was funded by the national government and by development partners (KEMSA,

2013). In our study, some essential medicines such as Salbutamol Inhaler, Dexamethasone Injection

and several topical medicines were never procured from KEMSA (0% proportional quantity). This

is partly because KEMSA has a standard order form that is used to order medicines. At the

beginning of 2010, the list had 116 essential medicines. Medicines may also be ordered but are

stocked out at the KEMSA warehouses hence not supplied. The average fill rate for essential

medicines on the KEMSA Standard Order Form was 42.7% meaning on average less than half the

order was usually honored. In one study, the average aggregate fill rate for the top 100 products was

21%, suggesting chronic shortages of almost all major items (The World Bank, 2009).

The proportional quantity contributed by FIF ranged from 0 to 100 percent. Some essential

medicines were never procured using FIF while others are procured 100% using FIF. FIF is used to

supplement KEMSA. Some of these perhaps are well provided through KEMSA while others maybe

too expensive to procure using FIF. Drugs such as Artemether Lumefantrine were never procured

using FIF, probably because of cost and also because they are to be dispensed free of charge. Even

though all the medicines are essential, some may be deemed more ‘vital’ hence will be given priority

during procurement.

KEMSA contributed a larger proportion of essential medicines before the new NHIF scheme. In

addition, KEMSA expenditure on essential medicines is greater before the new scheme. Compared

40

to the other sources, KEMSA was the largest contributor to essential medicines expenditure in the

period before introduction of the new NHIF scheme. The difference could be attributed to the

reduction in number of essential medicines included in the KEMSA Standard Order Form with time.

The reduction was aimed at increasing efficiency; on average KEMSA prices are lower than other

facilities due to economies of scale (UNIDO, 2010). At the beginning of 2010, the list had 116

essential medicines. The number of essential medicines in the list reduced with time. By September

2013, the list contained 71 essential medicines.

The decreasing supply of essential medicines from KEMSA could also be due to financial

constraints. In low income countries, the proportion of government spending dedicated to

pharmaceuticals has significantly reduced from 21.5% in 1990 to 16% in 2000 (WHO, 2012).WHO

estimates the level of public sector funds needed to provide essential medicines in a basic health care

package at around US$ 1.5-2 per capita. The MOH allocates of US$ 1.1 per capita which is

inadequate. In addition, based on national estimates, about Ksh 7.3 billion is required for

pharmaceuticals annually, but less than 2 billion is made available (Luoma et al., 2010). In a press

statement dated 20th August 2013 by the Principal Secretary Ministry of Health, it was

acknowledged that KEMSA was only able to meet 65% of the quantified needs Public Health

Facilities due to budgetary constraints (MO H, 2013). The rest 35% was expected to come from

Development Partners, health facilities cost sharing fees, and out of pocket expenses by patient. It

was expected that once the Abuja Declaration target of 15% of the government budget to healthcare

is met, the funding gap would be eliminated.

Following devolution of health, there was a delay in supply from KEMSA in late 2013; followed by

a halt in automatic supply of medicines. Actually only 2 out of 145 essential medicines were

supplied in the last quarter of 2013. KEMSA states in its website that it was mandated to supply up

to June 2013 and following instructions from the Ministry of Health supplied a one-off free supply

that ended 30th October 2013 (KEMSA, 2013). The devolution of health meant that the mandate to

procure medicines fell to the county governments. All funds for procurement of medical

commodities were devolved to the Counties, and the discretion of where to procure from fell to each

particular county. Some counties would opt to continue with KEMSA, which now was operating

under a new business model (KEMSA, 2013). Some counties opted for other private suppliers.

41

Several counties entered into partnerships with Mission for Essential Drugs and Supplies (MEDS).

Due to the MEDS County Governments Partnership Initiative, more than thirty counties began

procuring from MEDS (MEDS 2013).Generally, public health facilities in Kenya experienced

logistical problems when health was devolved precipitately due to lack of structures and clear cut

guidelines. The Parliamentary Committee for Health received several submissions outlining the

extent of shortage of drugs and other medical supplies in public health facilities. The Committee

observed that the capacity of Counties to take up the function of procuring drugs and medicaments

was weak (Parliamentary Committee for Health).

