Access to Health Care in Rural Jajarkot Baseline Survey Report of Findings

International Rescue Committee-Nepal Access to health care in rural Jajarkot Baseline Survey Report of Findings

Prepared by Neema Rani Tamang, IRC-Nepal Public Health Officer 2 November 2008

IRC/ISS health project

VDCs

Funded by ECHO The European Commission’s Humanitarian Aid department funds relief operations for victims of natural disasters and conflicts outside the European Union. Aid is channelled impartially, straight to victims, regardless of their race, ethnic group, religion, gender, age, nationality or political affiliation.

Table of contents

List of acronyms...... 3 Executive summary...... 4 1 Study context and justification...... 7 2 Objectives ...... 7 2.1 Primary objectives ...... 7 2.2 Secondary objectives...... 7 2.3 Study questions...... 7 3 Methods ...... 8 3.1 Study population ...... 8 3.2 Sample size calculation ...... 8 3.3 Sampling method ...... 8 3.4 Study period ...... 8 3.5 Data collection ...... 9 3.6 Data entry and validation...... 9 3.7 Data analysis...... 9 3.8 Ethical considerations...... 9 4 Results...... 10 4.1 Household characteristics and health access components...... 10 4.2 Factors associated with health access...... 21 5 Discussion ...... 24 6 Conclusions ...... 26 Annex 1: Questionnaire (English, Nepali) ...... 27 Annex 2: Informed consent form (English, Nepali)...... 33 Annex 3: Statistical tables ...... 35 Annex 4: List of 30 selected wards (clusters)...... 38

International Rescue Committee Page 2 of 38 List of acronyms

ECHO – European Commission’s Humanitarian Aid department FCHV – Female Community Health Volunteer HP – Health Post IRC – International Rescue Committee ISS – Interdependent Society MCHW – Maternal and Child Health Worker NGO – Non Government Organization OR – Odds ratio ORC – Outreach clinic PHC – Primary Health Care Centre SHP – Sub-health post VDC – Village Development Committee VHW – Village Health Worker

International Rescue Committee Page 3 of 38 Executive summary This survey was undertaken as part of IRC’s efforts in Jajarkot to improve access to and quality of health care in 10 VDCs. The study had three primary objectives: • Measure the access to health care in sub-health posts in 10 Village Development Committees (VDCs) of Jajarkot • Determine a baseline for measuring project impact • Investigate causes of lack of access to health care so that project interventions can be appropriately molded Out of those 10 VDCs (90 wards), 30 wards were selected at random, proportional to the ward population. In each ward, 26 households were selected randomly from voter registration lists and visited by teams of field interviewers during a period of just over two weeks in August 2008. A total of 774 households were interviewed and asked questions about access to health care over the previous three months.

Based on the results of the survey, answers to the three study questions were obtained: 1. Of the population who were sick in the three months prior to the survey, what percentage received care in a government health facility? 29% of households – with a 95% confidence interval of 21%-36% – in IRC’s 10 working VDCs received care at government facilities for a household member who was sick in the previous three months, as charted in Figure ES-1 below.

Figure ES-1: Access to health care in government facilities, Jajarkot, August 2008

The outcomes are remarkably similar to the figures obtained from the baseline access survey IRC and ISS conducted in Surkhet in September 2007, as shown in Table ES- 1 below, suggesting that the study methodology is robust.

Table ES-1: Comparison of outcomes from Jajarkot (August 2008) and Surkhet (September 2007) baseline surveys Outcome Jajarkot baseline Surkhet baseline Went to government facility 42% 43% If went to government facility, received care 68% 66% Went to government facility and received care 29% 28%

International Rescue Committee Page 4 of 38 2. For those people who were sick but did not receive care in a sub-health post, what was the reason(s)? The primary reason for people not accessing care in government facilities was lack (or perceived lack) of drugs – 61% of households gave that as a reason with a 95% confidence interval of 51%-70%. Other significant reasons were the facility being too far (22%), non-availability of staff (19%), the patient not being very sick (9%), not enough money (7%), and facility hours bad (4%). Those top six reasons are shown in Figure ES-2 below.

Top 6 reasons for not gaining access to health care, Aug 2008 (n=544)

70%

60%

50%

40%

30%

20%

10%

0% Percentage of respondents of Percentage Drug Too far Staff Not Money Facility problems problems sufficiently problems hours bad sick

Reason

Figure ES-2: Why patients did not access care in government facilities, Jajarkot, August 2008

3. For those people who were sick and did receive care in a sub-health post, what if any were the obstacles that had to be overcome in getting care? People receiving care were not unduly burdened by paying for it, with 87% paying no more than 50 rupees (less than one dollar) – see Figure ES-3 below – and only 4% having to sell land or livestock to afford care, though 35% receiving care did have to pay something, despite the fact that care in sub-health posts is supposed to be free for all.

International Rescue Committee Page 5 of 38 Cost of care in gov facility (rupees), Aug 2008 (n=217)

Don't know/no answer 101-500 1% 5% >500 7% 51-100 0%

1-50 No cost 23% 64%

Figure ES-3: Cost of care in government facilities, Jajarkot, August 2008

IRC and ISS can and will address the drug problems in sub-health posts, which has the potential to increase access another 61%, though of course that figure is not achievable in practice. The issue of distance will be addressed by IRC and ISS by conducting mobile clinics to supplement government outreach clinics and simultaneously provide on-the-job training for FCHVs. The staffing issues can be improved by government efforts toward better staff motivation, training, and time management. And the money obstacle can be avoided through more effective and consistent implementation of the existing free-care policy.

The survey results give IRC and ISS a clear roadmap for the future. The survey will be repeated at the end of the project to measure progress toward improving access.

International Rescue Committee Page 6 of 38 1 Study context and justification The International Rescue Committee (IRC) started working in Jajarkot in August 2008 to improve access to and quality of health care at the sub-health post level, with funding from ECHO and with local NGO partner the Interdependent Society (ISS). Although the project has a number of indicators to measure quality, and several proxy indicators for measuring access (such as the number of consultations in sub-health posts), a facility-based figure cannot capture the status of people who do not visit the facility. Using existing data, there is no direct way of measuring the extent to which people have access to health care nor whether by its end IRC’s project will have achieved an increase in access.

This survey was necessary to establish a baseline from which to measure progress made by IRC and ISS in working with the District Health Office to improve access to health care in Jajarkot, and to answer the question of how many (and what type of) people do have access to health facilities and what the obstacles are to obtaining health care in Jajarkot. The survey follows closely in the footsteps of comparable surveys in Surkhet to assess the progress made by a similar project in that district.1

2 Objectives 2.1 Primary objectives • Measure the access to government health care in sub-health posts and through outreach clinics and Female Community Health Volunteers (FCHVs) in 10 Village Development Committees (VDCs) of Jajarkot • Determine a baseline for measuring project impact • Investigate causes of lack of access to health care so that project interventions can be appropriately molded

2.2 Secondary objectives • To examine need for health care in study VDCs • To examine access by age, caste, economic status, and distance from health facility

2.3 Study questions • Of the population who were sick in the three months prior to the survey, what percentage received care in a government health facility? • For those people who were sick but did not receive care in a sub-health post, what was the reason(s)? • For those people who were sick and did receive care in a sub-health post, what if any were the obstacles that had to be overcome in getting care?

The first question addresses an important project indicator. (The project target is a 20% increase from baseline to end-of-project.) Answers to the other two will inform the activities to be undertaken in the project.

1 “Access to health care in rural Surkhet, baseline survey: report of findings”, International Rescue Committee report dated 31 October 2007; and “Access to health care in rural Surkhet, final survey: report of findings”, International Rescue Committee report dated 25 July 2008; available at http://un.org.np/reportlibrary/reportlibrary.php?bc=r&type=document.

International Rescue Committee Page 7 of 38 3 Methods 3.1 Study population The study population included all residents of the 10 VDCs, approximately 35,000 people. The VDCs are: Archhani, Bhagwati, Daha, Kortang, Majkot, Nayakbada, Paink, Ragda, Salma, and Talegaun.