Our findings showed that the proportion of essential medicines contributed by FIF was greater after

introduction of the new NHIF scheme at Webuye District Hospital. FIF expenditure on essential

medicines was also greater after introduction of the new scheme. Compared to the other sources, FIF

contributed the largest proportional quantity of essential medicines after introduction of the new

scheme. This is likely due to increase in amount of FIF allocated for medicines in 2012/13 and also

because receipts from KEMSA, previously the major supplier, declined in this period. In one study,

it was found that the FIF fund is increasingly being used for procurement of medicines, to plug the

gap resulting from insufficient supplies from KEMSA. During one assessment, it emerged that

between 30 and 60 percent of FIF is now utilized for procuring pharmaceuticals and medical

supplies (Luoma et al., 2010).

Our study showed that the proportion of essential medicines contributed by other facilities was

greater after introduction of the new NHIF scheme at Webuye District Hospital. This could be

attributed to increased cross-health facility exchange of essential medicines. For example, Webuye

District Hospital would exchange a commodity it has in excess for a different commodity in X

District Hospital. The increase in this activity could have been due to declining KEMSA supplies.

The period before implementation of the new scheme experienced a higher efficiency in utilization

of funds probably because supply from KEMSA was higher and KEMSA is generally cheaper due to

economies of scale.

The methodology used in medicine availability studies is quite varied, making comparisons difficult.

Most studies have shown that availability of essential medicines is lower in the public sector. In our

42

study, overall, there was no significant change in the stock-out rate after implementation of the new

scheme. The lowest stock-out rates were recorded between August 2012 and March 2013 probably

because of increase in FIF expenditure on essential medicines. The stock-out rate seemed to increase

after this period perhaps due to decreasing supply of essential medicines from KEMSA. In contrast,

reforms to the Mexico’s Seguro Popular (People’s Insurance) resulted in improved availability of

drugs. The percentage of fully filled prescriptions increased from 55% in 2002 to above 90% in

2006. This was a scheme that included everyone as it was aimed at universal coverage. This meant

that there was more financing made available than in the case of our study. (Frenk et al.,2009).

Stock-out rate of individual essential medicines for the entire period was highly varied. Stock-out

rates of 100% were recorded for more than one medicine, meaning some essential medicines were

not available for the entire four years. In contrast a few medicines had stock out rates as low as 0%.

Some medicines were most probably well supplied than others. It also seems that prioritization of

needs may have been in play. For example, some of the medicines with very low stock-out rates

were insulin and theatre medicines. These are used in life threatening situations. Medicine with the

highest stock out rates included some topical preparations and pediatric formulations. These may be

deemed less vital, and also unprofitable because pediatric preparations are free to the patient. Some

non-essential medicines may also have used for the same purpose as the essential one, for example

Pethidine Injection instead of Morphine Injection. The class of medicineswith the highest stock-out

rate was anti-helminthics. This could be because there were only two medicines in this class and one

of them, Praziquantel, was out of stock during the entire period.

Various other factors were explored to explain variability in stock-out rate. The first month of the

quarter was characterized by a higher stock-out rate than the second and third month. This could be

due to delays in procurement especially for medicines procured through the FIF. For the FIF,

procurement of essential medicines is usually done on a quarterly basis. The earliest the authority to

incur expenditure (AIE) can be received is middle of the first month. In one study, the AIE took an

average of 38 days to be processed up to the point of arriving at the beneficiary facility. The duration

ranged from 13 to 95 days (MOH, 2009). Local Purchase Orders may take at least 1 week to prepare

and supplies will take at least one week to be received at the facility. There is still a significant gap

in the financing of pharmaceuticals, despite the utilization of a diverse set of financing mechanisms

43

(Luoma et al., 2010). If financing was sufficient, a five month supply of essential medicines would

be procured to cater for the lead time resulting from the winding procurement procedures.

Stock-out rate is also dependent on the previous month’s stock-out rate due to autocorrelation which

is common to time series.

The study found a significant relationship between funding and availability of medicines. In a recent

study, inadequate funding was the most strongly cited (57.9%) factor that caused unavailability of

essential medicines in public hospitals (Mwathi and Osuga, 2014). In our study, actual FIF

expenditure on essential medicines was found to have great influence on the variability in monthly

percentage stock-out time. Increase in amount of FIF spent on medicines led to a decrease in

percentage stock-out time. Paradoxically, the expenditure on essential medicines by KEMSA

appeared to have no effect on monthly percentage stock-out time even though it was greater than the

amount from FIF at the beginning of the study period. This could be due to the fact that KEMSA

lists were quite limiting. The variation in amount of money was probably due to variation in quantity

of the same supplies. This reflects lack of flexibility in expenditure. For the FIF however, the

pharmacist had discretion on what to procure. He/she could therefore prioritize to procure medicines

that were not supplied by KEMSA.