3.2 Sample size calculation The sample size was calculated using the following formula: 2 2 pqkZ n = d 2 where the factor of 2 is the design effect accounting for a cluster survey design, k = number of groups in categories to be analyzed, Z = 1.96 (for 95% confidence interval), p = expected proportion with the characteristic of interest, q = expected proportion not having the characteristic (1-p), and d = half the desired width of the confidence interval (±d).

Since the proportion of the population that had access to health care when needed was not known before the survey, p is taken to be 50% (worst case). The desired precision is ±10%. The factor k is included to allow precision estimates of the level of access broken down by group characteristics, such as caste, giving a precise estimate not just for the overall population but for a specific caste or specific economic class; k is taken here to be 4.

Using the above values, the sample size is calculated to be 769.

3.3 Sampling method There are 9 wards in each of the 10 VDCs. The survey was conducted using a two-level cluster design: At the top level, 30 out of the 90 wards were selected randomly in proportion to ward population. The basic sampling unit was the household; within each ward at least 26 households were selected randomly as described below. Since the households of interest are those with at least one sick member in the past three months, the sample size, n, refers to those households only; households without sick members were supplemented with ones that did have sick members, though all sampled households were included in the survey. Thus the total number of sampled households was to be approximately n/s, where s is the (initially unknown) proportion of households with at least one sick member.

Within one cluster (ward), households were enumerated based on current voter registration lists obtained from the voter register list 2008, Election Commission Office, Kantipath, Kathmandu. Based on that list, 26 households were selected randomly before teams went to the field. Each household had an equal likelihood of being selected. Teams went to the field with a list of 26 households and the names of the adult members of those households. They physically located the households by asking about the names of household members. This process ensured a geographically diverse selection of households – some close to others, some isolated and remote – as well as a selection unbiased relative to characteristics of interest (distance from facilities, caste, poverty).

3.4 Study period Data collection lasted just over two weeks, from 17 August to 1 September. The study questionnaire addressed a recall period of three months before the time of the interview: June-August 2008.

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3.5 Data collection A standardized, piloted questionnaire was used at the household level by five pairs of trained local interviewers, which was essentially identical to the questionnaire used in the Surkhet survey.2 The preferred respondent in any household was the mother of the household; if she was not present, any adult female was accepted, and then any adult male, where “adult” was defined as at least 18 years old. Written consent to be interviewed was obtained from each respondent.

If a household was visited and no adult was home, then the closest neighbor was visited and interviewed, substituting for the pre-listed household. (And if no one at the closest neighbor was home, the next closest neighbor was visited, continuing until the team found someone at home.) Similarly, if no one in the household was sick in the previous three months, the closest neighbor was interviewed, continuing until a neighbor household was found in which someone was sick in the last three months. In that way, the team obtained interviews in each ward with at least 26 households in which someone was sick in the past three months. In some cases the household itself could not be found or was erroneous; in those cases the team took as a substitute the next closest household number from the voter registration list.

The questionnaire addressed distance from government health facilities, household assets, whether and how any sick household members obtained health care, and if not, why not.

3.6 Data entry and validation Data was entered into a computer by an ISS data entry technician using Epi Info 3.3 and spot checked randomly by IRC’s Clinical and Public Health Specialist and Public Health Officer.

3.7 Data analysis Epi Info 3.3 and Intercooled Stata 8.2 were used for data analysis. The non-response rate for specific questions was calculated as the fraction of respondents giving no answer or “don’t know” divided by the total number of households sampled. Univariate analysis consisted of calculation of variable frequencies and percentages, with confidence intervals calculated using robust variance estimation accounting for statistical dependence of samples within clusters (the 26 households within single wards). Confidence intervals were calculated only for those variables of particular interest. Stata’s “svymeans” command was used for the robust confidence interval calculations.

Bivariate analysis was conducted to determine the factors associated with achieving access to health care. Logistic regression was used to calculate odds ratios, with robust variance estimation again used to account for dependence within wards and resulting in adjusted p-values and confidence intervals. Stata’s “logistic” command with the “cluster” option was used for the analysis.

3.8 Ethical considerations No experimentation was carried out on human subjects. The questionnaire was brief and took no more than 10-15 minutes to administer to each household (generally only five minutes), causing a minimum of inconvenience for the respondents. No questions were emotionally disturbing, and there were no physically invasive examinations.

Respondents did not directly benefit from the survey, but the study results will be used to inform the project interventions, which will benefit the entire study population.

2 “Access to health care in rural Surkhet, final survey: report of findings”, International Rescue Committee report dated 25 July 2008; available at http://un.org.np/reportlibrary/reportlibrary.php?bc=r&type=document.

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Written informed consent was obtained from each study respondent. Confidentiality of responses was assured by storing paper questionnaires in locked file cabinets and by restricting access to the computer database to the data entry technician, the ISS project coordinator, and the IRC survey analysis team.

4 Results 4.1 Household characteristics and health access components A total of 774 households were sampled, 33% of the total number of households in the 30 selected wards and 14% of the total number of households in the 10 VDCs. The population of the sampled households was 5,041 people (mean household size of 6.5). No sampled household refused to respond to the survey, although some could not or would not answer individual questions. Of the sampled households, only 10 reported no household member being sick during the previous three months, so the total number of households with sick members was 764 (99%), just under the target of 769 (see Section 3.2).

Frequencies of the data collected during the survey are shown in Table 1 below, along with variables constructed from raw data. The primary objective of the study was to find the percent of households who had access to government health care, defined as the proportion of households that had a sick member in the past three months who went to a government facility and received care (A): sick with HHs # HHs with sick members who went to government andfacility received care A = . sick with HHs# with sick members The value of this proportion was A = 29%: of those households with a sick member, 29% both went to a government facility and received care for the patient. The statistical 95% confidence interval for this access result was 22%-35%, which means, loosely speaking, that based on the sampling design there is a 95% probability that the range from 22% to 35% contains the true population access figure. In other words, the actual access figure is unlikely to be greater than 35% or less than 22%.

The access percentage has two component parts: the proportion of households with sick members who went to a government facility; and of those households that took the patient to a government facility, the proportion that received care. The first (F) is defined as: sick with HHs # HHs with sick members who went to government facility F = sick with HHs# with sick members and the second (C) as: sick with HHs # HHs with sick members who went to government andfacility received care C = . sick with HHs # HHs with sick members who went to government facility It follows immediately that ×= CFA . In fact, from these survey data, it turns out that 42% of sick households went to a government facility – F = 42%, 95% confidence interval 34%-51% – and 68% of those received care: C = 68%, 61%-75%. As expected, 29% = 42% × 68%. The breakdown is shown graphically in Figure 1.

Table 1: Access survey variable frequencies Variable n Number Percent Brahmin/Chhetri 520 67% Janjati 19 2% Caste Dalit 774 235 30% seh Other 0 0% <=5 283 37%

Household size 74 7 All hou olds >=6 491 63%

International Rescue Committee Page 10 of 38 Variable n Number Percent <=1 361 47% Distance to >1, <=2 190 25% closest >2, <=4 185 24% government health

facility (hours) >4 774 32 4% Don't know/no answer 6 1% Sick in last 3 months 764 99%

Owns land 748 98% 764 <45 157 21% >=45, <75 140 19% Land value (1,000 >=75, <150 105 14%

rupees) 748 >=150 183 24% Don't know/no answer 163 22%

Owns livestock 726 95% 764 <8 53 7% >=8, <15 91 13% Livestock value >=15, <25 127 17%

(1,000 rupees) 726 >=25 357 49%

Don't know/no answer 98 13% <=30 471 62% How long ago 31-60 169 22% illness started (days) >60 123 16% Don't know/no answer 1 0% Male 312 41% Sex of patient Female 452 59% 0-4 147 19% 5-14 97 13% Age of patient 15-49 (years) 361 47% >=50 147 19%

Don't know/no answer 764 12 2% Illness 683 89% Injury 52 7% Nature of health Pregnancy complication 4 1% problem Delivery complication 10 1% Other 15 2% Don't know/no answer 0 0% Yes 747 98%

Households with someone sick in last three months sick in last three with someone Households Considered No serious 16 2% Don't know/no answer 1 0%