Our study also showed that stock out rate depended on the number of times an essential medicine

was purchased through FIF and the number of times it was ordered from KEMSA and not received

or was off the KEMSA list. It means therefore that when a medicine was on the KEMSA Standard

Order Form and orders for that particular medicine were honored, there was decrease in the stock-

out rate of that medicine. Erratic supply is therefore a factor than can lead to stock-outs. Even though

KEMSA did not seem to have an effect on monthly stock-out rate, it had an effect on stock-out rates

of individual medicines.

We concluded therefore that FIF had an effect on both variation of monthly stock-out rate and on

individual medicines stock-out rate, while KEMSA had an effect on variation in the stock-out rate of

individual medicines. From literature, inappropriate selection of medicines, irrational use of

medicines, poor inventory keeping, poor forecasting and quantification methods, poor distribution

44

practices are some of the other factors that are known to reduce availability of medicines ((Mwathi

and Osuga, 2014). These factors arise especially where personnel handling medicines are non-

pharmacists or are pharmacists who lack commodity management skills.

A visual inspection of Figure 4.4 indicates that there was a decrease in stock-out rate after

introduction of the new scheme, but this was not sustainable. The change could have been due to

increased funding of the medicines budget through the next major source, which is FIF. It was short-

lived probably because of the declining supply of essential medicines from KEMSA. NHIF has low

coverage. From the hospital accounting records NHIF monies for both in-patient and outpatient

accounted for at most 15% of the FIF collection. The rest 85% was paid out of pocket by uninsured

patients and from government maternity reimbursements. The money the hospital receives from

NHIF is therefore not expected to meet the needs of the general hospital attendance. The hospital

pharmacy practices equity in that all clients are treated the same, for example, if a medicine is in

stock, it is available for all. This may be seen as disadvantageous to the NHIF beneficiaries but on

moral grounds separation of services may not be advocated for.

Many countries see the initiation or promotion of one or more insurance schemes as a way to address

health financing issues. During implementation, it is important that the context and surrounding

issues are taken into account. The NHIF implemented the scheme into a system that was

experiencing major gaps in funding. The quality of care of the NHIF patients was most probably

compromised due to lack of availability of essential medicines. Issues that should be addressed when

designing a health insurance scheme include policy objectives, population coverage, benefits to be

included, organization of health services, premium calculation and payment mechanism, utilization

and cost-control measures and administrative arrangements (WHO, 2012).

45

CONCLUSION

After introduction of the NHIF Civil Servants and Discipline Services Medical scheme there was

increased funding for medicines from the FIF but reduced financing for essential medicines from the

government at Webuye District Hospital. There was very little change in availability of medicines.

The new scheme did little to improve access to medicines for civil servants. Contextual factors such

as reduced medicines financing from the government, challenges in devolution of health and other

factors that affect availability of medicines needed to be considered. Expanding the coverage of the

scheme is recommended so as to increase financing of essential medicines. Additional studies on

availability of essential medicines after devolution of health should be done.

RECOMMENDATIONS

1. Additional financing for essential medicines is required for Webuye District Hospital. NHIF

should be extended coverage to a larger percentage of the population. Alternatively, the capitation

rate should be increased. This will result in more funding to the hospital hence more financing of

medicines. It has been shown that increasing FIF expenditure on essential medicines reduces the

stock-out rate.

2. When implementing new insurance schemes, contextual factors that may affect quality of care

need to be taken into consideration. For example, if NHIF is to extend the outpatient benefits to the

general population, one consideration in implementation would be the fact that health services have

been devolved

3. KEMSA lists should be synchronized with facility formulary lists. Even though procurement is

now being done at the county level, KEMSA has an advantage due to efficiency that comes from

economies of scale. However the KEMSA fill-rate should also be improved.

4. Additional studies on determinants of stock-out rates in public hospitals in Kenya should be done.

5. Studies on quality of medicines procured through the Facility Improvement Fund should be done.

6. This study should be replicated in other public hospitals.

46

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insurance. Health Policy 88, 371–380.