Went to Yes 323 42% government No 440 58% facility 764 Don't know/no answer 1 0% Total who went to Yes 218 29% government No 544 71%

facility and 764 received care Don't know/no answer 2 0% Yes 106 14% Obtained care No 656 86%

from FCHV 764 Don't know/no answer 2 0% Obtained care Yes 32 4% from government No 764 730 96%

International Rescue Committee Page 11 of 38 Variable n Number Percent outreach clinic Don't know/no answer 2 0% Obtained care Yes 290 38% from government No 471 62%

facility, FCHV, or 764 outreach clinic Don't know/no answer 3 0% Sub-health post 298 92% Health post 20 6% Type of PHC 0 0% government Regional hospital

323 1 0% facility Surkhet District hospital 3 1% Khalanga Other 1 0% Drug problems 12 67% If not closest Facility hours bad 1 6% facility, reason Staff problems 18 3 17% Other 2 11% If went to Yes 218 68% government No 104 32%

facility, received 323 care Don't know/no answer 1 0% Those who went to government facility Those who went No cost 138 64%

in 1-50 50 23% Cost of care in 51-100 1 0% government facility (rupees) 101-500 217 11 5% >500 15 7% Don't know/no answer 2 1% Cash 52 66% Borrowed 23 29% Payment method Sold land, livestock

79 3 4% government facilities Other 1 1%

Those who received care received Those who Don't know/no answer 1 1% Drug problems 243 55% Too far 119 27% Staff problems 64 15% Not sufficiently sick 48 11% Money problems 36 8% Too busy 18 4% Home remedies used 17 4% Facility hours bad 16 4% Reason for not Patient too weak or sick 14 3% going to No companion 9 2%

government 440 facility Treatment not possible 5 1% Went to FCHV, MCHW, 4 1% ORC Unaware of services 3 1% Waiting time too long 2 0% Medical shop closer 1 0% Transportation problems 1 0% No faith in treatment 1 0% Other 19 4%

Those who did not go to government facilities government Those who did not go to Don't know/no answer 8 2%

Sought care elsewhere 440 219 50%

Where care was Did not receive care 9

21 1 0%

International Rescue Committee Page 12 of 38 Variable n Number Percent received Private pharmacy 192 88% Traditional healer 3 1% Home remedies used 12 5% FCHV 5 2% Other 6 3%

to Drug problems 87 84% Not possible 6 6% nt nt Reason for not Staff problems 39 38% receiving care at Money problems 0 0%

government 104

care at care at facility Facility hours bad 7 7% facilities

governme Waiting time too long 0 0% Other but did not receive but did not receive 3 3% Those who went Those who

re Drug problems 330 61% id id Reason for not Too far 119 22% going to or not Staff problems 103 19% receiving care at government Not sufficiently sick 544 48 9% facility Money problems 36 7% not go or did

Those who d Those who Facility hours bad 23 4% not receive ca not receive Note: Percenta ges for outcome variables do not include “don’t know/no answer” respon ses in the denominator

Figure 1: Access to health care in government facilities, Jajarkot, August 2008

The other data in Table 1 were collected (or calculated) to analyze the reasons for lack of access and to further characterize households in the IRC working area. As shown in Figure 2, over two thirds of the households were Brahmin/Chhetri with Dalits making up virtually all the rest.

International Rescue Committee Page 13 of 38 Caste of respondents, Aug 2008 (n=774)

Other Dalit 0% 30%

Janjati Brahmin/Chhetri 2% 68%

Figure 2: Caste of survey respondents, Jajarkot, August 2008

A critically important factor for access is how far people live from government facilities. More than half of the households reported living more than one hour from a government health facility (see Figure 3), reflecting the remoteness of the VDC surveyed.

Distance to health facility (hours), Aug 2008 (n=774)

>4 4% >2, <=4 24% <=1 47%

>1, <=2 25%

Figure 3: Distance to government facilities, Jajarkot, August 2008

Questions about land and livestock ownership were asked in an attempt to measure the affect of poverty on access. Almost all households owned both land and livestock, though there was much more of a spread in the value of land or livestock (see Figures 4 and 5). In the survey in general, very few respondents could not or would not give an answer, but for the value of land, almost a quarter of households did not know or gave no answer.

International Rescue Committee Page 14 of 38 Land value (1,000 rupees), Aug 2008 (n=748)

Don't know/no answer <45 22% 21%

>=45, <75 >=150 19% 24% >=75, <150 14%

Figure 4: Value of land owned by respondents, Jajarkot, August 2008

Livestock value (1,000 rupees), Aug 2008 (n=726)

Don't know/no answer <8 >=8, <15 13% 7% 13%

>=15, <25 17% >=25 50%

Figure 5: Value of livestock owned by respondents, Jajarkot, August 2008

Nearly 60% of the patients were female, with nearly half of the patients being adults under 50 years (see Figures 6 and 7). Fewer than 20% of the patients were children under five years old. The family considered 98% of the health problems to be serious, even when the illness was just a cold or other minor ailment. In villages where children can die from pneumonia or diarrhea, even minor ailments may be considered serious, but the implication for this analysis is that whether the disease was considered serious or not will not be useful for addressing access, and will not be considered further.

International Rescue Committee Page 15 of 38 Sex of patients, Aug 2008 (n=764)

Male 41%

Female 59%

Figure 6: Sex of patients, Jajarkot, August 2008

Age of patients, Aug 2008 (n=764)

Don't know/no answer >=50 2% 0-4 19% 19%

5-14 13% 15-49 47%

Figure 7: Age of patients, Jajarkot, August 2008

Of those 323 households who went to a government facility, 92% went to a sub-health post. The 6% who went to a health post visited nearby VDCs. For 94% of those going to a government facility, that facility was the closest one; for those 18 households that did not visit the closest facility, two thirds gave as reason lack of drugs and 17% mentioned staff problems (staff not available or unpleasant).

While the definition of “health access” used in this study is based on care received in a fixed government facility, Nepal’s (and IRC’s) strategy includes a strong emphasis on community-based care through Female Community Health Volunteers (FCHVs) as well as through outreach clinics, supposed to be held two or three times a month in each VDC, in wards other than the one in which the sub-health post is located. This survey included questions asking whether people received care from FCHVs or outreach clinics and the results show that while there is some utilization of FCHVs (14%), very few people use outreach clinics (4%). (See Figure 8.)

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Figure 8: Source of government care, Jajarkot, August 2008

The survey also asked about cost of care for those households (217) that received care in a government facility, and expenses were generally low (see Figure 9): 64% paid no money at all and 87% paid no more than 50 rupees (less than a dollar). Of the 79 households that did pay money, two thirds paid in cash, and almost all the rest borrowed money; only 4% had to sell land or livestock to pay for care. (See Figure 10).

Cost of care in gov facility (rupees), Aug 2008 (n=217)

Don't know/no answer 101-500 1% 5% >500 7% 51-100 0%

1-50 No cost 23% 64%

Figure 9: Cost of care in government facilities, Jajarkot, August 2008

International Rescue Committee Page 17 of 38 Method of paying for care, Aug 2008 (n=79)

Other 1% Sold land, livestock 4% Borrowed 29%

Cash 66%

Figure 10: How patients paid for care in government facilities, Jajarkot, August 2008

Over half the households with sick members did not go to a government facility, and they were asked why not (see Figure 11). Some households gave more than one response, and up to three responses were coded and included in Table 1; the percentages in the table are percentages of households, so the total will add up to more than 100%. More than half of the households gave drug problems as a reason for not going: either the facility was thought to lack drugs or the drugs were perceived to be ineffective, of poor quality. Over a quarter of the households cited distance as a factor, with the facility being too far away from home. Fifteen percent of the households cited staff problems (staff not available or rude) and 11% said that the patient was not sufficiently sick to go, even if the health problem had previously been judged to be “serious”. The last major reason given – by 8% of respondents – was money problems (not enough money or care judged to be too expensive). Other reasons were cited by fewer than 4% of households: too busy, bad facility hours, treated the patient at home, etc. Five households said something to the effect that treatment was not possible, which generally meant that the condition (e.g., if an operation or test was needed that had to be performed elsewhere) was not treatable at the sub-health post and so there was no point in going.

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Figure 11: Why patients did not seek care in government facilities, Jajarkot, August 2008

Of those households that sought care elsewhere, for whatever reason, the overwhelming majority (88%) went to a private clinic/pharmacy. Anecdotal comments given included that the medical shops (private pharmacies) were closer, the staff treated people better, service was faster, and the drugs were better (and available).

Of those households that did go to a government facility but did not receive treatment, almost everyone gave lack of drugs as the reason (see Figure 12). (Again, some households gave two reasons, so the percentages in the table may add up to more than 100%.) Over a third of respondents complained that staff were not present or treated patients rudely. No households cited money problems.

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Figure 12: Why patients who went to government facilities did not receive care, Jajarkot, August 2008

Finally, the reasons for not going to a government facility and those for not receiving treatment were merged together, so that the final entries in the table address all those 71% of households that did not go to government facility or did not receive care (i.e., did not access health care). The reasons given in the table are the six top reasons given for not having access to health care at government facilities: lack of (or poor) drugs, the facility too far away, facility staffing issues, patient not sufficiently sick, money problems, and inadequate facility hours. The overwhelming reason given was lack of drugs or poor quality drugs: 61% of respondents, with a 95% confidence interval of 51%-70%. (See Figure 13.)

International Rescue Committee Page 20 of 38 Top 6 reasons for not gaining access to health care, Aug 2008 (n=544)

70%

60%

50%

40%

30%

20%

10%

0% Percentage of respondents of Percentage Drug Too far Staff Not Money Facility problems problems sufficiently problems hours bad sick

Reason

Figure 13: Top 6 reasons for patients’ not being able to access health care, Jajarkot, August 2008

4.2 Factors associated with health access Beyond the above analysis of reasons given by households for not going to government health facilities or not receiving care, this section presents the results of a statistical analysis of factors that may be associated with health access. Table 2 breaks down access (referred to above as “A”) according to various variables that are statistically associated with access. Table A-1 in Annex 3 includes all variables that were hypothesized to be associated with access even though in the end this survey found no evidence for association.

For each factor, Table 2 shows the total number of households in each category (e.g., serious or not serious), the number of those that achieved access and the corresponding percentage, an odds ratio (OR) comparing each category with the reference category, and the p-value measuring the statistical significance of the association. The greater the divergence of the OR from unity (1), the stronger the association. In general, if the p-value is less than 0.05, it can be concluded that there is an association, and the smaller the p-value the stronger the likelihood that the finding is not due to chance. See Annex 3 for a more complete explanation of the OR and p-value.

Table 2: Factors associated with whether patients went to government facility and received care Factor Total Yes Percent Odds Ratio p-value Livestock value Rs 0-15,000* 143 47 33% Rs >=15,000 484 129 27% 0.74 0.096 Household size >=6* 487 128 26% 0-5 275 90 33% 1.36 0.055 Distance <=1 hour* 353 135 38% 1-2 hours 187 53 28% 0.64 0.054 2-4 hours 184 25 14% 0.25 <0.0005

International Rescue Committee Page 21 of 38 Factor Total Yes Percent Odds Ratio p-value >4 hours 32 4 13% 0.23 0.002 Distance (dichotomous) >1 hour* 403 82 20% <=1 hour 353 135 38% 2.42 <0.0005 *Reference group

Table 2 shows that there are very few statistically valid associations between access and the factors measured in this study, and in fact it is only distance for which the statistical significance is strong: People living an hour or closer to the facility were two and a half times as likely as those living farther away to have access to health care (OR=2.42, p=<0.0005). The livestock and household size associations were only borderline significant and the associations were weak: Relatively wealthy people – those with livestock worth more 15,000 rupees – are 1.35 times (1/0.74) less likely to have access to health care as those having livestock worth less than 15,000 rupees (p=0.096) and households having five or fewer members are 1.36 times more likely to access health care than larger households (p=0.055).

One way to gain greater confidence in an association is by finding a stimulus-response association, as with the four-category distance variable shown in the table, where the farther away the household, the less likely it is to access health care. In particular, people living 1-2 hours away are 1.5 (1/0.64) times as likely not to access health care as people living an hour or less away (p=0.054), people living between 2-4 hours away are 4 times (1/0.25) as likely not to access health care (p<0.0005), and people living more than four hours away are over 4 (1/0.21) times as likely not to access health care (p=0.002). Figure 14 graphically demonstrates the decline in access as distance increases.

Health access by distance August 2007 (n=756)

100% 90% 80% 70% 60% 50% 40% 30% 20% Percentage receivingcare 10% 0% <=1 hour* 1-2 hours 2-4 hours >4 hours

Distance to government health facility

Figure 14: Relationship between distance and access to health care, Jajarkot 2008

Tables 3 and 4 show the results of similar analyses of association, this time for the two components of access: 1) going to a government health facility and 2) receiving care there. As would be expected, for seeking care the same association with distance holds, but even more strongly. People who live more than an hour away from a facility are 3 times as likely as those living closer not to go to a government facility (p<0.0005), and people living more than four hours away are 4.8 (1/0.21) times as likely not to go. Figure 15 dramatically shows the drop in the percentage of patients who seek care from a government facility the farther away they live. While there is no association with household

International Rescue Committee Page 22 of 38 size, the association with livestock value is even stronger than for overall access: wealthier people were 1.6 times less likely to seek care than poorer people (p=0.014).

Table 3: Factors associated with whether patients went to government facility Factor Total Yes Percent OR p-value Livestock value Rs 0-15,000* 144 75 52% Rs >=15,000 484 194 40% 0.62 0.014 Distance <=1 hour* 354 202 57% 1-2 hours 187 66 35% 0.41 <0.0005 2-4 hours 184 47 26% 0.26 0.001 >4 hours 32 7 22% 0.21 0.001 Distance (dichotomous) >1 hour* 403 120 30% <=1 hour 354 202 57% 3.13 <0.0005 *Reference group

Seeking health care by distance August 2008 (n=756)

100%

90%

80%

70%

60%

50%

40%

30%

Percentage seeking care seeking Percentage 20%

10%

0% <=1 hour* 1-2 hours 2-4 hours >4 hours Distance to government health facility

Figure 15: Relationship between distance and seeking health care, Jajarkot, August 2008

In searching for factors associated with whether patients received care if they went to a facility, as shown in Table 4, a borderline significant (and unexpected) association with distance was found, as well as a strongly significant (and equally unexpected) association with household size: Small households were twice as likely to receive care as larger households (p=0.011). No other household variable for which data were collected during this study could be associated with whether patients received care once they had gone to a facility.

Table 4: Factors associated with whether patients received care if they went to a government facility Factor Total Yes Percent OR p-value Household size >=6* 205 128 62%

International Rescue Committee Page 23 of 38 Factor Total Yes Percent OR p-value 0-5 118 90 76% 2.01 0.011 Distance <=1 hour* 202 135 67% 1-2 hours 66 53 80% 1.99 0.046 2-4 hours 47 25 53% 0.56 0.081 >4 hours 7 4 57% 0.65 0.367 Distance (dichotomous) >1 hour* 120 82 68% <=1 hour 202 135 67% 0.95 0.864 *Reference group 5 Discussion The findings above clearly answer the primary research question driving the study: 29% of households in IRC’s 10 working VDCs had access to government health care in the preceding three months. This result is remarkably close to the figure obtained from the baseline access survey in Surkhet in September 2007 of 28%, as are the two component percentages as shown in Table 5. However, one major difference in the timing of the two studies is that the government universal free- care policy was initiated in January 2008, which contributed to a significant increase in access in Surkhet (to 43% by June 2008). Two findings discussed below suggest that the free-care policy has not been as effective in Jajarkot as it was in Surkhet.

Table 5: Comparison of outcomes from Jajarkot (August 2008) and Surkhet (September 2007) baseline surveys Outcome Jajarkot baseline Surkhet baseline Went to government facility 42% 43% If went to government facility, received care 68% 66% Went to government facility and received care 29% 28%

First, the biggest reason people in Jajarkot gave for not accessing government care was a perceived lack of drugs in the closest facility, generally a sub-health post, which suggests that while drugs may be free, they are often not available. If a solution to the drug problem can be found, access would be greatly increased. Along with ensuring a supply of drugs, people would have to be informed about the newly reliable drug supply. Lack of drugs was overwhelmingly the reason that people who went to government facilities were not treated, but more than half of households also cited it as their reason for not even seeking treatment at a government facility.