52

APPENDIX I: DATA COLLECTION FORMS

Form 1-FIF Allocated for purchase of medicines

2010-2011 2012-2013

Amount

allocated

(Kshs)

Total FIF

for the

quarter

% of

Total

FIF

Total

Amount

from

NHIF

Amount

allocated

(Kshs)

Total

FIF for

the

quarter

% of

Total

FIF

Total

Amount

from

NHIF

Quarter 1

Quarter 2

Quarter 3

Quarter X

Form 2-Number of days out of stock per month

Essential Medicine STRENGTH 2010-2011 2012-2013

Number of days out of

stock in a month (January

to December)

Number of days out of

stock in a month (January

to December)

ANAESTHETIC & ALLIED

Atropine injection 1mg/ml

Bupivacaine Injection 5mg/ml

Calcium gluconate injection 1G/10ml

Ephedrine injection

Halothane inhalation 100%v/v

Ketamine injection 50mg/ml

Lignocaine adrenaline/dental catridges 2%

Lignocaine injection 20mg/ml

Neostigmine injection 2.5mg/ml

Naloxone Injection

Pancuronium injection 2mg/ml

53

Sodium bicarbonate injection 0.84G/10ml

Suxamethonium injection 50mg/ml

Thiopentone injection 500mg/vial

Xylocaine (lignocaine) spray

ANALGESICS, ANTI-INFLAMMATORY

Aspirin 300mg tabs 300mg

Diclofenac Injection 75mg/ml 75/ml

Ibuprofen 200mg tablets 200mg

Ibuprofen suspension 200mg/5ml

Morphine Injection 10mg/ml

Morphine oral solution 1mg/ml

Paracetamol 500mg tabs 500mg

Paracetamol syrup 120mg/5ml

Paracetamol suppositories 125mg

ANTIALLERGICS, ANTIASTHMA DRUGS

Aminophylline injection 250mg/10ml

Beclomethasone Inhaler 100µg/puff

Chlorpheniramine 4mg tabs 4mg

Chlorpheniramine injection 10mg/ml

Chlorpheniramine syrup 4mg/5ml

Dexamethasone 0.5mg tabs 0.5mg

Dexamethasone injection 4mg/ml

Hydrocortisone injection 100mg/vial

Prednisolone 5mg 5mg

Salbutamol 4mg tabs 4mg

Salbutamol inhaler 200µg/puff

Salbutamol nebulising soln 5mg/ml

ANTICOAGULANTS

Heparin Inj 5000iu/ml

Warfarin 5mg tabs po

ANTIDIABETICS

Glibenclamide 5mg tabs 5mg/ml

Metformin 500mg tabs 500mg

Insulin Isophane Biphasic human 30/70 1000i.u

Insulin soluble human 1000i.u

ANTIHELMINTHICS

Albendazole 400mg tabs 400mg

Praziquantel 600mg tablets 600mg

54

CARDIOVASCULAR DRUGS

Atenolol 50mg tabs 50mg

Digoxin 0.25mg tabs 0.25mg

Enalapril 5mg tabs 5mg

Frusemide 40mg tabs 40mg

Frusemide injection 20mg/2ml

Hydralazine 20mg injection 20mg

Hydrochlorothiazide 50mg tabs 50mg

Magnesium sulphate injection 5g/10ml

Methyl Dopa 250mg tabs 250mg

Propranolol 40mg tabs 40mg

CNS DRUGS

Amitryptilline 25mg tabs 25mg

Benzhexol 5mg tabs 5mg

Carbamazepine 200mg tabs 200mg

Chlorpromazine 100mg tabs 100mg

Chlorpromazine injection 50mg/2ml

Diazepam 5mg tabs 5mg

Diazepam injection 10mg/2ml

Fluphenazine decanoate injection 25mg/ml

Fluoxetine caps 20mg

Haloperidol 5mg tabs 5mg

Haloperidol decanoate injection

Phenobarbitone 30mg tabs 30mg

Phenobarbitone injection

Phenytoin 50mg tablets 50mg

Phenytoin Injection

Valproic acid 200mg

GIT ACTING DRUGS

Bisacodyl tabs 5mg 5mg

Magnesium Trisilicate-Antacids 250/125mg

Metoclopramide 10mg tablets 10mg

Metoclopramide injection 10ml/2ml

Omeprazole 20mg caps 20mg

Ranitidine injection 25mg/ml

IV FLUIDS

Dextrose 10%

Dextrose 5%

55

Dextrose 50%

Half strength darrows

Normal saline (0.9% NaCl)

Sodium Lactate (hartmann's)