Second, while the economic impact on people receiving treatment was generally not onerous, with only 7% of people not accessing health care giving lack of money as a reason, and judging both by the reported costs (87% less than 50 rupees) and the method for paying (only 4% had to sell land or livestock), somewhat puzzling is the finding that over a third of respondents who received care had to pay something, despite the fact that all care in sub-health posts is supposed to be free. By contrast, in the IRC-ISS survey conducted in Surkhet in June 2008, just two months earlier, only 18% of respondents who received care reported having to pay something. That 64% of Jajarkot respondents paid nothing shows that the free-care policy is working, but apparently it is not being consistently implemented throughout the district.

While surveys in Surkhet showed no statistically significant association between access and poverty (as measured by assets such as land value and livestock value), this survey produced the result that wealthier people (as measured by livestock value) were less likely to seek care at government facilities. There is no obvious explanation for this finding, except possibly that wealthy people are more likely to make use of private pharmacies, which are more convenient, albeit more expensive.

International Rescue Committee Page 24 of 38 However, the data do not support that hypothesis; of households that did not seek government care, 89% of wealthy households received care at private pharmacies as opposed to 84% of poor households, but the difference is not statistically significant (p=0.471) (data not shown). Household size is sometimes also taken to be a proxy measure of poverty (large households being poorer), but in this survey it was indeed small households that were twice as likely to receive care given that they had gone to a facility. However, there is no obvious reason why household size should be related to receiving care, unless a household did not have sufficient money to pay for care, yet not a single household cited money as a reason for not receiving care. It is possible that both of these anomalous findings are spurious, due to chance only, but a more in-depth study would be necessary to decide for sure.

The issue of the government facilities being too far for some households (27% of those that did not seek treatment) is more difficult than the drug issue to resolve. One solution would be for the government to put more emphasis on outreach clinics; this study suggests that with only 4% of households receiving care from outreach clinics, that mechanism is vastly underutilized. Already the VHW and MCHW are supposed to be in the field 20 days per month, but in practice they work outside the sub-health post only two or three days per month at most. Sending them more regularly and effectively to more remote wards would help provide care to those people living far from the fixed facility. Increasing the role of FCHVs is also conceivable, but not an optimal solution, since they are, after all, volunteers, and it is risky to pin too much on their ability to provide routine care. Moreover, in Jajarkot there is at most one FCHV per ward, even though the wards are large and require hours of hiking to traverse, limiting the role a volunteer can play. Nonetheless, by the end of the IRC-ISS project in Surkhet 34% of households were receiving care from FCHVs, so it is worth putting forth an effort in Jajarkot to increase utilization of FCHVs.

Availability of staff was an issue for 19% of the people who did not obtain access. That is a problem that is well within the scope of government efforts by ensuring better time management of facility staff, increasing their motivation, and giving them better training. Those solutions are easy to write but harder to implement, and ensuring effective results is even more difficult. But this survey suggests that it is necessary.

A surprising number of households gave as reason for not going to a government facility that the patient was not very sick. At first glance that seems to contradict the supposed seriousness of the illness, and it may indeed be a contradiction. But it may also be true that people are saying that the disease is serious enough to have them concerned and want to seek care, but going to a facility is not worth it.

While the study was rigorously designed and conducted, there are inevitably some limitations. The primary limitation is that all illnesses were potentially included in the study, yet many people would not even attempt to seek care for simple illnesses such as a common cold. A more accurate reflection of access would measure whether people with serious illnesses can receive care in government facilities. This study attempted to address that variation by using the household’s own assessment of the seriousness of the illness to categorize the responses, with little success, since almost everyone rated the illness as “serious”.

Three months is a relatively long period to expect people to remember details of who was sick when, especially regarding minor illnesses. However, since the study was primarily interested in illnesses that would cause people to seek health care, and since people are likely to remember trips to health facilities in the past three months, the recall problem is not expected to have impacted the results in a serious way, though there may be a bias in favor of more recent, less serious diseases (since more distant, less serious diseases would be less likely to be remembered).

International Rescue Committee Page 25 of 38 Use of voter registration lists for household selection was risky, because any missing households would be excluded from the study and may be ones sharing characteristics of interest in the study (e.g., relative isolation). However, during field testing and implementation no evidence was found of systematic missing households, and there was no feasible alternative that would improve the selection; on the whole, there is no reason to think that any bias was introduced by using the voter registration lists. Many remote and isolated households were sampled that would never have been found using any other selection technique.

6 Conclusions The survey successfully provided answers to all the questions asked of it: 1. 29% of households in IRC’s 10 working VDCs received care at government facilities for a household member who was sick in the previous three months. This result sets the baseline for IRC’s work through July 2009. 2. The primary reason for people not accessing care in government facilities was lack (or perceived lack) of drugs. Other significant reasons were the facility being too far, non- availability of staff, not enough money, the patient not being very sick, and bad facility hours. 3. People receiving care were not unduly burdened by paying for it, with 87% paying no more than 50 rupees (less than one dollar) and only 4% having to sell land or livestock to afford care, though 35% receiving care did have to pay something, despite the fact that care in sub- health posts is supposed to be free for all.

The survey results give IRC and ISS a clear roadmap for the future. The survey will be repeated at the end of the project to measure progress toward improving access.

International Rescue Committee Page 26 of 38

Annex 1: Questionnaire (English, Nepali) [see following pages]

International Rescue Committee Page 27 of 38 IRC/ISS health access survey form, Jajarkot; 27 July 2008 Preferred informant: Mother of household or adult female; if none, then any adult; if none, then select next closest house. 1. Date: 2. Interviewer: 3. Supervisor: Supervisor signature: 4. VDC: 5. Ward: 6. Village:

7. Household number: 8. Respondent name: 9. Respondent caste:

Circle appropriate answer below How many people live in your household (only those who 10. Answer: stay in your house)? What is the nearest government health facility to your 11. Answer: house? How far is the nearest government health facility from your 12. Answer: house (in hours)? 13. 1-[0,1]; 2-(1,2]; 3-(2,4]; 4->4; 9-don’t know/no answer Has a member of your household been sick or injured over 14. 0-no; 1-yes; 9-don’t know/no answer the past 3 months? [Include health problems related to pregnancy, but not normal deliveries] If answer to previous question is “no” or “don’t know”, go to D. When was the last time someone in your household was 15. Answer: sick or injured (how long ago, in days)? 16. 1-[0,30]; 2-[31,60]; 3-[61,90]; 9-don’t know/no answer Please answer the following questions about the latest person in your household to be sick or injured: Sex 17. 0-male; 1-female; 9-no answer Age (years, at time of medical problem) 18. Answer: 19. 1-[0,4]; 2-[5,14]; 3-[15,49]; 4-≥50 9-don’t know/no answer Reason medical care needed 20. 1- illness; 2- injury; 3-pregnancy complication; 4-delivery complication; 5- other; 9-don’t know/no answer 21. Specify other: Did the family consider the health problem to be serious? 22. 0-no; 1-yes; 9-don’t know/no answer Did the patient go to a government health care facility? 23. 0-no; 1-yes; 9-don’t know/no answer If answer to previous question is “no” or “don’t know”, go to A What government facility did the patient go to first? 24. Answer: 25. 1-SHP; 2-HP; 3-PHC; 4-Regional hospital (Surkhet); 5-Bheri Zonal hospital; 6-other; 7-District hospital (Khalanga) 9- don’t know/no answer 26. Specify other: If the answer to no. 24 is not the same as no. 11: Why did 27. 1-facility had no drugs; 2- facility staff not the patient not go first to the closest government facility? available; 3-facility staff refuse to treat some patients; 4-facility staff receive patients rudely; 5-facility hours are not adequate; 6- facility was closed; 7-have to wait too long at facility for treatment; 8- other; 9-don’t know/no answer 28. Specify other: Did the patient receive care there or at any other 29. 0-no; 1-yes; 9-don’t know/no answer government facility? If answer to previous question is “no” or “don’t know”, go to B. What was the total cost of obtaining care (including 30. Answer: consultation, tests, drugs, transport) (in rupees)? 31. 1-no cost; 2-[1,50]; 3-[51,100]; 4- [101,500]; 5->500; 9-don’t know/no answer