ORAL ANTIBIOTICS

Amoxicillin 250mg caps 250mg

Amoxicillin dry suspension 125mg/5ml

Amoxicillin/Clavulanate 625mg tabs 625mg

Amoxicillin-clavulanic acid 228mg/5ml 228mg/5ml

Chloramphenical suspension 125mg/5ml

Chloramphenical caps 250mg

Ciprofloxacin 250mg tabs 250mg

Cotrimoxazole 400:80 tabs 480mg

Clindamycin tabs 150mg

Doxycycline 100mg caps 100mg

Erythromycin suspension 125mg/5ml

Erythromycin tabs 250mg 250mg

Flucloxacillin 250mg caps 250mg

Metronidazole 200mg tabs 200mg

Metronidazole suspension 200mg/5ml

Nitrofurantoin 100mg tabs 100mg

Tinidazole tabs 500mg

ORAL ANTIFUNGALS

Fluconazole tabs 50mg

Griseofulvin 250mg 250mg

Nystatin suspension 100,000iu/ml

EAR, EYE & SKIN PREPS

Amethocaine eye drops

Atropine Eye Drops 1%

BenzylBenzoate Emulsion

Calamine Lotion

Ciprofloxacin ear/eye drops

Clotrimazole cream

Gentamicin eye drops

Hydrocortisone ointment

Prednisolone eye drops

Salicylic acid powder

Silver sulphadiazine ointment

56

Tetracycline eye ointment

ANTIMALARIALS

Artemether/Lumefantrine 12 tabs




Quinine 300mg tabs 300mg

Quinine injection 300mg/ml

Sulfadoxine/pyrimethamine tabs 500mg/25mg

PARENTERAL ANTIBIOTICS

Ampicillin 500mg injection 500mg

Benzathine Penicillin 2.4MU 2.4MU

Benzyl penicillin 1 MU 1MU

Benzyl penicillin 5MU 5MU

Ceftriaxone Inj 1g IG/vial

Ceftriaxone Inj 250mg 250mg

Chloramphenical injection 10mg/ml

(Flu)cloxacillin 250mgs inj 250mg

Gentamicin injection 20mg/2ml 10mg/ml

Gentamicin injection 80mg/2ml 40mg/ml

Metronidazole injection 500mg 500mg

SUPPLEMENTS

Ferrous sulphate 200mg tabs 200mg

Folic acid 5mg tabs 5mg

Oral Rehydration Salts

Potassium Chloride Injection 150mg

Zinc Tablets 20mg

THYROID&ANTITHYROID

Carbimazole 5mg

OTHERS

Activated Charcoal tabs

Acyclovir 400mg tablets 400mg

Clotrimazole pessaries 200mg

Dextran 70 500ml

Misoprostol tablet/pessary 200mg

Oxytocin injection

Water for injections 10ml

57

Form 3-Procurement of essential medicines by month

MONTH & YEAR……………………………………………….

Essential

Medicine

procured

Quantity

from

KEMSA

Quantity

from FIF

Quantity

from other

GOK

facility

Quantity

from other

sources

Total

Quantity

Essential

Medicine

procured

By Cost

KEMSA

By Cost

FIF

By Cost

other

GOK

facility

By Cost

from other

sources

Total Cost

Form 4-KEMSA fill-rate and presence on KEMSA order form

CYCLE/DATE ORDER VALUE RECEIVED

VALUE

PREVIOUS

ORDER’S FILL

RATE

1

2

3

X

58

ORDER DATE………………………………….

Essential Medicine

on KEMSA list

Ordered

quantity(A)

Received

Quantity (B)

Fill ratio

(A/B)

Total Stock-

out rate

1

2

3

X

Record whether on medicine was ordered and came,

not ordered, ordered but didn’t come, not on

KEMSA list

Essential Medicine KEMSA

ORDER 1

KEMSA

ORDER 2

KEMSA

ORDER X

1

2

3

X

Form 5-Nature of drugs procured per quarter from FIF

MONTH………………………………………………………………..

DRUG

PROCURED

Essential?(No/Yes) Cost (KShs) On hospital draft formulary?

(No/yes)

59

Form 6-Consumption rate of essential drugs

Form 7-Monthly workload

Essential Drug UNIT

Adjusted Consumption rate in

daily defined dose(DDD)

Average cost

per DDD

1

2

3

4

Month

Outpatient

workload(number

of patients)

Inpatient workload(as total

bed days)

1

2

3

4

60

APPENDIX II-Letter of Ethical Approval

61

Documents

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