International Rescue Committee Page 28 of 38 If answer to previous question is “no cost”, go to C. How did your family pay for the treatment? [Select all 32. 1-cash; 2-borrowed money; 3-sold land or responses given by respondent.] livestock; 5-other; 9-don’t know/no answer 33. Specify other: Go to C. A Why did the patient not go to a 34. 1-lack of money for treatment; 2- lack of money for government health care facility? [Select transport; 3-too far; 4-facility had no drugs; 5- facility all responses given by respondent.] staff not available; 6-facility staff refuse to treat some patients; 7-facility staff receive patients rudely; 8-facility hours are not adequate; 9- facility was closed; 10-have to wait too long at facility for treatment; 11- not sufficiently sick; 12-other; 19-don’t know/no answer 35. Specify other: Did the patient seek care elsewhere? 36. 0-no; 1-yes; 9-don’t know/no answer If answer to previous question is “no” or “don’t know”, go to C. Where did the patient first receive care? 37. 1-did not receive care; 2- private clinic/medical shop; 3- traditional healer; 4-other; 9-don’t know/no answer 38. Specify other: Go to C. B Why did the patient not receive care at a 39. 1- no money for treatment; 2-facility had no drugs; 3- government facility? [Select all responses facility staff not available; 4-facility staff refused to given by respondent.] treat patient; 5-facility was closed; 6-had to wait too long at facility for treatment; 7-other; 9-don’t know/no answer 40. Specify other: C Did the patient receive care from an FCHV? 41. 0-no; 1-yes; 9-don’t know/no answer Did the patient receive care at a regular scheduled 42. 0-no; 1-yes; 9-don’t know/no answer government outreach clinic? Did the patient receive care at an IRC-ISS mobile 43. 0-no; 1-yes; 9-don’t know/no answer clinic? Does your household own any land? 44. 0-no; 1-yes; 9-don’t know/no answer If yes, and if you were to buy land exactly like yours 45. Answer: today, how much money would you have to pay for 46. 1-[0 , 44,999]; 2-[45,000 , 74,999]; 3-[75,000 , it (in rupees)? 1,49,999]; 4-≥1,50,000; 9-don’t know/no answer Does your household own any livestock (buffalo, 47. 0-no; 1-yes; 9-don’t know/no answer cows, oxen, goats, pigs, chickens)? If yes, and if you were to buy animals exactly like 48. Answer: yours today, how much money would you have to 49. 1-[0,7999]; 2-[8000, 14,999]; 3-[15,000 , pay for them? 24,999]; 4-≥25,000; 9-don’t know/no answer D: Those are all the questions I have; thank you very much for your time. [End of survey.]

International Rescue Committee Page 29 of 38 27 July 2008 Hffh/sf]6 lhNnfsf] :jf:Yo kx'Fr ;DaGwL ;j]{If0f kmf/d cGt/{fli6«o påf/ ;ldlt g]kfn ÷ cGt/lge{/ ;dfh k|fylds ;"rgfstf{ M 3/sf] cfdf jf jo:s dlxnf; olb geP s'g} jo:s ;b:o, olb geP glhssf] csf]{ 3/df hfg\xf];\ . 1. ldlt: 2. cGtjf{tf{ stf:{ 3. ;'kl/j]Ifs: ;'kl/j]Ifssf] b:tvt:

4. uf=lj=;=: 5. j8f: 6. ufpmF÷6f]n:

7. 3/w'/L g+=: 8. ;"rgfstf{sf] gfd: 9. hft:

pko'Qm pQ/df uf]nf] -)_ lrGx nufpg'xf];\ tkfO{+sf] kl/jf/df slt hgf ;b:ox? x'g'x'G5 -3/df w]/}h;f] 10. pQ/: a:g] ;b:ox? dfq_ < tkfO{+sf] 3/af6 ;a}eGbf glhssf] ;/sf/L :jf:Yo ;+:yf s'g xf] < 11. pQ/: tkfO{+sf] 3/af6 ;a}eGbf glhssf] ;/sf/L :jf:Yo ;+:yf slt 6f9f 5 - 12. pQ/: 306fdf pNn]v ug'{xf];_ < 13. 1-[),!]; 2-(!,@]; 3-(@,$]; 4->$; 9-yfxf 5}g÷pQ/ cfPg uPsf] tLg dlxgf leqdf tkfO+{sf] kl/jf/sf] s'g} ;b:o lj/fdL ePsf] 14. 0-lyPg; 1-lyof;] 9-yfxf 5\}g÷pQ/ cfPg jf rf]6k6s nfu]sf] lyof] < -k|;'lt ;DjGwL ;d:of eP pNn]v ug]{ t/ ;fdfGo ?kdf ePsf] ;'Ts]/LnfO{ pNn]v gug]{_ olb dflysf] k|Zgsf] pQ/ lyPg cyjf yfxf 5}g cfof] eg] Ddf hfg'xf]; . tkfO{+sf] 3/df clGtd k6s lj/fdL x'g'ePsf] JolQm slt lbg klxn] 15. pQ/: lj/fdL x'g'ePsf] lyof] < -lyof] eg] slt lbg cufl8_ 16. 1-[),#)]; 2-[#!,^)]; 3-[^!,()]; 9-yfxf 5}g÷pQ/ cfPg tkfO{+sf kl/jf/sf ;b:ox?dWo ;a}eGbf kl5 lj/fdL ePsf] JolQmsf] jf/]df pQ/ lbg'xf];: lnË 17. 0-k'?if; 1-dlxnf; 9-pQ/ cfPg pd]/ -lj/fdL ePsf] j]nfsf] pd]/ jif{df pNn]v ug'{xf];_ 18. pQ/: 19. 1-[),$]; 2-[%,!$]; 3-[!%,$(]; 4-≥%) jif{ 9-yfxf 5}g÷pQ/ cfPg pkrf/ ug'{kg]{ sf/0f 20. 1-lj/fdL eP/; 2-rf]6k6s nfu]/; 3- ue{jtL ;DjGwL ;d:of eP/; 4- ;'Ts]/L ;DjGwL ;d:of eP/; 5-cGo; 9- yfxf 5}g÷pQ/ cfPg 21. cGo -pNn]v ug]{_: tkfO{+sf] kl/jf/n] :jf:Yo ;DjGwL ;d:ofnfO{ ulDe/ ?kdf lnPsf] lyof] 22. 0-lyPg; 1-lyof;] 9-yfxf 5}g÷pQ/ cfPg < jxfF lj/fdL x'Fbf ;/sf/L :jf:Yo ;+:yfdf hfg'eof] < 23. 0-hfg'ePg; 1-hfg'eof]; 9-yfxf 5}g÷pQ/ cfPg olb dflysf] k|Zgsf] pQ/ hfg'ePg cyjf yfxf 5}g cfof] eg] Adf hfg'xf]; . tkfO{+sf] dfG5] lj/fdL x'Fbf pkrf/sf] nflu ;a}eGbf 24. pQ/: klxnf s'g ;/sf/L :jf:Yo ;+:yfdf hfg'ePsf] lyof] 25. 1-pk :jf:Yo rf}sL; 2-:jf:Yo rf}sL; 3-k|fylds :jf:Yo < s]Gb|; 4-If]qLo c:ktfn -;'v]{t_; 5-e]/L c~rn c:ktfn - g]kfnu+h_; 6-cGo; 7-lhNnf c:ktfn -vnª\uf_; 9-yfxf 5}g÷pQ/ cfPg 26. cGo -pNn]v ug]{_:

International Rescue Committee Page 30 of 38 olb k|Zg g=+@$ / !! sf] pQ/ Pp6} 5}g eg ] : 27. 1-:jf:Yo ;+:yfdf kof{Kt cf}ifwL geP/; 2-:jf:Yo ;+:yfdf lj/fdL lsg klxnf sd{rf/L geP/; 3-:jf:YosdL{n] lj/fdLsf] pkrf/ glhssf] ;/sf/L :jf:Yo ;+:yfdf hfg'ePg < ug{ c:jLsf/ ug]{ eP/; 4-:jf:YosdL{n] /fd|f] Jojxf/ gug]{ eP/; 5-:jf:Yo ;+:yfn] ;]jf lbg] ;do kof{Kt gePsf]n]; 6-:jf:Yo ;+:yf jGb ePsf]n]; 7-pkrf/sf] nflu :jf:Yo ;+:yfdf hfFbf w]/} ;do kv{g kg]{ ePsf]n]; 8- cGo; 9-yfxf 5}g÷pQ/ cfPg 28. cGo -pNn]v ug]{_: lj/fdLn] ToxL+ pkrf/ kfpg'eof] ls c? 29. 0-kfpg'ePg; 1-kfpg'eof]; 9-yfxf 5}g÷pQ/ cfPg s'g} ;/sf/L :jf:Yo ;+:yfdf hfg'eof] < olb dflysf] k|Zgsf] pQ/ hfg'ePg cyjf yfxf 5}g cfof] eg] Bdf hfg'xf]; . pkrf/ u/fpFbf hDdf slt ?k}ofF vr{ eof] -?k}ofFdf_ < -btf{, 30. pQ/: hfFr, cf}ifwL, oftfoft / cGo_ 31. 1-?k}ofF nfu]g; 2-[!,%)]; 3-[%!,!))]; 4- [!)!,%))]; 5->%)); 9-yfxf 5}g÷pQ/ cfPg olb dflysf] k|Zgsf] pQ/ ?k}ofF nfu]g cfof] eg] Cdf hfg'xf];\ . tkfO{+n] pkrf/ vr{ sxfFaf6 h'6fpg'eof] < -Ps eGbf a9L 32. 1-cfkm} ;+u ePsf] ?k}ofF; 2-;fk6L lnP/; 3-hUuf pQ/ cfPdf ;a} pNn]v ug'{xf];_ hldg jf j:t'efp a]r]/; 5-cGo; 9-yfxf 5}g÷pQ/ cfPg 33. cGo -pNn]v ug]{_: Cdf hfg'xf]; . A tkfO{+sf] dfG5] lj/fdL x'Fbf ;/sf/L :jf:Yo ;+:yfdf 34. 1-pkrf/sf] nflu ?k}ofF{ geP/; 2-oftfoft vr{ geP/; 3-w]/} pkrf/ u/fpg lsg hfg'ePg < -Ps eGbf a9L 6f9f eP/; 4-:jf:Yo ;+:yfdf kof{Kt cf}ifwL geP/; 5- pQ/ cfPdf ;a} pNn]v ug'{xf];_ :jf:Yo ;+:yfdf sd{rf/L geP/; 6-:jf:YosdL{n] lj/fdLsf] pkrf/ ug{ c:jLsf/ ug]{ eP/; 7-:jf:YosdL{n] /fd|f] Jojxf/ gug]{ eP/; 8-:jf:Yo ;+:yfn] ;]jf lbg] ;do kof{Kt gePsf]n]; 9-:jf:Yo ;+:yf jGb ePsf]n]; 10-pkrf/sf] nflu :jf:Yo ;+:yfdf hfFbf w]/} ;do kv{g kg]{ ePsf]n]; 11- pkrf/ ug'kg]{ u/L l;ls:t lj/fdL gePsf]n]; 12-cGo; 19- yfxf 5}g÷pQ/ cfPg 35. cGo -pNn]v ug]{_: lj/fdL pkrf/ vf]Hg st} hfg'eof] < 36. 0-hfg'ePg; 1-hfg'eof]; 9-yfxf 5}g÷pQ/ cfPg olb dflysf] k|Zgsf] pQ/ hfg'ePg cyjf yfxf 5}g cfof] eg] Cdf hfg'xf];\ . la/fdL pkrf/ vf]Hg hfg'eof] eg] ;a} eGbf 37. 1-pkrf/ kfOPg; 2-lglh cf}iflw k;n; 3-wfdL–emfFqmL; 4- klxnf sxFfaf6 pkrf/ kfpg'eof] < cGo; 9-yfxf 5}g÷pQ/ cfPg 38. cGo -pNn]v ug]{_: Cdf hfg'xf]; . B lj/fdLn] ;/sf/L :jf:Yo ;+:yfaf6 lsg pkrf/ 39. 1-pkrf/sf] nflu ?k}ofF{ geP/; 2-:jf:Yo ;+:yfdf kfpg'ePg < -Ps eGbf a9L pQ/ cfPdf ;a} pNn]v kof{Kt cf}ifwL geP/; 3-:jf:Yo ;+:yfdf sd{rf/L ug'{xf];_ geP/; 4-:jf:YosdL{n] lj/fdLsf] pkrf/ ug{ gdfg]sf]n]; 5-:jf:Yo ;+:yf aGb ePsf]n]; 6- pkrf/sf] nflu :jf:Yo ;+:yfdf hfFbf w]/} ;do kv{g'kg]{ ePsf]n]; 7-cGo; 9-yfxf 5}g÷pQ/ cfPg 40. cGo -pNn]v ug]{_: C lj/fdLn] dlxnf :jf:Yo :j+od ;]jsaf6 pkrf/ 41. 0-kfpg'ePg; 1-kfpg'eof]; 9-yfxf 5}g÷pQ/ cfPg kfpg'eof] < lj/fdLn] lgoldt ;~rfng x'g] ufFp 3/ lSnlgsaf6 42. 0-kfpg'ePg; 1-kfpg'eof]; 9-yfxf 5}g÷pQ/ cfPg pkrf/ kfpg'eof] <

International Rescue Committee Page 31 of 38 lj/fdLn] cfO=cf/=l;=/ cGt/ lge{/ ;dfhaf6 ;~rflnt 43. 0-kfpg'ePg; 1-kfpg'eof]; 9-yfxf 5}g÷pQ/ cfPg 3'lDt lSnlgsaf6 pkrf/ kfpg'eof] < tkfO{+x?sf] cfkm\gf] hUuf 5 < 44. 0-5}g; 1-5; 9-yfxf 5}g÷pQ/ cfPg olb 5 eg] : 45. pQ/: clxn] tkfO{+x?;+u ePsf] hlt hUuf ToxL+ lsGg' k/\of] eg] 46. 1-[), $$,(((]; 2-[$%,))) , &$,(((]; 3- slt ?k}ofF nfU5 < [&%,))) , !,$(,(((]; 4-≥!,%),))) ; 9-yfxf 5}g÷pQ/ cfPg tkfO{+x?sf] cfkm\g} j:t'efpm 5g\ < -e}+;L, ufO{, uf]?, 47. 0-5}gg; 1-5g; 9-yfxf 5}g÷pQ/ cfPg jfv|f, ;'+u'/, s'v'/f_ olb 5g eg ] : 48. pQ/: clxn] tkfO{+x?;+u ePsf] hlt j:t'efpm lsGg' k/\of] k/\of] 49. 1-[), &,(((]; 2-[*,))) , !$,(((]; 3-[!%,))) , eg] slt ?k}ofF nfUb5 < @$,(((]; 4-≥@%,))); 9-yfxf 5}g÷pQ/ cfPg D: xfdLn] tkfO{+nfO{ ;f]Wg'kg]{ k|Zgx? olQ g} x'g\ . xfdLnfO{ ;do lbO{ ;xof]u ug'{PePsf]df w]/} w]/} wGojfb . gd:sf/ . [;dfKt]

International Rescue Committee Page 32 of 38 Annex 2: Informed consent form (English, Nepali)

Consent form for health access survey in Jajarkot (revised 27 July 2008)

Introduction The International Rescue Committee-Nepal and the Interdependent Society are conducting a project in 10 VDCs of Jajarkot in collaboration with the District Health Office to improve access to quality health care in Jajarkot. We want to measure access at the beginning of the project to allow us to better plan project activities during the next year. Purposes • We would like to find out how many people were able to obtain health care when they needed it. • For people who could not obtain health care, we would like to find out why not. Procedure We will ask you some questions about your household, who has been sick recently, and where health care was obtained, if any. The entire interview should take no more than 15 minutes of your time. You do not have to answer any questions you do not want to. Benefits The results of the survey will allow us to plan better health care support in Jajarkot. You will not receive any money for answering our questions. Risks There will be the inconvenience of answering our questions, but no physical or emotional risks to the study. You may skip any question, including ones that make you uncomfortable. Being in the study is voluntary It is up to you whether to be in the study. You may refuse to be interviewed without penalty. Confidentiality Your name will be kept secret as far as we can do so. The study information will not be given to anyone except the health workers doing our study. Questions If you have questions about the study, call Anand Mohan Rai or Tula Ram Sijali, IRC-Nepal, Khalanga, Jajarkot.

VDC name ______Ward number ______Household number ______

Name of respondent (print) ______

I have read this consent form or someone has explained it to me. I freely agree to be in the survey.

______Signature or fingerprint of subject Person obtaining consent

______Date ______/______/______Witness

International Rescue Committee Page 33 of 38

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International Rescue Committee Page 34 of 38 Annex 3: Statistical tables Tables A-1, A-2, and A-3 break down access according to various variables such as caste and land value that might be hypothesized to affect access. For instance, it might be expected that poor people may have less access to health care than rich people. Table A-1 shows the access percentage for each category. If all the percentages are the same, then that particular factor is probably not associated with access. If the percentages are different, then it is necessary to assess the magnitude of the difference and how statistically significant that difference is.

The measure of difference used here is the odds ratio (OR), which is always given relative to a reference group that must be specified. In the table, the reference group for each factor is indicated by an asterisk (*). For example, the last factor in Table A-1 is a dichotomous coding of the variable for distance into two categories: greater than 1 hour away and one hour or less. The more distant category (>1 hour) is taken as the reference group. The access within that category is 20% (82 out of 403 distant households had access), while access within the nearby category is 38% (135 out of 353 nearby households had access). Since 38% is greater than 20%, it appears that nearby households had better access than distant households.

The odds ratio quantifies that observation and can be (loosely) interpreted as meaning that nearby people are 2.42 (the OR) times as likely as distant people to have access to government health care. The question is whether that difference between the distance groups is statistically significant or not, which is what the final column (p-value) measures. The p- value is (again, loosely) the probability that an OR of that magnitude could be obtained by chance. Just as 95% confidence intervals are standard, a p-value of 0.05 or less is taken as a standard for concluding that the OR is statistically different from the null (OR=1); in other words, a p-value of 0.05 would mean that there is only a 5% probability that the OR could have been obtained by chance. In the example of distance, the p-value is less than 0.0005, indicating that it is extremely unlikely that the association is due only to chance. Since the p- value is less than 0.05, it can be concluded that there is an association between distance and access. In general, if p is less than 0.05, it can be concluded that there is an association, and the smaller the p-value the stronger the odds that the finding is not due to chance.

Table A-1: Factors associated with whether patients went to government facility and received care Factors Total Yes Percent OR p-value Caste Brahmin/ Chhetri* 510 139 27% Janjati 19 7 37% 0.96 0.471 Dalit 233 72 31% 1.19 0.529 Other 0 0 Caste (dichotomous) Brahmin/ Chhetri* 510 139 27% Dalit/Janjati 252 79 31% 1.22 0.446 Land value Rs 0-75,000* 296 90 30% Rs >=75,000 288 85 30% 0.96 0.856 Livestock value Rs 0-15,000* 143 47 33% Rs >=15,000 484 129 27% 0.74 0.096 Sex of patient Male* 312 91 29% Female 450 127 28% 0.95 0.808 Considered serious Not serious* 16 4 25% Serious 745 214 29% 1.21 0.789 International Rescue Committee Page 35 of 38 Factors Total Yes Percent OR p-value Household size >=6* 487 128 26% 0-5 275 90 33% 1.36 0.055 Age of patient 0-4* 147 41 28% 5-14 97 32 33% 1.27 0.474 15-49 360 99 28% 0.98 0.938 >=50 147 43 29% 1.07 0.854 Distance <=1 hour* 353 135 38% 1-2 hours 187 53 28% 0.64 0.054 2-4 hours 184 25 14% 0.25 <0.0005 >4 hours 32 4 13% 0.23 0.002 Distance (dichotomous) >1 hour* 403 82 20% <=1 hour 353 135 38% 2.42 <0.0005 *Reference group

Table A-2: Factors associated with whether patients went to government facility Factors Total Yes Percent OR p-value Caste Brahmin/ Chhetri* 510 208 41% Janjati 19 10 53% 1.61 0.438 Dalit 234 105 45% 1.18 0.515 Other 0 0 Caste (dichotomous) Brahmin/ Chhetri* 510 208 41% Dalit/Janjati 253 115 45% 1.21 0.429 Land value Rs 0-75,000* 296 131 44% Rs >=75,000 288 127 44% 0.99 0.98 Livestock value Rs 0-15,000* 144 75 52% Rs >=15,000 484 194 40% 0.62 0.014 Sex of patient Male* 312 135 43% Female 451 188 42% 0.94 0.697 Considered serious Not serious* 16 5 31% Serious 746 318 43% 1.63 0.305 Household size >=6* 487 205 42% 0-5 276 118 43% 1.03 0.869 Age of patient 0-4* 147 63 43% 5-14 97 47 48% 0.77 0.461 15-49 360 149 41% 1.06 0.754 >=50 147 60 41% 1.34 0.774 Distance <=1 hour* 354 202 57% 1-2 hours 187 66 35% 0.41 <0.0005 2-4 hours 184 47 26% 0.26 0.001 >4 hours 32 7 22% 0.21 0.001

International Rescue Committee Page 36 of 38 Factors Total Yes Percent OR p-value Distance (dichotomous) >1 hour* 403 120 30% <=1 hour 354 202 57% 3.13 <0.0005 *Reference group

Table A-3: Factors associated with patients received care if went to a government facility, Factors Total Yes Percent OR p-value Caste Brahmin/ Chhetri* 208 139 67% Janjati 10 7 70% 1.16 0.795 Dalit 105 72 69% 1.12 0.723 Other 0 0 Caste (dichotomous) Brahmin/ Chhetri* 208 139 67% Dalit/Janjati 115 79 69% 1.12 0.686 Land value Rs 0-75,000* 131 90 69% Rs >=75,000 127 85 67% 0.922 0.757 Livestock value Rs 0-15,000* 75 47 63% Rs >=15,000 194 129 66% 1.14 0.624 Sex of patient Male* 135 91 67% Female 188 127 68% 1.023 0.928 Considered serious Not serious* 5 4 80% Serious 318 214 67% 0.519 0.593 Household size >=6* 205 128 62% 0-5 118 90 76% 2.005 0.011 Age of patient 0-4* 63 41 65% 5-14 47 32 68% 1.145 0.749 15-49 149 99 66% 1.062 0.868 >=50 60 43 72% 1.357 0.431 Distance <=1 hour* 202 135 67% 1-2 hours 66 53 80% 1.993 0.046 2-4 hours 47 25 53% 0.556 0.081 >4 hours 7 4 57% 0.652 0.367 Distance (dichotomous) >1 hour* 120 82 68% <=1 hour 202 135 67% 0.948 0.864 *Reference group

International Rescue Committee Page 37 of 38 Annex 4: List of 30 selected wards (clusters) VDC Ward(s) Total HHs Archhani 3 40 Archhani 5 30 Archhani 6 28 Archhani 9 54 Bhagwati 4 50 Bhagwati 9 65 Daha 7 66 Daha 8 61 Daha 9 64 Kortang 3 77 Majkot 5 85 Majkot 6 189 Nayakbada 2 174 Nayakbada 3 66 Nayakbada 6 66 Nayakbada 8 116 Paink 1 100 Paink 5 99 Ragda 1 51 Ragda 3 65 Ragda 4 92 Ragda 8 57 Ragda 9 48 Salma 3 87 Salma 5 121 Salma 6 89 Salma 7 106 Salma 9 76 Talegaun 5 53 Talegaun 7 54 Total 30 2,329

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